Search

Aims Pre-registration of study protocols in accessible databases is required for publication of study results in high-impact medical journals. Nonetheless, data on characteristics of clinical trials registered in these databases and their outcome, in terms of result reporting and publication are limited. Methods and results We searched for interventional, late-phase cardiovascular disease (CVD) studies in adults registered in Clinicaltrials.gov. first posted after 1 January 2013 and completed up to 31 December 2018. Data on study design, result reporting, and publication were collected, and potential associations with a pre-defined set of explanatory factors were examined. In total, 250 CVD trials were included in the analysis. Of these, 193 (77.2%) were randomized studies, 99 (39.6%) open label designs, and 126 (50.4%) had industry as main sponsor. One hundred and seventy-nine trials (71.6%) evaluated the effect of drugs and 27 (10.8%) evaluated devices. The most common primary outcomes were non-clinical endpoints (76.0%), with only 17% of studies evaluating clinical endpoints. Industry-funded trials focused on patent-protected drugs and devices more often than non-industry-funded trials (72.0% vs. 30.6%, P Conclusion Among late-stage cardiovascular trials only one-fourth had results posted on clinicaltrials.gov and

Introduction Preregistration of study protocols in publicly accessible databases is required for publication of study results in high-impact medical journals. Nonetheless, data on the characteristics of clinical trials registered in these databases and their outcome, in terms of result reporting and publication are limited. Methods The purpose of this study was to perform a comprehensive analysis of the characteristics of late-stage, cardiovascular disease (CVD) trials registered in Clinicaltrials.gov. We searched for interventional, late-phase (annotated as phase III) CVD studies in adults first posted after 1/1/2013 and completed up to 31/12/2018. Data on study design, result reporting, result spinning and publication were collected, and potential associations with a pre-defined set of explanatory factors were examined. Results The search yielded 352 studies. One hundred were excluded from further analysis because they were misclassified as CVD studies, while 2 were excluded as duplicate entries. In total, 250 CVD trials were included in the analysis. The most commonly studied fields were hypertension, coronary artery disease and heart failure. Of these, 193 (77.2%) were randomized studies, 99 (39.6%) open label designs, and 126 (50.4%) had industry as main sponsor. 179 trials (71.6%) evaluated the effect of drugs and 27 (10.8%) evaluated devices. Industry-funded trials focused on patent-protected drugs and devices more often than non-industry-funded trials (72.0% vs. 30.6%, P Conclusions Among late-stage cardiovascular trials only 1/4 had their results posted on clinicaltrials.gov and less than half had results published. Industry sponsors were more likely to invest in research on patent-protected drugs and devices than were non-industry sponsors. Having industry as a sponsor was independently associated with increased likelihood of results posting, but decreased likelihood of results publication. Results reporting was significantly associated with lower risk of results spinning. Funding Acknowledgement Type of funding source: None

Background Increasingly, health technology assessment (HTA) agencies must decide whether new medicines should be used routinely in the absence of randomised controlled trial (RCT) data, relying solely on non-randomised studies (NRS), which are at high risk of bias due to confounding. Against the background of increased availability and improved methods to analyse non-randomised data (e.g., propensity score methods and instrumental variables), it is important for decision-makers to have guidance on the analysis and interpretation of NRS to inform health economic evaluation. We therefore aimed to systematically and empirically assess the performance of NRS using different analytical methods as compared to RCTs and develop recommendations on the basis of our findings. Methods We conducted a large-scale meta-epidemiological review to obtain estimates of the discrepancy in treatment effects in matched RCTs and NRS of pharmacologic interventions from published meta-analyses indexed in MEDLINE and the Cochrane Database of Systematic Reviews. We also consulted with HTA bodies, regulators and academics from five European countries to learn from their experience with using non-randomised evidence. Results We compiled the largest dataset of clinical topics with matching RCTs and NRS using various analytical methods to date, covering >100 unique clinical questions. Incorporating information on direction of effect and effect size from >700 unique studies, the dataset can be used to evaluate discrepancies in treatment effects between study designs across a wide range of therapeutic areas. Conclusions An empirically based understanding of the risk of bias in NRS is required in order to promote the adequate use of non-randomised evidence as input for health economic decision-making.