Cargando…
Trends in Adaptive Design Methods in Dialysis Clinical Trials: A Systematic Review
RATIONALE & OBJECTIVE: Adaptive design methods are intended to improve the efficiency of clinical trials and are relevant to evaluating interventions in dialysis populations. We sought to determine the use of adaptive designs in dialysis clinical trials and quantify trends in their use over time...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8664746/ https://www.ncbi.nlm.nih.gov/pubmed/34939002 http://dx.doi.org/10.1016/j.xkme.2021.08.001 |
_version_ | 1784613909363163136 |
---|---|
author | Judge, Conor Murphy, Robert Reddin, Catriona Cormican, Sarah Smyth, Andrew O’Halloran, Martin O’Donnell, Martin J. |
author_facet | Judge, Conor Murphy, Robert Reddin, Catriona Cormican, Sarah Smyth, Andrew O’Halloran, Martin O’Donnell, Martin J. |
author_sort | Judge, Conor |
collection | PubMed |
description | RATIONALE & OBJECTIVE: Adaptive design methods are intended to improve the efficiency of clinical trials and are relevant to evaluating interventions in dialysis populations. We sought to determine the use of adaptive designs in dialysis clinical trials and quantify trends in their use over time. STUDY DESIGN: We completed a novel full-text systematic review that used a machine learning classifier (RobotSearch) for filtering randomized controlled trials and adhered to the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guidelines. SETTING & STUDY POPULATIONS: We searched MEDLINE (PubMed) and ClinicalTrials.gov using sensitive dialysis search terms. SELECTION CRITERIA FOR STUDIES: We included all randomized clinical trials with patients receiving dialysis or clinical trials with dialysis as a primary or secondary outcome. There was no restriction of disease type or intervention type. DATA EXTRACTION & ANALYTICAL APPROACH: We performed a detailed data extraction of trial characteristics and a completed a narrative synthesis of the data. RESULTS: 57 studies, available as 68 articles and 7 ClinicalTrials.gov summaries, were included after full-text review (initial search, 209,033 PubMed abstracts and 6,002 ClinicalTrials.gov summaries). 31 studies were conducted in a dialysis population and 26 studies included dialysis as a primary or secondary outcome. Although the absolute number of adaptive design methods is increasing over time, the relative use of adaptive design methods in dialysis trials is decreasing over time (6.12% in 2009 to 0.43% in 2019, with a mean of 1.82%). Group sequential designs were the most common type of adaptive design method used. Adaptive design methods affected the conduct of 50.9% of trials, most commonly resulting in stopping early for futility (41.2%) and early stopping for safety (23.5%). Acute kidney injury was studied in 32 trials (56.1%), kidney failure requiring dialysis was studied in 24 trials (42.1%), and chronic kidney disease was studied in 1 trial (1.75%). 27 studies (47.4%) were supported by public funding. 44 studies (77.2%) did not report their adaptive design method in the title or abstract and would not be detected by a standard systematic review. LIMITATIONS: We limited our search to 2 databases (PubMed and ClinicalTrials.gov) due to the scale of studies sourced (209,033 and 6,002 results, respectively). CONCLUSIONS: Adaptive design methods are used in dialysis trials but there has been a decline in their relative use over time. |
format | Online Article Text |
