Related Experiment Video
Updated: Aug 6, 2026
06:03
Integrating Augmented Reality Tools in Breast Cancer Related Lymphedema Prognostication and Diagnosis
Published on: February 6, 2020
Evaluating Allostatic Load as a Framework for Breast Cancer Risk Assessment Across Sociodemographic Groups: Insights
Antonio R Lopez1, Laura Jean Podewils2,3, Joanna Garcia4
1Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
Journal of Breast Imaging
|July 21, 2026
Summary
Allostatic load (AL), a measure of physiological stress, was linked to higher odds of malignant breast biopsy results in White, non-Hispanic women. This finding suggests AL may be a modifiable risk factor for breast cancer.
Area of Science:
- Biomedical Science
- Public Health
- Oncology
Background:
- Allostatic load (AL) quantifies physiological dysregulation from chronic stress exposure.
- Understanding AL's role in health disparities is crucial for targeted interventions.
Purpose of the Study:
- To investigate the association between allostatic load (AL) and malignant breast biopsy outcomes.
- To examine these associations across diverse sociodemographic subgroups.
Main Methods:
- Retrospective study of women (18+) undergoing image-guided breast biopsy.
- AL score calculated using eight biomarkers (e.g., blood pressure, BMI, creatinine).
- Multivariable logistic regression and stratified analyses by race/ethnicity were employed.
Main Results:
- The study included 668 participants; most were Hispanic and insured by Medicaid.
- A significant association between higher AL and malignant biopsy results was found in White, non-Hispanic women.
- Each one-unit increase in AL correlated with a 46% increased likelihood of malignancy in this subgroup (OR 1.46, P=0.03).
Conclusions:
- Allostatic load is associated with malignant breast biopsy results in specific sociodemographic groups.
- AL may represent a modifiable risk factor in breast cancer prevention strategies.
- Further research in diverse populations is needed to confirm findings and explore contributing factors.
Related Concept Videos
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
02:20Longitudinal Research
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
01:21Cancer Survival Analysis
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
01:20Comparing the Survival Analysis of Two or More Groups
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and Cox...