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Gastrointestinal stromal tumours: Preoperative imaging features to predict recurrence after curative resection
- Title
- Gastrointestinal stromal tumours: Preoperative imaging features to predict recurrence after curative resection
- Authors
- Jung, Haerang; Lee, Sang Min; Kim, Young Chul; Byun, Jieun; Park, Jin Young; Oh, Bo Young; Kwon, Mi Jung; Kim, Jeehyoung
- Ewha Authors
- 변지은
- SCOPUS Author ID
- 변지은
- Issue Date
- 2022
- Journal Title
- EUROPEAN JOURNAL OF RADIOLOGY
- ISSN
- 0720-048X
1872-7727
- Citation
- EUROPEAN JOURNAL OF RADIOLOGY vol. 149
- Keywords
- Gastrointestinal stromal tumours; Computed tomography; Logistic models; Nomograms; Postoperative recurrence
- Publisher
- ELSEVIER IRELAND LTD
- Indexed
- SCIE; SCOPUS
- Document Type
- Article
- Abstract
- Purpose: To identify whether preoperative factors could predict the recurrence after curative resection of gastrointestinal stromal tumours (GISTs) and evaluate the performance of a prediction model using preoperative factors for GIST recurrence compared to a model using preoperative/postoperative factors. Method: This retrospective study included patients who underwent curative resection and preoperative CT for GIST. CT imaging features as preoperative factors were analysed by two abdominal radiologists. Modified National Institutes of Health scores were accessed as a postoperative factor. Multiple logistic regression analysis was performed to assess the preoperative and postoperative factors in predicting GIST recurrence. Through the logistic regression, two prediction models using preoperative factors only and both preoperative/postoperative factors were constructed, respectively. The internal validation of the prediction models was performed using bootstrapping sampling. Results: Data in 113 patients were evaluated. Among them, 14 patients had recurrence. The multiple logistic regression analysis demonstrated that non-gastric location (odds ratio [OR] = 5.12, p = 0.029), ill-defined margin (OR = 4.93, p = 0.023), and prominent vessels around tumour (OR = 6.78, p = 0.007) were significant factors. The prediction models using these preoperative factors and adding a postoperative factor showed an area under the receiver operating characteristic curve of 0.863 and 0.897, respectively, which were not statistically different. The bootstrapping sampling showed the two models were valid. Conclusion: The prediction model derived from non-gastric location, ill-defined margin, and prominent vessels around tumour can be used preoperatively to estimate the risk of recurrence after resection of GIST.
- DOI
- 10.1016/j.ejrad.2022.110193
- Appears in Collections:
- 의과대학 > 의학과 > Journal papers
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