Dataset Information

ACCORD: A Multicentre, Seamless, Phase 2 Adaptive Randomisation Platform Study to Assess the Efficacy and Safety of Multiple Candidate Agents for the Treatment of COVID-19 in Hospitalised Patients: A structured summary of a study protocol for a randomised controlled trial.

ABSTRACT:

SUBMITTER: Wilkinson T

PROVIDER: S-EPMC7393340 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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ACCORD: A Multicentre, Seamless, Phase 2 Adaptive Randomisation Platform Study to Assess the Efficacy and Safety of Multiple Candidate Agents for the Treatment of COVID-19 in Hospitalised Patients: A structured summary of a study protocol for a randomised controlled trial.

Wilkinson Tom T Dixon Rupert R Page Clive C Carroll Miles M Griffiths Gareth G Ho Ling-Pei LP De Soyza Anthony A Felton Timothy T Lewis Keir E KE Phekoo Karen K Chalmers James D JD Gordon Anthony A McGarvey Lorcan L Doherty Jillian J Read Robert C RC Shankar-Hari Manu M Martinez-Alier Nuria N O'Kelly Michael M Duncan Graeme G Walles Roelize R Sykes James J Summers Charlotte C Singh Dave D

Trials 20200731 1

<h4>Objectives</h4>Stage 1: To evaluate the safety and efficacy of candidate agents as add-on therapies to standard of care (SoC) in patients hospitalised with COVID-19 in a screening stage. Stage 2: To confirm the efficacy of candidate agents selected on the basis of evidence from Stage 1 in patients hospitalised with COVID-19 in an expansion stage.<h4>Trial design</h4>ACCORD is a seamless, Phase 2, adaptive, randomised controlled platform study, designed to rapidly test candidate agents in the ...[more]

PMID: 32736596

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Project description:ObjectivesOpioid-induced respiratory depression (OIRD) and oversedation are rare but potentially devastating adverse events in hospitalised patients. We investigated which features predict an individual patient's risk of OIRD or oversedation; and developed a risk stratification tool that can be used to aid point-of-care clinical decision-making.DesignRetrospective observational study.SettingTwelve acute care hospitals in a large not-for-profit integrated delivery system.ParticipantsAll inpatients ≥18 years admitted between 1 July 2016 and 30 June 2018 who received an opioid during their stay (163 190 unique hospitalisations).Main outcome measuresThe primary outcome was occurrence of sedation or respiratory depression severe enough that emergent reversal with naloxone was required, as determined from medical record review; if naloxone reversal was unsuccessful or if there was no evidence of hypoxic encephalopathy or death due to oversedation, it was not considered an oversedation event.ResultsAge, sex, body mass index, chronic obstructive pulmonary disease, concurrent sedating medication, renal insufficiency, liver insufficiency, opioid naïvety, sleep apnoea and surgery were significantly associated with risk of oversedation. The strongest predictor was concurrent administration of another sedating medication (adjusted HR, 95% CI=3.88, 2.48 to 6.06); the most common such medications were benzodiazepines (29%), antidepressants (22%) and gamma-aminobutyric acid analogue (14.7%). The c-statistic for the final model was 0.755. The 24-point Oversedation Risk Criteria (ORC) score developed from the model stratifies patients as high (>20%, ≥21 points), moderate (11%-20%, 10-20 points) and low risk (≤10%, <10 points).ConclusionsThe ORC risk score identifies patients at high risk for OIRD or oversedation from routinely collected data, enabling targeted monitoring for early detection and intervention. It can also be applied to preventive strategies-for example, clinical decision support offered when concurrent prescriptions for opioids and other sedating medications are entered that shows how the chosen combination impacts the patient's risk.

Project description:BackgroundThe Randomised Evaluation of COVID-19 Therapy (RECOVERY) trial is aimed at addressing the urgent need to find effective treatments for patients hospitalised with suspected or confirmed COVID-19. The trial has had many successes, including discovering that dexamethasone is effective at reducing COVID-19 mortality, the first treatment to reach this milestone in a randomised controlled trial. Despite this, it continues to use standard or 'fixed' randomisation to allocate patients to treatments. We assessed the impact of implementing response adaptive randomisation within RECOVERY using an array of performance measures, to learn if it could be beneficial going forward. This design feature has recently been implemented within the REMAP-CAP platform trial.MethodsTrial data was simulated to closely match the data for patients allocated to standard care, dexamethasone, hydroxychloroquine, or lopinavir-ritonavir in the RECOVERY trial from March-June 2020, representing four out of five arms tested throughout this period. Trials were simulated in both a two-arm trial setting using standard care and dexamethasone, and a four-arm trial setting utilising all above treatments. Two forms of fixed randomisation and two forms of response-adaptive randomisation were tested. In the two-arm setting, response-adaptive randomisation was implemented across both trial arms, whereas in the four-arm setting it was implemented in the three non-standard care arms only. In the two-arm trial, randomisation strategies were performed at the whole trial level as well as within three pre-specified patient subgroups defined by patients' respiratory support level.ResultsAll response-adaptive randomisation strategies led to more patients being given dexamethasone and a lower mortality rate in the trial. Subgroup specific response-adaptive randomisation reduced mortality rates even further. In the two-arm trial, response-adaptive randomisation reduced statistical power compared to FR, with subgroup level adaptive randomisation exhibiting the largest power reduction. In the four-arm trial, response-adaptive randomisation increased statistical power in the dexamethasone arm but reduced statistical power in the lopinavir arm. Response-adaptive randomisation did not induce any meaningful bias in treatment effect estimates nor did it cause any inflation in the type 1 error rate.ConclusionsUsing response-adaptive randomisation within RECOVERY could have increased the number of patients receiving the optimal COVID-19 treatment during the trial, while reducing the number of patients needed to attain the same study power as the original study. This would likely have reduced patient deaths during the trial and lead to dexamethasone being declared effective sooner. Deciding how to balance the needs of patients within a trial and future patients who have yet to fall ill is an important ethical question for the trials community to address. Response-adaptive randomisation deserves to be considered as a design feature in future trials of COVID-19 and other diseases.

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Dataset Information

ACCORD: A Multicentre, Seamless, Phase 2 Adaptive Randomisation Platform Study to Assess the Efficacy and Safety of Multiple Candidate Agents for the Treatment of COVID-19 in Hospitalised Patients: A structured summary of a study protocol for a randomised controlled trial.

Publications

ACCORD: A Multicentre, Seamless, Phase 2 Adaptive Randomisation Platform Study to Assess the Efficacy and Safety of Multiple Candidate Agents for the Treatment of COVID-19 in Hospitalised Patients: A structured summary of a study protocol for a randomised controlled trial.

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