Communicating Uncertainties Associated With the Benefits and Risks of New Cancer Drugs
Phase: NA
Conditions: Cancer
Sponsor: London School of Economics and Political Science

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Study Protocol 
 
 
Communicating uncertainties associated with the benefits and risks of new 
cancer drugs 
 
 
Funders: Arnold Ventures; the London School of Economics and Political Science.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Final version date: May 2025 
 
 
 
 
 
 
 
 

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Randomized pre-post survey to evaluate the effect of communicating 
uncertainties from different sources 
 
 
Introduction 
Many newer cancer drugs are approved before uncertainties with their underlying clinical 
trial evidence have been adequately studied, in turn making it difficult to accurately 
determine the drug’s benefits and harms.1 For example, nearly one-third of new cancer 
drugs are approved without comparative data versus existing treatments.2 Fewer than half of 
cancer drugs demonstrate improvements on outcomes that matter most to patients (quality 
of life and overall survival), instead measuring unvalidated surrogate endpoints.3,4 Other 
uncertainties with new cancer drugs stem from a lack of diversity of clinical trial 
participants,5,6 and limited long-term data on the drug’s effects.  
 
Regulated information about prescription drugs rarely acknowledges these uncertainties, 
which limits the ability of patients and physicians to make informed and evidence-based 
decisions. In this study, we will examine the effect of communicating epistemic uncertainty 
associated with limitations in the clinical trial evidence supporting new cancer drugs. Cancer 
drugs are the single largest therapeutic category of new drug approvals,7 and the frequency 
and magnitude of uncertainties associated with the evidence of these drugs at the time of 
approval are considerable and increasing. Relative to other drugs, cancer drugs are more 
likely to be supported by fewer late-phase clinical trials at the time of approval. They are also 
more likely to be approved on the basis of non-randomized single arm trials and unvalidated 
surrogate endpoints.8 
 
However, prescription drug information rarely communicates uncertainties associated with 
the evidence of new drugs.9 As a result, there can be substantial differences between 
patients’ expectations and understanding of treatment, and evidence on the drug’s benefits 
and harms.10 Misperceptions are common among patients with metastatic cancer, who may 
mistake the palliative intent of treatment as being curative, and overestimate their likelihood 
of surviving longer.11 Misunderstanding the evidence of a drug’s benefits can also 
compromise patients’ ability to make informed decisions. Patients may have preferred 
choices that would have preserved their quality of life, rather than being exposed to the 
physical, financial, and time toxicities of non-curative and non-life extending treatments.12 
 
Objective 
To evaluate the effect of using brief statements to communicate different sources of 
uncertainty about the benefits and harms of new cancer drugs on participants’ decisions. 
 
Randomization 
We will conduct a randomized pre-post survey, evaluating the change in participants’ 
decisions before and after being given information about a source of uncertainty with a new 
cancer drug’s benefits and harms. By using a pre-post design, each group will serve as their 
own control and the randomization will ensure that participant characteristics are equally 
distributed. Participants will be randomized to 1 of 5 experimental conditions. Randomization 
will be done at the participant level, using the survey platform Qualtrics. 
 

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Participants 
We will recruit a nationally representative sample of US adults to participate in this study. 
Eligible participants will be above 18 years of age and fluent in English. Participants will be 
recruited through CloudResearch, a market research company which engages with 
hundreds of research panel providers that use various methods for recruitment. Participants 
will be asked for informed consent before initiating the survey. No identifying information 
about participants will be asked or known by the study team, and CloudResearch will not 
have access to the participants’ responses. 
 
Intervention 
In the pre-intervention phase, participants will be given information about a hypothetical new 
drug approved by the FDA for the treatment of non-small cell lung cancer. We based the 
information on adagrasib, which received accelerated approval in 2022 for the treatment of 
adults with KRAS G12C-mutated locally advanced or metastatic non-small cell lung cancer 
who have received at least one prior systemic therapy. We then developed brief statements 
to communicate the most common sources of uncertainties with new cancer drugs cited in 
FDA approval decisions (Table 1): (1) single-arm trial designs,13 (2) limited study populations 
(i.e., generalizability of clinical trial evidence),14,15 and (3) limited study durations (i.e., long-
term benefits and harms). We also included two additional uncertainties that are frequently 
mentioned in the scientific literature: (4) the use of unvalidated surrogate endpoints to 
support new cancer drug approvals,16,17 and (5) uncertain treatment effect size (i.e., the 
magnitude of therapeutic benefit).18  
 
Procedure 
At the start of the survey, participants will be given a vignette describing a 38-year-old 
woman diagnosed with non-small cell lung cancer. The woman’s doctor tells her about a new 
drug that was approved by the FDA for her disease and that is covered by her insurance. 
Participants will then be presented with a table summarizing the main benefits and harms of 
the drug, which was developed using the FDA’s Drug Trials Snapshot for adagrasib.  
 
