Abstract
This study aimed to illustrate how a new methodology to assess clinical trial outcome measures using a longitudinal item response theory–based model (IRM) could serve as an alternative to mixed model repeated measures (MMRM). Data from the EXACT (Exacerbation of chronic pulmonary disease tool) which is used to capture frequency, severity, and duration of exacerbations in COPD were analyzed using an IRM. The IRM included a graded response model characterizing item parameters and functions describing symptom-time course. Total scores were simulated (month 12) using uncertainty in parameter estimates. The 50th (2.5th, 97.5th) percentiles of the resulting simulated differences in average total score (drug minus placebo) represented the estimated drug effect (95%CI), which was compared with published MMRM results. Furthermore, differences in sample size, sensitivity, specificity, and type I and II errors between approaches were explored. Patients received either oral danirixin 75 mg twice daily (n = 45) or placebo (n = 48) on top of standard of care over 52 weeks. A step function best described the COPD symptoms-time course in both trial arms. The IRM improved precision of the estimated drug effect compared to MMRM, resulting in a sample size of 2.5 times larger for the MMRM analysis to achieve the IRM precision. The IRM showed a higher probability of a positive predictive value (34%) than MMRM (22%). An item model–based analysis data gave more precise estimates of drug effect than MMRM analysis for the same endpoint in this one case study.
Highlights
Confidence in clinical trial decision-making will depend on the precision of the outcome measures
This study aims to illustrate how a new methodology to assess clinical trial outcome measures using a non-linear mixed-effects model (NLME) analysis based on item-level data (IRM) could potentially replace the standard mixed model repeated measures (MMRM) analysis of total score data
A step function best described the COPD symptoms-time course in both danirixin and placebo arms, and different parameters per arm were estimated with a median relative standard error (RSE) of 0.15 (0.06–1.09) (Table S2)
Summary
Confidence in clinical trial decision-making will depend on the precision of the outcome measures. Patient-reported outcomes (PROs) are a type of clinical endpoint measure that is increasingly used in drug development to record how well a disease is managed from the patient’s point of view and to provide information supporting the patient experience for inclusion within a product licence [1]. These measurements are reported directly by the patient, without interpretation by a health professional [2]. The E-RS:COPD (Evaluating Respiratory Symptoms in COPD) consists of 11 items from this 14-item EXACT instrument, and it is intended to capture information related to respiratory symptoms
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
