Publications
27 results found
Ng K, Metcalf R, Sacco J, et al., 2023, Protocol for the EACH trial: a multicentre phase II study evaluating the safety and antitumour activity of the combination of avelumab, an anti-PD-L1 agent, and cetuximab, as any line treatment for patients with recurrent/metastatic head and neck squamous cell cancer (HNSCC) in the UK, BMJ Open, Vol: 13, ISSN: 2044-6055
INTRODUCTION: Head and neck cancer is the eighth most common cancer in the UK. Current standard of care treatment for patients with recurrent/metastatic squamous cell head and neck carcinoma (HNSCC) is platinum-based chemotherapy combined with the anti-epidermal growth factor receptor (anti-EGFR) monoclonal antibody, cetuximab. However, most patients will have poor median overall survival (OS) of 6-9 months despite treatment. HNSCC tumours exhibit an immune landscape poised to respond to immunotherapeutic approaches, with most tumours expressing the immunosuppressive receptor programmed death-ligand 1 (PD-L1). We undertook the current study to determine the safety and efficacy of avelumab, a monoclonal antibody targeting the interaction between PD-L1 and its receptor on cytotoxic T-cells, in combination with cetuximab. METHODS AND ANALYSIS: This is a multi-centre, single-arm dose de-escalation phase II safety and efficacy study of avelumab combined with cetuximab; the study was to progress to a randomised phase II trial, however, the study will now complete after the safety run-in component. Up to 16 participants with histologically/cytologically recurrent/metastatic squamous cell carcinoma (including HNSCC) who have not received cetuximab previously will be recruited. All patients will receive 10 mg/kg avelumab and cetuximab (500, 400 or 300 mg/m2 depending on the cohort open at time of registration) on days 1 and 15 of 4-week cycles for up to 1 year, (avelumab not given cycle 1 day 1). A modified continual reassessment method will be used to determine dose de-escalation. The primary objective is to establish the safety of the combination and to determine the optimum dose of cetuximab. Secondary objectives include assessing evidence of antitumour activity by evaluating response rates and disease control rates at 6 and 12 months as well as progression-free and OS. ETHICS AND DISSEMINATION: Approval granted by City and East REC (18/LO/0021). Find
Law M, Couturier D-L, Choodari-Oskooei B, et al., 2023, Correction: Medicines and Healthcare products Regulatory Agency's "Consultation on proposals for legislative changes for clinical trials": a response from the Trials Methodology Research Partnership Adaptive Designs Working Group, with a focus on data sharing, Trials, Vol: 24, ISSN: 1745-6215
Law M, Couturier D-L, Choodari-Oskooei B, et al., 2023, Medicines and Healthcare products Regulatory Agency's "Consultation on proposals for legislative changes for clinical trials": a response from the Trials Methodology Research Partnership Adaptive Designs Working Group, with a focus on data sharing, Trials, Vol: 24, ISSN: 1745-6215
In the UK, the Medicines and Healthcare products Regulatory Agency consulted on proposals "to improve and strengthen the UK clinical trials legislation to help us make the UK the best place to research and develop safe and innovative medicines". The purpose of the consultation was to help finalise the proposals and contribute to the drafting of secondary legislation. We discussed these proposals as members of the Trials Methodology Research Partnership Adaptive Designs Working Group, which is jointly funded by the Medical Research Council and the National Institute for Health and Care Research. Two topics arose frequently in the discussion: the emphasis on legislation, and the absence of questions on data sharing. It is our opinion that the proposals rely heavily on legislation to change practice. However, clinical trials are heterogeneous, and as a result some trials will struggle to comply with all of the proposed legislation. Furthermore, adaptive design clinical trials are even more heterogeneous than their non-adaptive counterparts, and face more challenges. Consequently, it is possible that increased legislation could have a greater negative impact on adaptive designs than non-adaptive designs. Overall, we are sceptical that the introduction of legislation will achieve the desired outcomes, with some exceptions. Meanwhile the topic of data sharing - making anonymised individual-level clinical trial data available to other investigators for further use - is entirely absent from the proposals and the consultation in general. However, as an aspect of the wider concept of open science and reproducible research, data sharing is an increasingly important aspect of clinical trials. The benefits of data sharing include faster innovation, improved surveillance of drug safety and effectiveness and decreasing participant exposure to unnecessary risk. There are already a number of UK-focused documents that discuss and encourage data sharing, for example, the Con
