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How to complete coursework.

In The Sims 4: Discover University , your Sim will need to pass their classes in order to graduate with their chosen Degree, which includes completing Coursework like written papers and taking exams.

This guide teaches you everything you need to know about How to Complete Coursework in TS4, including writing and submitting papers, taking exams, and creating a presentation.

Click on any of the links below to automatically scroll to that section of this guide:

What is Coursework in The Sims 4?

How to write a term paper, how to take final exam, how to give a presentation.

In the Discover University Expansion Pack, student Sims who have enrolled in a degree will have to attend classes to pass the semester (which lasts a week). Showing up isn't enough, though—it also includes Coursework.

Because university life is so hectic, you will need to make sure your Sim balances work and study because if they're too busy with a job to go to class and complete their Coursework, they won't be able to graduate.

To learn more about Degrees, including types and what careers your Sim can go into after graduating, check out our Degrees guide .

There are three types of Coursework:

• Written Term Paper
• Presentation

You can view each class your Sim is signed up for and what Coursework they'll need to complete that semester by clicking on the Career tab on your hotbar (or simply press J).

To write a Term Paper, your Sim will need access to a PC. Click on the PC, then "University" > "University Coursework" > "Term Paper." Here, you'll see two options: "Write Term Paper" and "Submit Plagiarized Term Paper."

If you want your Sim to get a good grade, don't cheat as it's impossible to get an A with a fake paper. Instead, choose for them to write it themselves.

After a few hours, your Sim will have produced their first draft. You can choose to hand this in but for a better grade, go back to the PC and click on "Edit Term Paper". Do this multiple times until you get a notification popup that says it is the best it can be. Now you can "Submit Term Paper" from the computer.

In Discover University , doing the Final Exam is easy: your Sim just goes to class on one of the final days of the semester and takes it automatically. But this doesn't mean there isn't work to do, though. If you want your Sim to get a high grade, they need to study.

Click on a PC, then "University" > "University Coursework" > "Study" and then choose the class the Final Exam is for. For a good grade, it's ideal that they study at least twice—the more, the better. They may also need to study for more than one class if multiple have a Final Exam as Coursework so make sure they have enough time to fit it all in!

It is also a good idea to raise the Skill that the class is tied to; again, the higher the better. You can check this in the Career tab in your hotbar.

This is the most confusing piece of Coursework your Sim is given as the game does not mention what you need to do, leaving you to figure it out for yourself. Upon starting the semester, a Presentation Board will be put in your Sim's inventory which you must place in the world.

Have your Sim interact with the board and "Compile Information." They will spend an hour or two throwing ideas onto the board. You can submit it like this, but if you want a higher grade, you will need to "Refine and Organize" until a popup appears notifying you it's the best it can be.

If you "Practice Presenting," your Sim's Charisma Skill will increase—something that you should ideally make them do a couple of times as it can help with the grade. Once this is done, your Sim will now be ready to hand their Presentation in.

Presentations can only be handed in during school hours: from Monday to Friday between 8AM and 4PM. Your Sim will be in class for a couple of hours while they present.

Homework is separate from Coursework but is just as important. It is a daily task, meaning you'll have to do it for each of your Sim's classes every day. It takes a couple of hours to complete it for each class.

To do Homework, go to your Sim's inventory and you'll see a black and white class book. You can either click it from the inventory itself or place it in the world and then click it, but when you do, homework options for each of your Sim's classes will pop up.

Your Sim will go and sit down somewhere to finish their homework, and their progress can be tracked in the Action Queue on the bottom left. The more homework your Sim does, the better their grade will be for that class at the end of the semester.

Now that you know all about How to Complete Coursework in The Sims 4, head on over to our Organizations page to learn all about the student societies your Sim can join.

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The Sims 4 Discover University: Guide to Academic Success

Presented by EA Game Changers

Getting into university is one thing; excelling in university is quite another. For most people, the joys of university lie in balancing work with pleasure. A little studying here, a little partying there, leading to an overall well-rounded university experience.

This guide is not for the casual university student. This guide will walk you through how to throw yourself completely into your education in order to achieve the best grades (and the best future) possible. Throw away your juice kegs and break out those textbooks because school is all you’re going to know for the next three terms.

For a breakdown on scholarships and applying to university, see our guide, Discover University: Applying to University !

Class Selections

Of course, it all starts with enrolling and selecting your degree and classes. No matter which degree you pursue, you’ll have to select up to 4 classes per term. Classes change every term so you’ll see new ones available every time you select your classes at the start of term. You can’t change which classes you’ll be taking for your degree; you can only choose the number of classes.

However, Sims have the option of enrolling in 1 elective each term. Electives are fun classes that focus on skills outside of your degree and you will be able to select which elective your Sim will take that term. There are all kinds of electives that span a wide variety of skills. Electives are fully integrated across all packs, so depending on which add-on content you have installed, you may see different electives for skills from different packs.

Electives are optional; your Sim doesn’t need to take any electives at all, but if they do choose to take an elective, they can only take up to 3 other classes. Sims are limited to 4 classes per term in total, so either 4 classes, or 3 classes and 1 elective.

Our recommendation? Take 3 classes and 1 elective every term for maximum academic success. Electives still count as credits towards your degree so taking an elective doesn’t hurt your progress at all, plus your Sim will graduate with a few extra skills thanks to the electives they took.

One term last 5 working days. There is no way to shorten or lengthen a term. They are fixed periods. Sims can begin a new term anytime during the week, but weekends don’t count as term days. If your Sim starts a new term on a Friday, the term won’t end until Thursday the following week. Starting a new term in the middle of the week can be a good academic strategy for dedicated students because it will give them the weekend to catch up on homework and final assignments.

How many terms your Sim needs to complete in order to graduate is entirely dependent on how many classes they decide to take per term. A Sim needs to earn 12 credits in order to graduate.

Here is the breakdown of how many terms your Sim will need to complete based upon their classes:

• 4 classes per term = 3 terms (15 working days)
• 3 classes per term = 4 terms (20 working days)
• 2 classes per term = 6 terms (30 working days)
• 1 class per term = 12 terms (60 working days)

These calculations are based on the assumption that your Sim completes the same number of classes every term. It is possible to take a different number of classes each term (4 classes one term, 2 the next term, for example), in which case the number of terms needed to graduate will vary.

Even if a Sim only takes 3 terms to graduate, they will still spend the majority of their young adult life in university; however, unlike past Sims games, your Sims are not trapped on campus with no way to work or live a life outside of university. Sims can live wherever they want, have a job, and raise a family while going to school, so this balances things out. If the length of university is not ideal for your play style, we recommend turning aging off in the game options while your Sim is in university. That way, they don’t lose any time to climb a career ladder or pursue other life goals.

Of course, you will want to be taking 4 classes every term for maximum efficiency. Sims who don’t mind sacrificing their social life and plan to devote all their time to their studies should take a full course load every term.

Attending Classes

It’s important to actually attend class in order to get the most out of your university education. Missing class will hurt your grades. Sims in the area will autonomously try to get to class a little early. Sims who’ve arrived to class early will wait outside the building with the other early bird students. This can be a good time to get some last minute homework finished or to quickly finish the rest of that coffee and snack you purchased to-go at the cafe vendor.

While your Sim is inside the classroom rabbithole, they will have various options available to them by clicking on their portrait, much like the different work options for inactive careers. Click the class icon on the Sim’s portrait to see the various actions they can take in class. Sims can Actively Listen, Take Notes, Sleep in Class, or Chat with Friends. To get the most out of every class, make sure your Sim is taking notes or actively listening. I’m sure we don’t need to tell you that sleeping in class and chatting with friends are not good ways to improve your grades.

If you’re taking a full course load, it’s likely that your Sim will have more than one class in a day, or even back to back classes. Make sure to check the career panel often to keep track of your class schedule so you can budget your time for homework, finals, and self-care effectively.

Ideally, you will want your Sim to attend every single class with all of their homework completed and taking an active role in the class while they are there. This will ensure your Sim gets the most out of their classes and, in turn, gets the best grades at the end of term.

Every course your Sim takes has homework due before every class. When your Sim enrolls in university, they are automatically given a homework notebook in their personal inventory. Sims can complete homework for all their classes using this notebook. Homework takes some time to complete, but Sims with high enough Research & Debate skill complete homework faster.

Sims who stay on top of their homework and pay attention in class will get more out of attending classes and it will have a positive impact on their final grade. Always complete homework before every class and actively pay attention in class for maximum academic success.

In addition to homework that must be completed on a regular basis throughout the term, each class also has a final. Finals are very important and worth a large chunk of your grade. Skipping out on your finals will have a big negative impact on your final grade, so make sure you complete all of them.

Each class will have different requirements for its final. Some classes will require your Sim to write a term paper. Others have final exams and presentations. Look at your class schedule in the career panel to see what’s required of each class.

Exams take place during the last class of the term. If your Sim has done all their homework and attended all their classes, they’re likely to do well on their exam, but Sims can also study for a class using a course book purchased from the university kiosk, a computer, or research station to boost their chances of doing well on their exam.

Don’t miss your final exam! Failing to write the exam results in a big fat zero and will seriously hurt your final grade!

PSST! You can also cheat on your exam by selecting the option on your Sim’s portrait while they’re in the exam… but you would never do that… would you? Getting caught has serious consequences.

Term Papers

Term papers can be written on the computer under the University menu option. A Sim can write and submit a term paper for a class at any point during the term, so dedicated Sims might want to get these out of the way early.

Term papers take a long time to complete, but Sims with high enough Research & Debate skill complete term papers faster. The first draft of a term paper is usually poor quality. Your Sim can submit poor quality term papers, but f they want the best grade, they should spend some time editing their paper before they submit it.

Term papers can be edited until they are outstanding quality. You’ll receive a notification telling you that your term paper won’t benefit from any further editing once your Sim has increased its quality to outstanding. Scrolling over the term paper option in the computer’s menu will tell you the quality of the term paper.

When your Sim is satisfied with the quality of their paper, they can submit it using the computer.

PSST! You can also plagiarize your term papers by selecting the plagiarize option on the computer… but you would never do that… would you? Getting caught has serious consequences.

Presentations

Your Sim will receive a presentation board in their personal inventory at the start of term for any classes that have a presentation requirement as their final. Presentations function similar to term papers; your Sim will need to compile all of their material on the board, then refine the presentation board until it’s suitable to present in class.

To start, drag the presentation board out of your Sim’s inventory and into the world somewhere, then choose the Capture Information option on the board. Your Sim will spend some time compiling all their material for their presentation onto the board. When they’ve finished, they will have a poor quality presentation board. You can see the board’s quality by hovering over it.

Sims can improve the quality of their presentation by refining and organizing it, and asking other Sims for feedback on their presentation. They can also practice their presentation. Practicing presentations builds the Charisma skill. Once the board cannot be improved any further, you will receive a notification informing you that your Sim’s presentation board looks great and that continuing to fiddle with it won’t improve it any more.

When your Sim is satisfied with the quality of their presentation, they can go to class with the presentation board in their inventory and present it. Presentations do not take place during regular classes; your Sim must click on the class rabbithole and select the presentation option. Presentations can only be given during the day. Your Sim won’t be able to present in the middle of the night.

Final Grades & Starting a New Term

If your Sim has done all their homework, attended every class as an active participant, and completed all their finals with outstanding quality, they should have no trouble getting an A+ grade in every class. However, perfect grades don’t come easy. You’ll find that your Sim has little to no time for extracurricular activities, organizations, or socialising when they are taking 4 classes and trying to achieve an A+ grade in every single one of them. University is definitely a rewarding challenge in The Sims 4 , just like in the real world.

Since grades aren’t given out until the end of term, it’s up to your Sim to take a proactive approach to finding out how they’re doing in their classes. They can visit their professors during their office hours or email them on the computer to get an idea of how they’re performing in their classes and how they can improve.

Once all coursework has been submitted, your Sim will be free to enjoy themselves (for once) while their final grades are being processed. Once the final grades are in, you’ll receive a popup with all your final grades for each class, as well as your overall GPA.

From there, you can choose to enroll in another term right away, or take some time off before starting a new term. If your Sim has any scholarships, they must enroll in a new term immediately or they will lose their scholarships. Tuition costs for the new term will be handled at this point as well. Sims can pay with household funds or take out a loan to pay any tuition costs for the new term that scholarships don’t cover.

Your Sim will also be given the opportunity to make different housing arrangements at the start of each new term. They can choose to stay wherever they are currently living, or move somewhere else. This change does not happen right away. Your Sim will have about a day left in their old residence, which gives them an opportunity to pack up any personal items they may have purchased for their living space. A small “Packing Up” event will occur a couple hours before the move to remind your Sim to gather up their things, too.

As long as your Sim continues on the path to success they started in their first term, all their future terms are bound to result in perfect A+ grades across the board. Keep doing that homework, working on those finals, and paying attention in class!

Have any tips of your own for academic success? Share them with us in the comments or come chat with us on social media!

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The Sims 4: How To Write and Publish A Research Paper

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When an expansion pack is released for The Sims 4 , it's not unusual for it to add a new skill to the game. At this point, given the amount of DLC available for The Sims 4 , there are all kinds of skills that Sims can learn; there are even a few that are so niche that many wouldn't expect to see.

RELATED: The Sims 4: Discover University Complete Guide

The Research & Debate skill was added to The Sims 4 with the release of the Discover University expansion pack. This is a skill that's all about using and spreading knowledge through dialogue. This guide will show players how they can take advantage of the Research & Debate skill to write and publish their own research papers in The Sims 4 .

How to Write and Publish a Research Paper

Being able to convince roommates to clean up the house or telling other Sims to go streaking aren't the only useful things gamers can do with the Research & Debate skill. With a high enough Research & Debate skill, players can take advantage of their knowledge and write and publish research papers.

In order to be able to write research papers, a Sim needs to reach Research & Debate skill level eight . If the Sim hasn't learned this skill yet, this can definitely take some time. Sims can increase their Research & Debate level by visiting the university commons and using the Research Archive Machine or the podium. Alternatively, this can also be done at home - the Sim needs to interact with the mirror to practice debate.

Once a Sim has gotten to Research & Debate skill level eight, the Write and Publish Research Paper option will become available on any computer . It is not possible to use this interaction on the Research Archive Machine.

Unlike books, as soon as the Sim finished writing the research paper, it will be automatically published, and they will receive a single payment for it .

Research Paper Earnings

The amount of money a Sim can earn by writing and publishing a research paper is random. They can write a research paper on any skill, and even if they write about a skill they've maxed, the paper could still fail among the academy community. Regardless, Sims only take about three hours to write and publish a research paper and they get a much better payment for it than they would for a day of work at most in-game jobs .

MORE: The Sims 4: The Best Career For Your Sim (Based On The University They Attended)

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The Sims 4: Academic Aspiration Guide

We have been graced with a new aspiration that came with The Sims 4: Discover University, the academic aspiration .

This aspiration isn’t the most fun , and has continued along the pattern of aspirations that guide you through a pack like we got with Island Living , Realm of Magic, and Strangerville.

The academic aspiration is focused on your sim getting good grades in school, attending guest lectures, and even tutoring students (a nice new way to make money).

Most simmers aren’t going to use this aspiration often, and this aspiration isn’t a necessity for every student going to University, but the reward trait is nice to have!

Watch The Video

Stages of the Academic Aspiration

• Achieve Level 3 Research & Debate
• Enroll in a University

The Research & Debate skill is one of two new skills added with Discover University. You can gain this skill by doing any coursework (i.e., homework, studying, term papers, etc) or by researching topics on a research machine that can be found in the commons or at a library.

The second part is easy, and pretty self-explanatory. You can check out this article on applying and enrolling in Uni!

Bright-Eyed Student

• Achieve Level 5 Research & Debate
• Attend Guest Lectures (0/3)
• Finish a Course with an A

To achieve level 5 of the Research & Debate skill, you need to continue working on school work and doing research at the research machines. This skill will naturally go up rather quick throughout your studies.

You can attend guest lectures by clicking on one of the buildings on campus that aren’t housing and choosing attend guest lecture . These lectures only happen between 5 pm and 7 pm, so plan accordingly.

Getting an A in University is actually quite hard, be sure to do your homework, finish your coursework, and study often. You can learn more about getting an A here!

Avid Academic

• Have a Term GPA of B or Higher
• Tutor Students (0/5)
• Achieve Level 6 Research & Debate

To get a term GPA of a B or higher, you’ll need to do decently in all of your classes that semester, as a GPA is the average of the classes you’ve taken. Try to study often and stay on top of your homework to get a B GPA.

Next, you’ll need to tutor students. There’s a building on campus where you can click and tutor students in any subject where you have a high skill. This can be done at any time of the day, and also will get you a bit of income which is a great way to make money in school.

