Background In the early phase of the pandemic, some guidelines recommended the use of corticosteroids for critically ill patients with COVID‐19, whereas others recommended against the use despite lack of firm evidence of either benefit or harm. In the COVID STEROID trial, we aimed to assess the effects of low‐dose hydrocortisone on patient‐centred outcomes in adults with COVID‐19 and severe hypoxia. Methods In this multicentre, parallel‐group, placebo‐controlled, blinded, centrally randomised, stratified clinical trial, we randomly assigned adults with confirmed COVID‐19 and severe hypoxia (use of mechanical ventilation or supplementary oxygen with a flow of at least 10 L/min) to either hydrocortisone (200 mg/day) versus a matching placebo for 7 days or until hospital discharge. The primary outcome was the number of days alive without life support at day 28 after randomisation. Results The trial was terminated early when 30 out of 1,000 participants had been enrolled because of external evidence indicating benefit from corticosteroids in severe COVID‐19. At day 28, the median number of days alive without life support in the hydrocortisone versus placebo group were 7 versus 10 (adjusted mean difference: ‐1.1 days, 95% CI ‐9.5 to 7.3, p = 0.79); mortality was 6/16 versus 2/14; and the number of serious adverse reactions 1/16 versus 0/14. Conclusions In this trial of adults with COVID‐19 and severe hypoxia, we were unable to provide precise estimates of the benefits and harms of hydrocortisone as compared with placebo as only 3% of the planned sample size were enrolled.
Objective To characterise and analyse the experiences of trial researchers of if and how conflicts of interest had unduly influenced clinical trials they had worked on, what management strategies they had used to minimise any potential influence, and their experiences and views on conflicts of interest more generally. Design Qualitative interview study. Participants Trial researchers who had participated in at least 10 clinical trials with methodological or statistical expertise. Researchers differed by geographical location, educational background, and experience with different types of funders. Interviewees were identified by searches on Web of Science and snowball sampling. 52 trial researchers were approached by email; 20 agreed to be interviewed. Setting Interviews conducted by telephone, recorded, transcribed verbatim, imported to NVivo 12, and analysed by systematic text condensation. Semistructured interviews focused on financial and non-financial conflicts of interest. Results The interviewees had participated in a median of 37.5 trials and were mainly male physicians who had experience with commercial and non-commercial trial funders. Two predefined themes (influence of conflicts of interest and management strategies) and two additional themes (definition and reporting of conflicts of interest) emerged. Examples of perceived influence of conflicts of interest were: choice of inferior comparator, manipulation of the randomisation process, prematurely stopping the trials, fabrication of data, blocking access to data, and spin (eg, overly favourable interpretation of the results). Examples of strategies to manage conflicts of interest were: disclosure procedures, exclusion of the funder from design and analysis, independent committees, contracts ensuring complete access to the data, and no restriction by the funder on analysis and reporting. Interviewees used different definitions or thresholds for what they considered to be conflicts of interest, and they described different criteria for when to report them. Some interviewees considered non-commercial financial conflicts of interest (eg, funding of trials by governmental health agencies with a political agenda) to be equally or more important than commercial financial conflicts of interest (eg, funding by drug and device companies), but more challenging to report and manage. Conclusion This study described how trial researchers perceive conflicts of interest unduly influencing clinical trials they had worked on, and the management strategies they used to prevent these influences. The results indicated considerable variability in researchers’ understanding of what conflicts of interest are and when they should be reported.
Randomised trials are often funded by commercial companies and methodological studies support a widely held suspicion that commercial funding may influence trial results and conclusions. However, these studies often have a risk of confounding and reporting bias. The risk of confounding is markedly reduced in meta‐epidemiological studies that compare fairly similar trials within meta‐analyses, and risk of reporting bias is reduced with access to unpublished data. Therefore, we initiated the COMmercial Funding In Trials (COMFIT) study aimed at investigating the impact of commercial funding on estimated intervention effects in randomised clinical trials based on a consortium of researchers who agreed to share meta‐epidemiological study datasets with information on meta‐analyses and trials included in meta‐epidemiological studies. Here, we describe the COMFIT study, its database, and descriptive results. We included meta‐epidemiological studies with published or unpublished data on trial funding source and results or conclusions. We searched five bibliographic databases and other sources. We invited authors of eligible meta‐epidemiological studies to join the COMFIT consortium and to share data. The final construction of the COMFIT database involves checking data quality, identifying trial references, harmonising variable categories, and removing non‐informative meta‐analyses as well as correlated meta‐analyses and trial results. We included data from 17 meta‐epidemiological studies, covering 728 meta‐analyses and 6841 trials. Seven studies (405 meta‐analyses, 3272 trials) had not published analyses on the impact of commercial funding, but shared unpublished data on funding source. On this basis, we initiated the construction of a combined database. Once completed, the database will enable comprehensive analyses of the impact of commercial funding on trial results and conclusions with increased statistical power and a markedly reduced risk of confounding and reporting bias.
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