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

Are the Current Processes and Regulations Fit for Purpose to Deliver Novel Therapies During Pandemics? A Perspective on COVID-19 from the UK

The COVID-19 pandemic was the first ‘stress test’ to assess whether the current regulations in the United Kingdom (UK) are fit for purpose to develop novel therapies during pandemics. It saw innovations and collaborations across the spectrum of the drug development and regulatory pathways, including extraordinary collaborations between the various stakeholders involved in the process, the repositioning of medicines, the deployment of multi-arm, multi-interventional adaptive trials, the institution of operational simplicity and flexibility across various trial activities, and regulatory innovations. The question arises whether the innovative flexibilities and the urgency that were instituted could have resulted in compromises to the integrity of the process. An assessment of the conduct of the RECOVERY trial and the speedy approval of dexamethasone by the UK Medicines and Healthcare products Regulatory Agency demonstrates that no compromises were made to the ethical and scientific integrity of the process. Lessons learnt could be applied for future pandemics and to enhance R&D productivity and contribute to global health by improving access to medicines, especially in low- and middle-income countries and for neglected or rare diseases. What is needed is not a major transformation in the process but the flexible adaptation of existing regulations to reduce bureaucracy and handover times. Arriving at an optimal balance between scientific standards, regulations and commercial conflicts of interest will pose considerable challenges but what the COVID-19 pandemic has shown is that where there is will, there is always a way.

Paediatric surgical trials, their fragility index, and why to avoid using it to evaluate results

BACKGROUND

The fragility index has been gaining ground in the evaluation of comparative clinical studies. Many scientists evaluated trials in their fields and deemed them to be fragile, although there is no consensus on the definition of fragility. We aimed to calculate the fragility index and its permutations for paediatric surgical trials.

METHODS

We searched pubmed for prospectively conducted paediatric surgical trials with intervention and control group without limitations and calculated their (reverse) fragility indices and respective quotients along with posthoc-power. Relationships between variables were evaluated using Spearman's ρ. We also calculated S values by negative log transformation base-2 of P values.

RESULTS

Of 516 retrieved records, we included 87. The median fragility index was 1.5 (interquartile range: 0-4) and the median reverse fragility index was 3 (interquartile range: 2-4), although they were statistically not different (Mood's test: χ² = 0.557, df = 1, P = 0.4556). P values and fragility indices were strongly inversely correlated (ρ = - 0.71, 95% confidence interval: - 0.53 to - 0.85, P < 0.0001), while reverse fragility indices were moderately correlated to P values (ρ = 0.5, 95% confidence interval: 0.37-0.62, P < 0.0001). A fragility index of 1 resulted from P values between 0.039 and 0.003, which resulted in S values between 4 and 8.

CONCLUSIONS

Fragility indices, reverse fragility indices, and their respective fragility quotients of paediatric surgical trials are low. The fragility index can be viewed as no more than a transformed P value with even more substantial limitations. Its inherent penalisation of small studies irrespective of their clinical relevance is particularly harmful for paediatric surgery. Consequently, the fragility index should be avoided.

Designing clinically useful psychopharmacological trials: challenges and ways forward

The clinical guidelines that underpin the use of drugs for mental disorders are informed by evidence from randomised controlled trials (RCTs). RCTs are performed to obtain marketing authorisation from regulators. The methods used in these RCTs could be appropriate for early phases of drug development because they identify drugs with important harms and drugs that are efficacious for specific health problems and populations. RCTs done before marketing authorisation do not tend to address clinical questions that concern the effectiveness of a drug in heterogeneous and comorbid populations, the optimisation of drug sequencing and discontinuation, or the comparative benefits and harms of different drugs that could be used for the same health problem. This Review proposes an overview of some shortcomings of RCTs, at an individual level and at the whole portfolio level, and identifies some methods in planning, conducting, and carrying out analyses in RCTs that could enhance their ability to support therapeutic decisions. These suggestions include: identifying patient-important questions to be investigated by psychopharmacological RCTs; embedding pragmatic RCTs within clinical practice to improve generalisability to target populations; collecting evidence about drugs in overlooked populations; developing methods to facilitate the recruitment of patients with mental disorders and to reduce the number of patients who drop out, using specific methods; using core outcome sets to standardise the assessment of benefits and harms; and recording systematically serious objective outcomes, such as suicide or hospitalisation, to be evaluated in meta-analyses. This work is a call to address questions relevant to patients using diverse design of RCTs, thus contributing to the development of a patient-centred, evidence-based psychiatry.

Blinding of study statisticians in clinical trials: a qualitative study in UK clinical trials units

Background

Blinding is an established approach in clinical trials which aims to minimise the risk of performance and detection bias. There is little empirical evidence to guide UK clinical trials units (CTUs) about the practice of blinding statisticians. Guidelines recommend that statisticians remain blinded to allocation prior to the final analysis. As these guidelines are not based on empirical evidence, this study undertook a qualitative investigation relating to when and how statisticians should be blinded in clinical trials.

Methods

Data were collected through online focus groups with various stakeholders who work in the delivery and oversight of clinical trials. Recordings of the focus groups were transcribed verbatim and thematic analysis was used to analyse the transcripts.

Results

Thirty-seven participants from 19 CTUs participated in one of six focus groups. Four main themes were identified, namely statistical models of work, factors affecting the decision to blind statisticians, benefits of blinding/not blinding statisticians and practicalities. Factors influencing the decision to blind the statistician included available resources, study design and types of intervention and outcomes and analysis.

Although blinding of the statistician is perceived as a desirable mitigation against bias, there was uncertainty about the extent to which an unblinded statistician might impart bias. Instead, in most cases, the insight that the statistician offers was deemed more important to delivery of a trial than the risk of bias they may introduce if unblinded.

Blinding of statisticians was only considered achievable with the appropriate resource and staffing, which were not always available. In many cases, a standard approach to blinding was therefore considered unrealistic and impractical; hence the need for a proportionate risk assessment approach identifying possible mitigations.

Conclusions

There was wide variation in practice between UK CTUs regarding the blinding of trial statisticians. A risk assessment approach would enable CTUs to identify risks associated with unblinded statisticians conducting the final analysis and alternative mitigation strategies. The findings of this study will be used to design guidance and a tool to support this risk assessment process.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-022-06481-9.

Using surrogate information to improve confirmatory platform trial with sample size re-estimation

Platform design which allows exploring multiple arms with a common control simultaneously is becoming essential for efficient drug development. However, one of the critical challenges for confirmatory platform trials is immature data for interim decisions, particularly for the treatment arm selection and sample size determination with limited data available. We use a modified conditional power (CP) for both treatment arm selection and sample size determination at interim analysis for the proposed platform trial. The modified CP uses the available data from both primary and surrogate endpoints. We also demonstrated the application in a case study of a lung cancer trial.

Great Expectations: recommendations for improving the methodological rigor of psychedelic clinical trials

RATIONALE

Psychedelic research continues to garner significant public and scientific interest with a growing number of clinical studies examining a wide range of conditions and disorders. However, expectancy effects and effective condition masking have been raised as critical limitations to the interpretability of the research.

OBJECTIVE

In this article, we review the many methodological challenges of conducting psychedelic clinical trials and provide recommendations for improving the rigor of future research.

