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Background When conducting a randomised controlled trial, there exist many different methods to allocate participants, and a vast array of evidence-based opinions on which methods are the most effective at doing this, leading to differing use of these methods. There is also evidence that study characteristics affect the performance of these methods, but it is unknown whether the study design affects researchers’ decision when choosing a method. Methods We conducted a review of papers published in five journals in 2019 to assess which randomisation methods are most commonly being used, as well as identifying which aspects of study design, if any, are associated with the choice of randomisation method. Randomisation methodology use was compared with a similar review conducted in 2014. Results The most used randomisation method in this review is block stratification used in 162/330 trials. A combination of simple, randomisation, block randomisation, stratification and minimisation make up 318/330 trials, with only a small number of more novel methods being used, although this number has increased marginally since 2014. More complex methods such as stratification and minimisation seem to be used in larger multicentre studies. Conclusions Within this review, most methods used can be classified using a combination of simple, block stratification and minimisation, suggesting that there is not much if any increase in the uptake of newer more novel methods. There seems to be a noticeable polarisation of method use, with an increase in the use of simple methods, but an increase in the complexity of more complex methods, with greater numbers of variables included in the analysis, and a greater number of strata.

IntroductionThe 2017 revisions of the McDonald diagnostic criteria promoted the use of lumbar punctures (LPs) to expedite a diagnosis of multiple sclerosis.ObjectivesTo assess patients’ experiences of the multiple sclerosis diagnostic pathway.MethodsFeedback from the 113 participants of DECISIve (DiagnosE using the Central veIn SIgn) underwent quantitative and qualitative analyses. Their views were further explored in 17 participant interviews.ResultsDECISIve participants felt the overall experience of MRI scans was more positive than their LPs (Wilcoxon signed ranks test Z=-4.4, p<0.001). Information given pre-procedure was considered sufficient by 89% for LPs and 96% for MRI scans. Complications were reported by 72 (64%) for their LP and only 9 (8%) for their MRI scan. Many interviewees reported considerable anxiety before their LP, caused by sharing of negative accounts through social networks or online. Even patients who reported tolerating the LP experienced high pain intensity during the procedure, and that there are surprising gaps in the existing patient literature.ConclusionsDECISIve participants expressed a unanimous preference for MRI scans over undergoing LPs. However, for those who do require an LP, recommendations to improve patient information materials and consent paperwork will be presented.

Background A nested case-control study is an efficient design that can be embedded within an existing cohort study or randomised trial. It has a number of advantages compared to the conventional case-control design, and has the potential to answer important research questions using untapped prospectively collected data. Methods We demonstrate the utility of the matched nested case-control design by applying it to a secondary analysis of the Abnormal Doppler Enteral Prescription Trial. We investigated the role of milk feed type and changes in milk feed type in the development of necrotising enterocolitis in a group of 398 high risk growth-restricted preterm infants. Results Using matching, we were able to generate a comparable sample of controls selected from the same population as the cases. In contrast to the standard case-control design, exposure status was ascertained prior to the outcome event occurring and the comparison between the cases and matched controls could be made at the point at which the event occurred. This enabled us to reliably investigate the temporal relationship between feed type and necrotising enterocolitis. Conclusions A matched nested case-control study can be used to identify credible associations in a secondary analysis of clinical trial data where the exposure of interest was not randomised, and has several advantages over a standard case-control design. This method offers the potential to make reliable inferences in scenarios where it would be unethical or impractical to perform a randomised clinical trial.

