Abstract
This manuscript aims to present the first item response theory (IRT) model within a pharmacometric framework to characterize the longitudinal changes of Aberrant Behavior Checklist (ABC) data in children with autism. Data were obtained from 120 patients, which included 20,880 observations of the 58 items for up to three months. Observed scores for each ABC item were modeled as a function of the subject's disability. Longitudinal IRT models with five latent disability variables based on ABC subscales were used to describe the irritability, lethargy, stereotypic behavior, hyperactivity, and inappropriate speech over time. The IRT pharmacometric models could accurately describe the longitudinal changes of the patient's disability while estimating different time-course of disability for the subscales. For all subscales, model-estimated disability was reduced following initiation of therapy, most markedly for hyperactivity. The developed framework provides a description of ABC longitudinal data that can be a suitable alternative to traditional ABC data collected in autism clinical trials. IRT is a powerful tool with the ability to capture the heterogeneous nature of ABC, which results in more accurate analysis in comparison to traditional approaches.
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This study was supported by Grant No. 97-01-81-17380 from Shiraz University of Medical Sciences Research Council and the Swedish Research Council Grant 2018-03317.
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Haem, E., Doostfatemeh, M., Firouzabadi, N. et al. A longitudinal item response model for Aberrant Behavior Checklist (ABC) data from children with autism. J Pharmacokinet Pharmacodyn 47, 241–253 (2020). https://doi.org/10.1007/s10928-020-09686-0
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DOI: https://doi.org/10.1007/s10928-020-09686-0