Senior Scholar

• Earn a Degree
• Contribute Knowledge on Research Archive Machine
• Achieve Level 7 Research & Debate
• Get a Job Using Degree

To finish off this aspiration, you’re going to need to earn your degree and complete all 12 credits that are necessary to graduate. then, when you graduate, you’ll need to get a job that fits in with your sim’s degree (i.e., psychology degree and education career).

Finally, you’re going to need to contribute knowledge on the research machines. This is a good way to make a bit of money and share the knowledge you’ve learned throughout school.

Academic Aspiration Reward Trait

“This Sim has proven they have what it takes to excel at University. Along the way, they learned a lot, allowing them to gain more skill using the Electromagnetic Research Archive Machine and earn more money from Publishing Research Papers and Contributing Knowledge.”

When you’re finally able to finish this aspiration, your sim will be awarded with the new higher education reward trait. As the description says, this trait is going to help your sim make way more money when they are doing academic tasks like writing papers and contributing knowledge.

You can make really great money from these tasks after you graduate, this could be a great side hustle for your sim, so having this higher education reward trait is really helpful to get the most out of it.

To contribute knowledge, you can click on a research machine and contribute any knowledge of a skill where you have a high skill. To write a research paper, you’ll need a computer but you can research scholarly papers using the research machine.

Final Thoughts

The academic aspiration is pretty basic, but it can help you through the University pack if you’ve never played before. Part of me wishes we would’ve gotten something a bit sillier, or even a slacker version of this same aspiration. What are your feelings? Let me know in the comments!

I've been playing the Sims since the first game was released when I was only 5 years old. It's been a huge passion of mine for two decades and I've loved every single minute of it. I also love dogs. And grilled cheese sandwiches. And I think me and Bob Pancakes could be friends.

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“There’s a building on campus where you can click and tutor students in any subject where you have a high skill. ” Which building would that be ? Thanks

Nevemind. It’s one of the class buildings. I couldn’t see the tutor interaction because my sim was still a teen, and teens cannot tutor. (I’m using a mod to play a teen at university)

Class building or building left side arena e-sports Tutor -> select any skill

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The Sims 4 Research and Debate Skill

Gettin' educated and convincing others in discover university.

The Research and Debate Skill in The Sims 4 Discover University

The Research and Debate Skill is very interesting to me. It's essentially a skill that teaches Sims to learn and to be more persuasive in convincing others. You'll get a bunch of different passive boosts by leveling this skill, a few unique abilities, and can get other Sims to shower, cook meals, or clean up the house - perfect for managing Roommates in The Sims 4 Discover University.

Leveling Research and Debate

There are a few ways to level Research and Debate - the cheapest is perhaps using a mirror to Practice Debate. See, here's the thing - the Electromagnetic Research Archive Machine... It's $12,000. So yeah, most Sims won't afford it without cheating in some money. You can get Podiums on the cheap in buy mode under Miscellaneous Activities and Skills - there is also a double podium setup you can use for debates. Of course, you could just travel to one of the University's students buildings where you can use the Archive free of charge. Just not from the comfort of home.

You can level up Research and Debate using the machine above, or just practice at a mirror! Put on your convincing face.

The ideal mood for Research and Debate is, of course, Focused. You'll gain +20% faster skill XP by being focused, 40% for very focused. Stack on a couple lot trait bonuses, and you'll cram info like a champion.

Research Machine is the New Death

The new death in Discover University is that when contributing knowledge using the Research Machine too much (specifically that high level ability), your Sim will grow exhausted. If you continue to do so beyond that point, they'll give their life to science. It's not a very exciting death but one very much worthy of warning people about.

Research and Debate Skill Unlocks

You get several active and passive abilities by leveling up Research and Debate. These help you complete homework faster, study more effectively, and even finish term papers faster.

• Level 1 - Research & Debate is all about learning information and then utilizing it-whether that be in a debate or through social influence. This skill can be improved and used with the Research Archive Machine to Research varying topics, and the Mirror to Practice Debating
• Level 2 - Your Sim can now finish reading books in less time. They can also Debate a Topic with other Sims at a Podium.
• Level 3 - Your Sim can now complete their homework at an accelerated rate. They can Prepare for Debate at the Electromagnetic Research Archive Machine and Convince other Sims to Bathe or Do a Keg Stand.
• Level 4 - Your Sim can now gain more study progress while studying. They can now research more skills on the Research Archive Machine.
• Level 5 - Your Sim has become more persuasive. They can Convince other Sims to Do his or her homework and cook meals.
• Level 6 - Your Sim can now complete University Presentations and Term Papers in record time. They may also Contribute Knowledge on the Research Archive Machine.
• Level 7 - Your Sim can now use their persuasive powers to Convince other Sims to Clean house. They can also Convince roommates thinking of leaving the house to Stay.
• Level 8 - Your Sim can now Write and Publish Research Papers at a Computer. They will also gain skill faster while reading sklil books.
• Level 9 - Your Sim can now Convince others to Go Streaking. They can also Convince Boss to Give Bonus on the phone.
• Level 10 - Your Sim can now have a Professional Debate with other Sim on a Podium Pair. They can also Give Professional Commentary at a Podium or Podium Pair. These are great ways to earn a few extra Simoleons.

Passive Study and School Work Bonuses

There are several of these unlocked above, so let's discuss just how good they are! It would appear that the level 3 Homework Speed buff is +25%, saving you at least 15-25mins each time your Sim needs to do homework, if not more. This stacks nicely with the Study Spot Lot Trait which can be put on any lot (and also increases skill gains - it's decidedly overpowered).

Study Speed is increased, therefore your Sim will increase their performance in a particular class much faster. This is all hidden to you, but if you miss class or fail to do homework it can be made up this way by spending a few hours studying for said course. You'll make up some of that time when it comes to making Term Papers and Presentations. The latter can be finished 40% faster. Not just the first stage, but all stages. In this way, Research and Debate is one of the best skills for students in Discover University. Who knew a skill around learning could be so useful to someone in Uni?

Convincing Others

"Look this homework's due in 3 hours, and I just don't feel like it. Could you help out a friend?" "Why, of course!" - Convincing others to do things is quite fun, but has a rather long global cooldown. You can't be a pest.

You can only do this every 4 hours (not on a per-Sim basis). You don't need to have met the target Sim in order for it to work, as the Convince To menu is available straight away. Overall, it can be super useful to get other Sims to do your Sim's homework though they won't gain skills. But you have Research and Debate, right, so you can definitely make up for that with a nice skill book.

You can practice debating at podiums, but also have a two-hour+ long debate with other Sims. Winning it gives you a +1 Confident moodlet for 4 hours, which is hardly appropriate given the time sink. Anyway, the main use of the debating wing of this skill is Convince and its use in helping you to rank up in the Debate Guild University Organization mentioned below.

Debate Organization - Britechester Students

The Debate Guild meets weekly, Tuesday from 4PM to 8PM. You can ask a member to join, and will then have a planner in the Organizations menu (Hotkey U, exists with clubs with Get Together).

There is a debate organization in Discover University, but I haven't explored it much just yet. You must be a student of Britechester in order to participate.

Meet someone from the Debate Guild, and you can ask the other Sim to join. Then manage its tasks and schedule on the Organizations panel (chat bubble icon in the bottom right interface). You'll get tasks, and gradually rank up. It's actually worthwhile to pursue this, because I saw there's a very, very expensive reward for reaching the highest rank. Something that's unattainable for a poor student interested in R&D! I won't spoil that for you.

Contributing Knowledge

You can make money with the Research and Debate skill. Probably about $300/hour, assuming you have something of value to contribute!

When your Sim gets higher level, they can use the Research Archive Machine to contribute knowledge on one of several skills, including Research and Debate, Painting, Charisma, Handiness, Logic, and Robotics. Having skill in these in addition to your Research and Debate Skill helps to improve the amounts you make. It takes a couple hours and gives about $600 at max level, maybe a little more.

Convince to Do Homework

While useful for getting another Sim to knock out your homework and freeing up some of your own Sim's time, this ability has a whopping 20 hour cooldown but seems to be per class .

Use the Research Archive to learn about ghosts on campus and, when a member of the Secret Society, learn about that Organization's origins. You can read about their origins in the link below, if you don't mind spoilers.

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Comments (6).

You can also buy a skill book

"Contributing Knowledge" three or so times in a row will make your Sim die of overexertion! I queued up the action a few times and then ended up killing my Sim :(

Yep, it's the new death included in the pack.

hi, anyone experience the skill to convince other to make homework not work well? they take book then put again in inventory, they not refuse. tried without mod. bug or 20 h countdown or other

My research and debate skill is level 10, but I can't seem to make people do what I convince them to do, they keep refusing. Is there some tips for people not to refuse?

This skill just seems really buggy. Try quitting out of your game and deleting the localthumbcache.package file from your TheSims4 folder. And sometimes doing a Game Repair from Origin can really help with glitches etc. However I think this skill is just not expected to work 100% of the time even with the skill maxed, you should be seeing more successes than failures though at Level 10, if your Sim knows the target Sim well.

Well, I don't know if it was taken out or whatever, but there is definitely NO option for my sim to practice debate in the mirror at her home (she's already graduated from University if that makes a difference).

Has anyone managed to earn course credits from participating in the debate guild's functions? The info given says it's possible, but I don't see any evidence of it as yet

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• Nov 15, 2020

Faster Term Paper & Presentation (University)

Updated: Oct 12, 2023

This small mod will help you at the University and will make writing term paper and preparing presentation faster. It’s around 2 times faster than with normal speed.

Expansion to work with: Discover University

(It doesn’t affect homework – faster homework mod was created by Scarlett and is currently updated by LittleMissSam )

This mod overrides following files:

E882D22F!0000001D! 0000000000036464.computer _University_TermPaper_Write_CourseA.InteractionTuning

E882D22F!0000001D! 0000000000036465.computer _University_TermPaper_Write_CourseB.InteractionTuning

E882D22F!0000001D! 0000000000036466.computer _University_TermPaper_Write_CourseC.InteractionTuning

E882D22F!0000001D! 0000000000036467.computer _University_TermPaper_Write_CourseD.InteractionTuning

E882D22F!0000001D!0000000000037233.univeristy_TermPresentation_CaptureInformation.InteractionTuning

E882D22F!0000001D!0000000000037234.univeristy_TermPresentation_RefineAndOrganize.InteractionTuning

Change log:

28/07/2022 - updated for July 26th patch

19/06/2022 - updated for June 14th patch

25/03/2021 - updated for March patch

13/11/2020 - updated for November patch

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How to Give a Presentation in The Sims 4 Discover University

In The Sims 4: Discover University, you’ll find various coursework types that propel your student sim to success in their classes. While some may ask you to prepare term papers, others will ask you to give presentations or take exams. This may sound simple at first, but there is some important information to note before moving further into the school year. If you’re interested in learning more, continue reading to discover how to give a presentation in The Sims 4: Discover University.

Before you can give a presentation, you’ll have to make one! To do this, head into your character’s inventory and look for the presentation board. When you’re ready to begin working on it, place it anywhere in the world and select the board to find “Capture Information”. Click on this to start creating your presentation.

Once you make the presentation and select the board again, you’ll immediately find multiple options:

• Ask for Feedback
• Refine and Organize
• Practice Presenting
• Give Final Presentation
• Put in Inventory

Typically, your presentation will start at a low quality. While you can still present it, your grades will be as high if you refine and organize it. Make sure to do this before giving your presentation if you want to maximize your chances of getting an A grade.

Related: How to Write a Term Paper in The Sims 4 Discover University

When ready, click “ Give Final Presentation ” to head towards the appropriate university building. Your character will bring the presentation board with them and perform over the span of 1-2 hours. Make sure you do this between 8 am-4:30 pm on a weekday, or else you won’t be able to give the presentation.

Once you complete this task, you’ll finish the course’s primary objective. Just make sure to keep an eye on your homework and attend class to maintain high grades.

The Sims 4 is available on PC, Mac, Xbox One, and PlayStation 4 through the official website . If you’d like to learn more about the game, check out How to Drop Out of University and How to Find Lost Homework in The Sims 4 .

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[OPEN] [DU] Option to write Term Paper disappears

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Re: [NEEDS INPUT] [DU] Option to write Term Paper disappears

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Re: Option to write Term Paper disappears

November 2019 - last edited November 2019

November 2019

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• Introduction
• Conclusions
• Article Information

a Inclusion criteria for tau pathology: low/medium or high tau indicated by standardized uptake value ratio >1.10 or positive visual read assessed by 18 F-flortaucipir positron emission tomography (PET) imaging.

b Inclusion criteria for amyloid pathology (≥37 Centiloids) assessed with 18 F-florbetapir or 18 F-florbetaben PET.

c Inclusion criteria for Mini-Mental State Examination: score of 20 to 28.

d Phosphorylated tau 181 (P-tau181) screening criterion was not implemented for the entire trial duration (eMethods in Supplement 3 ).

e Exclusion criteria for MRI include presence of amyloid-related imaging abnormalities of edema/effusion, >4 cerebral microhemorrhages, >1 area of superficial siderosis, and any intracerebral hemorrhage >1 cm or severe white matter disease.

f Summary of other screen failure can be found in eTable 3 in Supplement 3 (lists reason if ≥20 participants).

g Stratified by baseline tau categorization and enrolling sites.

h One additional death occurred after treatment completion and in the follow-up period.

i Alzheimer disease progression to a degree prompting study discontinuation, per investigator judgment.

j Treatment completion criteria: amyloid plaque level of 11 Centiloids on any single scan or 11 to <25 Centiloids on 2 consecutive scans.

k Participants who met treatment completion criteria are included in discontinuation and completion numbers.

l Percentage calculated as No./total No. of participants with a PET scan at visit: n = 761 at 24 wk, n = 672 at 52 wk, and n = 620 at 76 wk. Corresponding number of participants and percentages for the low/medium tau population were 20.3% (n = 106) at 24 wk, 51.9% (n = 241) at 52 wk, and 73.5% (n = 321) at 76 wk.

A, 35.1% slowing (95% CI, 19.90%-50.23%) of clinical progression. B, 22.3% slowing (95% CI, 11.38%-33.15%) of clinical progression. C, 36.0% slowing (95% CI, 20.76%-51.15%) of clinical progression. D, 28.9% slowing (95% CI, 18.41%-39.44%) of clinical progression. iADRS data were analyzed using the natural cubic spline model with 2 degrees of freedom (NCS2) and CDR-SB data were analyzed with mixed models for repeated measures (MMRM). For MMRM analyses, 95% CIs for least-squares mean changes were calculated with the normal approximation method. For the Alzheimer Disease Cooperative Study—Instrumental Activities of Daily Living, 13-item cognitive subscale of the Alzheimer Disease Assessment Scale, and CDR-SB clinical assessments analyzed with NCS2, see eFigure 1 (low/medium tau population) and eFigure 2 (combined population) in Supplement 3 and Table 2. For all clinical assessments analyzed with MMRM, see eFigure 3 (low/medium tau population) and 4 (combined population) in Supplement 3 and Table 2. P  < .001 for all 76 week time points.

Biomarker data shown were analyzed using mixed models for repeated measures (MMRM). For MMRM analyses, 95% CIs for the least-squares mean changes were calculated with the normal approximation method. P  < .001 for all time points in panels A-D. B, P value is from Fisher exact test comparing the percent amyloid negative by treatment groups at each visit. E and F, The analysis was conducted using a Cox proportional hazards model. There were 163 events among 573 participants in the placebo group and 100 events among 555 participants in the donanemab group in the low/medium tau population and 288 events among 844 participants in the placebo group and 186 events among 805 participants in the donanemab group in the combined population. CDR-G indicates Clinical Dementia Rating Global Score.

