论文标题
从当前状态数据的慢性状态下估计疾病持续时间的慢性死亡率：关于长期护理需求的仿真研究
Estimation of excess mortality in a chronic condition from current status data with disease duration: simulation study about need for long-term care
论文作者
论文摘要
本文介绍了一种估计与当前状态数据的死亡率比率R的方法，并在慢性状态下持续时间，以防总体总体的一般死亡率。除了一般死亡率外，该方法还需要研究参与者的四个信息：调查/访谈的年龄和时间，是否存在慢性状况（当前状态），如果是的，则在存在多长时间内（持续时间）。该方法使用的微分方程将与没有条件的人相比，将患病率，发病率和死亡率与慢性病患者的R进行估计。 为了证明可行性，运行了基于基于疾病死亡模型（多状态模型）的模拟，其转型率是由长期护理动机的。发现该方法需要大量的研究参与者（100000或更多）才能以相对低的相对误差估算R。尽管样本量较大，但当易于获取横截面信息时，该方法在设置中可能很有用，例如，在索赔数据中，可以从重要的统计数据中获得特定于国家年龄的一般死亡率。
This article describes a method to estimate the mortality rate ratio R from current status data with duration in a chronic condition in case the general mortality of the overall population is known. Apart from the general mortality, the method requires four pieces of information from the study participants: age and time at the survey/interview, whether the chronic condition is present (current status) and if so, for how long the condition is present (duration). The method uses a differential equation that relates prevalence, incidence and mortality to estimate R of the people with the chronic condition compared to those without the condition. To demonstrate feasibility, a simulation based on the illness-death model (multi-state model) with transition rates motivated from long-term care is run. It is found that the method requires a large number of study participants (100000 or more) to estimate R with a reasonably low relative error. Despite the large sample size, the method can be useful in settings when cross-sectional information are easily available, e.g., in claims data, and national age-specific general mortality rates are accessible from vital statistics.
