重新校准已建立的微观模拟模型,以捕捉结直肠癌发病率和死亡率的趋势和预测。

IF 3.1 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES
Medical Decision Making Pub Date : 2025-04-01 Epub Date: 2025-02-06 DOI:10.1177/0272989X251314050
Jie-Bin Lew, Qingwei Luo, Joachim Worthington, Han Ge, Emily He, Julia Steinberg, Michael Caruana, Dianne L O'Connell, Eleonora Feletto, Karen Canfell
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引用次数: 0

摘要

背景:在规划未来的癌症控制和筛查举措时,需要考虑不断变化的结直肠癌(CRC)发病率,包括最近50岁以下人群发病率的增加。对澳大利亚国家肠癌筛查计划(NBCSP)中CRC变化趋势的影响进行可靠的评估,对于项目规划至关重要。现有的CRC微观模拟模型Policy1-Bowel进行了更新,以再现澳大利亚CRC趋势数据,并提供CRC和筛查相关结果的最新预测,为预防CRC的临床实践指南提供信息。方法:重新校准Policy1-Bowel,在没有NBCSP的情况下,重现1995-2045年澳大利亚结直肠癌发病率的统计年龄-时期-队列模型趋势和预测,以及1995-2020年澳大利亚结直肠癌发病率趋势、分期分布和生存率的已发表数据。通过与已公布的1995-2015年澳大利亚结直肠癌死亡率趋势和到2040年的统计预测相比较,重新校准的Policy1-Bowel预测得到了验证。开发了元模型来帮助校准过程并显着减少计算负担。结果:对Policy1-Bowel进行了重新校准,并根据年龄、性别、肠道位置、癌症分期和出生年份确定了病变发生率、CRC分期进展率、检出率和生存率的最适合参数集。重新校准的模型得到了验证,并成功再现了1995-2015年观察到的结直肠癌死亡率和2016-2030年的统计预测。结论:重新校准的policy1 -肠模型捕获了澳大利亚CRC未来发病率和死亡率负担的重要额外细节。这一点尤其重要,因为CRC发病率较高的年轻人群接近筛查年龄,可以为这些群体的决策提供信息。元建模方法允许快速重新校准,并使定期更新纳入新的证据是可行的。重点:在澳大利亚,50岁以下人群的结直肠癌发病率呈上升趋势,而50岁以上人群的发病率呈下降趋势,随着新的治疗技术的出现,结直肠癌的生存率正在提高。为了评估筛查对未来健康和经济的影响并为政策提供信息,建模必须包括结肠直肠癌发病率、死亡率和诊断阶段的详细趋势和预测。我们使用了包括综合年龄期队列预测和元模型校准在内的新技术来更新Policy1-Bowel,这是澳大利亚结直肠癌和筛查的详细微观模拟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recalibrating an Established Microsimulation Model to Capture Trends and Projections of Colorectal Cancer Incidence and Mortality.

BackgroundChanging colorectal cancer (CRC) incidence rates, including recent increases for people younger than 50 y, need to be considered in planning for future cancer control and screening initiatives. Reliable estimates of the impact of changing CRC trends on the National Bowel Cancer Screening Program (NBCSP) are essential for programmatic planning in Australia. An existing microsimulation model of CRC, Policy1-Bowel, was updated to reproduce Australian CRC trends data and provide updated projections of CRC- and screening-related outcomes to inform clinical practice guidelines for the prevention of CRC.MethodsPolicy1-Bowel was recalibrated to reproduce statistical age-period-cohort model trends and projections of CRC incidence for 1995-2045 in the absence of the NBCSP as well as published data on CRC incidence trends, stage distribution, and survival in 1995-2020 in Australia. The recalibrated Policy1-Bowel predictions were validated by comparison with published Australian CRC mortality trends for 1995-2015 and statistical projections to 2040. Metamodels were developed to aid the calibration process and significantly reduce the computational burden.ResultsPolicy1-Bowel was recalibrated, and best-fit parameter sets were identified for lesion incidence, CRC stage progression rates, detection rates, and survival rates by age, sex, bowel location, cancer stage, and birth year. The recalibrated model was validated and successfully reproduced observed CRC mortality rates for 1995-2015 and statistical projections for 2016-2030.ConclusionThe recalibrated Policy1-Bowel model captures significant additional detail on the future incidence and mortality burden of CRC in Australia. This is particularly relevant as younger cohorts with higher CRC incidence rates approach screening ages to inform decision making for these groups. The metamodeling approach allows fast recalibration and makes regular updates to incorporate new evidence feasible.HighlightsIn Australia, colorectal cancer incidence rates are increasing for people younger than 50 y but decreasing for people older than 50 y, and colorectal cancer survival is improving as new treatment technologies emerge.To evaluate the future health and economic impact of screening and inform policy, modeling must include detailed trends and projections of colorectal cancer incidence, mortality, and diagnosis stage.We used novel techniques including integrative age-period cohort projections and metamodel calibration to update Policy1-Bowel, a detailed microsimulation of colorectal cancer and screening in Australia.

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来源期刊
Medical Decision Making
Medical Decision Making 医学-卫生保健
CiteScore
6.50
自引率
5.60%
发文量
146
审稿时长
6-12 weeks
期刊介绍: Medical Decision Making offers rigorous and systematic approaches to decision making that are designed to improve the health and clinical care of individuals and to assist with health care policy development. Using the fundamentals of decision analysis and theory, economic evaluation, and evidence based quality assessment, Medical Decision Making presents both theoretical and practical statistical and modeling techniques and methods from a variety of disciplines.
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