Trial protocol

Statistical analysis plan

Nonauthor collaborators

Data sharing statement

• Donanemab for Alzheimer Disease—Who Benefits and Who Is Harmed? JAMA Editorial August 8, 2023 Jennifer J. Manly, PhD; Kacie D. Deters, PhD
• Amyloid-Targeting Monoclonal Antibodies for Alzheimer Disease JAMA Editorial August 8, 2023 Gil D. Rabinovici, MD; Renaud La Joie, PhD
• Novel Alzheimer Disease Treatments and Reconsideration of US Pharmaceutical Reimbursement Policy JAMA Editorial August 8, 2023 Meredith B. Rosenthal, PhD
• Ushering in a New Era of Alzheimer Disease Therapy JAMA Editorial August 8, 2023 Eric W. Widera, MD; Sharon A. Brangman, MD; Nathaniel A. Chin, MD
• Role of Registries in Medicare Coverage of New Alzheimer Disease Drugs JAMA Viewpoint October 10, 2023 This Viewpoint discusses how the design of the Centers for Medicare & Medicaid Services (CMS) registry could impact Medicare’s ability to evaluate whether monoclonal antibodies are reasonable and necessary for patients with Alzheimer disease and help physicians understand when the drug is most beneficial. Ilina C. Odouard, MPH; Mariana P. Socal, MD, PhD; Gerard F. Anderson, PhD
• Who Should Get the New Alzheimer Disease Drug? JAMA Medical News & Perspectives October 17, 2023 This Medical News story examines the complexity of determining who to treat with lecanemab, the new Alzheimer disease drug. Rita Rubin, MA
• Use of Donanemab in Early Symptomatic Alzheimer Disease—Reply JAMA Comment & Response December 19, 2023 Cynthia D. Evans, PhD; John R. Sims, MD
• Use of Donanemab in Early Symptomatic Alzheimer Disease JAMA Comment & Response December 19, 2023 Nunzio Pomara, MD; Bruno Pietro Imbimbo, PhD
• Risks of Harm in Alzheimer Disease by Amyloid Lowering JAMA Viewpoint June 18, 2024 This Viewpoint discusses how data gaps in published research impede clinicians’ ability to clearly discuss the risks and benefits of amyloid-lowering drugs for treating Alzheimer disease. Madhav Thambisetty, MD, PhD; Robert Howard, MD
• Highlights from the Alzheimer’s Association International Conference JAMA Medical News & Perspectives August 16, 2024 This Medical News article is an interview about the latest findings presented at the recent Alzheimer’s Association International Conference. Rita Rubin, MA
• FDA Green-Lights Second Alzheimer Drug, Donanemab JAMA Medical News in Brief August 20, 2024 Emily Harris

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Sims JR , Zimmer JA , Evans CD, et al. Donanemab in Early Symptomatic Alzheimer Disease : The TRAILBLAZER-ALZ 2 Randomized Clinical Trial . JAMA. 2023;330(6):512–527. doi:10.1001/jama.2023.13239

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Donanemab in Early Symptomatic Alzheimer Disease : The TRAILBLAZER-ALZ 2 Randomized Clinical Trial

• 1 Eli Lilly and Company, Indianapolis, Indiana
• 2 Boston Center for Memory and Boston University Alzheimer’s Disease Center, Boston, Massachusetts
• 3 Department of Neurology and Department of Psychiatry, Alpert Medical School of Brown University, Providence, Rhode Island
• 4 Butler Hospital, Providence, Rhode Island
• 5 Department of Neurology, Indiana University School of Medicine, Indianapolis
• 6 Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden; Memory Clinic, Skåne University Hospital, Lund, Sweden
• 7 Scottish Brain Sciences, Edinburgh, United Kingdom
• Editorial Donanemab for Alzheimer Disease—Who Benefits and Who Is Harmed? Jennifer J. Manly, PhD; Kacie D. Deters, PhD JAMA
• Editorial Amyloid-Targeting Monoclonal Antibodies for Alzheimer Disease Gil D. Rabinovici, MD; Renaud La Joie, PhD JAMA
• Editorial Novel Alzheimer Disease Treatments and Reconsideration of US Pharmaceutical Reimbursement Policy Meredith B. Rosenthal, PhD JAMA
• Editorial Ushering in a New Era of Alzheimer Disease Therapy Eric W. Widera, MD; Sharon A. Brangman, MD; Nathaniel A. Chin, MD JAMA
• Viewpoint Role of Registries in Medicare Coverage of New Alzheimer Disease Drugs Ilina C. Odouard, MPH; Mariana P. Socal, MD, PhD; Gerard F. Anderson, PhD JAMA
• Medical News & Perspectives Who Should Get the New Alzheimer Disease Drug? Rita Rubin, MA JAMA
• Comment & Response Use of Donanemab in Early Symptomatic Alzheimer Disease—Reply Cynthia D. Evans, PhD; John R. Sims, MD JAMA
• Comment & Response Use of Donanemab in Early Symptomatic Alzheimer Disease Nunzio Pomara, MD; Bruno Pietro Imbimbo, PhD JAMA
• Viewpoint Risks of Harm in Alzheimer Disease by Amyloid Lowering Madhav Thambisetty, MD, PhD; Robert Howard, MD JAMA
• Medical News & Perspectives Highlights from the Alzheimer’s Association International Conference Rita Rubin, MA JAMA
• Medical News in Brief FDA Green-Lights Second Alzheimer Drug, Donanemab Emily Harris JAMA

Question   Does donanemab, a monoclonal antibody designed to clear brain amyloid plaque, provide clinical benefit in early symptomatic Alzheimer disease?

Findings   In this randomized clinical trial that included 1736 participants with early symptomatic Alzheimer disease and amyloid and tau pathology, the least-squares mean change in the integrated Alzheimer Disease Rating Scale score (range, 0-144; lower score indicates greater impairment) at 76 weeks was −6.02 in the donanemab group and −9.27 in the placebo group for the low/medium tau population and −10.19 in the donanemab group and −13.11 in the placebo group in the combined study population, both of which were significant differences.

Meaning   Among participants with early symptomatic Alzheimer disease and amyloid and tau pathology, donanemab treatment significantly slowed clinical progression at 76 weeks.

Importance   There are limited efficacious treatments for Alzheimer disease.

Objective   To assess efficacy and adverse events of donanemab, an antibody designed to clear brain amyloid plaque.

Design, Setting, and Participants   Multicenter (277 medical research centers/hospitals in 8 countries), randomized, double-blind, placebo-controlled, 18-month phase 3 trial that enrolled 1736 participants with early symptomatic Alzheimer disease (mild cognitive impairment/mild dementia) with amyloid and low/medium or high tau pathology based on positron emission tomography imaging from June 2020 to November 2021 (last patient visit for primary outcome in April 2023).

Interventions   Participants were randomized in a 1:1 ratio to receive donanemab (n = 860) or placebo (n = 876) intravenously every 4 weeks for 72 weeks. Participants in the donanemab group were switched to receive placebo in a blinded manner if dose completion criteria were met.

Main Outcomes and Measures   The primary outcome was change in integrated Alzheimer Disease Rating Scale (iADRS) score from baseline to 76 weeks (range, 0-144; lower scores indicate greater impairment). There were 24 gated outcomes (primary, secondary, and exploratory), including the secondary outcome of change in the sum of boxes of the Clinical Dementia Rating Scale (CDR-SB) score (range, 0-18; higher scores indicate greater impairment). Statistical testing allocated α of .04 to testing low/medium tau population outcomes, with the remainder (.01) for combined population outcomes.

Results   Among 1736 randomized participants (mean age, 73.0 years; 996 [57.4%] women; 1182 [68.1%] with low/medium tau pathology and 552 [31.8%] with high tau pathology), 1320 (76%) completed the trial. Of the 24 gated outcomes, 23 were statistically significant. The least-squares mean (LSM) change in iADRS score at 76 weeks was −6.02 (95% CI, −7.01 to −5.03) in the donanemab group and −9.27 (95% CI, −10.23 to −8.31) in the placebo group (difference, 3.25 [95% CI, 1.88-4.62]; P  < .001) in the low/medium tau population and −10.2 (95% CI, −11.22 to −9.16) with donanemab and −13.1 (95% CI, −14.10 to −12.13) with placebo (difference, 2.92 [95% CI, 1.51-4.33]; P  < .001) in the combined population. LSM change in CDR-SB score at 76 weeks was 1.20 (95% CI, 1.00-1.41) with donanemab and 1.88 (95% CI, 1.68-2.08) with placebo (difference, −0.67 [95% CI, −0.95 to −0.40]; P  < .001) in the low/medium tau population and 1.72 (95% CI, 1.53-1.91) with donanemab and 2.42 (95% CI, 2.24-2.60) with placebo (difference, −0.7 [95% CI, −0.95 to −0.45]; P  < .001) in the combined population. Amyloid-related imaging abnormalities of edema or effusion occurred in 205 participants (24.0%; 52 symptomatic) in the donanemab group and 18 (2.1%; 0 symptomatic during study) in the placebo group and infusion-related reactions occurred in 74 participants (8.7%) with donanemab and 4 (0.5%) with placebo. Three deaths in the donanemab group and 1 in the placebo group were considered treatment related.

Conclusions and Relevance   Among participants with early symptomatic Alzheimer disease and amyloid and tau pathology, donanemab significantly slowed clinical progression at 76 weeks in those with low/medium tau and in the combined low/medium and high tau pathology population.

Trial Registration   ClinicalTrials.gov Identifier: NCT04437511

Deposition of β-amyloid in the brain is an early event in Alzheimer disease that leads to neurofibrillary tangles composed of tau protein and other characteristic brain changes referred to as the amyloid cascade . 1 , 2 Abnormal β-amyloid is a key pathological hallmark of Alzheimer disease defined by the 2018 National Institute on Aging and the Alzheimer’s Association Research Framework 3 and is one of the major targets in Alzheimer disease research and drug development.

Over the past decade, considerable advances occurred in testing the amyloid cascade hypothesis in Alzheimer disease clinical trials. Numerous amyloid-targeting therapy trials failed to show appreciable slowing of clinical disease progression 4 - 7 ; however, aducanumab, lecanemab, and donanemab recently showed promising amyloid plaque clearance, potentially benefitting patients. 8 - 10

Donanemab is an immunoglobulin G1 monoclonal antibody directed against insoluble, modified, N-terminal truncated form of β-amyloid present only in brain amyloid plaques. Donanemab binds to N-terminal truncated form of β-amyloid and aids plaque removal through microglial-mediated phagocytosis. 11 In the phase 2 TRAILBLAZER-ALZ trial of donanemab vs placebo, the primary outcome was met, as measured by the integrated Alzheimer Disease Rating Scale (iADRS), an integrated assessment of cognition and daily function. 9 Adverse events of interest included amyloid-related imaging abnormalities and infusion-related reactions. 9 To confirm and expand results from TRAILBLAZER-ALZ, we report results from TRAILBLAZER-ALZ 2, a global phase 3 randomized clinical trial that assessed donanemab efficacy and adverse events in a larger group of participants with low/medium tau pathology (the population studied in the phase 2 trial) and in a combined population including those with high tau pathology, a population hypothesized to be more difficult to treat due to more advanced disease.

TRAILBLAZER-ALZ 2 was a 76-week, phase 3, randomized, double-blind, parallel, multicenter, placebo-controlled trial with participants screened at 277 sites in 8 countries (eTable 1 in Supplement 3 ). Enrollment began June 19, 2020, and ended November 5, 2021, and database lock/unblinding (double-blind phase) occurred on April 28, 2023. The trial was originally designed as a phase 2 trial but was subsequently amended to a larger phase 3 trial in February 2021 in an effort to confirm and expand the results of the previous TRAILBLAZER-ALZ trial. The trial was conducted according to the Declaration of Helsinki, the International Conference on Harmonization Good Clinical Practice Guideline, and local regulatory requirements. An independent ethics committee/institutional review board at each site approved the study protocol ( Supplement 1 ), which is provided alongside the statistical analysis plan ( Supplement 2 ). Participants and study partners provided written consent. An independent data and safety monitoring board provided trial oversight.

The trial included participants aged 60 to 85 years with early symptomatic Alzheimer disease (mild cognitive impairment [MCI] 12 or Alzheimer disease with mild dementia). 3 P-tau181 screening was removed in an early protocol amendment (eMethods in Supplement 3 ). Eligible participants had screening Mini-Mental State Examination (MMSE) scores of 20 to 28, amyloid pathology (≥37 Centiloids) assessed with 18 F-florbetapir 13 or 18 F-florbetaben 14 positron emission tomography (PET), and presence of tau pathology assessed by 18 F-flortaucipir PET imaging with central image evaluation. 13 , 15 Tau PET scans were categorized as low/medium or high tau by visual and quantitative reads as previously described 16 - 20 ( Supplements 1 and 2 ). Screening procedures also included magnetic resonance imaging (MRI), and key exclusion criteria included presence of amyloid-related imaging abnormalities of edema/effusion, more than 4 cerebral microhemorrhages, more than 1 area of superficial siderosis, and any intracerebral hemorrhage greater than 1 cm or severe white matter disease on MRI. For all eligibility criteria, see Supplement 1 . Demographic information, including race and ethnicity, was collected to potentially understand any differences in disease course, treatment effects, or adverse events. The participants self-reported race and ethnicity based on fixed categories.

Eligible participants were randomly assigned in a 1:1 ratio ( Figure 1 ) by a computer-generated sequence using interactive web response systems, with stratification by baseline tau categorization and enrolling sites; the randomization block size was 4. Randomized participants received either donanemab (700 mg for the first 3 doses and 1400 mg thereafter) or placebo, administered intravenously every 4 weeks for up to 72 weeks. If amyloid plaque level (assessed at 24 weeks and 52 weeks) was less than 11 Centiloids on any single PET scan or less than 25 but greater than or equal to 11 Centiloids on 2 consecutive PET scans (TRAILBLAZER-ALZ cutoffs 9 ), donanemab was switched to placebo in a blinded procedure. Final adverse events and efficacy assessments were performed at 76 weeks. Amyloid-related imaging abnormality monitoring occurred with scheduled MRIs at 4, 12, 24, 52, and 76 weeks and unscheduled MRIs at investigator discretion. Any participant with detected amyloid-related imaging abnormalities had imaging every 4 to 6 weeks until resolution or stabilization. Amyloid-related imaging abnormality management and treatment interruption guidelines (eTable 2 in Supplement 3 ) depended on severity and symptoms. If infusions were held, investigators were advised to await resolution of amyloid-related imaging abnormalities of edema/effusion on radiographic imaging and stabilization of amyloid-related imaging abnormalities of microhemorrhages and hemosiderin deposits before resuming infusions. Permanent discontinuation was advised for macrohemorrhages. Investigators made final amyloid-related imaging abnormality management decisions.

The primary outcome was change in the iADRS score from baseline to 76 weeks in either the low/medium tau population or combined (low/medium and high tau) population. The iADRS is an integrated assessment of cognition and daily function from the 13-item cognitive subscale of the Alzheimer Disease Assessment Scale (ADAS-Cog 13 ) and Alzheimer Disease Cooperative Study—Instrumental Activities of Daily Living (ADCS-iADL), measuring global disease severity across the Alzheimer disease continuum as a single summary score. The iADRS is validated and captures clinical progression from MCI due to Alzheimer disease through moderate dementia due to Alzheimer disease, and treatment effects have been demonstrated across MCI and Alzheimer disease with mild dementia. 6 , 9 , 21 - 27 The possible scores on the iADRS range from 0 to 144 (lower scores indicate greater impairment), and the meaningful within-patient change (MWPC) is a change of 5 points for those with Alzheimer disease with MCI and 9 points for those with Alzheimer disease with mild dementia. The MWPC, or minimal clinically important difference (MCID) as in Supplement 1 and 2 , is a threshold for outcome scores (either patient-reported or physician-measured) above which a patient or physician would consider the change meaningful. 28

Prespecified secondary outcomes included changes from baseline to 76 weeks by sum of boxes of the Clinical Dementia Rating Scale (CDR-SB), the ADAS-Cog 13 , the ADCS-iADL, and MMSE in the low/medium tau or combined population. Amyloid plaque reduction at 76 weeks, percentage of participants reaching amyloid clearance (<24.1 Centiloids measured by amyloid PET 9 , 29 ) at 24 weeks and 76 weeks, tau PET 1 (frontal cortical regions) change, volumetric MRI (vMRI; whole brain, hippocampus, and ventricles) change, and adverse events were additional secondary outcomes. Supplement 1 provides a complete listing and methodology of adverse events assessments. Amyloid-related imaging abnormalities of edema/effusion, amyloid-related imaging abnormalities of microhemorrhages and hemosiderin deposits, and infusion-related reactions were adverse events of special interest because they were considered class effects or observed in previous trials. 9 , 30 - 32 Secondary outcomes related to pharmacokinetics and antidrug antibodies were also prespecified and are planned for subsequent studies. Exploratory outcomes included change in plasma P-tau217 (C 2 N Diagnostics) at 76 weeks and time-based analyses: progression risk using the CDR Global score (CDR-G; progression defined as any increase from baseline in CDR-G at consecutive visits), participants with no progression at 1 year on the CDR-SB, and clinical progression delay (ie, months saved with treatment) on the iADRS and CDR-SB. Additional information about outcome measures, including score ranges and MWPCs, is provided in eMethods in Supplement 3 .

Prespecified primary and secondary outcomes were controlled for multiplicity (gated) at 76 weeks ( Supplement 2 and eMethods in Supplement 3 ) except for MMSE, changes in vMRI measurements, and adverse event assessments. Additional time points were gated for amyloid clearance and P-tau217. Nominal P values are reported for gated and nongated outcomes.