In the pre-intervention phase, we will ask participants how likely they would be to take the 
drug if they were in Alex’s position, and how certain they are that the drug will work. 
Participants will then be randomized to 1 of 5 statements about a source of uncertainty with 
the drug’s evidence. The post-intervention questions will re-assess participants’ decisions 
and perceptions of uncertainty, as well as their understanding of the uncertainty 
communicated in the statement. 
 
Primary outcome 
The co-primary outcomes of this study are changes in decision making and understanding. 
For decision making, we will measure the effect of communicating different sources of 
uncertainties on the change in participants’ hypothetical decisions, measured as the pre-post 
difference in their decision to take the drug if they were diagnosed with non-small cell lung 
cancer. For understanding, we will evaluate whether participant are able to identify the 
source of uncertainty with the drug’s evidence that they were randomized to. 
 
Secondary outcomes 
Participants’ perception of uncertainty (how confident they are the drug will work for Alex). 
 

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Statistical analysis 
We will compare the change in participants’ decisions pre- and post-intervention using the 
McNemar’s X2 test for paired data. In adjusted analyses, we will use regression models to 
control for covariates. 
 
Similar to previous studies that have communicated uncertainties with surrogate 
endpoints,19,20 we assumed an approximate 10% absolute difference in participants 
decisions’ pre- and post-intervention (60% vs 50%), which resulted in approximately 500 
people per group. We plan to recruit 600 per group (3,000 in total) in case of dropouts or 
errors during survey completion. 
 
We plan to exclude participants who complete the survey in 40% of the anticipated 
completion time, a conservative cutoff that is consistent with other studies.21 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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References 
1. Hilal T, Gonzalez-Velez M, Prasad V. Limitations in clinical trials leading to anticancer drug 
approvals by the US Food and Drug Administration. JAMA Intern Med. 2020;180(8):1108-
1115. doi:10.1001/jamainternmed.2020.2250 
2. Michaeli DT, Michaeli T. Overall Survival, Progression-Free Survival, and Tumor Response 
Benefit Supporting Initial US Food and Drug Administration Approval and Indication Extension 
of New Cancer Drugs, 2003-2021. J Clin Oncol. 2022;40(35):4095-4106. 
doi:10.1200/JCO.22.00535 
3. Gyawali B, Hey SP, Kesselheim AS. Assessment of the Clinical Benefit of Cancer Drugs 
Receiving Accelerated Approval. JAMA Intern Med. 2019;179(7):906-913. 
doi:10.1001/jamainternmed.2019.0462 
4. Davis C, Naci H, Gurpinar E, Poplavska E, Pinto A, Aggarwal A. Availability of evidence of 
benefits on overall survival and quality of life of cancer drugs approved by European 
Medicines Agency: Retrospective cohort study of drug approvals 2009-13. BMJ. 
2017;359:j4530-j4530. doi:10.1136/bmj.j4530 
5. Green AK, Curry M, Trivedi N, Bach PB, Mailankody S. Assessment of Outcomes Associated 
With the Use of Newly Approved Oncology Drugs in Medicare Beneficiaries. JAMA Netw 
Open. 2021;4(2):e210030-e210030. doi:10.1001/jamanetworkopen.2021.0030 
6. Orcutt X, Chen K, Mamtani R, Long Q, Parikh RB. Evaluating generalizability of oncology trial 
results to real-world patients using machine learning-based trial emulations. Nat Med. 
2025;31(2):457-465. doi:10.1038/s41591-024-03352-5 
7. Monge AN, Sigelman DW, Temple RJ, Chahal HS. Use of US Food and Drug Administration 
Expedited Drug Development and Review Programs by Orphan and Nonorphan Novel Drugs 
Approved From 2008 to 2021. JAMA Netw Open. 2022;5(11):e2239336-e2239336. 
doi:10.1001/jamanetworkopen.2022.39336 
8. Downing NS, Aminawung JA, Shah ND, Krumholz HM, Ross JS. Clinical trial evidence 
supporting FDA approval of novel therapeutic agents, 2005-2012. JAMA. 2014;311(4):368-
377. doi:10.1001/jama.2013.282034 
9. Davis C, Wagner AK, Salcher-Konrad M, et al. Communication of anticancer drug benefits and 
related uncertainties to patients and clinicians: document analysis of regulated information on 
prescription drugs in Europe. BMJ. 2023;380:e073711-e073711. doi:10.1136/bmj-2022-
073711 
10. Hoffmann TC, Del Mar C. Patients’ expectations of the benefits and harms of treatments, 
screening, and tests a systematic review. JAMA Intern Med. 2015;175(2):274-286. 
doi:10.1001/jamainternmed.2014.6016 
11. Weeks JC, Catalano PJ, Cronin A, et al. Patients’ Expectations about Effects of 
Chemotherapy for Advanced Cancer. N Engl J Med. 2012;367(17):1616-1625. 
doi:10.1056/nejmoa1204410 
12. Weeks JC, Cook EF, O’Day SJ, et al. Relationship between cancer patients’ predictions of 
prognosis and their treatment preferences. JAMA. 1998;279(21):1709-1714. 
doi:10.1001/jama.279.21.1709 
13. Agrawal S, Arora S, Amiri-Kordestani L, et al. Use of Single-Arm Trials for US Food and Drug 
Administration Drug Approval in Oncology, 2002-2021. JAMA Oncol. 2023;9(2):266-272. 
doi:10.1001/jamaoncol.2022.5985 

