Changing platforms without stopping the train: experiences of data management and data management systems when adapting platform protocols by adding and closing comparisons

Characteristics, Progression, and Output of Randomized Platform Trials: A Systematic Review

Importance

Platform trials have become increasingly common, and evidence is needed to determine how this trial design is actually applied in current research practice.

Objective

To determine the characteristics, progression, and output of randomized platform trials.

Evidence Review

In this systematic review of randomized platform trials, Medline, Embase, Scopus, trial registries, gray literature, and preprint servers were searched, and citation tracking was performed in July 2022. Investigators were contacted in February 2023 to confirm data accuracy and to provide updated information on the status of platform trial arms. Randomized platform trials were eligible if they explicitly planned to add or drop arms. Data were extracted in duplicate from protocols, publications, websites, and registry entries. For each platform trial, design features such as the use of a common control arm, use of nonconcurrent control data, statistical framework, adjustment for multiplicity, and use of additional adaptive design features were collected. Progression and output of each platform trial were determined by the recruitment status of individual arms, the number of arms added or dropped, and the availability of results for each intervention arm.

Findings

The search identified 127 randomized platform trials with a total of 823 arms; most trials were conducted in the field of oncology (57 [44.9%]) and COVID-19 (45 [35.4%]). After a more than twofold increase in the initiation of new platform trials at the beginning of the COVID-19 pandemic, the number of platform trials has since declined. Platform trial features were often not reported (not reported: nonconcurrent control, 61 of 127 [48.0%]; multiplicity adjustment for arms, 98 of 127 [77.2%]; statistical framework, 37 of 127 [29.1%]). Adaptive design features were only used by half the studies (63 of 127 [49.6%]). Results were available for 65.2% of closed arms (230 of 353). Premature closure of platform trial arms due to recruitment problems was infrequent (5 of 353 [1.4%]).

Conclusions and Relevance

This systematic review found that platform trials were initiated most frequently during the COVID-19 pandemic and declined thereafter. The reporting of platform features and the availability of results were insufficient. Premature arm closure for poor recruitment was rare.

Online error rate control for platform trials

Platform trials evaluate multiple experimental treatments under a single master protocol, where new treatment arms are added to the trial over time. Given the multiple treatment comparisons, there is the potential for inflation of the overall type I error rate, which is complicated by the fact that the hypotheses are tested at different times and are not necessarily pre-specified. Online error rate control methodology provides a possible solution to the problem of multiplicity for platform trials where a relatively large number of hypotheses are expected to be tested over time. In the online multiple hypothesis testing framework, hypotheses are tested one-by-one over time, where at each time-step an analyst decides whether to reject the current null hypothesis without knowledge of future tests but based solely on past decisions. Methodology has recently been developed for online control of the false discovery rate as well as the familywise error rate (FWER). In this article, we describe how to apply online error rate control to the platform trial setting, present extensive simulation results, and give some recommendations for the use of this new methodology in practice. We show that the algorithms for online error rate control can have a substantially lower FWER than uncorrected testing, while still achieving noticeable gains in power when compared with the use of a Bonferroni correction. We also illustrate how online error rate control would have impacted a currently ongoing platform trial.

Using the AR-V7 biomarker to determine treatment in metastatic castrate resistant prostate cancer, a feasibility randomised control trial, conclusions from the VARIANT trial

Background

Prostate cancer is the most commonly diagnosed malignancy in the UK. Castrate resistant prostate cancer (CRPC) can be difficult to manage with response to next generation hormonal treatment variable. AR-V7 is a protein biomarker that can be used to predict response to treatment and potentially better inform management in these patients. Our aim was to establish the feasibility of conducting a definitive randomised controlled trial comparing the clinical utility of AR-V7 biomarker assay in personalising treatments for patients with metastatic CRPC within the United Kingdom (UK) National Health Service (NHS). Due to a number of issues the trial was not completed successfully, we aim to discuss and share lessons learned herein.

Methods

We conducted a randomised, open, feasibility trial, which aimed to recruit 70 adult men with metastatic CRPC within three secondary care NHS trusts in the UK to be run over an 18-month period. Participants were randomised to personalised treatment based on AR-V7 status (intervention) or standard care (control). The primary outcome was feasibility, which included: recruitment rate, retention and compliance. Additionally, a baseline prevalence of AR-V7 expression was to be estimated.

Results

Fourteen participants were screened and 12 randomised with six into each arm over a nine-month period. Reliability issues with the AR-V7 assay meant prevalence was not estimated. Due to limited recruitment the study did not complete to target.

Conclusions

Whilst the trial did not complete to target, we have ascertained that men with advanced cancer are willing to take part in trials utilising biomarker guided treatment. A number of issues were identified that serve as important learning points in future clinical trials.

