A systematic assessment of the characteristics of randomized controlled trials cited by acute coronary syndrome clinical practice guidelines

Abstract

Aims The aim of this study was to describe the methodological features of the randomised controlled trials (RCTs) cited in American and European clinical practice guidelines (CPGs) for ST elevation myocardial infarction (STEMI) and non-ST elevation acute coronary syndrome (NSTE-ACS). Methods and results Out of 2128 non-duplicated references cited in the 2013 and 2014 ACC/AHA and 2017 and 2020 ESC CPGs for STEMI and NSTE-ACS, we extracted data for 407 RCTs (19.1% of total references). The majority were multicenter studies (81.8%), evaluated pharmacological interventions (63.1%), and had a 2-arm (82.6%), superiority (90.4%) design. Most RCTs (60.2%) had an active comparator, and 46.2% were funded by industry. The median observed sample size was 1001 patients (84.2% of RCTs achieved ≥80% of the intended sample size). Most RCTs had a single primary outcome (90.9%), which was a composite in just over half (51.9%). Amongst the RCTs testing for superiority, 44.0% reported a p-value of ≥0.05 for the primary outcome and 61.9% observed a risk reduction of >15%. The observed treatment effect was lower-than-expected in 67.6% of RCTs, with 34.4% having at least a 20% lower-than-expected treatment effect. The calculated post hoc statistical power was ≥80% for 33.9% of cited RCTs. Conclusions This analysis demonstrates that RCTs cited by CPGs can still have significant methodological issues and limitations, highlighting that a better understanding of the methodological aspects of RCTs is crucial in order to formulate recommendations relevant to clinical practice.

Globalization does not lead to homogenization in randomized controlled trials: Impact on sample size estimation

“…In an era where event rates in cardiovascular trials are falling progressively, global trials are needed to obtain larger sample sizes, as well as to improve representativeness and generalizability 5 . Whilst geographic differences in patient characteristics, outcomes and treatment effect can be perceived as new challenges for the study design and interpretation of future trials, 18 an optimistic trialist might use all this new useful information to ‘personalize’ the estimation of sample size according to the regions involved. Between‐country disparities in comorbidities, background therapies, and baseline risk, as well as in health care systems and level of attainment to evidence‐based management might be used to streamline the sample size calculation.…”