RESULTS

Although some challenges are shared with psychotherapy and pharmacology trials more broadly, psychedelic clinical trials have to contend with several unique sources of potential bias. The subjective effects of a high-dose psychedelic are often so pronounced that it is difficult to mask participants to their treatment condition; the significant hype from positive media coverage on the clinical potential of psychedelics influences participants' expectations for treatment benefit; and participant unmasking and treatment expectations can interact in such a way that makes psychedelic therapy highly susceptible to large placebo and nocebo effects. Specific recommendations to increase the success of masking procedures and reduce the influence of participant expectancies are discussed in the context of study development, participant recruitment and selection, incomplete disclosure of the study design, choice of active placebo condition, as well as the measurement of participant expectations and masking efficacy.

CONCLUSION

Incorporating the recommended design elements is intended to reduce the risk of bias in psychedelic clinical trials and thereby increases the ability to discern treatment-specific effects of psychedelic therapy.

Mapping ongoing nutrition intervention trials in muscle, sarcopenia, and cachexia: a scoping review of future research

Muscle loss alone, or in the context of sarcopenia or cachexia, is a prevalent condition and a predictor of negative outcomes in aging and disease. As adequate nutrition is essential for muscle maintenance, a growing number of studies has been conducted to explore the role of specific nutrients on muscle mass or function. Nonetheless, more research is needed to guide evidence-based recommendations. This scoping review aimed to compile and document ongoing clinical trials investigating nutrition interventions as a strategy to prevent or treat low muscle mass or function (strength and physical performance), sarcopenia, or cachexia. ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform were searched up to 21 April 2021 for planned and ongoing trials. Randomized controlled trials with ≥20 participants per arm were included based on intent to explore the effects of nutrition interventions on muscle-related outcomes (i.e. muscle mass or strength, physical performance, or muscle synthesis rate) in both clinical and non-clinical conditions (i.e. aging). Two reviewers independently screened records for eligibility, and a descriptive synthesis of trials characteristics was conducted. A total of 113 trials were included in the review. Most trials (69.0%) enroll adults with clinical conditions, such as cancer (19.5%), obesity and metabolic diseases (16.8%), and musculoskeletal diseases (10.7%). The effects of nutrition interventions on age-related muscle loss are explored in 31% of trials. Although nutrition interventions of varied types were identified, food supplements alone (48.7%) or combined with dietary advice (11.5%) are most frequently reported. Protein (17.7%), amino acids (10.6%), and β-hydroxy-β-methylbutyrate (HMB, 6.2%) are the top three food supplements' nutrients under investigation. Primary outcome of most trials (54.9%) consists of measures of muscle mass alone or in combination with muscle strength and/or performance (as either primary or secondary outcomes). Muscle strength and physical performance are primary outcomes of 38% and 31.9% of the trials, respectively. These measurements were obtained using a variety of techniques. Only a few trials evaluate muscle synthesis rate either as a primary or secondary outcome (5.3%). Several nutrition studies focusing on muscle, sarcopenia, and cachexia are underway and can inform future research in this area. Although many trials have similar type of interventions, methodological heterogeneity may challenge study comparisons, and future meta-analyses aiming to provide evidence-based recommendations. Upcoming research in this area may benefit from guidelines for the assessment of therapeutic effects of nutrition interventions.

Effects of β-hydroxy β-methylbutyrate (HMB) supplementation on muscle mass, function, and other outcomes in patients with cancer: a systematic review

Low muscle mass is prevalent among patients with cancer and a predictor of adverse clinical outcomes. To counteract muscle loss, β-hydroxy β-methylbutyrate (HMB) supplementation has been proposed as a potential therapy for older adults and various diseases states. This systematic review aimed to investigate the effects and safety of HMB supplementation in relation to muscle mass and function and other clinical outcomes in patients with cancer. A systematic search of MEDLINE, CINAHL, Embase, Cochrane Central Register of Controlled Trials, Scopus, ProQuest, and grey literature for reports published from inception to December 2021 was conducted. Included studies provided supplements containing any dose of HMB to adult patients with active cancer. A synthesis without meta-analysis was conducted using a vote-counting approach based solely on the direction of the effect (i.e. regardless of statistical significance). Risk of bias was assessed for each outcome domain, and evidence from higher-quality studies (i.e. those with either low or moderate risk of bias) was examined. Safety was evaluated using both lower-quality and higher-quality studies. Fifteen studies were included, in which six were randomized controlled trials in patients with various cancer types and treatments. Studies prescribed HMB combined with amino acids (73.3%), HMB in oral nutritional supplements (20.0%), or both supplement types (6.7%); Ca-HMB doses of 3.0 g/day were provided in 80.0% of the studies. Four studies had high risk of bias across all outcome domains. Considering the higher-quality studies, evidence of a beneficial effect of HMB supplementation was found in four of four studies for muscle mass, two of two for muscle function, three of three for hospitalization, and five of seven for survival. In contrast, no beneficial effects of HMB on quality of life or body weight was found in two of four and three of five studies, respectively. A limited number of higher-quality studies evaluating the impact of HMB on cancer therapy-related toxicity, inflammation, and tumour response were observed. No serious adverse effects directly related to the nutrition intervention were reported. Although limited, current evidence suggests that HMB supplementation has a beneficial effect on muscle mass and function in patients with cancer. Well-designed trials are needed to further explore the clinical benefit of HMB supplementation in this patient population.

Mathematical Modelling for Optimal Vaccine Dose Finding: Maximising Efficacy and Minimising Toxicity

Vaccination is a key tool to reduce global disease burden. Vaccine dose can affect vaccine efficacy and toxicity. Given the expense of developing vaccines, optimising vaccine dose is essential. Mathematical modelling has been suggested as an approach for optimising vaccine dose by quantitatively establishing the relationships between dose and efficacy/toxicity. In this work, we performed simulation studies to assess the performance of modelling approaches in determining optimal dose. We found that the ability of modelling approaches to determine optimal dose improved with trial size, particularly for studies with at least 30 trial participants, and that, generally, using a peaking or a weighted model-averaging-based dose–efficacy relationship was most effective in finding optimal dose. Most methods of trial dose selection were similarly effective for the purpose of determining optimal dose; however, including modelling to adapt doses during a trial may lead to more trial participants receiving a more optimal dose. Clinical trial dosing around the predicted optimal dose, rather than only at the predicted optimal dose, may improve final dose selection. This work suggests modelling can be used effectively for vaccine dose finding, prompting potential practical applications of these methods in accelerating effective vaccine development and saving lives.

Characteristics of Early Phase Clinical Trials for Rare Cancers: Insights From Interviews With Stakeholders

Background: Rare cancers occur with an incidence of no more than six cases per 100,000 people according to the definition used by the Surveillance of Rare Cancers in Europe project. For a variety of reasons (low prevalence, cytotoxicity), it is challenging to perform the necessary clinical studies to investigate the safety and efficacy of investigational medicines against such rare malignancies, reformulating even at the earliest stages of the drug development process. This article investigates the differences between phase I rare cancer trials performed in commercial (companies) and non-commercial settings (academic hospitals).

Materials and Methods: The differences were explored through the conduct of semi-structured interviews with three different stakeholder groups: representatives from academia (n = 7), representatives from companies (n = 4) and representatives from patient organizations (n = 4). All the interviews were transcribed verbatim and analyzed in NVivo using the framework method.

