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Bishal Gyawali, Elvira D’Andrea, Jessica M. Franklin, and Aaron S. Kesselheim

Background: Many new targeted cancer drugs have received FDA approval based on durable responses in nonrandomized controlled trials (non-RCTs). The goal of this study was to evaluate whether the response rates (RRs) and durations of response (DoRs) of targeted cancer drugs observed in non-RCTs are consistent when these drugs are tested in RCTs. Methods: We used the FDA’s Table of Pharmacogenomic Biomarkers in Drug Labeling to identify cancer drugs that were approved based on changes in biomarker endpoints through December 2017. We then identified the non-RCTs and RCTs for these drugs for the given indications and extracted the RRs and DoRs. We compared the RRs and median DoR in non-RCTs versus RCTs using the ratio of RRs and the ratio of DoRs, defined as the RRs (or DoRs) in non-RCTs divided by the RRs (or DoRs) in RCTs. The ratio of RRs or DoRs was pooled across the trial pairs using random-effects meta-analysis. Results: Of the 21 drug–indication pairs selected, both non-RCTs and RCTs were available for 19. The RRs and DoRs in non-RCTs were greater than those in RCTs in 63% and 87% of cases, respectively. The pooled ratio of RRs was 1.06 (95% CI, 0.95–1.20), and the pooled ratio of DoRs was 1.17 (95% CI, 1.03–1.33). RRs and DoRs derived from non-RCTs were also poor surrogates for overall survival derived from RCTs. Conclusions: The RRs were not different between non-RCTs and RCTs of cancer drugs approved based on changes to a biomarker, but the DoRs in non-RCTs were significantly higher than in RCTs. Caution must be exercised when approving or prescribing targeted drugs based on data on durable responses derived from non-RCTs, because the responses could be overestimates and poor predictors of survival benefit.

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Seanthel Delos Santos, Noah Witzke, Bishal Gyawali, Vanessa Sarah Arciero, Amanda Putri Rahmadian, Louis Everest, Matthew C. Cheung, and Kelvin K. Chan

Background: Regulatory approval of oncology drugs is often based on interim data or surrogate endpoints. However, clinically relevant data, such as long-term overall survival and quality of life (QoL), are often reported in subsequent publications. This study evaluated the ASCO-Value Framework (ASCO-VF) net health benefit (NHB) at the time of approval and over time as further evidence arose. Methods: FDA-approved oncology drug indications from January 2006 to December 2016 were reviewed to identify clinical trials scorable using the ASCO-VF. Subsequent publications of clinical trials relevant for scoring were identified (until December 2019). Using ASCO-defined thresholds (≤40 for low and ≥45 for substantial benefit), we assessed changes in classification of benefit at 3 years postapproval. Results: Fifty-five eligible indications were included. At FDA approval, 40.0% were substantial, 10.9% were intermediate, and 49.1% were low benefit. We then identified 90 subsequent publications relevant to scoring, including primary (28.9%) and secondary endpoint updates (47.8%), safety updates (31.1%), and QoL reporting (47.8%). There was a change from initial classification of benefit in 27.3% of trials (10.9% became substantial, 9.1% became low, and 7.3% became intermediate). These changes were mainly due to updated hazard ratios (36.4%), toxicities (56.4%), new tail-of-the-curve bonus (9.1%), palliation bonus (14.5%), or QoL bonus (18.2%). Overall, at 3 years postapproval, 40.0% were substantial, 9.1% were intermediate, and 50.9% were low benefit. Conclusions: Because there were changes in classification for more than one-quarter of indications, in either direction, reassessing the ASCO-VF NHB as more evidence becomes available may be beneficial to inform clinical shared decision-making. On average, there was no overall improvement in the ASCO-VF NHB with longer follow-up and evolution of evidence.