Effectiveness and cost-effectiveness of referral to a commercial open group behavioural weight management programme in adults with overweight and obesity: 5-year follow-up of the WRAP randomised controlled trial.

BACKGROUND: There is evidence that commercially available behavioural weight management programmes can lead to short-term weight loss and reductions in glycaemia. Here, we aimed to provide the 5-year impact and cost-effectiveness of these interventions compared with a brief intervention. METHODS: WRAP was a non-blinded, parallel-group randomised controlled trial (RCT). We recruited from primary care practices in England and randomly assigned participants to one of three interventions (brief intervention, 12-week open-group behavioural programme [WW, formerly Weight Watchers], or a 52-week open-group WW behavioural programme) in an uneven (2:5:5) allocation. Participants were followed up 5 years after randomisation using data from measurement visits at primary care practices or a research centre, review of primary care electronic medical notes, and self-report questionnaires. The primary outcome was change in weight at 5 years follow-up, assessed using analysis of covariance. We also estimated cost-effectiveness of the intervention. This study is registered at Current Controlled Trials, ISRCTN64986150. FINDINGS: Between Oct 18, 2012, and Feb 10, 2014, we recruited 1269 eligible participants (two participants were randomly assigned but not eligible and therefore excluded) and 1040 (82%) consented to be approached about additional follow-up and to have their medical notes reviewed at 5 years. The primary outcome (weight) was ascertained for 871 (69%) of 1267 eligible participants. Mean duration of follow-up was 5·1 (SD 0·3) years. Mean weight change from baseline to 5 years was -0·46 (SD 8·31) kg in the brief intervention group, -1·95 (9·55) kg in the 12-week programme group, and -2·67 (9·81) kg in the 52-week programme. The adjusted difference in weight change was -1·76 (95% CI -3·68 to 0·17) kg between the 52-week programme and the brief intervention; -0·80 (-2·13 to 0·54) kg between the 52-week and the 12-week programme; and -0·96 (-2·90 to 0·97) kg between the 12-week programme and the brief intervention. During the trial, the 12-week programme incurred the lowest cost and produced the highest quality-adjusted life-years (QALY). Simulations beyond 5 years suggested that the 52-week programme would deliver the highest QALYs at the lowest cost and would be the most cost-effective. No participants reported adverse events related to the intervention. INTERPRETATION: Although the difference in weight change between groups was not statistically significant, some weight loss was maintained at 5 years after an open-group behavioural weight management programme. Health economic modelling suggests that this could have important implications to reduce the incidence of weight-related disease and these interventions might be cost-saving. FUNDING: The UK National Institute for Health and Care Research Programme Grants for Applied Research and the Medical Research Council.

Adding flexibility to clinical trial designs: an example-based guide to the practical use of adaptive designs.

Adaptive designs for clinical trials permit alterations to a study in response to accumulating data in order to make trials more flexible, ethical, and efficient. These benefits are achieved while preserving the integrity and validity of the trial, through the pre-specification and proper adjustment for the possible alterations during the course of the trial. Despite much research in the statistical literature highlighting the potential advantages of adaptive designs over traditional fixed designs, the uptake of such methods in clinical research has been slow. One major reason for this is that different adaptations to trial designs, as well as their advantages and limitations, remain unfamiliar to large parts of the clinical community. The aim of this paper is to clarify where adaptive designs can be used to address specific questions of scientific interest; we introduce the main features of adaptive designs and commonly used terminology, highlighting their utility and pitfalls, and illustrate their use through case studies of adaptive trials ranging from early-phase dose escalation to confirmatory phase III studies.

Ganetespib in Combination with Pemetrexed-Platinum Chemotherapy in Patients with Pleural Mesothelioma (MESO-02): A Phase Ib Trial.