Results: According to the interviewees, the academic and commercial stakeholders collaborate in the majority of phase I rare cancer trials. In general, the commercial partner finances the trial, whereas academia is responsible for the execution of the study procedures. The average cost of undertaking these trials is difficult to estimate because it depends on what is specifically requested during the trial. The 3 + 3 study design remains the most widely used design and the use of expansion cohorts is controversial. With regard to the regulatory aspects of phase I rare cancer trials, it was expressed that a good regulatory framework facilitates the conduct of these studies, but that increased regulation and oversight also has drawbacks, e.g., differences in standards between different ethics committees, over interpretation of the rules, insufficient availability of qualified personnel and higher workloads. The patient organization representatives claimed that patients experience no differences in terms of accommodation, compensation and paperwork between the academic and commercial settings or the degree of follow-up. They also believed that the direct input of patients can bring added value to such studies not only with regard to the recruitment process and the feasibility of the study but also the legibility of the informed consent forms.

Conclusion: The growing need for first-in-man trials in rare malignancies needs to be highlighted, as difficult as they are to undertake and to co-develop, not only because rare cancer patients deserve an appropriate treatment, but also because these medicines represent the future of cancer therapy in the precision medicine era. Cooperation of commercial and academic sites are needed. Patient organizations need to be educated to take part in this process.

When is a two-stage single-arm trial efficient? An evaluation of the impact of outcome delay

BACKGROUND

Simon's two-stage design is a widely used adaptive design, particularly in phase II oncology trials due to its simplicity and efficiency. However, its efficiency can be adversely affected when the primary end-point takes time to observe, as is common in practice.

METHODS

We propose an optimal design, taking the delay in observing treatment outcome into consideration and compare the efficiency gained from using Simon's design over a single-stage design for real-life oncology trials. Based on the results, we provide a general rule-of-thumb for determining whether a two-stage single-arm design can provide any added advantage over a single-stage design, given the recruitment rate and primary end-point length.

RESULTS

We observed an average 15-30% loss in the estimated efficiency gain in real oncology trials that used Simon's design due to the delay in observing the treatment outcome. The delay-optimal design provides some advantage over Simon's design in terms of reduced sample size when the delay is large compared to the recruitment length.

DISCUSSION

Simon's two-stage design provides large benefit over a single-stage design, in terms of reduced sample size, when the primary end-point length is no more than 10% of the total recruitment time. It provides no efficiency advantage when this ratio is above 50%.

Adaptive Designs: Benefits and Cautions for Neurosurgery Trials

BACKGROUND

It is well accepted that randomized controlled trials provide the greatest quality of evidence about effectiveness and safety of new interventions. In neurosurgery, randomized controlled trials face challenges, with their use remaining relatively low compared with other clinical areas. Adaptive designs have emerged as a method for improving the efficiency and patient benefit of trials. They allow modifications to the trial design to be made as patient outcome data are collected. The benefit they provide is highly variable, predominantly governed by the time taken to observe the primary endpoint compared with the planned recruitment rate. They also face challenges in design, conduct, and reporting.

METHODS

We provide an overview of the benefits and challenges of adaptive designs, with a focus on neurosurgery applications. To investigate how often an adaptive design may be advantageous in neurosurgery, we extracted data on recruitment rates and endpoint lengths for ongoing neurosurgery trials registered in ClinicalTrials.gov.

RESULTS

We found that a majority of neurosurgery trials had a relatively short endpoint length compared with the planned recruitment period and therefore may benefit from an adaptive trial. However, we did not identify any ongoing ClinicalTrials.gov registered neurosurgery trials that mentioned using an adaptive design.

CONCLUSIONS

Adaptive designs may provide benefits to neurosurgery trials and should be considered for use more widely. Use of some types of adaptive design, such as multiarm multistage, may further increase the number of interventions that can be tested with limited patient and financial resources.

How to Study the Brain While Anesthetizing It?! A Scoping Review on Running Neuroanesthesiologic Studies and Trials That Include Neurosurgical Patients

This scoping review addresses the challenges of neuroanesthesiologic research: the population, the methods/treatment/exposure, and the outcome/results. These challenges are put into the context of a future research agenda for peri-/intraoperative anesthetic management, neurocritical care, and applied neurosciences. Finally, the opportunities of adaptive trial design in neuroanesthesiologic research are discussed.

An alternative metric for evaluating the potential patient benefit of response-adaptive randomization procedures

When planning a two-arm group sequential clinical trial with a binary primary outcome that has severe implications for quality of life (e.g., mortality), investigators may strive to find the design that maximizes in-trial patient benefit. In such cases, Bayesian response-adaptive randomization (BRAR) is often considered because it can alter the allocation ratio throughout the trial in favor of the treatment that is currently performing better. Although previous studies have recommended using fixed randomization over BRAR based on patient benefit metrics calculated from the realized trial sample size, these previous comparisons have been limited by failures to hold type I and II error rates constant across designs or consider the impacts on all individuals directly affected by the design choice. In this paper, we propose a metric for comparing designs with the same type I and II error rates that reflects expected outcomes among individuals who would participate in the trial if enrollment is open when they become eligible. We demonstrate how to use the proposed metric to guide the choice of design in the context of two recent trials in persons suffering out of hospital cardiac arrest. Using computer simulation, we demonstrate that various implementations of group sequential BRAR offer modest improvements with respect to the proposed metric relative to conventional group sequential monitoring alone. This article is protected by copyright. All rights reserved.

Evaluating enrollment and outcome criteria in trials of biologics for chronic rhinosinusitis with nasal polyps

OBJECTIVE

Treatment for chronic rhinosinusitis with nasal polyps (CRSwNP) generally involves intranasal corticosteroids (INCS) and saline irrigation, followed by short courses of systemic corticosteroids (SCS) or surgery with postoperative medical therapy for patients who do not respond to INCS. However, both SCS use and surgery are associated with a range of adverse effects or complications, have a high recurrence rate, and are unsuitable for some patients. Biologics targeting the underlying pathophysiology are promising treatment alternatives for these patients. Dupilumab, omalizumab, and mepolizumab are approved for use in patients with severe, uncontrolled CRSwNP. However, the lack of a consistent definition of severe CRSwNP makes the decision to initiate biologic treatment particularly complex. Furthermore, the position of each biologic in the overall management of CRSwNP remains to be clarified.

DATA SOURCES

Publications reporting results of phase III trials of dupilumab, omalizumab, mepolizumab, and benralizumab in the treatment of CRSwNP.

STUDY SELECTIONS

Randomized, controlled phase III trials of biologics approved for CRSwNP.

RESULTS

These trials all used different enrollment criteria. We discuss the complexities of assessing CRSwNP disease severity and highlight how these impact comparisons of the populations and outcomes of the phase III biologic trials.

CONCLUSION

To position biologic agents appropriately within the existing CRSwNP treatment paradigm, future trials will need to include comparable patient populations and standardized outcome measures. Such trials will help to ensure that biologic treatment is targeted appropriately to support optimal clinical outcomes.

Sputum lipoarabinomannan (LAM) as a biomarker to determine sputum mycobacterial load: exploratory and model-based analyses of integrated data from four cohorts

Background

Despite the high global disease burden of tuberculosis (TB), the disease caused by Mycobacterium tuberculosis (Mtb) infection, novel treatments remain an urgent medical need. Development efforts continue to be hampered by the reliance on culture-based methods, which often take weeks to obtain due to the slow growth rate of Mtb. The availability of a “real-time” measure of treatment efficacy could accelerate TB drug development. Sputum lipoarabinomannan (LAM; an Mtb cell wall glycolipid) has promise as a pharmacodynamic biomarker of mycobacterial sputum load.

