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• W4387161232 abstract "Abstract Background. Generalizability of predictive models for pathological complete response (pCR) and overall survival (OS) in breast cancer patients requires diverse datasets. This study employed four machine-learning models to predict pCR and OS up to 7.5 years using data from a diverse and underserved inner-city population. Methods. Demographics, staging, tumor subtypes, income, insurance status, and data from radiology reports were obtained from 475 breast cancer patients on neoadjuvant chemotherapy from 01/01/2017 to 12/31/2021 in an inner-city health system. Logistic regression, Neural Network, Random Forest, and Gradient Boosted Regression models were used to predict outcomes (pCR and OS) with five-fold cross validation. Results. pCR was not associated with age, race, ethnicity, differentiation, income, and insurance status (p > 0.05). ER-/HER2 + showed the highest pCR rate, followed by triple negative, ER+/HER2+, and ER+/HER2- (p < 0.05), tumor staging (p = 0.011), tumor size (p < 0.003) and background parenchymal enhancement (BPE) (p < 0.03) were associated with pCR. Machine-learning models ranked ER+/HER2-, ER-/HER2+, tumor size, and BPE as top predictors of pCR (AUC = 0.74–0.76). OS was associated with race, pCR status, tumor subtype, and insurance status (p < 0.05), but not ethnicity and incomes (p > 0.05). Machine-learning models ranked tumor stage, pCR, nodal stage, and triple negative subtype as top predictors of OS (AUC = 0.83–0.85). When grouping race and ethnicity by tumor subtypes, neither OS nor pCR were different due to race and ethnicity for each tumor subtype (p > 0.05). Conclusion. Tumor subtypes and imaging characteristics were top predictors of pCR in our inner-city population. Insurance status, race, tumor subtypes and pCR were associated with OS. Machine-learning models accurately predicted pCR and OS." @default.
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• W4387161232 date "2023-09-29" @default.
• W4387161232 modified "2023-09-30" @default.
• W4387161232 title "Machine learning prediction of pathological complete response and overall survival of breast cancer patients in an underserved inner-city population" @default.
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• W4387161232 doi "https://doi.org/10.21203/rs.3.rs-3378373/v1" @default.
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