Recommendations for data monitoring committees from the Clinical Trials Transformation Initiative

Training the Next Generation of Data Monitoring Committee Members: An Initiative of the Heart Failure Collaboratory

Clinical trials are vital for assessing therapeutic interventions. The associated data monitoring committees (DMCs) safeguard patient interests and enhance trial integrity, thus promoting timely, reliable evaluations of those interventions. We face an urgent need to recruit and train new DMC members. The Heart Failure Collaboratory (HFC), a multidisciplinary public-private consortium of academics, trialists, patients, industry representatives, and government agencies, is working to improve the clinical trial ecosystem. The HFC aims to improve clinical trial efficiency and quality by standardizing concepts, and to help meet the demand for experienced individuals on DMCs by creating a standardized approach to training new members. This paper discusses the HFC's training workshop, and an apprenticeship model for new DMC members. It describes opportunities and challenges DMCs face, along with common myths and best practices learned through previous experiences, with an emphasis on data confidentiality and need for quality independent statistical reporting groups.

REVISE: re-evaluating the inhibition of stress erosions in the ICU-statistical analysis plan for a randomized trial

BACKGROUND

The REVISE (Re-Evaluating the Inhibition of Stress Erosions in the ICU) trial will evaluate the impact of the proton pump inhibitor pantoprazole compared to placebo in invasively ventilated critically ill patients.

OBJECTIVE

To outline the statistical analysis plan for the REVISE trial.

METHODS

REVISE is a randomized clinical trial ongoing in intensive care units (ICUs) internationally. Patients ≥ 18 years old, receiving invasive mechanical ventilation, and expected to remain ventilated beyond the calendar day after randomization are allocated to either 40 mg pantoprazole intravenously or placebo while mechanically ventilated.

RESULTS

The primary efficacy outcome is clinically important upper GI bleeding; the primary safety outcome is 90-day mortality. Secondary outcomes are ventilator-associated pneumonia, Clostridioides difficile infection, new renal replacement therapy, ICU and hospital mortality, and patient-important GI bleeding. Tertiary outcomes are total red blood cells transfused, peak serum creatinine concentration, and duration of mechanical ventilation, ICU, and hospital length of stay. Following an interim analysis of results from 2400 patients (50% of 4800 target sample size), the data monitoring committee recommended continuing enrolment.

CONCLUSIONS

This statistical analysis plan outlines the statistical analyses of all outcomes, sensitivity analyses, and subgroup analyses. REVISE will inform clinical practice and guidelines worldwide.

TRIAL REGISTRATION

www.

CLINICALTRIALS

gov NCT03374800. November 21, 2017.

Guidelines for Data and Safety Monitoring in Pragmatic Randomized Clinical Trials Using Case Studies

Pragmatic randomized clinical trials (pRCTs) have a unique set of considerations for data and safety monitoring. Because of their unconventional trial designs coupled with collection of multilevel data and implementation outcomes in real-world settings, thoughtful consideration is needed on the presentation of the trial design and accruing data to facilitate review and decision-making by the trial's data and safety monitoring board (DSMB). To our knowledge, there is limited information available in practical guidelines for generalists and medical general practitioners on what to monitor and to report to the DSMB during the conduct of pRCTs and what the DSMB should focus on in its review of reports. This article discusses these matters in the context of 3 case studies focusing on a set of critical data and safety monitoring questions that would be of interest to the generalist conducting pRCTs. In considering these questions, we provide tabular and graphical illustrations of how data can be presented to the DSMB while drawing attention to those areas that the DSMB should focus on in its review of the trial. The strategies and viewpoints discussed herein provide practical guidelines and can serve as a resource for the generalist conducting pRCTs.

Beyond Participation: Evaluating the Role of Patients in Designing Oncology Clinical Trials

Historically, subject matter experts and healthcare professionals have played a pivotal role in driving oncology clinical trials. Although patients have been key participants, their deliberate and active contribution to the design and decision-making process has been limited. This scoping review aimed to examine the existing literature to scope the extent of active patient engagement in the design of oncology clinical trials and its corresponding influence on trial outcomes. We conducted a systematic search using two databases, namely MEDLINE (Ovid) and EMBASE, to identify relevant studies exploring patient engagement in cancer-related clinical research design. We identified seven studies that met the eligibility criteria. The studies highlighted the benefits of active patient involvement, such as improved recruitment strategies, and the attainment of more patient-centered trial outcomes. The influence of patient involvement varied from tangible developments like patient-friendly resources to indirect impacts like improved patient experiences and potentially higher adherence to trial intervention. The future of clinical trials should prioritize patients' values and perspectives, with regulatory bodies fostering these practices through clear guidelines. As the concept of patient centricity takes root in oncology research, the involvement of patients should evolve beyond mere participation.

