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Related Experiment Video

Updated: Jun 2, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

Risk prediction models for familial breast cancer.

Sarah A McGarrigle1,2, Yvonne P Hanhauser2, David Mockler3

  • 1Department of Surgery, Trinity College Dublin, Trinity St James's Cancer Institute, Dublin, Ireland.

The Cochrane Database of Systematic Reviews
|June 1, 2026
PubMed
Summary
This summary is machine-generated.

This study evaluated breast cancer risk prediction models for women with a family history. The BOADICEA model showed good calibration and modest discrimination, suggesting its utility in managing familial breast cancer risk.

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Area of Science:

  • Oncology
  • Epidemiology
  • Biostatistics

Background:

  • Women with a family history of breast cancer face an elevated risk.
  • Breast cancer risk prediction models are used to estimate this probability.
  • The optimal model for this specific population remains unclear.

Purpose of the Study:

  • To identify, describe, and appraise breast cancer risk prediction models for women with a family history of breast cancer.
  • To meta-analyze the performance of these models in predicting breast cancer occurrence.

Main Methods:

  • Systematic literature search of multiple databases (MEDLINE, Embase, CINAHL, Web of Science) up to February 2022, with an extended search.
  • Inclusion of studies developing or validating models that use family history as a predictor.
  • Data extraction using CHARMS checklist, risk of bias assessment using PROBAST, and random-effects meta-analyses for pooled performance statistics (calibration and discrimination) where data allowed.

Main Results:

  • Twelve models were externally validated in the target population; four were meta-analyzed.
  • Gail (BCRAT) and BOADICEA models demonstrated good calibration (Observed/Expected ratios near 1).
  • Tyrer-Cuzick (IBIS) overpredicted risk, BRCAPRO underpredicted risk. Discriminatory accuracy (C-statistic) was modest and similar across Tyrer-Cuzick (v8), BOADICEA, and BRCAPRO, slightly outperforming Gail.

Conclusions:

  • BOADICEA demonstrates good calibration and comparable modest discrimination to Tyrer-Cuzick (v8) and BRCAPRO in women with a family history of breast cancer.
  • These findings suggest BOADICEA may be useful for patient management in this setting.
  • Limitations include high risk of bias in many studies, small numbers of validation studies, and heterogeneity; further improvements in model discrimination and reporting are needed.