A stochastic model for predicting the mortality of breast cancer.
A stochastic model for predicting the mortality of breast cancer.
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DOI：
10.1093/jncimonographs/lgj011
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发表时间：
2006-01-01
期刊：
影响因子：
--
通讯作者：
Zelen, Marvin
中科院分区：
文献类型：
--
作者：
Lee, Sandra;Zelen, Marvin
考虑一组按出生年份确定的妇女，其中一些人最终将被诊断为乳腺癌。建立了一个随机模型，用于预测美国乳腺癌死亡率，该模型取决于乳腺X线摄影筛查的治疗和传播进展。预测的死亡率可以与没有筛查计划和缺乏现代治疗的常规护理的同一队列进行比较，或者与只有一部分参与筛查计划并接受现代治疗的队列进行比较。该模型设想妇女可能处于四种健康状态：即，1)无疾病或不能诊断的乳腺癌（S 0），2）临床前状态（Sp），3）临床状态（Sc），和4）疾病特异性死亡（Sd）。临床前疾病是指无症状但可以通过特殊检查诊断的乳腺癌。临床状态是指在常规护理下诊断出的有症状的疾病。该模型的基本假设之一是疾病是进行性的;即，前三种状态的转变是S 0->Sp-> Sc。另一个基本假设是与早期诊断相关的死亡率的任何降低是由于诊断的阶段转变;即，早期诊断导致更大比例的早期患者。该模型用于预测1975-2000年美国女性乳腺癌死亡率的变化。该模型是通用的，可以预测其他慢性病的死亡率，满足两个基本假设。
Consider a cohort of women, identified by year of birth, some of whom will eventually be diagnosed with breast cancer. A stochastic model is developed for predicting the U.S. breast cancer mortality that depends on advances in therapy and dissemination of mammographic screening. The predicted mortality can be compared with the same cohort having usual care with no screening program and absence of modern therapy, or a cohort in which only a proportion participate in a screening program and have modern therapy. The model envisions that a woman may be in four health states: i.e., 1) no disease or breast cancer that cannot be diagnosed (S0), 2) preclinical state (Sp), 3) clinical state (Sc), and 4) disease-specific death (Sd). The preclinical disease refers to breast cancer that is asymptomatic but that may be diagnosed with a special exam. The clinical state refers to symptomatic disease diagnosed under usual care. One of the basic assumptions of the model is that the disease is progressive; i.e., the transitions for the first three states are S0-->Sp-->Sc. The other basic assumption is that any reduction in mortality associated with earlier diagnosis is due to a stage shift in diagnosis; i.e., early diagnosis results in a larger proportion of earlier stage patients. The model is used to predict changes in female breast cancer mortality in the U.S. women for 1975-2000. The model is general and may predict mortality for other chronic diseases that satisfy the two basic assumptions.