Previous trials indicated that immune checkpoint inhibitors (ICIs) have improved advanced cancer patients’ overall survival (OS). However, the value of progression-free survival (PFS) as a surrogate for OS is controversial.
The individual patient data from POPLAR (NCT01903993), OAK (NCT02008227), CA209-038 trials (NCT01621490), and Sun Yat-sen Memorial Hospital cohort (SYSMH cohort). The phase II and phase III randomized controlled trials (RCTs) were included up to September 2020. The primary endpoint was to estimate correlations between PFS and OS. Pearman’s r was used to measure the correlation between PFS and OS, the 95% confidence interval (CI) of r was obtained by bootstrap method with 1000 replications. R2 was use to describe the accuracy of model. Subgroup analysis according to the tumor type, treatment and treat-line.
In the ICIs group, there was strong correlation between PFS and OS (r = 0.903 [95% CI 0.872-0.903], P < 0.001), and the training model for estimated OS by PFS was: OS = 1.828*PFS + 5.9758 (R2 = 0.8146) based on POPLAR and OAK trials (n=569, non-small cell lung cancer [NSCLC]). Correlation between predicted and observed OS was validated in the SYSMH cohort (n = 51, r = 0.790, P < 0.001, NSCLC) and CA209-038 trial (n = 73, r = 0.648, P < 0.001, melanoma). Correlation between predicted and observed median OS was validated in the subgroup analysis of NSCLC (22 RCTs, r= 0.867, P < 0.001), pancancer (53 RCTs, r = 0.601, P < 0.001), ICIs (39 RCTs, r = 0.765, P < 0.001), ICIs + chemotherapy (20 RCTs, r = 0.464, P = 0.026), first-line (27 RCTs, r = 0.274, P = 0.100), and other line (30 RCTs, r = 0.891, P < 0.001). However, the performance of chemotherapy group was not better than ICIs group.
This study indicated that PFS correlated strongly with OS in pancancer patient with ICIs evaluated by RECIST 1.1, and PFS can be recommended as a surrogate for OS.
Legal entity responsible for the study
Sun Yat-sen Memorial Hospital, Sun Yat-sen University.
National Science and Technology Major Project (2020ZX09201021), Medical Artificial Intelligence Project of Sun Yat-sen Memorial Hospital (YXRGZN201902), National Natural Science Foundation of China (81572596, 81972471, U1601223), Natural Science Foundation of Guangdong Province (2017A030313828), Guangzhou Science and Technology Major Program (201704020131), Guangdong Science and Technology Department (2017B030314026), Special Funds for the Cultivation of Guangdong College Students’ Scientific and Technological Innovation (PDJH2019A0212), National Students’ Innovation and Entrepreneurship Training Program (201910571001), Guangdong Medical University College Students’ Innovation Experiment Project (ZZZF001).
All authors have declared no conflicts of interest.