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The tolerability of oral iron supplementation for the treatment of iron deficiency anemia is disputed. Our aim was to quantify the odds of GI side-effects in adults related to current gold standard oral iron therapy, namely ferrous sulfate. Systematic review and meta-analysis of randomized controlled trials (RCTs) evaluating GI side-effects that included ferrous sulfate and a comparator that was either placebo or intravenous (i.v.) iron. Random effects meta-analysis modelling was undertaken and study heterogeneity was summarised using I2 statistics. Forty three trials comprising 6831 adult participants were included. Twenty trials (n = 3168) had a placebo arm and twenty three trials (n = 3663) had an active comparator arm of i.v. iron. Ferrous sulfate supplementation significantly increased risk of GI side-effects versus placebo with an odds ratio (OR) of 2.32 [95% CI 1.74-3.08, p<0.0001, I2 = 53.6%] and versus i.v. iron with an OR of 3.05 [95% CI 2.07-4.48, p<0.0001, I2 = 41.6%]. Subgroup analysis in IBD patients showed a similar effect versus i.v. iron (OR = 3.14, 95% CI 1.34-7.36, p = 0.008, I2 = 0%). Likewise, subgroup analysis of pooled data from 7 RCTs in pregnant women (n = 1028) showed a statistically significant increased risk of GI side-effects for ferrous sulfate although there was marked heterogeneity in the data (OR = 3.33, 95% CI 1.19-9.28, p = 0.02, I2 = 66.1%). Meta-regression did not provide significant evidence of an association between the study OR and the iron dose. Our meta-analysis confirms that ferrous sulfate is associated with a significant increase in gastrointestinal-specific side-effects but does not find a relationship with dose.

Adaptive designs can make clinical trials more flexible by utilising results accumulating in the trial to modify the trial’s course in accordance with pre-specified rules. Trials with an adaptive design are often more efficient, informative and ethical than trials with a traditional fixed design since they often make better use of resources such as time and money, and might require fewer participants. Adaptive designs can be applied across all phases of clinical research, from early-phase dose escalation to confirmatory trials. The pace of the uptake of adaptive designs in clinical research, however, has remained well behind that of the statistical literature introducing new methods and highlighting their potential advantages. We speculate that one factor contributing to this is that the full range of adaptations available to trial designs, as well as their goals, advantages and limitations, remains unfamiliar to many parts of the clinical community. Additionally, the term adaptive design has been misleadingly used as an all-encompassing label to refer to certain methods that could be deemed controversial or that have been inadequately implemented. We believe that even if the planning and analysis of a trial is undertaken by an expert statistician, it is essential that the investigators understand the implications of using an adaptive design, for example, what the practical challenges are, what can (and cannot) be inferred from the results of such a trial, and how to report and communicate the results. This tutorial paper provides guidance on key aspects of adaptive designs that are relevant to clinical triallists. We explain the basic rationale behind adaptive designs, clarify ambiguous terminology and summarise the utility and pitfalls of adaptive designs. We discuss practical aspects around funding, ethical approval, treatment supply and communication with stakeholders and trial participants. Our focus, however, is on the interpretation and reporting of results from adaptive design trials, which we consider vital for anyone involved in medical research. We emphasise the general principles of transparency and reproducibility and suggest how best to put them into practice.