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14. Alsan M, Durvasula M, Gupta H, Schwartzstein J, Williams H. Representation and 
Extrapolation: Evidence from Clinical Trials*. Q J Econ. 2024;139(1):575-635. 
doi:10.1093/qje/qjad036 
15. Alsan M, Campbell RA, Leister L, Ojo A. Investigator racial diversity and clinical trial 
participation. J Health Econ. 2025;100:102968. doi:10.1016/j.jhealeco.2025.102968 
16. Prasad V, Kim C, Burotto M, Vandross A. The strength of association between surrogate end 
points and survival in oncology: A systematic review of trial-level meta-analyses. JAMA Intern 
Med. 2015;175(8):1389-1398. doi:10.1001/jamainternmed.2015.2829 
17. Kovic B, Jin X, Kennedy SA, et al. Evaluating Progression-Free Survival as a Surrogate 
Outcome for Health-Related Quality of Life in Oncology: A Systematic Review and 
Quantitative Analysis. JAMA Intern Med. 2018;178(12):1586-1596. 
doi:10.1001/jamainternmed.2018.4710 
18. Tibau A, Molto C, Ocana A, et al. Magnitude of Clinical Benefit of Cancer Drugs Approved by 
the US Food and Drug Administration. J Natl Cancer Inst. 2018;110(5):486-492. 
doi:10.1093/jnci/djx232 
19. Schwartz LM, Woloshin S. Communicating uncertainties about prescription drugs to the 
public: A national randomized trial. Arch Intern Med. 2011;171(16):1463-1468. 
doi:10.1001/archinternmed.2011.396 
20. Kesselheim AS, Woloshin S, Eddings W, Franklin JM, Ross KM, Schwartz LM. Physicians’ 
knowledge about FDA approval standards and perceptions of the “breakthrough therapy” 
designation. JAMA. 2016;315(14):1516-1518. doi:10.1001/jama.2015.16984 
21. Forrest R, Lagarde M, Aggarwal A, Naci H. Preferences for speed of access versus certainty 
of the survival benefit of new cancer drugs: a discrete choice experiment. Lancet Oncol. 
2024;0(0). doi:10.1016/S1470-2045(24)00596-5 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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Table: Statements communicating sources of uncertainties 
 
Source of uncertainty 
Statement about uncertainty 
Single-arm trial 
Because Zenova has not been compared to other treatments, it is 
unknown if Zenova is better, the same, or worse than other treatments 
for non-small cell lung cancer. 
Limited study duration 
(Long-term benefits and 
harms) 
Since patients given Zenova were followed for a short time, the longer-
term benefits and harms of taking Zenova are unknown. 
Limited study population 
(generalizability) 
Zenova has not been studied in patients similar to Alex (patients with 
her race and ethnicity). It is unknown whether Zenova will work and 
what harms it will have for patients like her. 
Unvalidated surrogate 
endpoint 
Zenova has only been shown to shrink the size of tumors. It is unknown 
whether Zenova improves how patients feel or how long they live. 
Treatment effect size 
(magnitude of 
therapeutic benefit) 
It is unknown whether patients with non-small cell lung cancer will 
notice an improvement with Zenova. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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Survey 
 
 
Communicating Information About Prescription Drugs 
 
 
Welcome. Thank you for your interest in this study. 
 
About this study 
 
Researchers are interested in how to better communicate information about prescription 
drugs to the public. 
 