The evolving role of data & safety monitoring boards for real-world clinical trials

Introduction

Clinical trials provide the "gold standard" evidence for advancing the practice of medicine, even as they evolve to integrate real-world data sources. Modern clinical trials are increasingly incorporating real-world data sources - data not intended for research and often collected in free-living contexts. We refer to trials that incorporate real-world data sources as real-world trials. Such trials may have the potential to enhance the generalizability of findings, facilitate pragmatic study designs, and evaluate real-world effectiveness. However, key differences in the design, conduct, and implementation of real-world vs traditional trials have ramifications in data management that can threaten their desired rigor.

Methods

Three examples of real-world trials that leverage different types of data sources - wearables, medical devices, and electronic health records are described. Key insights applicable to all three trials in their relationship to Data and Safety Monitoring Boards (DSMBs) are derived.

Results

Insight and recommendations are given on four topic areas: A. Charge of the DSMB; B. Composition of the DSMB; C. Pre-launch Activities; and D. Post-launch Activities. We recommend stronger and additional focus on data integrity.

Conclusions

Clinical trials can benefit from incorporating real-world data sources, potentially increasing the generalizability of findings and overall trial scale and efficiency. The data, however, present a level of informatic complexity that relies heavily on a robust data science infrastructure. The nature of monitoring the data and safety must evolve to adapt to new trial scenarios to protect the rigor of clinical trials.

DMC reports in the 21st century: towards better tools for decision-making

Data Monitoring Committees (DMCs) have the important task to protect the safety of current and future patients during the conduct of a clinical study. Unfortunately, their work is often made difficult by voluminous DMC reports that are poorly structured and difficult to digest. In this article, we suggest improved solutions. Starting from a principled approach and building upon previous proposals, we offer concrete and easily understood displays, including related computer code. While leveraging modern tools, the most important is that these displays support the DMC's workflow in answering the relevant questions of interest. We hope that the adoption of these proposals can ease the task of DMCs, and importantly, lead to better decision-making for the benefit of patients.

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.

Stopping Trials Early Due to Harm

Stopping Trials Early Due to HarmDSMBs protect clinical trial participants from harm. We describe two trials stopped for potential harm to enrollees: a DSMB recommended termination soon after enrollment began when data showed higher mortality in the experimental versus the control arm, and a trial with completed enrollment was stopped while participants were being followed and treated.

Independent Oversight of Clinical Trials through Data and Safety Monitoring Boards

DSMBs: Protecting Patients and Scientific IntegrityDSMBs look after the welfare of patients enrolled in interventional clinical trials. DSMBs monitor for early establishment of efficacy, findings of harm, futility in obtaining a meaningful outcome, or changes in the ecology of care that render moot the question a trial aims to answer. This article opens a series of NEJM Evidence reviews about DSMBs.

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.

Detecting fabrication in large-scale molecular omics data

Fraud is a pervasive problem and can occur as fabrication, falsification, plagiarism, or theft. The scientific community is not exempt from this universal problem and several studies have recently been caught manipulating or fabricating data. Current measures to prevent and deter scientific misconduct come in the form of the peer-review process and on-site clinical trial auditors. As recent advances in high-throughput omics technologies have moved biology into the realm of big-data, fraud detection methods must be updated for sophisticated computational fraud. In the financial sector, machine learning and digit-frequencies are successfully used to detect fraud. Drawing from these sources, we develop methods of fabrication detection in biomedical research and show that machine learning can be used to detect fraud in large-scale omic experiments. Using the gene copy-number data as input, machine learning models correctly predicted fraud with 58-100% accuracy. With digit frequency as input features, the models detected fraud with 82%-100% accuracy. All of the data and analysis scripts used in this project are available at https://github.com/MSBradshaw/FakeData.