Background Blinding is an established approach in clinical trials which aims to minimise the risk of performance and detection bias. There is little empirical evidence to guide UK clinical trials units (CTUs) about the practice of blinding statisticians. Guidelines recommend that statisticians remain blinded to allocation prior to the final analysis. As these guidelines are not based on empirical evidence, this study undertook a qualitative investigation relating to when and how statisticians should be blinded in clinical trials. Methods Data were collected through online focus groups with various stakeholders who work in the delivery and oversight of clinical trials. Recordings of the focus groups were transcribed verbatim and thematic analysis was used to analyse the transcripts. Results Thirty-seven participants from 19 CTUs participated in one of six focus groups. Four main themes were identified, namely statistical models of work, factors affecting the decision to blind statisticians, benefits of blinding/not blinding statisticians and practicalities. Factors influencing the decision to blind the statistician included available resources, study design and types of intervention and outcomes and analysis. Although blinding of the statistician is perceived as a desirable mitigation against bias, there was uncertainty about the extent to which an unblinded statistician might impart bias. Instead, in most cases, the insight that the statistician offers was deemed more important to delivery of a trial than the risk of bias they may introduce if unblinded. Blinding of statisticians was only considered achievable with the appropriate resource and staffing, which were not always available. In many cases, a standard approach to blinding was therefore considered unrealistic and impractical; hence the need for a proportionate risk assessment approach identifying possible mitigations. Conclusions There was wide variation in practice between UK CTUs regarding the blinding of trial statisticians. A risk assessment approach would enable CTUs to identify risks associated with unblinded statisticians conducting the final analysis and alternative mitigation strategies. The findings of this study will be used to design guidance and a tool to support this risk assessment process.

Background There exist many different methods of allocating participants to treatment groups during a randomised controlled trial. Although there is research that explores trial characteristics that are associated with the choice of method, there is still a lot of variety in practice not explained. This study used qualitative methods to explore more deeply the motivations behind researchers’ choice of randomisation, and which features of the method they use to evaluate the performance of these methods. Methods Data was collected from online focus groups with various stakeholders involved in the randomisation process. Focus groups were recorded and then transcribed verbatim. A thematic analysis was used to analyse the transcripts. Results Twenty-five participants from twenty clinical trials units across the UK were recruited to take part in one of four focus groups. Four main themes were identified: how randomisation methods are selected; researchers’ opinions of the different methods; which features of the method are desirable and ways to measure method features. Most researchers agree that the randomisation method should be selected based on key trial characteristics; however, for many, a unit standard is in place. Opinions of methods were varied with some participants favouring stratified blocks and others favouring minimisation. This was generally due to researchers’ perception of the effect these methods had on balance and predictability. Generally, predictability was considered more important than balance as adjustments cannot be made for it; however, most researchers felt that the importance of these two methods was dependent on the design of the study. Balance is usually evaluated by tabulating variables by treatment arm and looking for perceived imbalances, predictability was generally considered much harder to measure, partly due to differing definitions. Conclusion There is a wide variety in practice on how randomisation methods are selected and researcher’s opinions on methods. The difference in practice observed when looking at randomisation method selection can be explained by a difference in unit practice, and also by a difference in researchers prioritisation of balance and predictability. The findings of this study show a need for more guidance on randomisation method selection.

Background Hearing loss is a prevalent condition that impacts on social, mental and physical health, and has a significant economic burden. Hearing aids can improve the quality of life for those living with hearing loss; however, low and inconsistent use remains common. Within the National Health Service (NHS), follow-up care for new hearing aid users is highly variable and often lacks structure, which may contribute to low use. The FAMOUS trial investigates whether a structured care model for follow-up, combined with evidence-based behaviour change interventions, improves hearing aid use compared to usual care. Methods FAMOUS is a multi-centre, two-arm parallel-group cluster randomised controlled trial (CRCT) with integral internal pilot, economic, and process evaluations. The trial involves 36 NHS audiology services and compares two types of follow-up for new adult hearing aid users: structured care, which includes personalised action plans, early monitoring, and routine follow-up at 6 weeks post-fitting, to usual care, which includes the offer of a follow-up 6–12 weeks after fitting. Recruitment is conducted through participating services over 3 months, with pseudo-anonymised routine data collected from electronic medical records of all patients who attend. Consent and outcomes are then collected from patients at 12 weeks post-fitting. For patients who provide consent to future contact, the primary outcome (self-reported daily hearing aid use) is collected at 12 months post-fitting. Secondary outcomes (quality-of-life (QoL), hearing-related disability, and economic measures) are collected at both timepoints. Qualitative interviews with a subset of patients and hearing professionals in the intervention arm will assess the acceptability and implementation of the intervention. Statistical analyses, including mixed-effects regression modelling, will be conducted under an intention-to-treat framework. Discussion FAMOUS addresses a critical evidence gap regarding the potential benefits of follow-up care for new hearing aid users. If the intervention is successful, it can be rolled out nationally using existing facilities with limited impact on resources, identified in the economic analysis, and would improve hearing aid use and quality of life for those living with hearing loss. Trial registration Prospectively registered with the International Standard Randomised Controlled Trial Number (ISRCTN) 10589817. Date of registration: 01/09/2022.