Methods

The present analysis evaluates LAM as a surrogate for Mtb burden in the sputum samples from 4 cohorts of a total of 776 participants. These include those from 2 cohorts of 558 non-TB and TB participants prior to the initiation of treatment (558 sputum samples), 1 cohort of 178 TB patients under a 14-day bactericidal activity trial with various mono- or multi-TB drug therapies, and 1 cohort of 40 TB patients with data from the first 56-day treatment of a standard 4-drug regimen.

Results

Regression analysis demonstrated that LAM was a predictor of colony-forming unit (CFU)/mL values obtained from the 14-day treatment cohort, with well-estimated model parameters (relative standard error ≤ 22.2%). Moreover, no changes in the relationship between LAM and CFU/mL were observed across the different treatments, suggesting that sputum LAM can be used to reasonably estimate the CFU/mL in the presence of treatment. The integrated analysis showed that sputum LAM also appears to be as good a predictor of time to Mycobacteria Growth Incubator Tube (MGIT) positivity as CFU/mL. As a binary readout, sputum LAM positivity is a strong predictor of solid media or MGIT culture positivity with an area-under-the-curve value of 0.979 and 0.976, respectively, from receiver-operator curve analysis.

Conclusions

Our results indicate that sputum LAM performs as a pharmacodynamic biomarker for rapid measurement of Mtb burden in sputum, and thereby may enable more efficient early phase clinical trial designs (e.g., adaptive designs) to compare candidate anti-TB regimens and streamline dose selection for use in pivotal trials.

Trial registration NexGen EBA study (NCT02371681)

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07308-3.

Uptake of the multi-arm multi-stage (MAMS) adaptive platform approach: a trial-registry review of late-phase randomised clinical trials

BACKGROUND

For medical conditions with numerous interventions worthy of investigation, there are many advantages of a multi-arm multi-stage (MAMS) platform trial approach. However, there is currently limited knowledge on uptake of the MAMS design, especially in the late-phase setting. We sought to examine uptake and characteristics of late-phase MAMS platform trials, to enable better planning for teams considering future use of this approach.

DESIGN

We examined uptake of registered, late-phase MAMS platforms in the EU clinical trials register, Australian New Zealand Clinical Trials Registry, International Standard Randomised Controlled Trial Number registry, Pan African Clinical Trials Registry, WHO International Clinical Trial Registry Platform and databases: PubMed, Medline, Cochrane Library, Global Health Library and EMBASE. Searching was performed and review data frozen on 1 April 2021. MAMS platforms were defined as requiring two or more comparison arms, with two or more trial stages, with an interim analysis allowing for stopping of recruitment to arms and typically the ability to add new intervention arms.

RESULTS

62 late-phase clinical trials using an MAMS approach were included. Overall, the number of late-phase trials using the MAMS design has been increasing since 2001 and been accelerated by COVID-19. The majority of current MAMS platforms were either targeting infectious diseases (52%) or cancers (29%) and all identified trials were for treatment interventions. 89% (55/62) of MAMS platforms were evaluating medications, with 45% (28/62) of the MAMS platforms having at least one or more repurposed medication as a comparison arm.

CONCLUSIONS

Historically, late-phase trials have adhered to long-established standard (two-arm) designs. However, the number of late-phase MAMS platform trials is increasing, across a range of different disease areas. This study highlights the potential scope of MAMS platform trials and may assist research teams considering use of this approach in the late-phase randomised clinical trial setting.

PROSPERO REGISTRATION NUMBER

CRD42019153910.

A transition to the AASM recommended hypopnea definition in adults: initiatives of the Hypopnea Scoring Rule Task Force

The American Academy of Sleep Medicine (AASM) recommends that hypopneas be identified using a definition that is based on a ≥30% decrease in airflow associated with a ≥3% reduction in the oxygen saturation or an arousal (H3A) for diagnosis of obstructive sleep apnea (OSA) in adults. This conflicts with the Centers for Medicare and Medicaid Services (CMS) definition, which requires a ≥4% decrease in the oxygen saturation to identify a hypopnea (H4) and does not acknowledge arousals. In 2018, the AASM board of directors constituted a Hypopnea Scoring Rule Task Force (HSRTF) with a mandate to "create a strategy for adoption and implementation of the AASM recommended adult hypopnea scoring criteria among members, payers and device manufacturers." The task force initiated several activities including a survey of AASM accredited laboratories and discussions with polysomnography software vendors. Survey results indicated that most laboratories scored polysomnograms using only the CMS definition. Vendors indicated that they could easily support dual scoring. Informal testing among task force members' laboratories confirmed there would be little additional work if dual scoring was performed. The task force convened several meetings of a working group of OSA content experts and interested parties, with the purpose of creating research recommendations to study the impact on relevant clinical outcomes using the different definitions of hypopnea. Several possible prospective and retrospective approaches were discussed with emphasis on the group of patients diagnosed with OSA based on an apnea-hypopnea index (AHI) using H3A but NOT H4. Based on the deliberations of the working group, the HSRTF submitted recommendations to the AASM Foundation concerning research project strategies for potential grant funding. Further discussions within the HSRTF focused on developing advocacy initiatives among patient stakeholder groups to change payer policy.

Year-to-year variation in attack rates could result in underpowered RSV vaccine efficacy trials

OBJECTIVE

Year-to-year variation of respiratory viruses may result in lower attack rates than expected. We aimed to illustrate the impact of year-to-year variation in attack rates on the likelihood of demonstrating vaccine efficacy (VE) .

STUDY DESIGN AND SETTING

We considered an individually randomized maternal vaccine trial against respiratory syncytial virus-associated hospitalisations (RSVH). For 10 RSVH per 1,000 infants, sample size to have 80% power for true VE of 50% and 70% was 9,846 and 4,424 participants. We reported power to show VE for varying attack rates, selected to reflect realistic year-to-year variation using observational studies. Eight scenarios including varying number of countries and seasons were developed to assess the influence of these trial parameters.

RESULTS

Including up to three seasons decreased the width of the interquartile range for power. Including more seasons concentrated statistical power closer to 80%. Least powered trials had higher statistical power with more seasons. In all scenarios, at least half of the trials had <80% power. For three-season trials, increasing the sample size by 10% reduced the percentage of underpowered trials to less than one-quarter of trials.

CONCLUSION

Year-to-year variation in RSV attack rates should be accounted for during trial design. Mitigation strategies include recruiting over more seasons, or adaptive trial designs.

Adaptive treatment allocation and selection in multi-arm clinical trials: a Bayesian perspective

BACKGROUND

Adaptive designs offer added flexibility in the execution of clinical trials, including the possibilities of allocating more patients to the treatments that turned out more successful, and early stopping due to either declared success or futility. Commonly applied adaptive designs, such as group sequential methods, are based on the frequentist paradigm and on ideas from statistical significance testing. Interim checks during the trial will have the effect of inflating the Type 1 error rate, or, if this rate is controlled and kept fixed, lowering the power.

