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IntroductionEarly phase dose-finding (EPDF) studies are critical for the development of new treatments, directly influencing whether compounds or interventions can be investigated in further trials to confirm their safety and efficacy. There exists guidance for clinical trial protocols and reporting of completed trials in the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) 2013 and CONsolidated Standards Of Reporting Randomised Trials (CONSORT) 2010 statements. However, neither the original statements nor their extensions adequately cover the specific features of EPDF trials. The DEFINE (DosE-FIndiNg Extensions) study aims to enhance transparency, completeness, reproducibility and interpretation of EPDF trial protocols (SPIRIT-DEFINE) and their reports once completed (CONSORT-DEFINE), across all disease areas, building on the original SPIRIT 2013 and CONSORT 2010 statements.Methods and analysisA methodological review of published EPDF trials will be conducted to identify features and deficiencies in reporting and inform the initial generation of the candidate items. The early draft checklists will be enriched through a review of published and grey literature, real-world examples analysis, citation and reference searches and consultation with international experts, including regulators and journal editors. Development of CONSORT-DEFINE commenced in March 2021, followed by SPIRIT-DEFINE from January 2022. A modified Delphi process, involving worldwide, multidisciplinary and cross-sector key stakeholders, will be run to refine the checklists. An international consensus meeting in autumn 2022 will finalise the list of items to be included in both guidance extensions.Ethics and disseminationThis project was approved by ICR’s Committee for Clinical Research. The Health Research Authority confirmed Research Ethics Approval is not required. The dissemination strategy aims to maximise guideline awareness and uptake, including but not limited to dissemination in stakeholder meetings, conferences, peer-reviewed publications and on the EQUATOR Network and DEFINE study websites.Registration detailsSPIRIT-DEFINE and CONSORT-DEFINE are registered with the EQUATOR Network.

Summary Randomised controlled trials are considered the gold standard in trial design. However, phase II oncology trials with a binary outcome are often single-arm. Although a number of reasons exist for choosing a single-arm trial, the primary reason is that single-arm designs require fewer participants than their randomised equivalents. Therefore, the development of novel methodology that makes randomised designs more efficient is of value to the trials community. This article introduces a randomised two-arm binary outcome trial design that includes stochastic curtailment (SC), allowing for the possibility of stopping a trial before the final conclusions are known with certainty. In addition to SC, the proposed design involves the use of a randomised block design, which allows investigators to control the number of interim analyses. This approach is compared with existing designs that also use early stopping, through the use of a loss function comprised of a weighted sum of design characteristics. Comparisons are also made using an example from a real trial. The comparisons show that for many possible loss functions, the proposed design is superior to existing designs. Further, the proposed design may be more practical, by allowing a flexible number of interim analyses. One existing design produces superior design realisations when the anticipated response rate is low. However, when using this design, the probability of rejecting the null hypothesis is sensitive to misspecification of the null response rate. Therefore, when considering randomised designs in phase II, we recommend the proposed approach be preferred over other sequential designs.

• Introduction: Type 1 diabetes (T1D) is a chronic autoimmune disease, characterised by progressive destruction of the insulin-producing β cells of the pancreas. One immunosuppressive agent that has recently shown promise in the treatment of new-onset T1D subjects aged 12-45 years is ATG, Thymoglobuline®, encouraging further exploration in lower age groups. Methods and analysis: MELD-ATG is a phase 2, multi-centre, randomised, double-blind, placebo-controlled, multi-arm parallel-group trial in participants 5-25 years diagnosed with T1D within 3–9 weeks of planned treatment day 1. A total of 114 participants will be recruited sequentially into seven different cohorts with the first cohort of 30 participants being randomised to placebo, 2.5 mg/kg, 1.5 mg/kg, 0.5 mg/kg and 0.1 mg/kg ATG total dose in a 1:1:1:1:1 allocation ratio. The next six cohorts of 12-15 participants will be randomised to placebo, 2.5 mg/kg, and one or two selected middle ATG total doses in a 1:1:1:1 or 1:1:1 allocation ratio, as dependent on the number of middle doses, given intravenously over 2 consecutive days. The primary objective will be to determine the changes in stimulated C-peptide response over the first 2 hours of a mixed meal tolerance test (MMTT) at 12 months for 2.5mg/kg ATG arm versus the placebo. Conditional on finding a significant difference at 2.5 mg/kg, a minimally effective dose will be sought. Secondary objectives include the determination of the effects of a particular ATG treatment dose on 1) stimulated C-peptide, 2) HbA1c, 3) daily insulin dose, 4) time in range by intermittent continuous glucose monitoring (CGM) measures, 5) fasting and stimulated dry blood spot (DBS) C-peptide measurements. Ethics and dissemination: MELD-ATG received first regulatory and ethical approvals in Belgium in September 2020 and from the German and UK regulators as of February 2021. The publication policy is set in the INNODIA grant agreement (www.innodia.eu)., Union’s Horizon 2020 research and innovation program EFPIA JDRF The Leona M. and Harry B. Helmsley Charitable Trust

Funder: National Institute of Health Research (NIHR) Cambridge Biomedical Research Centre, A standard two-arm randomised controlled trial usually compares an intervention to a control treatment with equal numbers of patients randomised to each treatment arm and only data from within the current trial are used to assess the treatment effect. Historical data are used when designing new trials and have recently been considered for use in the analysis when the required number of patients under a standard trial design cannot be achieved. Incorporating historical control data could lead to more efficient trials, reducing the number of controls required in the current study when the historical and current control data agree. However, when the data are inconsistent, there is potential for biased treatment effect estimates, inflated type I error and reduced power. We introduce two novel approaches for binary data which discount historical data based on the agreement with the current trial controls, an equivalence approach and an approach based on tail area probabilities. An adaptive design is used where the allocation ratio is adapted at the interim analysis, randomising fewer patients to control when there is agreement. The historical data are down-weighted in the analysis using the power prior approach with a fixed power. We compare operating characteristics of the proposed design to historical data methods in the literature: the modified power prior; commensurate prior; and robust mixture prior. The equivalence probability weight approach is intuitive and the operating characteristics can be calculated exactly. Furthermore, the equivalence bounds can be chosen to control the maximum possible inflation in type I error.

