Bayesian methods for the design and interpretation of clinical trials in very rare diseases

Value of information methods to design a clinical trial in a small population to optimise a health economic utility function

Background

Most confirmatory randomised controlled clinical trials (RCTs) are designed with specified power, usually 80% or 90%, for a hypothesis test conducted at a given significance level, usually 2.5% for a one-sided test. Approval of the experimental treatment by regulatory agencies is then based on the result of such a significance test with other information to balance the risk of adverse events against the benefit of the treatment to future patients. In the setting of a rare disease, recruiting sufficient patients to achieve conventional error rates for clinically reasonable effect sizes may be infeasible, suggesting that the decision-making process should reflect the size of the target population.

Methods

We considered the use of a decision-theoretic value of information (VOI) method to obtain the optimal sample size and significance level for confirmatory RCTs in a range of settings. We assume the decision maker represents society. For simplicity we assume the primary endpoint to be normally distributed with unknown mean following some normal prior distribution representing information on the anticipated effectiveness of the therapy available before the trial. The method is illustrated by an application in an RCT in haemophilia A. We explicitly specify the utility in terms of improvement in primary outcome and compare this with the costs of treating patients, both financial and in terms of potential harm, during the trial and in the future.

Results

The optimal sample size for the clinical trial decreases as the size of the population decreases. For non-zero cost of treating future patients, either monetary or in terms of potential harmful effects, stronger evidence is required for approval as the population size increases, though this is not the case if the costs of treating future patients are ignored.

Conclusions

Decision-theoretic VOI methods offer a flexible approach with both type I error rate and power (or equivalently trial sample size) depending on the size of the future population for whom the treatment under investigation is intended. This might be particularly suitable for small populations when there is considerable information about the patient population.

Electronic supplementary material

The online version of this article (10.1186/s12874-018-0475-0) contains supplementary material, which is available to authorized users.

Establishing core outcome sets for phenylketonuria (PKU) and medium-chain Acyl-CoA dehydrogenase (MCAD) deficiency in children: study protocol for systematic reviews and Delphi surveys

BACKGROUND

Inherited metabolic diseases (IMD) are a large group of rare single-gene disorders that are typically diagnosed early in life. There are important evidence gaps related to the comparative effectiveness of therapies for IMD, which are in part due to challenges in conducting randomized controlled trials (RCTs) for rare diseases. Registry-based RCTs present a unique opportunity to address these challenges provided the registries implement standardized collection of outcomes that are important to patients and their caregivers and to clinical providers and healthcare systems. Currently there is no core outcome set (COS) for studies evaluating interventions for paediatric IMD. This protocol outlines a study that will establish COS for each of two relatively common IMD in children, phenylketonuria (PKU) and medium-chain acyl-CoA dehydrogenase (MCAD) deficiency.

METHODS

This two-part study is registered with the Core Outcome Measures in Effectiveness Trials (COMET) initiative. Part 1 includes a rapid review and development of an evidence map to identify a comprehensive listing of outcomes reported in past studies of PKU and MCAD deficiency. The review follows established methods for knowledge synthesis, including a comprehensive search strategy, two stages of screening citations against inclusion/exclusion criteria by two reviewers working independently, and extraction of important data elements from eligible studies, including details of the outcomes collected and outcome measurement instruments. The review findings will inform part 2 of our study, a set of Delphi surveys to establish consensus on the highest priority outcomes for each condition. Healthcare providers, families of children with PKU or MCAD deficiency, and health system decision-makers will be invited to participate in two to three rounds of Delphi surveys. The design of the surveys will involve parents of children with IMD who are part of a family advisory forum.

DISCUSSION

This protocol is a crucial step in developing the capacity to launch RCTs with meaningful outcomes that address comparative effectiveness questions in the field of paediatric IMD. Such trials will contribute high-quality evidence to inform decision-making by patients and their family members, clinicians, and policy-makers.

