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.

Trends in mental health clinical research: Characterizing the ClinicalTrials.gov registry from 2007-2018.

While the epidemiologic burden of mental health disorders in the United States has been well described over the past decade, we know relatively little about trends in how these disorders are being studied through clinical research. We examined all US interventional mental health trials submitted to ClinicalTrials.gov between October 1, 2007 and April 30, 2018 to identify trends in trial characteristics, comparisons with non-mental health trials, and trial attributes associated with discontinuation and results reporting. International data were excluded to minimize potential confounding. Over this period, mental health and non-mental health trials grew at similar rates, though Industry and US government-funded trials declined and academic medical center/hospital/other (AMC/Hosp/Oth) funded trials grew faster in mental health research. The proportion of trials with safeguards against bias, including blinding and oversight by data monitoring committees (DMCs), decreased. This occurred during growth in the proportion of trials studying behavioral and non-pharmacological interventions, which often cannot be blinded and do not require DMC oversight. There was concurrent decline in pharmaceutical trials. There was significant growth in trials studying Non-DSM (Diagnostic and Statistical Manual-5) conditions (e.g. suicidality and wellness), as well as substance use, anxiety, and neurocognitive disorders. One in 12 trials was discontinued. Trial discontinuation was associated with industry and AMC/Hosp/Oth funders, pharmaceutical interventions, and lack of DMC oversight. Only 29.9% of completed trials reported results to the registry. Decreased results reporting was associated with behavioral interventions, phase 1 trials, and industry and AMC/Hosp/Oth funders. The main implications of these data are that funding is shifting away from traditional government and industry sources, there is increasing interest in non-pharmacological treatments and Non-DSM conditions, and there are changing norms in trial design characteristics regarding safeguards against bias. These trends can guide researchers and funding bodies when considering the trajectory of future mental health research.

Interim monitoring in a treatment strategy trial with a composite primary endpoint.

When a clinical trial has a composite endpoint and a comparison of treatment strategies with multiple intervention components, interim data reviews by a data safety and monitoring board (DSMB) can be challenging as the data evolve on multiple fronts. We illustrate with a study in the treatment of Kaposi sarcoma (KS), an HIV-associated cancer with a multi-faceted disease presentation. The study, ACTG-A5264/AMC-067, was a 1:1 randomized trial to compare two strategies: immediate initiation of etoposide with antiretroviral therapy (ART), or ART with delayed etoposide upon disease progression. The outcome was a composite endpoint that included the following events, ordered from worst to best in the following three categories: (1) KS progression at 48 weeks, death, initiation of alternate KS treatment, loss to study follow-up; (2) stable KS; and (3) partial or complete KS response at 48 weeks. We present the interim results on the composite endpoint and the individual components, where components favored different study arms at an interim review. To facilitate interim data monitoring for complex trials, we recommend clear communications between the study team and the DSMB prior to the initiation of the trial on the need for a composite endpoint, the intentions behind the defined strategies, and relative importance of individual components of the composite endpoint. We also recommend flexibility in the timing of data reviews by the DSMB to interpret emerging data in multiple dimensions. Clinicaltrials.govNCT01352117.

Ensuring trial conduct is consistent with trial design: assumption is the enemy of quality.

'Assumptions are made and most assumptions are wrong' (Albert Einstein) Clinical trial conduct must be consistent with trial design, yet conducting the trial according to plan remains a major challenge.We discuss the importance of optimal co-applicant team formation in trial leadership, appropriate delegation of tasks and staff supervision arrangements. Finally, we discuss five standard documents which we believe require particular attention. With appropriate engagement by or with co-applicants during the preparation of these five standard documents, we believe many of the pitfalls trials commonly experience can be avoided. The risks inherent in failing to identify and address mistaken assumptions during the preparation of these documents are discussed and recommendations for best practice suggested.

Bioethics in the Oversight of Clinical Research: Institutional Review Boards and Data and Safety Monitoring Boards.

This article describes oversight mechanisms for clinical research that have developed substantially over the last few decades, including institutional review boards and data safety and monitoring boards. LeRoy Walters and others in the 1970s in the US thoughtfully described the importance of fundamental ethical principles and the application of bioethics to clinical research. Dr. Walters's important essay and work with the National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research helped identify and explain ethical principles that guide research. These principles, subsequently enunciated by the Commission in the Belmont Report, remain central to our understanding of the ethics of clinical research and are the foundation of our regulations. In this article, I review some history, successes, and challenges of IRBs and DSMBs to exemplify the significance of understanding and applying ethical principles to the design and conduct of clinical research, and to honor Dr. Walters's contributions.

