Predictors of Survival After Surgical Treatment of Spinal Metastasis

Author:

Arrigo Robert T12,Kalanithi Paul32,Cheng Ivan4,Alamin Todd4,Carragee Eugene J4,Mindea Stefan A3,Park Jongsoo3,Boakye Maxwell32

Affiliation:

1. Stanford University School of Medicine, Stanford, California

2. Department of Outcomes Research Lab, VA Palo Alto Health Care System, Palo Alto, California

3. Department of Neurosurgery, Stanford University Medical Center, Palo Alto, California

4. Department of Orthopaedic Surgery, Stanford University Medical Center, Palo Alto, California

Abstract

Abstract BACKGROUND: Surgery for spinal metastasis is a palliative treatment aimed at improving patient quality of life by alleviating pain and reversing or delaying neurologic dysfunction, but with a mean survival time of less than 1 year and significant complication rates, appropriate patient selection is crucial. OBJECTIVE: To identify the most significant prognostic variables of survival after surgery for spinal metastasis. METHODS: Chart review was performed on 200 surgically treated spinal metastasis patients at Stanford Hospital between 1999 and 2009. Survival analysis was performed and variables entered into a Cox proportional hazards model to determine their significance. RESULTS: Median overall survival was 8.0 months, with a 30-day mortality rate of 3.0% and a 30-day complication rate of 34.0%. A Cox proportional hazards model showed radiosensitivity of the tumor (hazard ratio: 2.557, P < .001), preoperative ambulatory status (hazard ratio: 2.355, P = .0001), and Charlson Comorbidity Index (hazard ratio: 2.955, P < .01) to be significant predictors of survival. Breast cancer had the best prognosis (median survival, 27.1 months), whereas gastrointestinal tumors had the worst (median survival, 2.66 months). CONCLUSION: We identified the Charlson Comorbidity Index score as one of the strongest predictors of survival after surgery for spinal metastasis. We confirmed previous findings that radiosensitivity of the tumor and ambulatory status are significant predictors of survival.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Clinical Neurology,Surgery

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