Iasonos A, Wheeler GM, 2022, "Improving the performance of Bayesian logistic regression model with overdose control in oncology dose-finding studies" by Hongtao Zhang, Alan Chiang, and Jixian Wang, STATISTICS IN MEDICINE, Vol: 41, Pages: 5494-5496, ISSN: 0277-6715
Ahern AL, Breeze P, Fusco F, et al., 2022, 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, The Lancet Public Health, Vol: 7, Pages: e866-e875, ISSN: 2468-2667
BackgroundThere 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.MethodsWRAP 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.FindingsBetween 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
Wilson R, Arkell P, Riezk A, et al., 2022, Addition of probenecid to oral beta-lactam antibiotics: a systematic review and meta-analysis, Journal of Antimicrobial Chemotherapy, Vol: 77, Pages: 2364-2372, ISSN: 0305-7453
Objective: Explore literature comparing the pharmacokinetic and clinical outcomes from addition of probenecid to oral beta-lactams.Data sources: Medline and EMBASE were searched from inception to December 2021.Study eligibility criteria: All English language studies comparing the addition of probenecid (intervention) to an oral beta-lactam (flucloxacillin, penicillin-V, amoxicillin(+/-clavulanate), cephalexin, cefuroxime-axetil) alone (comparator).Risk of bias: Risk of Bias in Non-randomised studies of interventions (ROBINS-I) and Risk of Bias for Randomised studies 2 (ROB-2) tools were used.Methods of data synthesis: Data on antibiotic therapy, infection diagnosis, primary and secondary outcomes relating to pharmacokinetics and clinical outcomes plus adverse events were extracted and reported descriptively. For a subset of studies comparing treatment failure between probenecid and control groups, meta-analysis was performed. Results: Overall, 18/295 (6%) abstracts screened were included. Populations, methodology, and outcome data were heterogenous. Common populations included healthy volunteer (9/18;50%) and gonococcal infection (6/18;33%). Most studies were cross-over trials (11/18;61%) or parallel arm randomised trial (4/18;22%). Where pharmacokinetic analyses were performed, addition of probenecid to oral beta-lactams increased total AUC (7/7;100¬%), peak observed concentration (Cmax,5/8;63%), and serum half-life (t1/2,6/8;75%). Probenecid improved PTA (2/2;100%). Meta-analysis of 3105 (2258 intervention, 847 control) patients treated for gonococcal disease demonstrated a relative risk of treatment failure in the random effects model of 0.33 (95%CI:0.20-0.55; I2=7%), favouring probenecid. Conclusion: Probenecid boosted beta-lactam therapy is associated with improved outcomes in gonococcal disease. Pharmacokinetic data suggest that probenecid boosted oral beta-lactam therapy may have a broader application, but appropriately powered mechanistic and efficacy st
Phillips R, Cro S, Wheeler G, et al., 2022, Visualising harms in publications of randomised controlled trials: consensus and recommendations, BMJ: British Medical Journal, Vol: 377, ISSN: 0959-535X
Objective: To improve communication of harm in publications of randomised controlled trials via the development of recommendations for visually presenting harm outcomes.Design: Consensus study.Setting: 15 clinical trials units registered with the UK Clinical Research Collaboration, an academic population health department, Roche Products, and TheBMJ.Participants: Experts in clinical trials: 20 academic statisticians, one industry statistician, one academic health economist, one data graphics designer, and two clinicians.Main outcome measures: A methodological review of statistical methods identified visualisations along with those recommended by consensus group members. Consensus on visual recommendations was achieved (at least 60% of the available votes) over a series of three meetings with participants. The participants reviewed and critically appraised candidate visualisations against an agreed framework and voted on whether to endorse each visualisation. Scores marginally below this threshold (50-60%) were revisited for further discussions and votes retaken until consensus was reached.Results: 28 visualisations were considered, of which 10 are recommended for researchers to consider in publications of main research findings. The choice of visualisations to present will depend on outcome type (eg, binary, count, time-to-event, or continuous), and the scenario (eg, summarising multiple emerging events or one event of interest). A decision tree is presented to assist trialists in deciding which visualisations to use. Examples are provided of each endorsed visualisation, along with an example interpretation, potential limitations, and signposting to code for implementation across a range of standard statistical software. Clinician feedback was incorporated into the explanatory information provided in the recommendations to aid understanding and interpretation.Conclusions: Visualisations provide a powerful tool to communicate harms in clinical trials, offering an alt
