Reporting and interpretation of subgroup analyses in heart failure randomized controlled trials.

Autor: Khan, Muhammad Shahzeb, Khan, Muhammad Arbaz Arshad, Irfan, Simra, Siddiqi, Tariq Jamal, Greene, Stephen J., Anker, Stefan D., Sreenivasan, Jayakumar, Friede, Tim, Tahhan, Ayman Samman, Vaduganathan, Muthiah, Fonarow, Gregg C., Butler, Javed
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Zdroj: ESC Heart Failure; Feb2021, Vol. 8 Issue 1, p26-36, 11p
Abstrakt: Aims: This study aimed to investigate the reporting of subgroup analyses in heart failure (HF) randomized controlled trials (RCTs) and to determine the strength and credibility of subgroup claims. Methods and results: All primary HF RCTs published in nine high‐impact journals from 1 January 2008 to 31 December 2017 were included. Multivariable regression analysis was used to identify factors that may favour the reporting of results in specific subgroups. Strength of the subgroup effect claimed was classified into (i) strong, (ii) likely, or (iii) suggestive. Credibility of subgroup claim was scored using a pre‐specified 10 pointer criteria. Of the 261 HF RCTs studied, 107 (41%) reported subgroup analyses. Twenty‐five (23%) RCTs claimed a subgroup effect for the primary outcome of which six (24%) made a strong claim, eight (32%) claimed a likely effect, and 11 (44%) suggested a possible subgroup effect. Seven of the 25 RCTs did not employ interaction testing for subgroup claims of the primary outcome. Three out of 10 pre‐specified credibility criteria were satisfied by half of the trials. Fourteen trials justified the choice of subgroups, and 10 explicitly stated they were underpowered to detect differences within subgroups. Source of funding did not influence the frequency of reporting subgroup analyses (OR 0.53, 95% CI 0.78–3.62, P = 0.52). Conclusions: Appropriate credibility criteria were rarely met even by HF RCTs that held strong subgroup claims. Subgroup analyses should be pre‐specified, be adequately powered, present interaction terms, and be replicated in independent data before being integrated into clinical decision making. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
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