Clinically Available and Reproducible Prediction Models for IDH and CDKN2A/B Gene Status in Adult-type Diffuse Gliomas

Abstract

Purpose

Isocitrate dehydrogenase (IDH) and cyclin-dependent kinase inhibitor (CDKN) 2A/B status holds important prognostic value in diffuse gliomas. We aimed to construct prediction models using clinically available and reproducible characteristics for predicting IDH-mutant and CDKN2A/B homozygous deletion in adult-type diffuse glioma patients.

Materials and Methods

This retrospective, two-center study analysed 272 patients with adult-type diffuse glioma (230 for primary cohort and 42 for external validation cohort). Two radiologists independently assessed the patients’ images according to the Visually AcceSAble Rembrandt Images (VASARI) feature set. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to optimise variable selection. Multivariable logistic regression analysis was used to develop the prediction models. Calibration plots, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA) were used to validate the models. Nomograms were developed visually based on the prediction models.

Results

The interobserver agreement between the two radiologists for VASARI features was excellent (κ range, 0.813–1). For the IDH-mutant prediction model, the area under the curves (AUCs) was 0.88–0.96 in the internal and external validation sets, For the CDKN2A/B homozygous deletion model, the AUCs were 0.80–0.86 in the internal and external validation sets. The decision curves show that both prediction models had good net benefits.

Conclusion

The prediction models which basing on VASARI and clinical features provided a reliable and clinically meaningful preoperative prediction for IDH and CDKN2A/B status in diffuse glioma patients. These findings provide a foundation for precise preoperative non-invasive diagnosis and personalised treatment approaches for adult-type diffuse glioma patients.