Marital status and gender affect stage, tumor grade, treatment type and cancer specific mortality in T 1â2 N 0 M 0 renal cell carcinoma
World Journal of Urology Aug 31, 2017
Marchioni M, et al. – Researchers designed a logistic regression and competing–risks regression models to investigate the impact of marital status and gender on stage, tumor grade, treatment type and cancer specific mortality (CSM). It was indicated that male patients are at higher risk of less favorable baseline characteristics. Additionally, male, widowed and separated/divorced patients exhibit worse cancer control outcomes after treatment for T1Â2 N0 M0 renal cell carcinoma (RCC). The data demonstrates the need of more focused attention to those patients prior to, as well as after treatment for localized renal cell carcinoma. MethodsGo to Original
- Within Surveillance, Epidemiology, and End Results registry (2001Â2013), researchers distinguished 57,700 patients with T1Â2 N0 M0 RCC.
- They applied logistic regression and competing–risks regression models to investigate the impact of marital status and gender on stage, tumor grade, treatment type and cancer specific mortality (CSM).
- Of all patients, 8.8, 10.6 and 14.8% were, respectively, widowed, separated/divorced and never married.
- In this analysis, the three categories accounted for 3.9, 9.0 and 14.9% of males (35,641) and for 16.7, 13.1 and 14.7% of females (22,059).
- The data suggested that widowed (OR 1.13, p = 0.04), separated/divorced (OR 1.16, p = 0.02) and never married status (OR 1.38, p < 0.001) predisposed to higher rate of no surgical treatment.
- The results confirmed that widowed (HR 1.32, p < 0.001) and separated/divorced (HR 1.32, p < 0.001) status predisposed to higher CSM.
- It was noted that male gender predisposed to higher T–stage (OR 1.12, p < 0.001), higher tumor grade (OR 1.35, p < 0.001), no surgical treatment (OR 1.23, p < 0.001) and higher CSM (1.13, p = 0.01).
- It was demonstrated that interaction tests between gender and marital status failed to reach independent predictor status in all analyses.
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