Practical guidance for running late-phase platform protocols for clinical trials: lessons from experienced UK clinical trials units

BACKGROUND

Late-phase platform protocols (including basket, umbrella, multi-arm multi-stage (MAMS), and master protocols) are generally agreed to be more efficient than traditional two-arm clinical trial designs but are not extensively used. We have gathered the experience of running a number of successful platform protocols together to present some operational recommendations.

METHODS

Representatives of six UK clinical trials units with experience in running late-phase platform protocols attended a 1-day meeting structured to discuss various practical aspects of running these trials. We report and give guidance on operational aspects which are either harder to implement compared to a traditional late-phase trial or are specific to platform protocols.

RESULTS

We present a list of practical recommendations for trialists intending to design and conduct late-phase platform protocols. Our recommendations cover the entire life cycle of a platform trial: from protocol development, obtaining funding, and trial set-up, to a wide range of operational and regulatory aspects such as staffing, oversight, data handling, and data management, to the reporting of results, with a particular focus on communication with trial participants and stakeholders as well as public and patient involvement.

DISCUSSION

Platform protocols enable many questions to be answered efficiently to the benefit of patients. Our practical lessons from running platform trials will support trial teams in learning how to run these trials more effectively and efficiently.

Feasibility of a Platform Trial Design for the Development of Mobile Health Applications: A Review

Background: A novel adaptive trial design called platform trials (PTs) may offer an effective, efficient, and unbiased approach to evaluate different developer versions of mobile health (m-health) apps. However, the feasibility of their use for this purpose is yet to be explored. Objective: This literature review aims to explore the reported challenges associated with the adaptive PT design to assess its feasibility for the development of m-health apps. Methods: A descriptive literature review using two databases (MEDLINE and Embase) was conducted. Documents published in English between 1947 and September 20, 2020, were eligible for inclusion. Results: The titles and abstracts of 758 records were screened after which 179 full-text articles were assessed for eligibility. A total of 41 articles were included in the synthesis, all published after the year 2000. The synthesis yielded eight distinct categories of challenging issues with PTs relevant to their application in m-health app development, along with potential solutions. These categories are ethical issues (e.g., related to informed consent, equipoise, justice) (with 19 articles contributing content), biases (7 articles), temporal drift (4 articles), miscellaneous statistical issues (3 articles), logistical issues (e.g., cost and human resources, frequent amendments; 6 articles), sample size and power conflict (2 articles), generalizability of the results (2 articles), and operational challenges (1 article). Conclusion: Although PT designs are relatively new, they have promising feasibility for the seamless evaluation of interventions that undergo continuous development, including m-health apps; however, various challenges may hinder their successful implementation.

Practical guidance for planning resources required to support publicly-funded adaptive clinical trials

Adaptive designs are a class of methods for improving efficiency and patient benefit of clinical trials. Although their use has increased in recent years, research suggests they are not used in many situations where they have potential to bring benefit. One barrier to their more widespread use is a lack of understanding about how the choice to use an adaptive design, rather than a traditional design, affects resources (staff and non-staff) required to set-up, conduct and report a trial. The Costing Adaptive Trials project investigated this issue using quantitative and qualitative research amongst UK Clinical Trials Units. Here, we present guidance that is informed by our research, on considering the appropriate resourcing of adaptive trials. We outline a five-step process to estimate the resources required and provide an accompanying costing tool. The process involves understanding the tasks required to undertake a trial, and how the adaptive design affects them. We identify barriers in the publicly funded landscape and provide recommendations to trial funders that would address them. Although our guidance and recommendations are most relevant to UK non-commercial trials, many aspects are relevant more widely.

Economic Evaluation of Cost and Time Required for a Platform Trial vs Conventional Trials

IMPORTANCE

Platform trial design allows the introduction of new interventions after the trial is initiated and offers efficiencies to clinical research. However, limited guidance exists on the economic resources required to establish and maintain platform trials.

OBJECTIVE

To compare cost (US dollars) and time requirements of conducting a platform trial vs a series of conventional (nonplatform) trials using a real-life example.

DESIGN, SETTING, AND PARTICIPANTS

For this economic evaluation, an online survey was administered to a group of international experts (146 participants) with publication records of platform trials to elicit their opinions on cost and time to set up and conduct platform, multigroup, and 2-group trials. Using the reported entry dates of 10 interventions into Systemic Therapy in Advancing Metastatic Prostate Cancer: Evaluation of Drug Efficacy, the longest ongoing platform trial, 3 scenarios were designed involving a single platform trial (scenario 1), 1 multigroup followed by 5 2-group trials (scenario 2), and a series of 10 2-group trials (scenario 3). All scenarios started with 5 interventions, then 5 more interventions were either added to the platform or evaluated independently. Simulations with the survey results as inputs were used to compare the platform vs conventional trial designs. Data were analyzed from July to September 2021.

