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Randomised controlled trials (RCTs) inform healthcare decisions. It is now apparent that some published RCTs contain false data and some appear to have been entirely fabricated. Systematic reviews are performed to identify and synthesise all RCTs that have been conducted on a given topic. While it is usual to assess methodological features of the RCTs in the process of undertaking a systematic review, it is not usual to consider whether the RCTs contain false data. Studies containing false data therefore go unnoticed and contribute to systematic review conclusions. The INveStigating ProblEmatic Clinical Trials in Systematic Reviews (INSPECT-SR) project will develop a tool to assess the trustworthiness of RCTs in systematic reviews of healthcare-related interventions.
The INSPECT-SR tool will be developed using expert consensus in combination with empirical evidence, over five stages: (1) a survey of experts to assemble a comprehensive list of checks for detecting problematic RCTs, (2) an evaluation of the feasibility and impact of applying the checks to systematic reviews, (3) a Delphi survey to determine which of the checks are supported by expert consensus, culminating in, (4) a consensus meeting to select checks to be included in a draft tool and to determine its format and (5) prospective testing of the draft tool in the production of new health systematic reviews, to allow refinement based on user feedback. We anticipate that the INSPECT-SR tool will help researchers to identify problematic studies and will help patients by protecting them from the influence of false data on their healthcare.
The University of Manchester ethics decision tool was used, and this returned the result that ethical approval was not required for this project (30 September 2022), which incorporates secondary research and surveys of professionals about subjects relating to their expertise. Informed consent will be obtained from all survey participants. All results will be published as open-access articles. The final tool will be made freely available.
Longitudinal studies can provide timely and accurate information to evaluate and inform COVID-19 control and mitigation strategies and future pandemic preparedness. The Optimise Study is a multidisciplinary research platform established in the Australian state of Victoria in September 2020 to collect epidemiological, social, psychological and behavioural data from priority populations. It aims to understand changing public attitudes, behaviours and experiences of COVID-19 and inform epidemic modelling and support responsive government policy.
This protocol paper describes the data collection procedures for the Optimise Study, an ongoing longitudinal cohort of ~1000 Victorian adults and their social networks. Participants are recruited using snowball sampling with a set of seeds and two waves of snowball recruitment. Seeds are purposively selected from priority groups, including recent COVID-19 cases and close contacts and people at heightened risk of infection and/or adverse outcomes of COVID-19 infection and/or public health measures. Participants complete a schedule of monthly quantitative surveys and daily diaries for up to 24 months, plus additional surveys annually for up to 48 months. Cohort participants are recruited for qualitative interviews at key time points to enable in-depth exploration of people’s lived experiences. Separately, community representatives are invited to participate in community engagement groups, which review and interpret research findings to inform policy and practice recommendations.
The Optimise longitudinal cohort and qualitative interviews are approved by the Alfred Hospital Human Research Ethics Committee (# 333/20). The Optimise Study CEG is approved by the La Trobe University Human Ethics Committee (# HEC20532). All participants provide informed verbal consent to enter the cohort, with additional consent provided prior to any of the sub studies. Study findings will be disseminated through public website (https://optimisecovid.com.au/study-findings/) and through peer-reviewed publications.
Implementation of enhanced recovery pathways (ERPs) has resulted in improved patient-centred outcomes and decreased costs. However, there is a lack of high-level evidence for many ERP elements. We have designed a randomised, embedded, multifactorial, adaptive platform perioperative medicine (REMAP Periop) trial to evaluate the effectiveness of several perioperative therapies for patients undergoing complex abdominal surgery as part of an ERP. This trial will begin with two domains: postoperative nausea/vomiting (PONV) prophylaxis and regional/neuraxial analgesia. Patients enrolled in the trial will be randomised to arms within both domains, with the possibility of adding additional domains in the future.
In the PONV domain, patients are randomised to optimal versus supraoptimal prophylactic regimens. In the regional/neuraxial domain, patients are randomised to one of five different single-injection techniques/combination of techniques. The primary study endpoint is hospital-free days at 30 days, with additional domain-specific secondary endpoints of PONV incidence and postoperative opioid consumption. The efficacy of an intervention arm within a given domain will be evaluated at regular interim analyses using Bayesian statistical analysis. At the beginning of the trial, participants will have an equal probability of being allocated to any given intervention within a domain (ie, simple 1:1 randomisation), with response adaptive randomisation guiding changes to allocation ratios after interim analyses when applicable based on prespecified statistical triggers. Triggers met at interim analysis may also result in intervention dropping.
The core protocol and domain-specific appendices were approved by the University of Pittsburgh Institutional Review Board. A waiver of informed consent was obtained for this trial. Trial results will be announced to the public and healthcare providers once prespecified statistical triggers of interest are reached as described in the core protocol, and the most favourable interventions will then be implemented as a standardised institutional protocol.
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