Evaluation of Classical Clinical Endpoints As Surrogates for Overall Survival in Patients Treated with Immune Checkpoint Blockers: a Systematic Review and Meta-analysis
Overview
Authors
Affiliations
Purpose: Classical clinical endpoints [e.g., objective response rate (ORR), disease control rate (DCR), and progression-free survival (PFS)] may not be appropriate for immune checkpoint blockers (ICBs). We evaluated correlations between these endpoints and overall survival (OS) for surrogacy.
Methods: Randomized controlled trials (RCTs) of solid tumors patients treated with ICBs published between 01/2005 and 03/2017, and congress proceedings (2014-2016) were included. Arm-level analyses measured 6-month PFS rate to predict 18-month OS rate. Comparison-level analyses measured ORR odds ratio (OR), DCR OR, and 6-month PFS hazard ratio (HR) to predict OS HR. A pooled analysis for single-agent ICBs and ICBs plus chemotherapy vs chemotherapy was conducted. Studies of single-agent ICBs vs chemotherapy were separately analyzed.
Results: 27 RCTs involving 61 treatment arms and 10,300 patients were included. Arm-level analysis showed higher 6- or 9-month PFS rates predicted better 18-month OS rates for ICB arms and/or chemotherapy arms. ICB arms had a higher average OS rate vs chemotherapy for all PFS rates. Comparison-level analysis showed a nonsignificant/weak correlation between ORR OR (adjusted R = - 0.069; P = 0.866) or DCR OR (adjusted R = 0.271; P = 0.107) and OS HR. PFS HR correlated weakly with OS HR in the pooled (adjusted R = 0.366; P = 0.005) and single-agent (adjusted R = 0.452; P = 0.005) ICB studies. Six-month PFS HR was highly predictive of OS HR for single-agent ICBs (adjusted R = 0.907; P < 0.001), but weakly predictive in the pooled analysis (adjusted R = 0.333; P = 0.023).
Conclusions: PFS was an imperfect surrogate for OS. Predictive value of 6-month PFS HR for OS HR in the single-agent ICB analysis requires further exploration.
Yoo S, Fitzgerald C, Cho B, Fitzgerald B, Han C, Koh E Nat Med. 2025; .
PMID: 39762425 DOI: 10.1038/s41591-024-03398-5.
Sheng Y, Teng S, Wang J, Wang H, Tse A CPT Pharmacometrics Syst Pharmacol. 2023; 13(3):437-448.
PMID: 38111189 PMC: 10941555. DOI: 10.1002/psp4.13094.
Statistical considerations in long-term efficacy evaluation of anti-cancer therapies.
Li R, Zhang J, Wang J, Wang J Front Pharmacol. 2023; 14:1265953.
PMID: 37854717 PMC: 10579585. DOI: 10.3389/fphar.2023.1265953.
Kamat A, Apolo A, Babjuk M, Bivalacqua T, Black P, Buckley R J Clin Oncol. 2023; 41(35):5437-5447.
PMID: 37793077 PMC: 10713193. DOI: 10.1200/JCO.23.00307.
Trial Design for Cancer Immunotherapy: A Methodological Toolkit.
Saad E, Coart E, Deltuvaite-Thomas V, Garcia-Barrado L, Burzykowski T, Buyse M Cancers (Basel). 2023; 15(18).
PMID: 37760636 PMC: 10527464. DOI: 10.3390/cancers15184669.