Dataset Information

Description of subgroup reporting in clinical trials of chronic diseases: a meta-epidemiological study.

ABSTRACT:

Introduction

In trials, subgroup analyses are used to examine whether treatment effects differ by important patient characteristics. However, which subgroups are most commonly reported has not been comprehensively described.

Design and settings

Using a set of trials identified from the US clinical trials register (ClinicalTrials.gov), we describe every reported subgroup for a range of conditions and drug classes.

Methods

We obtained trial characteristics from ClinicalTrials.gov via the Aggregate Analysis of ClinicalTrials.gov database. We subsequently obtained all corresponding PubMed-indexed papers and screened these for subgroup reporting. Tables and text for reported subgroups were extracted and standardised using Medical Subject Headings and WHO Anatomical Therapeutic Chemical codes. Via logistic and Poisson regression models we identified independent predictors of result reporting (any vs none) and subgroup reporting (any vs none and counts). We then summarised subgroup reporting by index condition and presented all subgroups for all trials via a web-based interactive heatmap (https://ihwph-hehta.shinyapps.io/subgroup_reporting_app/).

Results

Among 2235 eligible trials, 23% (524 trials) reported subgroups. Follow-up time (OR, 95%CI: 1.13, 1.04-1.24), enrolment (per 10-fold increment, 3.48, 2.25-5.47), trial starting year (1.07, 1.03-1.11) and specific index conditions (eg, hypercholesterolaemia, hypertension, taking asthma as the reference, OR ranged from 0.15 to 10.44), predicted reporting, sponsoring source and number of arms did not. Results were similar on modelling any result reporting (except number of arms, 1.42, 1.15-1.74) and the total number of subgroups. Age (51%), gender (45%), racial group (28%) were the most frequently reported subgroups. Characteristics related to the index condition (severity/duration/types etc) were frequently reported (eg, 69% of myocardial infarction trials reported on its severity/duration/types). However, reporting on comorbidity/frailty (five trials) and mental health (four trials) was rare.

Conclusion

Other than age, sex, race ethnicity or geographic location and characteristics related to the index condition, information on variation in treatment effects is sparse.

Prospero registration number

CRD42018048202.

SUBMITTER: Wei L

PROVIDER: S-EPMC11328666 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Description of subgroup reporting in clinical trials of chronic diseases: a meta-epidemiological study.

Wei Lili L Butterly Elaine E Rodríguez Pérez Jesús J Chowdhury Avirup A Shemilt Richard R Hanlon Peter P McAllister David D

BMJ open 20240621 6

<h4>Introduction</h4>In trials, subgroup analyses are used to examine whether treatment effects differ by important patient characteristics. However, which subgroups are most commonly reported has not been comprehensively described.<h4>Design and settings</h4>Using a set of trials identified from the US clinical trials register (ClinicalTrials.gov), we describe every reported subgroup for a range of conditions and drug classes.<h4>Methods</h4>We obtained trial characteristics from ClinicalTrials ...[more]

PMID: 38908852

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Dataset Information

Description of subgroup reporting in clinical trials of chronic diseases: a meta-epidemiological study.

Introduction

Design and settings

Methods

Results

Conclusion

Prospero registration number

Publications

Description of subgroup reporting in clinical trials of chronic diseases: a meta-epidemiological study.

Similar Datasets

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