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Determining and reporting minimal important change for patient-reported outcome instruments in pulmonary medicine

Jeff Swigris, Brandon Foster, Nathan Johnson
European Respiratory Journal 2022 60: 2200717; DOI: 10.1183/13993003.00717-2022
Jeff Swigris
1National Jewish Health, Denver, CO, USA
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Brandon Foster
2Endpoint Outcomes, Boston, MA, USA
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Nathan Johnson
2Endpoint Outcomes, Boston, MA, USA
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Abstract

Utilising consistent terminology and a rigorous approach to determining and reporting minimal important change to the patient (MICP) would elevate quality of measurement science in our field and bolster confidence in using PROs as first-tier endpoints https://bit.ly/3OOGNhc

Footnotes

  • Conflict of interest: J. Swigris is the developer of several patient-reported outcome measures. Along with National Jewish Health (who owns the copyrights for them), J. Swigris sometimes receives royalties when they are used in sponsored research. B. Foster and N. Johnson have received consulting fees for work done in developing and validating patient-reported outcome measures.

  • Received April 20, 2022.
  • Accepted July 25, 2022.
  • Copyright ©The authors 2022. For reproduction rights and permissions contact permissions{at}ersnet.org
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Vol 60 Issue 4 Table of Contents
European Respiratory Journal: 60 (4)
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Determining and reporting minimal important change for patient-reported outcome instruments in pulmonary medicine
Jeff Swigris, Brandon Foster, Nathan Johnson
European Respiratory Journal Oct 2022, 60 (4) 2200717; DOI: 10.1183/13993003.00717-2022

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Determining and reporting minimal important change for patient-reported outcome instruments in pulmonary medicine
Jeff Swigris, Brandon Foster, Nathan Johnson
European Respiratory Journal Oct 2022, 60 (4) 2200717; DOI: 10.1183/13993003.00717-2022
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  • Article
    • Abstract
    • What is the minimal clinically important difference?
    • The concept of anchors
    • The mean change method
    • Other methods for determining the MCID: ROC curves and predictive modelling
    • Triangulating to generate a weighted MCID
    • Distribution-based approaches to MCID estimation
    • Incorporating statistical significance
    • Conclusion
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  • 3D (bio)printing of lungs
  • Prognostic models for respiratory diseases
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