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@ARTICLE{Hamdan:282315,
      author       = {Hamdan, Alzahra and Traschütz, Andreas and Beichert, Lukas
                      and Chen, Xiaomei and Gagnon, Cynthia and van de Warrenburg,
                      Bart P. and Santorelli, Filippo M. and Başak, Nazlı and
                      Coarelli, Giulia and Horvath, Rita and Klebe, Stephan and
                      Schüle, Rebecca and Hooker, Andrew C. and Synofzik, Matthis
                      and Karlsson, Mats O.},
      title        = {{I}ntegrated {M}odeling of {D}igital‐{M}otor and
                      {C}linician‐{R}eported {O}utcomes {U}sing {I}tem
                      {R}esponse {T}heory: {T}owards {P}owerful {T}rials for
                      {R}are {N}eurological {D}iseases},
      journal      = {CPT: pharmacometrics $\&$ systems pharmacology},
      volume       = {14},
      number       = {11},
      issn         = {2163-8306},
      address      = {London},
      publisher    = {Nature Publ. Group},
      reportid     = {DZNE-2025-01285},
      pages        = {1857 - 1868},
      year         = {2025},
      abstract     = {Robust and highly sensitive outcomes are crucial for small
                      trials in rare diseases. Combining different outcome types
                      might improve sensitivity to identify disease severity and
                      progression, yet innovative methodologies are scarce. Here
                      we develop an Item Response Theory framework that allows
                      integrated modeling of both continuous and categorical
                      outcomes (ccIRT). With degenerative ataxias, a group of rare
                      neurological coordination diseases, as a showcase, we
                      developed a ccIRT model integrating two ataxia outcome
                      types: a clinician-reported outcome (Scale for the
                      Assessment and Rating of Ataxia; SARA; categorical data) and
                      digital-motor outcomes for gait and limb coordination
                      (continuous data). The ccIRT model leveraged data from 331
                      assessments from a natural history study for spastic
                      ataxias. The model describes SARA items and digital-motor
                      outcomes data as functions of a common underlying ataxia
                      severity construct, evaluating 9 gait and 17 limb
                      coordination digital-motor measures for their ability to add
                      to SARA in estimating individual ataxia severity levels.
                      Based on our proposed workflow for assessing digital-motor
                      outcomes in ccIRT models, the final model selected three
                      digital gait and three limb coordination measures, reducing
                      average uncertainty in ataxia severity estimates by $49\%$
                      $(10\%$ SD) compared to the SARA-only IRT model. Trial
                      simulations showed a $49\%$ and $61\%$ reduction in sample
                      sizes needed to detect disease-modifying effects in two
                      genotypes. Overall, our ccIRT framework for combining
                      multiple outcome domains, even of different variable types,
                      facilitates a more precise estimation of disease severity
                      and a higher power, which is particularly relevant for rare
                      diseases with inherently small and short trials. Trial
                      Registration: ClinicalTrials.gov: NCT04297891.},
      keywords     = {Item Response Theory (Other) / clinical outcome assessments
                      (Other) / digital‐motor outcomes (Other) / genetic ataxias
                      (Other) / rare neurological diseases (Other)},
      cin          = {AG Gasser},
      ddc          = {610},
      cid          = {I:(DE-2719)1210000},
      pnm          = {353 - Clinical and Health Care Research (POF4-353)},
      pid          = {G:(DE-HGF)POF4-353},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.1002/psp4.70081},
      url          = {https://pub.dzne.de/record/282315},
}