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Randomised evaluations of surgical interventions are rare; some interventions have been widely adopted without rigorous evaluation. Unlike other medical areas, the randomised controlled trial (RCT) design has not become the default study design for the evaluation of surgical interventions. Surgical trials are difficult to successfully undertake and pose particular practical and methodological challenges. However, RCTs have played a role in the assessment of surgical innovations and there is scope and need for greater use. This article will consider the design, conduct and analysis of an RCT of a surgical intervention. The issues will be reviewed under three headings: the timing of the evaluation, defining the research question and trial design issues. Recommendations on the conduct of future surgical RCTs are made. Collaboration between research and surgical communities is needed to address the distinct issues raised by the assessment of surgical interventions and enable the conduct of appropriate and well-designed trials.

Recently, it was argued that clinically important differences should play no role in sample size calculations. Instead, it was proposed that sample size calculations should focus on setting realistic estimates of treatment benefit. We disagree, and argue in this article that considering the importance of a target difference is necessary in the context of randomised controlled trials of effectiveness, particularly definitive phase III trials. Ignoring clinical importance could have serious ethical and practical consequences.

Two commonly performed surgical interventions are available for severe (grade II–IV) haemorrhoids; traditional excisional surgery and stapled haemorrhoidopexy. Uncertainty exists as to which is most effective. The eTHoS trial was designed to establish the clinical effectiveness and cost-effectiveness of stapled haemorrhoidopexy compared with traditional excisional surgery. The eTHoS trial was a large, open-label, multicentre, parallel-group, pragmatic randomised controlled trial done in adult participants (aged 18 years or older) referred to hospital for surgical treatment for grade II–IV haemorrhoids. Participants were randomly assigned (1:1) to receive either traditional excisional surgery or stapled haemorrhoidopexy. Randomisation was minimised according to baseline EuroQol 5 dimensions 3 level score (EQ-5D-3L), haemorrhoid grade, sex, and centre with an automated system to stapled haemorrhoidopexy or traditional excisional surgery. The primary outcome was area under the quality of life curve (AUC) measured with the EQ-5D-3L descriptive system over 24 months, assessed according to the randomised groups. The primary outcome measure was analysed using linear regression with adjustment for the minimisation variables. This trial is registered with the ISRCTN registry, number ISRCTN80061723. Between Jan 13, 2011, and Aug 1, 2014, 777 patients were randomised (389 to receive stapled haemorrhoidopexy and 388 to receive traditional excisional surgery). Stapled haemorrhoidopexy was less painful than traditional excisional surgery in the short term and surgical complication rates were similar between groups. The EQ-5D-3L AUC score was higher in the traditional excisional surgery group than the stapled haemorrhoidopexy group over 24 months; mean difference −0·073 (95% CI −0·140 to −0·006; p=0·0342). EQ-5D-3L was higher for stapled haemorrhoidopexy in the first 6 weeks after surgery, the traditional excisional surgery group had significantly better quality of life scores than the stapled haemorrhoidopexy group. 24 (7%) of 338 participants who received stapled haemorrhoidopexy and 33 (9%) of 352 participants who received traditional excisional surgery had serious adverse events. As part of a tailored management plan for haemorrhoids, traditional excisional surgery should be considered over stapled haemorrhoidopexy as the surgical treatment of choice. National Institute for Health Research Health Technology Assessment programme.

