A new model outperforming RPA and DS-GPA scores for individualized survival prediction of patients following whole brain irradiation for brain metastasis.

Purpose: Survival after whole brain radiation therapy (WBRT) in patients with multiple brain metastases (BM) is currently predicted by group-based scoring systems with limited usability for decision. We aimed to develop a more relevant individualized predictive model than Radiation Therapy Oncology Group - Recursive Partitioning Analysis (RTOG-RPA) and Diagnosis - Specific Graded Prognostic Assessment (DS-GPA) for patients with limited life-expectancy.

Methods: Based on a Discovery cohort of patients undergoing WBRT, multivariable piecewise Cox regression models with time cut-offs at 1 and 3 months were developed to predict overall survival (OS).