Search Results

Background: Censoring due to early drug discontinuation (EDD) or withdrawal of consent or loss to follow-up (WCLFU) can result in postrandomization bias. In oncology, censoring rules vary with no defined standards. In this study, we sought to describe the planned handling and transparency of censoring data in oncology trials supporting FDA approval and to compare EDD and WCLFU in experimental and control arms. Methods: We searched FDA archives to identify solid tumor drug approvals and their associated trials between 2015 and 2019, and extracted the planned handling and reporting of censored data. We compared the proportion of WCLFU and EDD between the experimental and control arms by using generalized estimating equations, and performed logistic regression to identify trial characteristics associated with WCLFU occurring more frequently in the control group. Results: Censoring rules were defined adequately in 48 (59%) of 81 included studies. Only 14 (17%) reported proportions of censored participants clearly. The proportion of WCLFU was higher in the control group than in the experimental group (mean, 3.9% vs 2.5%; β-coefficient, −2.2; 95% CI, −3.1 to −1.3; P<.001). EDD was numerically higher in the experimental arm in 61% of studies, but there was no statistically significant difference in the proportion of EDD between the experimental and control groups (mean, 21.6% vs 19.9%, respectively; β-coefficient, 0.27; 95% CI, −0.32 to 0.87; P=.37). The proportion of EDD due to adverse effects (AEs) was higher in the experimental group (mean, 13.2% vs 8.5%; β-coefficient, 1.5; 95% CI, 0.57–2.45; P=.002). WCLFU was higher in the control group in studies with an active control group (odds ratio [OR], 10.1; P<.001) and in open label studies (OR, 3.00; P=.08). Conclusions: There are significant differences in WCLFU and EDD for AEs between the experimental and control arms in oncology trials. This may introduce postrandomization bias. Trials should improve the reporting and handling of censored data so that clinicians and patients are fully informed regarding the expected benefits of a treatment.

Background: It is unknown how often regional differences in oncology trials are observed. Based on our study findings, we quantified regional variation in registration studies in oncology and developed a question guide to help clinicians evaluate regional differences. Methods: Using FDA archives, we identified registration studies in solid tumor malignancies from 2010 to 2020. We extracted the baseline study characteristics and participating countries and determined whether the primary publication reported a regional subgroup analysis. For studies presenting outcomes stratified by region, we extracted the stratified hazard ratios (HRs) and extracted or calculated the test for heterogeneity. We performed a random effects meta-analysis and a pairwise comparison to determine whether outcomes differed between high-income versus mixed-income regions. Results: We included 147 studies in our final analysis. Studies supporting FDA drug approval have become increasingly multinational over time (β = 0.5; P=.04). The median proportion of countries from high-income groups was 81.2% (range, 44%–100%), with no participation from low-income countries in our cohort. Regional subgroup analysis was presented for 78 studies (53%). Regional heterogeneity was found in 17.8% (8/45) and 18% (8/44) of studies presenting an overall survival (OS) and progression-free survival endpoint, respectively. After grouping regions by income level, we found no difference in OS outcomes in high-income regions compared with mixed-income regions (n=20; HR, 0.95; 95% CI, 0.84–1.07). To determine whether regional variation is genuine, clinicians should evaluate the data according to the following 5 questions: (1) Are the regional groupings logical? (2) Is the regional difference on an absolute or relative scale? (3) Is the regional difference consistent and plausible? (4) Is the regional difference statistically significant? (5) Is there a clinical explanation? Conclusions: As registration studies in oncology become increasingly international, regional variations in trial outcomes may be detected. The question guide herein will help clinicians determine whether regional variations are likely to be clinically meaningful or statistical anomalies.

Background: Most anticancer drugs are approved by regulatory agencies based on surrogate measures. This article explores the variables associated with overall survival (OS), quality of life (QoL), and substantial clinical benefit among anticancer drugs at the time of approval and in the postmarketing period. Methods: Anticancer drugs approved by the FDA between January 2006 and December 2015 and with postmarketing follow-up until April 2019 were identified. We evaluated trial-level data supporting approval and any updated OS and/or QoL data. We applied the ESMO-Magnitude of Clinical Benefit Scale (ESMO-MCBS) and the ASCO Value Framework (ASCO-VF) to initial and follow-up studies. Results: We found that 58 drugs were approved for 96 indications based on 96 trials. At registration, approval was based on improved OS in 39 trials (41%) and improved QoL in 16 of 45 indications (36%). Postmarketing data showed an improvement in OS for 28 of 59 trials (47%) and in QoL for 22 of 48 indications (46%). At the time of approval, 25 of 94 (27%) and 26 of 80 scorable trials (33%) met substantial benefit thresholds using the ESMO-MCBS and ASCO-VF, respectively. In the postmarketing period, 37 of 69 (54%) and 35 of 65 (54%) trials met the substantial benefit thresholds. Drugs with companion diagnostics and immune checkpoint inhibitors were associated significantly with substantial clinical benefit. Conclusions: Compared with the time of approval, more anticancer drugs showed improved OS and QoL and met the ESMO-MCBS or ASCO-VF thresholds for substantial benefit over the course of postmarketing time. However, only approximately half of the trials met the threshold for substantial benefit. Companion diagnostic drugs and immunotherapy seemed to be associated with greater clinical benefit.