Treatment effect on ordinal functional outcome using piecewise multistate Markov model with unobservable baseline: an application to the modified Rankin scale.
Treatment effect on ordinal functional outcome using piecewise multistate Markov model with unobservable baseline: an application to the modified Rankin scale.
复制标题
使用具有不可观察基线的分段多状态马尔可夫模型对有序功能结果的治疗效果：改良兰金量表的应用。
DOI：
10.1080/10543406.2018.1489404
复制
发表时间：
2019
影响因子：
1.1
通讯作者：
Palesch,YukoY
中科院分区：
文献类型：
--
作者：
Cassarly,Christy;Martin,Renee'H;Chimowitz,Marc;Peña,EdselA;Ramakrishnan,Viswanathan;Palesch,YukoY
在临床试验中，纵向评估的顺序结局通常是二分的，只有最终指标用于主要分析，部分原因是为了便于临床解释。顺序量表的二分法和未能利用重复测量可降低统计功效。此外，在某些紧急情况下，无法在治疗前的基线评估相同的指标。对于这样一个数据集，分段常数多状态马尔可夫模型，其中包括一个潜在的未观察到的基线测量模型提出。这些模型可以用于分析疾病历史数据，并且在疾病过程自然地通过严重程度增加的阶段的临床应用中是有利的。使用急性卒中临床试验数据提供了两个示例。在这篇文章中得出的结论是一致的，从初步分析的治疗效果在两个激励的例子。使用这些模型可以对治疗效果进行更精细的检查，并描述从基线到随访访视的健康状态之间的变化，这可以提供对治疗效果的更多临床见解。
In clinical trials, longitudinally assessed ordinal outcomes are commonly dichotomized and only the final measure is used for primary analysis, partly for ease of clinical interpretation. Dichotomization of the ordinal scale and failure to utilize the repeated measures can reduce statistical power. Additionally, in certain emergent settings, the same measure cannot be assessed at baseline prior to treatment. For such a data set, a piecewise-constant multistate Markov model that incorporates a latent model for the unobserved baseline measure is proposed. These models can be useful in analyzing disease history data and are advantageous in clinical applications where a disease process naturally moves through increasing stages of severity. Two examples are provided using acute stroke clinical trials data. Conclusions drawn in this article are consistent with those from the primary analysis for treatment effect in both of the motivating examples. Use of these models allows for a more refined examination of treatment effect and describes the movement between health states from baseline to follow-up visits which may provide more clinical insight into the treatment effect.