Bioequivalence (BE) studies are most often conducted as crossover trials, and therefore establishing their required sample size necessitates specification of the within-person variance. Given that this specification is often difficult in practice, there has been great interest in recent years in the use of adaptive designs for BE trials. However, while numerous methods for this have now been presented, their focus has been solely on two-treatment BE studies. In some instances, it will be desired to incorporate more than a single test and reference formulation into a BE trial. It would therefore be useful to establish methodology for the design of adaptive multi-treatment BE trials, to acquire the benefits in the two-treatment setting in this more complex situation. Here, we achieve this for three-treatment studies by extending previously proposed designs for two-treatment trials. First, we discuss the additional design considerations that arise when multiple comparisons are made. Next, an extensive simulation study is employed to compare the performance of the proposed procedures. With this, we demonstrate that two-stage designs with desirable statistical operating characteristics can be readily identified for three-treatment BE trials. Supplementary materials for this article are available online.

Numerous publications have now addressed the principles of designing, analyzing, and reporting the results of stepped-wedge cluster randomized trials. In contrast, there is little research available pertaining to the design and analysis of multiarm stepped-wedge cluster randomized trials, utilized to evaluate the effectiveness of multiple experimental interventions. In this paper, we address this by explaining how the required sample size in these multiarm trials can be ascertained when data are to be analyzed using a linear mixed model. We then go on to describe how the design of such trials can be optimized to balance between minimizing the cost of the trial and minimizing some function of the covariance matrix of the treatment effect estimates. Using a recently commenced trial that will evaluate the effectiveness of sensor monitoring in an occupational therapy rehabilitation program for older persons after hip fracture as an example, we demonstrate that our designs could reduce the number of observations required for a fixed power level by up to 58%. Consequently, when logistical constraints permit the utilization of any one of a range of possible multiarm stepped-wedge cluster randomized trial designs, researchers should consider employing our approach to optimize their trials efficiency.

We describe and compare two methods for the group sequential design of two-arm experiments with Poisson distributed data, which are based on a normal approximation and exact calculations respectively. A framework to determine near-optimal stopping boundaries is also presented. Using this framework, for a considered example, we demonstrate that a group sequential design could reduce the expected sample size under the null hypothesis by as much as 44% compared to a fixed sample approach. We conclude with a discussion of the advantages and disadvantages of the two presented procedures.

Funder: NIHR Cambridge Biomedical Research Centre, Funder: Engineering and Physical Sciences Research Council; doi: http://dx.doi.org/10.13039/501100000266, 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.

Background Crossover designs are commonly utilised in randomised controlled trials investigating treatments for long-term chronic illnesses. One problem with this design is its inherent repeated measures necessitate the availability of an estimate of the within-person standard deviation (SD) to perform a sample size calculation, which may be rarely available at the design stage of a trial. Interim sample size re-estimation designs can be used to help alleviate this issue by adapting the sample size mid-way through the trial, using accrued information in a statistically robust way. Methods The AIM HY-INFORM study is part of the Informative Markers in Hypertension (AIM HY) Programme and comprises two crossover trials, each with a planned recruitment of 600 participants. The objective of the study is to test whether blood pressure response to first line antihypertensive treatment depends on ethnicity. An interim analysis is planned to reassess the assumptions of the planned sample size for the study. The aims of this paper are: (1) to provide a formula for sample size re-estimation in both crossover trials; and (2) to present a simulation study of the planned interim analysis to investigate alternative within-person SDs to that assumed. Results The AIM HY-INFORM protocol sample size calculation fixes the within-person SD to be 8 mmHg, giving > 90% power for a primary treatment effect of 4 mmHg. Using the method developed here and simulating the interim sample size reassessment, if we were to see a larger within-person SD of 9 mmHg at interim, 640 participants for 90% power 90% of the time in the three-period three-treatment design would be required. Similarly, in the four-period four-treatment crossover design, 602 participants would be required. Conclusions The formulas presented here provide a method for re-estimating the sample size in crossover trials. In the context of the AIM HY-INFORM study, simulating the interim analysis allows us to explore the results of a possible increase in the within-person SD from that assumed. Simulations show that without increasing the planned sample size of 600 participants, we can reasonably still expect to achieve 80% power with a small increase in the within-person SD from that assumed. Trial registration ClinicalTrials.gov, NCT02847338. Registered on 28 July 2016.

Historically, phase II oncology trials assessed a treatment’s efficacy by examining its tumor response rate in a single-arm trial. Then, approximately 25 years ago, certain statistical and pharmacological considerations ignited a debate around whether randomized designs should be used instead. Here, based on an extensive literature review, we review the arguments on either side of this debate. In particular, we describe the numerous factors that relate to the reliance of single-arm trials on historical control data and detail the trial scenarios in which there was general agreement on preferential utilization of single-arm or randomized design frameworks, such as the use of single-arm designs when investigating treatments for rare cancers. We then summarize the latest figures on phase II oncology trial design, contrasting current design choices against historical recommendations on best practice. Ultimately, we find several ways in which the design of recently completed phase II trials does not appear to align with said recommendations. For example, despite advice to the contrary, only 66.2% of the assessed trials that employed progression-free survival as a primary or coprimary outcome used a randomized comparative design. In addition, we identify that just 28.2% of the considered randomized comparative trials came to a positive conclusion as opposed to 72.7% of the single-arm trials. We conclude by describing a selection of important issues influencing contemporary design, framing this discourse in light of current trends in phase II, such as the increased use of biomarkers and recent interest in novel adaptive designs.

