Clinical trials in COVID-19 management & prevention: A meta-epidemiological study examining methodological quality

The Efficacy of Multivitamin, Vitamin A, Vitamin B, Vitamin C, and Vitamin D Supplements in the Prevention and Management of COVID-19 and Long-COVID: An Updated Systematic Review and Meta-Analysis of Randomized Clinical Trials

This review aims to evaluate the efficacy of any vitamin administration(s) in preventing and managing COVID-19 and/or long-COVID. Databases were searched up to May 2023 to identify randomized clinical trials comparing data on the effects of vitamin supplementation(s) versus placebo or standard of care on the two conditions of interest. Inverse-variance random-effects meta-analyses were conducted to estimate pooled risk ratios (RRs) and 95% confidence intervals (CIs) for all-cause mortality between supplemented and non-supplemented individuals. Overall, 37 articles were included: two regarded COVID-19 and long-COVID prevention and 35 records the COVID-19 management. The effects of vitamin D in preventing COVID-19 and long-COVID were contrasting. Similarly, no conclusion could be drawn on the efficacy of multivitamins, vitamin A, and vitamin B in COVID-19 management. A few positive findings were reported in some vitamin C trials but results were inconsistent in most outcomes, excluding all-cause mortality (RR = 0.84; 95% CI: 0.72-0.97). Vitamin D results were mixed in most aspects, including mortality, in which benefits were observed in regular administrations only (RR = 0.67; 95% CI: 0.49-0.91). Despite some benefits, results were mostly contradictory. Variety in recruitment and treatment protocols might explain this heterogeneity. Better-designed studies are needed to clarify these vitamins' potential effects against SARS-CoV-2.

Clinical trials and their impact on policy during COVID-19: a review

Background

Of over 8,000 recorded randomised trials addressing COVID-19, around 80% were of treatments, and 17% have reported results. Approximately 1% were adaptive or platform trials, with 25 having results available, across 29 journal articles and 10 preprint articles.

Methods

We conducted an extensive literature review to address four questions about COVID-19 trials, particularly the role and impact of platform/adaptive trials and lessons learned.

Results

The key findings were: Q1. Social value in conducting trials and uptake into policy? COVID-19 drug treatments varied substantially and changed considerably, with drugs found effective in definitive clinical trials replacing unproven drugs. Dexamethasone has likely saved ½-2 million lives, and was cost effective across a range of countries and populations, whereas the cost effectiveness of remdesivir is uncertain. Published economic and health system impacts of COVID-19 treatments were infrequent. Q2. Issues with adaptive trial designs. Of the 77 platform trials registered, 6 major platform trials, with approximately 50 treatment arms, recruited ~135,000 participants with funding over $100 million. Q3. Models of good practice. Streamlined set-up processes such as flexible and fast-track funding, ethics, and governance approvals are vital. To facilitate recruitment, simple and streamlined research processes, and pre-existing research networks to coordinate trial planning, design, conduct and practice change are crucial to success. Q4. Potential conflicts to avoid? When treating patients through trials, balancing individual and collective rights and allocating scarce resources between healthcare and research are challenging. Tensions occur between commercial and non-commercial sectors, and academic and public health interests, such as publication and funding driven indicators and the public good.

Conclusion

There is a need to (i) reduce small, repetitive, single centre trials, (ii) increase coordination to ensure robust research conducted for treatments, and (iii) a wider adoption of adaptive/platform trial designs to respond to fast-evolving evidence landscape.

Spin in randomized controlled trials of pharmacology in COVID-19: A systematic review

Spin, defined as the misrepresentation of the results of a study, could negate the validity of scientific findings. To explore the manifestation of spin, and identify the factors affecting spin in COVID-19 RCTs, a systematic review was performed from PubMed/Medline, National Institutes of Health, EMBASE, Cochrane, and Web of Science. RCTs on pharmacotherapy for COVID-19 with nonsignificant primary outcomes published in 2020 were included. 21 abstracts (33.9%) and 28 main texts (45.2%) were found to contain spin in at least one section. In the conclusion section, other spin strategies beautifying their findings that were not included in the abstract were found in the main texts. More factors influencing the level of spin were found in abstracts than in the main texts, but most of the levels of spin in abstracts were comparable to those in the main texts. Although common factors that affected the manifestation of spin in the main texts and abstracts were the sample size and type of journal, further research to determine multicollinearity between significant factors and the manifestation of spin is required.

