Statistical consideration when adding new arms to ongoing clinical trials: the potentials and the caveats.

BACKGROUND: Platform trials improve the efficiency of the drug development process through flexible features such as adding and dropping arms as evidence emerges. The benefits and practical challenges of implementing novel trial designs have been discussed widely in the literature, yet less consideration has been given to the statistical implications of adding arms. MAIN: We explain different statistical considerations that arise from allowing new research interventions to be added in for ongoing studies. We present recent methodology development on addressing these issues and illustrate design and analysis approaches that might be enhanced to provide robust inference from platform trials. We also discuss the implication of changing the control arm, how patient eligibility for different arms may complicate the trial design and analysis, and how operational bias may arise when revealing some results of the trials. Lastly, we comment on the appropriateness and the application of platform trials in phase II and phase III settings, as well as publicly versus industry-funded trials. CONCLUSION: Platform trials provide great opportunities for improving the efficiency of evaluating interventions. Although several statistical issues are present, there are a range of methods available that allow robust and efficient design and analysis of these trials

Optimized adaptive enrichment designs

Based on a Bayesian decision theoretic approach, we optimize frequentist single- and adaptive two-stage trial designs for the development of targeted therapies, where in addition to an overall population, a pre-defined subgroup is investigated. In such settings, the losses and gains of decisions can be quantified by utility functions that account for the preferences of different stakeholders. In particular, we optimize expected utilities from the perspectives both of a commercial sponsor, maximizing the net present value, and also of the society, maximizing cost-adjusted expected health benefits of a new treatment for a specific population. We consider single-stage and adaptive two-stage designs with partial enrichment, where the proportion of patients recruited from the subgroup is a design parameter. For the adaptive designs, we use a dynamic programming approach to derive optimal adaptation rules. The proposed designs are compared to trials which are non-enriched (i.e. the proportion of patients in the subgroup corresponds to the prevalence in the underlying population). We show that partial enrichment designs can substantially improve the expected utilities. Furthermore, adaptive partial enrichment designs are more robust than single-stage designs and retain high expected utilities even if the expected utilities are evaluated under a different prior than the one used in the optimization. In addition, we find that trials optimized for the sponsor utility function have smaller sample sizes compared to trials optimized under the societal view and may include the overall population (with patients from the complement of the subgroup) even if there is substantial evidence that the therapy is only effective in the subgroup

An alternative method to analyse the Biomarker-strategy design

Recent developments in genomics and proteomics enable the discovery of biomarkers that allow identification of subgroups of patients responding well to a treatment. One currently used clinical trial design incorporating a predictive biomarker is the so-called biomarker strategy design (or marker-based strategy design). Conventionally, the results from this design are analysed by comparing the mean of the biomarker-led arm with the mean of the randomised arm. Several problems regarding the analysis of the data obtained from this design have been identified in the literature. In this paper, we show how these problems can be resolved if the sample sizes in the subgroups fulfil the specified orthogonality condition. We also propose a novel analysis strategy that allows definition of test statistics for the biomarker-by-treatment interaction effect as well as for the classical treatment effect and the biomarker effect. We derive equations for the sample size calculation for the case of perfect and imperfect biomarker assays. We also show that the often used 1:1 randomisation does not necessarily lead to the smallest sample size. Application of the novel method is illustrated using a real data example

Variation of loads on a three-bladed horizontal axis tidal turbine with frequency and blade position

Sustainable and cost effective design for tidal current turbines requires knowledge of the complex nature of unsteady loads on turbine components including blades, rotor and support structure. This study investigates experimentally the variation with frequency of rotor thrust and torque loads, of streamwise root bending moment on individual blades and of loads on foundation at the bed. Comparisons between these different load spectra are also established. The impact of absolute rotor angular position on blade and rotor thrust loads is also examined. The study is based on measurements from a 1/15 scale, three-bladed, horizontal axis machine tested in a recirculating flume, in onset flows of 3% and 12% turbulence intensity. It is found that for frequencies below the rotational frequency, load spectra are correlated to spectral density of the onset flow velocity. Above the rotational frequency, loads are mainly affected by turbine operation phenomena. The tower shadowing effect is clearly identified through frequency and angular analysis. Finally, thrust loads as experienced by the rotor alone are for the first time compared with streamwise and transverse foundation loads. Higher frequency loads experienced by the tower are shown to be affected by different vortex shedding regimes associated with different regions of the wake. All the experimental measurements presented in this article can be accessed from http://dx.doi.org/10.7488/ds/2423

Evaluation of the effectiveness and cost-effectiveness of Families for Health V2 for the treatment of childhood obesity : study protocol for a randomized controlled trial

