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Clinical Trial
. 2000 Jul 1;47(4):1001-6.
doi: 10.1016/s0360-3016(00)00547-2.

Validation of the RTOG recursive partitioning analysis (RPA) classification for brain metastases

Affiliations
Clinical Trial

Validation of the RTOG recursive partitioning analysis (RPA) classification for brain metastases

L E Gaspar et al. Int J Radiat Oncol Biol Phys. .

Abstract

Purpose: The Radiation Therapy Oncology Group (RTOG) previously developed three prognostic classes for brain metastases using recursive partitioning analysis (RPA) of a large database. These classes were based on Karnofsky performance status (KPS), primary tumor status, presence of extracranial system metastases, and age. An analysis of RTOG 91-04, a randomized study comparing two dose-fractionation schemes with a comparison to the established RTOG database, was considered important to validate the RPA classes.

Methods and materials: A total of 445 patients were randomized on RTOG 91-04, a Phase III study of accelerated hyperfractionation versus accelerated fractionation. No difference was observed between the two treatment arms with respect to survival. Four hundred thirty-two patients were included in this analysis. The majority of the patients were under age 65, had KPS 70-80, primary tumor controlled, and brain-only metastases. The initial RPA had three classes, but only patients in RPA Classes I and II were eligible for RTOG 91-04.

Results: For RPA Class I, the median survival time was 6. 2 months and 7.1 months for 91-04 and the database, respectively. The 1-year survival was 29% for 91-04 versus 32% for the database. There was no significant difference in the two survival distributions (p = 0.72). For RPA Class II, the median survival time was 3.8 months for 91-04 versus 4.2 months for the database. The 1-year survival was 12% and 16% for 91-04 and the database, respectively (p = 0.22).

Conclusion: This analysis indicates that the RPA classes are valid and reliable for historical comparisons. Both the RTOG and other clinical trial organizers should currently utilize this RPA classification as a stratification factor for clinical trials.

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