Modeling of a composite score in Parkinson’s Disease using Item Response Theory
Gopichand Gottipati, Mats O. Karlsson, Elodie L. Plan
Dept of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
Objectives: Traditionally, the disease status in Parkinson’s Disease (PD) is quantified using Unified Parkinson’s Disease Rating Scale (UPDRS) and more recently, it was revised to Movement Disorder Society (MDS) sponsored – UPDRS [1]. The MDS-UPDRS scale includes a mix of 68 items rating motor or non-motor aspects of experiences of daily living, assessments and complications. The objective of the current analysis was to model MDS–UPDRS through the application of Item Response Theory (IRT) methodology.
Methods: Data used in this work were obtained from the Parkinson’s Progression Markers Initiative (PPMI) database [2]. Longitudinal MDS–UPDRS records were available from (up to) 60-week observational clinical study in 196 healthy controls (HC), 423 (de novo) PD subjects (diagnosed for ≤ 2 years and not taking any PD medication) and 64 SWEDD subjects (consented as PD subjects but not showing evidence of dopaminergic deficit). An IRT model was applied and the reported MDS–UPDRS responses were assumed to be related to an unobservable (latent) disease status variable. Modeling was performed using NONMEM 7.3 and simulation-based diagnostics were conducted using PsN and R.
Results: The final IRT model included 66 ordered categorical and 2 binary items, and a total of 337 item-specific parameters that were estimated using all the data. Item characteristic curves describing the probability of observing a specific score for an item were also constructed. The subject-specific disease status distribution of the PD subjects was used as a reference for the shifts in mean and variance for individuals of the HC and SWEDD cohorts. Typical individuals of the HC and SWEDD cohorts had a less severe disease status but a larger variability than the PD cohort, with an overlap between PD and SWEDD distributions more important than with the HC. Simulations with the IRT model were in good accordance with the observed MDS–UPDRS item level data. The time course of the disease status was described with different functions for each cohort, and only the PD patients displayed a significant linear increase over time.
Conclusions: It is the first time that PD is described using IRT methodology, although it has been applied in therapeutic areas such as Alzheimer’s disease [3], Multiple Sclerosis [4], and Schizophrenia [5]. IRT was shown to be more advantageous than conventional methods using total scores and can provide a framework for investigating disease progression and drug effects in PD.
References:
[1] Goetz C., Tilley B, Shaftman S, Stebbins G, Fahn S, Martinez M, Werner Poewe et al. Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS): Scale presentation and clinimetric testing results. Movement Disorders 2008; 23(15): 2129-2170.
[2] The Parkinson’s Progression Markers Initiative (PPMI) database (www.ppmi-info.org/data). For up-to-date information on the study, visit www.ppmi-info.org
[3] Ueckert S., Plan E, Ito K, Karlsson M, Corrigan B, Hooker A, & Alzheimer’s Disease Neuroimaging Initiative. . Improved utilization of ADAS-cog assessment data through Item Response Theory based pharmacometric modeling. Pharmaceutical Research 2014; 31(8):2152-2165.
[4] Kalezic A, Savic R, Munafo A, Ueckert S, Karlsson M. Application of Item Response Theory to EDSS Modeling in Multiple Sclerosis. PAGE 22 (2013) Abstract 2903 [www.page-meeting.org/?abstract=2903]
[5] Krekels E, Kalezi A, Friberg L, Vermeulen A, Karlsson M. Item Response Theory for Analyzing Placebo and Drug Treatment in Phase 3 Studies of Schizophrenia PAGE 23 (2014) Abstract 3145 [www.page-meeting.org/?abstract=3145]
Acknowledgement: PPMI – a public-private partnership – is funded by the Michael J. Fox Foundation for Parkinson’s Research and funding partners, including Abbvie, Inc.; Eli Lilly and Company and its subsidiary company Avid Radiopharmaceuticals; Biogen Idec Inc.; Bristol-Myers Squibb Company; Covance, Inc.; F-Hoffmann- La Roche Ltd and its subsidiary company Genetech, Inc.; GE Healthcare; GlaxoSmithKline plc.; H. Lundbeck A/S; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; Pfizer Inc.; Piramal Imaging; and UCB.
