Abstract
BACKGROUND: Programmed cell death protein 1 (PD-1) blockade-based therapies have become the new standard for first-line treatment of metastatic gastric cancer (mGC), but a lack of effective prognostic models hinders precise risk stratification in patients receiving this treatment. We aimed to develop an intuitive prognostic nomogram for human epidermal growth factor receptor 2 (HER2)-negative mGC patients receiving first-line anti-PD-1 therapies. PATIENTS AND METHODS: We conducted a retrospective study and collected baseline clinicopathological characteristics of patients with HER2-negative mGC receiving first-line PD-1 blockade-based therapies from October 2018 to July 2024. Cox regression models were utilized to determine independent prognostic factors. Time-dependent receiver operating characteristic (ROC) curves with area under the curves (AUCs), calibration plots and decision curve analyses (DCAs) were used to validate the nomogram. RESULTS: A total of 714 patients were included in the training cohort and 180 in the validation cohort. After univariate and multivariate Cox regression analyses, Eastern Cooperative Oncology Group performance status, pleural or peritoneal metastases, Lauren type, C-reactive protein and elevated lactate dehydrogenase were identified as independent prognostic factors associated with both progression-free survival (PFS) and overall survival (OS), and were used to develop a prognostic nomogram based on OS in the training cohort. The nomogram showed reasonable discrimination and good calibration in both the training and validation cohorts. Time-dependent ROC and DCAs indicated superior performance of the nomogram to programmed death-ligand 1 combined positive score and several previously reported models. Three risk groups were stratified according to the nomogram scores. Whether in the training or the validation cohort, patients in the intermediate- and high-risk groups had significantly inferior PFS and OS compared with those in the low-risk group (all P < 0.001). The risk stratification was significantly associated with disease control rates. Nevertheless, external validation is needed in the future for the generalizability of the nomogram. CONCLUSIONS: The nomogram provided personalized survival prediction for patients with HER2-negative mGC receiving first-line PD-1 blockade-based therapies and enabled prognostic stratification to identify patients with different survival risks.