Homer V, Yap C, Bond S, et al., 2022, Early phase clinical trials extension to guidelines for the content of statistical analysis plans, BMJ, Vol: 376, Pages: 1-10, ISSN: 1759-2151
Heath L, Jebb S, Stevens R, et al., 2022, Effects of a group-based weight management programme on anxiety and depression: A randomised controlled trial (RCT), PLoS One, Vol: 17, Pages: 1-12, ISSN: 1932-6203
ObjectivesThe aim was to investigate the impact of a group-based weight management programme on symptoms of depression and anxiety compared with self-help in a randomised controlled trial (RCT).MethodPeople with overweight (Body Mass Index [BMI]≥28kg/m2) were randomly allocated self-help (n = 211) or a group-based weight management programme for 12 weeks (n = 528) or 52 weeks (n = 528) between 18/10/2012 and 10/02/2014. Symptoms were assessed using the Hospital Anxiety and Depression Scale, at baseline, 3, 12 and 24 months. Linear regression modelling examined changes in Hospital Anxiety and Depression Scale between trial arms.ResultsAt 3 months, there was a -0.6 point difference (95% confidence interval [CI], -1.1, -0.1) in depression score and -0.1 difference (95% CI, -0.7, 0.4) in anxiety score between group-based weight management programme and self-help. At subsequent time points there was no consistent evidence of a difference in depression or anxiety scores between trial arms. There was no evidence that depression or anxiety worsened at any time point.ConclusionsThere was no evidence of harm to depression or anxiety symptoms as a result of attending a group-based weight loss programme. There was a transient reduction in symptoms of depression, but not anxiety, compared to self-help. This effect equates to less than 1 point out of 21 on the Hospital Anxiety and Depression Scale and is not clinically significant.
Roddie C, Dias J, O'Reilly MA, et al., 2021, Durable responses and low toxicity after fast off-rate CD19 chimeric antigen receptor-T therapy in adults with relapsed or refractory B-cell acute lymphoblastic leukemia., Journal of Clinical Oncology, Vol: 39, Pages: 1-13, ISSN: 0732-183X
PURPOSE: Prognosis for adult B-cell acute lymphoblastic leukemia (B-ALL) is poor, and there are currently no licensed CD19 chimeric antigen receptor (CAR) therapeutics. We developed a novel second-generation CD19-CAR (CAT19-41BB-Z) with a fast off rate, designed for more physiologic T-cell activation to reduce toxicity and improve engraftment. We describe the multicenter phase I ALLCAR19 (NCT02935257) study of autologous CAT19-41BB-Z CAR T cells (AUTO1) in relapsed or refractory (r/r) adult B-ALL. METHODS: Patients age ≥ 16 years with r/r B-ALL were eligible. Primary outcomes were toxicity and manufacturing feasibility. Secondary outcomes were depth of response at 1 and 3 months, persistence of CAR-T, incidence and duration of hypogammaglobulinemia and B-cell aplasia, and event-free survival and overall survival at 1 and 2 years. RESULTS: Twenty-five patients were leukapheresed, 24 products were manufactured, and 20 patients were infused with AUTO1. The median age was 41.5 years; 25% had prior blinatumomab, 50% prior inotuzumab ozogamicin, and 65% prior allogeneic stem-cell transplantation. At the time of preconditioning, 45% had ≥ 50% bone marrow blasts. No patients experienced ≥ grade 3 cytokine release syndrome; 3 of 20 (15%) experienced grade 3 neurotoxicity that resolved to ≤ grade 1 within 72 hours with steroids. Seventeen of 20 (85%) achieved minimal residual disease-negative complete response at month 1, and 3 of 17 underwent allogeneic stem-cell transplantation while in remission. The event-free survival at 6 and 12 months was 68.3% (42.4-84.4) and 48.3% (23.1%-69.7%), respectively. High-level expansion (Cmax 127,152 copies/µg genomic DNA) and durable CAR-T persistence were observed with B-cell aplasia ongoing in 15 of 20 patients at last follow-up. CONCLUSION: AUTO1 demonstrates a tolerable safety profile, high remission rates, and excellent persistence in r/r adult B-ALL. Preliminary data support further development of AUTO1 as a stand-a