Background/aims: Dose-escalation studies are essential in the early stages of developing novel treatments, when the aim is to find a safe dose for administration in humans. Despite their great importance, many dose-escalation studies use study designs based on heuristic algorithms with well-documented drawbacks. Bayesian decision procedures provide a design alternative that is conceptually simple and methodologically sound, but very rarely used in practice, at least in part due to their perceived statistical complexity. There are currently very few easily accessible software implementations that would facilitate their application. Methods: We have created MoDEsT, a free and easy-to-use web application for designing and conducting single-agent dose-escalation studies with a binary toxicity endpoint, where the objective is to estimate the maximum tolerated dose. MoDEsT uses a well-established Bayesian decision procedure based on logistic regression. The software has a user-friendly point-and-click interface, makes changes visible in real time, and automatically generates a range of graphs, tables, and reports. It is aimed at clinicians as well as statisticians with limited expertise in model-based dose-escalation designs, and does not require any statistical programming skills to evaluate the operating characteristics of, or implement, the Bayesian dose-escalation design. Results: MoDEsT comes in two parts: a ‘Design’ module to explore design options and simulate their operating characteristics, and a ‘Conduct’ module to guide the dose-finding process throughout the study. We illustrate the practical use of both modules with data from a real phase I study in terminal cancer. Conclusion: Enabling both methodologists and clinicians to understand and apply model-based study designs with ease is a key factor towards their routine use in early-phase studies. We hope that MoDEsT will enable incorporation of Bayesian decision procedures for dose escalation at the earliest stage of clinical trial design, thus increasing their use in early-phase trials.

The determination of the sample size required by a crossover trial typically depends on the specification of one or more variance components. Uncertainty about the value of these parameters at the design stage means that there is often a risk a trial may be under‐ or overpowered. For many study designs, this problem has been addressed by considering adaptive design methodology that allows for the re‐estimation of the required sample size during a trial. Here, we propose and compare several approaches for this in multitreatment crossover trials. Specifically, regulators favor reestimation procedures to maintain the blinding of the treatment allocations. We therefore develop blinded estimators for the within and between person variances, following simple or block randomization. We demonstrate that, provided an equal number of patients are allocated to sequences that are balanced for period, the proposed estimators following block randomization are unbiased. We further provide a formula for the bias of the estimators following simple randomization. The performance of these procedures, along with that of an unblinded approach, is then examined utilizing three motivating examples, including one based on a recently completed four‐treatment four‐period crossover trial. Simulation results show that the performance of the proposed blinded procedures is in many cases similar to that of the unblinded approach, and thus they are an attractive alternative.

Crossover designs are an extremely useful tool to investigators, and group sequential methods have proven highly proficient at improving the efficiency of parallel group trials. Yet, group sequential methods and crossover designs have rarely been paired together. One possible explanation for this could be the absence of a formal proof of how to strongly control the familywise error rate in the case when multiple comparisons will be made. Here, we provide this proof, valid for any number of initial experimental treatments and any number of stages, when results are analyzed using a linear mixed model. We then establish formulae for the expected sample size and expected number of observations of such a trial, given any choice of stopping boundaries. Finally, utilizing the four-treatment, four-period TOMADO trial as an example, we demonstrate that group sequential methods in this setting could have reduced the trials expected number of observations under the global null hypothesis by over 33%.

Rationale The doubly labelled water (DLW) method is the reference method for the estimation of free-living total energy expenditure (TEE). In this method, where both 2H and 18O are employed, different approaches have been adopted to deal with the non-conformity observed regarding the distribution space for the labels being non-coincident with total body water. However, the method adopted can have a significant effect on the estimated TEE. Methods We proposed a Bayesian reasoning approach to modify an assumed prior distribution for the space ratio using experimental data to derive the TEE. A Bayesian hierarchical approach was also investigated. The dataset was obtained from 59 adults (37 women) who underwent a DLW experiment during which the 2H and 18O enrichments were measured using isotope ratio mass spectrometry (IRMS). Results The TEE was estimated at 9925 (9106-11236) [median and interquartile range], 9646 (9167-10540), and 9,638 (9220-10340) kJ·day-1 for women and at 13961 (12851-15347), 13353 (12651-15088) and 13211 (12653-14238) kJ·day-1 for men, using normalized non-Bayesian, independent Bayesian and hierarchical Bayesian approaches, respectively. A comparison of hierarchical Bayesian with normalized non-Bayesian methods indicated a marked difference in behaviour between genders. The median difference was -287 kJ·day-1 for women, and -750 kJ·day-1 for men. In men there is an appreciable compression of the TEE distribution obtained from the hierarchical model compared with the normalized non-Bayesian methods (range of TEE 11234 – 15431 kJ·day-1 vs 10786 – 18221 kJ·day-1). An analogous, yet smaller, compression is seen in women (7081 – 12287 kJ·day-1 vs 6989 – 13775 kJ·day-1). Conclusions The Bayesian analysis is an appealing method to estimate TEE during DLW experiments. The principal advantages over those obtained using the classical least-squares method is the generation of potentially more useful estimates of total energy expenditure, and improved handling of outliers and missing data scenarios, particularly if a hierarchical model is used.

Introduction Most literature on optimal group-sequential designs focuses on minimising the expected sample size. We highlight other factors for consideration. Methods We discuss several quantities less-often considered in adaptive design: the median and standard deviation of the random required sample size, and the probability of committing an interim error. We consider how the optimal timing of interim analyses changes when these quantities are accounted for. Results Incorporating the standard deviation of the required sample size into an optimality framework, we demonstrate how and when this quantity means using a group-sequential approach is not optimal. The optimal timing of an interim analysis is shown to be highly dependent on the pre-specified preference for minimising the expected sample size relative to its standard deviation. Conclusions Examining multiple factors, which measure the advantages and disadvantages of group-sequential designs, helps determine the best design for a specific trial.