Development of a practical approach to expert elicitation for randomised controlled trials with missing health outcomes: Application to the IMPROVE trial

Background/aims:

The analyses of randomised controlled trials with missing data typically assume that, after conditioning on the observed data, the probability of missing data does not depend on the patient’s outcome, and so the data are ‘missing at random’ . This assumption is usually implausible, for example, because patients in relatively poor health may be more likely to drop out. Methodological guidelines recommend that trials require sensitivity analysis, which is best informed by elicited expert opinion, to assess whether conclusions are robust to alternative assumptions about the missing data. A major barrier to implementing these methods in practice is the lack of relevant practical tools for eliciting expert opinion. We develop a new practical tool for eliciting expert opinion and demonstrate its use for randomised controlled trials with missing data.

Methods:

We develop and illustrate our approach for eliciting expert opinion with the IMPROVE trial (ISRCTN 48334791), an ongoing multi-centre randomised controlled trial which compares an emergency endovascular strategy versus open repair for patients with ruptured abdominal aortic aneurysm. In the IMPROVE trial at 3 months post-randomisation, 21% of surviving patients did not complete health-related quality of life questionnaires (assessed by EQ-5D-3L). We address this problem by developing a web-based tool that provides a practical approach for eliciting expert opinion about quality of life differences between patients with missing versus complete data. We show how this expert opinion can define informative priors within a fully Bayesian framework to perform sensitivity analyses that allow the missing data to depend upon unobserved patient characteristics.

Results:

A total of 26 experts, of 46 asked to participate, completed the elicitation exercise. The elicited quality of life scores were lower on average for the patients with missing versus complete data, but there was considerable uncertainty in these elicited values. The missing at random analysis found that patients randomised to the emergency endovascular strategy versus open repair had higher average (95% credible interval) quality of life scores of 0.062 (−0.005 to 0.130). Our sensitivity analysis that used the elicited expert information as pooled priors found that the gain in average quality of life for the emergency endovascular strategy versus open repair was 0.076 (−0.054 to 0.198).

Conclusion:

We provide and exemplify a practical tool for eliciting the expert opinion required by recommended approaches to the sensitivity analyses of randomised controlled trials. We show how this approach allows the trial analysis to fully recognise the uncertainty that arises from making alternative, plausible assumptions about the reasons for missing data. This tool can be widely used in the design, analysis and interpretation of future trials, and to facilitate this, materials are available for download.

Using phase II data for the analysis of phase III studies: An application in rare diseases

BACKGROUND

Clinical research and drug development in orphan diseases are challenging, since large-scale randomized studies are difficult to conduct. Formally synthesizing the evidence is therefore of great value, yet this is rarely done in the drug-approval process. Phase III designs that make better use of phase II data can facilitate drug development in orphan diseases.

METHODS

A Bayesian meta-analytic approach is used to inform the phase III study with phase II data. It is particularly attractive, since uncertainty of between-trial heterogeneity can be dealt with probabilistically, which is critical if the number of studies is small. Furthermore, it allows quantifying and discounting the phase II data through the predictive distribution relevant for phase III. A phase III design is proposed which uses the phase II data and considers approval based on a phase III interim analysis. The design is illustrated with a non-inferiority case study from a Food and Drug Administration approval in herpetic keratitis (an orphan disease). Design operating characteristics are compared to those of a traditional design, which ignores the phase II data.

RESULTS

An analysis of the phase II data reveals good but insufficient evidence for non-inferiority, highlighting the need for a phase III study. For the phase III study supported by phase II data, the interim analysis is based on half of the patients. For this design, the meta-analytic interim results are conclusive and would justify approval. In contrast, based on the phase III data only, interim results are inconclusive and require further evidence.

CONCLUSION

To accelerate drug development for orphan diseases, innovative study designs and appropriate methodology are needed. Taking advantage of randomized phase II data when analyzing phase III studies looks promising because the evidence from phase II supports informed decision-making. The implementation of the Bayesian design is straightforward with public software such as R.