id | pubmed-8664746 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-86647462021-12-21 Trends in Adaptive Design Methods in Dialysis Clinical Trials: A Systematic Review Judge, Conor Murphy, Robert Reddin, Catriona Cormican, Sarah Smyth, Andrew O’Halloran, Martin O’Donnell, Martin J. Kidney Med Original Research RATIONALE & OBJECTIVE: Adaptive design methods are intended to improve the efficiency of clinical trials and are relevant to evaluating interventions in dialysis populations. We sought to determine the use of adaptive designs in dialysis clinical trials and quantify trends in their use over time. STUDY DESIGN: We completed a novel full-text systematic review that used a machine learning classifier (RobotSearch) for filtering randomized controlled trials and adhered to the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guidelines. SETTING & STUDY POPULATIONS: We searched MEDLINE (PubMed) and ClinicalTrials.gov using sensitive dialysis search terms. SELECTION CRITERIA FOR STUDIES: We included all randomized clinical trials with patients receiving dialysis or clinical trials with dialysis as a primary or secondary outcome. There was no restriction of disease type or intervention type. DATA EXTRACTION & ANALYTICAL APPROACH: We performed a detailed data extraction of trial characteristics and a completed a narrative synthesis of the data. RESULTS: 57 studies, available as 68 articles and 7 ClinicalTrials.gov summaries, were included after full-text review (initial search, 209,033 PubMed abstracts and 6,002 ClinicalTrials.gov summaries). 31 studies were conducted in a dialysis population and 26 studies included dialysis as a primary or secondary outcome. Although the absolute number of adaptive design methods is increasing over time, the relative use of adaptive design methods in dialysis trials is decreasing over time (6.12% in 2009 to 0.43% in 2019, with a mean of 1.82%). Group sequential designs were the most common type of adaptive design method used. Adaptive design methods affected the conduct of 50.9% of trials, most commonly resulting in stopping early for futility (41.2%) and early stopping for safety (23.5%). Acute kidney injury was studied in 32 trials (56.1%), kidney failure requiring dialysis was studied in 24 trials (42.1%), and chronic kidney disease was studied in 1 trial (1.75%). 27 studies (47.4%) were supported by public funding. 44 studies (77.2%) did not report their adaptive design method in the title or abstract and would not be detected by a standard systematic review. LIMITATIONS: We limited our search to 2 databases (PubMed and ClinicalTrials.gov) due to the scale of studies sourced (209,033 and 6,002 results, respectively). CONCLUSIONS: Adaptive design methods are used in dialysis trials but there has been a decline in their relative use over time. Elsevier 2021-08-20 /pmc/articles/PMC8664746/ /pubmed/34939002 http://dx.doi.org/10.1016/j.xkme.2021.08.001 Text en © 2021 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Original Research Judge, Conor Murphy, Robert Reddin, Catriona Cormican, Sarah Smyth, Andrew O’Halloran, Martin O’Donnell, Martin J. Trends in Adaptive Design Methods in Dialysis Clinical Trials: A Systematic Review |
title | Trends in Adaptive Design Methods in Dialysis Clinical Trials: A Systematic Review |
title_full | Trends in Adaptive Design Methods in Dialysis Clinical Trials: A Systematic Review |
title_fullStr | Trends in Adaptive Design Methods in Dialysis Clinical Trials: A Systematic Review |
title_full_unstemmed | Trends in Adaptive Design Methods in Dialysis Clinical Trials: A Systematic Review |
title_short | Trends in Adaptive Design Methods in Dialysis Clinical Trials: A Systematic Review |
title_sort | trends in adaptive design methods in dialysis clinical trials: a systematic review |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8664746/ https://www.ncbi.nlm.nih.gov/pubmed/34939002 http://dx.doi.org/10.1016/j.xkme.2021.08.001 |
work_keys_str_mv | AT judgeconor trendsinadaptivedesignmethodsindialysisclinicaltrialsasystematicreview AT murphyrobert trendsinadaptivedesignmethodsindialysisclinicaltrialsasystematicreview AT reddincatriona trendsinadaptivedesignmethodsindialysisclinicaltrialsasystematicreview AT cormicansarah trendsinadaptivedesignmethodsindialysisclinicaltrialsasystematicreview AT smythandrew trendsinadaptivedesignmethodsindialysisclinicaltrialsasystematicreview AT ohalloranmartin trendsinadaptivedesignmethodsindialysisclinicaltrialsasystematicreview AT odonnellmartinj trendsinadaptivedesignmethodsindialysisclinicaltrialsasystematicreview |