C-reactive protein as a response biomarker to immune checkpoint blockade: A meta-analysis.

Abstract

2559 Background: Tumor-promoting inflammation is a hallmark of cancer pathogenesis and is associated with poor outcomes and treatment resistance. C-reactive protein (CRP) is a routinely measured acute phase reactant whose synthesis is stimulated by cytokines and may thereby represent a surrogate for tumor promoting inflammation. Pre-treatment CRP has been associated with resistance to immune checkpoint blockade (ICB) in several studies. However, whether post-treatment changes in CRP correlate with ICB outcomes has not been systematically examined. Methods: We performed a systematic review to identify cohort studies or clinical trials in solid tumor patients receiving ICB therapy with CRP response comparator pairs (high/low) available. We included studies that had hazard ratio (HR) of overall survival (OS), progression-free survival (PFS), or odds ratio (OR) of objective response rate (ORR) available. We performed a meta-analysis using a random-effect model to evaluate if post-treatment changes in CRP are associated with ORR, PFS, or OS. Subgroup analysis for primary cancer type was performed. Heterogeneity was assessed using the I-squared statistic. Results: We screened 691 eligible studies; 19 met inclusion criteria and 2,101 patients were included. Patients experiencing post-ICB declines in CRP had improved ORR HR=4.67 [95% CI] [2.81-7.78] (p<0.0001, I2=42%), PFS HR=2.47 [1.98-3.09] (p<0.0001, I2=18%), and OS HR=2.28 [1.68-3.08] (p<0.0001, I2=56%). Heterogeneity among subgroups was low in ORR (I2=14.6%) and PFS analysis ( I2=0%), and moderate in OS analysis (I2=64.2%). Conclusions: In patients receiving ICB therapy, post-treatment declines in CRP were associated with improved ORR, PFS, and OS across multiple histologies. These findings support the integration of on-treatment CRP decline as a clinically relevant response biomarker for novel therapies directed at modulating tumor-promoting inflammation. A meta-regression analysis will help determine optimal post-treatment CRP cutpoints. Pooled OR of ORR [95%CI] and HR [95%CI] of PFS and OS with subgroup analysis results and heterogeneity assessment. [Table: see text]