Tocilizumab in COVID-19 – A Bayesian reanalysis of RECOVERY
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Abstract
Background
Randomised Evaluation of COVID-19 Therapy (RECOVERY) demonstrated that tocilizumab reduces mortality in hospitalized COVID-19 patients. However, substantial uncertainty remains whether tocilizumab’s effect is similar across clinically relevant subgroups. Whether this uncertainty can be resolved with Bayesian methods is unknown.
Design, Setting, Participants, and Interventions
RECOVERY was a controlled, open-label, platform UK trial that randomized (1:1) 4116 adults with oxygen saturation <92% on room air or receiving oxygen therapy with C-reactive protein ≥75 mg/L to either usual care or tocilizumab plus usual care.
Main outcome measures
Mortality and hospital discharge within 28 days.
Methods
Using Bayesian methods, we combined RECOVERY with evidence-based priors in-corporating previous COVID-19 tocilizumab RCTs. The probability of tocilizumab’s benefit for respiratory support and corticosteroid subgroups and sensitivity analyses were performed with different prior distributions and baseline risks.
Results
For all-cause mortality, the posterior probabilities of decreased deaths with tocilizumab were >99% and 19% in patients using and not using corticosteroids, respectively. In patients on simple oxygen only, non-invasive ventilation and invasive mechanical ventilation, the probabilities of decreased mortality were 96%, >99% and 77%, respectively. The probabilities for a clinically significant mortality reduction, as assessed by an absolute risk difference > 3% (number needed to treat ≤ 33), were 77%, 96%, 56%, respectively. Sensitivity analyses highlighted the uncertainty and lack of conclusive evidence for tocilizumab’s effect in patients on invasive mechanical ventilation and those without concurrent corticosteroids. Posterior probabilities of benefit for hospital discharge outcome were high and consistent across most subgroups.
Conclusions
In this Bayesian reanalysis, COVID-19 hospitalized patients exposed to corticosteroids or on non-invasive ventilation have a high probability of a clinically meaningful mortality benefit from tocilizumab. Tocilizumab also likely improves discharge from hospital in most subgroups. Future research should further address if patients on invasive mechanical ventilation can also benefit from tocilizumab.
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SciScore for 10.1101/2021.06.15.21258966: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: This study was exempt from obtaining formal institutional review board approval and the requirement to obtain informed patient consent because it is secondary research of publicly available data sets.
Consent: This study was exempt from obtaining formal institutional review board approval and the requirement to obtain informed patient consent because it is secondary research of publicly available data sets.Sex as a biological variable not detected. Randomization In National Health Service hospitals in the UK, 4,116 adults with oxygen saturation <92% on room air or receiving oxygen therapy and with C-reactive protein ≥ 75 mg/L were randomized to either usual care or tocilizumab plus usual … SciScore for 10.1101/2021.06.15.21258966: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: This study was exempt from obtaining formal institutional review board approval and the requirement to obtain informed patient consent because it is secondary research of publicly available data sets.
Consent: This study was exempt from obtaining formal institutional review board approval and the requirement to obtain informed patient consent because it is secondary research of publicly available data sets.Sex as a biological variable not detected. Randomization In National Health Service hospitals in the UK, 4,116 adults with oxygen saturation <92% on room air or receiving oxygen therapy and with C-reactive protein ≥ 75 mg/L were randomized to either usual care or tocilizumab plus usual care in a 1:1 ratio. Blinding not detected. Power Analysis RECOVERY was designed, with 90% power and alpha = 0.01, to detect a 5% absolute risk reduction assuming a control mortality risk of at least 25%. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Strengths and limitations: Our study has several strengths. Most importantly, Bayesian analyses permit the inclusion of prior beliefs and or prior objective evidence. We only included data from RCTs with a low or moderate risk of bias, as assessed by the living systematic review from which we based our data extraction process.[11] Further, we tried to mitigate potential biases associated with researcher degrees of freedom by pre-registering the data extraction process and part of the analysis plan,[14] and restricting our analyses to RECOVERY specified subgroups. Next, in contrast to P-values and confidence intervals, Bayesian analyses can provide intuitive and understandable probability estimates of each subgroup’s treatment effect. Moreover, these analyses not only inform the probability of any benefit but also calculation of the probabilities of clinically meaningful benefits. This enhances the readers’ ability to distinguish clinical from statistical significance. Lastly, we incorporated most of the high-quality evidence available on tocilizumab and COVID-19 to our prior distributions. Notwithstanding these strengths, our study also has limitations. First, we did not have access to patient-level data for any RCTs included in this article. Subgroup analyses that separate patients by a single baseline characteristic are over-simplified and can bring shortcomings.[2] Lack of patient-level data does not allow analyses using more complex statistical models that incorporate mul...
Results from TrialIdentifier: We found the following clinical trial numbers in your paper:
Identifier Status Title NCT04381936 Recruiting Randomised Evaluation of COVID-19 Therapy Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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