Use of patient-reported outcomes (PROs) and patient and public engagement are critical ingredients of pragmatic trials, which are intended to be patient centered. Engagement of patients and members of the public in selecting the primary trial outcome and determining the target difference can better ensure that the trial is designed to inform the decisions of those who ultimately stand to benefit. However, to the best of our knowledge, the use and reporting of PROs and patient and public engagement in pragmatic trials have not been described. The objectives of this study were to review a sample of pragmatic trials to describe (1) the prevalence of reporting patient and public engagement; (2) the prevalence and types of PROs used; (3) how its use varies across trial characteristics; and (4) how sample sizes and target differences are determined for trials with primary PROs. This was a methodological review of primary reports of pragmatic trials. We used a published electronic search filter in MEDLINE to identify pragmatic trials, published in English between January 1, 2014 and April 3, 2019; we identified the subset that were registered in ClinicalTrials.gov and explicitly labeled as pragmatic. Trial descriptors were downloaded from ClinicalTrials.gov; information about PROs and sample size calculations were extracted from the manuscript. Chi-squared, Cochran-Armitage, and Wilcoxon rank sum tests were used to examine associations between trial characteristics and use of PROs. Among 4,337 identified primary trial reports, 1,988 were registered in CT.gov, of which 415 were explicitly labeled as pragmatic. Use of patient and public engagement was identified in 39 (9.4%). PROs were measured in 235 (56.6%): 144 (34.7%) used PROs as primary outcomes and 91 (21.9%) as only secondary outcomes. Primary PROs were symptoms (64; 44%), health behaviors (36; 25.0%), quality of life (17; 11.8%), functional status (16; 11.1%), and patient experience (10; 6.9%). Trial characteristics with lower prevalence of use of PROs included being conducted exclusively in children or adults over age 65 years, cluster randomization, recruitment in low- and middle-income countries, and primary purpose of prevention; trials conducted in Europe had the highest prevalence of PROs. For the 144 trials with a primary PRO, 117 (81.3%) reported a sample size calculation for that outcome; of these, 71 (60.7%) justified the choice of target difference, most commonly, using estimates from pilot studies (31; 26.5%), standardized effect sizes (20; 17.1%), or evidence reviews (16; 13.7%); patient or stakeholder opinions were used to justify the target difference in 8 (6.8%). Limitations of this study are the need for trials to be registered in ClinicalTrials.gov, which may have reduced generalizability, and extracting information only from the primary trial report. In this study, we observed that pragmatic trials rarely report patient and public engagement and do not commonly use PROs as primary outcomes. When provided, target differences are often not justified and rarely informed by patients and stakeholders. Research funders, scientific journals, and institutions should support trialists to incorporate patient engagement to fulfill the mandate of pragmatic trials to be patient centered.

The target difference refers to the treatment effect specified in the sample size calculation conducted when designing the study to detect a difference between treatments (i.e. a superiority contrast). The main benefit of setting the target difference to the MID, if one were to do so, is that it ensures that the study has the required statistical power across a range of possible differences that are viewed as “important” to one or more stakeholder groups, assuming of course, that all the other assumptions of the sample size calculation are appropriate. Power is the proportion of these studies which would detect the effect of interest (as specified in the sample size calculation e.g. 2-sided p-value ≤ 0.05) if it really exists. Furthermore, it is often not reasonable to assume with confidence relevant nuisance parameters which have a bearing on the estimation of the treatment effect (e.g. the correlation between multiple baseline factors and the outcome of interest) [6]. [...]the stated power is often in practice an educated approximation (aside from considerations of the specification of the target difference).