RESULTS

The purpose of the paper is to demonstrate the usefulness of the Bayesian approach in the design and in the actual running of randomized clinical trials during phase II and III. This approach is based on comparing the performance of the different treatment arms in terms of the respective joint posterior probabilities evaluated sequentially from the accruing outcome data, and then taking a control action if such posterior probabilities fall below a pre-specified critical threshold value. Two types of actions are considered: treatment allocation, putting on hold at least temporarily further accrual of patients to a treatment arm, and treatment selection, removing an arm from the trial permanently. The main development in the paper is in terms of binary outcomes, but extensions for handling time-to-event data, including data from vaccine trials, are also discussed. The performance of the proposed methodology is tested in extensive simulation experiments, with numerical results and graphical illustrations documented in a Supplement to the main text. As a companion to this paper, an implementation of the methods is provided in the form of a freely available R package 'barts'.

CONCLUSION

The proposed methods for trial design provide an attractive alternative to their frequentist counterparts.

Real World Data in Health Technology Assessment of Complex Health Technologies

The available evidence on relative effectiveness and risks of new health technologies is often limited at the time of health technology assessment (HTA). Additionally, a wide variety in real-world data (RWD) policies exist among HTA organizations. This study assessed which challenges, related to the increasingly complex nature of new health technologies, make the acceptance of RWD most likely. A questionnaire was disseminated among 33 EUnetHTA member HTA organizations. The questions focused on accepted data sources, circumstances that allowed for RWD acceptance and barriers to acceptance. The questionnaire was validated and tested for reliability by an expert panel, and pilot-tested before dissemination via LimeSurvey. Twenty-two HTA organizations completed the questionnaire (67%). All reported accepting randomized clinical trials. The most accepted RWD source were patient registries (19/22, 86%), the least accepted were editorials and expert opinions (8/22, 36%). With orphan treatments or companion diagnostics, organizations tended to be most likely to accept RWD sources, 4.3-3.2 on a 5-point Likert scale, respectively. Additional circumstances were reported to accept RWD (e.g., a high disease burden). The two most important barriers to accepting RWD were lacking necessary RWD sources and existing policy structures. European HTA organizations seem positive toward the (wider) use of RWD in HTA of complex therapies. Expanding the use of patient registries could be potentially useful, as a large share of the organizations already accepts this source. However, many barriers still exist to the widespread use of RWD. Our results can be used to prioritize circumstances in which RWD might be accepted.

Efficacy of the Common Elements Treatment Approach (CETA) for Unhealthy Alcohol Use Among Adults with HIV in Zambia: Results from a Pilot Randomized Controlled Trial

This randomized controlled trial tested the efficacy of a multi-session, evidence-based, lay counselor-delivered transdiagnostic therapy, the Common Elements Treatment Approach (CETA), in reducing unhealthy alcohol use and comorbidities among persons living with HIV (PLWH) in Zambia. Adult PLWH with (a) unhealthy alcohol use plus mental health or substance use comorbidities, or (b) severe unhealthy alcohol use were randomized to receive a single-session alcohol brief intervention (BI) alone or BI plus referral to CETA. Outcomes were measured at baseline and a 6-month follow-up and included Alcohol Use Disorders Identification Test (AUDIT) score (primary), depression and trauma symptoms, and other substance use (secondary). We enrolled 160 participants; 78 were randomized to BI alone and 82 to BI plus CETA. Due to COVID-19, the trial ended early before 36 participants completed. Statistically and clinically significant reductions in mean AUDIT score from baseline to 6-month follow-up were observed in both groups, however, participants assigned to BI plus CETA had significantly greater reductions compared to BI alone (− 3.2, 95% CI − 6.2 to − 0.1; Cohen’s d: 0.48). The CETA effect size for AUDIT score increased in line with increasing mental health/substance use comorbidity (0 comorbidities d = 0.25; 1–2 comorbidities d = 0.36; 3+ comorbidities d = 1.6). Significant CETA treatment effects were observed for depression, trauma, and several other substances. BI plus referral to CETA was feasible and superior to BI alone for unhealthy alcohol use among adults with HIV, particularly among those with comorbidities. Findings support future effectiveness testing of CETA for HIV outcomes among PLWH with unhealthy alcohol use.

Clinical Trials Number: NCT03966885

A stochastically curtailed single‐arm phase II trial design for binary outcomes

Phase II clinical trials are a critical aspect of the drug development process. With drug development costs ever increasing, novel designs that can improve the efficiency of phase II trials are extremely valuable.Phase II clinical trials for cancer treatments often measure a binary outcome. The final trial decision is generally to continue or cease development. When this decision is based solely on the result of a hypothesis test, the result may be known with certainty before the planned end of the trial. Unfortunately, there is often no opportunity for early stopping when this occurs.Some existing designs do permit early stopping in this case, accordingly reducing the required sample size and potentially speeding up drug development. However, more improvements can be achieved by stopping early when the final trial decision is very likely, rather than certain, known as stochastic curtailment. While some authors have proposed approaches of this form, these approaches have various limitations.In this work we address these limitations by proposing new design approaches for single-arm phase II binary outcome trials that use stochastic curtailment. We use exact distributions, avoid simulation, consider a wider range of possible designs and permit early stopping for promising treatments. As a result, we are able to obtain trial designs that have considerably reduced sample sizes on average.

An order restricted multi-arm multi-stage clinical trial design

One family of designs that can noticeably improve efficiency in later stages of drug development are multi-arm multi-stage (MAMS) designs. They allow several arms to be studied concurrently and gain efficiency by dropping poorly performing treatment arms during the trial as well as by allowing to stop early for benefit. Conventional MAMS designs were developed for the setting, in which treatment arms are independent and hence can be inefficient when an order in the effects of the arms can be assumed (eg, when considering different treatment durations or different doses). In this work, we extend the MAMS framework to incorporate the order of treatment effects when no parametric dose-response or duration-response model is assumed. The design can identify all promising treatments with high probability. We show that the design provides strong control of the family-wise error rate and illustrate the design in a study of symptomatic asthma. Via simulations we show that the inclusion of the ordering information leads to better decision-making compared to a fixed sample and a MAMS design. Specifically, in the considered settings, reductions in sample size of around 15% were achieved in comparison to a conventional MAMS design.

Does delivering more dialysis improve clinical outcomes? What randomized controlled trials have shown

Some randomized controlled trials (RCTs) have sought to determine whether different dialysis techniques, dialysis doses and frequencies of treatment are able to improve clinical outcomes in end-stage kidney disease (ESKD). Virtually all of these RCTs were enacted on the premise that 'more' haemodialysis might improve clinical outcomes compared to 'conventional' haemodialysis. Aim of the present narrative review was to analyse these landmark RCTs by posing the following question: were their intervention strategies (i.e., earlier dialysis start, higher haemodialysis dose, intensive haemodialysis, increase in convective transport, starting haemodialysis with three sessions per week) able to improve clinical outcomes? The answer is no. There are at least two main reasons why many RCTs have failed to demonstrate the expected benefits thus far: (1) in general, RCTs included relatively small cohorts and short follow-ups, thus producing low event rates and limited statistical power; (2) the designs of these studies did not take into account that ESKD does not result from a single disease entity: it is a collection of different diseases and subtypes of kidney dysfunction. Patients with advanced kidney failure requiring dialysis treatment differ on a multitude of levels including residual kidney function, biochemical parameters (e.g., acid base balance, serum electrolytes, mineral and bone disorder), and volume overload. In conclusion, the different intervention strategies of the RCTs herein reviewed were not able to improve clinical outcomes of ESKD patients. Higher quality studies are needed to guide patients and clinicians in the decision-making process. Future RCTs should account for the heterogeneity of patients when considering inclusion/exclusion criteria and study design, and should a priori consider subgroup analyses to highlight specific subgroups that can benefit most from a particular intervention.