PURPOSE: Ganetespib, a highly potent, small-molecule Heatshock protein 90 inhibitor, has potential efficacy in malignant pleural mesothelioma (MPM) via activity on critical survival pathways and known synergies with antifolates and platinum chemotherapy. We conducted a dose-escalation study to identify the maximum tolerated dose (MTD) of ganetespib in patients with chemotherapy-naïve MPM. PATIENTS AND METHODS: MESO-02 (ClinicalTrials.gov: NCT01590160) was a nonrandomized, multicenter, phase Ib trial of 3-weekly ganetespib (100 mg/m2, 150 mg/m2, 200 mg/m2; days 1 and 15) with pemetrexed (500 mg/m2; day 1) and cisplatin (75 mg/m2; day 1) or carboplatin (area under concentration-time curve 5; day 1) in patients with MPM. Dose escalation was performed using the 3 + 3 design (cisplatin) and accelerated titration design (carboplatin). Secondary endpoints included best response, progression-free survival (PFS), and pharmacogenomic analyses. RESULTS: Of 27 patients enrolled (cisplatin, n = 16; carboplatin, n = 11), 3 experienced dose-limiting toxicities: grade 3 nausea (cisplatin, n = 1; carboplatin, n = 1) and grade 2 infusion-related reaction (carboplatin, n = 1). Ganetespib's MTD was 200 mg/m2. Partial response was observed in 14 of 27 patients (52%; 61% in 23 response-evaluable patients) and 13 of 21 (62%) with epithelioid histology. At the MTD, 10 of 18 patients (56%) had partial response, 15 of 18 (83%) had disease control, and median PFS was 6.3 months (95% CI, 5.0-10.0). One responder exhibited disease control beyond 50 months. Global loss of heterozygosity was associated with shorter time to progression (HR 1.12; 95% CI, 1.02-1.24; P = 0.018). CONCLUSIONS: Ganetespib can be combined safely with pemetrexed and platinum chemotherapy to treat patients with MPM. This class of agent should be investigated in larger randomized studies.

The effect of referral to an open-group behavioural weight-management programme on the relative risk of normoglycaemia, non-diabetic hyperglycaemia and type 2 diabetes: Secondary analysis of the WRAP trial.

AIM: To examine the impact of open-group behavioural weight-management programmes on the risk of diabetes among those with a body mass index (BMI) of ≥28 kg/m2 and those with non-diabetic hyperglycaemia (NDH). METHODS: This was a secondary analysis of data from the WRAP trial, in which participants (N = 1267; aged ≥18 years, BMI ≥ 28 kg/m2 ) were randomized to brief intervention (BI; self-help booklet), a weight-management programme (WW; formerly Weight Watchers) for 12 weeks, or WW for 52 weeks. We used multinomial logistic regression to examine the effect of intervention group on the risk of hyperglycaemia and diabetes at 12 months in all participants with glycaemic status at both time points (N = 480; 38%) and those with NDH at baseline (N = 387; 31%). We used mixed effects models and linear fixed effects models to examine the effect of intervention group on body weight and HbA1c at 12 months in people with NDH. RESULTS: There was a 61% relative reduction in the risk of NDH at the 12-month follow-up (12 weeks vs. BI: relative risk ratio [RRR] = 0.39 [95% CI 0.18, 0.87], P = .021; 52 weeks vs. BI: RRR = 0.38 [95% CI 0.17, 0.86], P = .020). For intervention effects on the risk of diabetes, confidence intervals were wide and overlapped 1 [12 weeks vs. BI: RRR = 0.49 [95% CI 0.12, 1.96], P = .312; 52 weeks vs. BI: RRR = 0.40 [95% CI 0.10, 1.63], P = .199). Participants with hyperglycaemia at baseline in the weight-management programme were more probable to have normoglycaemia at the 12-month follow-up [12-week programme vs. BI: RRR = 3.57 [95% CI 1.24, 10.29], P = .019; 52-week programme vs. BI: RRR = 4.14 [95% CI 1.42, 12.12], P = .009). CONCLUSIONS: Open-group behavioural weight-management programmes can help to prevent the development of NDH in people with overweight and obesity and to normalize glycaemia in people with NDH.

Designing and evaluating dose-escalation studies made easy: The MoDEsT web app.

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.

A Bayesian model-free approach to combination therapy phase I trials using censored time-to-toxicity data.

The product of independent beta probabilities escalation (PIPE) design for dual-agent phase I dose-escalation trials is a Bayesian model-free approach for identifying multiple maximum tolerated dose combinations of novel combination therapies. Despite only being published in 2015, the PIPE design has been implemented in at least two oncology trials. However, these trials require patients to have completed follow-up before clinicians can make dose-escalation decisions. For trials of radiotherapy or advanced therapeutics, this may lead to impractically long trial durations due to late-onset treatment-related toxicities. In this paper, we extend the PIPE design to use censored time-to-event (TITE) toxicity outcomes for making dose escalation decisions. We show via comprehensive simulation studies and sensitivity analyses that trial duration can be reduced by up to 35%, particularly when recruitment is faster than expected, without compromising on other operating characteristics.