Implementing monitoring triggers and matching of triggered and control sites in the TEMPER study: a description and evaluation of a triggered monitoring management system.

BACKGROUND: Triggered monitoring in clinical trials is a risk-based monitoring approach where triggers (centrally monitored, predefined key risk and performance indicators) drive the extent, timing, and frequency of monitoring visits. The TEMPER study used a prospective, matched-pair design to evaluate the use of a triggered monitoring strategy, comparing findings from triggered monitoring visits with those from matched control sites. To facilitate this study, we developed a bespoke risk-based monitoring system: the TEMPER Management System. METHODS: The TEMPER Management System comprises a web application (the front end), an SQL server database (the back end) to store the data generated for TEMPER, and a reporting function to aid users in study processes such as the selection of triggered sites. Triggers based on current practice were specified for three clinical trials and were implemented in the system. Trigger data were generated in the system using data extracted from the trial databases to inform the selection of triggered sites to visit. Matching of the chosen triggered sites with untriggered control sites was also performed in the system, while data entry screens facilitated the collection and management of the data from findings gathered at monitoring visits. RESULTS: There were 38 triggers specified for the participating trials. Using these, 42 triggered sites were chosen and matched with control sites. Monitoring visits were carried out to all sites, and visit findings were entered into the TEMPER Management System. Finally, data extracted from the system were used for analysis. CONCLUSIONS: The TEMPER Management System made possible the completion of the TEMPER study. It implemented an approach of standardising the automation of current-practice triggers, and the generation of trigger data to inform the selection of triggered sites to visit. It also implemented a matching algorithm informing the selection of matched control sites. We hope that by publishing this paper it encourages other trialists to share their approaches to, and experiences of, triggered monitoring and other risk-based monitoring systems.

A note on the draft International Council for Harmonisation guidance on estimands and sensitivity analysis.

In the second half of 2014, the Steering Committee of the International Council for Harmonisation endorsed the formation of an expert working group to develop an addendum to the International Council for Harmonisation E9 guideline (Statistical Principles for Clinical Trials). The addendum was to focus on two clinical trial topics: estimands and sensitivity analysis. A draft of the addendum, referred to as E9/R1, was developed by the expert working group and made available for public comments across the International Council for Harmonisation regions in the second half of 2017. A structured framework for clinical trial design and analysis proposed in the draft addendum are briefly described, including four key inputs for developing objective-driven estimands and strategies for tackling one of the inputs ('intercurrent events'). The proposed framework aligns each clinical trial objective with the corresponding statistical target of estimation (estimand), trial design and data to be collected, main method of estimation/inference, and sensitivity analysis to pressure test key analytic assumption(s) in the main analysis. A case study from the diabetes therapeutic area illustrates how the framework can be implemented in practice. International Council for Harmonisation E9/R1 is expected to enable better planning, conduct, analysis, and interpretation of randomised clinical trials. This will facilitate improvements in new drug applications and strengthen understanding of decision making by regulatory authorities and advisory committees.

Determination of fasiglifam-induced liver toxicity: Insights from the data monitoring committee of the fasiglifam clinical trials program.

