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Development and validation of a nomogram based on CT images and 3D texture analysis for preoperative prediction of the malignant potential in gastrointestinal stromal tumors.

ABSTRACT: BACKGROUND:Gastrointestinal stromal tumors (GISTs), which are the most common mesenchymal tumors of the digestive system, are treated varyingly according to the malignancy. The purpose of this study is to develop and validate a nomogram for preoperative prediction of the malignant potential in patients with GIST. METHODS:A total of 440 patients with pathologically confirmed GIST after surgery in our hospital from January 2011 to July 2019 were retrospectively analyzed. They were randomly divided into the training set (n?=?308) and validation set (n?=?132). CT signs and texture features of each patient were analyzed and predictive model were developed using the least absolute shrinkage and selection operator (lasso) regression. Then a nomogram based on selected parameters was developed. The predictive effectiveness of nomogram was evaluated by the area under receiver operating characteristic (ROC) curve (AUC). Concordance index (C-index) and calibration plots were formulated to evaluate the reliability and accuracy of the nomogram by bootstrapping based on internal (training set) and external (validation set) validity. The clinical application value of the nomogram was determined through the decision curve analysis (DCA). RESULTS:Totally 156 GIST patients with low-malignant (very low and low risk) and 284 ones with high-malignant potential (intermediate and high risk) are enrolled in this study. The prediction nomogram consisting of size, cystoid variation and meanValue had an excellent discrimination both in training and validation sets (AUCs (95% confidence interval(CI)): 0.935 (0.908, 0.961), 0.933 (0.892, 0.974); C-indices (95% CI): 0.941 (0.912, 0.956), 0.935 (0.901, 0.982); sensitivity: 81.4, 90.6%; specificity: 75.0, 75.7%; accuracy: 88.0, 88.6%, respectively). The calibration curves indicated a good consistency between the actual observation and nomogram prediction for differentiating GIST malignancy. Decision curve analysis demonstrated that the nomogram was clinically useful. CONCLUSION:This study presents a prediction nomogram that incorporates the CT signs and texture parameter, which can be conveniently used to facilitate the preoperative individualized prediction of malignancy in GIST patients.

SUBMITTER: Ren C

PROVIDER: S-EPMC6958787 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Development and validation of a nomogram based on CT images and 3D texture analysis for preoperative prediction of the malignant potential in gastrointestinal stromal tumors.

Ren Caiyue C Wang Shengping S Zhang Shengjian S

Cancer imaging : the official publication of the International Cancer Imaging Society 20200113 1

<h4>Background</h4>Gastrointestinal stromal tumors (GISTs), which are the most common mesenchymal tumors of the digestive system, are treated varyingly according to the malignancy. The purpose of this study is to develop and validate a nomogram for preoperative prediction of the malignant potential in patients with GIST.<h4>Methods</h4>A total of 440 patients with pathologically confirmed GIST after surgery in our hospital from January 2011 to July 2019 were retrospectively analyzed. They were r ...[more]

PMID: 31931874

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Project description:Preoperative imatinib mesylate therapy for gastrointestinal stromal tumors (GISTs) is controversial. This study aimed to explore the clinical efficacy and optimal duration of preoperative imatinib mesylate (IM) therapy in patients with locally advanced and recurrent/metastatic GISTs. We retrospectively examined patients who received preoperative imatinib mesylate therapy from January 2013 to December 2018 at Xiangya Hospital, Central South University and the Second Xiangya Hospital of Central South University, China. Clinical data, including the results of tests for mutations in KIT and PDGFR, findings from regularly conducted re-examinations, abdominal-enhanced computed tomography/magnetic resonance imaging data, responses to imatinib, progression-free survival, and overall cancer-specific survival, were recorded. A total of 25 patients were enrolled in our study, including 18 with a locally advanced GIST and 7 with recurrent or metastatic GISTs. Their ages ranged from 22 to 70?years (M:F = 1.6:0.9), with a mean age of 50.48 ± 12.51?years. The tumor locations included the stomach (56.0%), rectum (16.0%), enterocoelic/retroperitoneal sites (12.0%), and the small intestine (12.0%). Based on testing for mutations in KIT and PDGFR, 22 patients received 400?mg/day KIT, and 3 patients received 600?mg/day PDGFR. The median duration of preoperative IM therapy was 8.96 ± 4.81?months, ranging from 3 to 26?months. According to the Choi criteria, 24 patients achieved a partial response (PR), and 1 patient had stable disease (SD). All patients underwent surgery after preoperative IM therapy, and no postoperative complications appeared. The 2-year PFS and 5-year PFS were 92% and 60%, respectively, and the total 5-year cancer-specific survival (CSS) was 92%. Preoperative imatinib therapy is feasible for locally advanced and recurrent/metastatic GISTs and can effectively shrink the tumor size, allow organ sparing, and avoid extensive organ resection. Moreover, the optimal duration of preoperative IM therapy in patients with locally advanced and recurrent/metastatic GISTs was 8.96 ± 4.81?months, ranging from 3 to 26?months, and gastric GISTs had a better response to preoperative IM therapy than did non-gastric GISTs.

Dataset Information

Development and validation of a nomogram based on CT images and 3D texture analysis for preoperative prediction of the malignant potential in gastrointestinal stromal tumors.

Publications

Development and validation of a nomogram based on CT images and 3D texture analysis for preoperative prediction of the malignant potential in gastrointestinal stromal tumors.

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