4.7 Article

Recursive Partitioning Analysis for the Prediction of Stereotactic Radiosurgery Brain Metastases Lesion Control

Journal

ONCOLOGIST
Volume 18, Issue 3, Pages 330-335

Publisher

ALPHAMED PRESS
DOI: 10.1634/theoncologist.2012-0316

Keywords

Brain metastases; Stereotactic radiosurgery; Recursive partitioning analysis; Predictive modeling; Local control

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Purpose. The objective of this investigation was to identify independent pretreatment factors that predict for control of local brain metastases (BM) in a large single-institution series of patients receiving stereotactic radiosurgery (SRS). Recursive partitioning analysis was used to potentially identify a class of patients with durable lesion control characteristics. Methods. A retrospective SRS database containing baseline characteristics, treatment details, and follow-up data of newly diagnosed patients with 1-3 BM (on magnetic resonance imaging) treated with linear accelerator-based SRS was created. Three study endpoints were used: time to progression (primary endpoint, individual lesion progression; n = 536), time to first progression (secondary endpoint, first lesion progression on an individual patient basis; n = 380), and overall survival (secondary endpoint; n = 380). Recursive partitioning analysis (RPA) was performed to identify predictors of time to progression. Results. Multivariable analysis demonstrated that lesion aspect/phenotype and radiotherapy schedule were independent factors associated with both progression outcomes. Presence of tumor necrosis was found to be associated with a significant hazard of progression (hazard ratio >3), whereas use of the most intense radiotherapy fractionation schedule (21 Gy in one fraction) was associated with significant reductions in progression (hazard ratio <0.3). RPA using SRS dose and lesion aspect/phenotype was created and described three distinct prognostic groups. Conclusions. RPA of a large retrospective database of patients receiving SRS confirmed previous observations regarding the importance of SRS dose and lesion aspect/phenotype in lesion control and overall survival. The SRS lesion analysis may help to stratify future clinical trials and better define patient care options and prognosis. The Oncologist 2013;18:330-335

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