IntroductionNicotine replacement therapy (NRT) helps pregnant women quit smoking. Usual National Health Service (NHS) cessation care in pregnancy starts only after women stop smoking and comprises behavioural support and NRT. NRT is stopped if women restart smoking. We hypothesised that NRT would have a bigger effect on cessation in pregnancy if used: (1) to reduce smoking before quitting (‘preloading’), (2) during brief smoking lapses after quitting and (3) to help those who cannot stop smoking, to reduce instead.Methods and analysisA two-arm parallel group, open-label, multicentre, assessor-blind randomised controlled trial. Participants are recruited at hospital antenatal clinics and other NHS settings throughout England and Wales or via social media advertising. Those enrolled are in antenatal care, <25 weeks’ gestation, smoke ≥5 daily cigarettes; accept referral for NHS stop smoking support and agree to set quit dates, try NRT and vape less than daily. Participants are randomised to: (1) usual care (UC) or (2) UC plus an intervention combining (1) NRT for preloading, (2) counselling to continue NRT during brief smoking lapses, and for those who cannot stop, (3) NRT to reduce smoking. The primary outcome is biochemically validated, smoking abstinence from 6 weeks after randomisation to 36 weeks gestation. Secondary outcomes include birth outcomes and cost per quality-adjusted life year. Questionnaires collect follow-up data augmented by medical record information. We anticipate quit rates of 10% and 15.9% in the control and intervention groups (OR=1.7). By recruiting 1430 participants, smoking, nicotine and pregnancy 3 should have 90% power (alpha=5%) to detect this effect. We will use the Economics of Smoking in Pregnancy model to estimate cost-effectiveness.Ethics and disseminationEthics approval was granted by the West Midlands—Coventry & Warwickshire Research Ethics Committee (REC reference: 21/WM/0172; Protocol number 21001; IRAS Project ID: 291236). Written informed consent will be obtained from all participants. Findings will be disseminated to the public, funders, relevant practice and policy representatives and other researchers.Trial registration numberISRCTN84798566.

Background In a random effects meta-analysis model, true treatment effects for each study are routinely assumed to follow a normal distribution. However, normality is a restrictive assumption and the misspecification of the random effects distribution may result in a misleading estimate of overall mean for the treatment effect, an inappropriate quantification of heterogeneity across studies and a wrongly symmetric prediction interval. Methods We focus on problems caused by an inappropriate normality assumption of the random effects distribution, and propose a novel random effects meta-analysis model where a Box-Cox transformation is applied to the observed treatment effect estimates. The proposed model aims to normalise an overall distribution of observed treatment effect estimates, which is sum of the within-study sampling distributions and the random effects distribution. When sampling distributions are approximately normal, non-normality in the overall distribution will be mainly due to the random effects distribution, especially when the between-study variation is large relative to the within-study variation. The Box-Cox transformation addresses this flexibly according to the observed departure from normality. We use a Bayesian approach for estimating parameters in the proposed model, and suggest summarising the meta-analysis results by an overall median, an interquartile range and a prediction interval. The model can be applied for any kind of variables once the treatment effect estimate is defined from the variable. Results A simulation study suggested that when the overall distribution of treatment effect estimates are skewed, the overall mean and conventional I 2 from the normal random effects model could be inappropriate summaries, and the proposed model helped reduce this issue. We illustrated the proposed model using two examples, which revealed some important differences on summary results, heterogeneity measures and prediction intervals from the normal random effects model. Conclusions The random effects meta-analysis with the Box-Cox transformation may be an important tool for examining robustness of traditional meta-analysis results against skewness on the observed treatment effect estimates. Further critical evaluation of the method is needed.

