Abstract:
Objective Development and validation of a novel nomogram model to predict the long-term prognosis of patients with advanced gastric cancer.
Methods We conducted a retrospective analysis of clinical and follow-up data taken from patients at Fujian Medical University Union Hospital (132 cases) and the Affiliated Hospital of Qinghai University (45 cases) who underwent NAC followed by radical gastrectomy from January 2010 to December 2018. A radiomic signatures clinical nomogram (RS-CN) was established based on CT-RS. The prediction performance of the RS-CN was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC values), time-dependent ROC, and C-index.
Results In the training cohort, RS-CN yielded good predictive performance for OS in AGC patients as evaluated using C-Index (0.72); the AUC of RS-CN was significantly better than that of TRG classification (P=0.019) and was comparative to ypTNM stage (P=0.786). The validation cohort yielded similar outcomes. In both the training and validation cohorts, time-dependent ROC curves showed that RS-CN consistently outperformed TRG classification and ypTNMstage. The 3-year overall survival (OS) and disease-free survival (DFS) of patients in the low-risk group (RS-CN score ≤288.4) was significantly better than that of patients in the high-risk group (RS-CN score >288.4). Adjuvant chemotherapy (AC) significantly improved 3-year DFS in only the high-risk group (both P<0.05) but did not cause significant differences in 3-year OS (P=0.099).
Conclusions Compared with traditional ypTNM staging, our study developed nomogram based on CT-RS before NAC can help identify patients who may benefit from NAC and AC, providing a guide to facilitate precise NAC for AGC.
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