Literature DB >> 33002638

Prerandomization run-in periods in randomized controlled trials of chronic diseases: a methodological study.

David Collister1, Jennifer C Rodrigues2, Lawrence Mbuagbaw2, P J Devereaux3, Gordon Guyatt2, William Herrington4, Michael Walsh3.   

Abstract

OBJECTIVE: To systematically review the epidemiology of prerandomized run-in periods in randomized controlled trials (RCTs) of chronic diseases. STUDY DESIGN AND
SETTING: Meta-epidemiologic study of all RCTs from the four highest impact medical journals from 2011 to 2016. Eligible trials included parallel RCTs that evaluated pharmacologic therapies in adults with chronic diseases with a minimum follow-up of 24 weeks.
RESULTS: Of 262 eligible manuscripts, 48 (18.3%), representing 42 unique RCTs, included run-in periods. Run-in periods were most common in cardiovascular disease and diabetes trials. Of the 42 RCTs, in 22 patients received the experimental therapy, 15 placebo, 4 both (either sequentially or in combination), and one did not report the run-in period drug. The median run-in period duration was 28 days (Q1: Q3 14: 66 days). Reasons for including a run-in period included ensuring eligibility criteria were met (18, 42.9%), excluding participants with nonadherence (18, 42.9%) and intolerances to therapy (15, 35.7%), and to standardize therapy prior to randomization (8, 19.0%). The median run-in completion rate was 77.4% (Q1: Q3 62.2:87.8%).
CONCLUSIONS: Run-in periods are uncommon in RCTs of chronic drug treatments and when used, their reporting is heterogeneous. Further research to improve the design, use, and reporting of run-in periods is necessary.
Copyright © 2020 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Chronic disease; Meta-epidemiology; Pharmacologic therapies; Prerandomization; Randomized controlled trials; Run-in periods

Mesh:

Year:  2020        PMID: 33002638     DOI: 10.1016/j.jclinepi.2020.09.035

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  2 in total

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Review 2.  [Benefit assessment of digital health applications-challenges and opportunities].

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  2 in total

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