Cargando…
Practical issues encountered while determining Minimal Clinically Important Difference in Patient-Reported Outcomes
BACKGROUND: Using a real dataset, we highlighted several major methodological issues raised by the estimation of the Minimal Clinically Important Difference (MCID) of a Patient-Reported Outcomes instrument. We especially considered the management of missing data and the use of more than two times of...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7251729/ https://www.ncbi.nlm.nih.gov/pubmed/32460882 http://dx.doi.org/10.1186/s12955-020-01398-w |
_version_ | 1783539015638581248 |
---|---|
author | Woaye-Hune, Pascal Hardouin, Jean-Benoit Lehur, Paul-Antoine Meurette, Guillaume Vanier, Antoine |
author_facet | Woaye-Hune, Pascal Hardouin, Jean-Benoit Lehur, Paul-Antoine Meurette, Guillaume Vanier, Antoine |
author_sort | Woaye-Hune, Pascal |
collection | PubMed |
description | BACKGROUND: Using a real dataset, we highlighted several major methodological issues raised by the estimation of the Minimal Clinically Important Difference (MCID) of a Patient-Reported Outcomes instrument. We especially considered the management of missing data and the use of more than two times of measurement. While inappropriate missing data management and inappropriate use of multiple time points can lead to loss of precision and/or bias in MCID estimation, these issues are almost never dealt with and require cautious considerations in the context of MCID estimation. METHODS: We used the LIGALONGO study (French Randomized Controlled Trial). We estimated MCID on the SF-36 General Health score by comparing many methods (distribution or anchor-based). Different techniques for imputation of missing data were performed (simple and multiple imputations). We also consider all measurement occasions by longitudinal modeling, and the dependence of the score difference on baseline. RESULTS: Three hundred ninety-three patients were studied. With distribution-based methods, a great variability in MCID was observed (from 3 to 26 points for improvement). Only 0.2 SD and 1/3 SD distribution methods gave MCID values consistent with anchor-based methods (from 4 to 7 points for improvement). The choice of missing data imputation technique clearly had an impact on MCID estimates. Simple imputation by mean score seemed to lead to out-of-range estimate, but as missing not at random mechanism can be hypothesized, even multiple imputations techniques can have led to an slight underestimation of MCID. Using 3 measurement occasions for improvement led to an increase in precision but lowered estimates. CONCLUSION: This practical example illustrates the substantial impact of some methodological issues that are usually never dealt with for MCID estimation. Simulation studies are needed to investigate those issues. TRIAL REGISTRATION: NCT01240772 (ClinicalTrials.gov) registered on November 15, 2010. |
format | Online Article Text |
id | pubmed-7251729 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-72517292020-06-04 Practical issues encountered while determining Minimal Clinically Important Difference in Patient-Reported Outcomes Woaye-Hune, Pascal Hardouin, Jean-Benoit Lehur, Paul-Antoine Meurette, Guillaume Vanier, Antoine Health Qual Life Outcomes Research BACKGROUND: Using a real dataset, we highlighted several major methodological issues raised by the estimation of the Minimal Clinically Important Difference (MCID) of a Patient-Reported Outcomes instrument. We especially considered the management of missing data and the use of more than two times of measurement. While inappropriate missing data management and inappropriate use of multiple time points can lead to loss of precision and/or bias in MCID estimation, these issues are almost never dealt with and require cautious considerations in the context of MCID estimation. METHODS: We used the LIGALONGO study (French Randomized Controlled Trial). We estimated MCID on the SF-36 General Health score by comparing many methods (distribution or anchor-based). Different techniques for imputation of missing data were performed (simple and multiple imputations). We also consider all measurement occasions by longitudinal modeling, and the dependence of the score difference on baseline. RESULTS: Three hundred ninety-three patients were studied. With distribution-based methods, a great variability in MCID was observed (from 3 to 26 points for improvement). Only 0.2 SD and 1/3 SD distribution methods gave MCID values consistent with anchor-based methods (from 4 to 7 points for improvement). The choice of missing data imputation technique clearly had an impact on MCID estimates. Simple imputation by mean score seemed to lead to out-of-range estimate, but as missing not at random mechanism can be hypothesized, even multiple imputations techniques can have led to an slight underestimation of MCID. Using 3 measurement occasions for improvement led to an increase in precision but lowered estimates. CONCLUSION: This practical example illustrates the substantial impact of some methodological issues that are usually never dealt with for MCID estimation. Simulation studies are needed to investigate those issues. TRIAL REGISTRATION: NCT01240772 (ClinicalTrials.gov) registered on November 15, 2010. BioMed Central 2020-05-27 /pmc/articles/PMC7251729/ /pubmed/32460882 http://dx.doi.org/10.1186/s12955-020-01398-w Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Woaye-Hune, Pascal Hardouin, Jean-Benoit Lehur, Paul-Antoine Meurette, Guillaume Vanier, Antoine Practical issues encountered while determining Minimal Clinically Important Difference in Patient-Reported Outcomes |
title | Practical issues encountered while determining Minimal Clinically Important Difference in Patient-Reported Outcomes |
title_full | Practical issues encountered while determining Minimal Clinically Important Difference in Patient-Reported Outcomes |
title_fullStr | Practical issues encountered while determining Minimal Clinically Important Difference in Patient-Reported Outcomes |
title_full_unstemmed | Practical issues encountered while determining Minimal Clinically Important Difference in Patient-Reported Outcomes |
title_short | Practical issues encountered while determining Minimal Clinically Important Difference in Patient-Reported Outcomes |
title_sort | practical issues encountered while determining minimal clinically important difference in patient-reported outcomes |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7251729/ https://www.ncbi.nlm.nih.gov/pubmed/32460882 http://dx.doi.org/10.1186/s12955-020-01398-w |
work_keys_str_mv | AT woayehunepascal practicalissuesencounteredwhiledeterminingminimalclinicallyimportantdifferenceinpatientreportedoutcomes AT hardouinjeanbenoit practicalissuesencounteredwhiledeterminingminimalclinicallyimportantdifferenceinpatientreportedoutcomes AT lehurpaulantoine practicalissuesencounteredwhiledeterminingminimalclinicallyimportantdifferenceinpatientreportedoutcomes AT meuretteguillaume practicalissuesencounteredwhiledeterminingminimalclinicallyimportantdifferenceinpatientreportedoutcomes AT vanierantoine practicalissuesencounteredwhiledeterminingminimalclinicallyimportantdifferenceinpatientreportedoutcomes |