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Generalized pairwise comparisons of prioritized outcomes are a powerful and patient-centric analysis of multi-domain scores
BACKGROUND: Generalized pairwise comparisons (GPC) can be used to assess the net benefit of new treatments for rare diseases. We show the potential of GPC through simulations based on data from a natural history study in mucopolysaccharidosis type IIIA (MPS IIIA). METHODS: Using data from a historic...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10571482/ https://www.ncbi.nlm.nih.gov/pubmed/37828533 http://dx.doi.org/10.1186/s13023-023-02943-8 |
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author | Deltuvaite-Thomas, Vaiva De Backer, Mickaël Parker, Samantha Deneux, Marie Polgreen, Lynda E. O’Neill, Cara Salvaggio, Samuel Buyse, Marc |
author_facet | Deltuvaite-Thomas, Vaiva De Backer, Mickaël Parker, Samantha Deneux, Marie Polgreen, Lynda E. O’Neill, Cara Salvaggio, Samuel Buyse, Marc |
author_sort | Deltuvaite-Thomas, Vaiva |
collection | PubMed |
description | BACKGROUND: Generalized pairwise comparisons (GPC) can be used to assess the net benefit of new treatments for rare diseases. We show the potential of GPC through simulations based on data from a natural history study in mucopolysaccharidosis type IIIA (MPS IIIA). METHODS: Using data from a historical series of untreated children with MPS IIIA aged 2 to 9 years at the time of enrolment and followed for 2 years, we performed simulations to assess the operating characteristics of GPC to detect potential (simulated) treatment effects on a multi-domain symptom assessment. Two approaches were used for GPC: one in which the various domains were prioritized, the other with all domains weighted equally. The net benefit was used as a measure of treatment effect. We used increasing thresholds of clinical relevance to reflect the magnitude of the desired treatment effects, relative to the standard deviation of the measurements in each domain. RESULTS: GPC were shown to have adequate statistical power (80% or more), even with small sample sizes, to detect treatment effects considered to be clinically worthwhile on a symptom assessment covering five domains (expressive language, daily living skills, and gross-motor, sleep and pain). The prioritized approach generally led to higher power as compared with the non-prioritized approach. CONCLUSIONS: GPC of prioritized outcomes is a statistically powerful as well as a patient-centric approach for the analysis of multi-domain scores in MPS IIIA and could be applied to other heterogeneous rare diseases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13023-023-02943-8. |
format | Online Article Text |
id | pubmed-10571482 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-105714822023-10-14 Generalized pairwise comparisons of prioritized outcomes are a powerful and patient-centric analysis of multi-domain scores Deltuvaite-Thomas, Vaiva De Backer, Mickaël Parker, Samantha Deneux, Marie Polgreen, Lynda E. O’Neill, Cara Salvaggio, Samuel Buyse, Marc Orphanet J Rare Dis Research BACKGROUND: Generalized pairwise comparisons (GPC) can be used to assess the net benefit of new treatments for rare diseases. We show the potential of GPC through simulations based on data from a natural history study in mucopolysaccharidosis type IIIA (MPS IIIA). METHODS: Using data from a historical series of untreated children with MPS IIIA aged 2 to 9 years at the time of enrolment and followed for 2 years, we performed simulations to assess the operating characteristics of GPC to detect potential (simulated) treatment effects on a multi-domain symptom assessment. Two approaches were used for GPC: one in which the various domains were prioritized, the other with all domains weighted equally. The net benefit was used as a measure of treatment effect. We used increasing thresholds of clinical relevance to reflect the magnitude of the desired treatment effects, relative to the standard deviation of the measurements in each domain. RESULTS: GPC were shown to have adequate statistical power (80% or more), even with small sample sizes, to detect treatment effects considered to be clinically worthwhile on a symptom assessment covering five domains (expressive language, daily living skills, and gross-motor, sleep and pain). The prioritized approach generally led to higher power as compared with the non-prioritized approach. CONCLUSIONS: GPC of prioritized outcomes is a statistically powerful as well as a patient-centric approach for the analysis of multi-domain scores in MPS IIIA and could be applied to other heterogeneous rare diseases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13023-023-02943-8. BioMed Central 2023-10-12 /pmc/articles/PMC10571482/ /pubmed/37828533 http://dx.doi.org/10.1186/s13023-023-02943-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 Deltuvaite-Thomas, Vaiva De Backer, Mickaël Parker, Samantha Deneux, Marie Polgreen, Lynda E. O’Neill, Cara Salvaggio, Samuel Buyse, Marc Generalized pairwise comparisons of prioritized outcomes are a powerful and patient-centric analysis of multi-domain scores |
title | Generalized pairwise comparisons of prioritized outcomes are a powerful and patient-centric analysis of multi-domain scores |
title_full | Generalized pairwise comparisons of prioritized outcomes are a powerful and patient-centric analysis of multi-domain scores |
title_fullStr | Generalized pairwise comparisons of prioritized outcomes are a powerful and patient-centric analysis of multi-domain scores |
title_full_unstemmed | Generalized pairwise comparisons of prioritized outcomes are a powerful and patient-centric analysis of multi-domain scores |
title_short | Generalized pairwise comparisons of prioritized outcomes are a powerful and patient-centric analysis of multi-domain scores |
title_sort | generalized pairwise comparisons of prioritized outcomes are a powerful and patient-centric analysis of multi-domain scores |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10571482/ https://www.ncbi.nlm.nih.gov/pubmed/37828533 http://dx.doi.org/10.1186/s13023-023-02943-8 |
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