MedicalResearch.com Interview with:
Emerson Chen, MD
Chief Fellow, Hematology-Oncology, PGY-6
Oregon Health & Science University
MedicalResearch.com: What is the background for this study? What are the main findings?
Response: Many cancer drugs are approved annually giving the appearance of innovation; however, some drugs may have been approved because of a lower bar. Use of lesser endpoints like response rate (how tumor shrinks) and progression-free survival (how tumor has delayed growth) have been proposed to speed trials when compared against traditional endpoints like overall survival (how long patients might live).
Using published trials that led to cancer drug approval from 2006 to 2017, we estimated how long it would take to get each of these three endpoints across all cancer drugs and indications to see how much time we could save by using these weaker but faster endpoints.
We see that many trials using overall survival used less time than anticipated, and many trials using response rate or progression-free survival actually took quite a bit of time. In part that is due to researchers needing to document the duration of the response. But, whatever the reason, the time to get each of the three endpoints is actually more similar than different, and we estimate that our current use of these faster endpoints are saving us only 11 months compared to using only overall survival.
MedicalResearch.com: What should readers take away from your report?
Response: We all know that overall survival is the gold standard. These other endpoints may be reasonable if a disease is truly rare, has no treatment options, or has an investigative treatment that is truly promising. However, we see many pharmaceutical run trials are testing drugs in common cancers and in setting with other already approved options. While some cancer drugs are truly promising, marginal drugs also use the same drug approval criteria. In this study we see that the tradeoff of less certainty about the drug efficacy and the time to complete a trial may not be as drastic as we had imagined before.
MedicalResearch.com: What recommendations do you have for future research as a result of this work?
Response: The medical community and patients as well are paying more and more attention to the drug approval in the United States because of rising drug prices. The FDA and the pharmaceutical sponsors are required to report specific data to medical journals and to the public. While the oncology field has seen many drug approvals, many other fields in cardiology, rheumatology, and internal medicine also have seen many controversial drug approvals as well. Many levels of the drug approval process deserve scrutiny and more conversations. In oncology, as we have new classes of drugs, we need to see more drugs approved using patient-oriented endpoints like survival, quality of life, or symptoms-based assessments rather than using weaker endpoints based on CT scans. Simply using the “time saved” argument won’t do.
MedicalResearch.com: Is there anything else you would like to add?
Response: I really encourage other health services researcher to also look at the endpoints used in their fields and assess if the easier endpoints used in their fields have been validated and that the tradeoff between the time saved and certainty of clinical benefit is worth it.
I do not have any disclosures for this research study. I do want to acknowledge information technology resources I used were from Oregon Clinical and Translational Research Institute (1 UL1 RR024140 01). The senior author, Vinay Prasad, reports receiving royalties from his book Ending Medical Reversal; that his work is funded by the Laura and John Arnold Foundation; that he has received honoraria for Grand Rounds/lectures from several universities, medical centers, and professional societies and payments for contributions to Medscape. He is the host of Plenary Session podcast, which has Patreon backers.
Chen EY, Joshi SK, Tran A, Prasad V. Estimation of Study Time Reduction Using Surrogate End Points Rather Than Overall Survival in Oncology Clinical Trials. JAMA Intern Med. Published online April 01, 2019. doi:10.1001/jamainternmed.2018.8351
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