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Purpose <p>Accurate identification of breast cancer patients at risk of de novo bone metastasis (BM) may support staging and treatment planning. The current study externally validated a previously published nomogram in a Mexican cohort of women with newly diagnosed breast cancer.</p> Methods <p>A retrospective external validation study was conducted in women diagnosed at a tertiary referral cancer center in Mexico during 2023. Model performance was evaluated through discrimination, calibration, and clinical utility. Discrimination was assessed using the area under the receiver operating characteristic curve (AUC–ROC) and precision–recall curve (AUC–PR). Calibration was evaluated using calibration intercept and slope, calibration plots, and logistic recalibration. Decision curve analysis assessed clinical utility. A sensitivity analysis excluding surgery status was also performed.</p> Results <p>The validation cohort included 293 patients, of whom 11 (3.8%) presented with de novo bone metastasis. The original model demonstrated moderate discrimination (AUC–ROC 0.81, 95% CI 0.67–0.96; AUC–PR 0.32, 95% CI 0.05–0.66). In the sensitivity analysis, AUC–ROC remained similar (0.80; 95% CI 0.66–0.95), whereas AUC–PR decreased to 0.23 (95% CI 0.03–0.52). Calibration was suboptimal, with a calibration intercept of −2.99 and a slope of 0.90, indicating systematic overestimation of risk. Recalibration improved agreement between predicted and observed risks. Clinical utility was comparable across models, with modest improvements after recalibration.</p> Conclusions <p>The nomogram maintained reasonable discrimination but exhibited substantial calibration drift in this independent Mexican cohort. External validation and recalibration may be necessary before implementation in populations distinct from those used for model development.</p>

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External validation of a nomogram for de novo bone metastasis in breast cancer: a single-center Mexican cohort

  • 期刊论文

  • 发表日期：

    2026年7月4日

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  • Adrián Canizalez-Román,
  • Romina Llanes-Cardenas,
  • Francisco Antonio Martínez-Villa,
  • Diego Arriaga-Izabal

摘要

Purpose

Accurate identification of breast cancer patients at risk of de novo bone metastasis (BM) may support staging and treatment planning. The current study externally validated a previously published nomogram in a Mexican cohort of women with newly diagnosed breast cancer.

Methods

A retrospective external validation study was conducted in women diagnosed at a tertiary referral cancer center in Mexico during 2023. Model performance was evaluated through discrimination, calibration, and clinical utility. Discrimination was assessed using the area under the receiver operating characteristic curve (AUC–ROC) and precision–recall curve (AUC–PR). Calibration was evaluated using calibration intercept and slope, calibration plots, and logistic recalibration. Decision curve analysis assessed clinical utility. A sensitivity analysis excluding surgery status was also performed.

Results

The validation cohort included 293 patients, of whom 11 (3.8%) presented with de novo bone metastasis. The original model demonstrated moderate discrimination (AUC–ROC 0.81, 95% CI 0.67–0.96; AUC–PR 0.32, 95% CI 0.05–0.66). In the sensitivity analysis, AUC–ROC remained similar (0.80; 95% CI 0.66–0.95), whereas AUC–PR decreased to 0.23 (95% CI 0.03–0.52). Calibration was suboptimal, with a calibration intercept of −2.99 and a slope of 0.90, indicating systematic overestimation of risk. Recalibration improved agreement between predicted and observed risks. Clinical utility was comparable across models, with modest improvements after recalibration.

Conclusions

The nomogram maintained reasonable discrimination but exhibited substantial calibration drift in this independent Mexican cohort. External validation and recalibration may be necessary before implementation in populations distinct from those used for model development.