Analysis of responder-based endpoints: improving power through utilising continuous components.


Journal

Trials
ISSN: 1745-6215
Titre abrégé: Trials
Pays: England
ID NLM: 101263253

Informations de publication

Date de publication:
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

427

Subventions

Organisme : Medical Research Council
ID : MC_UU_00002/6
Pays : United Kingdom
Organisme : Cancer Research UK
ID : C48553/A1811
Pays : United Kingdom

Références

BMJ. 2006 May 6;332(7549):1080
pubmed: 16675816
Stat Med. 2013 Nov 20;32(26):4639-50
pubmed: 23776143
PLoS Med. 2017 Nov 16;14(11):e1002447
pubmed: 29145404
Stat Med. 2015 May 20;34(11):1904-11
pubmed: 25630496
Stat Methods Med Res. 2002 Aug;11(4):297-302
pubmed: 12197297
Arthritis Rheumatol. 2014 Dec;66(12):3255-64
pubmed: 25223724
PLoS One. 2014 Jun 16;9(6):e99111
pubmed: 24932522
Stat Med. 1995 Feb 15;14(3):247-55
pubmed: 7724910
J Clin Epidemiol. 1991;44(3):241-8
pubmed: 1999683
PLoS One. 2018 Dec 28;13(12):e0209869
pubmed: 30592741
Am J Obstet Gynecol. 2007 Feb;196(2):119.e1-6
pubmed: 17306647
Orphanet J Rare Dis. 2018 May 22;13(1):81
pubmed: 29788976
Stat Med. 2017 Dec 20;36(29):4616-4626
pubmed: 28850689
Res Nurs Health. 2005 Dec;28(6):496-503
pubmed: 16287057
Psychol Methods. 2009 Dec;14(4):349-66
pubmed: 19968397
Rheumatology (Oxford). 2016 Oct;55(10):1796-802
pubmed: 27338084
J Clin Epidemiol. 2018 Apr;96:84-92
pubmed: 29288712

Auteurs

James Wason (J)

Population Health Sciences Institute, Newcastle University, Baddiley-Clark Building, Newcastle upon Tyne, NE2 4BN, UK. james.wason@newcastle.ac.uk.
MRC Biostatistics Unit, University of Cambridge, Institute of Public Health, Robinson Way, Cambridge, CB2 0SR, UK. james.wason@newcastle.ac.uk.

Martina McMenamin (M)

MRC Biostatistics Unit, University of Cambridge, Institute of Public Health, Robinson Way, Cambridge, CB2 0SR, UK.

Susanna Dodd (S)

Department of Biostatistics, University of Liverpool (a member of Liverpool Health Partners), 1-5 Brownlow Street, Liverpool, L69 3GL, UK.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH