Enhancing the OncoSim-Breast model using Canadian breast density information.

IF 3.4 2区医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Health Reports Pub Date : 2026-05-20 DOI:10.25318/82-003-x202600500002-eng

Oguzhan Alagoz, Rochelle Garner, Claude Nadeau, Andrew Coldman, Jean Hai Ein Yong, Martin J Yaffe, James G Mainprize, Dori Simeonov

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引用次数: 0

Abstract

Background: Breast cancer is the most commonly diagnosed cancer among women in Canada. Breast density substantially influences breast cancer risk and mammography performance. However, OncoSim-Breast, a Canadian microsimulation model representing breast cancer control, including cancer onset, screening, and survival, has not previously explicitly accounted for breast density. This study describes the incorporation of density-specific parameters into the OncoSim-Breast model.

Data and methods: Breast density-specific inputs were integrated into OncoSim-Breast using data from five Canadian provinces. Three key parameters - prevalence, relative risk of breast cancer, and digital mammography performance (sensitivity and specificity) - were estimated by age group and breast density category, following the American College of Radiology's Breast Imaging Reporting and Data System (BI-RADS) classification (categories A to D). Calibration experiments and internal validations were conducted to ensure the updated OncoSim-Breast model aligned with observed data from the Canadian Cancer Registry.

Results: The prevalence of dense breasts declined with age: BI-RADS categories C and D accounted for 58% of women younger than 50 years and 26% of those aged 70 and older. Digital mammography sensitivity also decreased with increasing density: among women younger than 50 years, sensitivity was 88% for Category A and 69% for Category D. The updated OncoSim-Breast model accurately replicated age-specific incidence, age-adjusted incidence, and stage distribution based on historical data from the Canadian Cancer Registry (2010 to 2019).

Interpretation: Incorporating breast density-specific parameters substantially improved the accuracy and policy relevance of OncoSim-Breast. The updated model provides a validated tool to inform screening policy decisions for Canadian women, allowing consideration for the effect of the variability of breast density among women.

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利用加拿大乳腺密度信息增强OncoSim-Breast模型。

背景：乳腺癌是加拿大女性中最常见的癌症。乳腺密度对乳腺癌风险和乳房x光检查表现有很大影响。然而，OncoSim-Breast，一个加拿大的代表乳腺癌控制的微模拟模型，包括癌症的发病、筛查和生存，之前并没有明确地解释乳腺密度。本研究描述了将密度特异性参数纳入OncoSim-Breast模型。数据和方法：使用来自加拿大五个省的数据，将乳腺密度特定输入整合到OncoSim-Breast中。三个关键参数-患病率，乳腺癌的相对风险和数字乳房x光检查表现（敏感性和特异性）-按照年龄组和乳腺密度类别进行估计，遵循美国放射学院乳腺成像报告和数据系统（BI-RADS）分类（A至D类）。进行校准实验和内部验证，以确保更新的OncoSim-Breast模型与加拿大癌症登记处的观察数据一致。结果：致密性乳房的患病率随着年龄的增长而下降：BI-RADS C类和D类占50岁以下女性的58%，70岁及以上女性的26%。数字乳房x线摄影的敏感性也随着密度的增加而下降：在50岁以下的女性中，A类敏感性为88%，d类敏感性为69%。更新的oncosimm - breast模型准确地复制了基于加拿大癌症登记处（2010年至2019年）历史数据的年龄特异性发病率、年龄调整发病率和分期分布。解释：纳入乳腺密度特异性参数大大提高了OncoSim-Breast的准确性和政策相关性。更新后的模型提供了一个有效的工具，为加拿大妇女的筛查政策决策提供信息，允许考虑妇女乳房密度变化的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Health Reports PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-

CiteScore

7.30

自引率

4.00%

发文量

期刊介绍： Health Reports publishes original research on diverse topics related to understanding and improving the health of populations and the delivery of health care. We publish studies based on analyses of Canadian national/provincial representative surveys or Canadian national/provincial administrative databases, as well as results of international comparative health research. Health Reports encourages the sharing of methodological information among those engaged in the analysis of health surveys or administrative databases. Use of the most current data available is advised for all submissions.