Analysis of responder-based endpoints: improving power through utilising continuous components.
Augmented binary method
Composite endpoint
Efficiency
Responder analysis
Statistical analysis
Journal
Trials
ISSN: 1745-6215
Titre abrégé: Trials
Pays: England
ID NLM: 101263253
Informations de publication
Date de publication:
25 May 2020
25 May 2020
Historique:
received:
24
06
2019
accepted:
27
04
2020
entrez:
27
5
2020
pubmed:
27
5
2020
medline:
30
1
2021
Statut:
epublish
Résumé
Clinical trials and other studies commonly assess the effectiveness of an intervention through the use of responder-based endpoints. These classify patients based on whether they meet a number of criteria which often involve continuous variables categorised as being above or below a threshold. The proportion of patients who are responders is estimated and, where relevant, compared between groups. An alternative method called the augmented binary method keeps the definition of the endpoint the same but utilises information contained within the continuous component to increase the power considerably (equivalent to increasing the sample size by > 30%). In this article we summarise the method and investigate the variety of clinical conditions that use endpoints to which it could be applied. We reviewed a database of core outcome sets (COSs) that covered physiological and mortality trial endpoints recommended for collection in clinical trials of different disorders. We identified responder-based endpoints where the augmented binary method would be useful for increasing power. Out of the 287 COSs reviewed, we identified 67 new clinical areas where endpoints were used that would be more efficiently analysed using the augmented binary method. Clinical areas that had particularly high numbers were rheumatology (11 clinical disorders identified), non-solid tumour oncology (10 identified), neurology (9 identified) and cardiovascular (8 identified). The augmented binary method can potentially provide large benefits in a vast array of clinical areas. Further methodological development is needed to account for some types of endpoints.
Sections du résumé
BACKGROUND
BACKGROUND
Clinical trials and other studies commonly assess the effectiveness of an intervention through the use of responder-based endpoints. These classify patients based on whether they meet a number of criteria which often involve continuous variables categorised as being above or below a threshold. The proportion of patients who are responders is estimated and, where relevant, compared between groups. An alternative method called the augmented binary method keeps the definition of the endpoint the same but utilises information contained within the continuous component to increase the power considerably (equivalent to increasing the sample size by > 30%). In this article we summarise the method and investigate the variety of clinical conditions that use endpoints to which it could be applied.
METHODS
METHODS
We reviewed a database of core outcome sets (COSs) that covered physiological and mortality trial endpoints recommended for collection in clinical trials of different disorders. We identified responder-based endpoints where the augmented binary method would be useful for increasing power.
RESULTS
RESULTS
Out of the 287 COSs reviewed, we identified 67 new clinical areas where endpoints were used that would be more efficiently analysed using the augmented binary method. Clinical areas that had particularly high numbers were rheumatology (11 clinical disorders identified), non-solid tumour oncology (10 identified), neurology (9 identified) and cardiovascular (8 identified).
CONCLUSIONS
CONCLUSIONS
The augmented binary method can potentially provide large benefits in a vast array of clinical areas. Further methodological development is needed to account for some types of endpoints.
Identifiants
pubmed: 32450909
doi: 10.1186/s13063-020-04353-8
pii: 10.1186/s13063-020-04353-8
pmc: PMC7249409
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
427Subventions
Organisme : Medical Research Council
ID : MC_UU_00002/6
Pays : United Kingdom
Organisme : Cancer Research UK
ID : C48553/A1811
Pays : United Kingdom
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