Study design: This is a retrospective cohort.
Objective: Determine the relationship of body morphometry to postoperative survival in patients with vertebral metastases.
Summary of background data: Most operations for vertebral metastases aim for palliation not cure, yet expected patient survival heavily influences treatment plans. We seek to demonstrate that preoperative fat and muscle volumes on standard-of-care computed tomography (CT) are independent predictors of survival after surgery for vertebral metastases.
Materials and methods: Included data were preoperative neurological status, adjuvant treatments, CT-assessed body composition, health comorbidities, details of oncologic disease, and Tomita and Tokuhashi scores. Body composition-visceral fat area, subcutaneous fat area, and total muscle area-were assessed on preoperative L3/4 CT slice with Image J software. Multivariable logistic regressions were used to determine independent predictors of 3-, 6-, and 12-month survival.
Results: We included 75 patients (median age, 57, 57.3% male, 66.7% white) with the most common primary lesions being lung (17.3%), prostate (14.7%), colorectal (12.0%), breast (10.7%), and kidney (9.3%). The only independent predictor of 3-month survival was visceral fat area [95% confidence interval (CI): 1.02-1.23 per 1000 mm; P=0.02]. Independent predictors of survival at 6 months were body mass index (95% CI: 1.04-1.35 per kg/m; P=0.009), Karnofsky performance status (95% CI: 1.00-1.15; P<0.05), modified Charlson Comorbidity Index (95% CI: 1.11-7.91; P=0.03), and postoperative chemotherapy use (95% CI: 1.13-4.71; P=0.02). Independent predictors of 12-month survival were kidney primary pathology (95% CI: 0.00-0.00; P<0.01), body mass index (95% CI: 1.03-1.39 per kg/m; P=0.02), and being ambulatory preoperatively (95% CI: 1.28-17.06; P=0.02).
Conclusions: Visceral fat mass was an independent, positive predictor of short-term postoperative survival in patients treated for vertebral metastases. As a result, we believe that the prognostic accuracy of current predictors may be improved by the addition of visceral fat volume as a risk factor.