Journal article
Recursive partitioning analysis is predictive of overall survival for patients undergoing spine stereotactic radiosurgery
Journal of neuro-oncology, Vol.137(2), pp.289-293
04/01/2018
DOI: 10.1007/s11060-017-2716-1
PMID: 29299738
Abstract
Spine stereotactic radiosurgery (SRS) offers excellent radiographic and pain control for patients with spine metastases. We created a prognostic index using recursive partitioning analysis (RPA) to allow better patient selection for spine SRS. Patients who underwent single-fraction spine SRS for spine metastases were included. Primary histologies were divided into favorable (breast/prostate), radioresistant (renal cell/sarcoma/melanoma) and other. Cox proportional hazards regression was done to identify factors associated with overall survival (OS). RPA was performed to identify factors to classify patients into distinct risk groups with respect to OS. A total of 444 patients were eligible. Median dose was 16 Gy (range 8-18) in 1 fraction and median follow-up was 11.7 months. At time of analysis, 103 (23.1%) patients were alive. Median OS was 12.9 months. RPA identified three distinct classes. Class 1 was defined as KPS > 70 with controlled systemic disease (n = 142); class 3 was defined as KPS ≤ 70 and age < 54 years or KPS ≤ 70 age ≥ 54 years and presence of visceral metastases (n = 95); all remaining patients comprise class 2 (n = 207). Median overall survival was 26.7 months for class 1, 13.4 months for class 2, and 4.5 months for class 3 (p < 0.01). Our analysis demonstrates that there is considerably variability in survival among patients undergoing spine SRS. We created an objective risk stratification via RPA for spine SRS. Given the safety and efficacy of spine SRS and good survival in class 1 and 2 patients, this RPA can help clinicians identify patients who may benefit from upfront spine SRS.
Details
- Title: Subtitle
- Recursive partitioning analysis is predictive of overall survival for patients undergoing spine stereotactic radiosurgery
- Creators
- Ehsan H Balagamwala - Cleveland ClinicJacob A Miller - Cleveland Clinic Lerner College of MedicineChandana A Reddy - Cleveland ClinicLilyana Angelov - Cleveland ClinicJohn H Suh - Cleveland ClinicMuhammad B Tariq - Cleveland Clinic Lerner College of MedicineErin S Murphy - Cleveland ClinicKailin Yang - Cleveland Clinic Lerner College of MedicineToufik Djemil - Cleveland Clinic FloridaAnthony Magnelli - Cleveland ClinicAlireza M Mohammadi - Cleveland ClinicSherry Soeder - Cleveland ClinicSamuel T Chao - Cleveland Clinic
- Resource Type
- Journal article
- Publication Details
- Journal of neuro-oncology, Vol.137(2), pp.289-293
- DOI
- 10.1007/s11060-017-2716-1
- PMID
- 29299738
- ISSN
- 0167-594X
- eISSN
- 1573-7373
- Language
- English
- Date published
- 04/01/2018
- Academic Unit
- Radiation Oncology
- Record Identifier
- 9984696710202771
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