Morphometrics predicts overall survival in patients with multiple myeloma spine metastasis: A retrospective cohort study
Zakaria HM, Elibe E, Macki M, Smith R, Boyce-Fappiano D, Lee I, Griffith B, Siddiqui F, and Chang V. Morphometrics predicts overall survival in patients with multiple myeloma spine metastasis: A retrospective cohort study. Surg Neurol Int 2018; 9:172.
Surg Neurol Int
Treatment strategies for spinal metastases for myeloma range from conservative measures (radiation and chemotherapy) to invasive (surgical). Identifying better predictors of overall survival (OS) would help in surgical decision making. Analytic morphometrics has been shown to predict survival in oncologic patients, and our study evaluates whether morphometrics is predictive of survival in patients with multiple myeloma (MM) spinal metastases.
For this observational retrospective cohort study, we identified 46 patients with MM spinal metastases who had undergone stereotactic body radiation therapy. OS was the primary outcome measure. Morphometric analysis of the psoas muscle was performed using computed tomography scans of the lumbar spine.
OS was statistically correlated with age (P = 0.025), tumor burden (P = 0.023), and number of levels radiated (P = 0.029), but not with gender. Patients in the lowest tertile of average psoas size had significantly shorter survival compared to the highest tertile, hazard ratio (HZ) 6.87 (95% CI = 1.65-28.5, P = 0.008). When calculating the psoas size to vertebral body ratio and correlating this measure to OS, the lowest tertile again had significantly shorter OS compared to the highest tertile, HZ 6.87 (95% CI = 1.57-29.89, P = 0.010); the middle tertile also showed significantly shorter OS compared to the highest tertile, HZ 5.07 (95% CI = 1.34-19.10, P = 0.016). Kaplan-Meier survival curves were used to visually illustrate the differences in survival between different tertiles (Log-rank test P = 0.006).
Morphometric analysis successfully predicts long-term survival in patients with MM. More research is needed to validate these results and to see if these methodologies can be applied to other cancer histologies.