Prospective adverse event risk evaluation in clinical trials

Proactive and objective regulatory risk management of ongoing clinical trials is limited, especially when it involves the safety of the trial. We seek to prospectively evaluate the risk of facing adverse outcomes from standardized and routinely collected protocol data. We conducted a retrospective cohort study of 2860 Phase 2 and Phase 3 trials that were started and completed between 1993 and 2017 and documented in ClinicalTrials.gov. Adverse outcomes considered in our work include Serious or Non-Serious as per the ClinicalTrials.gov definition. Random-forest-based prediction models were created to determine a trial's risk of adverse outcomes based on protocol data that is available before the start of a trial enrollment. A trial's risk is defined by dichotomic (classification) and continuous (log-odds) risk scores. The classification-based prediction models had an area under the curve (AUC) ranging from 0.865 to 0.971 and the continuous-score based models indicate a rank correlation of 0.6-0.66 (with p-values < 0.001), thereby demonstrating improved identification of risk of adverse outcomes. Whereas related frameworks highlight the prediction benefits of incorporating data that is highly context-specific, our results indicate that Adverse Event (AE) risks can be reliably predicted through a framework of mild data requirements. We propose three potential applications in leading regulatory remits, highlighting opportunities to support regulatory oversight and informed consent decisions.

Institutionally chartered Data and Safety Monitoring Boards: structured approaches to assuring participant safety in clinical research

Data and Safety Monitoring Boards (DSMBs) derived from the need to monitor large federally funded multi-center clinical trials and evolved to include commercial and other large and complex trials. Eventually, academic health centers also created institutionally focused trial monitoring mechanisms. The basic general principles that define traditional DSMBs extend to the institutional level. The primary responsibilities are assuring safety of the participants, preserving the integrity of the trial, and ensuring the reliability of the results. Institutionally chartered DSMBs meet these responsibilities but usually have fewer members, have a structure specific to the needs of the trial, are more focused and/or have different scope reviewing smaller, single site, higher risk, and investigator-initiated studies and are flexible to accommodate institution-specific requirements and approaches. Their purpose is to meet the responsibilities of oversight for safety and data integrity, ensure proper study design, rigor and conduct, as well as provide statistical support appropriate to the setting of the research. Academic health centers should recognize the importance and existence of institution level safety and data monitoring and provide support as much as possible. Investigators should have sufficient resources available to assemble DSMBs. The Clinical and Translational Science Awards Collaborative DSMB Workgroup provides an online manual to assist investigators.

What should we report? Lessons learnt from the development and implementation of serious adverse event reporting procedures in non-pharmacological trials in palliative care

Background/aims

Serious adverse event reporting guidelines have largely been developed for pharmaceutical trials. There is evidence that serious adverse events, such as psychological distress, can also occur in non-pharmaceutical trials. Managing serious adverse event reporting and monitoring in palliative care non-pharmaceutical trials can be particularly challenging. This is because patients living with advanced malignant or non-malignant disease have a high risk of hospitalisation and/or death as a result of progression of their disease rather than due to the trial intervention or procedures. This paper presents a number of recommendations for managing serious adverse event reporting that are drawn from two palliative care non-pharmacological trials.

Methods

The recommendations were iteratively developed across a number of exemplar trials. This included examining national and international safety reporting guidance, reviewing serious adverse event reporting procedures from other pharmacological and non-pharmacological trials, a review of the literature and collaboration between the ACTION study team and Data Safety Monitoring Committee. These two groups included expertise in oncology, palliative care, statistics and medical ethics and this collaboration led to the development of serious adverse event reporting procedures.

Results

The recommendations included; allowing adequate time at the study planning stage to develop serious adverse event reporting procedures, especially in multi-national studies or research naïve settings; reviewing the level of trial oversight required; defining what a serious adverse event is in your trial based on your study population; development and implementation of standard operating procedures and training; refining the reporting procedures during the trial if necessary and publishing serious adverse events in findings papers.

Conclusions

There is a need for researchers to share their experiences of managing this challenging aspect of trial conduct. This will ensure that the processes for managing serious adverse event reporting are continually refined and improved so optimising patient safety.

Trial registration

ACTION trial registration number: ISRCTN63110516 (date of registration 03/10/2014).

Namaste trial registration number: ISRCTN14948133 (date of registration 04/10/2017).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12904-021-00714-5.

A joint industry-sponsored data monitoring committee model for observational, retrospective drug safety studies in the real-world setting

Purpose

To share better practice in establishing data monitoring committees (DMCs) for observational, retrospective safety studies with joint‐industry sponsorship.

Methods

A DMC model was created to monitor data from an observational, retrospective, post‐authorization safety study investigating risk of medullary thyroid cancer in patients treated with long‐acting glucagon‐like peptide‐1 receptor agonists (LA GLP‐1RAs) (NCT01511393). Sponsors reviewed regulatory guidelines, best practice and sponsors' standard operation procedures on DMCs. Discussions were held within the four‐member consortium, assessing applicability to observational, retrospective, real‐world studies. A DMC charter was drafted based on a sponsor‐proposed, adapted DMC model. Thereafter, a kick‐off meeting between sponsors and DMC members was held to receive DMC input and finalize the charter.

