Cox regression multivariate analysis
REGRESSION, METASTASIS, METASTASES, PRIMARY TUMOR
As a multivariate survival analysis model, the Cox regression model can effectively process the final examination data, control various confounding factors, quantitatively analyze the effect strength and direction of the observation indicators, and comprehensively analyze the effect of prognostic factors. To further determine the factors affecting the survival rate of patients with lumbosacral osteoblastic metastases, we analyzed all covariates using the Cox regression equation.The patient’s sex, age, location, preoperative KPS score, spinal segment, primary tumor growth, organ metastasis, and surgical method were included in the multivariate Cox proportional hazards regression model. The variables and their respective values that finally contributed to the effect equation are presented in Table Sixty-two cases of lumbosacral vertebral osteoblastic metastasis multivariate Cox regression analysisCox regression analysis showed that age, primary tumor, and metastatic spinal segment were independent predictors of long-term survival in patients with lumbosacral osteoblastic metastases.