Development and Validation of an Inflammation-Combined Prognostic Index (ICPI)-Based Nomogram for Predicting Overall Survival in Gastric Cancer

建立和验证基于炎症联合预后指数(ICPI)的列线图预测胃癌患者的总生存期

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Abstract

PURPOSE: This study aims to investigate the correlation between a novel integrated inflammatory marker: The inflammation-combined prognostic index (ICPI), combining NLR, PLR, and MLR, with the clinicopathological characteristics and overall survival (OS) of gastric cancer (GC). PATIENTS AND METHODS: Data from 876 patients with GC were retrospectively analyzed from January 1, 2017, to April 30, 2023. PSM was employed to mitigate confounding factors between groups. Receiver operating characteristic (ROC) curves were utilized to determine the optimal cutoff value. Univariate, LASSO, and multivariate regression analyses were executed. Subsequently, a nomogram for predicting OS was developed and validated. RESULTS: The cohort with a poor prognosis exhibited significantly elevated levels of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and ICPI (P<0.001). Similarly, higher levels of NLR, PLR, MLR, and ICPI were associated with a poorer prognosis (P<0.001). Following regression analysis, ICPI, T-stage, lymph node ratio (LNR), and primary site were identified as independent risk factors affecting OS. A nomogram was constructed based on these factors to predict 1-, 3-, and 5-year OS, yielding C-indexes of 0.8 and 0.743 for the training and validation sets, respectively. The calibration curves demonstrated close alignment between predicted and actual results, indicating high predictive accuracy. Moreover, the decision curve underscored the practical utility of the model. CONCLUSION: The new inflammatory parameter ICPI integrates NLR, PLR and MLR. The ICPI-based nomogram and web calculator accurately predict OS in patients with GC.

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