Department of Epidemiology and Biostatistics, School of Medicine, University of California San Francisco, San Francisco, California, United States of America.
Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California, United States of America.
PLoS One. 2023 May 19;18(5):e0282878. doi: 10.1371/journal.pone.0282878. eCollection 2023.
Complex systems models of breast cancer have previously focused on prediction of prognosis and clinical events for individual women. There is a need for understanding breast cancer at the population level for public health decision-making, for identifying gaps in epidemiologic knowledge and for the education of the public as to the complexity of this most common of cancers.
We developed an agent-based model of breast cancer for the women of the state of California using data from the U.S. Census, the California Health Interview Survey, the California Cancer Registry, the National Health and Nutrition Examination Survey and the literature. The model was implemented in the Julia programming language and R computing environment. The Paradigm II model development followed a transdisciplinary process with expertise from multiple relevant disciplinary experts from genetics to epidemiology and sociology with the goal of exploring both upstream determinants at the population level and pathophysiologic etiologic factors at the biologic level. The resulting model reproduces in a reasonable manner the overall age-specific incidence curve for the years 2008-2012 and incidence and relative risks due to specific risk factors such as BRCA1, polygenic risk, alcohol consumption, hormone therapy, breastfeeding, oral contraceptive use and scenarios for environmental toxin exposures.
The Paradigm II model illustrates the role of multiple etiologic factors in breast cancer from domains of biology, behavior and the environment. The value of the model is in providing a virtual laboratory to evaluate a wide range of potential interventions into the social, environmental and behavioral determinants of breast cancer at the population level.
乳腺癌的复杂系统模型此前主要集中在预测个体女性的预后和临床事件上。为了进行公共卫生决策、了解流行病学知识的差距,以及向公众普及这种最常见癌症的复杂性,有必要从人群水平上了解乳腺癌。
我们使用来自美国人口普查、加利福尼亚健康访谈调查、加利福尼亚癌症登记处、国家健康和营养检查调查以及文献的数据,为加利福尼亚州的女性开发了一个基于代理的乳腺癌模型。该模型是用 Julia 编程语言和 R 计算环境实现的。Paradigm II 模型的开发遵循跨学科的过程,涉及来自遗传学、流行病学和社会学等多个相关学科的专家,旨在探索人群水平的上游决定因素和生物学水平的病理生理病因因素。所得到的模型以合理的方式再现了 2008-2012 年特定年龄段的总体发病率曲线,以及特定风险因素(如 BRCA1、多基因风险、酒精摄入、激素治疗、母乳喂养、口服避孕药使用)的发病率和相对风险,以及环境毒素暴露的情景。
Paradigm II 模型说明了生物学、行为和环境领域中多种病因因素在乳腺癌中的作用。该模型的价值在于提供了一个虚拟实验室,可以评估人群水平上对乳腺癌的社会、环境和行为决定因素进行广泛的潜在干预措施。