Background:ATRiUM is a phase 1 trial to assess the safety, tolerability, pharmacokinetics and preliminary antitumour activity of ascending doses of combined therapy with the ATR inhibitor ceralasertib AZD6738 and gemcitabine, Using a Model based design NCT03669601. The combination was shown to act synergistically in laboratory models of pancreatic cancer. Based on these data, ATRiUM is now open to recruitment in Cambridge and Glasgow, UK. Methods:ATRiUM utilises a novel Bayesian model-based design for dual-agent dose escalation, that handles three levels of toxicity the highest of which is a dose limiting toxicity and two dosing schedules. The model assumes that the toxicity levels come from a multinomial distribution and toxicity increases monotonically as doses increase. Different schedules and doses 40-120 mg of ceralasertib; intermittent days 1-4, 8-11, 15-18 and continuous days 1-21 with gemcitabine 625-1000 mg/m2 administered on days 3, 10 and 17 of a 28-day cycle, will be assessed using the Bayesian framework. The aim is to recruit up to 55 patients, including up to 40 in the dose escalation phase across 3 gemcitabine doses and 6 ceralasertib dose/schedules. An expansion cohort (10-15 patients) is planned in patients with pancreatic cancer, based on our pre-clinical findings. Tumour monitoring will be undertaken by CT imaging RECIST 1.1, liquid biopsies circulating free DNA and advanced imaging radiomics. Baseline tissue biopsies will be analysed to identify potential predictive biomarkers e.g. ATM loss, as described pre-clinically. Imaging MSI will be used to characterise the intra-tumoural distribution of gemcitabine, its metabolites and ceralasertib and compared to plasma PK. Detailed studies of sequential tumour biopsies will include immunohistochemistry, RNAseq and Imaging Mass Cytometry IMC and be used to evaluate early pharmacodynamic responses to the combination. To investigate whether the combination increases tumour immunogenicity, the immune effects of the combination will be evaluated in both tumour by IMC and RNAseq and peripherally, by the serial collection and analysis of PBMCs and plasma for cytokine analysis. Adults with solid tumours are eligible for the dose escalation, if fulfilling standard Phase I eligibility criteria with measurable tumour lesions amenable to biopsy. Two out of six planned cohorts have been completed with no DLTs identified and cohort 3 will open in January 2021. ATRiUM is supported by the Integrative Cancer Medicine theme of the CRUK Cambridge Centre, the NIHR Cambridge Biomedical Centre, the Cambridge ECMC and a grant from AstraZeneca. Citation Format: Bruno Henrique de Paula, Bristi Basu, Adrian Mander, Josephine Khan, Purity Bundi, Richard Goodwin, James Thaventhiran, Gonzalez-Lopes Alberto, Godfrey Edmund, Sabita Islam, Subha Anand, Jeff Evans, Vincenzo Graziano, Eva Serrao, Maria Pawula, Tatiana Hernandez, Emma Dean, Simon Smith, Duncan Jodrell. ATRiUM: A first-in-human dose escalation phase I trial of ceralasertib (AZD6738) and gemcitabine as combination therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr CT214.

Phase I trials of anti-cancer therapies aim to identify a maximum tolerated dose (MTD), defined as the dose that causes unacceptable toxicity in a target proportion of patients. Both rule-based and model-based methods have been proposed for MTD recommendation. The escalation with overdose control (EWOC) approach is a model-based design where the dose assigned to the next patient is one that, given all available data, has a posterior probability of exceeding the MTD equal to a pre-specified value known as the feasibility bound. The aim is to conservatively dose-escalate and approach the MTD, avoiding severe overdosing early on in a trial. The EWOC approach has been applied in practice with the feasibility bound either fixed or varying throughout a trial, yet some of the methods may recommend incoherent dose-escalation, that is, an increase in dose after observing severe toxicity at the current dose. We present examples where varying feasibility bounds have been used in practice, and propose a toxicity-dependent feasibility bound approach that guarantees coherent dose-escalation and incorporates the desirable features of other EWOC approaches. We show via detailed simulation studies that the toxicity-dependent feasibility bound approach provides improved MTD recommendation properties to the original EWOC approach for both discrete and continuous doses across most dose-toxicity scenarios, with comparable performance to other approaches without recommending incoherent dose escalation. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Background: The development of a nurse-led approach to managing epilepsy in adults with an intellectual disability offers the potential of improved outcomes and lower costs of care. We undertook a cluster randomised trial to assess the impact on costs and outcomes of the provision of intellectual disability nurses working to a designated epilepsy nurse competency framework. Here, we report the impact of the intervention on costs. Method: Across the UK, 8 sites randomly allocated to the intervention recruited 184 participants, 9 sites allocated to treatment as usual recruited 128 participants. Cost and outcome data were collected mainly by telephone interview at baseline and after six months. Total costs at six months were compared from the perspective of health & social services, and society, with adjustments for pre-specified participant and cluster characteristics at baseline including costs. Missing data was imputed using Multiple Imputation. Uncertainty was quantified by bootstrapping. Results: The intervention was associated with lower per participant costs from a health & social services perspective of -£357 (2014/15 GBP) (95% CI -£986, £294) and from a societal perspective of -£631 (95% CI -£1,473, £181). Results were not sensitive to the exclusion of accommodation costs. Conclusions: Our findings suggest that the competency framework is unlikely to increase the cost of caring for people with epilepsy and intellectual disability and may reduce costs., This paper presents independent research commissioned by the National Institute for Health Research (NIHR) under its Health Technology Assessment Programme (Grant 10/104/16 PI Dr H Ring). During the time that this research was carried out, H Ring also received support from the NIHR Collaboration for Leadership in Applied Health Research and Care (CLAHRC) East of England at Cambridgeshire and Peterborough NHS Foundation Trust.