Results

Due to this study's observational, retrospective nature, assuring participant safety – central for traditional explanatory clinical trial models – was not applicable to our DMC model. The overall strategy and key indication for our real‐world model included preserving study integrity and credibility. Therefore, DMC member independence and their contribution of expert knowledge were essential. To ensure between‐sponsor data confidentiality, all study committees/corporations and sponsors, besides the DMC, received blinded data only (adapted to refer to data blinding that revealed the specific marketed LA GLP‐1RA/sponsor). Communication and blinding/unblinding of these data were facilitated by the contract research organization, which also provided crucial operational oversight.

Conclusions

To our knowledge, we have established the first DMC model for joint industry‐sponsored, observational, retrospective safety studies. This model could serve as a precedent for others performing similar post‐marketing, joint industry‐sponsored pharmacovigilance activities.

Data monitoring committees for clinical trials evaluating treatments of COVID-19

The first cases of coronavirus disease 2019 (COVID-19) were reported in December 2019 and the outbreak of SARS-CoV-2 was declared a pandemic in March 2020 by the World Health Organization. This sparked a plethora of investigations into diagnostics and vaccination for SARS-CoV-2, as well as treatments for COVID-19. Since COVID-19 is a severe disease associated with a high mortality, clinical trials in this disease should be monitored by a data monitoring committee (DMC), also known as data safety monitoring board (DSMB). DMCs in this indication face a number of challenges including fast recruitment requiring an unusually high frequency of safety reviews, more frequent use of complex designs and virtually no prior experience with the disease. In this paper, we provide a perspective on the work of DMCs for clinical trials of treatments for COVID-19. More specifically, we discuss organizational aspects of setting up and running DMCs for COVID-19 trials, in particular for trials with more complex designs such as platform trials or adaptive designs. Furthermore, statistical aspects of monitoring clinical trials of treatments for COVID-19 are considered. Some recommendations are made regarding the presentation of the data, stopping rules for safety monitoring and the use of external data. The proposed stopping boundaries are assessed in a simulation study motivated by clinical trials in COVID-19.

Enhancing clarity of clinical trial safety reports for data monitoring committees

A Data Monitoring Committee (DMC) evaluates patient safety in a clinical trial of an investigational intervention through periodic review of adverse events (AEs) and clinical safety assessments. Our aim was to construct DMC report displays to enhance the DMC safety review through use of graphics and clear identification and adjustment for missing data caused by early discontinuations and ongoing study participation. Suggested displays include a study snapshot graph, enhanced adverse event incidence tables including the incidence density and plotted incidence proportions, line graphs in place of by-patient listings, and trend plots in place of tables for continuous assessments.

Covid-19 pandemic research opportunity: Is the Middle East & North Africa (MENA) missing out?

BACKGROUND

The Covid-19 pandemic has caused fear and panic worldwide, forcing healthcare systems to disregard conventional practices and adopt innovation to contain the infection and death. Globally, there has been a rapid proliferation of research studies and clinical trials assessing risks, infectivity and treatment.

METHODS

This review assesses the opportunities and challenges in the Middle East North Africa (MENA) region to engage in the conduct of high quality clinical trials during the Covid-19 pandemic.

RESULTS

Opportunities are abundant for conducting clinical trials in MENA countries, including substantial cost savings, academic health centers, integrated health information systems, international accreditation, and international collaborations. Yet, the MENA region has missed out on opportunities to advance patient research during prior infectious disease outbreaks caused by the Severe Acute Respiratory Syndrome, Ebola, and the Middle East Respiratory Syndrome, as evidenced by the lack of concerted research and clinical trials from the region. A large vulnerable population, especially the poor expatriate work force, the current isolation of the health centers, and the lack of an expert network or field trained task force, all contribute to challenges preventing the formation of a pan Arab research enterprise for epidemics.

CONCLUSION

Quality clinical research is critical during public health emergencies to identify treatments and solutions. The efficient conduct of clinical trials requires innovative strategies in research design, approval, and dissemination. Many countries in the MENA region have an opportunity to quickly ramp up research capacity and contribute significantly to the fight against the Covid-19 global threat.

