Abstract
BACKGROUND: Although the number of clinical trials on lung cancer is rapidly increasing, the clinical benefits have not received sufficient attention. This study aims to assess the clinical benefits and estimate the minimal clinically important differences (MCIDs) for overall survival (OS) and progression-free survival (PFS) to provide quantitative guidance for treatment decisions and study design in lung cancer trials. METHODS: This study systematically searched lung cancer randomized controlled trials (RCTs) from PubMed, Embase, and the Cochrane Library. The clinical benefits were estimated using the frameworks of the European Society for Medical Oncology - Magnitude of Clinical Benefit Scale (ESMO-MCBS) and the American Society of Clinical Oncology - Value Framework (ASCO-VF). The MCIDs for OS and PFS were calculated using the distribution-based method. The differences in clinical benefits of lung cancer trials between the MCIDs and the two frameworks were compared. RESULTS: A total of 319 lung cancer RCTs were included. The mean improved OS and PFS were 2.28 and 1.76 months between the interventional and control groups, respectively. Around 15.79% of trials with OS as the primary endpoint were rated as grades 4 or above, and only 6.02% of trials with PFS as the primary endpoint reached grade 4 by ESMO-MCBS. The overall MCIDs for OS and PFS in non-small cell lung cancer (NSCLC) were 7.66 and 3.11 months, while 2.29 and 1.13 months in small cell lung cancer (SCLC), respectively. A total of 79.61% of RCTs evaluating OS (5.92% with clinical benefits and 73.68% without clinical benefits) and 68.26% evaluating PFS (3.59% with clinical benefits and 64.67% without clinical benefits) were consistently identified as reaching clinical benefits by the MCIDs and two frameworks. CONCLUSIONS: Although lung cancer RCTs showed statistically significant improvement in OS and PFS, most trials did not show clinical benefits, with a limited increase in survival months. A fair-to-moderate consistency of clinical benefits classification was observed between the MCIDs and the two frameworks. Further explorations into MCID are anticipated to deepen our understanding and promote its application in the future.