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A preoperative risk prediction model for high malignancy potential gastrointestinal stromal tumors of the stomach.
Kim, Jun Young; Kim, Tae Jun; Lee, Dong Kyu; Min, Yang Won; Lee, Hyuk; Min, Byung-Hoon; Lee, Jun Haeng; An, Ji Yeong; Choi, Min Gew; Sohn, Tae Sung; Bae, Jae Moon; Kim, Hye Seung; Ahn, Joong Hyun; Kim, Jae J.
Affiliation
  • Kim JY; Department of Medicine, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, Korea.
  • Kim TJ; Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea.
  • Lee DK; Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea.
  • Min YW; Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea.
  • Lee H; Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea.
  • Min BH; Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea.
  • Lee JH; Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea.
  • An JY; Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
  • Choi MG; Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
  • Sohn TS; Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
  • Bae JM; Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
  • Kim HS; Statistics and Data Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
  • Ahn JH; Statistics and Data Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
  • Kim JJ; Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Korea. jjkim@skku.edu.
Surg Endosc ; 36(3): 2129-2137, 2022 03.
Article de En | MEDLINE | ID: mdl-33999252
ABSTRACT

BACKGROUND:

Gastric gastrointestinal stromal tumors (GISTs) exhibit various degrees of aggression and malignant potential. However, no systematic preoperative evaluation strategy to predict the malignancy potential of gastric GISTs has yet been developed. This study aimed to develop a reliable and easy-to-use preoperative risk-scoring model for predicting high malignancy potential (HMP) gastric GISTs.

METHODS:

The data of 542 patients with pathologically confirmed gastric GISTs who underwent resection were reviewed. Multivariate logistic regression analysis was used to identify significant predictors of HMP. The risk-scoring system (RSS) was based on the predictive factors for HMP, and its performance was validated using a split-sample approach.

RESULTS:

A total of 239 of 542 (44.1%) surgically resected gastric GISTs had HMP. Multivariate analysis demonstrated that tumor size, location, and surface changes were independent risk factors for HMP. Based on the accordant regression coefficients, the presence of surface ulceration was assigned 1 point. Tumor sizes of 4-6 cm and > 6 cm were assigned 2 and 5 points, respectively. Two points were assigned to cardia or fundus locations. A score of 3 points was the optimal cut-off value for HMP prediction. HMP were found in 19.8% and 82.7% of the low and high-risk groups of the RSS, respectively. The area under the receiver-operating characteristic curve for predicting HMP was 0.81 (95% confidence interval (CI) 0.75-0.86). Discrimination was good after validation (0.75, 95% CI 0.69-0.81).

CONCLUSION:

This simple RSS could be useful for predicting the malignancy potential of gastric GISTs and may aid preoperative clinical decision making to ensure optimal treatment.
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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Tumeurs de l'estomac / Tumeurs stromales gastro-intestinales Type d'étude: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limites: Humans Langue: En Journal: Surg Endosc Sujet du journal: DIAGNOSTICO POR IMAGEM / GASTROENTEROLOGIA Année: 2022 Type de document: Article

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Tumeurs de l'estomac / Tumeurs stromales gastro-intestinales Type d'étude: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limites: Humans Langue: En Journal: Surg Endosc Sujet du journal: DIAGNOSTICO POR IMAGEM / GASTROENTEROLOGIA Année: 2022 Type de document: Article