Development and Validation of a Predictive Model for Gastric Cancer Based on the Albumin-to-Neutrophil-to-Lymphocyte Ratio: A Retrospective Cohort Study

Objective This study aims to examine the correlation between ANLR and OS, PFS in patients diagnosed with gastric cancer, with the goal of elucidating its predictive value and clinical relevance. Method A retrospective analysis was conducted on clinical case data from 2,051 patients who underwent radical gastrectomy for gastric cancer between 2012 and 2021, as recorded in the INSCOC database. Determine the optimal cut-off value of ANLR through the ROC curve. The survival curve was generated using the Kaplan-Meier method, the Cox proportional hazards regression model was utilized to analyze the association between ANLR and both OS and PFS. The nomogram prognostic model was constructed, with internal and external validations performed through ROC curve, calibration curve and DCA to evaluate the model's performance. Result This study ultimately included 1766 patients, with 1203 patients in the internal validation cohort and 563 patients in the external validation cohort. The optimal cutoff value of ANLR was 20.39. Patients with high ANLR (≥ 20.39) had better OS and PFS than those with low ANLR (< 20.39). Multivariate Cox regression showed that ANLR was an independent prognostic factor for OS (HR = 0.623, 95% CI: 0.490–0.792, p < 0.001) and PFS (HR = 0.589, 95% CI: 0.439–0.791, p < 0.001). The Nomogram model predicted OS and PFS with AUCs of 0.660 and 0.710. The external validation showed good calibration and discriminatory efficacy (C-index: OS 0.664, PFS 0.883). Conclusion The ANLR can serve as an effective biomarker for the prognostic assessment of patients with gastric cancer. The nomogram model is beneficial for individualized prognostic prediction and clinical decision-making.