RECURSIVE PARTITIONING ANALYSIS (RPA) OF PROGNOSTIC FACTORS IN 3 RADIATION-THERAPY ONCOLOGY GROUP (RTOG) BRAIN METASTASES TRIALS

Purpose: Promising results from new approaches such as radiosurgery or stereotactic surgery of brain metastases have recently been reported, Are these results due to the therapy alone or can the results be attr ibuted in part to patient selection? An analysis of tumor/patient char acteristics and treatment variables in previous Radiation Therapy Onco logy Group (RTOG) brain metastases studies was considered necessary to fully evaluate the benefit of these new interventions, Methods and Ma terials: The database included 1200 patients from three consecutive RT OG trials conducted between 1979 and 1993, which tested several differ ent dose fractionation schemes and radiation sensitizers, Using recurs ive partitioning analysis (RPA), a statistical methodology which creat es a regression tree according to prognostic significance, eighteen pr etreatment characteristics and three treatment-related variables were analyzed, Results: According to the RPA tree the best survival (median : 7.1 months) was observed in patients < 65 years of age with a Karnof sky Performance Status (KPS) of at least 70, and a controlled primary tumor with the brain the only site of metastases, The worst survival ( median: 2.3 months) was seen in patients with a KPS less than 70, All other patients had relatively minor differences in observed survival, with a median of 4.2 months, Conclusions: Based on this analysis, we s uggest the following three classes: Class 1: patients with KPS greater than or equal to 70, < 65 Sears of age with controlled primary and no extracranial metastases; Class 3: KPS < 70; Class 2- all others, Usin g these classes or stages, new treatment techniques can be tested on h omogeneous patient groups, (C) 1997 Elsevier Science Inc.