A phase II Bayesian sequential clinical trial in advanced Waldenström macroglobulinemia patients treated with bortezomib: interest of addition of dexamethasone

In patients with advanced Waldenström macroglobulinemia (WM), overall response rate (ORR) and median progression-free survival (PFS) achieved with bortezomib alone and bortezomib rituximab combination were 27-85% and 7.9 months, and 81% and 16.4 months, respectively. We checked the role of dexamethasone in combination with bortezomib by enrolling in a phase II trial 34 patients with relapsed/refractory WM. Bortezomib (1.3 mg/m² IV D1, 4, 8, and 11 every 21 days) was used for six cycles. In non-responding patients, dexamethasone (20 mg daily for two days) was added to each infusion after the second cycle. After two cycles, the Bayes estimated ORR was 43.2 (95% Credible Interval: 28.0-59.1%) using the informative prior. Two-year survival rate was 84.0% and the median PFS 15.3 months without difference between patients treated with or without dexamethasone. We conclude that dexamethasone must be associated to bortezomib-based regimen.

Aquatic therapy for boys with Duchenne muscular dystrophy (DMD): an external pilot randomised controlled trial

BACKGROUND

Standard treatment of Duchenne muscular dystrophy (DMD) includes regular physiotherapy. There are no data to show whether adding aquatic therapy (AT) to land-based exercises helps maintain motor function. We assessed the feasibility of recruiting and collecting data from boys with DMD in a parallel-group pilot randomised trial (primary objective), also assessing how intervention and trial procedures work.

METHODS

Ambulant boys with DMD aged 7-16 years established on steroids, with North Star Ambulatory Assessment (NSAA) score ≥8, who were able to complete a 10-m walk test without aids or assistance, were randomly allocated (1:1) to 6 months of either optimised land-based exercises 4 to 6 days/week, defined by local community physiotherapists, or the same 4 days/week plus AT 2 days/week. Those unable to commit to a programme, with >20% variation between NSAA scores 4 weeks apart, or contraindications to AT were excluded. The main outcome measures included feasibility of recruiting 40 participants in 6 months from six UK centres, clinical outcomes including NSAA, independent assessment of treatment optimisation, participant/therapist views on acceptability of intervention and research protocols, value of information (VoI) analysis and cost-impact analysis.

RESULTS

Over 6 months, 348 boys were screened: most lived too far from centres or were enrolled in other trials; 12 (30% of the targets) were randomised to AT (n = 8) or control (n = 4). The mean change in NSAA at 6 months was -5.5 (SD 7.8) in the control arm and -2.8 (SD 4.1) in the AT arm. Harms included fatigue in two boys, pain in one. Physiotherapists and parents valued AT but believed it should be delivered in community settings. Randomisation was unattractive to families, who had already decided that AT was useful and who often preferred to enrol in drug studies. The AT prescription was considered to be optimised for three boys, with other boys given programmes that were too extensive and insufficiently focused. Recruitment was insufficient for VoI analysis.

CONCLUSIONS

Neither a UK-based RCT of AT nor a twice weekly AT therapy delivered at tertiary centres is feasible. Our study will help in the optimisation of AT service provision and the design of future research.

TRIAL REGISTRATION

ISRCTN41002956.

