Novel Composite Scoring System for Predicting Prognosis in Stage IV Gastric Cancer Patients Treated with Immune Checkpoint Inhibitors

一种用于预测接受免疫检查点抑制剂治疗的IV期胃癌患者预后的新型综合评分系统

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Abstract

BACKGROUND: Gastric cancer (GC) with distant metastases has a poor prognosis, and immune checkpoint inhibitors (ICIs) effectively improve the survival time of patients with this disease. This study aimed to identify effective prognostic markers that can predict the treatment effect of ICIs in patients with stage IV GC. METHODS: This study included 256 patients with GC with distant metastases who had received treatment with ICIs. A receiver operating characteristic (ROC) curve was used to analyze the predictive ability and optimal cutoff values of immune-inflammatory markers. Kaplan‒Meier survival curves were used to analyze the differences in progression-free survival (PFS) and overall survival (OS) among patients. Cox proportional hazard regression analysis was used to identify independent prognostic factors for PFS and OS. RESULTS: By comparing the area under the ROC curve (AUC) of immune-inflammatory markers, we selected the preoperative platelet count/(lymphocyte count × prealbumin count) ratio and fibrinogen/albumin ratio to form a combined score (PLPR-FAR score). The ROC curve revealed that when the PLPR-FAR score was used to predict patient PFS and OS, the AUC were 0.614 and 0.672, respectively. The Kaplan‒Meier survival curve revealed that patients with higher PLPR-FAR scores had significantly shorter PFS and OS than those with lower PLPR-FAR scores. Cox proportional hazard regression analysis revealed that the PLPR-FAR score was an independent risk factor for PFS and OS in stage IV GC patients. CONCLUSION: The PLPR-FAR score may help identify which patients are more likely to benefit from ICIs treatment, and could serve as a novel and promising prognostic biomarker.

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