Evaluation of Cumulative Meta-analysis of Rare Events as a Tool for Clinical Trials Safety Monitoring

This meta-analysis evaluates the use of cumulative meta-analysis of rare events as a tool for safety monitoring of clinical trials using the example of coronary bioresorbable vascular scaffold–associated thrombosis.

Achieving effective informed oversight by DMCs in COVID clinical trials

Best practices of data monitoring committees (DMCs) in randomized clinical trials are well established. Independent oversight provided by DMCs is particularly important in trials conducted in public health emergencies, such as in HIV/AIDS or coronavirus epidemics. Special considerations are needed to enable DMCs to effectively address novel circumstances they face in such settings. In the COVID-19 pandemic, these include the remarkable speed in which data regarding benefits and risks of interventions are accumulated. DMCs must hold frequent virtual meetings, using state-of-the-art communication software that protects against risk for security breaches. Data capture and DMC reports should be focused on the most informative measures about benefits and risks. Because numerous clinical trials are being concurrently conducted in the COVID-19 setting, often addressing closely related scientific questions, structures for DMC oversight should be efficient and adequately informative. When these concurrently conducted trials are evaluating related regimens in related clinical settings, often individually underpowered for safety and having separate DMCs, processes should be implemented enabling these DMCs to share with each other emerging confidential evidence to better assess risks and benefits. Ideally a single DMC would monitor a portfolio of clinical trials or a trial with multiple arms, such as a platform trial.

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For 5 decades, DMCs have monitored RCTs for safety and benefit.

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In 2020, the World Health Organization declared covid-19 disease to be a pandemic.

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Numerous trials have emerged to evaluate potential therapeutics and vaccines.

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Covid-19 trials bring new challenges to the DMC process, due to the epidemic speed.

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Patients are being recruited and outcome data accumulating very rapidly.

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DMCs oversight very important for extreme emergencies such as coronavirus epidemics.

The role of data and safety monitoring boards in implementation trials: When are they justified?

The National Institutes of Health requires data and safety monitoring boards (DSMBs) for all phase III clinical trials. The National Heart, Lung and Blood Institute requires DSMBs for all clinical trials involving more than one site and those involving cooperative agreements and contracts. These policies have resulted in the establishment of DSMBs for many implementation trials, with little consideration regarding the appropriateness of DSMBs and/or key adaptations needed by DSMBs to monitor data quality and participant safety. In this perspective, we review the unique features of implementation trials and reflect on key questions regarding the justification for DSMBs and their potential role and monitoring targets within implementation trials.

A third trial oversight committee: Functions, benefits and issues

Background/aims:

Clinical trial oversight is central to the safety of participants and production of robust data. The United Kingdom Medical Research Council originally set out an oversight structure comprising three committees in 1998. The first committee, led by the trial team, is hands-on with trial conduct/operations (‘Trial Management Group’) and essential. The second committee (Data Monitoring Committee), usually completely independent of the trial, reviews accumulating trial evidence and is used by most later phase trials. The Independent Data Monitoring Committee makes recommendations to the third oversight committee. The third committee, (‘Trial Steering Committee’), facilitates in-depth interactions of independent and non-independent trial members and gives broader oversight (blinded to comparative analysis). We investigated the roles and functioning of the third oversight committee with multiple research methods. We reflect upon these findings to standardise the committee’s remit and operation and to potentially increase its usage.

Methods:

We utilised findings from our recent published suite of research on the third oversight committee to inform guideline revision. In brief, we conducted a survey of 38 United Kingdom–registered Clinical Trials Units, reviewed a cohort of 264 published trials, observed 8 third oversight committee meetings and interviewed 52 trialists. We convened an expert panel to discuss third oversight committees. Subsequently, we interviewed nine patient/lay third committee members and eight committee Chairs.

Results:

In the survey, most Clinical Trials Units required a third committee for all their trials (27/38, 71%) with independent members (ranging from 1 to 6). In the survey and interviews, the independence of the third committee was valued to make unbiased consideration of Independent Data Monitoring Committee recommendations and to advise on trial progress, protocol changes and recruitment issues in conjunction with the trial leadership. The third committee also advised funders and sponsors about trial continuation and represented patients and the public by including lay members. Of the cohort of 264 published trials, 144 reported a ‘steering’ committee (55%), but the independence of these members was not described so these may have been internal Trial Management Groups. Around two thirds of papers (60%) reported having an Independent Data Monitoring Committee and 26.9% neither a steering nor an Independent Data Monitoring Committee. However, before revising the third committee charter (Terms of Reference), greater standardisation is needed around defining member independence, composition, primacy of decision-making, interactions with other committees and the lifespan.