Meta-analysis of few small studies in orphan diseases

Meta-analyses in orphan diseases and small populations generally face particular problems, including small numbers of studies, small study sizes and heterogeneity of results. However, the heterogeneity is difficult to estimate if only very few studies are included. Motivated by a systematic review in immunosuppression following liver transplantation in children, we investigate the properties of a range of commonly used frequentist and Bayesian procedures in simulation studies. Furthermore, the consequences for interval estimation of the common treatment effect in random-effects meta-analysis are assessed. The Bayesian credibility intervals using weakly informative priors for the between-trial heterogeneity exhibited coverage probabilities in excess of the nominal level for a range of scenarios considered. However, they tended to be shorter than those obtained by the Knapp-Hartung method, which were also conservative. In contrast, methods based on normal quantiles exhibited coverages well below the nominal levels in many scenarios. With very few studies, the performance of the Bayesian credibility intervals is of course sensitive to the specification of the prior for the between-trial heterogeneity. In conclusion, the use of weakly informative priors as exemplified by half-normal priors (with a scale of 0.5 or 1.0) for log odds ratios is recommended for applications in rare diseases. © 2016 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd.

Application and Evaluation of an Expert Judgment Elicitation Procedure for Correlations

The purpose of the current study was to apply and evaluate a procedure to elicit expert judgments about correlations, and to update this information with empirical data. The result is a face-to-face group elicitation procedure with as its central element a trial roulette question that elicits experts' judgments expressed as distributions. During the elicitation procedure, a concordance probability question was used to provide feedback to the experts on their judgments. We evaluated the elicitation procedure in terms of validity and reliability by means of an application with a small sample of experts. Validity means that the elicited distributions accurately represent the experts' judgments. Reliability concerns the consistency of the elicited judgments over time. Four behavioral scientists provided their judgments with respect to the correlation between cognitive potential and academic performance for two separate populations enrolled at a specific school in the Netherlands that provides special education to youth with severe behavioral problems: youth with autism spectrum disorder (ASD), and youth with diagnoses other than ASD. Measures of face-validity, feasibility, convergent validity, coherence, and intra-rater reliability showed promising results. Furthermore, the current study illustrates the use of the elicitation procedure and elicited distributions in a social science application. The elicited distributions were used as a prior for the correlation, and updated with data for both populations collected at the school of interest. The current study shows that the newly developed elicitation procedure combining the trial roulette method with the elicitation of correlations is a promising tool, and that the results of the procedure are useful as prior information in a Bayesian analysis.

How do you design randomised trials for smaller populations? A framework

How should we approach trial design when we can get some, but not all, of the way to the numbers required for a randomised phase III trial?We present an ordered framework for designing randomised trials to address the problem when the ideal sample size is considered larger than the number of participants that can be recruited in a reasonable time frame. Staying with the frequentist approach that is well accepted and understood in large trials, we propose a framework that includes small alterations to the design parameters. These aim to increase the numbers achievable and also potentially reduce the sample size target. The first step should always be to attempt to extend collaborations, consider broadening eligibility criteria and increase the accrual time or follow-up time. The second set of ordered considerations are the choice of research arm, outcome measures, power and target effect. If the revised design is still not feasible, in the third step we propose moving from two- to one-sided significance tests, changing the type I error rate, using covariate information at the design stage, re-randomising patients and borrowing external information.We discuss the benefits of some of these possible changes and warn against others. We illustrate, with a worked example based on the Euramos-1 trial, the application of this framework in designing a trial that is feasible, while still providing a good evidence base to evaluate a research treatment.This framework would allow appropriate evaluation of treatments when large-scale phase III trials are not possible, but where the need for high-quality randomised data is as pressing as it is for common diseases.

Alternative designs for clinical trials in rare diseases

Evidence-based medicine requires strong scientific evidence upon which to base treatment. In rare diseases, study populations are often small, and thus this evidence is difficult to accrue. Investigators, though, should be creative and develop a flexible toolkit of methods to deal with the problems inherent in the study of rare disease. This narrative review presents alternative clinical trial designs for studying treatments of rare diseases, including cross-over and n-of-1 trials, randomized placebo-phase design, enriched enrollment, randomized withdrawal design, and classes of adaptive designs. Examples of applications of these designs are presented along with their advantages and disadvantages. Additional analytical considerations such as Bayesian analysis, internal pilots, and use of biomarkers as surrogate outcomes are further discussed. A framework for selecting appropriate clinical trial design is proposed to guide investigators in the process of selecting alternative designs for rare diseases. © 2016 Wiley Periodicals, Inc.