The trial was originally designed as a phase 2 trial with a plan to enroll 500 participants and assess CDR-SB as the primary outcome, but was subsequently amended to a phase 3 trial assessing the iADRS score as the primary outcome in February 2021 in an effort to confirm and expand the results of the TRAILBLAZER-ALZ trial. No unblinded data analysis of TRAILBLAZER-ALZ 2 was performed or used to inform design or analyses. Further details regarding major protocol or study adjustments are in eMethods in Supplement 3 and the trial protocol in Supplement 1 .

Revised study sample size and power calculations were based on the primary results from the TRAILBLAZER-ALZ trial, 9 where mean progression in the placebo and donanemab groups on iADRS was −10.06 and −6.86 (approximately 32% slowing of disease progression) over 76 weeks, respectively. Multiple longitudinal data sets were simulated and the natural cubic spline model with 2 degrees of freedom (NCS2) was fit to each sample to determine the power. The powering and sample size determination of the trial was based on the low/medium tau population. With a sample size of approximately 1000 randomized participants in the low/medium tau population and an assumed 30% discontinuation rate, the NCS model provided greater than 95% power to achieve statistical significance at a 2-sided α level of .05. The total planned enrollment (including both the low/medium and high tau populations) was 1800.

Most statistical analyses were done with SAS version 9.4 (SAS Institute). Some time-based progression analyses were analyzed with R Project version 4.3.0 (R Foundation).

The efficacy analyses were conducted by using the evaluable efficacy population (participants with a baseline and at least 1 postbaseline efficacy measurement based on randomized treatment). A prespecified gated testing scheme 33 , 34 was used to control for study-wise type I error rate at 2-sided α level of .05, with 80% of initial α spend (.04) for multiplicity control allocated to the low/medium tau population and 20% of initial α spend (.01) for multiplicity control allocated to the combined population (testing scheme in Supplement 2 ; eMethods in Supplement 3 also describes time-based analyses not described below).

Clinical outcomes (except for CDR-SB) were primarily analyzed using an NCS2 model. The protocol-specified week value for each participant was used as a continuous variable to create NCS basis functions with knot locations at 0 weeks, the median observation time, and 76 weeks. The model restricted baseline estimates to be the same for treatment and placebo groups. The baseline score and each scheduled postbaseline score were dependent variables in the model. The model’s independent variables included NCS basis expansion terms (2 terms), NCS basis expansion term × treatment interaction (2 terms), baseline age, concomitant acetylcholinesterase inhibitor and/or memantine use at baseline (yes/no), and randomization stratifying factors (pooled site and baseline tau category [baseline tau category in combined population only]). An unstructured variance covariance matrix was used to model the within-participant errors using restricted maximum likelihood. The Kenward-Roger approximation was used to estimate the denominator degrees of freedom.

The MMRM was used to primarily assess CDR-SB, plasma P-tau217, amyloid PET, and vMRI. The analysis model used change from baseline as the dependent variable. The model was adjusted for age, baseline value, visit as a categorical variable, treatment, baseline × visit interactions, treatment × visit interactions, concomitant acetylcholinesterase inhibitor/memantine use at baseline (CDR-SB only), and randomization stratifying factors of pooled site and, for combined population only, baseline tau category. For vMRI, only age and baseline brain volumes were covariates. The covariance matrix structure used was the same as NCS. Plasma P-tau 217 value was log 10 -transformed to meet the normality assumption.

Both the NCS2 and MMRM use the same protocol-specified time values for each participant in the analysis; the NCS2 model makes additional parametric assumptions for the shape of the longitudinal mean structure that can lead to increased efficiency.

The percent slowing relative to placebo was calculated by dividing the least-squares mean (LSM) change from baseline treatment differences at 76 weeks by the LSM change from baseline with placebo at 76 weeks and multiplying by 100.

ANCOVA analysis was conducted for tau PET standardized uptake value ratio (SUVR), with change from baseline to 76 weeks as the dependent variable and covariates of baseline tau SUVR, age, and, for the combined population, tau burden.

MMRM, NCS with 3 degrees of freedom model (NCS3), and bayesian disease progression model (DPM) were applied as sensitivity analyses for the primary outcome. DPM was applied to measure the proportion of disease progression in donanemab-treated participants relative to placebo-treated participants using a disease progression ratio, as previously described. 35 Details on sensitivity analyses for censoring after amyloid-related imaging abnormalities or infusion-related reactions, per-protocol analysis, and analysis of study completers are in eMethods in Supplement 3 . Details of subgroup analyses and time-based analyses are also described in eMethods in Supplement 3 .

Cox proportional hazard models were applied to CDR-G (gated), iADRS (nongated), and CDR-SB (nongated). Progression to next clinical stage was defined as any increase in CDR-G at 2 consecutive visits from baseline. MWPC was established as an iADRS change of greater than or equal to 5 for those with Alzheimer disease with MCI and greater than or equal to 9 points for those with Alzheimer disease with mild dementia and a CDR-SB change of greater than or equal to 1 point for those with Alzheimer disease with MCI and greater than or equal to 2 points for Alzheimer disease with mild dementia at 2 consecutive visits from baseline.

Analyses of the high tau population alone (ie, not combined with the low/medium tau population) for primary and secondary outcomes was performed post hoc.

Adverse events were evaluated in all participants exposed to study drug and were summarized according to event frequency by treatment assignment.

If less than 30% of the ADCS-iADL, 3 or fewer items of the ADAS-Cog 13, or 1 box of the CDR were missing, the total score for these assessments was imputed. If more items were missing than defined, the total score at that visit was considered missing ( Supplement 2 ). If either the ADCS-iADL or ADAS-Cog 13 scores were missing, the iADRS score was considered as missing. The missing data for NCS and MMRM analyses were handled by the likelihood-based mixed-effect model and the model parameters were estimated using restricted likelihood estimation incorporating all the observed data.

All presented primary, secondary, and exploratory outcomes were controlled for multiplicity (gated) in at least 1 population except for MMSE, vMRI measurements, and safety assessments. Of the 24 gated outcomes (eMethods in Supplement 3 ), 23 were statistically significant.

Of 8240 participants screened, 1736 were enrolled (mean age, 73.0 years; 996 [57.4%] women) and 76% completed the trial: 860 were assigned to receive donanemab and 876 were assigned to receive placebo ( Figure 1 ). Baseline characteristics are summarized by treatment groups in both low/medium tau (n = 1182) and combined populations (n = 1736) ( Table 1 ). As expected, the combined population had higher tau biomarkers at baseline due to the inclusion of participants with high tau pathology and showed greater impairment across baseline clinical assessments.

In the low/medium tau population, LSM change from baseline in the iADRS score at 76 weeks was −6.02 (95% CI, −7.01 to −5.03) in the donanemab group and −9.27 (95% CI, −10.23 to −8.31) in the placebo group (difference, 3.25 [95% CI, 1.88-4.62]; P  < .001), representing a 35.1% (95% CI, 19.90%-50.23%) slowing of disease progression ( Figure 2 , Table 2 ).

In the combined population, LSM change from baseline in the iADRS score at 76 weeks was −10.19 (95% CI, −11.22 to −9.16) in the donanemab group and −13.11 (95% CI, −14.10 to −12.13) in the placebo group (difference, 2.92 [95% CI, 1.51-4.33]; P  < .001), representing a 22.3% (95% CI, 11.38%-33.15%) slowing of disease progression ( Figure 2 , Table 2 ).

In the low/medium tau population, the differences between treatment groups in the LSM change from baseline at 76 weeks was −0.67 (95% CI, −0.95 to −0.40) (36.0% [95% CI, 20.76%-51.15%] slowing of clinical progression) for CDR-SB, 1.83 (95% CI, 0.91-2.75) (39.9% [95% CI, 19.15%-60.58%] slowing of clinical progression) for ADCS-iADL, and −1.52 (95% CI, −2.25 to −0.79) (32.4% [95% CI, 16.55%-48.35%] slowing of clinical progression) for ADAS-Cog 13 ( Figure 2 , Table 2 ; eFigure 1 and 3 in Supplement 3 ).

In the combined population, the differences in the LSM change from baseline to 76 weeks between the donanemab and placebo groups were −0.70 (95% CI, −0.95 to −0.45) (28.9% [95% CI, 18.26%-39.53%] slowing of clinical progression) for CDR-SB, 1.70 (95% CI, 0.84-2.57) (27.8% [95% CI, 13.48%-42.13%] slowing of clinical progression) for ADCS-iADL, and −1.33 (95% CI, −2.09 to −0.57) (19.5% [95% CI, 8.23%-30.83%] slowing of clinical progression) for ADAS-Cog13 ( Figure 2 , Table 2 ; eFigures 2 and 4 in Supplement 3 ).

At 76 weeks, brain amyloid plaque level decreased by 88.0 Centiloids (95% CI, −90.20 to −85.87) with donanemab treatment and increased by 0.2 Centiloids (95% CI, −1.91 to 2.26) in the placebo group in the low/medium tau population; in the combined population, amyloid plaque level decreased by 87.0 Centiloids (95% CI, −88.90 to −85.17) with donanemab treatment and decreased by 0.67 Centiloids (95% CI, −2.45 to 1.11) in the placebo group ( Figure 3 A). The percentages of donanemab-treated participants in the low/medium tau population who reached amyloid clearance 29 , 38 were 34.2% (95% CI, 30.22%-38.34%) at 24 weeks and 80.1% (95% CI, 76.12%-83.62%) at 76 weeks compared with 0.2% (95% CI, 0.03%-1.02%) at 24 weeks and 0% (95% CI, 0.00%-0.81%) at 76 weeks of placebo-treated participants. In the combined population, amyloid clearance was reached in 29.7% (95% CI, 26.56%-33.04%) of participants at 24 weeks and 76.4% (95% CI, 72.87%-79.57%) at 76 weeks of donanemab-treated participants compared with 0.2% (95% CI, 0.07%-0.90%) at 24 weeks and 0.3% (95% CI, 0.08%-1.05%) at 76 weeks of placebo-treated participants ( Figure 3 B).

Evaluation of the LSM change from baseline to 76 weeks in frontal tau SUVR (cerebellar gray reference) did not show a significant difference in the low/medium tau or in the combined population (eFigure 5 in Supplement 3 ). The difference in LSM change in tau SUVR from placebo in the frontal lobe at 76 weeks was −0.0002 (95% CI, −0.01 to 0.01; P  = .97) in the low/medium tau population and −0.0041 (95% CI, −0.01 to 0.01; P  = .45) in the combined population.

For both the low/medium tau and combined populations, at 76 weeks, vMRI (a non-gated secondary outcome) showed a greater decrease in whole brain volume, a lesser decrease in the hippocampal volume, and a greater increase in ventricular volume in the donanemab group than in the placebo group (eFigure 6 in Supplement 3 ).

P-tau217 was significantly reduced from baseline with donanemab treatment compared with placebo in the low/medium tau and combined population. The difference in LSM change in tau SUVR (log 10 -based) vs placebo was −0.25 (95% CI, −0.28 to −0.22; P  < .001) in the low/medium tau population and −0.22 (95% CI −0.24 to −0.20; P  < .001) in the combined population at 76 weeks ( Figure 3 C and D).

There was a 38.6% (CDR-G hazard ratio, 0.61 [95% CI, 0.47-0.80]; P  < .001) lower risk of disease progression in the low/medium tau population and a 37.4% (CDR-G hazard ratio, 0.63 [95% CI, 0.51-0.77; P  < .001) lower risk of disease progression in the combined population with donanemab treatment compared with placebo over the 18-month trial ( Figure 3 E and F; see eFigure 7 in Supplement 3 for nongated disease progression analyses of iADRS and CDR-SB). Substantial decline in the low/medium tau population occurred in 100 (18%) donanemab-treated participants and 163 (28%) placebo-treated participants and, in the combined population, occurred in 186 (23%) donanemab-treated and 288 (34%) placebo-treated participants. In addition, in the low/medium tau population, an estimated 47% of participants were stable (showed no decline in CDR-SB from baseline) with donanemab at 1 year compared with 29% of participants receiving placebo ( P  < .001) (eTable 6 in Supplement 3 ). At 76 weeks, disease progression with donanemab treatment in the low/medium tau population was delayed by 4.36 months (95% CI, 1.87-6.85) on the iADRS and 7.53 months (95% CI, 5.69-9.36) on the CDR-SB.

Sensitivity analyses of the iADRS score (eFigure 8 in Supplement 3 ) using NCS3, MMRM, and DPM analyses, NCS2 in the completers and per protocol populations, and censoring change scores after amyloid-related imaging abnormalities edema/effusion and/or infusion-related reaction observations were consistent with the primary analysis (33.4%-39.6% slowing of clinical progression).

The findings as measured by iADRS and CDR-SB were generally consistent across baseline characteristic subgroups where the subgroup was sufficiently large (eFigure 9 in Supplement 3 ).

Analysis of the smaller (n = 552) high tau population alone (ie, not combined with the low/medium tau population) for all primary and secondary outcomes was completed post hoc. The difference between the donanemab and placebo groups in the LSM change from baseline at 76 weeks was 1.26 (95% CI, −1.77 to 4.28; P  = .42) for the iADRS score and −0.69 (95% CI −1.19 to −0.20; P  = .006) for the CDR-SB score. For additional assessments in the high tau population, see eTables 4, 5, and 10 and eFigures 10-13 in Supplement 3 .

The incidence of death was 1.9% in the donanemab group and 1.1% in the placebo group, while the incidence of serious adverse events was 17.4% in the donanemab group and 15.8% in the placebo group ( Table 3 ). In the donanemab group, 3 participants with serious amyloid-related imaging abnormalities subsequently died (2 APOE ε4 heterozygous carriers and one noncarrier; none were prescribed anticoagulant or anti-platelet medications; one resumed treatment after resolution of severe amyloid-related imaging abnormalities edema/effusion that was accompanied by severe amyloid-related imaging abnormalities microhemorrhages and hemosiderin deposits and one had superficial siderosis at baseline) (eTable 9 in Supplement 3 ). Treatment-emergent adverse events were reported by 759 of 853 participants (89.0%) receiving donanemab and 718 of 874 participants (82.2%) receiving placebo. Treatment discontinuation due to adverse events was reported in 112 participants receiving donanemab and 38 participants receiving placebo. The most common adverse events that led to treatment discontinuation were infusion-related reactions, either amyloid-related imaging abnormalities edema/effusion or microhemorrhages and hemosiderin deposits, and hypersensitivity (eTable 7 in Supplement 3 ).

Either amyloid-related imaging abnormalities of edema/effusion or microhemorrhages and hemosiderin deposits occurred in 314 participants (36.8%) receiving donanemab and 130 (14.9%) receiving placebo. Amyloid-related imaging abnormalities of edema/effusion, determined via MRI, occurred in 205 participants (24.0%) in the donanemab group and in 18 (2.1%) in the placebo group. Most amyloid-related imaging abnormalities of edema/effusion events were mild to moderate (see eTable 2 in Supplement 3 ) (n = 188 [93.1%] in the donanemab group; n = 17 [100%] in the placebo group). Symptomatic amyloid-related imaging abnormalities of edema/effusion were reported by 52 participants (6.1%) in the donanemab group (25.4% of those with amyloid-related imaging abnormalities of edema/effusion), with 45 participants (86.5%) having symptom resolution. Most cases (57.9%) of first amyloid-related imaging abnormalities of edema/effusion occurred after receiving up to 3 donanemab infusions. Serious amyloid-related imaging abnormalities of edema/effusion (see Table 3 ) occurred in 13 participants (1.5%) receiving donanemab. First events of amyloid-related imaging abnormalities of edema/effusion radiographically resolved in 198 (98.0%) donanemab-treated participants and 11 (64.7%) placebo-treated participants, with a mean amyloid-related imaging abnormalities of edema/effusion resolution time of 72.4 days for those receiving donanemab and 63.5 days for those receiving placebo. Edema/effusion were numerically less common among APOE ε4 noncarriers than carriers, with higher frequency among homozygotes than heterozygotes ( Table 3 ; further details in eTable 8 in Supplement 3 ).

The incidence of amyloid-related imaging abnormalities of microhemorrhages and hemosiderin deposits, determined via MRI, was higher in the donanemab group than the placebo group (268 participants [31.4%] vs 119 participants [13.6%]). Incidence of amyloid-related imaging abnormalities of microhemorrhages and hemosiderin deposits in the absence of amyloid-related imaging abnormalities of edema/effusion was not different between treatments (12.7% in the donanemab group vs 12.4% in the placebo group). The incidence of microhemorrhage and superficial siderosis was greater in the donanemab group than in the placebo group (microhemorrhage: 26.8% vs 12.5%; superficial siderosis: 15.7% vs 3.0%). Three intracerebral hemorrhages greater than 1 cm were recorded in the donanemab group and 2 were recorded in the placebo group ( Table 3 ).

