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已发表论文

用于预测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

 

Authors Yang L , Li H , Xia M , Pu X 

Received 17 February 2025

Accepted for publication 25 April 2025

Published 22 May 2025 Volume 2025:18 Pages 6491—6504

DOI http://doi.org/10.2147/JIR.S519724

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Professor Ning Quan

Lingbing Yang,1,* Hongwei Li,2,* Mingyu Xia,3 Xiaomeng Pu4 

1Department of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, People’s Republic of China; 2Department of Gastrointestinal Surgery, Harbin Medical University Cancer Hospital, Harbin, People’s Republic of China; 3Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, Harbin, People’s Republic of China; 4School of Stomatology, Gansu Health Vocational College, Lanzhou, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Xiaomeng Pu, Email 1176959368@qq.com

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.

Keywords: gastric cancer, immune checkpoint inhibitors, prognosis, immune-inflammatory markers

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