Evidence exist that primary care referral to an open-group behavioural programme is an effective strategy for management of obesity, but little evidence on optimal intervention duration is available. We aimed to establish whether 52-week referral to an open-group weight-management programme would achieve greater weight loss and improvements in a range of health outcomes and be more cost-effective than the current practice of 12-week referrals. In this non-blinded, parallel-group, randomised controlled trial, we recruited participants who were aged 18 years or older and had body-mass index (BMI) of 28 kg/m2 or higher from 23 primary care practices in England. Participants were randomly assigned (2:5:5) to brief advice and self-help materials, a weight-management programme (Weight Watchers) for 12 weeks, or the same weight-management programme for 52 weeks. We followed-up participants over 2 years. The primary outcome was weight at 1 year of follow-up, analysed with mixed-effects models according to intention-to-treat principles and adjusted for centre and baseline weight. In a hierarchical closed-testing procedure, we compared combined behavioural programme arms with brief intervention, then compared the 12-week programme and 52-week programme. We did a within-trial cost-effectiveness analysis using person-level data and modelled outcomes over a 25-year time horizon using microsimulation. This study is registered with Current Controlled Trials, number ISRCTN82857232. Between Oct 18, 2012, and Feb 10, 2014, we enrolled 1269 participants. 1267 eligible participants were randomly assigned to the brief intervention (n=211), the 12-week programme (n=528), and the 52-week programme (n=528). Two participants in the 12-week programme had been found to be ineligible shortly after randomisation and were excluded from the analysis. 823 (65%) of 1267 participants completed an assessment at 1 year and 856 (68%) participants at 2 years. All eligible participants were included in the analyses. At 1 year, mean weight changes in the groups were −3·26 kg (brief intervention), −4·75 kg (12-week programme), and −6·76 kg (52-week programme). Participants in the behavioural programme lost more weight than those in the brief intervention (adjusted difference −2·71 kg, 95% CI −3·86 to −1·55; p<0·0001). The 52-week programme was more effective than the 12-week programme (−2·14 kg, −3·05 to −1·22; p<0·0001). Differences between groups were still significant at 2 years. No adverse events related to the intervention were reported. Over 2 years, the incremental cost-effectiveness ratio (ICER; compared with brief intervention) was £159 per kg lost for the 52-week programme and £91 per kg for the 12-week programme. Modelled over 25 years after baseline, the ICER for the 12-week programme was dominant compared with the brief intervention. The ICER for the 52-week programme was cost-effective compared with the brief intervention (£2394 per quality-adjusted life-year [QALY]) and the 12-week programme (£3804 per QALY). For adults with overweight or obesity, referral to this open-group behavioural weight-loss programme for at least 12 weeks is more effective than brief advice and self-help materials. A 52-week programme produces greater weight loss and other clinical benefits than a 12-week programme and, although it costs more, modelling suggests that the 52-week programme is cost-effective in the longer term. National Prevention Research Initiative, Weight Watchers International (as part of an UK Medical Research Council Industrial Collaboration Award).

Background For many disease areas, there are often treatments in different stages of the development process. We consider the design of a two-arm parallel group trial where it is planned to add a new experimental treatment arm during the trial. This could potentially save money, patients, time and resources; however, the addition of a treatment arm creates a multiple comparison problem. Current practice in trials when a new treatment arm has been added is to compare the new treatment only to controls randomised concurrently, and this is the setting we consider here. Furthermore, for standard multi-arm trials, optimal allocation randomises a larger number of patients to the control arm than to each experimental treatment arm. Methods In this paper we propose an adaptive design, the aim of which is to adapt the sample size of the trial when the new treatment arm is added to control the family-wise error rate (FWER) in the strong sense, whilst maintaining the marginal power of each treatment-to-control comparison at the level of the original study. We explore optimal allocation for designs where a treatment arm is added with the aim of increasing the overall power of the study, where we define the overall power to be the probability of detecting all treatments that are better than the control. Results and conclusions An increase in sample size is required to maintain the marginal power for each pairwise comparison when adding a treatment arm if control of the FWER is required at the level of the type I error in the original study. When control of the FWER is required in a single trial which adds an additional experimental treatment arm, but control of the FWER is not required in separate trials, depending on the design characteristics, it may be better to run a separate trial for each experimental treatment, in terms of the number of patients required. An increase in overall power can be achieved when optimal allocation is used once a treatment arm has been added to the trial, rather than continuing with equal allocation to all treatment arms.

Introduction The continual reassessment method (CRM) is a model-based design for phase I trials, which aims to find the maximum tolerated dose (MTD) of a new therapy. The CRM has been shown to be more accurate in targeting the MTD than traditional rule-based approaches such as the 3 + 3 design, which is used in most phase I trials. Furthermore, the CRM has been shown to assign more trial participants at or close to the MTD than the 3 + 3 design. However, the CRM’s uptake in clinical research has been incredibly slow, putting trial participants, drug development and patients at risk. Barriers to increasing the use of the CRM have been identified, most notably a lack of knowledge amongst clinicians and statisticians on how to apply new designs in practice. No recent tutorial, guidelines, or recommendations for clinicians on conducting dose-finding studies using the CRM are available. Furthermore, practical resources to support clinicians considering the CRM for their trials are scarce. Methods To help overcome these barriers, we present a structured framework for designing a dose-finding study using the CRM. We give recommendations for key design parameters and advise on conducting pre-trial simulation work to tailor the design to a specific trial. We provide practical tools to support clinicians and statisticians, including software recommendations, and template text and tables that can be edited and inserted into a trial protocol. We also give guidance on how to conduct and report dose-finding studies using the CRM. Results An initial set of design recommendations are provided to kick-start the design process. To complement these and the additional resources, we describe two published dose-finding trials that used the CRM. We discuss their designs, how they were conducted and analysed, and compare them to what would have happened under a 3 + 3 design. Conclusions The framework and resources we provide are aimed at clinicians and statisticians new to the CRM design. Provision of key resources in this contemporary guidance paper will hopefully improve the uptake of the CRM in phase I dose-finding trials.

