Clinical and VASARI Features to Predict CDKN2A/B Homozygous Deletion in IDH -Mutant Astrocytomas: A Multicenter Study
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND AND PURPOSE: Cyclin-dependent kinase inhibitor (CDKN)2A/B homozygous deletion holds an important value in the prognostic analysis of isocitrate dehydrogenase (IDH)-mutant astrocytomas. This study aimed to develop and validate a prediction model based on clinical and Visually AcceSAble Rembrandt Images (VASARI) MRI features for identifying CDKN2A/B homozygous deletion status in IDH-mutant astrocytomas. MATERIALS AND METHODS: Preoperative MR images of 122 patients with astrocytoma (101 without CDKN2A/B homozygous deletion, and 21 with CDKN2A/B homozygous deletion) were retrospectively collected as a training set. Eighteen patients with astrocytomas from another center (14 without CDKN2A/B homozygous deletion, and 4 with CDKN2A/B homozygous deletion) were enrolled as an external test set. VASARI features in MR images of patients with astrocytoma were evaluated by radiologists. Prediction models for identifying CDKN2A/B homozygous deletion status based on clinical and VASARI features were constructed by using logistic regression. RESULTS: Multivariate regression analysis showed that definition of enhancing margin (OR: 13.19, P = .003) was an independent predictor of CDKN2A/B homozygous deletion in IDH-mutant astrocytomas. The area under the curve of prediction model in the training set and external test set was 0.84 (95% CI, 0.73–0.96) and 0.96 (95% CI, 0.86–1.00), respectively. The optimal cutoff value of the nomogram calculated by using the Youden index was 124.20 points. Under the cutoff value, the prediction model exhibited 85% accuracy, 67% sensitivity, and 88% specificity in the training set, and 83% accuracy, 75% sensitivity, and 86% specificity in external test set. CONCLUSIONS: The nomogram model based on clinical and VASARI MRI features was useful for prediction of CDKN2A/B homozygous deletion status in IDH-mutant astrocytomas.
DOI: 10.3174/ajnr.a8861
Authors: Huiquan Yang, Zhengyang Zhu, Lu Zhou, Jianan Zhou, Zhennan Tao, Xi Wu, Chuanshuai Tian, Dongming Liu, Liangpeng Wei, Haoyao Wang, Zihe Zhao, Yan Zhu, Xun Wang, Tiexiang Li, Wenwei Lin, Yuxiang Dai, Xin Zhang, Bing Zhang
Language: English
Subfield: Genetics
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4414318928
