Harmonisation of large-scale, heterogeneous individual participant adverse event data from randomised trials of statin therapy.

Pubmed ID: 35815805

Pubmed Central ID: PMC7613840

Journal: Clinical trials (London, England)

Publication Date: Dec. 1, 2022

Affiliation: National Health and Medical Research Council, Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia.

MeSH Terms: Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Randomized Controlled Trials as Topic

Grants: MC_UU_00017/4, CH/1996001/9454, MC_UU_00017/3, 17/140/02

Authors: Cholesterol Treatment Trialists' Collaboration

Cite As: Cholesterol Treatment Trialists' Collaboration. Harmonisation of large-scale, heterogeneous individual participant adverse event data from randomised trials of statin therapy. Clin Trials 2022 Dec;19(6):593-604. Epub 2022 Jul 9.

Studies:

Abstract

BACKGROUND: Meta-analyses of individual-level data from randomised trials are often required to detect clinically worthwhile effects. The Cholesterol Treatment Trialists' Collaboration, which includes data from numerous large long-term statin trials, is conducting a review of the effects of statin therapy on all adverse events collected in those trials. This article describes the approaches used and challenges faced to systematically capture and categorise the data. METHODS: Protocols, statistical analysis plans, case report forms, clinical study reports and datasets were obtained, reviewed and checked. Relevant baseline and follow-up data from each trial was then reorganised into standardised formats based upon the Clinical Data Interchange Standards Consortium Study Data Tabulation Model. Adverse event data were organised and coded (automatically or, where necessary, manually) according to a common medical dictionary based upon the Medical Dictionary for Regulatory Activities. RESULTS: Data from 23 double-blind statin trials and 5 open-label statin trials were provided, either through direct data transfer or through online access platforms. Together, these trials provided 845 datasets containing over 38 million records relating to 30,495 study variables and 181,973 randomised participants. Of the 46 Clinical Data Interchange Standards Consortium Study Data Tabulation Model domains that could potentially have been used to organise the data, the 13 most relevant to the project were identified and utilised, including 6 domains related to post-randomisation adverse events. Nearly 1.2 million adverse events were extracted and mapped to over 45,000 unique adverse event terms. Of these adverse events, 99% were coded to a Medical Dictionary for Regulatory Activities 'lower level term', with the remainder coded to a 'higher level term' or, very rarely, only a 'higher level group term'. CONCLUSION: In this meta-analysis of adverse event data from the large randomised trials of statins, approaches based on common standards for data organisation and classification have provided a resource capable of allowing reliable and rapid evaluation of any previously unknown benefits or hazards of statin therapy.