Evaluating the association of TRPA1 gene polymorphisms with pain sensitivity: a protocol for an adaptive recall by genotype study

BACKGROUND

Pain is a complex polygenic trait whose common genetic underpinnings are relatively ill-defined due in part to challenges in measuring pain as a phenotype. Pain sensitivity can be quantified, but this is difficult to perform at the scale required for genome wide association studies (GWAS). Existing GWAS of pain have identified surprisingly few loci involved in nociceptor function which contrasts strongly with rare monogenic pain states. This suggests a lack of resolution with current techniques. We propose an adaptive methodology within a recall-by-genotype (RbG) framework using detailed phenotyping to screen minor alleles in a candidate 'nociceptor' gene in an attempt to estimate their genetic contribution to pain.

METHODS/DESIGN

Participants of the Avon Longitudinal Study of Parents and Children will be recalled on the basis of genotype at five common non-synonomous SNPs in the 'nociceptor' gene transient receptor potential ankylin 1 (TRPA1). Those homozygous for the common alleles at each of the five SNPs will represent a control group. Individuals homozygous for the minor alleles will then be recruited in a series of three sequential test groups. The outcome of a pre-planned early assessment (interim) of the current test group will determine whether to continue recruitment or switch to the next test group. Pain sensitivity will be assessed using quantitative sensory testing (QST) before and after topical application of 10% cinnamaldehyde (a TRPA1 agonist).

DISCUSSION

The design of this adaptive RbG study offers efficiency in the assessment of associations between genetic variation at TRPA1 and detailed pain phenotypes. The possibility to change the test group in response to preliminary data increases the likelihood to observe smaller effect sizes relative to a conventional multi-armed design, as well as reducing futile testing of participants where an effect is unlikely to be observed. This specific adaptive RbG design aims to uncover the influence of common TRPA1 variants on pain sensation but can be applied to any hypothesis-led genotype study where costly and time intensive investigation is required and / or where there is large uncertainty around the expected effect size.

TRIAL REGISTRATION

ISRCTN, ISRCTN16294731. Retrospectively registered 25th November 2021.

Key Recommendations from the 2021 “Inclusion of Older Adults in Clinical Research” Workshop

Older adults are often underrepresented in clinical research, even though older adults are major consumers of novel therapies. We present major themes and recommendations from the 2021 "Inclusion of Older Adults in Clinical Research" Workshop, convened by the Clinical and Translational Science Award (CTSA) Inclusion of Older Adults as a Model for Special Populations Workgroup and the Research Centers Collaborative Network (RCCN). The goal of this workshop was to develop strategies to assist the research community in increasing the inclusion of older adults in clinical research. Major identified barriers include historical lack of federal guidelines, ageist biases and stereotypes, and lack of recruitment and retention techniques or infrastructure focused on older adults. Three key recommendations emerged: 1) engaging with the policymaking process to further promote inclusion; 2) using the CTSA Workgroup Presentation Materials Library and other resources to overcome ageism, and 3) building institutional capacity to support age inclusion.

Quantifying Efficiency Gains of Innovative Designs of Two-Arm Vaccine Trials for COVID-19 Using an Epidemic Simulation Model

Clinical trials of a vaccine during an epidemic face particular challenges, such as the pressure to identify an effective vaccine quickly to control the epidemic, and the effect that time-space-varying infection incidence has on the power of a trial. We illustrate how the operating characteristics of different trial design elements maybe evaluated using a network epidemic and trial simulation model, based on COVID-19 and individually randomized two-arm trials with a binary outcome. We show that "ring" recruitment strategies, prioritizing participants at an imminent risk of infection, can result in substantial improvement in terms of power in the model we present. In addition, we introduce a novel method to make more efficient use of the data from the earliest cases of infection observed in the trial, whose infection may have been too early to be vaccine-preventable. Finally, we compare several methods of response-adaptive randomization (RAR), discussing their advantages and disadvantages in the context of our model and identifying particular adaptation strategies that preserve power and estimation properties, while slightly reducing the number of infections, given an effective vaccine.

Role of peer support in a hepatitis C elimination programme

Many people with chronic hepatitis C infection don't engage in treatment. To eliminate hepatitis C and avoid health inequalities therapy must be provided to everyone. In other diseases peers with lived experience of the condition have improved care but, for hepatitis C, studies have not shown unequivocal benefit. We completed a retrospective analysis of the English National Health Service treatment registry comparing treatment networks with and without peers using Bayesian Poisson (for count outcomes) or Bayesian Binomial (for proportion outcomes) mixed effects models with time fixed effects. For each outcome, we estimated relative ratio (RR-Poisson model) or odds ratio (Odds Ratio (OR)-Binomial model) between peer and non-peer networks. We analysed 30,729 patients within 20 operational delivery networks. In networks with peers there was an increase in the number of people initiating therapy (RR 1.12 95%, credible interval 1.02-1.21) and an increase in the proportion completing therapy (OR 2.45 95%, credible interval 1.49-3.84). However, we saw no change in proportions of people using drugs who initiated therapy nor any significant change in virological response (OR 1.14 95% credible interval 0.979-1.36). We repeated the analysis looking at the impact of peers two months after they had been introduced, when they had established networks of contacts, and saw an increase in the proportion of people treated in addiction services. In treating patients with chronic hepatitis C infection the inclusion of peer supporters may increase the number of people who initiate and complete antiviral therapy.

Factors influencing the statistical planning, design, conduct, analysis and reporting of trials in health care: A systematic review

Background

Trials in health care are prospective human research studies designed to test the effectiveness and safety of health care interventions, such as medications, surgeries, medical devices and other treatment or prevention interventions. Statistics is an important and powerful tool in trials. Inappropriately designed trials and/or inappropriate statistical analysis produce unreliable results and a lack of transparency when reported, with limited clinical use.

Aim

This systematic literature review aimed to identify, describe and synthesise factors contributing to or influencing the statistical planning, design, conduct, analysis and reporting of trials.

Methods

Information sources were retrieved from the following electronic citation databases: PubMed, Web of Science, PsycINFO, and CINAHL and the grey literature repository: OpenGrey. 90 articles and guidelines were included in this review. A narrative, thematic synthesis identified the key factors influencing the statistical planning, design, conduct, analysis and reporting of trials in health care.

Findings and conclusion

We identified three analytical themes within which factors are grouped. These are: “what makes a statistician?“, “the need for dynamic statistical involvement and collaboration throughout a trial – it's not just about the numbers”, “and the “accountability of statisticians in ensuring the safety of trial participants and the integrity of trial data”. While important insights emerged about the qualifications, training, roles, and responsibilities of statisticians and their collaboration with other team members in a trial, further empirical research is warranted to elicit the perceptions of trial team members at the centre of statistics in trials.

