Comparison of efficacy discrepancy between early-phase clinical trials and phase III trials of PD-1/PD-L1 inhibitors.

BACKGROUND: Phase III clinical trials are pivotal for evaluating therapeutics, yet a concerning failure rate has been documented, particularly impacting oncology where accelerated approvals of immunotherapies are common. These failures are predominantly attributed to a lack of therapeutic efficacy, indicating overestimation of results from phase II studies. Our research aims to systematically assess overestimation in early-phase trials involving programmed cell death-1 (PD-1)/programmed cell death-ligand 1(PD-L1) inhibitors compared with phase III trials and identify contributing factors. METHODS: We matched 51 pairs of early-phase and phase III clinical trials from a pool of over 9,600 PD-1/PD-L1 inhibitor trials. The matching criteria included identical treatment regimens, cancer types, treatment lines, and biomarker enrichment strategies. To assess overestimation, we compared the overall response rates (ORR) between early-phase and phase III trials. We established independent variables related to eligibility criteria, and trial design features of participants to analyze the factors influencing the observed discrepancy in efficacy between the two phases through univariable and multivariable logistic analyses. RESULT: Early-phase trial outcomes systematically overestimated the subsequent phase III results, yielding an odds ratio (OR) comparing ORR in early-phase versus phase III: 1.66 (95% CI: 1.43 to 1.92, p<0.05). This trend of inflated ORR was consistent across trials testing PD-1/PD-L1 monotherapies and combination therapies involving PD-1/PD-L1. Among the examined factors, the exclusion of patients with autoimmune diseases was significantly associated with the disparity in efficacy between early-phase trials and phase III trials (p=0.023). We calculated a Ward statistic of 2.27 to validate the effectiveness of the model. CONCLUSION: These findings underscore the tendency of overestimation of efficacy in early-phase trials involving immunotherapies. The observed differences could be attributed to variations in the inclusion of patients with autoimmune disorders in early-phase trials. These insights have the potential to inform stakeholders in the future development of cancer immunotherapies.

Control Groups in RCTs Supporting Approval of Drugs for Systemic Rheumatic Diseases, 2012-2022.

Importance: Randomized clinical trials (RCTs) testing innovative drugs must strive to use optimal control groups to reflect the best available treatments. A comprehensive evaluation of the quality of control groups in pivotal RCTs supporting systemic rheumatic disease (SRD) drug approvals by the Food and Drug Administration (FDA) is lacking. Objective: To examine the proportion of pivotal RCTs that used optimal control groups among RCTs supporting newly approved SRD drugs in the US over the past decade. Design, Setting, and Participants: In this study, individual RCTs supporting SRD new drug approvals by the FDA between January 2012 and October 2022 were analyzed for design, study duration, control group, and primary end point. The quality of control groups was determined by comparison with published guidelines before and during the trial. Main Outcomes and Measures: The primary measure was the proportion of RCTs using optimal control groups. Differences in response rate between investigating and control groups and the response rate of placebo control groups were also examined. Results: Between January 2012 and October 2022, the FDA approved 44 SRD drugs, involving 65 pivotal RCTs. Overall, 16 RCTs used optimal control groups. In 55 trials, no active groups were used, and more than 80% of these trials were suboptimal (47 trials [85.5%]). Among 56 trials for systemic arthritis, 49 trials used suboptimal control groups, mainly placebo or dose-response controls (47 trials), with a few active controls (2 trials). Studies of other SRDs frequently used placebo or dose-response controls but were considered optimal controls (8 trials). There was significant improvement in response rates of investigating compared with placebo groups, with relative risk mostly exceeding 1.50 (range, 0.90; 95% CI, 0.69-1.17 for anifrolumab to 11.00; 95% CI, 2.69-44.96 for mepolizumab). In all placebo-controlled trials, the median (IQR) response rate in placebo groups was 26.0% (19.2%-32.3%). Conclusions and Relevance: These findings suggest that the quality of control groups in RCTs leading to SRD drug approval needs improvement and that despite challenges in translating scientific theories to clinical scenarios, it is crucial to consistently prioritize efforts to promote appropriate control group selection to ensure the accurate assessment of innovative drug efficacy.

Characteristics of race/ethnicity in trials leading to anti-rheumatic drug approval for inflammatory arthritis by the US Food and Drug Administration.

OBJECTIVE: Presenting the racial/ethnic representation in clinical trials leading to new approvals of inflammatory arthritis (IA) by the US Food and Drug Administration (FDA) to determine the extent of racial/ethnic disparities. METHODS: Pivotal trials supporting the approval of new indications from July 2012 to June 2022 were collected from Drugs@FDA, the FDA-approved drugs database. More details were then identified by searching Pubmed and the National Institutes of Health trials registry. General characteristics of the approved drugs and demographic data for each pivotal trial, especially the race/ethnicity data, were collected. The enrollment profiles of each race/ethnicity were analyzed and then compared with the 2020 US census data. RESULTS: From 2012 to 2022, 34 new approvals were identified based on 59 clinical trials. The Black was consistently underrepresented in all subtypes of IA and drugs, while the White was overrepresented compared to the 2020 US census data. For Asian and Hispanic participants, these pivotal trials presented relatively heterogeneities in enrollments. As for the trends over time, increased involvements of White were still observed in rheumatoid arthritis (RA), psoriatic arthritis, and spondyloarthritis, while increased involvements of Black and decreased enrollments of Asian and Hispanic were only observed in RA. CONCLUSIONS: Despite many efforts to eliminate racial/ethnic disparities, the Black was consistently underrepresented in pivotal clinical trials compared to the 2020 US national race/ethnicity distribution data. The White was consistently overrepresented, and the Hispanic presented heterogeneous results. No evident time trend was observed.

Evolution of drug regulations and regulatory innovation for anticancer drugs in China.

Over the past two decades, China has introduced significant changes to drug regulations through regulatory innovations to accelerate drug review and approvals, keeping in line with the rapidly growing scientific innovation in drug research and development (R&D). In this study, we outlined the revolution of drug regulation in China since the establishment of the State Drug Administration in 1998. More particularly, we performed a comprehensive analysis of newly approved anticancer drugs in China from the year 2005 to May 2021, as a powerful illustration of how the revolution has changed the drug R&D landscape. Innovative drug development in China has boomed, benefiting in particular from pro-innovation policies as well as expedited program designations by the authority. We found a significant increase in the number of both imported and domestic new anticancer drugs from 2005 to 2021, with the emergence of drugs with novel mechanisms of action, including immune checkpoint inhibitors and cell therapy products. Drug lag has also been dramatically shortened by more than 70% for imported drugs in years 2016-2020 compared to years 2006-2010. Furthermore, we provide an insight into the potential approaches to further optimize the science-based and clinical value-based regulatory and R&D drug ecosystem in China. This review provides evidence of significant impacts of regulations and policies on drug R&D and suggests that the constantly adapting regulatory ecosystem will speed up drug development in China and worldwide.