BACKGROUND: Different approaches to safety event collection influence the determination of liver toxicity within drug development programs. Herein, a description of how fasiglifam-induced liver injury was detected is provided. METHODS: This eight-trial drug development program was intended to evaluate fasiglifam (25 mg, 50 mg) against placebo or active comparators (glimepiride, sitagliptin) in approximately 11,000 suboptimally controlled patients with type 2 diabetes (terminated Dec 2013 due to liver toxicity). Liver safety had been pre-identified as a concern, and within the phase 3 trials, was measured through (1) adverse event reporting, (2) central predefined liver monitoring schedule with various thresholds for potential drug-induced liver injury, and (3) blinded adjudication of serious liver toxicity by a panel of experts in drug-induced liver injury. A single data monitoring committee provided safety oversight across all trials within the program. FINDINGS: Prior to program termination, 7595 of 7602 (99.9%) randomized participants across the eight trials received at least one dose of the study drug (fasiglifam, placebo, or active control). No concerning trends were noted in adverse or serious adverse event frequency, suspected unexpected serious adverse reaction, alanine or aspartate transaminase elevations, or hepatobiliary or gastrointestinal adverse events as reported by local site investigators. However, the predefined central liver safety measurements revealed a greater frequency of possible Hy's Law cases (5 vs 2) and a 3- to 7-fold greater relative risk in alanine or aspartate transaminase elevation (with respect to upper limit of normal) within fasiglifam recipients compared with placebo/active control: alanine or aspartate transaminase > 3×: relative risk 3.34 (95% confidence interval 2.29-4.90), alanine or aspartate transaminase > 5×: relative risk 6.60 (95% confidence interval 3.03-14.38), alanine or aspartate transaminase > 8×: relative risk 6.14 (95% confidence interval 2.18-17.27), and alanine or aspartate transaminase > 10×: relative risk 6.74 (95% confidence interval 2.05, 22.14). All elevations resolved on study drug discontinuation. Drug-induced liver injury was adjudicated as highly likely or probably related in 0.64% of fasiglifam-treated versus 0.06% placebo or active control-treated patients. CONCLUSION: In spite of clear liver toxicity detected with a systematic surveillance program, liver safety signals were not identified from investigator adverse event reporting alone. By integrating key safety monitoring processes within the randomized design of adequately sized clinical trials, the rare but serious liver toxicity signal became clear, leading to timely program termination.

Triggered or routine site monitoring visits for randomised controlled trials: results of TEMPER, a prospective, matched-pair study.

BACKGROUND/AIMS: In multi-site clinical trials, where trial data and conduct are scrutinised centrally with pre-specified triggers for visits to sites, targeted monitoring may be an efficient way to prioritise on-site monitoring. This approach is widely used in academic trials, but has never been formally evaluated. METHODS: TEMPER assessed the ability of targeted monitoring, as used in three ongoing phase III randomised multi-site oncology trials, to distinguish sites at which higher and lower rates of protocol and/or Good Clinical Practice violations would be found during site visits. Using a prospective, matched-pair design, sites that had been prioritised for visits after having activated 'triggers' were matched with a control ('untriggered') site, which would not usually have been visited at that time. The paired sites were visited within 4 weeks of each other, and visit findings are recorded and categorised according to the seriousness of the deviation. The primary outcome measure was the proportion of sites with ≥1 'Major' or 'Critical' finding not previously identified centrally. The study was powered to detect an absolute difference of ≥30% between triggered and untriggered visits. A sensitivity analysis, recommended by the study's blinded endpoint review committee, excluded findings related to re-consent. Additional analyses assessed the prognostic value of individual triggers and data from pre-visit questionnaires completed by site and trials unit staff. RESULTS: In total, 42 matched pairs of visits took place between 2013 and 2016. In the primary analysis, 88.1% of triggered visits had ≥1 new Major/Critical finding, compared to 81.0% of untriggered visits, an absolute difference of 7.1% (95% confidence interval -8.3%, +22.5%; p = 0.365). When re-consent findings were excluded, these figures reduced to 85.7% versus 59.5%, (difference = 26.2%, 95% confidence interval 8.0%, 44.4%; p = 0.007). Individual triggers had modest prognostic value but knowledge of the trial-related activities carried out by site staff may be useful. CONCLUSION: Triggered monitoring approaches, as used in these trials, were not sufficiently discriminatory. The rate of Major and Critical findings was higher than anticipated, but the majority related to consent and re-consent with no indication of systemic problems that would impact trial-wide safety issues or integrity of the results in any of the three trials. Sensitivity analyses suggest triggered monitoring may be of potential use, but needs improvement and investigation of further central monitoring triggers is warranted. TEMPER highlights the need to question and evaluate methods in trial conduct, and should inform further developments in this area.

The independent statistician model: How well is it working?

With the initiation in the late 1960s of the data and safety monitoring board or equivalently the data monitoring committee in randomized clinical trials came the need for interim statistical reports for these committees to review for study conduct and early evidence of harm or overwhelming evidence of benefit, perhaps leading to early trial termination. Initially, the statistical team was part of the data coordinating center for the trial. Later, starting in the early 1990s in many industry-sponsored trials, this statistical unit was separated organizationally from the team that collected and managed the data. This unit, often referred to as the statistical data analysis center, prepares reports for the data monitoring committee, which cover study conduct, data quality and completeness, primary and secondary outcomes, and safety measures by study arm in an unblinded fashion. The role of the statistical data analysis center is critical to any well-functioning data monitoring committee. With the proliferation of data monitoring committees has grown the need for many more well-trained and experienced statistical data analysis centers. In my experience, some such units perform their tasks extremely well but many do not. There is a tremendous need and opportunity to provide training for statistical data analysis centers, and what sponsors and data monitoring committees should expect from statistical data analysis centers.

