癌症发病率的比例风险模型和年龄-时期-队列分析。
Proportional hazards models and age-period-cohort analysis of cancer rates.
机构信息
Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Rockville, MD 20852-7244, USA.
出版信息
Stat Med. 2010 May 20;29(11):1228-38. doi: 10.1002/sim.3865.
Abstract
Age-period-cohort (APC) analysis is widely used in cancer epidemiology to model trends in cancer rates. We develop methods for comparative APC analysis of two independent cause-specific hazard rates assuming that an APC model holds for each one. We construct linear hypothesis tests to determine whether the two hazards are absolutely proportional or proportional after stratification by cohort, period, or age. When a given proportional hazards model appears adequate, we derive simple expressions for the relative hazards using identifiable APC parameters. To demonstrate the utility of these new methods, we analyze cancer incidence rates in the United States in blacks versus whites for selected cancers, using data from the National Cancer Institute's Surveillance, Epidemiology, and End Results Program. The examples illustrate that each type of proportionality may be encountered in practice.
摘要
年龄-时期-队列（APC）分析广泛应用于癌症流行病学中，用于对癌症发病率的趋势进行建模。我们开发了针对两种独立的特定原因风险率的比较 APC 分析方法，假设每种方法都适用 APC 模型。我们构建线性假设检验来确定两个风险率是否绝对成比例或在按队列、时期或年龄分层后成比例。当给定的比例风险模型看起来足够时，我们使用可识别的 APC 参数推导出相对风险的简单表达式。为了展示这些新方法的实用性，我们使用美国国家癌症研究所的监测、流行病学和最终结果计划的数据，分析了美国黑人和白人中特定癌症的癌症发病率。这些例子说明，在实践中可能会遇到每种类型的比例性。
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