Luo Sheng, Zou Haotian, Goetz Christopher G, Choi Dongrak, Oakes David, Simuni Tanya, Stebbins Glenn T
Department of Biostatistics and Bioinformatics Duke University Durham North Carolina USA.
Department of Biostatistics University of North Carolina at Chapel Hill Chapel Hill North Carolina USA.
Mov Disord Clin Pract. 2021 Aug 3;8(7):1083-1091. doi: 10.1002/mdc3.13311. eCollection 2021 Oct.
Although nontremor and tremor Part 3 Movement Disorder Society-Unified Parkinson's Disease Rating Scale items measure different impairment domains, their distinct progression and drug responsivity remain unstudied longitudinally. The total score may obscure important time-based and treatment-based changes occurring in the individual domains.
Using the unique advantages of item response theory (IRT), we developed novel longitudinal unidimensional and multidimensional models to investigate nontremor and tremor changes occurring in an interventional Parkinson's disease (PD) study.
With unidimensional longitudinal IRT, we assessed the 33 Part 3 item data (22 nontremor and 10 tremor items) of 336 patients with early PD from the STEADY-PD III (Safety, Tolerability, and Efficacy Assessment of Isradipine for PD, placebo vs. isradipine) study. With multidimensional longitudinal IRT, we assessed the progression rates over time and treatment (in overall motor severity, nontremor, and tremor domains) using Markov Chain Monte Carlo implemented in Stan.
Regardless of treatment, patients showed significant but different time-based deterioration rates for total motor, nontremor, and tremor scores. Isradipine was associated with additional significant deterioration over placebo in total score and nontremor scores, but not in tremor score. Further highlighting the 2 separate latent domains, nontremor and tremor severity changes were positively but weakly correlated (correlation coefficient, 0.108).
Longitudinal IRT analysis is a novel statistical method highly applicable to PD clinical trials. It addresses limitations of traditional linear regression approaches and previous IRT investigations that either applied cross-sectional IRT models to longitudinal data or failed to estimate all parameters simultaneously. It is particularly useful because it can separate nontremor and tremor changes both over time and in response to treatment interventions.
尽管非震颤和震颤部分3运动障碍协会统一帕金森病评定量表项目测量的是不同的损伤领域，但它们不同的进展情况和药物反应性尚未进行纵向研究。总分可能会掩盖各个领域中发生的基于时间和治疗的重要变化。
利用项目反应理论（IRT）的独特优势，我们开发了新颖的纵向单维和多维模型，以研究帕金森病（PD）干预性研究中发生的非震颤和震颤变化。
采用单维纵向IRT，我们评估了来自STEADY-PD III（伊拉地平治疗PD的安全性、耐受性和疗效评估，安慰剂与伊拉地平对照）研究的336例早期PD患者的33个部分3项目数据（22个非震颤项目和10个震颤项目）。采用多维纵向IRT，我们使用在Stan中实现的马尔可夫链蒙特卡罗方法评估了随时间和治疗（在总体运动严重程度、非震颤和震颤领域）的进展率。
无论治疗如何，患者在总运动、非震颤和震颤评分方面均显示出显著但不同的基于时间的恶化率。与安慰剂相比，伊拉地平在总分和非震颤评分方面与额外的显著恶化相关，但在震颤评分方面没有。进一步突出了两个独立的潜在领域，非震颤和震颤严重程度变化呈正相关但相关性较弱（相关系数为0.108）。
纵向IRT分析是一种高度适用于PD临床试验的新颖统计方法。它解决了传统线性回归方法和以前IRT研究的局限性，以前的研究要么将横断面IRT模型应用于纵向数据，要么未能同时估计所有参数。它特别有用，因为它可以区分非震颤和震颤随时间以及对治疗干预的变化。
