Estimation of mortality rates for disease simulation models using Bayesian evidence synthesis
Estimation of mortality rates for disease simulation models using Bayesian evidence synthesis
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DOI：
10.1177/0272989x06291326
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发表时间：
2006-09-01
影响因子：
3.6
通讯作者：
Gazelle, G. Scott
中科院分区：
文献类型：
--
作者：
McMahon, Pamela M.;Zaslavsky, Alan M.;Gazelle, G. Scott
目的.作者提出了一种贝叶斯方法，用于估计疾病模拟模型输入的竞争风险。当对导致大部分全因死亡率的疾病建模时，特别是当感兴趣的疾病的死亡率和其他原因的死亡率都受到相同风险因素的影响时，建议采用这种方法。方法.作者证明了贝叶斯证据合成估计其他原因的死亡率，分层吸烟状态，用于肺癌的模拟模型。使用与死亡登记相关的国家（美国）调查数据（国家健康访谈调查[NHIS]-多死因文件）拟合3种死因（肺癌、心脏病和所有其他原因）的原因特异性风险模型，控制年龄、性别、种族和吸烟状况。在WinBUGS（版本1.4.1，MRC Biostatistics Unit，UK）中对NHIS数据与关于死亡人数和原因的国家生命统计数据进行了综合。说明了对NHIS和生命统计数据之间不一致的纠正。一项已发表的队列研究是吸烟相关死亡率的既往信息来源。结果根据5年年龄间隔、种族（白色和黑色）、性别和吸烟状况（目前、以前和从不吸烟）分层，估计特定时间段（1987-1995年）肺癌和其他原因死亡（进一步分为心脏病和所有其他原因）年死亡率的边缘后验密度。总体而言，目前吸烟的黑人死亡率最高。结论.贝叶斯证据合成是估计按人口因素分层的死因别死亡率的有效方法。
Purpose. The authors propose a Bayesian approach for estimating competing risks for inputs to disease simulation models. This approach is suggested when modeling a disease that causes a large proportion of all-cause mortality, particularly when mortality from the disease of interest and other-cause mortality are both affected by the same risk factor. Methods. The authors demonstrate a Bayesian evidence synthesis by estimating other-cause mortality, stratified by smoking status, for use in a simulation model of lung cancer. National (US) survey data linked to death registries (National Health Interview Survey [NHIS]-Multiple Cause of Death files) were used to fit cause-specific hazard models for 3 causes of death (lung cancer, heart disease, and all other causes), controlling for age, sex, race, and smoking status. Synthesis of NHIS data with national vital statistics data on numbers and causes of deaths was performed in WinBUGS (version 1.4.1, MRC Biostatistics Unit, UK). Correction for inconsistencies between the NHIS and vital statistics data is described. A published cohort study was a source of prior information for smoking-related mortality. Results. Marginal posterior densities of annual mortality rates for lung cancer and other-cause death (further divided into heart disease and all other causes), stratified by 5-year age interval, race (white and black), gender, and smoking status (current, former, never), were estimated, specific to a time period (1987-1995). Overall, black current smokers experienced the highest mortality rates. Conclusions. Bayesian evidence synthesis is an effective method for estimation of cause-specific mortality rates, stratified by demographic factors.