Correspondence

Clinical trials should begin and end with systematic reviews of relevant evidence: 12 years and waiting

To investigate the prevalence of meta-analyses containing potentially redundant randomized controlled trials (RCTs) and the factors associated with the presence of redundancy.

This is a cross-sectional study, based on a random sample of references (n = 4500) that were published during 2020 and 2021, indexed in PubMed, Embase, or the Cochrane Database of Systematic Reviews, and retrieved through comprehensive searches using terms about systematic reviews and meta-analysis. From each systematic review, one meta-analysis fulfilling all the following criteria, if available, was included in this study: (1) assessing the effect of the intervention on a primary outcome of the systematic review; (2) combining RCTs only. The primary outcome was prevalence of meta-analyses containing potentially redundant RCTs. Potentially redundant RCTs referred to the trials that started 1 year after the overall effect estimate from cumulative meta-analysis had been statistically robust, as determined by trial sequential analysis when appropriate. The number of potentially redundant trials (if any) in each eligible meta-analysis and the number of participants involved in those trials were documented and contrasted across groups. Logistic regression analysis was conducted to explore the factors associated with presence of potential redundancy.

Of the 448 eligible meta-analyses, 57 (12.7%, 95% confidence interval (CI) 9.8–16.2%) contained potentially redundant RCTs. When limited to the 333 low-heterogeneity meta-analyses, the prevalence was 17.1% (95% CI 13.5–21.5%). The total number of potentially redundant RCTs was 295 (involving 85,385 participants), accounting for 38.5% of the RCTs (and 30.3% of the participants) included in the 57 meta-analyses. In these meta-analyses, the median number of potentially redundant RCTs and the participants involved were 2 (range: 1–50) and 352 (range: 17–26997), respectively. Potentially redundant RCTs were more likely to be present in the meta-analyses evaluating pharmaceutical intervention (odds ratio [OR] 2.31, 95% CI 1.16–4.49), assessing efficacy outcomes (OR 7.25, 95% CI 0.85–61.87), containing more than 5 RCTs (OR 6.47, 95% CI 3.22–12.99), or with the earliest RCT reporting statistically significant effect estimate (OR 5.30, 95% CI 2.64–10.64).

This study found that 12.7% to 17.1% of recently published meta-analyses contained potentially redundant RCTs, highlighting the importance of conducting or examining systematic reviews of existing evidence to justify new RCTs. More importantly, the study identified some scenarios in which redundancy was more likely to occur and thus has implications for trialists, funding agencies, ethics committees, and journal editors.

Human protection policies require assessment of how proposed clinical trials relate to prior and ongoing studies testing similar hypotheses. We assessed the extent to which clinical trial protocols cited relevant published and ongoing clinical trials that would have been easily accessible with reference searches.

We created a random sample of trial protocols using ClinicalTrials.gov, stratifying by industry and non-industry-sponsored studies. We then conducted reference searches to determine the extent to which protocols cited clinical trials with identical intervention-indication pairings that were accessible in PubMed and ClinicalTrials.gov at the time of trial initiation.

Of the 101 trial protocols evaluated, 73 had at least one identified citable trial. None contained statements suggesting a systematic search for relevant clinical evidence. Of industry-sponsored trial protocols with at least one identified citable trial, 7 of 23 (30.4%) did not cite any published clinical trials and 10 of 33 (30.3%) did not cite any ongoing relevant trials. Of the non-industry-sponsored trial protocols with at least one identified citable trial, 5 of 28 (17.9%) did not cite any published clinical trials and 14 of 19 (73.7%) did not cite any ongoing trials.

Clinical trial protocols undercite accessible, relevant trials and do not document systematic searches for relevant clinical trials. Consequently, ethics review committees often receive an incomplete picture of the research landscape if they review protocols similar to those deposited on ClinicalTrials.gov.

This study was funded by the Canadian Institutes of Health Research and the Greenwall Foundation.

We sought to map the landscape of trials investigating hydroxychloroquine (HCQ) for SARS-CoV-2 in order to draw conclusions about how clinical trials have been conducted in the pandemic environment and offer potential regulatory recommendations.

We identified and captured data related to registered studies using HCQ to treat SARS-CoV-2 registered with the publicly available National Institutes of Health (NIH) Clinical Trials Registry between February and November 2020.

Between February and November 2020, 206 studies investigating HCQ in SARS-CoV-2 were registered with the NIH Clinical Trials Registry. As of November 2020, 135 studies were listed as ongoing, 22 have been completed, and 46 are either suspended or have been terminated. Reasons for suspension or termination included difficulties with patient recruitment (n = 9), emerging evidence showing a lack of benefit of HCQ (n = 7), and recommendations by regulatory boards to discontinue (n = 10).

Many clinical trials of HCQ were launched in the first months of the pandemic, and a significant proportion of them remained active as of November 2020. The medical community appears to have responded very quickly to political interest in HCQ, while responding much more slowly to the evolving medical evidence of its lack of efficacy.

We aimed to map the resource use during systematic review (SR) production and reasons why steps of the SR production are resource intensive to discover where the largest gain in improving efficiency might be possible.

We conducted a scoping review. An information specialist searched multiple databases (e.g., Ovid MEDLINE, Scopus) and implemented citation-based and grey literature searching. We employed dual and independent screenings of records at the title/abstract and full-text levels and data extraction.

We included 34 studies. Thirty-two reported on the resource use—mostly time; four described reasons why steps of the review process are resource intensive. Study selection, data extraction, and critical appraisal seem to be very resource intensive, while protocol development, literature search, or study retrieval take less time. Project management and administration required a large proportion of SR production time. Lack of experience, domain knowledge, use of collaborative and SR-tailored software, and good communication and management can be reasons why SR steps are resource intensive.

Resource use during SR production varies widely. Areas with the largest resource use are administration and project management, study selection, data extraction, and critical appraisal of studies.