Conclusion:

A third oversight committee has benefits for trial oversight and conduct, and a revised charter will facilitate greater standardisation and wider adoption.

The natural course of unruptured intracranial aneurysms in a Chinese cohort: protocol of a multi-center registration study in CIAP

BACKGROUND

Subarachnoid hemorrhage (SAH) accounts for 4.4% of cerebral vascular disease, which is one of the leading causes of death in China. Rupture of intracranial aneurysms (IAs) is the most common cause of SAH. The natural history of unruptured IAs (UIAs) and the risk factors for rupture are among the key issues regarding the pathogenesis of IA and SAH that remain unclear in the Chinese population.

METHODS

The China Intracranial Aneurysm Project (CIAP) is a prospective, observational, multicenter registry study of the natural courses, risk factors for the onset and rupture, treatment methods, comorbidity management and other aspects of intracranial aneurysms. To date, there are five studies in the CIAP. CIAP-1 is a prospective observational cohort study of UIAs. More than 5000 patients who will be followed for at least 1 year are expected to be enrolled in this cohort. These participants come from more than 20 centers that represent different regions in China. Enrollment began on May 1, 2017, and will take approximately 5 years. A nationwide online database of UIAs will be built. Participants' basic, lifestyle, clinical and follow-up information will be collected. The blood samples will be stored in the Central Biological Specimen Bank. Strict standards have been established and will be followed in this study to ensure efficient implementation.

DISCUSSION

The natural course of UIAs in the Chinese population will be explored in this registry study. In addition, the risk factors for the rupture of the UIAs and the joint effect of those factors will be analyzed. The present study aims to create a nationwide database of UIAs and investigate the natural course of UIAs in China. Trial registration The Natural Course of Unruptured Intracranial Aneurysms in a Chinese Cohort (ClinicalTrials.gov Identifier: NCT03117803). Registered: July 5, 2017.

Next generation sequencing based assessment of the alloreactive T cell receptor repertoire in kidney transplant patients during rejection: a prospective cohort study

BACKGROUND

Kidney transplantation is the optimal treatment in end stage renal disease but the allograft survival is still hampered by immune reactions against the allograft. This process is driven by the recognition of allogenic antigens presented to T-cells and their unique T-cell receptor (TCR) via the major histocompatibility complex (MHC), which triggers a complex immune response potentially leading to graft injury. Although the immune system and kidney transplantation have been studied extensively, the subtlety of alloreactive immune responses has impeded sensitive detection at an early stage. Next generation sequencing of the TCR enables us to monitor alloreactive T-cell populations and might thus allow the detection of early rejection events.

METHODS/DESIGN

This is a prospective cohort study designed to sequentially evaluate the alloreactive T cell repertoire after kidney transplantation. The TCR repertoire of patients who developed biopsy confirmed acute T cell mediated rejection (TCMR) will be compared to patients without rejection. To track the alloreactive subsets we will perform a mixed lymphocyte reaction between kidney donor and recipient before transplantation and define the alloreactive TCR repertoire by next generation sequencing of the complementary determining region 3 (CDR3) of the T cell receptor beta chain. After initial clonotype assembly from sequencing reads, TCR repertoire diversity and clonal expansion of T cells of kidney transplant recipients in periphery and kidney biopsy will be analyzed for changes after transplantation, during, prior or after a rejection. The goal of this study is to describe changes of overall T cell repertoire diversity, clonality in kidney transplant recipients, define and track alloreactive T cells in the posttransplant course and decipher patterns of expanded alloreactive T cells in acute cellular rejection to find an alternative monitoring to invasive and delayed diagnostic procedures.

DISCUSSION

Changes of the T cell repertoire and tracking of alloreactive T cell clones after combined bone marrow and kidney transplant has proven to be of potential use to monitor the donor directed alloresponse. The dynamics of the donor specific T cells in regular kidney transplant recipients in rejection still rests elusive and can give further insights in human alloresponse.

TRIAL REGISTRATION

Clinicaltrials.gov: NCT03422224 , registered February 5th 2018.