Meloxicam in Combating Clinical Mastitis: Nanotechnology-Driven Hope and Opportunities

Mastitis has well-recognized harmful effects on dairy farm profitability. Furthermore, mastitis impairs the milk component synthesizing ability of secretary tissues. Various therapies are available for the treatment of clinical mastitis. Meloxicam exhibits preferential binding to Cyclooxygenase-2 (COX-2) receptor and consequently generates fewer negative gastrointestinal side effects than nonspecific COX inhibitors such as flunixin meglumine and ketoprofen. Toward this end, research efforts directed at understanding the use of meloxicam alone and in combination with other antibiotics to improve milk quality and production. Therefore, in this review, we have highlighted the mechanism, biopharmaceutical challenges, and merits of meloxicam usage in dairy cattle mastitis. In addition, we also presented the integration of artificial neural network, in silico docking, and nanotechnology-driven topical drug delivery cargo as future opportunity for efficient delivery of meloxicam in the management of clinical mastitis.

Designing and conducting adaptive trials to evaluate interventions in health services and implementation research: practical considerations

Randomized controlled clinical trials are widely considered the gold standard for evaluating the efficacy or effectiveness of interventions in health care. Adaptive trials incorporate changes as the study proceeds, such as modifying allocation probabilities or eliminating treatment arms that are likely to be ineffective. These designs have been widely used in drug discovery studies but can also be useful in health services and implementation research and have been minimally used. As motivating examples, we use an ongoing adaptive trial and two completed parallel group studies and highlight potential advantages, disadvantages, and important considerations when using adaptive trial designs in health services and implementation research. In addition, we investigate the impact on power and the study duration if the two completed parallel-group trials had instead been conducted using adaptive principles. Compared with traditional trial designs, adaptive designs can often allow one to evaluate more interventions, adjust participant allocation probabilities (e.g., to achieve covariate balance), and identify participants who are likely to agree to enroll. These features could reduce resources needed to conduct a trial. However, adaptive trials have potential disadvantages and practical aspects that need to be considered, most notably outcomes that can be rapidly measured and extracted (e.g., long-term outcomes that take significant time to measure from data sources can be challenging), minimal missing data, and time trends. In conclusion, adaptive designs are a promising approach to help identify how best to implement evidence-based interventions into real-world practice in health services and implementation research.

Kidney dysfunction requiring dialysis is a heterogeneous syndrome: we should treat it like one

PURPOSE OF REVIEW

Advanced kidney failure requiring dialysis, commonly labeled end-stage kidney disease or chronic kidney disease stage 5D, is a heterogeneous syndrome -a key reason that may explain why: treating advanced kidney dysfunction is challenging and many clinical trials involving patients on dialysis have failed, thus far. Treatment with dialytic techniques - of which maintenance thrice-weekly hemodialysis is most commonly used - is broadly named kidney 'replacement' therapy, a term that casts the perception of a priori abandonment of intrinsic kidney function and subsumes patients into a single, homogeneous group.

RECENT FINDINGS

Patients with advanced kidney failure necessitating dialytic therapy may have ongoing endogenous kidney function, and differ in their clinical manifestations and needs. Different terminology, for example, kidney dysfunction requiring dialysis (KDRD) with stages of progressive severity could better capture the range of phenotypes of patients who require kidney 'assistance' therapy.

SUMMARY

Classifying patients with KDRD based on objective, quantitative levels of endogenous kidney function, as well as patient-reported symptoms and quality of life, would facilitate hemodialysis prescriptions tailored to level of kidney dysfunction, clinical needs, and personal priorities. Such classification would encourage clinicians to move toward personalized, physiological, and adaptive approach to hemodialysis therapy.

Protection by inclusion: Increasing enrollment of women in cardiovascular trials

Despite differences in biology that influence disease incidence, drug metabolism, and response to therapies, women remain under-enrolled in cardiovascular clinical trials. Estimates regarding treatment efficacy and safety are derived from male-predominant trial populations, with inadequate balance between sex subgroups for meaningful analysis on sex-specific treatment effects. Treatment strategies for women, particularly women of childbearing years, are derived from trials with predominantly men participants, from lower quality, observational studies, or anecdotal evidence. Guideline recommendations for women who are pregnant or lactating are typically based on opinion as there is little evidence to guide them. In this review, we discuss trial design factors independently associated with the under-enrollment of women, identify possible strategies to increase the enrollment of women in trials, and suggest multi-level actions that could close sex-based research disparities. Recruiting and retaining women trialists, independently associated with increased enrollment of women and Black, Indigenous, and Persons of Color (BIPOC) participants, and diversifying research teams may be effective approaches. Modifying trial design by eliminating default sex-specific exclusion criteria, developing patient-centered consent and participation processes, incorporating pragmatic follow-up schemes, and incorporating sex/gender analysis into trial planning may also increase the enrollment of women participants. Journals and funding bodies should require trials to report participant to prevalence ratios, sex-disaggregated trial flow, and sex-treatment interactions. Healthcare systems can help create research-ready cultures that both enhance patient engagement in trials and expedite end-of-trial knowledge translation.

Trends in Adaptive Design Methods in Dialysis Clinical Trials: A Systematic Review

Rationale & Objective

Adaptive design methods are intended to improve the efficiency of clinical trials and are relevant to evaluating interventions in dialysis populations. We sought to determine the use of adaptive designs in dialysis clinical trials and quantify trends in their use over time.

Study Design

We completed a novel full-text systematic review that used a machine learning classifier (RobotSearch) for filtering randomized controlled trials and adhered to the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guidelines.

Setting & Study Populations

We searched MEDLINE (PubMed) and ClinicalTrials.gov using sensitive dialysis search terms.

Selection Criteria for Studies

We included all randomized clinical trials with patients receiving dialysis or clinical trials with dialysis as a primary or secondary outcome. There was no restriction of disease type or intervention type.

Data Extraction & Analytical Approach

We performed a detailed data extraction of trial characteristics and a completed a narrative synthesis of the data.

Results

57 studies, available as 68 articles and 7 ClinicalTrials.gov summaries, were included after full-text review (initial search, 209,033 PubMed abstracts and 6,002 ClinicalTrials.gov summaries). 31 studies were conducted in a dialysis population and 26 studies included dialysis as a primary or secondary outcome. Although the absolute number of adaptive design methods is increasing over time, the relative use of adaptive design methods in dialysis trials is decreasing over time (6.12% in 2009 to 0.43% in 2019, with a mean of 1.82%). Group sequential designs were the most common type of adaptive design method used. Adaptive design methods affected the conduct of 50.9% of trials, most commonly resulting in stopping early for futility (41.2%) and early stopping for safety (23.5%). Acute kidney injury was studied in 32 trials (56.1%), kidney failure requiring dialysis was studied in 24 trials (42.1%), and chronic kidney disease was studied in 1 trial (1.75%). 27 studies (47.4%) were supported by public funding. 44 studies (77.2%) did not report their adaptive design method in the title or abstract and would not be detected by a standard systematic review.

Limitations

We limited our search to 2 databases (PubMed and ClinicalTrials.gov) due to the scale of studies sourced (209,033 and 6,002 results, respectively).

Conclusions

Adaptive design methods are used in dialysis trials but there has been a decline in their relative use over time.