Introduction Poor adherence to photoprotection for people with xeroderma pigmentosum (XP) can be life-threatening. A randomised controlled trial (RCT) is being conducted to test the efficacy of a personalised adherence intervention (XPAND) to reduce the level of ultraviolet radiation (UVR) reaching the face, by improving photoprotection activities in adults with XP.Methods and analysis A two-armed parallel groups RCT, where we randomised 24 patients with suboptimal adherence to either an intervention group who received XPAND in 2018 or a delayed intervention group who will receive XPAND in 2019. XPAND involves seven sessions, one-to-one with a facilitator, using behaviour change techniques and specially designed materials to target barriers to photoprotection. Following baseline assessment in April 2018 (t0) and intervention, the primary outcome will be measured across 21 consecutive days in June and July 2018 (t1). The primary outcome is the average daily UVR dose to the face (D-to-F), calculated by combining objective UVR exposure at the wrist (measured by a dosimeter) with face photoprotection activities recorded on a daily UVR protection diary. Secondary outcomes include average daily UVR D-to-F across 21 days in August (t2); psychosocial process variables measured by daily questions (t0, t1, t2) and self-report questionnaires (t0, t1, t2, December 2018 (t3)). Intervention cost-utility is assessed by service use and personal cost questionnaires (t0, t3). The delayed intervention control arm participants will complete three further assessments in April 2019 (t4) and June–July 2019 (t5), and December 2019 (t6) with dosimetry and UVR protection diary completed for 21 days at t4 and t5. A process evaluation will be conducted using mixed methods.Ethics and dissemination Ethical approval has been received from West London & GTAC REC 17/LO/2110. Results will be disseminated in peer-reviewed journals and at conferences. This study tests a novel intervention, which, if successful, will be integrated into routine care.Trial registration number NCT03445052; Pre-results.

Background\ud \ud 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.\ud \ud \ud Methods\ud \ud We developed the guideline in seven overlapping stages:1)\ud \ud Building on prior research to inform the need for a guideline;\ud \ud \ud \ud 2)\ud \ud A scoping literature review to inform future stages;\ud \ud \ud \ud 3)\ud \ud Drafting the first checklist version involving an External Expert Panel;\ud \ud \ud \ud 4)\ud \ud A two-round Delphi process involving international, multidisciplinary, and cross-sector key stakeholders;\ud \ud \ud \ud 5)\ud \ud 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;\ud \ud \ud \ud 6)\ud \ud Refining and finalising the checklist; and\ud \ud \ud \ud 7)\ud \ud Writing-up and dissemination of the E&E document.\ud \ud \ud \ud \ud The CONSORT Executive Group oversaw the entire development process.\ud \ud \ud Results\ud \ud 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.\ud \ud \ud Conclusions\ud \ud 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. Type 1 diabetes (T1D) results from loss of immune regulation, leading to the development of autoimmunity to pancreatic β cells, involving autoreactive T effector cells (Teffs). Tregs, which prevent autoimmunity, require IL-2 for maintenance of immunosuppressive functions. Using a response-adaptive design, we aimed to determine the optimal regimen of aldesleukin (recombinant human IL-2) to physiologically enhance Tregs while limiting expansion of Teffs. METHODS. DILfrequency is a nonrandomized, open-label, response-adaptive study of participants, aged 18–70 years, with T1D. The initial learning phase allocated 12 participants to 6 different predefined regimens. Then, 3 cohorts of 8 participants were sequentially allocated dose frequencies, based on repeated interim analyses of all accumulated trial data. The coprimary endpoints were percentage change in Tregs and Teffs and CD25 (α subunit of the IL-2 receptor) expression by Tregs, from baseline to steady state. RESULTS. Thirty-eight participants were enrolled, with thirty-six completing treatment. The optimal regimen to maintain a steady-state increase in Tregs of 30% and CD25 expression of 25% without Teff expansion is 0.26 × 106 IU/m2 (95% CI –0.007 to 0.485) every 3 days. Tregs and CD25 were dose-frequency responsive, Teffs were not. The commonest adverse event was injection site reaction (464 of 694 events). CONCLUSIONS. Using a response-adaptive design, aldesleukin treatment can be optimized. Our methodology can generally be employed to immediately access proof of mechanism, thereby leading to more efficient and safe drug development. TRIAL REGISTRATION. International Standard Randomised Controlled Trial Number Register, ISRCTN40319192; ClinicalTrials.gov, {"type":"clinical-trial","attrs":{"text":"NCT02265809","term_id":"NCT02265809"}}NCT02265809. FUNDING. Sir Jules Thorn Trust, the Swiss National Science Foundation, Wellcome, JDRF, and NIHR Cambridge Biomedical Research Centre.

Potential predictive biomarkers are often measured on a continuous scale, but in practice, a threshold value to divide the patient population into biomarker 'positive' and 'negative' is desirable. Early phase clinical trials are increasingly using biomarkers for patient selection, but at this stage, it is likely that little will be known about the relationship between the biomarker and the treatment outcome. We describe a single-arm trial design with adaptive enrichment, which can increase power to demonstrate efficacy within a patient subpopulation, the parameters of which are also estimated. Our design enables us to learn about the biomarker and optimally adjust the threshold during the study, using a combination of generalised linear modelling and Bayesian prediction. At the final analysis, a binomial exact test is carried out, allowing the hypothesis that 'no population subset exists in which the novel treatment has a desirable response rate' to be tested. Through extensive simulations, we are able to show increased power over fixed threshold methods in many situations without increasing the type-I error rate. We also show that estimates of the threshold, which defines the population subset, are unbiased and often more precise than those from fixed threshold studies. We provide an example of the method applied (retrospectively) to publically available data from a study of the use of tamoxifen after mastectomy by the German Breast Study Group, where progesterone receptor is the biomarker of interest. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Cognitive impairment is increasingly recognised as an important potential adverse effect of medication. However, many drug development programmes do not incorporate sensitive cognitive measurements. Here, we review the rationale for cognitive safety assessment, and explain several basic methodological principles for measuring cognition during clinical drug development, including study design and statistical analysis, from Phase I through to postmarketing. The crucial issue of how cognition should be assessed is emphasized, especially the sensitivity of measurement. We also consider how best to interpret the magnitude of any identified effects, including comparison with benchmarks. We conclude by discussing strategies for the effective communication of cognitive risks.

