Development and validation of a prognostic model for recurrent glioblastoma patients treated with bevacizumab and irinotecan

Background Predictive markers and prognostic models are required in order to individualize treatment of recurrent glioblastoma (GBM) patients. Here, we sought to identify clinical factors able to predict response and survival in recurrent GBM patients treated with bevacizumab (BEV) and irinotecan. Material and methods A total of 219 recurrent GBM patients treated with BEV plus irinotecan according to a previously published treatment protocol were included in the initial population. Prognostic models were generated by means of multivariate logistic and Cox regression analysis. Results In multivariate analysis, corticosteroid use had a negative predictive impact on response at first evaluation (OR 0.45; 95% CI 0.22-0.93; p = 0.03) and at best response (OR 0.51; 95% CI 0.26-1.02; p = 0.056). Three significant (p