Interleukin-2 (IL-2) has an essential role in the expansion and function of CD4+ regulatory T cells (Tregs). Tregs reduce tissue damage by limiting the immune response following infection and regulate autoreactive CD4+ effector T cells (Teffs) to prevent autoimmune diseases, such as type 1 diabetes (T1D). Genetic susceptibility to T1D causes alterations in the IL-2 pathway, a finding that supports Tregs as a cellular therapeutic target. Aldesleukin (Proleukin; recombinant human IL-2), which is administered at high doses to activate the immune system in cancer immunotherapy, is now being repositioned to treat inflammatory and autoimmune disorders at lower doses by targeting Tregs. To define the aldesleukin dose response for Tregs and to find doses that increase Tregs physiologically for treatment of T1D, a statistical and systematic approach was taken by analysing the pharmacokinetics and pharmacodynamics of single doses of subcutaneous aldesleukin in the Adaptive Study of IL-2 Dose on Regulatory T Cells in Type 1 Diabetes (DILT1D), a single centre, non-randomised, open label, adaptive dose-finding trial with 40 adult participants with recently diagnosed T1D. The primary endpoint was the maximum percentage increase in Tregs (defined as CD3+CD4+CD25highCD127low) from the baseline frequency in each participant measured over the 7 d following treatment. There was an initial learning phase with five pairs of participants, each pair receiving one of five pre-assigned single doses from 0.04 × 106 to 1.5 × 106 IU/m2, in order to model the dose-response curve. Results from each participant were then incorporated into interim statistical modelling to target the two doses most likely to induce 10% and 20% increases in Treg frequencies. Primary analysis of the evaluable population (n = 39) found that the optimal doses of aldesleukin to induce 10% and 20% increases in Tregs were 0.101 × 106 IU/m2 (standard error [SE] = 0.078, 95% CI = -0.052, 0.254) and 0.497 × 106 IU/m2 (SE = 0.092, 95% CI = 0.316, 0.678), respectively. On analysis of secondary outcomes, using a highly sensitive IL-2 assay, the observed plasma concentrations of the drug at 90 min exceeded the hypothetical Treg-specific therapeutic window determined in vitro (0.015-0.24 IU/ml), even at the lowest doses (0.040 × 106 and 0.045 × 106 IU/m2) administered. A rapid decrease in Treg frequency in the circulation was observed at 90 min and at day 1, which was dose dependent (mean decrease 11.6%, SE = 2.3%, range 10.0%-48.2%, n = 37), rebounding at day 2 and increasing to frequencies above baseline over 7 d. Teffs, natural killer cells, and eosinophils also responded, with their frequencies rapidly and dose-dependently decreased in the blood, then returning to, or exceeding, pretreatment levels. Furthermore, there was a dose-dependent down modulation of one of the two signalling subunits of the IL-2 receptor, the β chain (CD122) (mean decrease = 58.0%, SE = 2.8%, range 9.8%-85.5%, n = 33), on Tregs and a reduction in their sensitivity to aldesleukin at 90 min and day 1 and 2 post-treatment. Due to blood volume requirements as well as ethical and practical considerations, the study was limited to adults and to analysis of peripheral blood only. The DILT1D trial results, most notably the early altered trafficking and desensitisation of Tregs induced by a single ultra-low dose of aldesleukin that resolves within 2-3 d, inform the design of the next trial to determine a repeat dosing regimen aimed at establishing a steady-state Treg frequency increase of 20%-50%, with the eventual goal of preventing T1D. ISRCTN Registry ISRCTN27852285; ClinicalTrials.gov NCT01827735.