The Clinical Trials Transformation Initiative: Methodology supporting the mission

The mission of the Clinical Trials Transformation Initiative, a public-private partnership co-founded by the U.S. Food and Drug Administration and Duke University, is to develop and drive adoption of practices that will increase the quality and efficiency of clinical trials. The Clinical Trials Transformation Initiative works collaboratively with key stakeholders, implements "fit-for-purpose" evidence-gathering projects, and develops actionable recommendations and tools to address the challenges faced by the clinical trials enterprise. In pursuit of its mission, The Clinical Trials Transformation Initiative follows an innovative and collaborative, five-step methodology: (1) state the problem and identify impediments to research, (2) gather evidence to identify gaps and barriers, (3) explore results by analyzing and interpreting findings, (4) finalize solutions by developing recommendations and tools, and (5) drive adoption through disseminating and implementing recommendations and tools. This article describes each step of the Clinical Trials Transformation Initiative's methodology, with a specific focus on describing the evidence-gathering activities.

Rationale and Design of an Adaptive Phase 2b/3 Clinical Trial of Selepressin for Adults in Septic Shock. Selepressin Evaluation Programme for Sepsis-induced Shock-Adaptive Clinical Trial

Septic shock carries substantial morbidity and mortality. The failure of many promising therapies during late-phase clinical trials prompted calls for alternative trial designs. We describe an innovative trial evaluating selepressin, a novel selective vasopressin V_1a receptor agonist, for adults with septic shock. SEPSIS-ACT (Selepressin Evaluation Programme for Sepsis-induced Shock-Adaptive Clinical Trial) is a blinded, randomized, placebo-controlled, two-part, adaptive phase 2b/3 trial, evaluating up to four selepressin dosing strategies. The primary outcome is pressor- and ventilator-free days, with a value of zero assigned for death within 30 days. We calculate Bayesian probabilities of final trial success to guide interim decision-making. Part 1 (dose-finding) has an adaptive sample size based on response-adaptive randomization and prespecified rules to determine stopping for futility or selection of the best dosing regimen for Part 2. Part 2 (confirmation) randomizes a minimum of 1,000 patients equally to the selected dosing regimen or placebo. The final estimate of treatment effect compares all selepressin-treated patients with all placebo-treated patients. The sample size of 1,800 provides 91% power to detect an increase of 1.5 pressor- and ventilator-free days with a reduction in mortality of 1.5%. The trial received a Special Protocol Assessment agreement from the U.S. Food and Drug Administration Center for Drug Evaluation and Research and is underway in Europe and the United States. SEPSIS-ACT is an innovative trial that addresses both optimal dose and confirmation of benefit, accelerating the evaluation of selepressin while mitigating risks to patients and sponsor through use of response-adaptive randomization, a novel registration endpoint, prespecified futility stopping rules, and a large sample size. Clinical Trial registered with www.clinicaltrials.gov (NCT02508649).

Reporting of data monitoring committees and adverse events in paediatric trials: a descriptive analysis

OBJECTIVES

For 300 paediatric trials, we evaluated the reporting of: a data monitoring committee (DMC); interim analyses, stopping rules and early stopping; and adverse events and harm-related endpoints.

METHODS

For this cross-sectional evaluation, we randomly selected 300 paediatric trials published in 2012 from the Cochrane Central Register of Controlled Trials. We collected data on the reporting of a DMC; interim analyses, stopping rules and early stopping; and adverse events and harm-related endpoints. We reported the findings descriptively and stratified by trial characteristics.

RESULTS

Eighty-five (28%) of the trials investigated drugs, and 18% (n=55/300) reported a DMC. The reporting of a DMC was more common among multicentre than single centre trials (n=41/132, 31% vs n=14/139, 10%, p<0.001) and industry-sponsored trials compared with those sponsored by other sources (n=16/50, 32% vs n=39/250, 16%, p=0.009). Trials that reported a DMC enrolled more participants than those that did not (median [range]): 224 (10-60480) vs 91 (10-9528) (p<0.001). Only 25% of these trials reported interim analyses, and 42% reported stopping rules. Less than half (n=143/300, 48%) of trials reported on adverse events, and 72% (n=215/300) reported on harm-related endpoints. Trials that reported a DMC compared with those that did not were more likely to report adverse events (n=43/55, 78% vs 100/245, 41%, p<0.001) and harm-related endpoints (n=52/55, 95% vs. 163/245, 67%, p<0.001). Only 32% of drug trials reported a DMC; 18% and 19% did not report on adverse events or harm-related endpoints, respectively.

CONCLUSIONS

The reporting of a DMC was infrequent, even among drug trials. Few trials reported stopping rules or interim analyses. Reporting of adverse events and harm-related endpoints was suboptimal.

