Yanghee Woo1, Taeil Son, Kijun Song, Naoki Okumura, Yanfeng Hu, Gyu-Seok Cho, Jong Won Kim, Seung-Ho Choi, Sung Hoon Noh, Woo Jin Hyung. 1. *Department of Surgery, Columbia University College of Physicians and Surgeons, New York, NY†Department of Surgery, Eulji University School of Medicine, Seoul, Republic of Korea‡Department of Biostatistics, Yonsei University College of Medicine, Seoul, Republic of Korea§Department of Surgical Oncology, Gifu University School of Medicine, Gifu, Japan¶Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China||Department of Surgery, Soonchunhyang University, Bucheon, Republic of Korea**Department of Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea††Gastric Cancer Center, Yonsei Cancer Hospital, Yonsei University Health System, Seoul, Republic of Korea‡‡Robot and MIS Center, Severance Hospital, Yonsei University Health System, Seoul, Republic of Korea.
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.
OBJECTIVE: The prognoses of gastric cancerpatients 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 cancerpatients. SUMMARY BACKGROUND DATA: A prediction model of 5-year overall survival for surgically treated gastric cancerpatients 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 cancerpatients after gastrectomy. Our predictive model was also valid in patients who underwent noncurative resection or inadequate lymphadenectomy.
Authors: H G van den Boorn; E G Engelhardt; J van Kleef; M A G Sprangers; M G H van Oijen; A Abu-Hanna; A H Zwinderman; V M H Coupé; H W M van Laarhoven Journal: PLoS One Date: 2018-02-08 Impact factor: 3.240
Authors: Sung Hoon Kim; Bong Il Song; Hae Won Kim; Kyoung Sook Won; Young Gil Son; Seung Wan Ryu Journal: Korean J Radiol Date: 2020-07 Impact factor: 3.500