Kay R
Biometrics. 1986 Dec;42(4):855-65.
In studies of serial cancer markers or disease states and their relation to survival, data on the marker or state are usually obtained at infrequent time points during follow-up. A Markov model is developed to assess the dependence of risk of death on marker level or disease state and inferences within this model are based directly on data collected in this haphazard way. An application relating changing levels of serum alpha-fetoprotein to death in hepatocellular carcinoma is discussed in detail.
在对系列癌症标志物或疾病状态及其与生存率的关系进行研究时，关于标志物或状态的数据通常是在随访期间不频繁的时间点获取的。建立了一个马尔可夫模型来评估死亡风险对标志物水平或疾病状态的依赖性，并且该模型中的推断直接基于以这种随意方式收集的数据。详细讨论了一个将血清甲胎蛋白水平变化与肝细胞癌死亡相关联的应用。
