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We generalize the Dunnett test to derive efficacy and futility boundaries for a flexible multi-arm multistage clinical trial for a normally distributed endpoint with known variance. We show that the boundaries control the familywise error rate in the strong sense. The method is applicable for any number of treatment arms, number of stages and number of patients per treatment per stage. It can be used for a wide variety of boundary types or rules derived from á-spending functions. Additionally, we show how sample size can be computed under a least favourable configuration power requirement and derive formulae for expected sample sizes.

Intrusive memories (IMs) after traumatic events can be distressing and disrupt mental health and functioning. We evaluated the impact of a brief remotely-delivered digital imagery-competing task intervention on the number of IMs for intensive care unit (ICU) staff who faced repeated trauma exposure during the COVID-19 pandemic using a two-arm, parallel-group, single-blind randomised controlled trial, with the comparator arm receiving delayed access to active treatment (crossover). Eligible participants worked clinically in a UK NHS ICU during the pandemic and had at least 3 IMs of work-related traumatic events in the week before recruitment. Participants were randomly assigned (1:1) to immediate (weeks 1–4) or delayed (weeks 5–8) intervention access. Sequential Bayesian analyses to optimise the intervention and increase trial efficiency are reported elsewhere [1]. The primary endpoint for the pre-specified frequentist analysis of the final study population compared the number of IMs experienced in week 4 between the immediate and delayed access arms. Secondary outcomes included clinical symptoms, work functioning and wellbeing. Safety was assessed throughout the trial by scheduled questions and free report. All analyses were undertaken on an intention-to-treat basis (86 randomised participants). There were significantly fewer intrusive memories during week 4 in the immediate (median = 1, IQR = 0–3, n = 43), compared to the comparator delayed arm (median = 10, IQR = 6–17, n = 43), IRR 0.31, 95% CI: 0.20–0.48, p < 0.001. After crossover, the delayed arm also showed a significant reduction in IMs at week 8 compared to week 4. There were convergent findings for symptoms of PTSD, insomnia and anxiety, work engagement and burnout, general functioning and quality of life. The intervention was found safe and acceptable to participants. All adverse events were unrelated to the study. Our study provides the first evidence of a benefit on reducing IMs, improving other clinical symptoms, work functioning and wellbeing, as well as safety of a brief remotely-delivered digital imagery-competing task intervention. An efficacy trial with an active control and longer follow-up is warranted. The trial is registered at ClinicalTrials.gov (NCT04992390).

We describe a general method for finding a confidence region for a parameter vector that is compatible with the decisions of a two-stage closed test procedure in an adaptive experiment. The closed test procedure is characterized by the fact that rejection or nonrejection of a null hypothesis may depend on the decisions for other hypotheses and the compatible confidence region will, in general, have a complex, nonrectangular shape. We find the smallest cross-product of simultaneous confidence intervals containing the region and provide computational shortcuts for calculating the lower bounds on parameters corresponding to the rejected null hypotheses. We illustrate the method with an adaptive phase II/III clinical trial.

Among hospitalized patients with Covid-19, treatment with dexamethasone resulted in lower 28-day mortality than usual care, according to the level of respiratory support the patients were receiving, indicating a possible correlation between efficacy and the stage of infection.

Investigators in China report the results of an open-label, randomized clinical trial of lopinavir–ritonavir for the treatment of Covid-19 in 199 infected adult patients. The primary end point was the time to clinical improvement.