A Bayesian adaptive design for clinical trials in rare diseases

Development of treatments for rare diseases is challenging due to the limited number of patients available for participation. Learning about treatment effectiveness with a view to treat patients in the larger outside population, as in the traditional fixed randomised design, may not be a plausible goal. An alternative goal is to treat the patients within the trial as effectively as possible. Using the framework of finite-horizon Markov decision processes and dynamic programming (DP), a novel randomised response-adaptive design is proposed which maximises the total number of patient successes in the trial and penalises if a minimum number of patients are not recruited to each treatment arm. Several performance measures of the proposed design are evaluated and compared to alternative designs through extensive simulation studies using a recently published trial as motivation. For simplicity, a two-armed trial with binary endpoints and immediate responses is considered. Simulation results for the proposed design show that: (i) the percentage of patients allocated to the superior arm is much higher than in the traditional fixed randomised design; (ii) relative to the optimal DP design, the power is largely improved upon and (iii) it exhibits only a very small bias and mean squared error of the treatment effect estimator. Furthermore, this design is fully randomised which is an advantage from a practical point of view because it protects the trial against various sources of bias. As such, the proposed design addresses some of the key issues that have been suggested as preventing so-called bandit models from being implemented in clinical practice.

Systematic reviews in paediatric multiple sclerosis and Creutzfeldt-Jakob disease exemplify shortcomings in methods used to evaluate therapies in rare conditions

BACKGROUND

Randomized controlled trials (RCTs) are the gold standard design of clinical research to assess interventions. However, RCTs cannot always be applied for practical or ethical reasons. To investigate the current practices in rare diseases, we review evaluations of therapeutic interventions in paediatric multiple sclerosis (MS) and Creutzfeldt-Jakob disease (CJD). In particular, we shed light on the endpoints used, the study designs implemented and the statistical methodologies applied.

METHODS

We conducted literature searches to identify relevant primary studies. Data on study design, objectives, endpoints, patient characteristics, randomization and masking, type of intervention, control, withdrawals and statistical methodology were extracted from the selected studies. The risk of bias and the quality of the studies were assessed.

RESULTS

Twelve (seven) primary studies on paediatric MS (CJD) were included in the qualitative synthesis. No double-blind, randomized placebo-controlled trial for evaluating interventions in paediatric MS has been published yet. Evidence from one open-label RCT is available. The observational studies are before-after studies or controlled studies. Three of the seven selected studies on CJD are RCTs, of which two received the maximum mark on the Oxford Quality Scale. Four trials are controlled observational studies.

CONCLUSIONS

Evidence from double-blind RCTs on the efficacy of treatments appears to be variable between rare diseases. With regard to paediatric conditions it remains to be seen what impact regulators will have through e.g., paediatric investigation plans. Overall, there is space for improvement by using innovative trial designs and data analysis techniques.

Trial design for evaluating novel treatments during an outbreak of an infectious disease

Tragically, the outbreak of Ebola that started in West Africa in 2014 has been far more extensive and damaging than any previous outbreaks. The duration of the outbreak has, for the first time, allowed the clinical evaluation of Ebola treatments. This article discusses the designs used for two such clinical trials which have recruited patients in Liberia and Sierra Leone. General principles are outlined for trial designs intended to be deployed quickly, adapt flexibly and provide results soon enough to influence the course of the current epidemic rather than just providing evidence for use should Ebola break out again. Lessons are drawn for the conduct of clinical research in future outbreaks of infectious diseases, where the sequence of events may or may not be similar to the West African Ebola epidemic.

