A Novel Prediction Model of Prognosis After Gastrectomy for Gastric Carcinoma Development and Validation Using Asian Databases
DC Field | Value | Language |
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dc.contributor.author | Woo, Yanghee | - |
dc.contributor.author | Son, Taeil | - |
dc.contributor.author | Song, Kijun | - |
dc.contributor.author | Okumura, Naoki | - |
dc.contributor.author | Hu, Yanfeng | - |
dc.contributor.author | Cho, Gyu-Seok | - |
dc.contributor.author | Kim, Jong Won | - |
dc.contributor.author | Choi, Seung-Ho | - |
dc.contributor.author | Noh, Sung Hoon | - |
dc.contributor.author | Hyung, Woo Jin | - |
dc.date.accessioned | 2023-11-06T06:47:42Z | - |
dc.date.available | 2023-11-06T06:47:42Z | - |
dc.date.issued | 2016-07 | - |
dc.identifier.issn | 0003-4932 | - |
dc.identifier.issn | 1528-1140 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/68427 | - |
dc.description.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. | - |
dc.format.extent | 7 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | LIPPINCOTT WILLIAMS & WILKINS | - |
dc.title | A Novel Prediction Model of Prognosis After Gastrectomy for Gastric Carcinoma Development and Validation Using Asian Databases | - |
dc.type | Article | - |
dc.identifier.doi | 10.1097/SLA.0000000000001523 | - |
dc.identifier.bibliographicCitation | ANNALS OF SURGERY, v.264, no.1, pp 114 - 120 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.wosid | 000377769600021 | - |
dc.identifier.scopusid | 2-s2.0-84960157536 | - |
dc.citation.endPage | 120 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 114 | - |
dc.citation.title | ANNALS OF SURGERY | - |
dc.citation.volume | 264 | - |
dc.type.docType | Article; Proceedings Paper | - |
dc.publisher.location | 미국 | - |
dc.subject.keywordAuthor | gastrectomy | - |
dc.subject.keywordAuthor | nomogram | - |
dc.subject.keywordAuthor | staging | - |
dc.subject.keywordAuthor | stomach neoplasm | - |
dc.subject.keywordPlus | DISEASE-SPECIFIC SURVIVAL | - |
dc.subject.keywordPlus | STAGING SYSTEM | - |
dc.subject.keywordPlus | EXTERNAL VALIDATION | - |
dc.subject.keywordPlus | 7TH EDITION | - |
dc.subject.keywordPlus | CANCER | - |
dc.subject.keywordPlus | RESECTION | - |
dc.subject.keywordPlus | NOMOGRAM | - |
dc.subject.keywordPlus | CLASSIFICATION | - |
dc.subject.keywordPlus | RECURRENCE | - |
dc.subject.keywordPlus | NUMBER | - |
dc.relation.journalResearchArea | Surgery | - |
dc.relation.journalWebOfScienceCategory | Surgery | - |
dc.description.journalRegisteredClass | sci | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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