EXPOSURE

Platform trial design.

MAIN OUTCOMES AND MEASURES

Total trial setup and conduct cost and cumulative duration.

RESULTS

Although setup time and cost requirements of a single trial were highest for the platform trial, cumulative requirements of setting up a series of multiple trials in scenarios 2 and 3 were larger. Compared with the platform trial, there was a median (IQR) increase of 216.7% (202.2%-242.5%) in cumulative setup costs for scenario 2 and 391.1% (365.3%-437.9%) for scenario 3. In terms of total cost, there was a median (IQR) increase of 17.4% (12.1%-22.5%) for scenario 2 and 57.5% (43.1%-69.9%) for scenario 3. There was a median (IQR) increase in cumulative trial duration of 171.1% (158.3%-184.3%) for scenario 2 and 311.9% (282.0%-349.1%) for scenario 3. Cost and time reductions in the platform trial were observed in both the initial and subsequently evaluated interventions.

CONCLUSIONS AND RELEVANCE

Although setting up platform trials can take longer and be costly, the findings of this study suggest that having a single infrastructure can improve efficiencies with respect to costs and efforts.

Combining factorial and multi-arm multi-stage platform designs to evaluate multiple interventions efficiently

BACKGROUND

Factorial-MAMS design platform designs have many advantages, but the practical advantages and disadvantages of combining the two designs have not been explored.

METHODS

We propose practical methods for a combined design within the platform trial paradigm where some interventions are not expected to interact and could be given together.

RESULTS

We describe the combined design and suggest diagrams that can be used to represent it. Many properties are common both to standard factorial designs, including the need to consider interactions between interventions and the impact of intervention efficacy on power of other comparisons, and to standard multi-arm multi-stage designs, including the need to pre-specify procedures for starting and stopping intervention comparisons. We also identify some specific features of the factorial-MAMS design: timing of interim and final analyses should be determined by calendar time or total observed events; some non-factorial modifications may be useful; eligibility criteria should be broad enough to include any patient eligible for any part of the randomisation; stratified randomisation may conveniently be performed sequentially; and analysis requires special care to use only concurrent controls.

CONCLUSION

A combined factorial-MAMS design can combine the efficiencies of factorial trials and multi-arm multi-stage platform trials. It allows us to address multiple research questions under one protocol and to test multiple new treatment options, which is particularly important when facing a new emergent infection such as COVID-19.

Experiences of running a stratified medicine adaptive platform trial: Challenges and lessons learned from 10 years of the FOCUS4 trial in metastatic colorectal cancer

BACKGROUND

Complex innovative design trials are becoming increasingly common and offer potential for improving patient outcomes in a faster time frame. FOCUS4 was the first molecularly stratified trial in metastatic colorectal cancer and it remains one of the first umbrella trial designs to be launched globally. Here, we aim to describe lessons learned from delivery of the trial over the last 10 years.

METHODS

FOCUS4 was a Phase II/III molecularly stratified umbrella trial testing the safety and efficacy of targeted therapies in metastatic colorectal cancer. It used adaptive statistical methodology to decide which sub-trial should close early, and new therapies were added as protocol amendments. Patients with newly diagnosed metastatic colorectal cancer were registered, and central laboratory testing was used to stratify their tumour into molecular subtypes. Following 16 weeks of first-line therapy, patients with stable or responding disease were eligible for randomisation into either a molecularly stratified sub-trial (FOCUS4-B, C or D) or non-stratified FOCUS4-N. The primary outcome for all studies was progression-free survival comparing the intervention with active monitoring/placebo. At the close of the trial, feedback was elicited from all investigators through surveys and interviews and consolidated into a series of recommendations and lessons learned for the delivery of similar future trials.

RESULTS

Between January 2014 and October 2020, 1434 patients were registered from 88 UK hospitals. Of the 20 drug combinations that were explored for inclusion in the platform trial, three molecularly targeted sub-trials were activated: FOCUS4-D (February 2014-March 2016) evaluated AZD8931 in the BRAF-PIK3CA-RAS wildtype subgroup; FOCUS4-B (February 2016-July 2018) evaluated aspirin in the PIK3CA mutant subgroup and FOCUS4-C (June 2017-October 2020) evaluated adavosertib in the RAS+TP53 double mutant subgroup. FOCUS4-N was active throughout and evaluated capecitabine monotherapy versus a treatment break. A total of 361 (25%) registered patients were randomised into a sub-trial. Feedback on the experiences of delivery of FOCUS4 could be grouped into three main areas of challenge: funding/infrastructure, biomarker testing procedures and trial design efficiencies within which 20 recommendations are summarised.