This study is being led by researchers at the London School of Economics and Political 
Science (UK) and Harvard Medical School (US). Funding was provided by Arnold Ventures 
and the LSE Phelan United States Centre. 
 
The survey takes about 10 minutes to complete. 
 
Consent 
Participation in this survey is voluntary. The survey is anonymous – that means we will not 
record your name or any information that could connect you to your answers.  
 
If you have any questions regarding this study, please contact the researcher, Avi Cherla, at 
a.j.cherla@lse.ac.uk. If you have any concerns regarding the conduct of this research, 
please contact the LSE research ethics managers via research.ethics@lse.ac.uk.  
 
Instructions 
Please try to answer all questions even if you are not completely sure about an answer. 
Once you complete a question, you will not be able to go back and change your answer.  
 
By clicking the next button, you indicate that you: 
1) Are 18 years or older 
2) Live in the US 
3) Are fluent in reading, writing, and speaking in English 
4) Have read and understand the instructions 
5) Consent to participating in the survey 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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Section A: Sources of prescription drug information 
 
First, we want to learn about how you find information about prescription drugs. 
 
1. When you are looking for information about prescription drugs, how often do you use 
each of the following sources? (Matrix grid response options: Never, rarely, 
sometimes, often) 
• 
Print media (for example, New York Times, Wall Street Journal) 
• 
Broadcast media (for example, CNN, Fox, NBC) 
• 
Social media (for example, Facebook, Twitter [X], Instagram) 
• 
Government website (for example, FDA, CDC) 
• 
Other health websites (for example, WebMD, Mayo Clinic) 
• 
Advertisements (TV, online, or print) 
• 
Family or friends 
• 
Physician, nurse, or other health professional 
 
2. Do you trust that information about prescription drugs from these sources is correct? 
(matrix grid with sources from above) 
• 
Strongly disagree 
• 
Somewhat disagree 
• 
Somewhat agree 
• 
Strongly agree 
 
3. Overall, how easy is it for you to find trustworthy information about prescription 
drugs? 
• 
Very difficult 
• 
Somewhat difficult 
• 
Somewhat easy 
• 
Very easy 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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Next, you will be presented with a scenario, followed by a series of questions relating 
to it. [stand-alone page] 
 
 
Please read the following scenario about Alex.  
 
Alex is 38 years old. A year ago, Alex was diagnosed with non-small cell lung cancer that 
had spread to other parts of her body. Since her diagnosis, Alex has tried 2 different 
treatments, but none have worked. Alex’s doctor says that less than 10% of people in her 
situation live for more than 5 years.  
 
Alex’s doctor tells her that the US Food and Drug Administration (FDA) recently approved a 
new drug for patients like her who did not respond to other treatments. Her doctor wants to 
know if she would be interested in taking the drug. It would be covered by Alex’s health 
insurance with no additional costs.  
 
Here is the information Alex’s doctor gave her to help her decide about the new drug. The 
source of this information was the US Food and Drug Administration (FDA). 
 
 
Information about ZENOVA for non-small cell lung cancer  
 
ZENOVA is a prescription medicine used to treat adult patients with non-small cell lung cancer 
(NSCLC) that has an abnormal KRAS G12C gene mutation, is locally advanced or has spread 
to other parts of the body (metastatic) and has progressed on or after one prior treatment.  
 
The FDA approved ZENOVA based on evidence from 1 clinical trial in 112 patients. 
Benefits 
% of patients in trial 
Partial or complete shrinkage of tumors 
43% 
     Complete shrinkage of tumors 
1% 
     Partial shrinkage of tumors 
42% 
Harms 
% of patients in trial 
Serious harms (life threatening or requiring hospitalization) 
45% 
     Pneumonia 
17% 
     Hepatoxicity (liver damage) 
10% 
Common side effects  
98% 
     Diarrhea 
70% 
     Nausea 
69% 
 
 
 
 
 
 

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Section D: Decision making (pre intervention) 
 
4. Imagine you were Alex and diagnosed with non-small cell lung cancer. How likely are 
you to take the new drug, Zenova?  
• 
Very unlikely 
• 
Somewhat unlikely 
• 
Somewhat likely 
• 
Very likely 
 
Section E: Perception of uncertainty (pre intervention) 
 
5. How certain are you that Zenova will work for Alex? 
• 
Very uncertain 
• 
Somewhat uncertain 
• 
Somewhat certain 
• 
Very certain 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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Alex’s doctor mentions that there was more information about Zenova available from 
the FDA. [separate page] 
 
Here is the additional information, which is about uncertainties with Zenova: 
 
[show uncertainty statement and drug table] 
 
 
 