Background Randomised controlled trials in surgery can be a challenge to design and conduct, especially when including a non-surgical comparison. As few as half of initiated surgical trials reach their recruitment target, and failure to recruit is cited as the most frequent reason for premature closure of surgical RCTs. The aim of this qualitative evidence synthesis was to identify and synthesise findings from qualitative studies exploring the challenges in the design and conduct of trials directly comparing surgical and non-surgical interventions. Methods A qualitative evidence synthesis using meta-ethnography was conducted. Six electronic bibliographic databases (Medline, Central, Cinahl, Embase and PsycInfo) were searched up to the end of February 2018. Studies that explored patients’ and health care professionals’ experiences regarding participating in RCTs with a surgical and non-surgical comparison were included. The GRADE-CERQual framework was used to assess confidence in review findings. Results In total, 3697 abstracts and 49 full texts were screened and 26 published studies reporting experiences of patients and healthcare professionals were included. The focus of the studies (24/26) was primarily related to the challenge of recruitment. Two studies explored reasons for non-compliance to treatment allocation following randomisation. Five themes related to the challenges to these types of trials were identified: (1) radical choice between treatments; (2) patients’ discomfort with randomisation: I want the best treatment for me as an individual; (3) challenge of equipoise: patients’ a priori preferences for treatment; (4) challenge of equipoise: clinicians’ a priori preferences for treatment and (5) imbalanced presentation of interventions. Conclusion The marked dichotomy between the surgical and non-surgical interventions was highlighted in this review as making recruitment to these types of trials particularly challenging. This review identified factors that increase our understanding of why patients and clinicians may find equipoise more challenging in these types of trials compared to other trial comparisons. Trialists may wish to consider exploring the balance of potential factors influencing patient and clinician preferences towards treatments before they start recruitment, to enable issues specific to a particular trial to be identified and addressed. This may enable trial teams to make more efficient considered design choices and benefit the delivery of such trials.

Background Randomised controlled trials (RCTs) need to be reported so that their results can be unambiguously and robustly interpreted. Binary outcomes yield unique challenges, as different analytical approaches may produce relative, absolute, or no treatment effects, and results may be particularly sensitive to the assumptions made about missing data. This review of recently published RCTs aimed to identify the methods used to analyse binary primary outcomes, how missing data were handled, and how the results were reported. Methods Systematic review of reports of RCTs published in January 2019 that included a binary primary outcome measure. We identified potentially eligible English language papers on PubMed, without restricting by journal or medical research area. Papers reporting the results from individually randomised, parallel-group RCTs were included. Results Two hundred reports of RCTs were included in this review. We found that 64% of the 200 reports used a chi-squared-style test as their primary analytical method. Fifty-five per cent (95% confidence interval 48% to 62%) reported at least one treatment effect measure, and 38% presented only a p value without any treatment effect measure. Missing data were not always adequately described and were most commonly handled using available case analysis (69%) in the 140 studies that reported missing data. Imputation and best/worst-case scenarios were used in 21% of studies. Twelve per cent of articles reported an appropriate sensitivity analysis for missing data. Conclusions The statistical analysis and reporting of treatment effects in reports of randomised trials with a binary primary endpoint requires substantial improvement. Only around half of the studied reports presented a treatment effect measure, hindering the understanding and dissemination of the findings. We also found that published trials often did not clearly describe missing data or sensitivity analyses for these missing data. Practice for secondary endpoints or observational studies may differ.

