RECURSIVE PARTITIONING ANALYSIS OF PROGNOSTIC FACTORS IN 3 RADIATION-THERAPY ONCOLOGY GROUP MALIGNANT GLIOMA TRIALS

Background: Despite notable technical advances in therapy for malignan t gliomas during the past decade, improved patient survival has not be en clearly documented, suggesting that pretreatment prognostic factors influence outcome more than minor modifications in therapy. Age, perf ormance status, and tumor histopathology have been identified as the p retreatment variables most predictive of survival outcome. However, an analysis of the association of survival with both pretreatment charac teristics and treatment-related variables is necessary to assure relia ble evaluation of new approaches for treatment of malignant glioma. Pu rpose: This study of malignant glioma patients used a nonparametric st atistical technique to examine the associations of both pretreatment p atient and tumor characteristics and treatment-related variables with survival duration. This technique was used to identify subgroups with survival rates sufficiently different to create improvements in the de sign and stratification of clinical trials. Methods: We used a recursi ve partitioning technique to analyze survival in 1578 patients entered in three Radiation Therapy Oncology Group malignant glioma trials fro m 1974 to 1989 that used several radiation therapy (RT) regimens with and without chemotherapy or a radiation sensitizer. This approach crea tes a regression tree according to prognostic variables that classifie s patients into homogeneous subsets by survival. Twenty-six pretreatme nt characteristics and six treatment-related variables were analyzed. Results: The most significant split occurred by age (<50 versus greate r-than-or-equal-to 50 years). Patients younger than 50 years old were categorized by histology (astrocytomas with anaplastic or atypical foc i [AAF] versus glioblastoma multiforme [GBM]) and subsequently by norm al or abnormal mental status for AAF patients and by performance statu s for those with GBM. For patients aged 50 years or older, performance status was the most important variable, with normal or abnormal-menta l status creating the only significant split in the poorer performance status group. Treatment-related variables produced a subgroup showing significant differences only for better performance status GBM patien ts over age 50 (by extent of surgery and RT dose). Median survival tim es were 4.7-58.6 months for the 12 subgroups resulting from this analy sis, which ranged in size from 32 to 256 patients. Conclusions: This a pproach permits examination of the interaction between prognostic vari ables not possible with other forms of multivariate analysis. Implicat ions: The recursive partitioning technique can be employed to refine t he stratification and design of malignant glioma trials.