| Literature DB >> 32950502 |
João Pedro Ferreira1, Murray Epstein2, Faiez Zannad3.
Abstract
The current Coronavirus Disease 2019 (COVID-19) pandemic has exerted an unprecedented impact across the globe. As a consequence of this overwhelming catastrophe, long-established prevailing medical and scientific paradigms have been disrupted. The response of the scientific community, medical journals, media, and some politicians has been far from ideal. The present manuscript discusses the failure of the scientific enterprise in its initiatives to address the COVID-19 outbreak as a consequence of the disarray attributable to haste and urgency. To enhance conveying our message, this manuscript is organized into 3 interrelated sections: 1) the accelerated pace of publications coupled with a dysfunctional review process; 2) failure of the clinical trial enterprise; 3) propagation of misleading information by the media. In response we propose a template comprising a focus on randomized controlled clinical trials, and an insistence on responsible journal publication, and enumeration of policies to deal with social media-propagated news. We conclude with a reconsideration of the appropriate role of academic medicine and journals.Entities:
Keywords: COVID-19; Media; Medical journals; Scientific community
Year: 2020 PMID: 32950502 PMCID: PMC7499175 DOI: 10.1016/j.amjmed.2020.08.021
Source DB: PubMed Journal: Am J Med ISSN: 0002-9343 Impact factor: 4.965
Bias (Deviation from the Truth) of Observational Studies
| Bias | What Is It? | Example |
|---|---|---|
| Selection bias | The groups being studied are not comparable because they were not selected at random | Patients taking antihypertensive medication may have poorer outcome, not because of the medication but because they are sicker, that is, they represent a group of sicker people |
| Information bias | Incorrect determination of exposure, outcome, or both | Information about a treatment or an event is collected differently across patient populations, for example, hospital records vs phone calls vs face-to-face visits |
| Confounding | The association between the exposure and outcome is determined by another factor that can be measured or unmeasured | The association between a treatment for diabetes and outcome may be determined by the patients’ income or access to health care, for example, poorer people may not have insurance to cover their health expenses |
| Exaggeration of the effect | The magnitude of the effect seems greater on a relative scale than what it actually is on an absolute scale | In the absence of a prespecified sample size/events and expected treatment effect, an observational study may report an “important” relative effect even in the setting of a low event rate and small difference in events. For example, an outcome affecting 1.7% of the population on the “exposed/treated” and 1.3% on the “nonexposed/treated” may give an odds (or hazards) ratio around 1.3, which is usually translated by a “30% increase of event,” but the absolute difference is 0.4%, which should be translated into a 0.4% increase and not 30%. |
Given these limitations, the results from observational studies should be regarded as “hypothesis-generating” to be tested in randomized controlled trials; observational studies should not guide treatment decisions.
Framework to Support Editors and Reviewers in the Handling of Observational Analyses
| Checklist | Comment |
|---|---|
Participants must provide informed consent for participation in the study | Data coming from sources without proof of signed informed consent should not be taken seriously |
The study must have ethical approval from a clearly identified and reachable ethics committee | Data that do not meet ethical standards should not be considered for publication |
Clear information about the data oversight and management must be provided | The people responsible for the data oversight and data-management must be identified and reachable if required |
Clear information about the statistical approach must be provided and a statistical analysis plan (SAP) should be available | The statistical methods must be very detailed, including on the handling of missing data and rationale of the adjustment technique used; the statistician(s) must be reachable and accountable. |
The data should be available upon reasonable request | The full dataset used for the analysis should be available for independent verification. For example, upon request from a journal |
The study should be registered in an official agency | It is strongly recommended a prior registry of the cohort along with its description (eg, in ClinicalTrials.gov) |
The study should have well-defined entry criteria, comparator arm, sample size calculation, outcomes of interest, and follow-up/exposure time | Observational studies should mimic the standards used for randomized trials |
Critical Appraisal of the COVID-19 Randomized Controlled Trials
| Study | Patients | Treatments | Main Findings | Methodological Issues |
|---|---|---|---|---|
| A Trial of Lopinavir–Ritonavir in Adults Hospitalized with Severe COVID-19 | 199 adult patients hospitalized with confirmed SARS-CoV-2 infection | 1:1 assignment of lopinavir–ritonavir (400 mg and 100 | Lopinavir–ritonavir was not different from standard care in the time to clinical improvement. | The trial was not blinded, which could have influenced decision-making and the use of concomitant treatments. |
| Triple Combination of Interferon Beta-1b, Lopinavir–Ritonavir, and Ribavirin in the Treatment of Patients Admitted to Hospital with COVID-19: an Open-Label, Randomized, Phase 2 Trial | 127 adult patients hospitalized with confirmed SARS-CoV-2 infection | 2:1 assignment to a combination of | The combination group had a significantly shorter median time from start of study treatment to negative nasopharyngeal swab. | The trial was not blinded, which could have influenced decision-making and the use of concomitant treatments. |
| Remdesivir in Adults with Severe COVID 19: A Randomized, Double-Blind, Placebo-Controlled, Multicenter Trial | 237 adult patients hospitalized with confirmed SARS-CoV-2 infection | 2:1 ratio assignment to intravenous remdesivir (200 mg on day 1 | Remdesivir was not associated | Exaggerated claims of treatment effect not supported by the data. |