Jayaram A, Wingate A, Wetterskog D, et al., 2021, Plasma tumor gene conversions after one cycle abiraterone acetate for metastatic castration-resistant prostate cancer: a biomarker analysis of a multicenter international trial, Annals of Oncology, Vol: 32, Pages: 726-735, ISSN: 0923-7534
Sweeting M, Mander A, Wheeler G, 2021, Bayesian Adaptive Designs for Phase I Trials, Principles and Practice of Clinical Trials, Editors: Piantadosi, Meinert, Publisher: Springer, ISBN: 9783319526355
Phase I trials mark the first experimentation of a new drug or combination of drugs in a human population. The primary aim of a cancer phase I trial is to seek a safe dose or range of doses suitable for phase II experimentation. Bayesian adaptive designs have long been proposed to allow safe dose escalation and dose finding within phase I trials. There are now a vast number of designs proposed for use in phase I trials though widespread application of these designs is still limited. More recent designs have focused on the incorporation of multiple sources of information into dose-finding algorithms to improve trial safety and efficiency. This chapter reviews some of the papers that extend the simple dose-escalation trial design with a binary toxicity outcome. Specifically, the chapter focuses on five key topics: (1) overdose control, (2) use of partial outcome follow-up, (3) grading of toxicity outcomes, (4) incorporation of both toxicity and efficacy information, and (5) dual-agent or dose-scheduling designs. Each extension is illustrated with an example from a real-life trial with reference to freely available software. These extensions open the way to a broader class of phase I trials being conducted, leading to safer and more efficient trials.
Burnett T, Mozgunov P, Pallmann P, et al., 2020, Adding flexibility to clinical trial designs: an example-based guide to the practical use of adaptive designs, BMC Medicine, Vol: 18, Pages: 1-21, ISSN: 1741-7015
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.
Ahern AL, Griffin SJ, Wheeler GM, et al., 2020, 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, Diabetes, Obesity and Metabolism, Vol: 22, Pages: 2069-2076, ISSN: 1462-8902
AimTo 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).MethodsThis 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.ResultsThere 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).ConclusionsOpen‐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.
Fennell DA, Danson S, Woll PJ, et al., 2020, Ganetespib in combination with pemetrexed–platinum chemotherapy in patients with pleural mesothelioma (MESO-02): a phase Ib trial, Clinical Cancer Research, Vol: 26, Pages: 4748-4755, ISSN: 1078-0432
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.
Grayling MJ, Wheeler GM, 2020, A review of available software for adaptive clinical trial design, Clinical Trials, Vol: 17, Pages: 323-331, ISSN: 1740-7745
Background/aims:The increasing cost of the drug development process has seen interest in the use of adaptive trial designs grow substantially. Accordingly, much research has been conducted to identify barriers to increasing the use of adaptive designs in practice. Several articles have argued that the availability of user-friendly software will be an important step in making adaptive designs easier to implement. Therefore, we present a review of the current state of software availability for adaptive trial design.Methods:We review articles from 31 journals published in 2013–2017 that relate to methodology for adaptive trials to assess how often code and software for implementing novel adaptive designs is made available at the time of publication. We contrast our findings against these journals’ policies on code distribution. We also search popular code repositories, such as Comprehensive R Archive Network and GitHub, to identify further existing user-contributed software for adaptive designs. From this, we are able to direct interested parties toward solutions for their problem of interest.Results:Only 30% of included articles made their code available in some form. In many instances, articles published in journals that had mandatory requirements on code provision still did not make code available. There are several areas in which available software is currently limited or saturated. In particular, many packages are available to address group sequential design, but comparatively little code is present in the public domain to determine biomarker-guided adaptive designs.Conclusions:There is much room for improvement in the provision of software alongside adaptive design publications. In addition, while progress has been made, well-established software for various types of trial adaptation remains sparsely available.
