Abstract BACKGROUND We assess the efficacy of the metabolomic profile from glioma biopsies, in providing estimates of postsurgical Overall Survival in glioma patients. MATERIAL AND METHODS Tumor biopsies from 46 patients bearing gliomas, obtained neurosurgically in the period 1992–1998, were analyzed by high resolution 1H magnetic resonance spectroscopy (HR- 1H MRS), following retrospectively individual postsurgical Overall Survival up to 720 weeks. RESULTS The Overall Survival profile could be resolved in three groups; Short (shorter than 52 weeks, n=19), Intermediate (between 53 and 364 weeks, n=19) or Long (longer than 365 weeks, n=8), respectively. Classical histopathological analysis assigned WHO grades II-IV to every biopsy but notably, some patients with low grade glioma depicted unexpectedly Short Overall Survival, while some patients with high grade glioma, presented unpredictably Long Overall Survival. To explore reasons underlying this behavior, we analyzed HR- 1H MRS spectra from acid extracts of these biopsies, to identify the metabolite patterns underlying OS predictions. Poor prognosis was found in biopsies with higher contents of alanine, acetate, glutamate, total choline, phosphorylcholine and glycine, while more favorable prognosis was achieved in biopsies with larger contents of total creatine, glycerol-phosphorylcholine and myo-inositol. We implemented then a multivariate analysis approach to identify hierarchically the influence of these metabolomic biomarkers on OS predictions, using Classification Regression Trees (CRTs). Metabolomic CRTs grew up to 3 branches and split into 8 nodes, predicting correctly the outcome of 94.7% of the patients in the Short Overall Survival group, 78.9 % of the patients in the Intermediate Overall Survival group, and 75% of the patients in the Long Overall Survival group, respectively. CONCLUSION Present results suggest that metabolic profiling by HR-1H MRS provides more accurate Overall Survival estimates of glioma patients than classical histopathological grading, thus allowing to implement more accurate therapeutic decisions.