Evidence, eminence and extrapolation

A full independent drug development programme to demonstrate efficacy may not be ethical and/or feasible in small populations such as paediatric populations or orphan indications. Different levels of extrapolation from a larger population to smaller target populations are widely used for supporting decisions in this situation. There are guidance documents in drug regulation, where a weakening of the statistical rigour for trials in the target population is mentioned to be an option for dealing with this problem. To this end, we propose clinical trials designs, which make use of prior knowledge on efficacy for inference. We formulate a framework based on prior beliefs in order to investigate when the significance level for the test of the primary endpoint in confirmatory trials can be relaxed (and thus the sample size can be reduced) in the target population while controlling a certain posterior belief in effectiveness after rejection of the null hypothesis in the corresponding confirmatory statistical test. We show that point‐priors may be used in the argumentation because under certain constraints, they have favourable limiting properties among other types of priors. The crucial quantity to be elicited is the prior belief in the possibility of extrapolation from a larger population to the target population. We try to illustrate an existing decision tree for extrapolation to paediatric populations within our framework. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Changing the Paradigm for the Treatment and Development of New Therapies for FSGS

Focal segmental glomerulosclerosis (FSGS) is a renal pathology finding that represents a constellation of rare kidney diseases, which manifest as proteinuria, edema nephrotic syndrome, hypertension, and increased risk for kidney failure. Therapeutic options for FSGS are reviewed displaying the expected efficacy from 25 to 69% depending on specific therapy, patient characteristics, cost, and common side effects. This variability in treatment response is likely caused, in part, by the heterogeneity in the etiology and active molecular mechanisms of FSGS. Clinical trials in FSGS have been scant in number and slow to recruit, which may stem, in part, from reliance on classic clinical trial design paradigms. Traditional clinical trial designs based on the "learn and confirm" paradigm may not be appropriate for rare diseases, such as FSGS. Future drug development and testing will require novel approaches to trial designs that have the capacity to enrich study populations and adapt the trial in a planned way to gain efficiencies in trial completion timelines. A clinical trial simulation is provided that compares a classical and more modern design to determine the maximum tolerated dose in FSGS.

Elicitation of expert prior opinion: application to the MYPAN trial in childhood polyarteritis nodosa

OBJECTIVES

Definitive sample sizes for clinical trials in rare diseases are usually infeasible. Bayesian methodology can be used to maximise what is learnt from clinical trials in these circumstances. We elicited expert prior opinion for a future Bayesian randomised controlled trial for a rare inflammatory paediatric disease, polyarteritis nodosa (MYPAN, Mycophenolate mofetil for polyarteritis nodosa).

METHODS

A Bayesian prior elicitation meeting was convened. Opinion was sought on the probability that a patient in the MYPAN trial treated with cyclophosphamide would achieve disease remission within 6-months, and on the relative efficacies of mycophenolate mofetil and cyclophosphamide. Expert opinion was combined with previously unseen data from a recently completed randomised controlled trial in ANCA associated vasculitis.

RESULTS

A pan-European group of fifteen experts participated in the elicitation meeting. Consensus expert prior opinion was that the most likely rates of disease remission within 6 months on cyclophosphamide or mycophenolate mofetil were 74% and 71%, respectively. This prior opinion will now be taken forward and will be modified to formulate a Bayesian posterior opinion once the MYPAN trial data from 40 patients randomised 1:1 to either CYC or MMF become available.

CONCLUSIONS

We suggest that the methodological template we propose could be applied to trial design for other rare diseases.

Takayasu arteritis in childhood: retrospective experience from a tertiary referral centre in the United Kingdom

Introduction

Takayasu arteritis (TA) is an idiopathic large-vessel vasculitis affecting the aorta and its major branches. Although the disease rarely affects children, it does occur, even in infants. The objective of this study was to evaluate the clinical features, disease activity, treatment and outcome of childhood TA in a tertiary UK centre.