No specific antiviral drug has been proven effective for treatment of patients with severe coronavirus disease 2019 (COVID-19). Remdesivir (GS-5734), a nucleoside analogue prodrug, has inhibitory effects on pathogenic animal and human coronaviruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in vitro, and inhibits Middle East respiratory syndrome coronavirus, SARS-CoV-1, and SARS-CoV-2 replication in animal models. We did a randomised, double-blind, placebo-controlled, multicentre trial at ten hospitals in Hubei, China. Eligible patients were adults (aged ≥18 years) admitted to hospital with laboratory-confirmed SARS-CoV-2 infection, with an interval from symptom onset to enrolment of 12 days or less, oxygen saturation of 94% or less on room air or a ratio of arterial oxygen partial pressure to fractional inspired oxygen of 300 mm Hg or less, and radiologically confirmed pneumonia. Patients were randomly assigned in a 2:1 ratio to intravenous remdesivir (200 mg on day 1 followed by 100 mg on days 2–10 in single daily infusions) or the same volume of placebo infusions for 10 days. Patients were permitted concomitant use of lopinavir–ritonavir, interferons, and corticosteroids. The primary endpoint was time to clinical improvement up to day 28, defined as the time (in days) from randomisation to the point of a decline of two levels on a six-point ordinal scale of clinical status (from 1=discharged to 6=death) or discharged alive from hospital, whichever came first. Primary analysis was done in the intention-to-treat (ITT) population and safety analysis was done in all patients who started their assigned treatment. This trial is registered with ClinicalTrials.gov, NCT04257656. Between Feb 6, 2020, and March 12, 2020, 237 patients were enrolled and randomly assigned to a treatment group (158 to remdesivir and 79 to placebo); one patient in the placebo group who withdrew after randomisation was not included in the ITT population. Remdesivir use was not associated with a difference in time to clinical improvement (hazard ratio 1·23 [95% CI 0·87–1·75]). Although not statistically significant, patients receiving remdesivir had a numerically faster time to clinical improvement than those receiving placebo among patients with symptom duration of 10 days or less (hazard ratio 1·52 [0·95–2·43]). Adverse events were reported in 102 (66%) of 155 remdesivir recipients versus 50 (64%) of 78 placebo recipients. Remdesivir was stopped early because of adverse events in 18 (12%) patients versus four (5%) patients who stopped placebo early. In this study of adult patients admitted to hospital for severe COVID-19, remdesivir was not associated with statistically significant clinical benefits. However, the numerical reduction in time to clinical improvement in those treated earlier requires confirmation in larger studies. Chinese Academy of Medical Sciences Emergency Project of COVID-19, National Key Research and Development Program of China, the Beijing Science and Technology Project.

Among 4716 hospitalized adult patients with Covid-19 in the United Kingdom, those who were treated with hydroxychloroquine did not have a lower incidence of death at 28 days than those who received usual care.

Adaptive designs for clinical trials permit alterations to a study in response to accumulating data in order to make trials more flexible, ethical, and efficient. These benefits are achieved while preserving the integrity and validity of the trial, through the pre-specification and proper adjustment for the possible alterations during the course of the trial. Despite much research in the statistical literature highlighting the potential advantages of adaptive designs over traditional fixed designs, the uptake of such methods in clinical research has been slow. One major reason for this is that different adaptations to trial designs, as well as their advantages and limitations, remain unfamiliar to large parts of the clinical community. The aim of this paper is to clarify where adaptive designs can be used to address specific questions of scientific interest; we introduce the main features of adaptive designs and commonly used terminology, highlighting their utility and pitfalls, and illustrate their use through case studies of adaptive trials ranging from early-phase dose escalation to confirmatory phase III studies.

AbstractAdaptive designs (ADs) allow pre-planned changes to an ongoing trial without compromising the validity of conclusions and it is essential to distinguish pre-planned from unplanned changes that may also occur. The reporting of ADs in randomised trials is inconsistent and needs improving. Incompletely reported AD randomised trials are difficult to reproduce and are hard to interpret and synthesise. This consequently hampers their ability to inform practice as well as future research and contributes to research waste. Better transparency and adequate reporting will enable the potential benefits of ADs to be realised.This extension to the Consolidated Standards Of Reporting Trials (CONSORT) 2010 statement was developed to enhance the reporting of randomised AD clinical trials. We developed an Adaptive designs CONSORT Extension (ACE) guideline through a two-stage Delphi process with input from multidisciplinary key stakeholders in clinical trials research in the public and private sectors from 21 countries, followed by a consensus meeting. Members of the CONSORT Group were involved during the development process.The paper presents the ACE checklists for AD randomised trial reports and abstracts, as well as an explanation with examples to aid the application of the guideline. The ACE checklist comprises seven new items, nine modified items, six unchanged items for which additional explanatory text clarifies further considerations for ADs, and 20 unchanged items not requiring further explanatory text. The ACE abstract checklist has one new item, one modified item, one unchanged item with additional explanatory text for ADs, and 15 unchanged items not requiring further explanatory text.The intention is to enhance transparency and improve reporting of AD randomised trials to improve the interpretability of their results and reproducibility of their methods, results and inference. We also hope indirectly to facilitate the much-needed knowledge transfer of innovative trial designs to maximise their potential benefits.

