Recursive Partitioning Analysis Index is Predictive for Overall Survival in Patients Undergoing Spine Stereotactic Body Radiation Therapy for Spinal Metastases

To generate a prognostic index using recursive partitioning analysis (RPA) for patients undergoing spine stereotactic body radiation therapy (sSBRT) for spinal metastases (sMet). From an IRB-approved database of patients treated with sSBRT, 174 patients were identified treated for sMet between 2/2006 and 8/2009. Patients were treated to a median dose of 14 Gy (range: 8-24) typically in a single fraction (range: 1-5). Kaplan-Meier analysis was performed to detect any correlation between survival and histology. Histologies were divided into 3 tumor types: “favorable” included breast and prostate; “radioresistant” included renal cell, melanoma, and sarcoma; and “radiosensitive” included all other histologies. RPA was performed to identify any association of the following variables with overall survival (OS) following sSBRT: tumor type, gender, age, Karnofsky Performance Status (KPS), control of primary, extraosseous metastases, time from primary diagnosis (TPD), dose of sSBRT (<14 Gy vs. ≥14 Gy), extent of spine disease (epidural only, bone and epidural, bone only), upfront or salvage treatment, presence of paraspinal extension, and previous surgery. Median follow-up was 8.9 months (range: 0.5-48.3). Median OS time from sSBRT was 10.7 months (mos). Median OS for “favorable” histologies was 14 mo, 11.2 mo for “radioresistant” histologies, and 7.3 mos for “radiosensitive” histologies (p = 0.02). RPA analysis resulted in 3 classes (p < 0.0001, graph to be presented at meeting). Class 1 is defined as: TPD>30 mos and KPS>70; Class 2: TPD>30 mos and KPS≤70 (or) TPD≤30 mos and age < 70 yo; Class 3: TPD≤30 mos and age≥70 yo. Median OS was 21.1 mos for Class 1 (n = 59), 8.7 mos for Class 2 (n = 104), and 2.4 mos for Class 3 (n = 11). sSBRT patients treated for sMet have a wide variability in OS. We developed a RPA classification system that is predictive of OS. While many patients are treated for palliation of pain or to avoid symptomatic progression, this index may be used to predict who may benefit the most from sSBRT. Given that this proposed classification system is based on a single institution's experience with sSBRT, this index will need multi-institutional validation.