A web-based prediction model for long-term cancer-specific survival of middle-aged patients with early-stage gastric cancer: a multi-institutional retrospective study.

Autor: Zhang, Simeng, Zheng, Longbo, Zhang, Yuxia, Gao, Yuan, Liu, Lei, Jiang, Zinian, Wang, Liang, Ma, Zheng, Wu, Jinhui, Chen, Jiansheng, Lu, Yun, Wang, Dongsheng
Předmět:
Zdroj: Journal of Cancer Research & Clinical Oncology; Dec2023, Vol. 149 Issue 18, p16551-16561, 11p
Abstrakt: Background: This study constructed and validated a prognostic model to evaluate long-term cancer-specific survival (CSS) in middle-aged patients with early gastric cancer (EGC). Methods: We extracted clinicopathological data from relevant patients between 2004 and 2015 from Surveillance, Epidemiology, and End Results (SEER) database, and randomly divided the patients into a training group (N = 688) and a validation group (N = 292). In addition, 102 Chinese patients were enrolled for external validation. Univariate and multivariate Cox regression models were used to screen for independent prognostic factors, and a nomogram was constructed to predict CSS. We used the concordance index (C-index), calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) to evaluate the predictive performance of the model. Results: Univariate and multivariate COX regression analyses showed that tumor location, differentiation grade, N stage, chemotherapy, and number of regional nodes examined were independent risk factors for prognosis, and these factors were used to construct the nomogram. The C-index of the model in the training cohort, internal validation cohort, and external validation cohort was 0.749 (95% CI 0.699–0.798), 0.744 (95% CI 0.671–0.818), and 0.807 (95% CI 0.721–0.893), respectively. The calibration curve showed that the model had an excellent fit. The DCA curve showed that the model had good predictive performance and practical clinical value. Conclusion: This study developed and validated a new nomogram to predict CSS in middle-aged patients with EGC. The prediction model has unique and practical value and can help doctors carry out individualized treatment and judge prognosis. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
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