The antiviral drug molnupiravir was licensed for treating at-risk patients with COVID-19 on the basis of data from unvaccinated adults. We aimed to evaluate the safety and virological efficacy of molnupiravir in vaccinated and unvaccinated individuals with COVID-19. This randomised, placebo-controlled, double-blind, phase 2 trial (AGILE CST-2) was done at five National Institute for Health and Care Research sites in the UK. Eligible participants were adult (aged ≥18 years) outpatients with PCR-confirmed, mild-to-moderate SARS-CoV-2 infection who were within 5 days of symptom onset. Using permuted blocks (block size 2 or 4) and stratifying by site, participants were randomly assigned (1:1) to receive either molnupiravir (orally; 800 mg twice daily for 5 days) plus standard of care or matching placebo plus standard of care. The primary outcome was the time from randomisation to SARS-CoV-2 PCR negativity on nasopharyngeal swabs and was analysed by use of a Bayesian Cox proportional hazards model for estimating the probability of a superior virological response (hazard ratio [HR]>1) for molnupiravir versus placebo. Our primary model used a two-point prior based on equal prior probabilities (50%) that the HR was 1·0 or 1·5. We defined a priori that if the probability of a HR of more than 1 was more than 80% molnupiravir would be recommended for further testing. The primary outcome was analysed in the intention-to-treat population and safety was analysed in the safety population, comprising participants who had received at least one dose of allocated treatment. This trial is registered in ClinicalTrials.gov, NCT04746183, and the ISRCTN registry, ISRCTN27106947, and is ongoing. Between Nov 18, 2020, and March 16, 2022, 1723 patients were assessed for eligibility, of whom 180 were randomly assigned to receive either molnupiravir (n=90) or placebo (n=90) and were included in the intention-to-treat analysis. 103 (57%) of 180 participants were female and 77 (43%) were male and 90 (50%) participants had received at least one dose of a COVID-19 vaccine. SARS-CoV-2 infections with the delta (B.1.617.2; 72 [40%] of 180), alpha (B.1.1.7; 37 [21%]), omicron (B.1.1.529; 38 [21%]), and EU1 (B.1.177; 28 [16%]) variants were represented. All 180 participants received at least one dose of treatment and four participants discontinued the study (one in the molnupiravir group and three in the placebo group). Participants in the molnupiravir group had a faster median time from randomisation to negative PCR (8 days [95% CI 8–9]) than participants in the placebo group (11 days [10–11]; HR 1·30, 95% credible interval 0·92–1·71; log-rank p=0·074). The probability of molnupiravir being superior to placebo (HR>1) was 75·4%, which was less than our threshold of 80%. 73 (81%) of 90 participants in the molnupiravir group and 68 (76%) of 90 participants in the placebo group had at least one adverse event by day 29. One participant in the molnupiravir group and three participants in the placebo group had an adverse event of a Common Terminology Criteria for Adverse Events grade 3 or higher severity. No participants died (due to any cause) during the trial. We found molnupiravir to be well tolerated and, although our predefined threshold was not reached, we observed some evidence that molnupiravir has antiviral activity in vaccinated and unvaccinated individuals infected with a broad range of SARS-CoV-2 variants, although this evidence is not conclusive. Ridgeback Biotherapeutics, the UK National Institute for Health and Care Research, the Medical Research Council, and the Wellcome Trust.