Establishing Long-Term Efficacy in Chronic Disease: Use of Recursive Partitioning and Propensity Score Adjustment to Estimate Outcome in MS

ContextEstablishing the long-term benefit of therapy in chronic diseases has been challenging. Long-term studies require non-randomized designs and, thus, are often confounded by biases. For example, although disease-modifying therapy in MS has a convincing benefit on several short-term outcome-measures in randomized trials, its impact on long-term function remains uncertain.
ObjectiveData from the 16-year Long-Term Follow-up study of interferon-beta-1b is used to assess the relationship between drug-exposure and long-term disability in MS patients.
Design/SettingTo mitigate the bias of outcome-dependent exposure variation in non-randomized long-term studies, drug-exposure was measured as the medication-possession-ratio, adjusted up or down according to multiple different weighting-schemes based on MS severity and MS duration at treatment initiation. A recursive-partitioning algorithm assessed whether exposure (using any weighing scheme) affected long-term outcome. The optimal cut-point that was used to define “high” or “low” exposure-groups was chosen by the algorithm. Subsequent to verification of an exposure-impact that included all predictor variables, the two groups were compared using a weighted propensity-stratified analysis in order to mitigate any treatment-selection bias that may have been present. Finally, multiple sensitivity-analyses were undertaken using different definitions of long-term outcome and different assumptions about the data.
Main Outcome MeasureLong-Term Disability.
ResultsIn these analyses, the same weighting-scheme was consistently selected by the recursive-partitioning algorithm. This scheme reduced (down-weighted) the effectiveness of drug exposure as either disease duration or disability at treatment-onset increased. Applying this scheme and using propensity-stratification to further mitigate bias, high-exposure had a consistently better clinical outcome compared to low-exposure (Cox proportional hazard ratio = 0.30–0.42; p<0.0001).
ConclusionsEarly initiation and sustained use of interferon-beta-1b has a beneficial impact on long-term outcome in MS. Our analysis strategy provides a methodological framework for bias-mitigation in the analysis of non-randomized clinical data.
Trial RegistrationClinicaltrials.govNCT00206635

研究背景：确定慢性病治疗的长期获益一直是颇具挑战性的课题。长期研究往往需采用非随机化设计，因此常受各类偏倚的干扰。例如，尽管多发性硬化（multiple sclerosis, MS）的疾病修正治疗（disease-modifying therapy）在随机对照试验中，于多项短期结局指标上展现出确凿的获益，但其对患者长期功能的影响仍不明确。
研究目的：本研究依托干扰素β-1b（interferon-beta-1b）的16年长期随访研究数据，旨在评估多发性硬化患者的药物暴露与长期残疾之间的关联。
研究设计与场景：为缓解非随机化长期研究中结局依赖性暴露变异带来的偏倚，本研究以药物持有率（medication-possession-ratio）作为药物暴露的衡量指标，并根据治疗起始时的多发性硬化严重程度与病程，通过多种不同的加权方案对其进行调整。采用递归分割算法（recursive-partitioning algorithm），评估采用任意加权方案的药物暴露是否对长期结局产生影响。该算法将选取用于定义“高”或“低”暴露组的最优截断点。在验证包含所有预测变量的暴露影响后，通过加权倾向得分分层分析（propensity-stratified analysis）对两组进行比较，以缓解可能存在的治疗选择偏倚。最后，本研究针对长期结局的不同定义与数据的不同假设，开展了多维度敏感性分析（sensitivity-analyses）。
主要结局指标：长期残疾。
研究结果：在本次分析中，递归分割算法始终选取了相同的加权方案。该方案会随着治疗起始时的病程或残疾程度加重，降低（下调权重）药物暴露的效应值。采用该加权方案并结合倾向得分分层分析进一步缓解偏倚后，高暴露组的临床结局始终优于低暴露组（Cox比例风险比（Cox proportional hazard ratio）=0.30~0.42；p<0.0001）。
研究结论：早期启动并持续使用干扰素β-1b（interferon-beta-1b），对多发性硬化患者的长期结局具有有益影响。本研究的分析策略，为非随机化临床数据的偏倚缓解提供了方法论框架。
试验注册：Clinicaltrials.gov NCT00206635