The increasing prevalence of overweight and obesity needs effective approaches for weight loss in primary care and community settings. We compared weight loss with standard treatment in primary care with that achieved after referral by the primary care team to a commercial provider in the community. In this parallel group, non-blinded, randomised controlled trial, 772 overweight and obese adults were recruited by primary care practices in Australia, Germany, and the UK. Participants were randomly assigned with a computer-generated simple randomisation sequence to receive either 12 months of standard care as defined by national treatment guidelines, or 12 months of free membership to a commercial programme (Weight Watchers), and followed up for 12 months. The primary outcome was weight change over 12 months. Analysis was by intention to treat (last observation carried forward [LOCF] and baseline observation carried forward [BOCF]) and in the population who completed the 12-month assessment. This trial is registered, number ISRCTN85485463. 377 participants were assigned to the commercial programme, of whom 230 (61%) completed the 12-month assessment; and 395 were assigned to standard care, of whom 214 (54%) completed the 12-month assessment. In all analyses, participants in the commercial programme group lost twice as much weight as did those in the standard care group. Mean weight change at 12 months was −5·06 kg (SE 0·31) for those in the commercial programme versus −2·25 kg (0·21) for those receiving standard care (adjusted difference −2·77 kg, 95% CI −3·50 to −2·03) with LOCF; −4·06 kg (0·31) versus −1·77 kg (0·19; adjusted difference −2·29 kg, −2·99 to −1·58) with BOCF; and −6·65 kg (0·43) versus −3·26 kg (0·33; adjusted difference −3·16 kg, −4·23 to −2·11) for those who completed the 12-month assessment. Participants reported no adverse events related to trial participation. Referral by a primary health-care professional to a commercial weight loss programme that provides regular weighing, advice about diet and physical activity, motivation, and group support can offer a clinically useful early intervention for weight management in overweight and obese people that can be delivered at large scale. Weight Watchers International, through a grant to the UK Medical Research Council.

Background Adequate reporting of adaptive designs (ADs) maximises their potential benefits in the conduct of clinical trials. Transparent reporting can help address some obstacles and concerns relating to the use of ADs. Currently, there are deficiencies in the reporting of AD trials. To overcome this, we have developed a consensus-driven extension to the CONSORT statement for randomised trials using an AD. This paper describes the processes and methods used to develop this extension rather than detailed explanation of the guideline. Methods We developed the guideline in seven overlapping stages: Building on prior research to inform the need for a guideline; A scoping literature review to inform future stages; Drafting the first checklist version involving an External Expert Panel; A two-round Delphi process involving international, multidisciplinary, and cross-sector key stakeholders; A consensus meeting to advise which reporting items to retain through voting, and to discuss the structure of what to include in the supporting explanation and elaboration (E&E) document; Refining and finalising the checklist; and Writing-up and dissemination of the E&E document. The CONSORT Executive Group oversaw the entire development process. Results Delphi survey response rates were 94/143 (66%), 114/156 (73%), and 79/143 (55%) in rounds 1, 2, and across both rounds, respectively. Twenty-seven delegates from Europe, the USA, and Asia attended the consensus meeting. The main checklist has seven new and nine modified items and six unchanged items with expanded E&E text to clarify further considerations for ADs. The abstract checklist has one new and one modified item together with an unchanged item with expanded E&E text. The E&E document will describe the scope of the guideline, the definition of an AD, and some types of ADs and trial adaptations and explain each reporting item in detail including case studies. Conclusions We hope that making the development processes, methods, and all supporting information that aided decision-making transparent will enhance the acceptability and quick uptake of the guideline. This will also help other groups when developing similar CONSORT extensions. The guideline is applicable to all randomised trials with an AD and contains minimum reporting requirements.

Background Gehan’s two-stage design was historically the design of choice for phase II oncology trials. One of the reasons it is less frequently used today is that it does not allow for a formal test of treatment efficacy, and therefore does not control conventional type-I and type-II error-rates. Methods We describe how recently developed methodology for flexible two-stage single-arm trials can be used to incorporate the hypothesis test commonly associated with phase II trials in to Gehan’s design. We additionally detail how this hypothesis test can be optimised in order to maximise its power, and describe how the second stage sample sizes can be chosen to more readily provide the operating characteristics that were originally envisioned by Gehan. Finally, we contrast our modified Gehan designs to Simon’s designs, based on two examples motivated by real clinical trials. Results Gehan’s original designs are often greatly under- or over-powered when compared to type-II error-rates typically used in phase II. However, we demonstrate that the control parameters of his design can be chosen to resolve this problem. With this, though, the modified Gehan designs have operating characteristics similar to the more familiar Simon designs. Conclusions The trial design settings in which Gehan’s design will be preferable over Simon’s designs are likely limited. Provided the second stage sample sizes are chosen carefully, however, one scenario of potential utility is when the trial’s primary goal is to ascertain the treatment response rate to a certain precision.

In phase I cancer clinical trials, the maximum tolerated dose of a new drug is often found by a dose-escalation method known as the A + B design. We have developed an interactive web application, AplusB, which computes and returns exact operating characteristics of A + B trial designs. The application has a graphical user interface (GUI), requires no programming knowledge and is free to access and use on any device that can open an internet browser. A customised report is available for download for each design that contains tabulated operating characteristics and informative plots, which can then be compared with other dose-escalation methods. We present a step-by-step guide on how to use this application and provide several illustrative examples of its capabilities.