The relationship between pragmatism, timing, and study size on impact of randomized trials: a qualitative, hypothesis generating study of trials of systemic corticosteroids for COVID-19

OBJECTIVE

To explore qualitatively the relationship between selected trial design choices and proxies for a scientific and clinical uptake in a cohort of published randomized controlled trials (RCTs) of corticosteroids for COVID-19, to identify design characteristics that may result in trials with potential to eliminate equipoise, achieve uptake, and help reduce research waste.

STUDY DESIGN AND SETTING

A systematic literature search and qualitative, narrative review of published RCTs (up to April 13, 2021) evaluating the effectiveness of systemic corticosteroids in treatment of COVID-19. We extracted information on sample size, number of centers, single-country or multi-country conduct, dates of initiation and of publication, risk of bias and pragmatism scores, and also on an impact measured by citation in scientific literature and in clinical guidelines. We qualitatively compared design features of the highest impact vs. other trials.

RESULTS

Randomised Evaluation of COVID-19 Therapy (RECOVERY) was by the most impactful of the seven eligible RCTs as it was 10 times more frequently cited in peer-reviewed literature and influenced all the selected COVID-19 treatment guidelines. All trials started recruiting from similar dates. RECOVERY was a single-country, multicentre platform trial at low risk of bias, features which also fail to distinguish it from the other trials. RECOVERY was distinguished by more strongly pragmatic design features, more centers, and more rapid recruitment resulting in a larger sample size and early publication.

CONCLUSION

Higher pragmatism scores may contribute to recruiting more centers and more rapid recruitment of patients at each center, leading to larger size, earlier publication, and greater scientific and guideline uptake. By eliminating equipoise, RECOVERY rendered other simultaneous trials redundant. Further work is needed to confirm these findings in a larger quantitative study and to identify the individual contribution of each characteristic of pragmatism to conduct and impact of trials and their interaction in different national contexts. Until then, research waste might be reduced by designing trials with as many of the characteristics of RECOVERY as is feasible.

Artificial intelligence in COVID-19 evidence syntheses was underutilized, but impactful: a methodological study

OBJECTIVES

A rapidly developing scenario like a pandemic requires the prompt production of high-quality systematic reviews, which can be automated using artificial intelligence (AI) techniques. We evaluated the application of AI tools in COVID-19 evidence syntheses.

STUDY DESIGN

After prospective registration of the review protocol, we automated the download of all open-access COVID-19 systematic reviews in the COVID-19 Living Overview of Evidence database, indexed them for AI-related keywords, and located those that used AI tools. We compared their journals' JCR Impact Factor, citations per month, screening workloads, completion times (from pre-registration to preprint or submission to a journal) and AMSTAR-2 methodology assessments (maximum score 13 points) with a set of publication date matched control reviews without AI.

RESULTS

Of the 3,999 COVID-19 reviews, 28 (0.7%, 95% CI 0.47-1.03%) made use of AI. On average, compared to controls (n = 64), AI reviews were published in journals with higher Impact Factors (median 8.9 vs. 3.5, P < 0.001), and screened more abstracts per author (302.2 vs. 140.3, P = 0.009) and per included study (189.0 vs. 365.8, P < 0.001) while inspecting less full texts per author (5.3 vs. 14.0, P = 0.005). No differences were found in citation counts (0.5 vs. 0.6, P = 0.600), inspected full texts per included study (3.8 vs. 3.4, P = 0.481), completion times (74.0 vs. 123.0, P = 0.205) or AMSTAR-2 (7.5 vs. 6.3, P = 0.119).

CONCLUSION

AI was an underutilized tool in COVID-19 systematic reviews. Its usage, compared to reviews without AI, was associated with more efficient screening of literature and higher publication impact. There is scope for the application of AI in automating systematic reviews.

The Fragility of Statistically Significant Results in Randomized Clinical Trials for COVID-19

IMPORTANCE

Interpreting results from randomized clinical trials (RCTs) for COVID-19, which have been published rapidly and in vast numbers, is challenging during a pandemic.

OBJECTIVE

To evaluate the robustness of statistically significant findings from RCTs for COVID-19 using the fragility index.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study included COVID-19 trial articles that randomly assigned patients 1:1 into 2 parallel groups and reported at least 1 binary outcome as significant in the abstract. A systematic search was conducted using PubMed to identify RCTs on COVID-19 published until August 7, 2021.

EXPOSURES

Trial characteristics, such as type of intervention (treatment drug, vaccine, or others), number of outcome events, and sample size.

MAIN OUTCOMES AND MEASURES

Fragility index.