Infusion-related reactions were reported by 74 participants (8.7%) in the donanemab group and 4 (0.5%) in the placebo group. Serious infusion-related reactions or hypersensitivity occurred in 3 participants (0.4%) in the donanemab group. Most infusion-related reactions were mild to moderate and occurred during or within 30 minutes of the end of the infusion and between the second and fifth infusion (73.6%). Anaphylactic reaction occurred in 3 participants (0.4%) in the donanemab group and were considered to be mild to moderate.

In this phase 3 trial, donanemab significantly slowed Alzheimer disease progression, based on the iADRS score, compared with placebo in the low/medium tau and combined tau populations and across secondary clinical outcomes of CDR-SB, ADAS-Cog 13 , and ADCS-iADL scores.

Donanemab treatment resulted in clinically meaningful benefit (considered to be >20% slowing of clinical progression 39 - 41 ) on the iADRS and CDR-SB scales for both the low/medium tau and combined populations, regardless of statistical model. Additional support for clinical relevance is the 38.6% risk reduction of disease progression as measured on the CDR-G score and the 4.4 to 7.5 months saved over the 18-month study (low/medium tau population). Furthermore, an estimated 47% of participants receiving donanemab had no change in the CDR-SB at 1 year (no disease progression), compared with 29% of participants receiving placebo.

This trial used a definition of a MWPC 28 based on any incremental change on the CDR-G scale (Alzheimer disease with MCI to mild Alzheimer disease or mild Alzheimer disease to moderate Alzheimer disease) or point changes of −5 on the iADRS and 1 on the CDR-SB for those with Alzheimer disease with MCI or −9 on the iADRS and 2 on the CDR-SB for those with Alzheimer disease with mild dementia at consecutive visits from baseline. In analyses assessing whether individual participants reached thresholds of clinically important progression over the course of the trial, donanemab resulted in significantly lower risk of meaningful change on the CDR-G as well as the prespecified nongated analyses of the iADRS and CDR-SB outcomes.

These clinical outcomes were achieved in 52% of low/medium tau participants completing donanemab treatment by 1 year, based on when a participant met amyloid clearance criteria. Limited-duration dosing was a distinct trial design feature reflecting donanemab binding specificity for amyloid plaque and implemented to decrease burden, cost, and potentially unnecessary treatments. 11 Early significant changes on both brain amyloid PET scans and P-tau217 blood test results suggest opportunities for clinical monitoring of therapy. Donanemab treatment resulted in significantly reduced brain amyloid plaque in participants at all time points assessed, with 80% (low/medium tau population) and 76% (combined population) of participants achieving amyloid clearance at 76 weeks. Clearance beyond 76 weeks, and associated Alzheimer disease biomarkers levels, are currently being studied in the ongoing extension phase. The lack of response in frontal tau-PET is inconsistent with the TRAILBLAZER-ALZ phase 2 results. 9 , 38 Additional regions have yet to be analyzed and reported. Factors resulting in this inconsistency will be examined. Changes in vMRI (including a greater decrease in whole brain volume in the donanemab group) were consistent with previous reports 9 , 42 and would benefit from further exploration.

The general belief is that treating Alzheimer disease at the earliest disease stage is likely to result in more clinically meaningful effects. 43 , 44 Post hoc evaluation in only high tau participants demonstrated no differences ( P < .05) on the primary outcome or on most secondary clinical outcomes in donanemab-treated compared with placebo-treated participants within the 18-month trial, with the exception of CDR-SB. Compared with significant differences in the low/medium tau population, this supports the hypothesis that a greater benefit from amyloid-lowering therapies may occur when initiated at an earlier disease stage.

Similar to other amyloid-lowering drugs, and the phase 2 TRAILBLAZER-ALZ trial, amyloid-related imaging abnormalities are an associated adverse event. When amyloid-related imaging abnormalities occur, they are mostly asymptomatic and resolve in approximately 10 weeks. When symptoms occur, they are usually mild, consisting of a headache or increase in confusion, but can have more severe symptoms such as seizures. In some instances, these events can be life-threatening and result in, or lead to, death. For 1.6% of participants in the donanemab treatment group, amyloid-related imaging abnormalities led to serious outcomes, such as hospitalization, and required supportive care and/or corticosteroid use. It is also important to note that 3 deaths in TRAILBLAZER-ALZ 2 occurred after serious amyloid-related imaging abnormalities. Further evaluation of the risks associated with serious and life-threatening amyloid-related imaging abnormalities will be important to identify the best approaches for managing risks and maximizing benefit, in addition to earlier treatment of the disease when less amyloid pathology is present and, theoretically, when amyloid-related imaging abnormalities risk is lower.

This study has several limitations. First, an inherent limitation to limited-duration dosing was variability in total donanemab doses received and/or duration of donanemab dosing. Second, data collection was for 76 weeks, limiting long-term understanding of donanemab; however, a study extension is ongoing. Third, the studied populations were primarily White (91.5%), which may limit generalizability to other populations due to a lack of racial and ethnic diversity. Fourth, although no related protocol amendments were necessary, this trial was conducted during the COVID-19 pandemic, and COVID-19 was the most commonly reported adverse event across treatment groups (see eMethods in Supplement 3 ). Fifth, direct comparison of results to other amyloid-targeting trials is not possible due to trial design differences such as stratification by baseline tau PET category. Sixth, amyloid-related imaging abnormality and infusion-related reaction occurrences may have caused participants and investigators to infer treatment assignment; attempts to minimize bias included blinding CDR raters to adverse event information and, based on sensitivity analyses, censoring change scores after the first observation of amyloid-related imaging abnormalities of edema/effusion and/or infusion-related reactions did not impact the results.

Among participants with early symptomatic Alzheimer disease and amyloid and tau pathology, donanemab significantly slowed clinical progression at 76 weeks in those with low/medium tau and in the combined low/medium and high tau pathology population.

Accepted for Publication: June 28, 2023.

Published Online: July 17, 2023. doi:10.1001/jama.2023.13239

Corresponding Author: John R. Sims, MD, Eli Lilly and Company, Lilly Corporate Center DC 1532, Indianapolis, IN 46285 ( [email protected] ).

Author Contributions: Dr Solomon had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Sims, Zimmer, Ardayfio, Sparks, Wessels, Wang, Collins, Salloway, Mintun, Skovronsky.

Acquisition, analysis, or interpretation of data: Sims, Zimmer, Evans, Lu, Ardayfio, Sparks, Wessels, Shcherbinin, Wang, Nery, Collins, Solomon, Apostolova, Hansson, Ritchie, Brooks, Mintun, Skovronsky.

Drafting of the manuscript: Sims, Evans, Ardayfio, Wang, Nery, Collins, Ritchie, Skovronsky.

Critical review of the manuscript for important intellectual content: Sims, Zimmer, Ardayfio, Wessels, Shcherbinin, Salloway, Apostolova, Ritchie, Mintun, Skovronsky.

Statistical analysis: Lu, Ardayfio, Sparks, Wang, Salloway, Skovronsky.

Obtained funding: Sims, Brooks, Mintun, Skovronsky.

Administrative, technical, or material support: Zimmer, Evans, Wessels, Shcherbinin, Collins, Salloway, Brooks, Mintun, Skovronsky.

Supervision: Sims, Wessels, Nery, Collins, Solomon, Brooks, Mintun, Skovronsky.

Other - imaging and biomarker analysis: Collins.

Other - suggested additional analyses: Apostolova.

Conflict of Interest Disclosures: Dr Sims reported being an employee of Eli Lilly and Company during the conduct of the study. Dr Zimmer reported receiving personal fees from and being a shareholder in Eli Lilly and Company during the conduct of the study. Dr Evans reported being an employee of and minority shareholder in Eli Lilly and Company during the conduct of the study. Dr Lu reported being an employee of and stockholder in Eli Lilly. Dr Ardayfio reported being an employee of and stockholder in Eli Lilly during the conduct of the study. Dr Wessels reported being a minor shareholder in Eli Lilly and Company outside the submitted work. Dr Shcherbinin reported being an employee of and stockholder in Eli Lilly and Company during the conduct of the study and Eli Lilly and Company having patents pending relevant to this research. Dr Nery reported being an employee of and shareholder in Eli Lilly and Company during the conduct of the study. Dr Collins reported being an employee of and stockholder in from Eli Lilly and Company during the conduct of the study. Dr Salloway reported receiving personal fees and grants from Biogen, Eli Lilly, Genentech, Avid, Roche, Eisai, Novartis, Acumen, NovoNordisk, and Prothena during the conduct of the study. Dr Apostolova reported receiving grants from NIA, Alzheimer Association, AVID Radiopharmaceuticals, Life Molecular Imaging, and Roche Diagnostics and personal fees from Eli Lilly, Biogen, Two Labs, IQVIA, Genentech, Siemens, Corium, GE Healthcare, Eisa, Roche Diagnostics, Alnylam, Alzheimer Association, and from the US Food And Drug Administration outside the submitted work. Dr Hansson reported personal fees from AC Immune, Amylyx, Alzpath, BioArtic, Biogen, Cerveau, Eisai, Eli Lilly, Fujirebio, Merk, Novartis, Novo Nordisk, Roche, Sanofi, and Siemens outside the submitted work. Dr Ritchie reported receiving personal fees from Actinogen, Biogen, Cogstate, Eisai, Eli Lilly, Janssen Cilag, Merck, Novo Nordisk, Roche Diagnostics, and Signant and being founder of and majority shareholder in Scottish Brain Sciences outside the submitted work. Dr Brooks reported being an employee of and shareholder in Eli Lilly and Company. Dr Mintun reported being an employee of and shareholder in Eli Lilly and Company and having a patent pending with Eli Lilly and Company. Dr Skovronsky reported being an employee of and shareholder in Eli Lilly and Company. No other disclosures were reported.

Funding/Support: This work was funded by Eli Lilly and Company.

Role of the Funder/Sponsor: Eli Lilly and Company was responsible for design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Group Information: The TRAILBLAZER-ALZ 2 Investigators appear listed in Supplement 4 .

Data Sharing Statement: See Supplement 5 .

Additional Contributions: We thank all the trial participants and their families and caregivers who participated in the TRAILBLAZER-ALZ 2 trial as well as the site staff, raters, and site investigators (see list in Supplement 4 ); members of the data and safety monitoring board; vendor partners including BioAgilitix, Clario, Clinical Trial Media, Cogstate, C 2 N Diagnostics, Invicro, IQVIA, Labcorp and Quanterix. The authors would like to thank the following salaried employees of Eli Lilly and Company for their contributions to TRAILBLAZER-ALZ 2, for which they received no additional compensation: Andrea Abram, MBA; Hrideep Antony, BS; Anupa Arora, MD; Theresa Bauer, BS; Jude Burger, MS; Yang Dai, MS; Russell A Delgiacco, MS; Marybeth Devine, BS; Dawn East, BS; Tim Edison, PharmD; Naohisa Hatekeyama, MS; Jeremy T Hemiup, MS, MBA; Stacy A Huckins, BS; Blaire Iris Kaufman, BS; Rashna Khanna, MD; Min Jung Kim, MS; Albert Lo, MD, PhD; Dedeepya Masarapu, B Pharm; Shoichiro Sato, MD, PhD; Adam Schaum, MAS; Linda Shurzinske, MS; Andrea L Speas, RNN, BSN; LisaAnn Trembath, MS; Giulia Tronchin, PhD; Melissa Veenhuizen, DVM, MS; Wen Xu, PhD; and Wei Zhou, MS. The authors would like to acknowledge Paula Hauck, PhD; Deirdre Hoban, PhD; and Carmen Deveau, PhD, salaried employees of Eli Lilly and Company, for project management support, and strategic scientific communication expertise, for which they received no additional compensation.

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The mine of the future gets connected

A groundbreaking partnership uses private cellular networks to transform mining.

Global Vertical Partner Lead, Mining, Ericsson Enterprise Wireless Solutions

Imagine… Rock bolts in a mine that detect movement and warn workers. Drill rigs that work in total autonomous sync with one another. Systems that tell workers what’s approaching around the corner, so they can avoid collisions. Welcome to the mine of the future—being realized today by a unique partnership of Ericsson and mining equipment provider Epiroc.

Mining companies worldwide are racing to boost productivity, cut costs and improve safety. At the same time, they're under pressure to reduce their environmental impact. The solution? Automation and digitalization, enabled by robust, reliable cellular networks.

The full potential of these innovations is often constrained by the limitations of existing communication infrastructure. That’s changing, thanks to the partnership between Ericsson and Epiroc, a frontrunner in mining equipment and solutions.

Since 2016, this collaboration has focused on simplifying the use of private cellular technologies for wireless telematics data, digitalization and automation in mines. By standardizing site automation and connectivity, mining products, services and solutions are becoming safer, smarter and more efficient.

Epiroc and Ericsson, both veterans in the mining industry, understand of the industry’s key communications needs. Their expertise, in turn, drives the development of advanced solutions for next-generation mining.

Why cellular shines in mining environments

Mines are complicated structures, with extensive tunnels twisting and turning for hundreds of kilometers underground or vast surfaces covered in roads. Modern mining demands a high level of connectivity due to its challenging and unforgiving environment. With both human lives and business goals at stake, mining operations require connectivity that:

• remains continuously available  
• provides high bandwidth and low latency for automated and semi-automated machines
• ensures multi-layer security

Private cellular networks, especially those using 4G LTE or 5G technology, deliver significant advantages over traditional communication methods like Wi-Fi in the demanding environment of a mine.

These networks offer superior coverage and capacity, ensuring reliable connectivity in extensive underground tunnels or large open-pit operations.

The high bandwidth and low latency of 4G and 5G networks are essential for modern mining applications, enabling real-time control of autonomous drilling rigs and the instant transmission of high-definition video for remote monitoring.

Fig. 1. Use cases found along the mining process that benefit from cellular connectivity

While Wi-Fi provides localized, cost-effective coverage in controlled areas, private networks deliver reliable connectivity across vast underground tunnels and operations. LTE/5G networks require fewer access points compared to Wi-Fi, thus reducing the cost of deployment and operations, and lowering the risk of network outages, which can affect worker safety. However, mines will use both Wi-Fi and private networks within their deployments from both a short- and long-term perspective.

Mines are long-term investments – many having been operating for decades. As mining operations change and evolve—the communication infrastructure must expand and adjust accordingly. Private cellular networks offer this flexibility, allowing for easy scalability as new areas are developed or operations shift.

Epiroc makes the tools for next-gen mining. Ericsson connects them.

Building connectivity for the mine of the future requires a collaborative approach. Epiroc provides specialized technical solutions for mines, including advanced drill rigs, load-and-haul-and-dump vehicles (LHDs), rock excavation equipment, and more. Recent acquisitions have enhanced Epiroc’s capabilities with technology, enabling real-time visualization of underground employees and mining vehicles on a digital global mining map. This new ability allows drivers to see what’s approaching, ultimately improving safety and efficiency. Epiroc also offers similar solutions for above-ground mining operations, all supported by private cellular networks.

The Ericsson-Epiroc partnership is already demonstrating how cellular networks can enhance the deployment and effectiveness of cutting-edge mining technologies:

Autonomous operations – Cellular networks elevate the performance of autonomous vehicles, such as Epiroc’s Pit Viper drill rigs, enabling synchronized operations in open-pit mines, through low-latency communication.

Advanced monitoring and safety – Cellular networks support extensive sensor networks throughout a mine, providing real-time data on everything from air quality to rock stability.  The high-bandwidth capabilities of cellular networks also allow for the creation of digital twins for remote monitoring.

Efficient resource management – Enhanced connectivity offers precise control of smart ventilation systems, optimizing energy consumption while ensuring a safe working environment.

NEXGEN SIMS: A glimpse at the future of mining

The potential of cellular networks in mining is perhaps best exemplified by the NEXGENS (Next Generation Sustainable Intelligent Mining System) project. This EU-funded initiative, led by Epiroc in collaboration with Ericsson and other global partners, aimed to create a mining system that significantly reduced greenhouse gas emissions and boost safety through advanced automation. During its three-year duration, Epiroc established a test facility in Sweden, where Ericsson Private 5G (EP5G) technology provided the communication backbone for a range of advanced applications.

One of the most challenging aspects of the project was the implementation of autonomous mine machinery in mixed-traffic scenarios—environments where autonomous machines, semi-autonomous equipment, conventional vehicles, and human workers must safely coexist.

The EP5G-based solution developed for NEXGEN SIMS met the stringent 24ms latency requirement for real-time safety-critical communication, a level of performance simply not possible with traditional Wi-Fi networks, underscoring the transformative potential of cellular technology in mining operations

A broad ecosystem amplifies innovation

While the Ericsson-Epiroc partnership is at the forefront of the cellular revolution in mining, it's part of a broader ecosystem driving innovation in the sector. Ericsson has fostered collaborations with various partners, including telecommunications providers and technology companies, to deploy cellular solutions in mines across Canada and Australia.