Methods

We analysed a retrospective case series of children fulfilling the TA classification criteria of the European League against Rheumatism, the Paediatric Rheumatology European Society and the Paediatric Rheumatology International Trials Organisation. Data regarding demographics, clinical features, treatments and outcomes were recorded. Descriptive statistics are expressed as median and range. Fisher’s exact test was used for group comparisons. The Paediatric Vasculitis Activity Score (PVAS), Paediatric Vasculitis Damage Index (PVDI), Disease Extent Index-Takayasu (DEI.Tak) and Indian Takayasu Arteritis Activity Score (ITAS2010) were calculated retrospectively.

Results

A total of 11 children (64% female) with age at diagnosis of 11.8 (1.3 to 17) years were identified over a 23-year period. The median time to diagnosis was 17 (0 to 132) months. The most common clinical features at presentation were arterial hypertension (72.7%), systemic features (36%) and cardiovascular (45%), neurological (36%), pulmonary (27%), skin (9%), renal (9%) and gastrointestinal (9%) involvement. At presentation, PVAS was 5/63 (1 to 13); DEI.Tak was 7/81 (2 to 12) and ITAS2010 was 9/57 (6 to 20). Treatment included corticosteroids (81.8%), combined with methotrexate in most cases (72.7%). Cyclophosphamide (36.4%) and biologic agents (45.5%) were reserved for severe and/or refractory cases. PVDI at latest follow-up was 5.5/72 (3 to 15). Mortality was 27%. Young age at disease onset (<5 years old) and permanent PVDI scores ≥3 were significantly associated with mortality risk (P = 0.024).

Conclusion

TA is a rare and potentially life-threatening large-vessel vasculitis. Improved awareness of TA is essential to secure a timely diagnosis. Although the evidence base for the treatment of TA in children is weak, we found that it is essential to treat it aggressively because our data emphasise that the mortality and morbidity in the paediatric population remains high.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-015-0545-1) contains supplementary material, which is available to authorized users.

Bayesian methods for setting sample sizes and choosing allocation ratios in phase II clinical trials with time-to-event endpoints

Conventional phase II trials using binary endpoints as early indicators of a time-to-event outcome are not always feasible. Uveal melanoma has no reliable intermediate marker of efficacy. In pancreatic cancer and viral clearance, the time to the event of interest is short, making an early indicator unnecessary. In the latter application, Weibull models have been used to analyse corresponding time-to-event data. Bayesian sample size calculations are presented for single-arm and randomised phase II trials assuming proportional hazards models for time-to-event endpoints. Special consideration is given to the case where survival times follow the Weibull distribution. The proposed methods are demonstrated through an illustrative trial based on uveal melanoma patient data. A procedure for prior specification based on knowledge or predictions of survival patterns is described. This enables investigation into the choice of allocation ratio in the randomised setting to assess whether a control arm is indeed required. The Bayesian framework enables sample sizes consistent with those used in practice to be obtained. When a confirmatory phase III trial will follow if suitable evidence of efficacy is identified, Bayesian approaches are less controversial than for definitive trials. In the randomised setting, a compromise for obtaining feasible sample sizes is a loss in certainty in the specified hypotheses: the Bayesian counterpart of power. However, this approach may still be preferable to running a single-arm trial where no data is collected on the control treatment. This dilemma is present in most phase II trials, where resources are not sufficient to conduct a definitive trial.

Vasculitis in children

Primary systemic vasculitides of the young are relatively rare diseases, but are associated with significant morbidity and mortality, particularly if there is diagnostic delay. We provide an overview of paediatric vasculitides with emphasis on key differences in vasculitis presentation and management between children and adults. Significant advances in the field of paediatric vasculitis research include the development of classification criteria and disease outcome tools for paediatric disease; inclusion of paediatric patients in international multicentre randomized controlled trials of therapies in vasculitis; and development of rare disease trial designs for therapeutic trials of paediatric vasculitis. The continuation of unmet needs as well as the exploration of potential therapeutic avenues and considerations in the design of future trials are also discussed.