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DOI 10.1093/jnci/djae335

Медицинская библиотека · Journal of the National Cancer Institute · 2025

Evaluating the performance of the Breast and Ovarian Analysis of Disease Incidence Algorithm model in predicting 10-year breast cancer risks in UK Biobank.

Petitjean Carmen, Wilcox Naomi, Ficorella Lorenzo, Dennis Joe, Tyrer Jonathan, Lush Michael, Simard Jacques, Easton Douglas, Antoniou Antonis C, Yang Xin

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Аннотация

BACKGROUND

The Breast and Ovarian Analysis of Disease Incidence Algorithm (BOADICEA) model predicts breast cancer risk using cancer family history, epidemiological, and genetic data. We evaluated its validity in a large prospective cohort.

METHODS

We assessed model calibration, discrimination and risk classification ability in 217 885 women (6838 incident breast cancers) aged 40-70 years of self-reported White ethnicity with no previous cancer from the UK Biobank. Age-specific risk classification was assessed using relative risk thresholds equivalent to the absolute lifetime risk categories of less than 17%, 17%-30%, and 30% or more, recommended by the National Institute for Health and Care Excellence guidelines. We predicted 10-year risks using BOADICEA v.6 considering cancer family history, questionnaire-based risk factors, a 313-single nucleotide polymorphisms polygenic score, and pathogenic variants. Mammographic density data were not available.

RESULTS

The polygenic risk score was the most discriminative risk factor (area under the curve [AUC] = 0.65). Discrimination was highest when considering all risk factors (AUC = 0.66). The model was well calibrated overall (expected-to-observed ratio = 0.99, 95% confidence interval [CI] = 0.97 to 1.02; calibration slope = 0.99, 95% CI = 0.99 to 1.00), and in deciles of predicted risks. Discrimination was similar in women aged younger and older than 50 years. There was some underprediction in women aged younger than 50 years (expected-to-observed ratio = 0.89, 95% CI = 0.84 to 0.94; calibration slope = 0.96, 95% CI = 0.94 to 0.97), which was explained by the higher breast cancer incidence in UK Biobank than the UK population incidence in this age group. The model classified 87.2%, 11.4%, and 1.4% of women in relative risk categories less than 1.6, 1.6-3.1, and at least 3.1, identifying 25.6% of incident breast cancer patients in category relative risk of at least 1.6.

CONCLUSION

BOADICEA, implemented in CanRisk (www.canrisk.org), provides valid 10-year breast cancer risk, which can facilitate risk-stratified screening and personalized breast cancer risk management.

Для цитирования: Petitjean Carmen, Wilcox Naomi, Ficorella Lorenzo, Dennis Joe, Tyrer Jonathan, Lush Michael, Simard Jacques, Easton Douglas, Antoniou Antonis C, Yang Xin. Evaluating the performance of the Breast and Ovarian Analysis of Disease Incidence Algorithm model in predicting 10-year breast cancer risks in UK Biobank.. Journal of the National Cancer Institute. 2025. DOI: 10.1093/jnci/djae335.

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