A Novel Prediction Model of Prognosis After Gastrectomy for Gastric Carcinoma Development and Validation Using Asian Databases
- Authors
- Woo, Yanghee; Son, Taeil; Song, Kijun; Okumura, Naoki; Hu, Yanfeng; Cho, Gyu-Seok; Kim, Jong Won; Choi, Seung-Ho; Noh, Sung Hoon; Hyung, Woo Jin
- Issue Date
- Jul-2016
- Publisher
- LIPPINCOTT WILLIAMS & WILKINS
- Keywords
- gastrectomy; nomogram; staging; stomach neoplasm
- Citation
- ANNALS OF SURGERY, v.264, no.1, pp 114 - 120
- Pages
- 7
- Journal Title
- ANNALS OF SURGERY
- Volume
- 264
- Number
- 1
- Start Page
- 114
- End Page
- 120
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/68427
- DOI
- 10.1097/SLA.0000000000001523
- ISSN
- 0003-4932
1528-1140
- Abstract
- Objective: The prognoses of gastric cancer patients vary greatly among countries. Meanwhile, tumor-node-metastasis (TNM) staging system shows limited accuracy in predicting patient-specific survival for gastric cancer. The objective of this study was to create a simple, yet universally applicable survival prediction model for surgically treated gastric cancer patients. Summary Background Data: A prediction model of 5-year overall survival for surgically treated gastric cancer patients regardless of curability was developed using a test data set of 11,851 consecutive patients. Methods: The model's coefficients were selected based on univariate and multivariate analysis of patient, tumor, and surgical factors shown to significantly impact survival using a Cox proportional hazards model. For internal validation, discrimination was calculated with the concordance index (C-statistic) using the bootstrap method and calibration assessed. The model was externally validated using 4 data sets from 3 countries. Results: Our model's C-statistic (0.824) showed better discrimination power than current tumor-node-metastasis staging (0.788) (P < 0.0001). Bootstrap internal validation demonstrated that coefficients remained largely unchanged between iterations, with an average C-statistic of 0.822. The model calibration was accurate in predicting 5-year survival. In the external validation, C-statistics showed good discrimination (range: 0.798-0.868) in patient data sets from 4 participating institutions in 3 different countries. Conclusions: Utilizing clinically practical patient, tumor, and surgical information, we developed a universally applicable prediction model for accurately determining the 5-year overall survival of gastric cancer patients after gastrectomy. Our predictive model was also valid in patients who underwent noncurative resection or inadequate lymphadenectomy.
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