Effect of allostatic load and measures of segregation on cancer detection and false positive rate after screening mammography.

565 Background: Allostatic load (AL), a cumulative stress measure and residential segregation (MRSs) have been associated with breast cancer (BC) outcomes. We assess the association of AL and MRSs on breast screening outcomes. Methods: From the Mass General Brigham Biobank, we retrospectively identify women aged ≥40, who underwent screening mammography from Jan 1, 2021 to Dec 31, 2021. We collected age, self-reported race/ethnicity, and zip code. Five MRSs were computed: Dissimilarity, Isolation (BI), Delta Index, Absolute Centralization, and Spatial Proximity. To compute AL, we assessed cardiovascular, metabolic, immune and renal lab values. AL was assigned one point for each lab value in the worst quartile and summed. We assessed any false positive (FP) and cancer diagnoses within 12 months after the index screen. Multiple imputation was performed for missing covariates. Multivariable logistic regression models were constructed to assess age, race, AL, and each MRSs association with cancer detection and FP rates. Rubin's rules were applied to estimate overall odds ratios (OR), confidence intervals (CI), and p-values for all covariates. Results: Of 13,754 women assessed, 1.2% (n=169) women received a cancer diagnosis. Most of the women were White (87.6%), 2.6% Asian, 5.3% Black; 1.5% self-identified as Hispanic; mean age, 64.4±11.3SD. Each point increase in AL increased the risk of cancer detection after screening mammography by 15% (OR=1.15,95% CI[1.06, 1.25],p=0.001). No association was detected between each MRS and cancer detection (all p>0.22). BI, the expected proportion of neighbors belonging to the same group, was associated with FP rate, with BI > 0.6 increasing the odds of FPs (OR=2.80[1.13-6.92],p=0.026). After adjusting for AL and MRSs, age and race were not significantly associated with cancer detection, but 5-year changes in age were associated with lower FP rate (OR=0.82[0.80, 0.84],p<0.001). Conclusions: AL was associated with an increased risk of cancer detection after screening mammography after adjusting for age, race, and MRSs. The MRS BI above 0.6 was associated with an increased false positive rate. Further work is needed to confirm these observations. Clinical Relevance Statement: AL and MRS (i.e., BIS) may represent potential biomarkers for personalized mammographic screening for BC.

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Publication Details

Journal
Journal of Clinical Oncology
Published
2025-05-28
DOI
https://doi.org/10.1200/jco.2025.43.16_suppl.565
Primary Topic
AI in cancer detection
Type
article
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article

Effect of allostatic load and measures of segregation on cancer detection and false positive rate after screening mammography.

Ruth C. Carlos, Sarah Bell, Nathaniel D. Mercaldo, Braelyn Wekwerth et al.
Journal of Clinical Oncology
AI in cancer detection
article

Effect of allostatic load and measures of segregation on cancer detection and false positive rate after screening mammography.

Ruth C. Carlos, Sarah Bell, Nathaniel D. Mercaldo, Braelyn Wekwerth, Niam Abeysiriwardena
article en

Abstract

565 Background: Allostatic load (AL), a cumulative stress measure and residential segregation (MRSs) have been associated with breast cancer (BC) outcomes. We assess the association of AL and MRSs on breast screening outcomes. Methods: From the Mass General Brigham Biobank, we retrospectively identify women aged ≥40, who underwent screening mammography from Jan 1, 2021 to Dec 31, 2021. We collected age, self-reported race/ethnicity, and zip code. Five MRSs were computed: Dissimilarity, Isolation (BI), Delta Index, Absolute Centralization, and Spatial Proximity. To compute AL, we assessed cardiovascular, metabolic, immune and renal lab values. AL was assigned one point for each lab value in the worst quartile and summed. We assessed any false positive (FP) and cancer diagnoses within 12 months after the index screen. Multiple imputation was performed for missing covariates. Multivariable logistic regression models were constructed to assess age, race, AL, and each MRSs association with cancer detection and FP rates. Rubin's rules were applied to estimate overall odds ratios (OR), confidence intervals (CI), and p-values for all covariates. Results: Of 13,754 women assessed, 1.2% (n=169) women received a cancer diagnosis. Most of the women were White (87.6%), 2.6% Asian, 5.3% Black; 1.5% self-identified as Hispanic; mean age, 64.4±11.3SD. Each point increase in AL increased the risk of cancer detection after screening mammography by 15% (OR=1.15,95% CI[1.06, 1.25],p=0.001). No association was detected between each MRS and cancer detection (all p>0.22). BI, the expected proportion of neighbors belonging to the same group, was associated with FP rate, with BI > 0.6 increasing the odds of FPs (OR=2.80[1.13-6.92],p=0.026). After adjusting for AL and MRSs, age and race were not significantly associated with cancer detection, but 5-year changes in age were associated with lower FP rate (OR=0.82[0.80, 0.84],p<0.001). Conclusions: AL was associated with an increased risk of cancer detection after screening mammography after adjusting for age, race, and MRSs. The MRS BI above 0.6 was associated with an increased false positive rate. Further work is needed to confirm these observations. Clinical Relevance Statement: AL and MRS (i.e., BIS) may represent potential biomarkers for personalized mammographic screening for BC.

Journal of Clinical OncologyVol. 43(16_suppl)
University of Michigan (US), Massachusetts General Hospital (US), Columbia University (US)
Openalex Percentile: Top 95%
AI in cancer detection
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