Introduction Despite a proliferation of statistical methodologies and developments within randomised controlled trials (RCTs) in recent decades, it is unclear which approaches are being implemented in practice. Oxford Clinical Trials Research Unit (OCTRU) is a UK Clinical Research Collaboration (UKCRC) registered Clinical Trials Unit (CTU) that has been operational since 2013 based in the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences at the University of Oxford. We performed a review of all published RCTs conducted within OCTRU, with particular emphasis on trial methodology, statistical study design and statistical analysis. Methods Studies were considered eligible if they were: RCTs conducted by OCTRU, have been completed and disseminated their primary results. Studies were ineligible if they were: a pilot or feasibility trial, a simulation study, a secondary analysis of an existing RCT, or a phase I trial. Phase II trials were considered if they were randomised. We performed double data extraction of all fields for all eligible trials. General trial information, such as primary disease area, main funding source, sample size, trial design and analysis information (e.g. number of study outcomes and analyses performed), were extracted and summarised. An analysis was defined as any time a statistical model was fit or a corresponding statistical test (e.g. χ 2 test) and/or estimation of a parameter was performed. Results Of the 142 OCTRU studies registered & funded (as of June 2023), 70 were completed and written up and 27 were eligible at the time of this review. The rest were ongoing or found to be ineligible. Included studies were published between 2014 and 2023, the majority in the last 5 years (20/27, 74% published between 2020 and 2023). All trials were multi-centre, prospectively designed and referred to both a study protocol and sample size justification (usually a power calculation) in their published results. Most included studies had elements of what could be referred to as a ‘standard’ RCT; used a parallel group design (93%), powered with superiority question (26/27, 96%), had two randomised groups (23/27, 85%) or used an equal allocation ratio (25/27, 93%). The median sample size was 451 (interquartile range: 238–836). The median total number of analyses performed was 22 (Interquartile range: 14–30) with the most analyses performed within a single trial being 69. Eighty-one per cent (22/27) of trials had a primary outcome with either binary or continuous data. Linear mixed effects, linear regression or logistic regression was used as the primary analysis model in 74% of the 27 trials. All trials that included at least one analysis (26/27) featured at least one additional analysis on the primary outcome, the most popular additional analyses were on an alternative population (for example a per-protocol population), occurring in 20/27, 74% of all trials, or a subgroup (18/27, 67%)). Conclusions This review summarises RCTs conducted by one academic UKCRC-registered CTU with a focus on the trial design and statistical analysis. We found most RCTs adopted what could be considered a ‘standard’ design, using appropriate, but not complex, analysis methods. Consideration of variation in practice across other groups, both academic and commercial, through a larger review would allow systematic exploration of methodological differences, less common study design usage, and would enable a fuller understanding of practice, outcomes, and methods used in different clinical areas and contexts.

Background High participant retention enhances the validity of clinical trials. A monetary incentive can increase retention, but it is not known if when it is provided and if it is conditional matters. We aimed to determine whether there was a difference in the number of follow-up trial questionnaires returned when a monetary (gift voucher) incentive was given to participants at recruitment (non-conditional), compared to informing participants at recruitment that the incentive would be given only once their 14-day daily diary (questionnaire) had been returned (conditional). Method A cluster randomised study within a trial embedded within the Antivirals for influenza-Like Illness, An rCt of Clinical and Cost effectiveness in primary CarE (ALIC 4 E) Trial. Matched site pairs (GP practices) were randomised using computer-generated random numbers, to either a non-conditional or conditional monetary voucher incentive (only once their 14-day daily diary (questionnaire) had been returned. Sites were matched on previous recruitment levels and practice list size. Analyses were conducted according to randomised groups irrespective of compliance with a two-sided 5% level statistical significance level. The main analysis of the primary outcome (site proportion of diaries returned) was linear regression accounting for site pair (using cluster-robust variance). Additional weighted, paired and non-parametric sensitivity analyses were conducted. Secondary outcomes were the site average number of completed pages, time to return diary, and cost related to the incentive (administration and postage). Results Of the 42 randomised sites (21 for each intervention), only 28 recruited at least one participant with only 10 practice pairs recruiting participants at both constituent sites. Raw diaries return proportions were 0.58 (127/220) and 0.73 (91/125) for non-conditional and conditional incentive groups. Regression analysis adjusted for site pair showed no significant difference in returns, − 0.09, (95% CI, − 0.29, 0.10, p  = 0.34); when weighted, there was still no clear difference: 0.15 (95% CI, − 0.02, 0.31, p  = 0.07). There was no clear statistical evidence of a difference in time taken to return questionnaires, nor the proportion of pages completed, by the intervention group in the main analyses (all p  > 0.05). The conditional incentive was approximately £23 cheaper per diary returned based upon observed data. Conclusion There was no clear evidence of a statistically significant difference in the proportion of participant-completed diaries returned between conditional or non-conditional incentive groups. The time to questionnaire return and completeness of the returned questionnaires were similar in both groups. There was substantial statistical uncertainty in the findings. Some of the sensitivity analyses suggested that a meaningful benefit of a conditional incentive of a magnitude that would be meaningful was plausible. The conditional approach costs less in cash terms.