Of Straws, Camels, Research Regulation, and IRBs

Institutional review boards (IRBs) have become beleaguered by a growth in responsibilities related to research oversight in the past several decades. A number of regulatory bodies have appeared in response to these novel and complex responsibilities, seeking to respond to among other issues, conflicts of interest, new technologies, and the potential misuse of research findings. Here, we examine several examples of these novel regulatory bodies as well as a number of concerns related to them that have been largely unacknowledged. Evidence suggests that there can be disharmony and conflicts between these regulatory bodies and IRBs, a lack of clarity with regard to their roles and responsibilities, as well as shortcomings within these entities that, at times, look a lot like the worries that have long been raised in relation to IRBs. We offer a brief discussion of how some of these concerns might be ameliorated, either through a significant restructuring of the system of research oversight, or perhaps through smaller changes to these regulatory bodies.

How to construct an optimal interim report: What the data monitoring committee does and doesn’t need to know

Background:

Data monitoring committees for randomized clinical trials have the responsibility of safeguarding interests of trial participants. To do so, the data monitoring committee must receive reports on safety and efficacy to assess risk/benefit and on trial conduct to ensure that the study can achieve its goals. This article outlines the key components of reports to the data monitoring committee and the important role of the unblinded statistician in preparing those reports.

Methods:

Most data monitoring committee meetings include open and closed sessions. For each session, there is a report of interim results. The open session is attended by the sponsor and lead investigators, including the statistician(s) responsible for the trial design. These investigators are blinded to the interim treatment comparisons. The closed session is attended by the data monitoring committee members and by the statistician(s) who prepared the closed report. These individuals are unblinded to interim treatment comparisons and therefore are not involved in study design changes. The optimal content of data monitoring committee reports and qualifications of the unblinded statistician(s) are discussed.

Reports:

Open reports should include responses to data monitoring committee recommendations, a synopsis of the protocol, a review of the protocol history and amendments, and information on enrollment, baseline characteristics, completeness of follow-up, and data quality. The open report is also a vehicle through which the sponsor and investigators should inform the data monitoring committee of relevant external information. Data in the open report are pooled over the treatment groups. The open report should not include data summaries by treatment group. The closed report should include a written summary with references to key tables and figures and methods used to prepare them. Tables and figures should summarize baseline characteristics, follow-up completeness, treatment adherence, and major safety and efficacy outcomes by treatment group. Text summaries should accompany the tables and figures. The data monitoring committee monitoring history (e.g. treatment differences at previous meetings) should be summarized. The unblinded statistician preparing the closed report should be familiar with the protocol and data collection plan and be capable of customizing the report to the current stage of the trial. This includes anticipating questions that may arise during the data monitoring committee review and pro-actively including data summaries to address these questions.

Conclusions:

There is considerable variation in the quality of open and closed data monitoring committee reports. Open and closed data monitoring committee reports should be concise, up to date, and informative. To achieve this, unblinded statisticians responsible for preparing closed data monitoring committee reports should be familiar with the statistical methods, the trial protocol, and the data collection plan. They should be capable of anticipating questions from the data monitoring committee and responding to requests for additional analyses.

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

Adaptive designs can make clinical trials more flexible by utilising results accumulating in the trial to modify the trial's course in accordance with pre-specified rules. Trials with an adaptive design are often more efficient, informative and ethical than trials with a traditional fixed design since they often make better use of resources such as time and money, and might require fewer participants. Adaptive designs can be applied across all phases of clinical research, from early-phase dose escalation to confirmatory trials. The pace of the uptake of adaptive designs in clinical research, however, has remained well behind that of the statistical literature introducing new methods and highlighting their potential advantages. We speculate that one factor contributing to this is that the full range of adaptations available to trial designs, as well as their goals, advantages and limitations, remains unfamiliar to many parts of the clinical community. Additionally, the term adaptive design has been misleadingly used as an all-encompassing label to refer to certain methods that could be deemed controversial or that have been inadequately implemented.We believe that even if the planning and analysis of a trial is undertaken by an expert statistician, it is essential that the investigators understand the implications of using an adaptive design, for example, what the practical challenges are, what can (and cannot) be inferred from the results of such a trial, and how to report and communicate the results. This tutorial paper provides guidance on key aspects of adaptive designs that are relevant to clinical triallists. We explain the basic rationale behind adaptive designs, clarify ambiguous terminology and summarise the utility and pitfalls of adaptive designs. We discuss practical aspects around funding, ethical approval, treatment supply and communication with stakeholders and trial participants. Our focus, however, is on the interpretation and reporting of results from adaptive design trials, which we consider vital for anyone involved in medical research. We emphasise the general principles of transparency and reproducibility and suggest how best to put them into practice.