CONCLUSION

Adaptive stratified medicine platform studies are feasible in common cancers but present challenges. Our stakeholder feedback has helped to inform how these trial designs can succeed and answer multiple questions efficiently, providing resource is adequate.

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.

Implementing effective community-based surveillance in research studies of maternal, newborn and infant outcomes in low resource settings

Background

Globally adopted health and development milestones have not only encouraged improvements in the health and wellbeing of women and infants worldwide, but also a better understanding of the epidemiology of key outcomes and the development of effective interventions in these vulnerable groups. Monitoring of maternal and child health outcomes for milestone tracking requires the collection of good quality data over the long term, which can be particularly challenging in poorly-resourced settings. Despite the wealth of general advice on conducting field trials, there is a lack of specific guidance on designing and implementing studies on mothers and infants. Additional considerations are required when establishing surveillance systems to capture real-time information at scale on pregnancies, pregnancy outcomes, and maternal and infant health outcomes.

Main body

Based on two decades of collaborative research experience between the Kintampo Health Research Centre in Ghana and the London School of Hygiene and Tropical Medicine, we propose a checklist of key items to consider when designing and implementing systems for pregnancy surveillance and the identification and classification of maternal and infant outcomes in research studies. These are summarised under four key headings: understanding your population; planning data collection cycles; enhancing routine surveillance with additional data collection methods; and designing data collection and management systems that are adaptable in real-time.

Conclusion

High-quality population-based research studies in low resource communities are essential to ensure continued improvement in health metrics and a reduction in inequalities in maternal and infant outcomes. We hope that the lessons learnt described in this paper will help researchers when planning and implementing their studies.

Clinical trials in amyotrophic lateral sclerosis: a systematic review and perspective

Amyotrophic lateral sclerosis is a progressive and devastating neurodegenerative disease. Despite decades of clinical trials, effective disease-modifying drugs remain scarce. To understand the challenges of trial design and delivery, we performed a systematic review of Phase II, Phase II/III and Phase III amyotrophic lateral sclerosis clinical drug trials on trial registries and PubMed between 2008 and 2019. We identified 125 trials, investigating 76 drugs and recruiting more than 15 000 people with amyotrophic lateral sclerosis. About 90% of trials used traditional fixed designs. The limitations in understanding of disease biology, outcome measures, resources and barriers to trial participation in a rapidly progressive, disabling and heterogenous disease hindered timely and definitive evaluation of drugs in two-arm trials. Innovative trial designs, especially adaptive platform trials may offer significant efficiency gains to this end. We propose a flexible and scalable multi-arm, multi-stage trial platform where opportunities to participate in a clinical trial can become the default for people with amyotrophic lateral sclerosis.

Implementation of platform trials in the COVID-19 pandemic: A rapid review

Motivation

Platform designs - master protocols that allow for new treatment arms to be added over time - have gained considerable attention in recent years. Between 2001 and 2019, 16 platform trials were initiated globally. The COVID-19 pandemic seems to have provided a new motivation for these designs. We conducted a rapid review to quantify and describe platform trials used in COVID-19.

Methods

We cross-referenced PubMed, ClinicalTrials.gov, and the Cytel COVID-19 Clinical Trials Tracker to identify platform trials, defined by their stated ability to add future arms.

Results

We identified 58 COVID-19 platform trials globally registered between January 2020 and May 2021. According to trial registries, 16 trials have added new therapies (median 3, IQR 4) and 11 have dropped arms (median 3, IQR 2.5). About 50% of trials publicly share their protocol, and 31 trials (53%) intend to share trial data. Forty-nine trials (84%) explicitly report adaptive features, and 21 trials (36%) state Bayesian methods.

Conclusions

During the pandemic, there has been a surge in the number of platform trials compared to historical use. While transparency in statistical methods and clarity of data sharing policies needs improvement, platform trials appear particularly well-suited for rapid evidence generation. Trials secured funding quickly and many succeeded in adding new therapies in a short time period, thus demonstrating the potential for these trial designs to be implemented beyond the pandemic. The evidence gathered here may provide ample insight to further inform operational, statistical, and regulatory aspects of future platform trial conduct.

Molecular profiling of advanced soft-tissue sarcomas: the MULTISARC randomized trial

BACKGROUND

Soft-tissue sarcomas (STS) represent a heterogeneous group of rare tumors including more than 70 different histological subtypes. High throughput molecular analysis (next generation sequencing exome [NGS]) is a unique opportunity to identify driver mutations that can change the usual one-size-fits-all treatment paradigm to a patient-driven therapeutic strategy. The primary objective of the MULTISARC trial is to assess whether NGS can be conducted for a large proportion of metastatic STS participants within a reasonable time, and, secondarily to determine whether a NGS-guided therapeutic strategy improves participant's outcome.

