Development and Temporal Validation of a Three-Metabolite Cerebrospinal Fluid Model for the Diagnosis of Leptomeningeal Metastasis from Solid Tumors

Background/Objectives: Leptomeningeal metastasis (LM) is a severe complication of solid tumors. Cerebrospinal fluid (CSF) cytology is only about 70% sensitive on a single examination, and objective markers are needed.

Methods

CSF from 49 patients with LM and 16 with intracranial disease without LM was analyzed by targeted LC–MS in a training batch (n = 30) and a temporally independent validation batch (n = 35). Metabolites selected by both LASSO and random forest entered a logistic regression model, which was applied unchanged to the validation batch and evaluated by repeated and nested cross-validation on all 65 samples.

Results

Hydroxyphenyllactic acid, argininosuccinic acid and norepinephrine were selected by both algorithms. The model reached an AUC of 0.954 in the training batch and 0.839 (95% CI 0.687–0.991) in the validation batch. In repeated cross-validation on all 65 samples, the AUC was 0.790 (95% CI 0.655–0.924), with sensitivity 0.714 and specificity 0.938; nested cross-validation gave 0.747.