The Contribution of Artificial Intelligence in Achieving the Sustainable Development Goals (SDGs): What Can Eye Health Can Learn From Commercial Industry and Early Lessons From the Application of Machine Learning in Eye Health Programmes

Achieving The United Nations sustainable developments goals by 2030 will be a challenge. Researchers around the world are working toward this aim across the breadth of healthcare. Technology, and more especially artificial intelligence, has the ability to propel us forwards and support these goals but requires careful application. Artificial intelligence shows promise within healthcare and there has been fast development in ophthalmology, cardiology, diabetes, and oncology. Healthcare is starting to learn from commercial industry leaders who utilize fast and continuous testing algorithms to gain efficiency and find the optimum solutions. This article provides examples of how commercial industry is benefitting from utilizing AI and improving service delivery. The article then provides a specific example in eye health on how machine learning algorithms can be purposed to drive service delivery in a resource-limited setting by utilizing the novel study designs in response adaptive randomization. We then aim to provide six key considerations for researchers who wish to begin working with AI technology which include collaboration, adopting a fast-fail culture and developing a capacity in ethics and data science.

Design of a novel clinical trial of prehospital pediatric airway management

Emergency Medical Services personnel are often the first to intervene in the care of critically ill children. Airway management is a fundamental step in prehospital resuscitation, yet there is significant variation in current prehospital airway management practices. Our objective is to present a methodologic approach to determine the optimal strategy for prehospital pediatric airway management. We describe the conceptual premise for the Pediatric Prehospital Airway Resuscitation Trial, a novel Bayesian adaptive sequential platform trial. We developed an innovative design to enable comparison of the three predominant prehospital pediatric airway techniques (bag-mask-ventilation, supraglottic airway insertion, and endotracheal intubation) in three distinct disease groups (cardiac arrest, major trauma, and other respiratory failure). We used a Bayesian statistical approach to provide flexible modeling that can adapt based on prespecified rules according to accumulating trial data with patient enrollment continuing until stopping rules are met. The approach also allows the comparison of multiple interventions in sequence across the different disease states. This Bayesian hierarchical model will be the primary analysis method for the Pediatric Prehospital Airway Resuscitation Trial. The model integrates information across subgroups, a technique known as "borrowing" to generate accurate global and subgroup-specific estimates of treatment effects and enables comparisons of airway intervention arms within the overarching trial. We will use this Bayesian hierarchical linear model that adjusts for subgroup to estimate treatment effects within each subgroup. The model will predict a patient-centered score of 30-day intensive care unit-free survival using arm, subgroup, and emergency medical services agency as predictors. The novel approach of Pediatric Prehospital Airway Resuscitation Trial will provide a feasible method to determine the optimal strategy for prehospital pediatric airway management and may transform the design of future prehospital resuscitation trials.

Expected Value of Sample Information to Guide the Design of Group Sequential Clinical Trials

Introduction

Adaptive designs allow changes to an ongoing trial based on prespecified early examinations of accrued data. Opportunities are potentially being missed to incorporate health economic considerations into the design of these studies.

Methods

We describe how to estimate the expected value of sample information for group sequential design adaptive trials. We operationalize this approach in a hypothetical case study using data from a pilot trial. We report the expected value of sample information and expected net benefit of sampling results for 5 design options for the future full-scale trial including the fixed-sample-size design and the group sequential design using either the Pocock stopping rule or the O’Brien-Fleming stopping rule with 2 or 5 analyses. We considered 2 scenarios relating to 1) using the cost-effectiveness model with a traditional approach to the health economic analysis and 2) adjusting the cost-effectiveness analysis to incorporate the bias-adjusted maximum likelihood estimates of trial outcomes to account for the bias that can be generated in adaptive trials.

Results

The case study demonstrated that the methods developed could be successfully applied in practice. The results showed that the O’Brien-Fleming stopping rule with 2 analyses was the most efficient design with the highest expected net benefit of sampling in the case study.

Conclusions

Cost-effectiveness considerations are unavoidable in budget-constrained, publicly funded health care systems, and adaptive designs can provide an alternative to costly fixed-sample-size designs. We recommend that when planning a clinical trial, expected value of sample information methods be used to compare possible adaptive and nonadaptive trial designs, with appropriate adjustment, to help justify the choice of design characteristics and ensure the cost-effective use of research funding.

Highlights

Randomised clinical trials in critical care: past, present and future

Randomised clinical trials (RCTs) are the gold standard for providing unbiased evidence of intervention effects. Here, we provide an overview of the history of RCTs and discuss the major challenges and limitations of current critical care RCTs, including overly optimistic effect sizes; unnuanced conclusions based on dichotomization of results; limited focus on patient-centred outcomes other than mortality; lack of flexibility and ability to adapt, increasing the risk of inconclusive results and limiting knowledge gains before trial completion; and inefficiency due to lack of re-use of trial infrastructure. We discuss recent developments in critical care RCTs and novel methods that may provide solutions to some of these challenges, including a research programme approach (consecutive, complementary studies of multiple types rather than individual, independent studies), and novel design and analysis methods. These include standardization of trial protocols; alternative outcome choices and use of core outcome sets; increased acceptance of uncertainty, probabilistic interpretations and use of Bayesian statistics; novel approaches to assessing heterogeneity of treatment effects; adaptation and platform trials; and increased integration between clinical trials and clinical practice. We outline the advantages and discuss the potential methodological and practical disadvantages with these approaches. With this review, we aim to inform clinicians and researchers about conventional and novel RCTs, including the rationale for choosing one or the other methodological approach based on a thorough discussion of pros and cons. Importantly, the most central feature remains the randomisation, which provides unparalleled restriction of confounding compared to non-randomised designs by reducing confounding to chance.

Optimising a couples-focused intervention to increase couples' HIV testing and counselling using the person-based approach: a qualitative study in Kwa-Zulu Natal, South Africa

OBJECTIVES

This qualitative study explored how to optimise a couples-focused intervention to promote couples HIV testing and counselling (CHTC).

SETTING

Community setting in Kwa-Zulu Natal, South Africa.

PARTICIPANTS

Qualitative interviews were conducted with 20 couples who had participated in a couples-focused intervention and five staff members delivering the intervention. Partners were interviewed individually by researchers of the same gender.

INTERVENTION

A couples-focused intervention comprised of two group sessions and four couples counselling sessions was previously shown to significantly increase uptake to CHTC in Kwa-Zulu Natal, South Africa. However, more than half of couples participating in the intervention still chose not to test together during follow-up.

ANALYSIS

The transcripts were analysed using the table of changes from the person-based approach. Proposed optimisations were discussed with a community group to ensure the intervention was as persuasive and acceptable as possible.

RESULTS

Many couples found it challenging to discuss CHTC with their partner due to an implied lack of trust. Optimisations to the intervention were identified to increase readiness to discuss CHTC, including education about serodiscordance, discussions about CHTC by peer mentors and open discussion of personal barriers to CHTC during couples' counselling sessions. Additional training for staff in open questioning techniques could help them feel more comfortable to explore couples' perceived barriers to CHTC, rather than advising couples to test. A logic model was developed to show anticipated mechanisms through which the optimised intervention would increase uptake to CHTC, including increasing knowledge, increasing positive outcome beliefs and managing negative emotions.

CONCLUSIONS

In-depth qualitative research informed optimisations to a couples-focused intervention for further evaluation in South Africa to encourage uptake to CHTC. Suggestions are made for optimal methods to gain open feedback on intervention experiences where participants may be reluctant to share negative views.