Handling missing quality of life data in HIV clinical trials: what is practical?
Handling missing quality of life data in HIV clinical trials: what is practical?
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DOI：
10.1007/s11136-007-9284-3
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发表时间：
2008-02-01
影响因子：
3.5
通讯作者：
Wu, Albert W.
中科院分区：
文献类型：
--
作者：
Fairclough, Diane L.;Thijs, Herbert;Wu, Albert W.
在临床试验中缺失健康相关的生活质量（HRQOL）数据可能会影响结论，但在HIV临床试验中尚未对其影响进行彻底研究。尽管多次建议避免完整病例（CC）分析和末次观察值结转（LOCF），但这些方法通常用于处理缺失数据。本次调查的目的是描述使用不同的分析方法的假设下，完全随机缺失（MCAR），随机缺失（MAR），和随机缺失（MNAR）使用HIV作为一个实证example.Methods医疗结果研究艾滋病毒（MOS-HIV）健康调查数据相结合，从两个大的开放标签的跨国艾滋病毒临床试验比较治疗A和B超过48周。纳入HRQOL分析需要在基线和至少一次随访访视（第8、16、24、40、48周）时完成MOS-HIV。分析的主要结果是从第0周到第48周的心理健康总结（MHS）、身体健康总结（PHS）、疼痛和健康困扰评分的变化，使用CC、LOCF、广义估计方程（GEE）、使用联合混合效应模型的直接似然和敏感性分析以及马尔可夫链蒙特卡罗（MCMC）多重插补进行分析。所有模型均包括时间和处理。基线和纵向变量（不良事件和停药原因）仅用于插补model.Results共511例患者随机分配到治疗A和473治疗B完成了MOS-HIV在基线和至少一个随访访视。在第48周，71%的治疗A组患者和31%的治疗B组患者完成了MOS-HIV调查。检查每个治疗组内的变化，CC和MCMC通常产生最大或最积极的变化。联合模型是最保守的;直接似然和GEE产生中间结果; LOCF显示没有一致的趋势。组内变化的范围大于组间差异（治疗A的MHS评分内：0.1至1.6，治疗B：0.4至2.0;组间：-0.7至0.4;治疗A的PHS评分内：-1.5至0.4，治疗B：-1.7至-0.2;组间：0.1至1.1）。疼痛和健康困扰评分的组内变化和组间差异的大小相似。在所有情况下，估计值的范围都很小
Aims Missing health-related quality of life ( HRQOL) data in clinical trials can impact conclusions but the effect has not been thoroughly studied in HIV clinical trials. Despite repeated recommendations to avoid complete case ( CC) analysis and last observation carried forward ( LOCF), these approaches are commonly used to handle missing data. The goal of this investigation is to describe the use of different analytic methods under assumptions of missing completely at random ( MCAR), missing at random ( MAR), and missing not at random ( MNAR) using HIV as an empirical example.Methods Medical Outcomes Study HIV ( MOS-HIV) Health Survey data were combined from two large open-label multinational HIV clinical trials comparing treatments A and B over 48 weeks. Inclusion in the HRQOL analysis required completion of the MOS-HIV at baseline and at least one follow-up visit ( weeks 8, 16, 24, 40, 48). Primary outcomes for the analysis were change from week 0 to 48 in mental health summary ( MHS), physical health summary ( PHS), pain and health distress scores analyzed using CC, LOCF, generalized estimating equations ( GEE), direct likelihood and sensitivity analyses using joint mixed-effects model, and Markov chain Monte Carlo ( MCMC) multiple imputation. Time and treatment were included in all models. Baseline and longitudinal variables ( adverse event and reason for discontinuation) were only used in the imputation model.Results A total of 511 patients randomized to treatment A and 473 to treatment B completed the MOS-HIV at baseline and at least one follow-up visit. At week 48, 71% of patients on treatment A and 31% on treatment B completed the MOS-HIV survey. Examining changes within each treatment group, CC and MCMC generally produced the largest or most positive changes. The joint model was most conservative; direct likelihood and GEE produced intermediate results; LOCF showed no consistent trend. There was greater spread for within-group changes than between-group differences ( within MHS scores for treatment A: 0.1 to 1.6, treatment B: 0.4 to 2.0; between groups: -0.7 to 0.4; within PHS scores for treatment A: -1.5 to 0.4, treatment B: -1.7 to -0.2; between groups: 0.1 to 1.1). The size of within-group changes and between group differences was of similar magnitude for the pain and health distress scores. In all cases, the range of estimates was small