| Remdesivir for the Treatment of Covid-19 – Preliminary Report | 1063 adult patients hospitalized with confirmed SARS-CoV-2 infection | 1:1 ratio assignment to intravenous remdesivir (200 mg on day 1 | Remdesivir reduced the time to recovery (median: 11 vs 15 d). | Treatment cross-over. |
| Remdesivir for 5 or 10 Days in Patients with Severe Covid-19 | 397 adult patients hospitalized with confirmed SARS-CoV-2 infection, oxygen saturation of 94% or less (in ambient air), and radiologic evidence of pneumonia | 1:1 ratio assignment to intravenous remdesivir (200 mg on day 1 | No difference between a 5-d course and a 10-d course of remdesivir was found. | Open label. |
| A Randomized Trial of Hydroxychloroquine as Postexposure Prophylaxis for COVID-19 | 821 asymptomatic participants who had household or occupational exposure to someone with confirmed COVID-19 | Participants were randomly assigned to receive either placebo or hydroxychloroquine (800 mg once, followed by 600 mg in 6 to 8 h, then 600 mg daily for 4 additional d) within 4 d after exposure | Hydroxychloroquine did not prevent illness compatible with COVID-19 or confirmed infection. | No consistent proof of exposure to SARS-CoV-2 or laboratory confirmation. |
| Effect of Convalescent Plasma Therapy on Time to Clinical Improvement in Patients with Severe and Life-threatening COVID-19 | 103 participants with laboratory-confirmed COVID-19 that was severe (respiratory distress or hypoxemia) or life-threatening (shock, organ failure, or requiring mechanical ventilation) | Convalescent plasma in addition to standard treatment vs standard treatment alone (control) | Convalescent plasma therapy did not result in a statistically significant improvement in time to clinical improvement within 28 d. | Open-label. |
| Study to evaluate the safety and antiviral activity of remdesivir (GS-5734) in participants with severe Coronavirus Disease. | 397 patients hospitalized with COVID-19 with oxygen saturation ≤94% while breathing ambient air, and radiologic evidence of pneumonia | Patients were randomly assigned in a 1:1 ratio to receive intravenous remdesivir for either 5 d or 10 d | No difference between a 5-d course and a 10-d course of remdesivir. | Open label. |
| Dexamethasone in Hospitalized Patients with Covid-19 – Preliminary Report | 6425 patients hospitalized with COVID-19 | Oral or intravenous dexamethasone (6 mg once daily) for up to 10 d or usual care alone | The use of dexamethasone resulted in lower 28-d mortality among those who were receiving either invasive mechanical ventilation or oxygen alone at randomization but not among those receiving no respiratory support. | Open-label. |
COVID-19 = Coronavirus Disease 2019; SARS-CoV-2 = severe acute respiratory syndrome coronavirus 2.
Potential Solutions to Increase the Quality of Randomized Trials and Information Diffusion
| Problem | Potential Solution |
|---|---|
| Observational and RCT findings are given the same consideration/weight by the media and many scientists | Medical journals should diffuse in the media the differences between an observational study and an RCT; A grading of evidence (eg, “GRADE”) should be used along with the release of the study so that people can evaluate to what extent they should rely on the information; Observational studies should generate hypotheses to be tested in RCTs and not inform about treatment decisions. |
| RCTs (to date) are underpowered for assessing mortality and have many methodological caveats | Coordination is warranted to allocate resources for performing larger and well-powered studies; The WHO should be able to provide such coordination and multilateral approach by liaising with the coordinating agencies and the Country/Union level (eg, EMA, NIH); Independent DSMB should have the final decision on whether the trial should be stopped or not, and also inform about potential trial misconduct. |
| Exaggerated claims about efficacy are presented in the study conclusions and abstract | Reviewers and journal editors should pay much attention to the wording and any suggestion of exaggerated effect, particularly in the abstract, which is the most widely read part of the article. |
| Spread of “fake news” | Social media platforms should improve their systems of “fake news” detection using real-time algorithms that can cross-check information, providing a grading on how reliable that information is. An easy-to-implement color code could be used, with “green” = reliable, “yellow” = needs confirmation, “red” = unreliable/false; Media in general should be more informed about the conduct of medical research and the grade of evidence, while complying with the ethical principles of journalism. |
DMSD = data monitoring and safety board; EMA = European Medicines Agency; “GRADE” = grading quality of evidence and strength of recommendations; NIH = National Institutes of Health; RCT = randomized controlled trial; WHO = World Health Organization.
GRADE Working Group (https://www.bmj.com/content/328/7454/1490).
https://www.spj.org/ethicscode.asp.
FigureColor-code proposal for grading evidence on medical news in the media (including social media). The color-code fact check would appear as a bar or logo on top of the shared messages. RCT = randomized controlled trial.
The Central Role of Medical Journals and Editors for Retaining Transparency and Quality of Evidence
| Proposed Role of Medical Journals and Editors |
|---|
Powerful agents for counteracting medical misinformation |
Should join forces to achieve global consensus and take action on matters of public interest |
Could provide guidance and regulation for information diffusion in the media |
Social media platforms (eg, Twitter) can be used to diffuse medical information (upon further regulation – see also |
Reward systems should place more emphasis on long-term scientific achievements, rather than immediate online rewards |
Clinical impact metrics should be created. For example, by conducting surveys with clinicians from a certain area of expertise to gather information on how much they used a research article for their clinical practice |
Medical journals should reduce incentives on publications by “press release.” For example, publications that have been previously presented in media without robust data should no longer be considered suitable for publication in a medical journal |