Natural language processing algorithms identify wild-type isocitrate dehydrogenase gliomas in electronic health records.

ABSTRACT:

Background

In 2021, the World Health Organization reclassified glioblastomas to include only gliomas with wild-type isocitrate dehydrogenase (IDHwt). Reclassification has created a challenge for retrospective identification of patients with GBM, as many were classified with outdated definitions. This study aims to address this challenge by using natural language processing (NLP) on electronic health record (EHR) data to identify patients with wild-type IDH glioma.

Methods

We manually adjudicated a subset of 1499 pathology records for evidence of IDHwt glioma as well as the methylation status of the MGMT promoter. We then trained several regularized logistic regression models that identify the IDH mutation and MGMT promoter status using biomedical concepts identified in the t

SUBMITTER: Forrest N 

PROVIDER: S-EPMC12284639 | biostudies-literature | 2025 Jan-Dec

REPOSITORIES: biostudies-literature