RESULTS

Of the 47 RCTs for COVID-19 included, 36 (77%) were studies of the effects of treatment drugs, 5 (11%) were studies of vaccines, and 6 (13%) were of other interventions. A total of 138 235 participants were included in these trials. The median (IQR) fragility index of the included trials was 4 (1-11). The medians (IQRs) of the fragility indexes of RCTs of treatment drugs, vaccines, and other interventions were 2.5 (1-6), 119 (61-139), and 4.5 (1-18), respectively. The fragility index among more than half of the studies was less than 1% of each sample size, although the fragility index as a proportion of events needing to change would be much higher.

CONCLUSIONS AND RELEVANCE

This cross-sectional study found a relatively small number of events (a median of 4) would be required to change the results of COVID-19 RCTs from statistically significant to not significant. These findings suggest that health care professionals and policy makers should not rely heavily on individual results of RCTs for COVID-19.

How informative were early SARS-CoV-2 treatment and prevention trials? a longitudinal cohort analysis of trials registered on ClinicalTrials.gov

Background

Early in the SARS-CoV-2 pandemic, commentators warned that some COVID trials were inadequately conceived, designed and reported. Here, we retrospectively assess the prevalence of informative COVID trials launched in the first 6 months of the pandemic.

Methods

Based on prespecified eligibility criteria, we created a cohort of Phase 1/2, Phase 2, Phase 2/3 and Phase 3 SARS-CoV-2 treatment and prevention efficacy trials that were initiated from 2020-01-01 to 2020-06-30 using ClinicalTrials.gov registration records. We excluded trials evaluating behavioural interventions and natural products, which are not regulated by the U.S. Food and Drug Administration (FDA). We evaluated trials on 3 criteria of informativeness: potential redundancy (comparing trial phase, type, patient-participant characteristics, treatment regimen, comparator arms and primary outcome), trials design (according to the recommendations set-out in the May 2020 FDA guidance document on SARS-CoV-2 treatment and prevention trials) and feasibility of patient-participant recruitment (based on timeliness and success of recruitment).

Results

We included all 500 eligible trials in our cohort, 58% of which were Phase 2 and 84.8% were directed towards the treatment of SARS-CoV-2. Close to one third of trials met all three criteria and were deemed informative (29.9% (95% Confidence Interval 23.7–36.9)). The proportion of potentially redundant trials in our cohort was 4.1%. Over half of the trials in our cohort (56.2%) did not meet our criteria for high quality trial design. The proportion of trials with infeasible patient-participant recruitment was 22.6%.

Conclusions

Less than one third of COVID-19 trials registered on ClinicalTrials.gov during the first six months met all three criteria for informativeness. Shortcomings in trial design, recruitment feasibility and redundancy reflect longstanding weaknesses in the clinical research enterprise that were likely amplified by the exceptional circumstances of a pandemic.

Rehabilitation and COVID-19: rapid living systematic review by Cochrane Rehabilitation Field - third edition. Update as of June 30th, 2021

INTRODUCTION

This paper updates and summarizes the current evidence informing rehabilitation of patients with COVID-19 and/or describing the consequences of the disease and its treatment.

EVIDENCE ACQUISITION

Studies published from May 1st to June 30th, 2021 were selected, excluding descriptive studies and expert opinions. Papers were categorized according to study design, research question, COVID-19 phase, limitations of functioning of rehabilitation interest, and type of rehabilitation service involved. From this edition, we improved the quality assessment using the Joanna Briggs Institute checklists for observational studies and the Cochrane Risk of Bias Tool for randomized-controlled clinical trials (RCTs).

EVIDENCE SYNTHESIS

Twenty-five, out of 3699 papers, were included. They were three RCTs, 13 cross-sectional studies and nine cohort studies. Twenty studies reported data on symptom prevalence (N.=13) or disease natural history (N.=7); and five studies reported intervention effectiveness at the individual level. All study participants were COVID survivors and 48% of studies collected information on participants 6 months or longer after COVID-19 onset. The most frequent risks of bias for RCTs concerned weaknesses in allocation concealment, blinding of therapists, and lack of intention-to-treat analysis. Most analytical studies failed to identify or deal with confounders, describe or deal with dropouts or eventually perform an appropriate statistical analysis.

CONCLUSIONS

Most studies in this updated review targeted the prevalence of limitations of functioning of rehabilitation interest in COVID-19 survivors. This is similar to past review findings; however, data in the new studies was collected at longer follow-up periods (up to one year after symptom onset) and in larger samples of participants. More RCTs and analytical observational studies are available, but the methodological quality of recently published studies is low. There is a need for good quality intervention efficacy and effectiveness studies to complement the rapidly expanding evidence from observational studies.