The NCC mathematical modeling framework for decision-making of six major cancers

IF 7.6 Q1 ONCOLOGY
Changfa Xia, Wanqing Chen
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引用次数: 0

Abstract

Objective

Mathematical modeling and simulation is a useful research method to inform decision-making. This article aims to describe the National Cancer Center (NCC) modeling framework and how well it reproduces observed empirical data for six major cancers.

Methods

We developed the NCC modeling framework for six major cancers in China (lung, liver, stomach, colorectal, esophageal, and breast), which simulates the life-histories represented by states among normal, precancerous lesion, stage-specific invasive cancer, and death for six cancers separately. Each NCC simulation model could be illustrated as an integrated framework of 3 modules: a demography module, natural history module, and screening module. Combined with costs and health utilities data, the models could have many detailed outputs for informing decisions, including the harm of screening (e.g., false positives, complications, and overdiagnosis), healthcare costs, and benefits (quality-adjusted life years gained, cancer incidence and mortality, and investment returns). We calibrated the models to Chinese population-based observations on cancer incidence, mortality, and stage distribution. All models are validated by comparing model simulated results to data observed from nationwide cancer registration and a large prospective cohort study.

Results

The simulated results from the calibrated models consistently match the epidemiological patterns in six major cancer incidence, mortality, and stage distributions in China. Model projected age-specific cancer incidence and mortality were close to the observed data in the national cancer registration. The NCC modeling framework reproduced the cumulative cancer cases and deaths observed in the prospective cohort study at 7.0 and 10.8 years of follow-up. Model estimated net survival rates also consistent with population-based statistics.

Conclusion

The NCC modeling framework's ability to reproduce the observed population-level cancer statistics and the cancer cases in a prospective cohort study suggests its results are reliable to inform decision-making related to six major cancers in China.

六种主要癌症决策的NCC数学建模框架
目的数学建模与仿真是一种为决策提供信息的有效研究方法。本文旨在描述国家癌症中心(NCC)建模框架,以及它如何很好地再现六种主要癌症的观察经验数据。方法:我们针对中国六种主要癌症(肺癌、肝癌、胃癌、结肠直肠癌、食管癌和乳腺癌)开发了NCC建模框架,分别模拟了六种癌症的正常、癌前病变、分期特异性浸润性癌症和死亡状态所代表的生活史。每个NCC模拟模型都可以被描述为3个模块的集成框架:人口统计模块、自然历史模块和筛选模块。结合成本和健康效用数据,这些模型可以为决策提供许多详细的输出,包括筛查的危害(例如,假阳性、并发症和过度诊断)、医疗保健成本和收益(获得的质量调整寿命年、癌症发病率和死亡率以及投资回报)。我们将模型校准为基于中国人群的癌症发病率、死亡率和分期分布的观察结果。通过将模型模拟结果与全国癌症登记和大型前瞻性队列研究中观察到的数据进行比较,验证了所有模型。结果校正模型的模拟结果与中国六种主要癌症发病率、死亡率和分期分布的流行病学模式一致。模型预测的年龄特异性癌症发病率和死亡率与国家癌症登记中观察到的数据接近。NCC建模框架再现了前瞻性队列研究中随访7.0年和10.8年时观察到的累积癌症病例和死亡人数。模型估计的净存活率也与基于人群的统计数据一致。NCC建模框架能够再现观察到的人群水平的癌症统计数据和前瞻性队列研究中的癌症病例,这表明其结果对于中国六种主要癌症的相关决策是可靠的。
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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CiteScore
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