How to design a dose-finding study using the continual reassessment method.

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.

Incoherent dose-escalation in phase I trials using the escalation with overdose control approach.

A desirable property of any dose-escalation strategy for phase I oncology trials is coherence: if the previous patient experienced a toxicity, a higher dose is not recommended for the next patient; similarly, if the previous patient did not experience a toxicity, a lower dose is not recommended for the next patient. The escalation with overdose control (EWOC) approach is a model-based design that has been applied in practice, under which the dose assigned to the next patient is the one that, given all available data, has a posterior probability of exceeding the maximum tolerated dose equal to a pre-specified value known as the feasibility bound. Several methodological and applied publications have considered the EWOC approach with both feasibility bounds fixed and increasing throughout the trial. Whilst the EWOC approach with fixed feasibility bound has been proven to be coherent, some proposed methods of increasing the feasibility bound regardless of toxicity outcomes of patients can lead to incoherent dose-escalation. This paper formalises a proof that incoherent dose-escalation can occur if the feasibility bound is increased without consideration of preceding toxicity outcomes, and shows via simulation studies that only small increases in the feasibility bound are required for incoherent dose-escalations to occur.

Adaptive designs in clinical trials: why use them, and how to run and report them.

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.

Extended and standard duration weight-loss programme referrals for adults in primary care (WRAP): a randomised controlled trial.

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/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. 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; 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). INTERPRETATION: 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).

Toxicity-dependent feasibility bounds for the escalation with overdose control approach in phase I cancer trials.

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.

Modelling semi-attributable toxicity in dual-agent phase I trials with non-concurrent drug administration.

In oncology, combinations of drugs are often used to improve treatment efficacy and/or reduce harmful side effects. Dual-agent phase I clinical trials assess drug safety and aim to discover a maximum tolerated dose combination via dose-escalation; cohorts of patients are given set doses of both drugs and monitored to see if toxic reactions occur. Dose-escalation decisions for subsequent cohorts are based on the number and severity of observed toxic reactions, and an escalation rule. In a combination trial, drugs may be administered concurrently or non-concurrently over a treatment cycle. For two drugs given non-concurrently with overlapping toxicities, toxicities occurring after administration of the first drug yet before administration of the second may be attributed directly to the first drug, whereas toxicities occurring after both drugs have been given some present ambiguity; toxicities may be attributable to the first drug only, the second drug only or the synergistic combination of both. We call this mixture of attributable and non-attributable toxicity semi-attributable toxicity. Most published methods assume drugs are given concurrently, which may not be reflective of trials with non-concurrent drug administration. We incorporate semi-attributable toxicity into Bayesian modelling for dual-agent phase I trials with non-concurrent drug administration and compare the operating characteristics to an approach where this detail is not considered. Simulations based on a trial for non-concurrent administration of intravesical Cabazitaxel and Cisplatin in early-stage bladder cancer patients are presented for several scenarios and show that including semi-attributable toxicity data reduces the number of patients given overly toxic combinations. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

AplusB: A Web Application for Investigating A + B Designs for Phase I Cancer Clinical Trials.

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.

Adaptive designs for dual-agent phase I dose-escalation studies.

Anticancer agents used in combination are fundamental to successful cancer treatment, particularly in a curative setting. For dual-agent phase I trials, the goal is to identify drug doses and schedules for further clinical testing. However, current methods for establishing the recommended phase II dose for agents in combination can fail to fully explore drug interactions. With increasing numbers of anticancer drugs requiring testing, new adaptive model-based trial designs that improve on current practice have been proposed, although uptake has been minimal. We describe the methods available and discuss some of the opportunities and challenges faced in dual-agent phase I trials, as well as giving examples of trials in which adaptive designs have been implemented successfully. Improving the design and execution of phase I trials of drug combinations critically relies on collaboration between the statistical and clinical communities to facilitate the implementation of adaptive, model-based designs.