METHODS

This is a randomized, multicentre, phase II/III trial inspired by the design of umbrella and biomarker-driven trials. The setting plans up to 17 investigational centres across France and the recruitment of 960 participants. Participants aged at least 18 years, with unresectable locally advanced and/or metastatic STS confirmed by the French sarcoma pathological reference network, are randomized according to 1:1 allocation ratio between the experimental arm "NGS" and the standard "No NGS". NGS will be considered feasible if (i) NGS results are available and interpretable, and (ii) a report of exome sequencing including a clinical recommendation from a multidisciplinary tumor board is provided to investigators within 7 weeks from reception of the samples on the biopathological platform. A feasibility rate of more than 70% is expected (null hypothesis: 70% versus alternative hypothesis: 80%). In terms of care, participants randomized in "No NGS" arm and who fail treatment will be able to switch to the NGS arm at the request of the investigator.

DISCUSSION

The MULTISARC trial is a prospective study designed to provide high-level evidence to support the implementation of NGS in routine clinical practice for advanced STS participants, on a large scale.

TRIAL REGISTRATION

clinicaltrial.gov NCT03784014 .

Stratified randomization for platform trials with differing experimental arm eligibility

BACKGROUND

Platform trials facilitate efficient use of resources by comparing multiple experimental agents to a common standard of care arm. They can accommodate a changing scientific paradigm within a single trial protocol by adding or dropping experimental arms-critical features for trials in rapidly developing disease areas such as COVID-19 or cancer therapeutics. However, in these trials, efficacy and safety issues may render certain participant subgroups ineligible to some experimental arms, and methods for stratified randomization do not readily apply to this setting.

METHODS

We propose extensions for conventional methods of stratified randomization for platform trials whose experimental arms may differ in eligibility criteria. These methods balance on a prespecified set of stratification variables observable prior to arm assignment that remains the same across experimental arms. To do so, we suggest modifying block randomization by including experimental arm eligibility as a stratifying variable, and we suggest modifying the imbalance score calculation in dynamic balancing by performing pairwise comparisons between each eligible experimental arm and standard of care arm participants eligible to that experimental arm.

RESULTS

We provide worked examples to illustrate the proposed extensions. In addition, we also provide a formula to quantify the relative efficiency loss of platform trials with varying eligibility compared with trials with non-varying eligibility as measured by the size of the common standard of care arm.

CONCLUSIONS

This article presents important extensions to conventional methods for stratified randomization in order to facilitate the implementation of platform trials with differing experimental arm eligibility.

Moving forward in clinical research with master protocols

With billions of dollars in research and development (R&D) funding continuing to be invested, the novel coronavirus disease 2019 (COVID-19) has become into a singular focus for the scientific community. However, the collective response from the scientific communities have seen poor return on investment, particularly for therapeutic research for COVID-19, revealing the existing weaknesses and inefficiencies of the clinical trial enterprise. In this article, we argue for the importance of structural changes to existing research programs for clinical trials in light of the lessons learned from COVID-19.

Challenges in valuing and paying for combination regimens in oncology: reporting the perspectives of a multi-stakeholder, international workshop

BACKGROUND

It is increasingly common for two or more treatments for cancer to be combined as a single regimen. Determining value and appropriate payment for such regimens can be challenging. This study discusses these challenges, and possible solutions.

METHODS

Stakeholders from around the world attended a 2-day workshop, supported by a background paper. This study captures key outcomes from the discussion, but is not a consensus statement.

RESULTS

Workshop attendees agreed that combining on-patent treatments can result in affordability and value for money challenges that delay or deny patient access to clinically effective treatments in many health systems. Options for addressing these challenges include: (i) Increasing the value of combination therapies through improved clinical development; (ii) Willingness to pay more for combinations than for single drugs offering similar benefit, or; (iii) Aligning the cost of constituent therapies with their value within a regimen. Workshop attendees felt that (i) and (iii) merited further discussion, whereas (ii) was unlikely to be justifiable. Views differed on the feasibility of (i). Key to (iii) would be systems allowing different prices to apply to different uses of a drug.

CONCLUSIONS

Common ground was identified on immediate actions to improve access to combination regimens. These include an exploration of the legal challenges associated with price negotiations, and ensuring that pricing systems can support implementation of negotiated prices for specific uses. Improvements to clinical development and trial design should be pursued in the medium and longer term.