Fig 2. End to end mining connectivity ecosystem

These deployments have already yielded measurable productivity gains, proving the business value of cellular networks in mining. As more companies adopt these technologies, one could expect additional innovations and best practices to rapidly spread throughout the industry.  

What’s your vision for the mine of the future? The network is ready for you.

Looking ahead, advanced technologies will play a vital role to mining’s future. However, the successful implementation of these technologies will depend on having a robust, reliable and flexible communication infrastructure.

Private cellular networks, as demonstrated by the Ericsson-Epiroc partnership and projects like NEXGEN SIMS, provide this crucial foundation. By enabling seamless connectivity, high-bandwidth data transmission and ultra-low latency communication, these networks not only support current mining technologies but also enable the next generation of innovations.

For mining executives and engineers aiming to future-proof their operations, understanding and leveraging the potential of private cellular networks is undeniable. As the industry continues to evolve, those who effectively harness these technologies will be best positioned to lead in efficiency and safety.

Apr 02, 2024

Industry 4.0

Feb 22, 2024

Network Functions Virtualization (NFV)

Apr 10, 2024

Resilient 5G systems

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• Published: 19 June 2024

Why do patients with cancer die?

• Adrienne Boire   ORCID: orcid.org/0000-0002-9029-1248 1   na1 ,
• Katy Burke 2   na1 ,
• Thomas R. Cox   ORCID: orcid.org/0000-0001-9294-1745 3 , 4   na1 ,
• Theresa Guise 5   na1 ,
• Mariam Jamal-Hanjani 6 , 7 , 8   na1 ,
• Tobias Janowitz   ORCID: orcid.org/0000-0002-7820-3727 9 , 10   na1 ,
• Rosandra Kaplan 11   na1 ,
• Rebecca Lee   ORCID: orcid.org/0000-0003-2540-2009 12 , 13   na1 ,
• Charles Swanton   ORCID: orcid.org/0000-0002-4299-3018 7 , 8 , 14   na1 ,
• Matthew G. Vander Heiden   ORCID: orcid.org/0000-0002-6702-4192 15 , 16   na1 &
• Erik Sahai   ORCID: orcid.org/0000-0002-3932-5086 12   na1  

Nature Reviews Cancer volume  24 ,  pages 578–589 ( 2024 ) Cite this article

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Cancer is a major cause of global mortality, both in affluent countries and increasingly in developing nations. Many patients with cancer experience reduced life expectancy and have metastatic disease at the time of death. However, the more precise causes of mortality and patient deterioration before death remain poorly understood. This scarcity of information, particularly the lack of mechanistic insights, presents a challenge for the development of novel treatment strategies to improve the quality of, and potentially extend, life for patients with late-stage cancer. In addition, earlier deployment of existing strategies to prolong quality of life is highly desirable. In this Roadmap, we review the proximal causes of mortality in patients with cancer and discuss current knowledge about the interconnections between mechanisms that contribute to mortality, before finally proposing new and improved avenues for data collection, research and the development of treatment strategies that may improve quality of life for patients.

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Causes of death among people living with metastatic cancer

Deceptive measures of progress in the NHS long-term plan for cancer: case-based vs. population-based measures

Changes in long term survival after diagnosis with common hematologic malignancies in the early 21st century

Introduction.

The phrase ‘metastasis accounts for 90% of cancer deaths’ is one of the most widely used in cancer research, yet it is overly simplistic, imprecise and it is difficult to find any primary analysis supporting the statement. Although patients with metastatic disease are overwhelmingly more likely to die than patients with non-metastatic cancer 1 , 2 , the determinants of cancer mortality are multifaceted and frequently involve dysfunction of multiple interconnected systems within the body. Understanding the mechanisms underpinning the causes of mortality, and subsequently intervening, has the potential to make cancer a less destructive disease, improving both the quality and length of life for patients with cancer. However, systematic analyses of the acute and root causes of mortality in patients with cancer are scarce, in part because death certificates rarely record enough information to understand the exact reason why the patient died beyond them having a malignancy. Causes of death may be simply listed as ‘metastatic carcinoma’ or ‘complications of cancer’, which give little insights into why a patient actually died. Potentially concomitant comorbidities are also not fully recorded. Even in cases in which the cause of death may be attributed to a single event, for example, a  thromboembolism , the underlying cause of that specific event may be complex. Indeed, metastatic cancer leads to perturbed function of multiple organ systems, and importantly, not just the organs to which disease has spread. This is probably due to the exuberant activation of local and systemic inflammatory, tissue repair and immune-suppressive programmes.

A simple view would be that death from metastatic disease correlates with the burden of disease. However, evidence suggests that the situation is more complex, with many factors influencing how metastases impact vital functions and ultimately lead to death. First, metastases to different organs will lead to different impacts on overall health. For example, brain metastases can lead to dysfunction of the central nervous system 3 , whereas peritoneal metastases may cause obstruction of the bowel 4 . In addition, the size or extent of metastases may not necessarily correlate with dysfunction of the organ where it is located 5 . Second, the production of the molecular mediators of organ dysfunction can vary between metastases and cancers of different origins. Third, individual patient characteristics such as age, sex, overall health, pre-existing comorbidities, genetics and socio-economic status vary 6 . Together, these factors directly influence the course of and physiological response to metastatic disease and can have profound indirect effects by limiting available treatment options and/or the ability of patients to tolerate or complete all intended treatment 7 , 8 . To understand why patients with cancer die, a closer examination of the factors contributing to mortality in patients with cancer and a dissection of the intricate web of causes that shape the frequency and dynamics of death are required.

Death may be related to an acute event, but the underlying mechanisms which trigger it may be modifiable or even preventable. In addition, other deaths may be the end stage of a continuum of deterioration, allowing the possibility of targeted intervention to improve quality of life. Moreover, it has been noted that early palliative care improves survival 9 . Ultimately, increased understanding of the processes occurring in patients with advanced disease should lead to improved strategies to minimize ill-health and suffering at the end of life. Coupled to this, patients and those around them should be enabled to have essential discussions about their wishes and preferences, minimizing potentially inappropriate treatments and maximizing quality of life 10 . Therefore, in this Roadmap, we briefly review data considering the immediate causes of mortality, highlight the intricate interconnections between different aspects of patient deterioration and conclude with recommendations for future studies of late-stage cancer that may shed new light on this important aspect of cancer biology and medicine.

Acute events leading to mortality

Although some cancers can be considered a chronic condition, with many patients living with their disease for years, the immediate cause of mortality can often be an acute event. Here, we briefly summarize common acute events leading to death in patients with cancer (Fig.  1 ). Although it is not possible to precisely determine, it is likely that the acute causes discussed subsequently may account for up to half of cancer deaths 11 , 12 . Immediate causes of mortality in other patients are less clear, with a more gradual deterioration typically occurring in vital organ systems (Fig.  1 ).

This schematic shows organs that frequently become dysfunctional in patients with late-stage cancer.

Vascular coagulation and cardiac failure

Patients with cancer are at an elevated risk of thromboembolism, which may trigger respiratory failure, fatal strokes, heart failure or myocardial infarction 13 . In some cases, disseminated intravascular coagulation can lead to thrombotic obstruction of small and midsize vessels leading to organ failure 14 . Haemorrhagic complications from depletion of platelets, via either immune or non-immune mechanisms 15 , 16 , and reduced levels of coagulation proteins can also be life-threatening 14 .  Congestive heart failure can also be a proximal cause of mortality, although the underlying causes are complex and include loss of cardiac muscle (associated with cachexia), shifts in intravascular fluid status and thromboembolic events 17 . Interestingly, bone metastases are particularly associated with cardiovascular problems, although the underlying mechanism remains unclear 18 . Comorbidities affecting the cardiovascular system may also make patients more prone to such events. Spatial occlusion of or invasion into vessels by cancer metastases can also lead to failure in blood supply or catastrophic haemorrhage 19 , 20 , 21 , 22 .

Displacement, functional impairment or obstruction of vital organs

The volume of disease may impair the function of a vital organ. This can be the case with brain metastases and glioblastoma or other primary brain cancers, with extensive invasion, brain herniation or oedema resulting in  midline shift or increased intracranial pressure irreversibly compromising brain function 22 , 23 , 24 . In addition, patients may develop seizures, which, if uncontrolled, can result in death 25 , 26 . However, this does not apply to all brain metastases, with  leptomeningeal metastases having minimal impact on intracranial pressure and brain structure; instead, these commonly obstruct cerebrospinal fluid flow and/or affect nerve function resulting in  hydrocephalus , deterioration of neurological function and death 26 .

Large lung metastases may impair the essential function of gas exchange. However, patients with miliary-like disease — characterized by nodules too numerous to count — can live with extensive disease in an organ with surprisingly little impact on function until a hard-to-predict tipping point is reached, which is then followed by rapid deterioration 27 . As with brain metastases, the volume of disease is often not sufficient to account for organ failure, as even a relatively small volume (<100 ml lung metastases volume compared with 4–5 l total lung volume) can be fatal 28 .  Lung oedema and pleural effusion are additional common contributors to death. Oedema may be caused by other pathologies such as infection or heart failure, whereas pleural effusion may be related to the presence of disease within the pleura as opposed to total tumour volume 28 , 29 .

Bowel obstruction can be a cause of mortality, especially in patients with peritoneal disease as found in particular in ovarian, colorectal and gastrointestinal cancers 30 . Both liver and kidney failure will also cause death in patients with cancer. Reasons for the failure of these organs include obstruction of the bile duct or ureters by metastases, therapy-induced toxicity leading to compromised normal organ function (discussed subsequently) and reduced tissue perfusion owing to hypotension or dehydration 31 , 32 , 33 , 34 . In addition, sepsis can result from obstruction of the bile ducts or ureters, which occurs unpredictably and often progresses rapidly leading to multiple organ failure and ultimately death.

Bacterial infections are the most common infection in patients with cancer, owing to impaired immune systems resulting from both the cancer itself and certain cancer treatments (discussed in detail subsequently), which induce myelosuppression and leukopenia. Patients with cancer can have an elevated risk of opportunistic viral, fungal and protozoal infections, which would typically be considered mild in healthy individuals, but which can cause serious life-threatening complications in those with cancer. Pneumonia and other lung infections leading to respiratory failure are often listed as causes of mortality in patients with cancer 35 , 36 . One of the most striking recent examples of this is the increased mortality observed in patients with cancer, particularly those with haematological cancers, who succumbed to COVID-19 compared with the general population 36 , 37 .

Paraneoplastic syndromes

Paraneoplastic syndromes are a group of rare disorders that can occasionally cause irreversible damage to critical organs and death. They are most associated with lung, breast, ovarian and lymphatic cancers, causing tissue or organ dysfunction at sites distinct from the location of the tumour 38 . Various mechanisms underpin paraneoplastic syndromes, including the inappropriate production of cytokines, hormones and antibodies. For example, excess parathyroid hormone-related protein (PTHRP) production by tumours can lead to hypercalcaemia 39 , 40 . Inappropriate anti-diuretic hormone production is commonly associated with small-cell lung cancer resulting in  hyponatraemia 41 . Furthermore, some neuroendocrine pancreatic tumours (insulinomas) secrete large amounts of insulin 42 . Tumours can also trigger the aberrant production of autoantibodies leading to disorders such as  Lambert–Eaton myasthenic syndrome (LEMS) or anti- N -methyl- d -aspartate receptor (NMDAR) encephalitis and myasthenia gravis 43 . Although treatment can usually manage the symptoms, in a subset of cases the syndromes cannot be controlled and are fatal 38 .

Therapy-induced toxicity

Although therapies are developed and administered with the intent of primarily targeting the tumour, almost all have some detrimental impact on normal tissue function. In some cases, the unintended consequences of therapy can be life-threatening. Autoimmune reactions resulting from targeting immune checkpoints can have fatal consequences, including  myocarditis and encephalitis 44 , 45 , 46 . Chemotherapy can lead to death as a result of acute neutropenic sepsis 47 . Depletion of platelets because of therapy can lead to fatal bleeding 16 . Arrhythmias, cardiomyopathy and coronary vasospasm are also a cause of death related to some anticancer treatments such as 5-fluorouracil and capecitabine 48 , 49 , 50 . The long-term detrimental effects of some therapies are discussed in detail subsequently.

Underlying causes

Determination of the proximal cause of mortality prompts further questions around the underlying factors giving rise to lethal pathology and ultimately how metastatic cancer triggers or accelerates those factors. In this section, we consider how chronic disruption of three major physiological organ systems is perturbed in patients with cancer and how these might contribute to mortality.

The immune and haematopoietic systems

In patients with cancer, the immune system becomes progressively less able to mount effective responses to infectious challenge, a phenomenon often generically termed ‘immune exhaustion’ (this usage is distinct from the more specific usage of immune exhaustion as a failure of tumour-reactive T cells to function). As a result, patients with metastatic disease have increased susceptibility to a wide range of infections and typically suffer more severe consequences than would otherwise be observed in healthy individuals 51 . Multiple mechanisms contribute to the reduced capability of the immune system to respond to infection. The presence of cancer cells in diverse organs triggers similar cellular and molecular events to wound responses 52 . The production of cytokines including interleukin 6 (IL-6), granulocyte colony-stimulating factor (GCSF) and granulocyte–macrophage colony-stimulating factor (GM–CSF), both by tumour cells and by other cells of the tumour microenvironment (TME), perturbs haematopoiesis leading to altered subsets of leukocytes 53 . Although, in the short term, this may have limited consequences on the ability of the body to respond to other challenges, prolonged disruption to haematopoiesis can strain the ability of haematopoietic stem cells (HSCs) to generate sufficient cells of the right type to cope with infections, with increased myeloid-to-lymphoid cell ratios.  Clonal haematopoiesis can be increased in patients with cancer, with myeloid skewing of immune cells and overall myeloid-mediated immune suppression and diminished naive T cell reservoirs 53 . Reduced production of platelets and altered iron metabolism leading to compromised oxygen carrying by red blood cells is also observed in many patients 54 . Other problems such as  immunoparesis can arise, with a high frequency observed in patients with multiple myeloma 55 .

T cell responses to infection are impaired in the presence of cancer with decreased proliferation and expression of granzyme B typically observed 56 . The chronic stimulation of T cells with neoantigens arising from ongoing mutational processes may also contribute to their weakened functionality. Moreover, immune surveillance of tumours inevitably selects for the production of immune suppressive factors by cancer cells, which further compound the issue 57 . Once again, comorbidities leading to either immune suppression or autoimmunity can intersect with the detrimental effects of cancer on the immune system.

Other consequences of cancer can indirectly result in an increased likelihood of infection. For example, vessel obstruction from cancer results in decreased flow of fluids such as bile, urine and lymph, creating environments in which bacteria can thrive 58 . Blockage of the bronchial tree can lead to pneumonia 59 . The invasive phenotype of cancer can result in  fistula formation (for example, rectovaginal in colorectal cancer), which enables bacteria to invade 60 . Furthermore, patients are often rendered bedbound or have limited mobility as cancer progresses, resulting in an increased chance of infections through decreased respiratory ventilation and atelectasis , as well as pressure sores and oedema 61 .

Disruption to haematopoiesis can also contribute to defects in coagulation and haemostasis . Elevated platelet numbers, termed thrombocytosis, are found in patients with cancer and are correlated with higher mortality 62 . The altered inflammatory cytokine milieu caused by the tumour may promote megakaryopoiesis, potentially through increasing thrombopoietin (TPO) production by the liver, and leading to higher platelet numbers. The risk of clotting can be further increased by the production of  tissue factor , which is responsible for initiating the clotting cascade, by tumour cells 63 . These mechanisms increase the likelihood of fatal thromboembolisms 63 .

