Study Design. Retrospective cohort study. Objective. To evaluate a scoring system to predict morbidity for patients undergoing metastatic spinal tumor surgery (MSTS). Summary of Background Data. Multiple scoring systems exist to predict survival for patients with spinal metastasis. The potential benefits and risks of surgery need to be evaluated for patients with disseminated cancer and limited life expectancy. Few scoring systems exist to predict perioperative morbidity after MSTS. Methods. We reviewed records of patients who underwent MSTS at our institution between 2013 and 2019. All perioperative complications occurring within 30 days were recorded. A clinical scoring system consisting of five variables (age ≥ 70 yr, hypoalbuminemia, poor preoperative functional status [Karnofsky ≤ 40], Frankel Grade A-C, and multilevel disease ≥2 continuous vertebral bodies) was evaluated as a predictive tool for morbidity; every parameter was assigned a value of 0 if absent or 1 if present (total possible score = 5). The effect of the scoring system on morbidity was evaluated using stepwise multiple logistic regression. Model accuracy was calculated by receiver operating characteristic analysis. Results. One hundred and five patients were identified, with a male prevalence of 58.1% and average age at surgery of 61 years. The overall 30-day complication rate was 36.2%. The perioperative morbidity was 4.6%, 30.0%, 53.9%, and 64.7% for patients with scores of 0, 1, 2, and ≥3 points, respectively (P < 0.001). On multiple logistic regression analysis controlling for covariates not present in the model, the scoring system was significantly associated with 30-day morbidity (OR 3.11; 95% CI, 1.72–5.59; P < 0.001). The model's accuracy was estimated at 0.75. Conclusion. Our proposed model was found to accurately predict perioperative morbidity after MSTS. The Spine Oncology Morbidity Assessment (SOMA) score may prove useful for risk stratification and possibly decision-making, though further validation is needed. Level of Evidence: 4
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