Collaborative Platform Trials to Fight COVID-19: Methodological and Regulatory Considerations for a Better Societal Outcome

For the development of coronavirus disease 2019 (COVID‐19) drugs during the ongoing pandemic, speed is of essence whereas quality of evidence is of paramount importance. Although thousands of COVID‐19 trials were rapidly started, many are unlikely to provide robust statistical evidence and meet regulatory standards (e.g., because of lack of randomization or insufficient power). This has led to an inefficient use of time and resources. With more coordination, the sheer number of patients in these trials might have generated convincing data for several investigational treatments. Collaborative platform trials, comparing several drugs to a shared control arm, are an attractive solution. Those trials can utilize a variety of adaptive design features in order to accelerate the finding of life‐saving treatments. In this paper, we discuss several possible designs, illustrate them via simulations, and also discuss challenges, such as the heterogeneity of the target population, time‐varying standard of care, and the potentially high number of false hypothesis rejections in phase II and phase III trials. We provide corresponding regulatory perspectives on approval and reimbursement, and note that the optimal design of a platform trial will differ with our societal objective and by stakeholder. Hasty approvals may delay the development of better alternatives, whereas searching relentlessly for the single most efficacious treatment may indirectly diminish the number of lives saved as time is lost. We point out the need for incentivizing developers to participate in collaborative evidence‐generation initiatives when a positive return on investment is not met.

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.

Implementation of the Randomized Embedded Multifactorial Adaptive Platform for COVID-19 (REMAP-COVID) trial in a US health system-lessons learned and recommendations

Background

The Randomized Embedded Multifactorial Adaptive Platform for COVID-19 (REMAP-COVID) trial is a global adaptive platform trial of hospitalized patients with COVID-19. We describe implementation at the first US site, the UPMC health system, and offer recommendations for implementation at other sites.

Methods

To implement REMAP-COVID, we focused on six major areas: engaging leadership, trial embedment, remote consent and enrollment, regulatory compliance, modification of traditional trial management procedures, and alignment with other COVID-19 studies.

Results

We recommend aligning institutional and trial goals and sharing a vision of REMAP-COVID implementation as groundwork for learning health system development. Embedment of trial procedures into routine care processes, existing institutional structures, and the electronic health record promotes efficiency and integration of clinical care and clinical research. Remote consent and enrollment can be facilitated by engaging bedside providers and leveraging institutional videoconferencing tools. Coordination with the central institutional review board will expedite the approval process. Protocol adherence, adverse event monitoring, and data collection and export can be facilitated by building electronic health record processes, though implementation can start using traditional clinical trial tools. Lastly, establishment of a centralized institutional process optimizes coordination of COVID-19 studies.

Conclusions

Implementation of the REMAP-COVID trial within a large US healthcare system is feasible and facilitated by multidisciplinary collaboration. This investment establishes important groundwork for future learning health system endeavors.

Trial registration

NCT02735707. Registered on 13 April 2016.

A platform trial in practice: adding a new experimental research arm to the ongoing confirmatory FLAIR trial in chronic lymphocytic leukaemia

BACKGROUND

The FLAIR trial in chronic lymphocytic leukaemia has a randomised, controlled, open-label, confirmatory, platform design. FLAIR was successfully amended to include an emerging promising experimental therapy to expedite its assessment, greatly reducing the time to reach the primary outcome compared to running a separate trial and without compromising the validity of the research or the ability to recruit to the trial and report the outcomes. The methodological and practical issues are presented, describing how they were addressed to ensure the amendment was a success.

METHODS

FLAIR was designed as a two-arm trial requiring 754 patients. In stage 2, two new arms were added: a new experimental arm and a second control arm to protect the trial in case of a change in practice. In stage 3, the original experimental arm was closed as its planned recruitment target was reached. In total, 1516 participants will be randomised to the trial.

RESULTS

The changes to the protocol and randomisation to add and stop arms were made seamlessly without pausing recruitment. The statistical considerations to ensure the results for the original and new hypotheses are unbiased were approved following peer review by oversight committees, Cancer Research UK, ethical and regulatory committees and pharmaceutical partners. These included the use of concurrent comparators in case of any stage effect, appropriate control of the type I error rate and consideration of analysis methods across trial stages. The operational aspects of successfully implementing the amendments are described, including gaining approvals and additional funding, data management requirements and implementation at centres.

CONCLUSIONS

FLAIR is an exemplar of how an emerging experimental therapy can be assessed within an existing trial structure without compromising the conduct, reporting or validity of the trial. This strategy offered considerable resource savings and allowed the new experimental therapy to be assessed within a confirmatory trial in the UK years earlier than would have otherwise been possible. Despite the clear efficiencies, treatment arms are rarely added to ongoing trials in practice. This paper demonstrates how this strategy is acceptable, feasible and beneficial to patients and the wider research community.

