医学
乳腺癌
内科学
癌症
肿瘤科
风险因素
乳腺癌的危险因素
观察研究
队列
入射(几何)
比例危险模型
优势比
体质指数
置信区间
流行病学
危险系数
队列研究
人口
肥胖
作者
Anne Kreklau,Ivonne Nel,Sabine Kasimir-Bauer,Rainer Kimmig,Anna Christina Frackenpohl,Bahriye Aktas
出处
期刊:in Vivo
[Stanford University Highwire Press]
日期:2021-02-23
卷期号:35 (2): 1007-1015
标识
DOI:10.21873/invivo.12344
摘要
BACKGROUND/AIM Breast cancer survivors are increasingly interested in lifestyle modifications in order to reduce the risk of recurrence and mortality. Therefore, we aimed to study the association between survival and lifestyle related risk factors such as obesity, alcohol intake, smoking, medication and atopic diseases. PATIENTS AND METHODS In this observational single center study, clinicopathological parameters of 635 women with primary breast cancer were sampled. A logistic regression model was applied to investigate correlations among clinical data and various life style related factors. Patients were stratified according to lifestyle and treatment characteristics. Cox regression and the Kaplan-Meier method were used to analyze survival differences in various patient subsets and to identify possible prognostic factors. RESULTS Logistic regression analysis indicated a correlation between low Body Mass Index (BMI) and extended progression-free survival (PFS). Cox regression showed that patients not using beta-blockers had a significantly prolonged overall survival (OS) compared to beta-blocker users [hazard ratio (HR)=3.7; 95% confidence interval (CI)=1.66-8.14, p=0.01]. Apparently, the clincopathological parameters including BMI, HER2-, estrogen receptor (ER) and progesteron receptor (PR)-status as well as treatment with chemo-, radio- and endocrine therapy did not play a role regarding the survival differences between beta-blocker users and non-users. CONCLUSION Patients not using beta-blockers appeared to benefit from extended PFS and OS. Further, patients with a rather low BMI (<30 kg/m2) seemed to have a survival benefit compared to obese patients. Particularly, among postmenopausal women, beta-blocker intake and obesity appeared to be possible life style related prognostic factors that could be used for patient stratification.
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