Background: Several variables are associated with the likelihood of isocitrate dehydrogenase 1 or 2 (IDH1/2) mutation in gliomas, though no guidelines yet exist for when testing is warranted, especially when an R132H IDH1 immunostain is negative.
Methods: A cohort of 89 patients was used to build IDH1/2 mutation prediction models in World Health Organization grades II-IV gliomas, and an external cohort of 100 patients was used for validation. Logistic regression and backward model selection with the Akaike information criterion were used to develop prediction models.
Results: A multivariable model, incorporating patient age, glioblastoma multiforme diagnosis, and prior history of grade II or III glioma, was developed to predict IDH1/2 mutation probability. This model generated an area under the curve (AUC) of 0.934 (95% CI: 0.878, 0.978) in the external validation cohort and 0.941 (95% CI: 0.918, 0.962) in the cohort of The Cancer Genome Atlas. When R132H IDH1 immunostain information was added, AUC increased to 0.986 (95% CI: 0.967, 0.998). This model had an AUC of 0.947 (95% CI: 0.891, 0.995) in predicting whether an R132H IDH1 immunonegative case harbored a less common IDH1 or IDH2 mutation. The models were also 94% accurate in predicting IDH1/2 mutation status in gliomas from The Cancer Genome Atlas. An interactive web-based application for calculating the probability of an IDH1/2 mutation is now available using these models.
Conclusions: We have integrated multiple variables to generate a probability of an IDH1/2 mutation. The associated web-based application can help triage diffuse gliomas that would benefit from mutation testing in both clinical and research settings.
Keywords: IDH1; IDH2; glioma.
© The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.