TRIAL REGISTRATION

ISRCTN Registry ISRCTN01844152 . Registered on August 08, 2014.

Adaptive platform trials using multi-arm, multi-stage protocols: getting fast answers in pandemic settings

Global health pandemics, such as coronavirus disease 2019 (COVID-19), require efficient and well-conducted trials to determine effective interventions, such as treatments and vaccinations. Early work focused on rapid sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), subsequent in-vitro and in-silico work, along with greater understanding of the different clinical phases of the infection, have helped identify a catalogue of potential therapeutic agents requiring assessment. In a pandemic, there is a need to quickly identify efficacious treatments, and reject those that are non-beneficial or even harmful, using randomised clinical trials. Whilst each potential treatment could be investigated across multiple, separate, competing two-arm trials, this is a very inefficient process. Despite the very large numbers of interventional trials for COVID-19, the vast majority have not used efficient trial designs. Well conducted, adaptive platform trials utilising a multi-arm multi-stage (MAMS) approach provide a solution to overcome limitations of traditional designs. The multi-arm element allows multiple different treatments to be investigated simultaneously against a shared, standard-of-care control arm. The multi-stage element uses interim analyses to assess accumulating data from the trial and ensure that only treatments showing promise continue to recruitment during the next stage of the trial. The ability to test many treatments at once and drop insufficiently active interventions significantly speeds up the rate at which answers can be achieved. This article provides an overview of the benefits of MAMS designs and successes of trials, which have used this approach to COVID-19. We also discuss international collaboration between trial teams, including prospective agreement to synthesise trial results, and identify the most effective interventions. We believe that international collaboration will help provide faster answers for patients, clinicians, and health care systems around the world, including for future waves of COVID-19, and enable preparedness for future global health pandemics.

Adaptive platform trials using multi-arm, multi-stage protocols: getting fast answers in pandemic settings

Global health pandemics, such as coronavirus disease 2019 (COVID-19), require efficient and well-conducted trials to determine effective interventions, such as treatments and vaccinations. Early work focused on rapid sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), subsequent in-vitro and in-silico work, along with greater understanding of the different clinical phases of the infection, have helped identify a catalogue of potential therapeutic agents requiring assessment. In a pandemic, there is a need to quickly identify efficacious treatments, and reject those that are non-beneficial or even harmful, using randomised clinical trials. Whilst each potential treatment could be investigated across multiple, separate, competing two-arm trials, this is a very inefficient process. Despite the very large numbers of interventional trials for COVID-19, the vast majority have not used efficient trial designs. Well conducted, adaptive platform trials utilising a multi-arm multi-stage (MAMS) approach provide a solution to overcome limitations of traditional designs. The multi-arm element allows multiple different treatments to be investigated simultaneously against a shared, standard-of-care control arm. The multi-stage element uses interim analyses to assess accumulating data from the trial and ensure that only treatments showing promise continue to recruitment during the next stage of the trial. The ability to test many treatments at once and drop insufficiently active interventions significantly speeds up the rate at which answers can be achieved. This article provides an overview of the benefits of MAMS designs and successes of trials, which have used this approach to COVID-19. We also discuss international collaboration between trial teams, including prospective agreement to synthesise trial results, and identify the most effective interventions. We believe that international collaboration will help provide faster answers for patients, clinicians, and health care systems around the world, including for each further wave of COVID-19, and enable preparedness for future global health pandemics.

Effect size estimates from umbrella designs: Handling patients with a positive test result for multiple biomarkers using random or pragmatic subtrial allocation

Umbrella trials have been suggested to increase trial conduct efficiency when investigating different biomarker-driven experimental therapies. An overarching platform is used for patient screening and subsequent subtrial allocation according to patients’ biomarker status. Two subtrial allocation schemes for patients with a positive test result for multiple biomarkers are (i) the pragmatic allocation to the eligible subtrial with the currently fewest included patients and (ii) the random allocation to one of the eligible subtrials. Obviously, the subtrials compete for such patients which are consequently underrepresented in the subtrials. To address questions of the impact of an umbrella design in general as well as with respect to subtrial allocation and analysis method, we investigate an umbrella trial with two parallel group subtrials and discuss generalisations. First, we analytically quantify the impact of the umbrella design with random allocation on the number of patients needed to be screened, the biomarker status distribution and treatment effect estimates compared to the corresponding gold standard of an independent parallel group design. Using simulations and real data, we subsequently compare both allocation schemes and investigate weighted linear regression modelling as possible analysis method for the umbrella design. Our results show that umbrella designs are more efficient than the gold standard. However, depending on the biomarker status distribution in the disease population, an umbrella design can introduce differences in estimated treatment effects in the presence of an interaction between treatment and biomarker status. In principle, weighted linear regression together with the random allocation scheme can address this difference though it is difficult to assess if such an approach is applicable in practice. In any case, caution is required when using treatment effect estimates derived from umbrella designs for e.g. future trial planning or meta-analyses.