Background: Effective programs to help children manage their weight are required. Families for Health focuses on a parenting approach, designed to help parents develop their parenting skills to support lifestyle change within the family. Families for Health V1 showed sustained reductions in overweight after 2 years in a pilot evaluation, but lacks a randomized controlled trial (RCT) evidence base. Methods/design: This is a multi-center, investigator-blind RCT, with parallel economic evaluation, with a 12-month follow-up. The trial will recruit 120 families with at least one child aged 6 to 11 years who is overweight (≥91st centile BMI) or obese (≥98th centile BMI) from three localities and assigned randomly to Families for Health V2 (60 families) or the usual care control (60 families) groups. Randomization will be stratified by locality (Coventry, Warwickshire, Wolverhampton). Families for Health V2 is a family-based intervention run in a community venue. Parents/carers and children attend parallel groups for 2.5 hours weekly for 10 weeks. The usual care arm will be the usual support provided within each NHS locality. A mixed-methods evaluation will be carried out. Child and parent participants will be assessed at home visits at baseline, 3-month (post-treatment) and 12-month follow-up. The primary outcome measure is the change in the children’s BMI z-scores at 12 months from the baseline. Secondary outcome measures include changes in the children’s waist circumference, percentage body fat, physical activity, fruit/vegetable consumption and quality of life. The parents’ BMI and mental well-being, family eating/activity, parent–child relationships and parenting style will also be assessed. Economic components will encompass the measurement and valuation of service utilization, including the costs of running Families for Health and usual care, and the EuroQol EQ-5D health outcomes. Cost-effectiveness will be expressed in terms of incremental cost per quality-adjusted life year gained. A de novo decision-analytic model will estimate the lifetime cost-effectiveness of the Families for Health program. Process evaluation will document recruitment, attendance and drop-out rates, and the fidelity of Families for Health delivery. Interviews with up to 24 parents and children from each arm will investigate perceptions and changes made. Discussion: This paper describes our protocol to assess the effectiveness and cost-effectiveness of a parenting approach for managing childhood obesity and presents challenges to implementation. Trial registration: Current Controlled Trials ISRCTN4503220

An evaluation of the fixed concentration procedure for assessment of acute inhalation toxicity

Acute inhalation studies are conducted in animals as part of chemical hazard identification and for classification and labelling. Current methods employ death as an endpoint (OECD TG403 and TG436) while the recently approved fixed concentration procedure (FCP) (OECD TG433) uses fewer animals and replaces lethality as an endpoint with evident toxicity. Evident toxicity is the presence of clinical signs that predict that exposure to the next highest concentration will cause severe toxicity or death in most animals. Approval of TG433 was the result of an international initiative, led by the National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs), which collected data from six laboratories on clinical signs recorded for inhalation studies on 172 substances. This paper summarises previously published data and describes the additional analyses of the dataset that were essential for approval of the TG

Efficient Adaptive Designs for Clinical Trials of Interventions for COVID-19.

The COVID-19 pandemic has led to an unprecedented response in terms of clinical research activity. An important part of this research has been focused on randomized controlled clinical trials to evaluate potential therapies for COVID-19. The results from this research need to be obtained as rapidly as possible. This presents a number of challenges associated with considerable uncertainty over the natural history of the disease and the number and characteristics of patients affected, and the emergence of new potential therapies. These challenges make adaptive designs for clinical trials a particularly attractive option. Such designs allow a trial to be modified on the basis of interim analysis data or stopped as soon as sufficiently strong evidence has been observed to answer the research question, without compromising the trial's scientific validity or integrity. In this article, we describe some of the adaptive design approaches that are available and discuss particular issues and challenges associated with their use in the pandemic setting. Our discussion is illustrated by details of four ongoing COVID-19 trials that have used adaptive designs

Centerscope

Centerscope, formerly Scope, was published by the Boston University Medical Center "to communicate the concern of the Medical Center for the development and maintenance of improved health care in contemporary society.

Measuring the impact and costs of a universal group based parenting programme : protocol and implementation of a trial

Background Sub-optimal parenting is a common risk factor for a wide range of negative health, social and educational outcomes. Most parenting programmes have been developed in the USA in the context of delinquency prevention for targeted or indicated groups and the main theoretical underpinning for these programmes is behaviour management. The Family Links Nurturing Programme (FLNP) focuses on family relationships as well as behaviour management and is offered on a universal basis. As a result it may be better placed to improve health and educational outcomes. Developed in the UK voluntary sector, FLNP is popular with practitioners, has impressed policy makers throughout the UK, has been found to be effective in before/after and qualitative studies, but lacks a randomised controlled trial (RCT) evidence base. Methods/Design A multi-centre, investigator blind, randomised controlled trial of the FLNP with a target sample of 288 south Wales families who have a child aged 2-4 yrs living in or near to Flying Start/Sure Start areas. Changes in parenting, parent child relations and parent and child wellbeing are assessed with validated measures immediately and at 6 months post intervention. Economic components include cost consequences and cost utility analyses based on parental ranking of states of quality of life. Attendance and completion rates and fidelity to the FLNP course delivery are assessed. A nested qualitative study will assess reasons for participation and non-participation and the perceived value of the programme to families. By the end of May 2010, 287 families have been recruited into the trial across four areas of south Wales. Recruitment has not met the planned timescales with barriers including professional anxiety about families entering the control arm of the trial, family concern about video and audio recording, programme facilitator concern about the recording of FLNP sessions for fidelity purposes and delays due to the new UK research governance procedures. Discussion Whilst there are strong theoretical arguments to support universal provision of parenting programmes, few universal programmes have been subjected to randomised controlled trials. In this paper we describe a RCT protocol with quantitative and qualitative outcome measures and an economic evaluation designed to provide clear evidence with regard to effectiveness and costs. We describe challenges implementing the protocol and how we are addressing these