Adaptive 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. In order to encourage its wide dissemination this article is freely accessible on the BMJ and Trials journal websites.“To maximise the benefit to society, you need to not just do research but do it well” Douglas G Altman

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. Electronic supplementary material The online version of this article (10.1186/s12874-019-0659-2) contains supplementary material, which is available to authorized users.

In a group sequential clinical trial, accumulated data are analyzed at numerous time points to allow early decisions about a hypothesis of interest. These designs have historically been recommended for their ethical, administrative, and economic benefits. In this article, we first discuss a collection of new commands for computing the stopping boundaries and required group size of various classical group sequential designs, assuming a normally distributed outcome variable. Then, we demonstrate how the performance of several designs can be compared graphically.

Longitudinal studies are often used to investigate age-related developmental change. Whereas a single cohort design takes a group of individuals at the same initial age and follows them over time, an accelerated longitudinal design takes multiple single cohorts, each one starting at a different age. The main advantage of an accelerated longitudinal design is its ability to span the age range of interest in a shorter period of time than would be possible with a single cohort longitudinal design. This paper considers design issues for accelerated longitudinal studies. A linear mixed effect model is considered to describe the responses over age with random effects for intercept and slope parameters. Random and fixed cohort effects are used to cope with the potential bias accelerated longitudinal designs have due to multiple cohorts. The impact of other factors such as costs and the impact of dropouts on the power of testing or the precision of estimating parameters are examined. As duration-related costs increase relative to recruitment costs the best designs shift towards shorter duration and eventually cross-sectional design being best. For designs with the same duration but differing interval between measurements, we found there was a cutoff point for measurement costs relative to recruitment costs relating to frequency of measurements. Under our model of 30% dropout there was a maximum power loss of 7%., This work was supported by the Medical Research Council (G0800860)

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.

Background/Aims: The stepped-wedge cluster randomised trial design has received substantial attention in recent years. Although various extensions to the original design have been proposed, no guidance is available on the design of stepped-wedge cluster randomised trials with interim analyses. In an individually randomised trial setting, group sequential methods can provide notable efficiency gains and ethical benefits. We address this by discussing how established group sequential methodology can be adapted for stepped-wedge designs. Methods: Utilising the error spending approach to group sequential trial design, we detail the assumptions required for the determination of stepped-wedge cluster randomised trials with interim analyses. We consider early stopping for efficacy, futility, or efficacy and futility. We describe first how this can be done for any specified linear mixed model for data analysis. We then focus on one particular commonly utilised model and, using a recently completed stepped-wedge cluster randomised trial, compare the performance of several designs with interim analyses to the classical stepped-wedge design. Finally, the performance of a quantile substitution procedure for dealing with the case of unknown variance is explored. Results: We demonstrate that the incorporation of early stopping in stepped-wedge cluster randomised trial designs could reduce the expected sample size under the null and alternative hypotheses by up to 31% and 22%, respectively, with no cost to the trial’s type-I and type-II error rates. The use of restricted error maximum likelihood estimation was found to be more important than quantile substitution for controlling the type-I error rate. Conclusion: The addition of interim analyses into stepped-wedge cluster randomised trials could help guard against time-consuming trials conducted on poor performing treatments and also help expedite the implementation of efficacious treatments. In future, trialists should consider incorporating early stopping of some kind into stepped-wedge cluster randomised trials according to the needs of the particular trial.

In this article, we present a set of commands and Mata functions to evaluate different distributional quantities of the multivariate normal distribution and a particular type of noncentral multivariate t distribution. Specifically, their densities, distribution functions, equicoordinate quantiles, and pseudo–random vectors can be computed efficiently, in either the absence or the presence of variable truncation.

SummaryBackgroundType 1 diabetes (T1D) results from loss of immune regulation leading to the development of autoimmunity to pancreatic beta-cells, involving autoreactive T effector cells (Teffs). Regulatory T cells (Tregs), that prevent autoimmunity, require Interleukin-2 (IL-2) for maintenance of immunosuppressive functions and, alterations in the IL-2 pathway predispose to T1D. Using an adaptive trial design we aimed to determine the optimal regimen of aldesleukin (recombinant human IL-2) to physiologically enhance Tregs while limiting expansion of autoreactive Teffs.MethodsDILfrequency is a single-center, non-randomised, open-label, response-adaptive study of participants aged 18 to 70 years with T1D. The initial learning phase allocated 12 participants to six different predefined dose-frequency regimens. Then, three cohorts of 8 participants were sequentially allocated dose-frequencies, based on repeated interim analyses of all accumulated trial data. The co-primary endpoints were percentage change in Tregs, Teffs and, CD25 (α subunit of the IL-2 receptor) expression by Tregs, from baseline to steady state. Trial registration ISRCTN40319192 and ClinicalTrials.gov (NCT02265809).Findings115 participants were assessed between November 17th 2014 and May 22nd 2016, 38 participants were enrolled with 36 completing treatment. The optimal regimen to maintain a steady state increase in Tregs of 30% and CD25 expression of 25% without Teff expansion is 0.26 × 106 IU/m2 (95% CI (−0.007 to 0.485)) every 3 days (1.3 to 4.4). Tregs and CD25 were dose-frequency responsive, while Teffs were not. The commonest adverse event was injection site reaction (464/694 events), with a single participant developing transient eosinophilia at the highest dose (0.47 × 106 IU/m2).InterpretationThis response-adaptive trial defined a well-tolerated aldesleukin regimen that specifically induces Treg expansion that can now be trialled to treat T1D.FundingSir Jules Thorn Trust, Wellcome, JDRF, SNSF, NIHR

BACKGROUND: 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. METHODS: 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/m(2) 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. FINDINGS: 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; pINTERPRETATION: 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. FUNDING: National Prevention Research Initiative, Weight Watchers International (as part of an UK Medical Research Council Industrial Collaboration Award).

