From associations to clinical practice: translating inflammatory-nutritional indices into a machine learning-driven model for breast cancer risk stratification with cross-ethnic validation - Takeaways - MDSpire

From associations to clinical practice: translating inflammatory-nutritional indices into a machine learning-driven model for breast cancer risk stratification with cross-ethnic validation

  • By

  • Yue Li

  • Ting Ding

  • Xiaoyan Zhou

  • Chao Lu

  • Yue Zhang

  • Qian He

  • Jiangbo Ding

  • July 15, 2026

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  • 1

    The study evaluated inflammatory-nutritional indices and their association with breast cancer risk and mortality using NHANES data.

  • 2

    Advanced Lung Cancer Inflammation Index (ALI) was inversely associated with breast cancer risk and all-cause mortality.

  • 3

    Neutrophil percentage-to-albumin ratio (NPAR), systemic inflammation response index (SIRI), and neutrophil-to-lymphocyte ratio (NLR) showed positive associations with breast cancer.

  • 4

    Machine learning model using XGBoost identified NPAR as the top predictive feature, achieving an AUC of 0.832.

  • 5

    External validation of the model yielded AUCs of 0.781 and 0.730 for different cohorts, indicating the need for population-specific calibration.

Original Source(s)

From associations to clinical practice: translating inflammatory-nutritional indices into a machine learning-driven model for breast cancer risk stratification with cross-ethnic validation

  • by Yue Li, Ting Ding, Xiaoyan Zhou, Chao Lu, Yue Zhang, Qian He, Jiangbo Ding

  • July 15, 2026

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