Ibrahim Fowzia, Tom Brian D M, Scott David L, Prevost Andrew Toby
Centre for Rheumatic Diseases, Department of Inflammation Biology, School of Immunology & Microbial Sciences, Faculty of Life Sciences & Medicine, King's College London, Cutcombe Road, London SE5 9RJ, UK.
MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
Ther Adv Musculoskelet Dis. 2022 Sep 17;14:1759720X221114103. doi: 10.1177/1759720X221114103. eCollection 2022.
Composite measures, like the Disease Activity Score for 28 joints (DAS28), are key primary outcomes in rheumatoid arthritis (RA) trials. DAS28 combines four different components in a continuous measure. When one or more of these components are missing the overall composite score is also missing at intermediate or trial endpoint assessments.
This study examined missing data patterns and mechanisms in a longitudinal RA trial to evaluate how best to handle missingness when analysing composite outcomes.
The Tumour-Necrosis-Factor Inhibitors against Combination Intensive Therapy (TACIT) trial was an open label, pragmatic randomized multicentre two arm non-inferiority study. Patients were followed up for 12 months, with monthly measurement of the composite outcome and its components. Active RA patients were randomized to conventional disease modifying drugs (cDMARDs) or Tumour Necrosis Factor-α inhibitors (TNFis).
The TACIT trial was used to explore the extent of missing data in the composite outcome, DAS28. Patterns of missing data in components and the composite outcome were examined graphically. Longitudinal multivariable logistic regression analysis assessed missing data mechanisms during follow-up.
Two hundred and five patients were randomized: at 12 months 59/205 (29%) had unobserved composite outcome and 146/205 (71%) had an observed DAS28 outcome; however, 34/146 had one or more intermediate assessments missing. We observed mixed missing data patterns, especially for the missing composite outcome due to one component missing rather than patient not attending thier visit. Age and gender predicted missingness components, providing strong evidence the missing observations were unlikely to be Missing Completely at Random (MCAR).
Researchers should undertake detailed evaluations of missing data patterns and mechanisms at the final and intermediate time points, whether or not the outcome variable is a composite outcome. In addition, the impact on treatment estimates in patients who only provide data at milestone assessments need to be assessed.
复合指标，如28个关节疾病活动评分（DAS28），是类风湿关节炎（RA）试验的关键主要结局。DAS28在一个连续指标中综合了四个不同的组成部分。当这些组成部分中的一个或多个缺失时，在中期或试验终点评估时，整体复合评分也会缺失。
本研究调查了一项RA纵向试验中的缺失数据模式和机制，以评估在分析复合结局时如何最好地处理缺失值。
肿瘤坏死因子抑制剂联合强化治疗（TACIT）试验是一项开放标签、实用的随机多中心双臂非劣效性研究。对患者进行了12个月的随访，每月测量复合结局及其组成部分。活动性RA患者被随机分为接受传统改善病情抗风湿药物（cDMARDs）或肿瘤坏死因子-α抑制剂（TNFis）治疗。
利用TACIT试验探讨复合结局DAS28中缺失数据的程度。以图表形式检查了各组成部分和复合结局中缺失数据的模式。纵向多变量逻辑回归分析评估了随访期间的缺失数据机制。
205例患者被随机分组：在12个月时，59/205（29%）的患者未观察到复合结局，146/205（71%）的患者有可观察到的DAS28结局；然而，34/146的患者有一项或多项中期评估缺失。我们观察到了混合的缺失数据模式，尤其是由于一个组成部分缺失而非患者未就诊导致的复合结局缺失。年龄和性别可预测组成部分的缺失情况，有力证据表明缺失观察值不太可能是完全随机缺失（MCAR）。
研究人员应在最终和中期时间点对缺失数据模式和机制进行详细评估，无论结局变量是否为复合结局。此外，还需要评估仅在里程碑评估时提供数据的患者对治疗估计的影响。
ISRCTN编号：37438295。
