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Population characteristics as important contextual factors in rheumatological trials: an exploratory meta-epidemiological study from an OMERACT Working Group. | LitMetric
Musculoskeletal Statistics Unit, The Parker Institute, Bispebjerg and Frederiksberg Hospital, University of Copenhagen, Copenhagen, Denmark.
Published: October 2020
AI Article Synopsis
Article Abstract
Objectives: To explore whether trial population characteristics modify treatment responses across various interventions, comparators and rheumatic conditions.
Methods: In this meta-epidemiological study, we included trials from systematic reviews available from the Cochrane Musculoskeletal Group published up to 23 April 2019 in Cochrane Library with meta-analyses of five or more randomised controlled trials (RCTs) published from year 2000. From trial reports, we extracted data on 20 population characteristics. For characteristics with sufficient data (ie, available for ≥2/3 of the trials), we performed multilevel meta-epidemiological analyses.
Results: We identified 19 eligible systematic reviews contributing 187 RCTs (212 comparisons). Only age and sex were explicitly reported in ≥2/3 of the trials. Using information about the country of the trials led to sufficient data for five further characteristics, that is, 7 out of 20 (35%) protocolised characteristics were analysed. The meta-regressions showed effect modification by economic status, place of residence, and, nearly, from healthcare system (explaining 4.8%, 0.9% and 1.5% of the between-trial variation, respectively). No effect modification was demonstrated from age, sex, patient education/health literacy or predominant religion.
Conclusions: This study demonstrates the scarce reporting of most population characteristics, hampering investigation of their impact with meta-research. Our sparse results suggest that place of residence (ie, continent of the trial), economic status (based on World Bank classifications) and healthcare system (based on WHO index for health system performance) may be important in explaining the variation in treatment response across trials. There is an urgent need for consistent reporting of important population characteristics in trials.
