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Effect of age, sex, and morbidity count on trial attrition: meta-analysis of individual participant level data from phase 3/4 industry funded clinical trials

OBJECTIVES: To estimate the association between individual participant characteristics and attrition from randomised controlled trials. DESIGN: Meta-analysis of individual participant level data (IPD). DATA SOURCES: Clinical trial repositories (Clinical Study Data Request and Yale University Open Da...

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Autores principales: Lees, Jennifer S, Hanlon, Peter, Butterly, Elaine W, Wild, Sarah H, Mair, Frances S, Taylor, Rod S, Guthrie, Bruce, Gillies, Katie, Dias, Sofia, Welton, Nicky J, McAllister, David A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9978693/
https://www.ncbi.nlm.nih.gov/pubmed/36936559
http://dx.doi.org/10.1136/bmjmed-2022-000217
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author Lees, Jennifer S
Hanlon, Peter
Butterly, Elaine W
Wild, Sarah H
Mair, Frances S
Taylor, Rod S
Guthrie, Bruce
Gillies, Katie
Dias, Sofia
Welton, Nicky J
McAllister, David A
author_facet Lees, Jennifer S
Hanlon, Peter
Butterly, Elaine W
Wild, Sarah H
Mair, Frances S
Taylor, Rod S
Guthrie, Bruce
Gillies, Katie
Dias, Sofia
Welton, Nicky J
McAllister, David A
author_sort Lees, Jennifer S
collection PubMed
description OBJECTIVES: To estimate the association between individual participant characteristics and attrition from randomised controlled trials. DESIGN: Meta-analysis of individual participant level data (IPD). DATA SOURCES: Clinical trial repositories (Clinical Study Data Request and Yale University Open Data Access). ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Eligible phase 3 or 4 trials identified according to prespecified criteria (PROSPERO CRD42018048202). MAIN OUTCOME MEASURES: Association between comorbidity count (identified using medical history or concomitant drug treatment data) and trial attrition (failure for any reason to complete the final trial visit), estimated in logistic regression models and adjusted for age and sex. Estimates were meta-analysed in bayesian linear models, with partial pooling across index conditions and drug classes. RESULTS: In 92 trials across 20 index conditions and 17 drug classes, the mean comorbidity count ranged from 0.3 to 2.7. Neither age nor sex was clearly associated with attrition (odds ratio 1.04, 95% credible interval 0.98 to 1.11; and 0.99, 0.93 to 1.05, respectively). However, comorbidity count was associated with trial attrition (odds ratio per additional comorbidity 1.11, 95% credible interval 1.07 to 1.14). No evidence of non-linearity (assessed via a second order polynomial) was seen in the association between comorbidity count and trial attrition, with minimal variation across drug classes and index conditions. At a trial level, an increase in participant comorbidity count has a minor impact on attrition: for a notional trial with high level of attrition in individuals without comorbidity, doubling the mean comorbidity count from 1 to 2 translates to an increase in trial attrition from 29% to 31%. CONCLUSIONS: Increased comorbidity count, irrespective of age and sex, is associated with a modest increased odds of participant attrition. The benefit of increased generalisability of including participants with multimorbidity seems likely to outweigh the disadvantages of increased attrition.
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spelling pubmed-99786932023-03-16 Effect of age, sex, and morbidity count on trial attrition: meta-analysis of individual participant level data from phase 3/4 industry funded clinical trials Lees, Jennifer S Hanlon, Peter Butterly, Elaine W Wild, Sarah H Mair, Frances S Taylor, Rod S Guthrie, Bruce Gillies, Katie Dias, Sofia Welton, Nicky J McAllister, David A BMJ Med Research OBJECTIVES: To estimate the association between individual participant characteristics and attrition from randomised controlled trials. DESIGN: Meta-analysis of individual participant level data (IPD). DATA SOURCES: Clinical trial repositories (Clinical Study Data Request and Yale University Open Data Access). ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Eligible phase 3 or 4 trials identified according to prespecified criteria (PROSPERO CRD42018048202). MAIN OUTCOME MEASURES: Association between comorbidity count (identified using medical history or concomitant drug treatment data) and trial attrition (failure for any reason to complete the final trial visit), estimated in logistic regression models and adjusted for age and sex. Estimates were meta-analysed in bayesian linear models, with partial pooling across index conditions and drug classes. RESULTS: In 92 trials across 20 index conditions and 17 drug classes, the mean comorbidity count ranged from 0.3 to 2.7. Neither age nor sex was clearly associated with attrition (odds ratio 1.04, 95% credible interval 0.98 to 1.11; and 0.99, 0.93 to 1.05, respectively). However, comorbidity count was associated with trial attrition (odds ratio per additional comorbidity 1.11, 95% credible interval 1.07 to 1.14). No evidence of non-linearity (assessed via a second order polynomial) was seen in the association between comorbidity count and trial attrition, with minimal variation across drug classes and index conditions. At a trial level, an increase in participant comorbidity count has a minor impact on attrition: for a notional trial with high level of attrition in individuals without comorbidity, doubling the mean comorbidity count from 1 to 2 translates to an increase in trial attrition from 29% to 31%. CONCLUSIONS: Increased comorbidity count, irrespective of age and sex, is associated with a modest increased odds of participant attrition. The benefit of increased generalisability of including participants with multimorbidity seems likely to outweigh the disadvantages of increased attrition. BMJ Publishing Group 2022-09-01 /pmc/articles/PMC9978693/ /pubmed/36936559 http://dx.doi.org/10.1136/bmjmed-2022-000217 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
spellingShingle Research
Lees, Jennifer S
Hanlon, Peter
Butterly, Elaine W
Wild, Sarah H
Mair, Frances S
Taylor, Rod S
Guthrie, Bruce
Gillies, Katie
Dias, Sofia
Welton, Nicky J
McAllister, David A
Effect of age, sex, and morbidity count on trial attrition: meta-analysis of individual participant level data from phase 3/4 industry funded clinical trials
title Effect of age, sex, and morbidity count on trial attrition: meta-analysis of individual participant level data from phase 3/4 industry funded clinical trials
title_full Effect of age, sex, and morbidity count on trial attrition: meta-analysis of individual participant level data from phase 3/4 industry funded clinical trials
title_fullStr Effect of age, sex, and morbidity count on trial attrition: meta-analysis of individual participant level data from phase 3/4 industry funded clinical trials
title_full_unstemmed Effect of age, sex, and morbidity count on trial attrition: meta-analysis of individual participant level data from phase 3/4 industry funded clinical trials
title_short Effect of age, sex, and morbidity count on trial attrition: meta-analysis of individual participant level data from phase 3/4 industry funded clinical trials
title_sort effect of age, sex, and morbidity count on trial attrition: meta-analysis of individual participant level data from phase 3/4 industry funded clinical trials
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9978693/
https://www.ncbi.nlm.nih.gov/pubmed/36936559
http://dx.doi.org/10.1136/bmjmed-2022-000217
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