Evaluating the Association Between Allostatic Load and Malignancy on Image-Guided Breast Biopsy.

Kwak, Lily; Patel, Saloni; Yenokyan, Gayane; Sadigh, Gelareh; Miles, Randy C; McDonald, Elizabeth S; Oluyemi, Eniola T; Carlos, Ruth C · J Am Coll Radiol · 2026

retrospective_cohort · Level III

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Abstract

Allostatic load (AL) is a measure of physiologic dysregulation representing the cumulative effect of activation of the stress response system. The purpose of this study was to evaluate the association between AL and malignant pathology on image-guided breast biopsy. This retrospective cohort study evaluated data from women aged 18 and older who underwent stereotactic-guided or ultrasound-guided breast biopsy at our tertiary academic institution from April 1, 2017, to March 31, 2022. We recorded patient age, race, ethnicity, Gail Model breast cancer risk score, area deprivation index, as well as AL calculated using clinical laboratory metrics from four major physiological systems-cardiovascular, immune, metabolic, and renal. The primary outcome was malignant pathology, and the secondary outcome was high-risk pathology. The association between AL and pathology result was evaluated using multivariable logistic regressions. In all, 253 patients were included in the study with mean age of 61 years (SD 12). After adjustment for age, race, ethnicity, and area deprivation index, higher AL was associated with a 22% increase in odds of malignant breast pathology (odds ratio [OR] 1.22 per additional biomarker positivity, 95% confidence interval [CI] 1.03-1.44). The association remained positive but was no longer significant after further adjustment for the Gail 5-year risk score (OR 1.17, 95% CI 0.93-1.47). Of note, 33.6% of patients had missing Gail risk score. No significant association of AL with high-risk pathology (OR 0.99, 95% CI 0.77-1.28) was observed. Our study results suggest that increased AL is associated with malignant pathology result in women undergoing image-guided core needle breast biopsy. This has implications for efforts to optimize personalized screening recommendations and reduce cancer disparities.

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