Iatrogenic effects also have a role in the reduced immune function in patients with cancer. Cytotoxic therapies interfere with the proliferation and division of haematopoietic stem cells and can leave the immune system unable to mount effective responses to pathogens, leading to mortality 64 . In severe cases, pancytopenia results, marked by a substantial decrease in all three major blood cell lineages (red cells, white cells and platelets) 65 . This can lead to severe anaemia, increased infection susceptibility and increased likelihood of bleeding 47 , 66 , 67 . In other cases, more limited subsets of haematopoietic cells are affected. Thrombocytopenia — low platelet levels — leads to hypocoagulation and elevates the likelihood of haemorrhage 66 . Therefore, during cancer development and treatment, haemostasis mechanisms may be either augmented or attenuated; in both cases, the result is less predictable and less well-controlled coagulation. Neutropenia — low neutrophil levels — renders patients less able to fight infection and contributes to cancer mortality from infections that in many cases are thought to arise from resident mucosal flora 68 . Treatments, including chemotherapy and radiotherapy, often result in the breakdown of mucosal barriers (for example, oral mucositis) resulting in higher numbers of infections from pathogens, which normally reside on these surfaces 69 . In addition, corticosteroids, which are often given to alleviate symptoms or manage toxicity, can also contribute to the suppression of immune responses and compound the risk of infections in patients 70 . Clonal haematopoiesis, which as mentioned earlier is already more frequent in patients with cancer, can be further increased by chemotherapy 71 . More generally, cancer therapies can increase ageing-associated processes and reduce organ function 72 . Opioid pain relief administered to those with late-stage disease can also suppress the function of various bodily systems 73 . Finally, infections can arise owing to the insertion of drains and stents, or central venous catheters (CVCs; also known as lines) for the delivery of therapies. Infections from such lines are estimated to be around 0.5–10 per 1,000 CVC-days 74 , 75 .

Immunotherapies present a different set of immune complications from conventional therapies. These primarily relate to over-activation of the immune system leading to autoimmunity and, in some cases, cytokine storms that are treated with anti-cytokine therapies such as tocilizumab, anakinra and ruxilitinib, all of which can further suppress the immune response 76 . However, deaths attributable to autoimmune side effects of immune checkpoint inhibitors are rare (<1% in an analysis of more than 8,000 patients) especially if toxicity is managed promptly 77 , 78 . Colitis is a frequent problem, with disruption to colonic barrier function leading to increased susceptibility to perforation, which can be life-threatening.  Guillain–Barré syndrome , hepatitis and myocarditis are also causes of immune checkpoint inhibitor-related deaths 79 , 80 , 81 . Once again, high-dose corticosteroids are the main first-line treatment to manage autoimmune side effects in patients receiving immunotherapy and can lead to suppression of the immune system.  Hyperprogressive disease is observed in some patients following immunotherapy, the reasons for which are still being delineated, but there is probably a role for innate lymphoid cells releasing pro-growth cytokines 82 . Cell-based immunotherapies can also lead to disrupted bone marrow function and subsequent myelosuppression 83 .

The nervous system

The brain serves as a central nexus, orchestrating all vital functions. It is the hub of thought processes, emotions and sensory perception and regulates, directly or indirectly, everything from heartbeat and breathing to appetite. In addition to physical disruption of brain structure and intracranial pressure (discussed earlier) 84 , brain metastases impact the nervous system in multiple ways. Tumours in the brain or its surrounding tissues can substantially impair neural connections, leading to cognitive deficits, motor and sensory dysfunction, and even personality changes 84 , 85 , 86 . Interactions between brain metastases and neurons lead to changes in cortical function 87 , 88 , 89 . Even in regions of the brain without overt metastases, neuro-excitability can be increased, leading to changes in cognition, alertness and mood 90 . Tumours can slow the posterior dominant rhythm, leading to reduced alertness, loss of working memory and deterioration of quality of life 91 . Circadian rhythms are also impacted, leading to problems in memory and sleep, which is vital for the repair processes of the body that are essential for overall health and functioning 92 . Ultimately, many of these changes are not sustainable long-term. How these changes may lead to death is unclear, but they may follow similar trajectories to those in patients with dementia.

Brain function can also be disrupted in patients without brain metastases, with autonomic nervous system dysfunction often reported 93 . Intriguingly, anhedonia — a lack of ability to experience pleasure — occurs in many patients 94 . The mechanistic causes of this are unclear, but it is not restricted to patients with brain metastasis suggesting that circulating systemic factors may play a role. The wider effects of metastatic cancer on the mental well-being of a patient are discussed in Box  1 . However, beyond an effect on well-being, the disruption of brain function can contribute to anorexia, and reduced nutrition can influence many other physiological and pathophysiological processes 95 , 96 .

The role of the  peripheral nervous system in cancer-related death is not well described. Although the burgeoning field of cancer neuroscience provides evidence that the efferent system can support local and metastatic tumour growth 97 , 98 , 99 , at this time, it is unclear whether the reverse is also true. As mentioned earlier, there is clear evidence of autonomic nervous system dysfunction in patients with cancer 93 , raising the possibility that cancer-mediated interruption of afferent impulses might impact overall survival. Further studies are needed to explore this possibility.

Box 1 Psychosocial and societal factors contributing to the deterioration of patients with late-stage cancer

Psychological and social factors can have major and wide-ranging impacts on patients with incurable cancer. This manifests in more than threefold higher suicide rates 145 , 146 , 147 . Of note, these rates were further exacerbated in less advantaged sociodemographic groups 148 , arguing that financial issues and possibly health-care access are linked to suicide in patients with cancer. However, psychological symptoms are far more extensive than those captured in studies of suicide. Anhedonia and depression are frequent in patients with cancer, impacting their overall well-being, treatment adherence and outcomes including mortality 149 . These psychological challenges often intertwine with physical symptoms, compounding the burden of each 150 . Several studies have linked stress-related psychosocial factors to cancer mortality 151 , with recent work beginning to uncover the cellular and molecular mechanisms at play 152 .

Research on the psychosocial aspects of cancer care, including emotional and cognitive well-being, remains under-emphasized. Barriers to the integration of psychosocial care into cancer care include stigma, difficulty identifying substantial distress, limited access to evidence-based psychosocial treatments and concerns about cost 153 . Yet, an integrated system of psychosocial care including population-based screening and targeted treatment and access to good-quality palliative care improves emotional wellbeing 154 and physical symptoms 155 and is likely to be cost-saving 156 . A deeper understanding of the mechanisms underlying neuropsychological systems and insights into how metastatic disease impacts the physiological and chemical axes of the brain will be crucial. Such insights could inform tailored interventions, therapies and support structures that address the emotional toll of cancer, enhancing the holistic care approach and improving quality of life. Expanding psychosocial research can help bridge gaps in addressing mental health in patients with cancer, ultimately improving quality of life of patients during and after treatment 146 , 147 .

Metabolism and cachexia — catabolic effects of cancer

The presence of metastases presents altered energetic and anabolic demands on the body, leading to detrimental imbalances in metabolism 100 . Progressive and involuntary loss of body weight — termed cachexia — is a widespread multiorgan phenomenon commonly seen in patients with metastatic cancer 100 , 101 . This complex syndrome is characterized by a net negative energy balance, driven by the combination of increased energy expenditure and catabolism, with reduced appetite and caloric intake. A persistent decrease in nutrient intake is a key component across patients with many different cancer types, leading to breakdown of host tissues, with the degree of loss of adipose tissue and muscle mass varying between patients and among different cancer types 102 . However, the contribution of increased energy expenditure (as a result of tumour burden) is less clear.  Sarcopenia may be particularly prominent in some patients, possibly representing an independent pathology from other more global tissue wasting phenotypes, and in extreme cases, loss of cardiac or intercostal muscle mass can be fatal owing to insufficient cardiac or respiratory function, respectively 103 , 104 . These events have also been observed in the context of extreme starvation in patients with non-cancer conditions; for example, anorexia nervosa, in which cardiac dysfunction, in particular bradycardia and sinus pauses, can cause pulseless electrical activity and death 105 , 106 . Electrolyte disturbances and hypoglycaemia that are often observed in cases of severe malnutrition may exacerbate the risk of such arrhythmias 105 . Cachexia also has effects on other organs and tissues, including the brain and immune system 107 . Compromised immune function is a major consequence of starvation-induced tissue wasting 108 and suggests that altered systemic metabolism leading to, or associated with cachexia, may be a contributor to the immune dysfunction present in some patients with cancer 108 . Conversely, several studies have shown that both the brain and immune system can contribute to cachexia 100 , 101 .

Cachexia is multifactorial and has many potential causes. In some limited cases, tumour metabolism leads to systemic changes that increase energy usage. For example, high levels of lactate secretion by tumours can trigger the liver to convert lactate back to glucose, which requires energy input — termed the Cori cycle 109 . Such cycles can increase metabolic demand on the liver leading to further perturbation of liver function. However, cachexia does not correlate with disease volume in many cancer types 110 . Therefore, it is hard to reconcile a model in which the energetic and anabolic demands of the volume of disease are the main trigger for cachexia. Numerous studies have begun to reveal the possible molecular underpinnings of cachexia in some cancer types. Disruption of signalling by transforming growth factor-β (TGFβ) and related ligands is a recurring theme 111 , 112 , 113 . For example, circulating growth/differentiation factor 15 (GDF15; also known as MIC1), a highly conserved member of the TGFβ superfamily, is a known mediator of anorexia and weight loss, and increased circulating levels of this molecule in patients with lung cancer have been shown to correlate with cachexia development 114 . Clinical trials are currently underway to determine whether blockade of GDF15 ameliorates cachexia 115 . TGFβ itself can also promote muscle loss via the induction of myostatin 116 , and the induction of signalling by activin — another TGFβ superfamily ligand — can also have similar effects on muscle mass 117 , 118 . Furthermore, modulation of ryanodine receptor 1 (RYR1) downstream of TGFβ can perturb sarcomere organization and thereby lead to muscle weakness 111 . As such, preclinical studies have demonstrated the potential utility of TGFβ blockade in preventing cachexia 112 .

Elevated levels of cytokines, including tumour necrosis factor (TNF), IL-1 and IL-6, can also have roles in cachexia 119 , 120 , 121 . TNF induces multiple aspects of cachexia 122 . Muscle wasting is promoted through increased TNF and downstream nuclear factor-κB (NF-κB)-dependent ubiquitin-mediated proteolysis of muscle protein 123 , 124 . IL-6 triggers muscle loss through both NF-κB-dependent and JAK/STAT-dependent mechanisms 120 . Lipid metabolism is impacted by TNF reducing the expression of lipoprotein lipase and free fatty acid transporters, thereby reducing the accumulation of fat 125 . TNF can also reduce appetite through the production of  corticotropin-releasing hormone (CRH). IL-1, which triggers similar proximal changes in cell signalling to TNF, can activate many of the same processes 125 . It is also interesting to note that TGFβ, IL-1 and IL-6 are associated with programmes in cancer cells that drive metastasis, which could potentially explain why metastatic disease is linked to cachexia more strongly than the presence of primary disease alone.

Whole body dysfunction

Although consideration of different organ systems is useful for highlighting some of the key events contributing to cancer mortality, the interconnected nature of body systems and the pleiotropic characteristics of the molecular mediators at play mean that it is essential to consider whole body dysfunction when thinking about causes of cancer mortality. Furthermore, such analyses may explain cancer deaths without an acute proximal cause. As discussed earlier, cytokines with potent effects on the immune system, as well as effects on appetite, can be contributors to cachexia. Therefore, it is unsurprising that tumours impact both immune and metabolic function. The immune and nervous systems are highly sensitive to metabolite availability; for example, the brain has a high demand for glucose 108 , 126 . Several factors, including lactic acid production and kidney dysfunction, can lead to life-threatening systemic acidosis in patients with cancer, particularly haematological malignancies with high cell turnover 127 . These can be further exacerbated upon initiation of cytotoxic therapy resulting in  tumour lysis syndrome which can be fatal 128 . Consequently, metabolic perturbations and cachexia impact these systems. Over time, the cumulative stress of metabolic alterations caused by metastases, chronic changes in the level of cytokines, constant generation of tumour (neo)-antigens, aggressive therapies and incidental infections lead to exhaustion of the adaptive immune system and hamper the regenerative capacity of many organ systems with debilitating effects 18 . This multifaceted burden can ultimately trigger a body-wide shutdown leading to death.

Are mortality causes cancer-specific?

Although a subset of mortality causes are cancer-specific, such as metastatic invasion compromising specific organ function, the progressive and interconnected deterioration of multiple organ systems probably underlies many cancer-related deaths. This may be further influenced by interaction with other comorbidities. Of note, similar progressive deterioration is sometimes observed in the context of chronic infection and inflammation, with both cachexia and immune exhaustion associated with diseases such as tuberculosis (TB) and human immunodeficiency virus (HIV) infection 129 , 130 , 131 . This raises the question of whether the causes of death in patients with cancer are specific to cancer, or whether cancer (or any other chronic disease) is simply an accelerant of ageing processes occurring in healthy individuals. This hypothesis has practical implications because, if proven, it would suggest that lessons and approaches from other disease contexts could be readily transferable to patients with metastatic cancer. For example, the targeting or modulation of senescent cells is an active area of anti-ageing research, and numerous preclinical studies have indicated that similar strategies can attenuate the systemic effects of cancer 132 , 133 , 134 .

Recommendations

One goal of this Roadmap is to propose ways to improve our understanding of why patients with cancer die and thereby develop better strategies to ameliorate symptoms and prolong life with good quality. To this end, we propose that the following steps would be useful (Fig. 2 ).

This scheme shows how recommendations can interlink to provide both an improved understanding of the underlying biology behind late-stage cancer and strategies to improve quality of life of patients.

Improved records and reporting

It is notable that systematic reviews of the precise causes of cancer mortality are infrequent. This gap in knowledge, and recognition that this is often simply not known, is a major hindrance to learning and progress. Although improved accuracy of reporting on death certificates would be desirable, it would require a shift in longstanding clinical habits and may not be easily achievable in health-care systems under strain. Nonetheless, we advocate for locally enacting more consistency in death certificates, with specific acute causes included in addition to the underlying cause of cancer where known. Palliative care primarily focuses on symptom control for patients while balancing the potential benefits and burdens of additional diagnoses. Nevertheless, to address the gaps in our knowledge, it would be desirable to fund and establish prospective studies that continue active monitoring of patients as they transition from active disease treatment to palliative care. If possible, monitoring should be non-invasive as to not compromise patient comfort at the end of life. The great advances being made in patient monitoring with  wearable technologies might facilitate this and could be used for earlier detection of infections enabling quicker intervention. Caregiver involvement in reporting of symptoms may also play a role. Furthermore, consent to obtain more detailed information from the community and palliative care teams on the contributing factors to death would provide further insight. Patient and public engagement in this type of research will be critical, with studies indicating patient desire to participate in the right context 135 , 136 . In addition to information gathered before death, research autopsies have the potential to shed further light on the aetiology of death, such as thromboembolic events that may not have been detected in the absence of symptoms or diagnostic testing — discussed in Box  2 . Moreover, the availability of post-mortem samples can aid research into the biological underpinnings of metastases and processes leading to death. The greatest amount of information would be gained from cohorts additionally enrolled into warm autopsy programmes (Box  2 ).

Box 2 Research Autopsy Programmes and their optimization

Research autopsies are initiatives that involve the prompt collection of tissues from deceased individuals shortly after death, whereas tissue morphology is intact, and cells and tissues have not undergone substantial post-mortem changes. Research autopsy studies can be labour-intensive, and care is required in their logistical planning. The post-mortem interval (PMI) to autopsy can vary depending on the infrastructure available and can have implications for the utility of samples collected after death. For example, shorter PMIs achieved in rapid warm autopsy studies can more effectively facilitate in vitro (for example, cell line) and in vivo (for example, organoid and xenograft) models and can derive better quality RNA 157 , 158 . However, such studies are not easily established in the absence of out-of-hours facilities and expert input. Autopsies performed with longer PMIs, for example, up to several days after death, have been shown to have maintained tissue morphology and adequate DNA and RNA to facilitate cellular imaging techniques and genomic sequencing approaches 159 , 160 . Therefore, there is merit and general scientific value with autopsies regardless of the PMI, provided that consideration is given to the question being addressed, and the experimental approach.

The most powerful data are obtained from patients already involved in clinical studies before death. Information about disease course, longitudinal scans and tissue and blood analysis (cell counts, electrolytes, cytokines, metabolites and possibly circulating tumour DNA (ctDNA)) greatly enhances what can be learnt from post-mortem tissues. However, sensitivity is required to align the desire to acquire data with the wishes of the patients and their families, such that ultimately each autopsy has the potential to be meaningful and shed light on the biological processes leading to death.

More detailed observational clinical studies

Disease burden is not well correlated with survival; however, we propose that the accurate identification of prognostic factors correlating with survival should provide important insights into what ultimately precipitates mortality. As the cost of both targeted and non-targeted analyses of proteins and metabolites decreases, it should also become more feasible to explore molecular predictors of survival. Once identified, such factors could then be monitored in a targeted way prospectively with the potential to intervene where possible. In this setting, both the tumour and patient trajectory would receive precision-tailored treatments, the impact of which would need to be studied in randomized controlled trials. Even in the context of early phase trials, additional data could be obtained about patient symptoms in addition to safety considerations and tumour burden. Clinical imaging could also be exploited. Many patients receive computed tomography (CT) and positron-emission tomography (PET) scans, which contain abundant information about the burden and location of metastases and offer the opportunity to study changes in extent of adipose and muscle tissue and therefore body composition in relation to cachexia. Machine learning and artificial intelligence can be capitalized on to accurately measure these parameters, meaning that what would have previously been prohibitive owing to hours of radiologist time being required is now feasible 137 , 138 . In addition to the analysis of scans, the application of machine-learning approaches to metabolite, cytokine, immune cell and wearable technology-derived multimodal and multidimensional data may also uncover previously unknown parameters that correlate with mortality 139 . As outlined in Box  1 , incorporating psychosocial metrics into the study of late-stage cancer could also enable improvements in mental well-being of patients.

