Association Between Pre-Treatment and Post-Treatment 3-Month Red Cell Distribution Width with Three-Year Prognosis of Prostate Cancer

前列腺癌治疗前后3个月红细胞分布宽度与三年预后的相关性

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Abstract

PURPOSE: Red cell distribution width (RDW), an inflammation biomarker, has been linked to poor outcomes in patients with different types of cancers. The present study aimed to investigate the relationship between pre-/post-treatment 3-month RDW levels and changes in RDW with 3-year prognosis of prostate cancer. PATIENTS AND METHODS: A total of 348 patients with prostate cancer were recruited between June 1, 2012 and June 1, 2017 and were followed up for at least 3 years. RDW was measured with the Mindray BC-6800Plus automatic blood counting system at pre- and post-treatment 3-month. Demographic and clinical information of the participants were also collected. The overall survival (OS) and cancer-specific survival (CSS) were analyzed using the Kaplan-Meier method. Cox regression and competing risk regression analyses were performed. RESULTS: During the follow-up period, 51 (14.66%) deaths occurred. The levels of pre- and post-treatment RDW levels were significantly higher in the death group than in the survival group (p<0.001). In the death group, the level of RDW continued to rise in most subjects, and the mean level of RDW was significantly higher at post-treatment than pre-treatment, contrary to the results observed in the survival group. Multivariate Cox regression analysis revealed that high pre-treatment RDW, high post-treatment RDW, and persistently higher RDW were independently associated with OS and CSS (p<0.001). Similar results were observed in the competing risk regression analysis. Kaplan-Meier analysis revealed that patients with higher pre-treatment RDW levels, higher post-treatment RDW levels, and persistently higher RDW levels had poorer 3-year OS and CSS rates (p<0.05). CONCLUSION: The levels of and changes in RDW before and after treatment were associated with the 3-year prognosis of prostate cancer, suggesting that RDW might be an efficient prognostic predictor in patients with prostate cancer.

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