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Αλέξανδρος Γ. Σφακιανάκης

Sunday, February 28, 2021

An Observational Study on Breast Cancer Survival and Lifestyle Related Risk Factors

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In Vivo. 2021 Mar-Apr;35(2):1007-1015. doi: 10.21873/invivo.12344.

ABSTRACT

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 regres sion 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.

PMID:33622896 | DOI:10.21873/invivo.12344

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