Medium to long term follow-up of survival and quality of life in patients with primary tumors of the cervical spine: Experience From a large single center - Xu, Nanfang; Chang, Shuai; Liu, Xiaoguang; Jiang, Liang; Yu, Miao; Wu, Fengliang; Dang, Lei; Zhou, Hua; Li, Yan; Wang, Yongqiang; Liu, Xiao; Wu, Yunxia; et al. (Frontiers in Surgery, 2023)
Abstract Objectives: To evaluate the survival and medium to long term health-related quality of life (HRQoL) of patients with primary cervical spinal tumors in a cross-sectional study and to identify any significant associations with demographic or clinical characteristics. Methods: Patients diagnosed with primary cervical spinal tumors were retrospectively enrolled and their clinical, radiologic, and follow-up data (specifically the EQ-5D questionnaire) were collected. Univariate and multivariate Cox time-dependent regression analyses were performed to examine the significance of certain variables on overall survival. Univariate and multivariate logistic regression analyses were conducted to identify variables significant for overall HRQoL and each dimension of the EQ-5D. Results: A total of 341 patients were enrolled in the study with a mean follow-up of 70 months. The diagnosis was benign in 246 cases, malignant in 84, and unconfirmed in 11. The 5-year overall survival rate was 86% and the 10-year overall survival rate was 65%. EQ-5D data were available for 187 patients. Surgery, myelopathy, malignancy, spinal pain relieved by lying down or supine position, and tumor infiltration on MRI were significant predictors for overall survival. Enneking stage and age were significant predictors for HRQoL. Conclusions: The present study involving 341 primary cervical spine tumor patients with medium to long term follow-up (>5 years on average) allowed a comprehensive evaluation of the epidemiological characteristics of these patients, especially their survival and long-term HRQoL. With further validation, the risk factors identified in the study could potentially be used to guide evidence-based decision-making in disease management.