Prognostic Factors Associated With Overall Survival in Breast Cancer Patients With Metastatic Spinal Disease

转移性脊柱疾病乳腺癌患者总生存期的预后因素

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Abstract

Introduction The spine is the third most frequent site of metastasis, after the lungs and liver, in breast cancer patients. The current treatment modality is based on the prognosis calculated according to multiple clinical features; therefore, multiple scores have been developed to make the therapeutic decision; however, there are no specific scores to take an adequate therapeutic approach in the treatment of vertebral metastases due to breast cancer. The aim of the study is to identify the prognostic factors associated with survival in breast cancer patients with spinal metastatic disease. Methods A retrospective cohort study was carried out at the National Cancerology Institute (INCAN) in Mexico City from January 2011 to December 2017. To this extent, 56 consecutive cases of patients with breast cancer were included. Multiple demographic, laboratory, and clinical variables were taken into account for the survival calculation. Kaplan-Meier graphs and log-rank tests were performed to observe significant differences by subgroups in survival, and Cox regression was used for multivariate analysis. Results Concerning the survival analysis, the patients who presented extra-spinal metastases, an unstable spine, and Frankel grade C had a statistically significantly worse prognosis. In the multivariate analysis, the variables included extra-spinal metastases, age >50 years, spinal instability, serum alkaline phosphatase, and CA 15.3 serum levels, finding statistical significance with a p=0.015. Conclusion Prognostic factors associated with shorter overall survival in breast cancer patients with metastatic spinal disease were the presence of extra-spinal metastases and spinal instability. Additionally, the use of the Tomita and Tokuhashi scores for patients with breast cancer and spinal metastases is not justified at present. The study should be continued with a larger population to decrease biases and obtain a more homogeneous sample, as well as to obtain a personalized score to determine a more efficient treatment for these patients.

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