Pre-Diagnostic Allostatic Load Predicts Poorly Differentiated and Larger Breast Tumors among Black Women: Findings from the Women's Circle of Health Follow-Up Study.

CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION(2020)

引用 21|浏览37
暂无评分
摘要
Background: Few studies have empirically tested the association of allostatic load (AL) with breast cancer clinicopathology. The aim of this study was to examine the association of AL, measured using relevant biomarkers recorded in medical records before breast cancer diagnosis, with unfavorable tumor clinicopathologic features among Black women. Methods: In a sample of 409 Black women with nonmetastatic breast cancer who are enrolled in the Women's Circle of Health Follow-Up Study, we estimated prediagnostic AL using two measures: AL measure 1 [lipid profile-based-assessed by systolic and diastolic blood pressure (SBP, DBP), high-density lipoprotein, low-density lipoprotein, total cholesterol, triglycerides, and glucose levels; waist circumference; and use of diabetes, hypertension, or hypercholesterolemia medication] and AL measure 2 (inflammatory index-based-assessed by SBP, DBP, glucose, and albumin levels; estimated glomerular filtration rate; body mass index; waist circumference; and use of medications previously described). We used Cohen's statistic to assess agreement between the two AL measures and multivariable logistic models to assess the associations of interest. Results: AL measures 1 and 2 moderately agreed (kappa = 0.504). Higher prediagnostic AL predicted higher grade (poorly differentiated vs. well/moderately differentiated) using AL measure 1 [OR = 2.16; 95% confidence interval (CI), 1.18-3.94] and AL measure 2 (OR = 1.60; 95% CI, 1.02-2.51), and larger tumor size (>= 2 cm vs. <2 cm; OR = 1.58; 95% CI, 1.01-2.46) using AL measure 2 only. Conclusions: Elevated prediagnostic AL might contribute to more unfavorable breast cancer clinicopathology. Impact: Addressing elevated prediagnostic levels of AL has potentially important clinical implications.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要