A practical prognostic peripheral blood-based risk model for the evaluation of the likelihood of a response and survival of metastatic cancer patients treated with immune checkpoint inhibitors

Abstract

Background: Less than half of unselected metastatic cancer patients benefit from the immune checkpoint inhibitor (ICI) therapy. Systemic cancer-related inflammation may influence the efficacy of ICIs and thus, systemic inflammatory markers could have prognostic and/or predictive potential in ICI therapy. Here, we aimed to identify a combination of inflammation-related laboratory parameters to establish a practical prognostic risk model for the pretreatment evaluation of a response and survival of ICI-treated patients with different types of metastatic cancers.

Methods: The study-cohort consisted of a real-world patient population receiving ICIs for metastatic cancers of different origins (n = 158). Laboratory parameters determined before the initiation of the ICI treatment were retrospectively collected. Six inflammation-related parameters i.e., elevated values of neutrophils, platelets, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR) and lactate dehydrogenase (LDH), and the presence of anemia, were each scored with one point, giving 0-6 risk points for each patient. The patients with information of all these six parameters (n = 109) were then stratified into low-risk (0-3 points) and high-risk (4-6 points) groups. The overall response rate (ORR), overall survival (OS), and progression-free survival (PFS) according to the risk scores were determined.

Results: The risk model was strongly associated with the outcome of the patients. The ORR to ICI treatment in the high-risk group was 30.3% in comparison to 53.9% in the low-risk group (p = 0.023). The medians for OS were 10.0 months and 27.3 months, respectively (p < 0.001), and the corresponding medians for PFS were 3.9 months and 6.3 months (p = 0.002). The risk group remained as a significant prognostic factor for both OS (HR 3.04, 95% CI 1.64-5.64, p < 0.001) and PFS (HR 1.79, 95% CI 1.04-3.06, p = 0.035) in the Cox multivariate analyses.

Conclusions: We propose a readily feasible, practical risk model consisted of six inflammation-related laboratory parameters as a tool for outcome prediction in metastatic cancer patients treated with ICIs. The risk model was strongly associated with the outcome of the patients in terms of all the evaluated indicators i.e., ORR, OS and PFS. Yet, further studies are needed to validate the risk model.

Keywords: ICI; Immune checkpoint inhibitor; Inflammation; Predictive; Prognostic; cancer.