In this paper, we review the adaptive design methodology of Li et al. (Biostatistics 3:277–287) for two-stage trials with mid-trial sample size adjustment. We argue that it is closer in principle to a group sequential design, in spite of its obvious adaptive element. Several extensions are proposed that aim to make it even more attractive and transparent alternative to a standard (fixed sample size) trial for funding bodies to consider. These enable a cap to be put on the maximum sample size and for the trial data to be analysed using standard methods at its conclusion. The regulatory view of trials incorporating unblinded sample size re-estimation is also discussed. © 2014 The Authors. Pharmaceutical Statistics published by John Wiley & Sons, Ltd.

Objective In randomized controlled trials of weight loss interventions, high dropout rates are a problem resulting in a large amount of missing outcome data. It is common for participants with missing data to be excluded from analysis (complete-case analysis). The aim of this article is to demonstrate how published complete-case results can be used to explore how study results would change depending on assumptions about dropout weight loss. Methods The methods are based on three extensions to a method for obtaining baseline observation carried forward (BOCF) results from complete-case results. The first extension is a generalization to any dropout weight loss. Second, to show that it is not necessary to assume that dropout weight loss is the same in each treatment arm. Third, to show that variation in dropout weight loss can be incorporated. Using these extensions, sensitivity analyses to the missing data can be conducted via the use of plots. Results The methods are demonstrated using two examples of published results from studies of weight loss interventions. It is also shown how the BOCF method could be useful to meta-analysts. Conclusion By using simple plots, readers can explore how different assumptions about dropout weight loss affect the results of published weight loss trials.

Objective Overweight and obesity are associated with a dyslipidaemia which can be improved by weight loss. Whether genetic predisposition to an adverse lipid profile modifies such beneficial effects of weight loss on lipid levels in overweight and obese individuals was examined. Design and methods White European participants (n = 374) who completed a 12-month weight loss trial were genotyped for 36 lipid-associated single nucleotide polymorphisms (SNPs), previously identified in genome-wide association studies (GWAS). Genetic predisposition scores (GPSs) were calculated for four lipid traits by summing the number of risk alleles (RA) for each participant. The associations of each GPS with four lipid traits were assessed at baseline, and with lipid changes in response to weight change after 12 months. Results At baseline, the trait-specific GPSs were associated with 0.11 ± 0.04 mM higher total cholesterol/RA (P = 0.004), 0.05 ± 0.02 mM higher low density lipoprotein cholesterol/RA (P = 0.005), 0.03 ± 0.007 mM lower high density lipoprotein cholesterol/RA (P = 0.00002) and 0.04 ± 0.01 mM higher triglyceride/RA (P = 0.00002). After the intervention, weight loss was associated with improvements in all lipids (P < 0.01). GPS attenuated the weight loss-associated reduction in TC so those with a higher GPS had less improvement (interaction = 0.01 ± 0.005 mM/GPS/kg weight loss, P = 0.003). A similar pattern was observed for LDLC (interaction = 0.004 ± 0.002 mM/GPS/kg weight loss, P = 0.07). There was no evidence of a GPS-modifying effect for change in HDLC or TG. Conclusion Genetic predisposition is an important determinant of lipid levels and appears to limit the improvement in TC and to some extent LDLC levels, but not in other plasma lipids, in response to weight loss. © 2013 American Institute of Chemical Engineers AIChE J, 2013 Copyright © 2013 The Obesity Society.

(2010). Acute effects of hyperglycaemia on asymmetric dimethylarginine (ADMA), adiponectin and inflammatory markers (IL-6, hs-CRP) in overweight and obese women with metabolic syndrome. British Journal of Biomedical Science: Vol. 67, No. 4, pp. 216-218.

Consumption of oily fish is sporadic, whereas controlled intervention studies of n-3 (ω-3) fatty acids usually provide capsules containing eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) as a daily dose. This methodologic study explored whether there are differences in the short-, medium-, and long-term incorporation of EPA and DHA into blood plasma and cells with the provision of identical amounts of EPA and DHA, equivalent to 2 oily fish servings per week (or 6.54 g/wk EPA and DHA), either intermittently (i.e., 1 portion twice per week) or continuously (i.e., divided into daily amounts). The study was part of a randomized, double-blind controlled intervention lasting 12 mo, with participants stratified by age and sex. There were 5 intervention groups, 2 of which are reported here: the 2 intermittent portions (2I) and 2 continuous portions (2C) groups. EPA and DHA were measured in plasma phosphatidylcholine, platelets, and blood mononuclear cells (MNCs) at 9 time points. Sixty-five participants completed the study (2I group, n = 30, mean age of 49.2 y; 2C group, n = 35, mean age of 50.6 y). The incorporation pattern over the 12-mo intervention was different between the 2 groups in all samples (P < 0.0001, time × treatment interaction). At the end of the 12-mo intervention, the 2C group had higher EPA, DHA, and EPA + DHA in platelets (all P < 0.01) and higher EPA and EPA + DHA in MNCs (both P < 0.05) compared with the 2I group. No significant differences were shown for plasma phosphatidylcholine EPA (P = 0.1), DHA (P = 0.15), EPA + DHA (P = 0.07), or MNC DHA (P = 0.06). In conclusion, the pattern of consumption does affect the incorporation of EPA and DHA into cells used as biomarkers of intake. The differences identified here need to be considered in the design of studies and when extrapolating results from continuous capsule-based intervention studies to dietary guidelines for oily fish consumption. This trial was registered at www.controlled-trials.com as ISRCTN48398526.