An overview of platform trials with a checklist for clinical readers

OBJECTIVES

The objective of the study was to outline key considerations for general clinical readers when critically evaluating publications on platform trials and for researchers when designing these types of clinical trials.

STUDY DESIGN AND SETTING

In this review, we describe key concepts of platform trials with case study discussion of two hallmark platform trials in STAMPEDE and I-SPY2. We provide reader's guide to platform trials with a critical appraisal checklist.

RESULTS

Platform trials offer flexibilities of dropping ineffective arms early based on interim data and introducing new arms into the trial. For platform trials, it is important to consider how interventions are compared and evaluated throughout and how new interventions are introduced. For intervention comparisons, it is important to consider what the primary analysis is, what and how many interventions are active simultaneously, and allocation between different arms. Interim evaluation considerations should include the number and timing of interim evaluations and outcomes and statistical rules used to drop interventions. New interventions are usually introduced based on scientific merits, so consideration of these merits is important, together with the timing and mechanisms in which new interventions are added.

CONCLUSION

More efforts are needed to improve the scientific literacy of platform trials. Our review provides an overview of the important concepts of platform trials.

Short-Term Therapies for Treatment of Acute and Advanced Heart Failure-Why so Few Drugs Available in Clinical Use, Why Even Fewer in the Pipeline?

Both acute and advanced heart failure are an increasing threat in term of survival, quality of life and socio-economical burdens. Paradoxically, the use of successful treatments for chronic heart failure can prolong life but-per definition-causes the rise in age of patients experiencing acute decompensations, since nothing at the moment helps avoiding an acute or final stage in the elderly population. To complicate the picture, acute heart failure syndromes are a collection of symptoms, signs and markers, with different aetiologies and different courses, also due to overlapping morbidities and to the plethora of chronic medications. The palette of cardio- and vasoactive drugs used in the hospitalization phase to stabilize the patient's hemodynamic is scarce and even scarcer is the evidence for the agents commonly used in the practice (e.g. catecholamines). The pipeline in this field is poor and the clinical development chronically unsuccessful. Recent set backs in expected clinical trials for new agents in acute heart failure (AHF) (omecamtiv, serelaxine, ularitide) left a field desolately empty, where only few drugs have been approved for clinical use, for example, levosimendan and nesiritide. In this consensus opinion paper, experts from 26 European countries (Austria, Belgium, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Israel, Italy, The Netherlands, Norway, Poland, Portugal, Russia, Slovenia, Spain, Sweden, Switzerland, Turkey, U.K. and Ukraine) analyse the situation in details also by help of artificial intelligence applied to bibliographic searches, try to distil some lesson-learned to avoid that future projects would make the same mistakes as in the past and recommend how to lead a successful development project in this field in dire need of new agents.

Mind the gap? The platform trial as a working environment

BACKGROUND

Trials have become bigger and more complicated due to the complexity introduced by biomarker stratification, and the advent of multi-arm multi-stage trials, and umbrella and basket platform designs. The trials unit at University College London has been at the forefront of this work, with ground-breaking trials such as STAMPEDE and FOCUS4. The trial management and data management teams on these trials have summarised the operational challenges, to enable the broader clinical trials community to learn from their experiences. In a small-scale qualitative study, we examined the personal experience of individual researchers working on these trials.

COMMENTARY

We found reports of high workloads, with potentially significant stress for individuals and with an impact on their career choices. We conclude that there was an initial underestimation of the work required and of the inherent, largely unanticipated, challenges. We discuss the importance of fully understanding these trials' resource requirements, both for those writing grant applications and critically, for those with responsibility for deciding on funding. The working environment was characterised by three features: complexity, scale and heightened expectations. These features are highly attractive for professional development and engender high levels of loyalty and commitment. We observed a trade-off between these intrinsic rewards and the continuous demands of overlapping tasks, balancing a mix of routine and high-profile work, and the changing nature of pivotal roles. Such demands present challenges for colleague relationships, by enhancing the potential for competition and by disrupting the natural opportunities to pause, review and celebrate team achievements. In addition, molecular stratification in effect brings the patient into the trial office, as a specific individual, despite anonymisation, who is owed test results and a treatment decision. We discuss these observations with a view to interconnecting the need for compassion for patients with caring for the researchers engaged in the research ecosystem who are aiming to produce much hoped-for advances in medical science.

CONCLUSIONS

There is a need for increased awareness of the challenge these studies place on those throughout the team delivering the study. Such considerations must influence leaders and funders, both in their initial budget considerations and throughout delivery.