Background Existing guidelines recommend statisticians remain blinded to treatment allocation prior to the final analysis and that any interim analyses should be conducted by a separate team from the one undertaking the final analysis. However, there remains substantial variation in practice between UK Clinical Trials Units (CTUs) when it comes to blinding statisticians. Therefore, the aim of this study was to develop guidance to advise CTUs on a risk-proportionate approach to blinding statisticians within clinical trials. Methods This study employed a mixed methods approach involving three stages: (I) a quantitative study using a cohort of 200 studies (from a major UK funder published between 2016 and 2020) to assess the impact of blinding statisticians on the proportion of trials reporting a statistically significant finding for the primary outcome(s); (II) a qualitative study using focus groups to determine the perspectives of key stakeholders on the practice of blinding trial statisticians; and (III) combining the results of stages I and II, along with a stakeholder meeting, to develop guidance for UK CTUs. Results After screening abstracts, 179 trials were included for review. The results of the primary analysis showed no evidence that involvement of an unblinded trial statistician was associated with the likelihood of statistically significant findings being reported, odds ratio (OR) 1.02 (95% confidence interval (CI) 0.49 to 2.13). Six focus groups were conducted, with 37 participants. The triangulation between stages I and II resulted in developing 40 provisional statements. These were rated independently by the stakeholder group prior to the meeting. Ten statements reached agreement with no agreement on 30 statements. At the meeting, various factors were identified that could influence the decision of blinding the statistician, including timing, study design, types of intervention and practicalities. Guidance including 21 recommendations/considerations was developed alongside a Risk Assessment Tool to provide CTUs with a framework for assessing the risks associated with blinding/not blinding statisticians and for identifying appropriate mitigation strategies. Conclusions This is the first study to develop a guidance document to enhance the understanding of blinding statisticians and to provide a framework for the decision-making process. The key finding was that the decision to blind statisticians should be based on the benefits and risks associated with a particular trial.

Background In the UK, approximately 8% of live births are preterm (before 37 weeks gestation), more than 90% of whom are born between 30 and 36 weeks, forming the largest proportion of a neonatal units’ workload. Neonatologists are cautious in initiating full milk feeds for preterm infants due to fears of necrotising enterocolitis (NEC). There is now evidence to dispute this fear. Small studies have shown that feeding preterm infants full milk feeds enterally from birth could result in a shorter length of hospital stay, which is important to parents, clinicians and NHS services without increasing the risk of NEC. This trial aims to investigate whether full milk feeds initiated in the first 24 h after birth reduces the length of hospital stay in comparison to introduction of gradual milk feeding with IV fluids or parenteral nutrition. Methods FEED1 is a multi-centre, open, parallel group, randomised, controlled superiority trial of full milk feeds initiated on the day of birth versus gradual milk feeds for infants born at 30 +0 to 32 +6 (inclusive) weeks gestation. Recruitment will take place in around 40 UK neonatal units. Mothers will be randomised 1:1 to full milk feeds, starting at 60 ml/kg day, or gradual feeds, as per usual local practice. Mother’s expressed breast milk will always be the first choice of milk, though will likely be supplemented with formula or donor breast milk in the first few days. Feeding data will be collected until full milk feeds are achieved (≥ 140 ml/kg/day for 3 consecutive days). The primary outcome is length of infant hospital stay. Additional data will be collected 6 weeks post-discharge. Follow-up at 2 years (corrected gestational age) is planned. The sample size is 2088 infants to detect a between group difference in length of stay of 2 days. Accounting for multiple births, this requires 1700 women to be recruited. Primary analysis will compare the length of hospital stay between groups, adjusting for minimisation variables and accounting for multiple births. Discussion This trial will provide high-quality evidence on feeding practices for preterm infants. Full milk feeds from day of birth could result in infants being discharged sooner. Trial registration ISRCTN ISRCTN89654042 . Prospectively registered on 23 September 2019: ISRCTN is a primary registry of the WHO ICTRP network, and all items from the WHO Trial Registration dataset are included.