OBJECTIVE: To analyse whether high dietary energy density (DED) is associated with increased fat mass and risk of excess adiposity in free-living children. DESIGN: Longitudinal, observational cohort study. SUBJECTS: Six hundred and eighty-two healthy children from the Avon Longitudinal Study of Parents and Children. MEASUREMENTS: Diet was assessed at age 5 and 7 years using 3-day diet diaries, and DED (kJ g(-1)) was calculated excluding drinks. Fat mass was estimated at age 9 years using Dual-Energy X-ray Absorptiometry. To adjust for body size, fat mass index (FMI) was calculated by dividing fat mass (kg) by height (m(5.8)). Excess adiposity was defined as the top quintile of logFMI. RESULTS: Mean DED at age 5 years was higher among children with excess adiposity at age 9 years compared to the remaining sample (8.8+/-0.16 vs 8.5+/-0.07 kJ g(-1)), but there was no evidence of an association with excess adiposity at age 9 years (odds ratio (OR)=1.14, 95% confidence interval (CI) 0.90-1.44) after controlling for potential confounders. Mean DED at age 7 years was higher among children with excess adiposity compared to the remaining sample (9.1+/-0.12 vs 8.8+/-0.06 kJ g(-1)) and a 1 kJ g(-1) rise in DED increased the odds of excess adiposity at 9 years by 36% (OR=1.36, 95% CI 1.09-1.69) after controlling for potential confounders. CONCLUSION: Higher DED at age 7 years, but not age 5 years, is a risk factor for excess adiposity at age 9 years, perhaps reflecting deterioration in the ability to compensate for extra calories in an energy-dense diet. DED tracks strongly from age 5 to 7 years suggesting intervention to alter dietary habits need to commence at younger ages to prevent the formation of preferences for energy dense foods.

Background: Estimation of the intake of oily fish at a population level is difficult. The measurement of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) in biological samples may provide a useful biomarker of intake. Objective: We identified the most appropriate biomarkers for the assessment of habitual oily fish intake and changes in intake by elucidating the dose- and time-dependent response of EPA and DHA incorporation into various biological samples that represent roles in fatty acid transport, function, and storage. Design: This was a double-blind, randomized, controlled intervention trial in 204 men and women that lasted 12 mo. EPA and DHA capsules were provided in a manner to reflect sporadic consumption of oily fish (ie, 1, 2, or 4 times/wk). EPA and DHAwere assessed at 9 time points over 12 mo in 9 sample types (red blood cells, mononuclear cells, platelets, buccal cells, adipose tissue, plasma phosphatidylcholine, triglycerides, cholesteryl esters, and nonesterified fatty acids). Results: A dose response (P , 0.05) was observed for EPA and DHA in all pools except for red blood cell EPA (P = 0.057). EPA and DHA measures in plasma phosphatidylcholine and platelets were best for the discrimination between different intakes (P , 0.0001). The rate of incorporation varied between sample types, with the time to maximal incorporation ranging from days (plasma phosphatidylcholine) to months (mononuclear cells) to .12 mo (adipose tissue). Conclusions: Plasma phosphatidylcholine EPA plus DHAwas identified as the most suitable biomarker of acute changes in EPA and DHA intake, and platelet and mononuclear cell EPA plus DHAwere the most suitable biomarkers of habitual intake. This trial was registered at Current Controlled Trials (www.controlled-trials.com) as ISRCTN48398526. Am J Clin Nutr 2012;96:748‐58.

In Phase II oncology trials, therapies are increasingly being evaluated for their effectiveness in specific populations of interest. Such targeted trials require designs that allow for stratification based on the participants' molecular characterisation. A targeted design proposed by Jones and Holmgren (JH) Jones CL, Holmgren E: 'An adaptive Simon two-stage design for phase 2 studies of targeted therapies', Contemporary Clinical Trials 28 (2007) 654-661.determines whether a drug only has activity in a disease sub-population or in the wider disease population. Their adaptive design uses results from a single interim analysis to decide whether to enrich the study population with a subgroup or not; it is based on two parallel Simon two-stage designs. We study the JH design in detail and extend it by providing a few alternative ways to control the familywise error rate, in the weak sense as well as the strong sense. We also introduce a novel optimal design by minimising the expected sample size. Our extended design contributes to the much needed framework for conducting Phase II trials in stratified medicine. © 2016 The Authors Pharmaceutical Statistics Published by John Wiley & Sons Ltd.

Background In adults with intellectual disability (ID) and epilepsy there are suggestions that improvements in management may follow introduction of epilepsy nurse-led care. However, this has not been tested in a definitive clinical trial and results cannot be generalised from general population studies as epilepsy tends to be more severe and to involve additional clinical comorbidities in adults with ID. This trial investigates whether nurses with expertise in epilepsy and ID, working proactively to a clinically defined role, can improve clinical and quality of life outcomes in the management of epilepsy within this population, compared to treatment as usual. The trial also aims to establish whether any perceived benefits represent good value for money. Methods/design The EpAID clinical trial is a two-arm cluster randomised controlled trial of nurse-led epilepsy management versus treatment as usual. This trial aims to obtain follow-up data from 320 participants with ID and drug-resistant epilepsy. Participants are randomly assigned either to a ‘treatment as usual’ control or a ‘defined epilepsy nurse role’ active arm, according to the cluster site at which they are treated. The active intervention utilises the recently developed Learning Disability Epilepsy Specialist Nurse Competency Framework for adults with ID. Participants undergo 4 weeks of baseline data collection, followed by a minimum of 20 weeks intervention (novel treatment or treatment as usual), followed by 4 weeks of follow-up data collection. The primary outcome is seizure severity, including associated injuries and the level of distress manifest by the patient in the preceding 4 weeks. Secondary outcomes include cost-utility analysis, carer strain, seizure frequency and side effects. Descriptive measures include demographic and clinical descriptors of participants and clinical services in which they receive their epilepsy management. Qualitative study of clinical interactions and semi-structured interviews with clinicians and participants’ carers are also undertaken. Discussion The EpAID clinical trial is the first cluster randomised controlled trial to test possible benefits of a nurse-led intervention in adults with epilepsy and ID. This research will have important implications for ID and epilepsy services. The challenges of undertaking such a trial in this population, and the approaches to meeting these are discussed. Trial registration International Standard Randomised Controlled Trial Number: ISRCTN96895428 version 1.1. Registered on 26 March 2013. Electronic supplementary material The online version of this article (doi:10.1186/s13063-016-1429-7) contains supplementary material, which is available to authorized users.