Increasing the relevance of model systems

Preclinical models will also have a place in determining the linkage between events found to precede death and cause of death; however, there should be an emphasis on reverse translation of questions from human studies to preclinical models. By way of example, this could involve modelling how metastases impinge on the ability of the body to respond to infection by challenging metastatic mouse models with a pathogen. Animal ethics and husbandry considerations mean that mice are housed in controlled environments in which exposure to pathogens is rare and the types of pathogen exposure are very narrow, so this type of information is currently lacking. To be optimally informative, practical and ethical complications around studying end-of-life physiology seen in patients need to be considered. Most models are chosen for their rapid progression, often with less than a month between primary or metastatic tumour seeding and death. These are not optimal for studying longer timescale chronic changes in patients. The development of slower progressing models, implementation of multiple lines of treatment and mimicking presence of other comorbidities should enable models to more accurately recapitulate observations made in patients. Furthermore, most preclinical cancer research currently uses young mice that fail to accurately mirror the interplay between ageing and cancer seen in humans 140 , with differences between chronological and immunological age providing a further confounding factor 141 . Researchers need to recognize the importance of and adopt more age-appropriate mouse models to better understand cancer mortality. In addition, most studies focus solely on tumour burden (which may only be possible at the point of death rather than longitudinally) or tumour size as a marker of disease, owing to the technical challenges of accurately quantifying organ impairment. Furthermore, tumour volume response and progression are poor surrogates of mortality in patients 142 ; therefore, better modelling of other metrics of tumour activity and impact on the body system may lead to better drug development. Minimizing and alleviating suffering in experimental animals is critical; hence ethical considerations limit the ability to study mortality in mice. Therefore, an expanded repertoire of analysis would help to understand how metastases impact specific systems and events, including the haematopoietic and nervous systems, as well as whole-body physiology and metabolism. Analysis of small volumes of blood can provide data on metabolites and cytokines, as well as complete blood counts (red blood cells, white blood cells and platelets), whereas increasingly sophisticated and automated technology is available to monitor mouse behaviour 143 . It is worth noting that weight loss is frequently used as a humane end point, which indicates that many cancer models trigger cachexia and that with appropriate measurements there is an opportunity to learn more about this phenomenon in existing models. We advocate more detailed reporting of why mice were culled in experimental studies — for example, tumour volume, weight loss, laboured breathing, complete blood cell counts and blood chemistry.

Clinical trials

The types of analyses detailed earlier will provide correlation between different factors and mortality, but not causative linkage. Ultimately, this information depends on testing in the context of clinical trials. Many of the mediators of immune dysfunction and cachexia can now be targeted with function blocking antibodies or forms of receptor traps and are being actively explored in clinical trials 115 , 144 . Several of these interventions were originally developed for chronic inflammatory conditions, which further highlights links between cancer and inflammation. The use of appropriately chosen secondary end points would provide an opportunity for testing whether correlative associations have a causal basis. In addition, many cancer drug trials stop providing an intervention at the point where a cancer progresses. The mechanisms behind cancer cachexia suggest that trials should be adapted to additionally consider clinical benefit in terms of weight, muscle loss and other specific determinants of efficacy, rather than solely monitor cancer progression.

Concluding remarks

Although efforts at cancer prevention and the development of curative treatment rightly receive considerable attention, we argue that understanding the precise events leading to cancer mortality should not be overlooked by funding bodies. Understanding the causes of dysfunction across multiple organ systems may provide novel strategies to manage symptoms of advanced cancer. Furthermore, better knowledge of the processes leading to death could enable patients and those around them to have essential discussions about their wishes and preferences, minimizing potentially inappropriate treatments and maximizing quality and enjoyment of life. In addition, more precise biomarkers of the likely timing of death may enable patients and their families to better utilize the time that is left. In the longer term, strategies to prevent organ dysfunction should offer considerable benefits to both patients with high tumour burden and those who have low disease burden but die from factors produced by cancer.

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Acknowledgements

A.B. is funded by National Institutes of Health/National Cancer Institute P30 CA008748 and R01-CA245499. K.B. is employed by the UK National Health Service. T.R.C. acknowledges funding support from the National Health and Medical Research Council (NHMRC) Ideas (2000937), Project (1129766, 1140125), Development (2013881) and Fellowship (1158590) schemes, a Cancer Institute NSW Career Development Fellowship (CDF171105), Cancer Council NSW project support (RG19-09, RG23-11) and Susan G. Komen for the Cure (CCR17483294). T.G. is funded by the Cancer Prevention and Research Institute of Texas Grant 00011633. M.J.-H. has received funding from CRUK, NIH National Cancer Institute, IASLC International Lung Cancer Foundation, Lung Cancer Research Foundation, Rosetrees Trust, UKI NETs and NIHR. T.J. acknowledges funding from Cancer Grand Challenges (NIH: 1OT2CA278690-01; CRUK: CGCATF-2021/100019), the Mark Foundation for Cancer Research (20-028-EDV), the Osprey Foundation, Fortune Footwear, Cold Spring Harbour Laboratory (CSHL) and developmental funds from CSHL Cancer Center Support Grant 5P30CA045508. R.K. is funded by the Intramural Research Program, the National Cancer Institute, NIH Clinical Center and the National Institutes of Health (NIH NCI ZIABC011332-06 and NIH NCI ZIABC011334-10). R.L. is supported by a Wellcome Early Career Investigator Award (225724/Z/22/Z). E.S. is supported by the Francis Crick Institute, which receives its core funding from Cancer Research UK (CC2040), the UK Medical Research Council (CC2040) and the Wellcome Trust (CC2040) and the European Research Council (ERC Advanced Grant CAN_ORGANISE, Grant agreement number 101019366). E.S. reports personal grants from Mark Foundation and the European Research Council. C.S. is a Royal Society Napier Research Professor (RSRP\R\210001). His work is supported by the Francis Crick Institute that receives its core funding from Cancer Research UK (CC2041), the UK Medical Research Council (CC2041) and the Wellcome Trust (CC2041) and the European Research Council under the European Union’s Horizon 2020 research and innovation programme (ERC Advanced Grant PROTEUS Grant agreement number 835297). M.G.V.H. reports support from the Lustgarten Foundation, the MIT Center for Precision Cancer Medicine, the Ludwig Center at MIT and NIH grants R35 CA242379 and P30 CA1405141.

Author information

These authors contributed equally: Adrienne Boire, Katy Burke, Thomas R. Cox, Theresa Guise, Mariam Jamal-Hanjani, Tobias Janowitz, Rosandra Kaplan, Rebecca Lee, Charles Swanton, Matthew G. Vander Heiden, Erik Sahai.

Authors and Affiliations

Memorial Sloan Kettering Cancer Center, New York, NY, USA

Adrienne Boire

University College London Hospitals NHS Foundation Trust and Central and North West London NHS Foundation Trust Palliative Care Team, London, UK

Cancer Ecosystems Program, The Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia

Thomas R. Cox

School of Clinical Medicine, St Vincent’s Healthcare Clinical Campus, UNSW Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia

Department of Endocrine Neoplasia and Hormonal Disorders, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

Theresa Guise

Cancer Metastasis Laboratory, University College London Cancer Institute, London, UK

Mariam Jamal-Hanjani

Department of Oncology, University College London Hospitals, London, UK

Mariam Jamal-Hanjani & Charles Swanton

Cancer Research UK Lung Centre of Excellence, University College London Cancer Institute, London, UK

Cold Spring Harbour Laboratory, Cold Spring Harbour, New York, NY, USA

Tobias Janowitz

Northwell Health Cancer Institute, New York, NY, USA

Paediatric Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA

Rosandra Kaplan

Tumour Cell Biology Laboratory, The Francis Crick Institute, London, UK

Rebecca Lee & Erik Sahai

Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK

Rebecca Lee

Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK

Charles Swanton

Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA

Matthew G. Vander Heiden

Dana-Farber Cancer Institute, Boston, MA, USA

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Contributions

All authors researched data for the article. A.B., K.B., T.R.C., T.G., T.J., C.S., M.G.V.H, R.K., M.J.-H. and E.S. contributed substantially to discussion of the content. T.C., R.L. and E.S. wrote the article. All authors reviewed and/or edited the manuscript before submission.

Corresponding authors

Correspondence to Thomas R. Cox or Erik Sahai .

Ethics declarations

Competing interests.

A.B. is an inventor on pending patents 63/449,817, 63/052,139 as well as awarded patents 11,305,014 and 10,413,522; all issued to the Sloan Kettering Institute. She has received personal fees from Apelis Pharmaceuticals and serves as an unpaid member of the Evren Technologies SAB. K.B., T.R.C., T.G., T.J. and R.K. declare no competing interests. M.J.-H. reports support from Achilles Therapeutics Scientific Advisory Board and Steering Committee, Pfizer, Astex Pharmaceuticals, Oslo Cancer Cluster and Bristol Myers Squibb outside the submitted work. R.L. reports personal fees from Pierre Fabre and has research funding from BMS, Astra Zeneca and Pierre Fabre outside the submitted work. E.S. reports grants from Novartis, Merck Sharp Dohme, AstraZeneca and personal fees from Phenomic outside the submitted work. C.S. reports grants and personal fees from Bristol Myers Squibb, AstraZeneca, Boehringer-Ingelheim, Roche-Ventana, personal fees from Pfizer, grants from Ono Pharmaceutical, Personalis, grants, personal fees and other support from GRAIL, other support from AstraZeneca and GRAIL, personal fees and other support from Achilles Therapeutics, Bicycle Therapeutics, personal fees from Genentech, Medixci, China Innovation Centre of Roche (CiCoR) formerly Roche Innovation Centre, Metabomed, Relay Therapeutics, Saga Diagnostics, Sarah Canon Research Institute, Amgen, GlaxoSmithKline, Illumina, MSD, Novartis, other support from Apogen Biotechnologies and Epic Bioscience outside the submitted work; in addition, C.S. has a patent for PCT/US2017/028013 licensed to Natera Inc., UCL Business, a patent for PCT/EP2016/059401 licensed to Cancer Research Technology, a patent for PCT/EP2016/071471 issued to Cancer Research Technology, a patent for PCT/GB2018/051912 pending, a patent for PCT/GB2018/052004 issued to Francis Crick Institute, University College London, Cancer Research Technology Ltd, a patent for PCT/GB2020/050221 issued to Francis Crick Institute, University College London, a patent for PCT/EP2022/077987 pending to Cancer Research Technology, a patent for PCT/GB2017/053289 licensed, a patent for PCT/EP2022/077987 pending to Francis Crick Institute, a patent for PCT/EP2023/059039 pending to Francis Crick Institute and a patent for PCT/GB2018/051892 pending to Francis Crick Institute. C.S. is Co-chief Investigator of the NHS Galleri trial funded by GRAIL. He is Chief Investigator for the AstraZeneca MeRmaiD I and II clinical trials and Chair of the Steering Committee. C.S. is cofounder of Achilles Therapeutics and holds stock options. M.G.V.H. is a scientific adviser for Agios Pharmaceuticals, iTeos Therapeutics, Sage Therapeutics, Faeth Therapeutics, Droia Ventures and Auron Therapeutics on topics unrelated to the presented work.

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Nature Reviews Cancer thanks Vickie Baracos, Clare M. Isacke, who co-reviewed with Amanda Fitzpatrick and Erica Sloan and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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An autoimmune encephalitis characterized by complex neuropsychiatric features and the presence of immunoglobulin G (IgG) antibodies against the NR1 subunit of the NMDA receptors in the central nervous system.

Partial collapse or incomplete inflation of the lung.

Pressure-induced movement of brain tissue.

An ageing-associated process in which haematopoiesis becomes dominated by one or a small number of genetically distinct stem or progenitor cells. Clonal haematopoiesis is linked to an increased risk of haematological malignancies.

Inability of the heart to pump blood properly.

Constriction of the arteries that supply blood to the heart.

(CRH). One of the major factors that drives the response of the body to stress.

(DIC). A rare but serious condition in which abnormal blood clotting occurs throughout the blood vessels of the body.

Inflammation of the brain.

An abnormal connection that forms between two body parts, such as an organ or blood vessel and another often unrelated structure in close proximity.

A rare disorder in which the immune system of a body attacks the nerves, which can lead to paralysis.

The stopping of flow of blood, typically associated with the bodies response to prevent and stop bleeding.

A build-up of fluid within the cavities of the brain.

Elevated calcium levels in the blood, often caused by overactive parathyroid glands. Hypercalcaemia is linked to kidney stones, weakened bones, altered digestion and potentially altered cardiac and brain function.

(HPD). Rapid tumour progression sometimes observed during immune checkpoint inhibitor treatment.

The condition that occurs when the level of sodium in the blood is low.

Harm, which is often unavoidable, caused by cancer treatments.

The marked suppression of polyclonal immunoglobulins in the body.

(LEMS). A neuromuscular junction disorder affecting communication between nerves and muscles, which manifests as a result of a paraneoplastic syndrome or a primary autoimmune disorder. Many cases are associated with small-cell lung cancer.

When cancer cells spread to the tissue layers covering the brain and spinal cord (the leptomeninges).

Also known as pulmonary oedema is a condition caused by excess fluid in the lungs. This fluid collects in the alveoli compromising function and making it difficult to breathe.

The observation of displacement of brain tissue across the centre line of the brain, suggestive of uneven intracranial pressure.

Decreased blood flow to the myocardium, commonly called a heart attack.

Inflammation specifically of the middle layer of the heart wall.

A group of rare disorders that occur when the immune system reacts to changes in the body triggered by the presence of a neoplasm.

A dense network of nerves that transmit information from the brain (efferent neurons) to the periphery and conversely transmit information from the periphery to the brain (afferent neurons). A component of the peripheral nervous system is the autonomic nervous system.

A build-up of fluid between the tissues that line the lungs and the chest wall.

A condition characterized by loss of skeletal muscle mass and function.

The lodging of a circulating blood clot within a vessel leading to obstruction. Thromboembolisms may occur in veins (venous thromboembolism) and arteries (arterial thromboembolism).

A key component of the pathway regulating blood clotting, specifically the receptor and cofactor for factor VII/VIIa.

A syndrome occurs when tumour cells release their contents into the bloodstream, either spontaneously or more typically, in response to therapeutic intervention.

Devices worn on the body, typically in the form of accessories or clothing, that incorporate advanced electronics and technology to monitor, track or enhance various aspects of human life. Examples include smartwatches and fitness trackers.

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Boire, A., Burke, K., Cox, T.R. et al. Why do patients with cancer die?. Nat Rev Cancer 24 , 578–589 (2024). https://doi.org/10.1038/s41568-024-00708-4

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Accepted : 15 May 2024

Published : 19 June 2024

Issue Date : August 2024

DOI : https://doi.org/10.1038/s41568-024-00708-4

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Journal of Materials Chemistry C

Recent advances of flexible iontronic pressure sensors: materials, microstructure designs, applications, and opportunities.

Flexible iontronic pressure sensors are the emerging flexible pressure sensors with extraordinary sensing performances, such as high sensitivity, outstanding resolution, and strong signal intensity due to the formation of electrical double-layer capacitance. In recent years, significant advancements have been made in the preparation and application of flexible iontronic pressure sensors in the fields of e-skins and wearable electronics. In this review, recent advances of flexible iontronic pressure sensors are comprehensively overviewed from the perspective of key performance indicators, such as sensitivity, linearity, response/recovery time, durability, accuracy, and detection range. The factors influencing each performance indicator are systematically elaborated to give readers a deep understanding. Then, we systemically introduce strategies to enhance sensing performances of flexible iontronic pressure sensors, including material choosing and structural design of electrodes and dielectric layers. Subsequently, the applications of flexible iontronic pressure sensors in health monitoring, information transmission, human-machine interaction, and spatial pressure mapping are comprehensively introduced. Finally, the directions for future development of flexible iontronic pressure sensors are thoroughly discussed.

• This article is part of the themed collections: Journal of Materials Chemistry C Recent Review Articles and Journal of Materials Chemistry C HOT Papers

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J. Wang, Y. Chen, S. Tu, X. Cui, J. Chen and Y. Zhu, J. Mater. Chem. C , 2024, Accepted Manuscript , DOI: 10.1039/D4TC03226H

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