Reassessing the Net Benefit of Cancer Drugs With Evolution of Evidence Using the ASCO Value Framework.

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.

Quantifying the Survival Benefits of Oncology Drugs With a Focus on Immunotherapy Using Restricted Mean Survival Time.

BACKGROUND: Restricted mean survival time (RMST) overcomes limitations of current measures of survival benefits because it directly captures information of the entire area under Kaplan-Meier survival curves. Using RMST difference (absolute survival benefit) and RMST ratio (relative survival benefit), we quantified the magnitude of survival benefits of recent oncology drugs and compared immunotherapies with nonimmunotherapies. METHODS: Kaplan-Meier curves were extracted from phase II/III randomized controlled trials used by the FDA for oncology drug approvals from January 2011 through November 2017 with overall survival (OS) or progression-free survival (PFS) as primary endpoints. RMST differences, ratios, and their 95% confidence intervals were meta-analyzed to estimate absolute and relative survival benefits of contemporary oncology drugs and to compare immunotherapies with nonimmunotherapies. Meta-regression was conducted to adjust for potential confounders. RESULTS: Ninety-four trials with a total of 51,639 patients were included. Overall absolute survival benefits (RMST differences) were 1.55 months for OS (95% CI, 1.32-1.77) and 2.99 months for PFS (95% CI, 2.65-3.33). Overall relative survival benefits (RMST ratios) were 1.11 for OS (95% CI, 1.09-1.13) and 1.42 for PFS (95% CI, 1.36-1.48). Immunotherapy absolute PFS benefit was less than that of nonimmunotherapy (1.56 vs 3.23 months), whereas immunotherapy absolute OS benefit was larger than that of nonimmunotherapy by 0.59 months (2.02 vs 1.43 months). Adjusted OS RMST difference was 0.91 months greater for immunotherapy than for nonimmunotherapy after adjusting for confounders. CONCLUSIONS: Absolute survival benefits of recent oncology drugs are modest. Survival benefits of immunotherapies are not dramatically superior to those of nonimmunotherapies. Routine reporting and use of RMST may help patients, physicians, and payers make more informed and responsible decisions regarding the care of patients with cancer.