Pallmann P, Wan F, Mander AP, et al., 2020, Designing and evaluating dose-escalation studies made easy: The MoDEsT web app, Clinical Trials, Vol: 17, Pages: 147-156, ISSN: 1740-7745
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 a
Wheeler GM, Sweeting MJ, Mander AP, 2019, A Bayesian model‐free approach to combination therapy phase I trials using censored time‐to‐toxicity data, Journal of the Royal Statistical Society: Series C (Applied Statistics), Vol: 68, Pages: 309-329, ISSN: 0035-9254
The product of independent beta probabilities escalation 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 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. We extend the product of independent probabilities escalation design to use censored time‐to‐event 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.
Wheeler GM, Mander AP, Bedding A, et al., 2019, How to design a dose-finding study using the continual reassessment method, BMC Medical Research Methodology, Vol: 19, ISSN: 1471-2288
IntroductionThe 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.MethodsTo 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.ResultsAn 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.ConclusionsThe framework and resources we provide are aimed at clinicians
Pallmann P, Bedding AW, Choodari-Oskooei B, et al., 2018, Adaptive designs in clinical trials: why use them, and how to run and report them, BMC Medicine, Vol: 16, Pages: 1-15, ISSN: 1741-7015
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 resu
Wheeler GM, 2018, Incoherent dose-escalation in phase I trials using the escalation with overdose control approach, Statistical Papers, Vol: 59, Pages: 801-811, ISSN: 0932-5026
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.
Wheeler GM, Sweeting MJ, Mander AP, 2017, Toxicity-dependent feasibility bounds for the escalation with overdose control approach in phase I cancer trials, Statistics in Medicine, Vol: 36, Pages: 2499-2513, ISSN: 0277-6715
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.
Ahern AL, Wheeler GM, Aveyard P, et al., 2017, Extended and standard duration weight-loss programme referrals for adults in primary care (WRAP): a randomised controlled trial, The Lancet, Vol: 389, Pages: 2214-2225, ISSN: 0140-6736
BackgroundEvidence 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.MethodsIn 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.FindingsBetween 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 particip
Wheeler G, 2017, Overview of phase I designs, Handbook of Methods for Designing, Monitoring, and Analyzing Dose-Finding Trials, Editors: O'Quigley, Iasonos, Bornkamp, Publisher: Chapman and Hall/CRC, Pages: 3-26, ISBN: 9781498746106
This chapter describes the main rule-based and model-based approaches for conducting phase I dose-escalation studies with a single binary dose-limiting toxicity (DLT) endpoint. Most methods for phase I trials are based on the assumption of monotonicity; that is, if a patient has a DLT at a given dose level, then the same patient would have had a DLT had they been given a higher dose level than the one they received. The primary objective of a phase I clinical trial is to investigate the safety profile of a novel drug or drug combination and identify a tolerable dose schedule that is likely to benefit patients. Rule-based designs have long been popular with clinicians in cytotoxic drug experimentation. The 3 + 3 design is the most commonly used design in phase I clinical trials and has long been considered the routine method by clinicians for estimating the maximum tolerated dose (MTD) of novel drugs in oncology.
Wheeler GM, Sweeting MJ, Mander AP, et al., 2017, Modelling semi‐attributable toxicity in dual‐agent phase I trials with non‐concurrent drug administration, Statistics in Medicine, Vol: 36, Pages: 225-241, ISSN: 0277-6715
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.
Wheeler GM, Sweeting MJ, Mander AP, 2016, AplusB: A web application for investigating A + B designs for phase I cancer clinical trials, PLoS One, Vol: 11, Pages: 1-17, ISSN: 1932-6203
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.
Harrington JA, Wheeler GM, Sweeting MJ, et al., 2013, Adaptive designs for dual-agent phase I dose-escalation studies, Nature Reviews Clinical Oncology, Vol: 10, Pages: 277-288, ISSN: 1759-4774
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.
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.