Section F: Decision making (post-intervention) 
 
6. Considering this additional information, if you were Alex and diagnosed with non-
small cell lung cancer, how likely are you now to take Zenova? 
• 
Very unlikely 
• 
Somewhat unlikely 
• 
Somewhat likely 
• 
Very likely 
 
Section G: Perception of uncertainty (post-intervention) 
 
7. Considering the additional information you learned about Zenova, how certain are 
you now that Zenova will work for Alex? 
• 
Very uncertain 
• 
Somewhat uncertain 
• 
Somewhat certain 
• 
Very certain 
 
Section H: Understanding 
 
8. Please rate your agreement with the following statements. (Matrix grid with 5 point 
scale for strongly disagree, disagree, etc.) 
• 
Zenova works better than other treatments for non-small cell lung cancer 
• 
Zenova’s longer-term benefits and harms are well known 
• 
Zenova has been studied in patients that are similar to Alex (race and 
ethnicity) 
• 
Zenova improves how patients feel or how long they live 
• 
Zenova has a very large benefit for patients with non-small cell lung cancer 
 
 
 
 
 
 
 
 
 
 

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Section I: Perceived importance of knowing about uncertainty 
 
9. Was the additional information about uncertainty with Zenova helpful to your 
decision? 
• 
Strongly disagree 
• 
Somewhat disagree 
• 
Somewhat agree 
• 
Strongly agree 
 
10. Do you think that uncertainties about drug benefits and harms should always be 
communicated? 
• 
Strongly disagree 
• 
Somewhat disagree 
• 
Somewhat agree 
• 
Strongly agree 
 
Imagine that your doctor prescribed you a new drug and there was some information about 
the drug that was still unknown. Which of these uncertainties do you think are important to 
know when deciding about taking a new drug?  
 
11. Unknown whether the drug is better or worse than other treatments. 
1. Not at all important 
2. Somewhat unimportant 
3. Somewhat important 
4. Very important 
 
12. Unknown what the long-term benefits and harms of the drug are. 
1. Not at all important 
2. Somewhat unimportant 
3. Somewhat important 
4. Very important 
 
13. Unknown how well the drug works for someone of your age, of your race, or with 
your health conditions. 
1. Not at all important 
2. Somewhat unimportant 
3. Somewhat important 
4. Very important 
 
14. Unknown whether the drug will help patients feel better or live longer. 
1. Not at all important 
2. Somewhat unimportant 
3. Somewhat important 
4. Very important 
 
15. Unknown whether patients notice a difference with the drug (the benefits are too 
small to notice). 

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1. Not at all important 
2. Somewhat unimportant 
3. Somewhat important 
4. Very important 
 
 
 
Section J: Demographics 
 
Finally, please tell us about yourself. 
 
16. How old are you? 
• 
18 to 24 
• 
25 to 44 
• 
45 to 64 
• 
65 and older 
 
17. What is your sex? 
• 
Male 
• 
Female 
• 
Other 
• 
Prefer not to say 
 
18. What is your race and ethnicity? 
• 
White 
• 
Hispanic or Latino 
• 
African American or Black 
• 
American Indian or Alaska Native 
• 
Asian 
• 
Other 
 
19. What is the highest level of education that you completed? 
• 
Less than high school 
• 
High school or equivalent 
• 
College or undergraduate degree 
• 
Graduate degree and higher 
 
20. What is your approximate yearly income? 
• 
Less than $25,000 
• 
$25,000 to $49,999 
• 
$50,000 to $74,999 
• 
$75,000 to $99,999 
• 
More than $100,000 
 
21. Have you, a close friend, or immediate family member (i.e. your partner, parents, 
siblings, or children) ever been diagnosed with cancer? (Select as many that apply). 
• 
I have been diagnosed (currently, or in the past) 

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• 
An immediate family member has been diagnosed 
• 
A close friend has been diagnosed 
• 
To my knowledge, none of my close friends or family, or myself, has been 
diagnosed with cancer 
 
22. How would you describe your political views? 
• 
Liberal 
• 
Slightly liberal 
• 
Moderate 
• 
Slightly conservative 
• 
Conservative 
• 
Prefer not to say 
 
23. Would you describe yourself as generally optimistic or pessimistic? 
• 
Pessimistic 
• 
Somewhat pessimistic 
• 
Neither pessimistic or optimistic 
• 
Somewhat optimistic 
• 
Optimistic 
 
24. How often do you need someone to help you understand instructions or other written 
material from your doctor or pharmacy about prescription drugs? 
• 
Never 
• 
Rarely 
• 
Sometimes 
• 
Often 
• 
Always