Data Monitoring Committees: Current issues.

Maintaining confidentiality of emerging data and ensuring the independence of Data Monitoring Committees are best practices of considerable importance to the ability of these committees to achieve their mission of safeguarding the interests of study participants and enhancing the integrity and credibility of clinical trials. Even with the wide recognition of these principles, there are circumstances where confidentiality issues remain challenging, controversial or inconsistently addressed. First, consider settings where a clinical trial's interim data could provide the evidence regulatory authorities require for decisions about marketing approval, yet where such a trial would be continued post-approval to provide more definitive evidence about principal safety and/or efficacy outcomes. In such settings, data informative about the longer term objectives of the trial should remain confidential until pre-specified criteria for trial completion have been met. Second, for those other than Data Monitoring Committee members, access to safety and efficacy outcomes during trial conduct, even when presented as data pooled across treatment arms, should be on a limited "need to know" basis relating to the ability to carry out ethical or scientific responsibilities in the conduct of the trial. Third, Data Monitoring Committee members should have access to unblinded efficacy and safety data throughout the trial to enable timely and informed judgments about risks and benefits. Fourth, it should be recognized that a mediator potentially could be useful in rare settings where the Data Monitoring Committee would have serious ethical or scientific concerns about the sponsor's dissemination or lack of dissemination of information. Data Monitoring Committee Contract Agreements, Indemnification Agreements and Charters should be developed in a manner to protect Data Monitoring Committee members and their independence, in order to enhance the Data Monitoring Committee's ability to effectively address their mission.

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.

A cohort examination to establish reporting of the remit and function of Trial Steering Committees in randomised controlled trials.

BACKGROUND: The DAMOCLES project established a widely used Data Monitoring Committee (DMC) Charter for randomised controlled trials (RCTs). Typically, within the UK, the DMC is advisory and recommends to another executive body; the Trial Steering Committee (TSC). Despite the executive role of the TSC, the CONSORT Statement does not explicitly require reporting of TSC activity, although is included as an example of good reporting. A lack of guidance on TSC reporting can impact transparency of trial oversight, ultimately leading to a misunderstanding regarding role and, subsequently, further variation in practice. This review aimed to establish reporting practice of TSC involvement in RCTs, and thus make recommendations for reporting. METHODS: A cohort examination identifying reporting practice was undertaken. The cohort comprised RCTs published in three leading medical journals (the British Medical Journal, The Lancet and the New England Journal of Medicine) within 6 months in 2012 and the full NIHR HTA Monograph series. Details of TSC constitution and impact were extracted from main publications and published supplements. RESULTS: Of 415 publications, 264 were eligible. These were typical in terms of trial design. Variations in reporting between journals and monographs was notable. TSC presence was identified in approximately half of trials (n = 144), of which 109 worked alongside a DMC. No publications justified not convening a TSC. When reported, the role of the committee and examples of impact in design, conduct and analysis were summarised. CONCLUSIONS: We present the first review of reporting TSC activity in the published academic literature. An absence of reporting standards with regards to TSC constitution, activity and impact on trial conduct was identified which can influence transparency of reporting trial oversight. Consistent reporting is vital for the benefits and impact of the TSC role to be understood to support adoption of this oversight structure and reduce global variations in practice.

Recommendations for data monitoring committees from the Clinical Trials Transformation Initiative.

Background/aims Use of data monitoring committees to oversee clinical trials was first proposed nearly 50 years ago. Since then, data monitoring committee use in clinical trials has increased and evolved. Nonetheless, there are no well-defined criteria for determining the need for a data monitoring committee, and considerable variability exists in data monitoring committee composition and conduct. To understand and describe the role and function of data monitoring committees, and establish best practices for data monitoring committee trial oversight, the Clinical Trials Transformation Initiative-a public-private partnership to improve clinical trials-launched a multi-stakeholder project. Methods The data monitoring committee project team included 16 individuals charged with (1) clarifying the purpose of data monitoring committees, (2) identifying best practices for independent data monitoring committee conduct, (3) describing effective communication practices, and (4) developing strategies for training data monitoring committee members. Evidence gathering included a survey, a series of focus group discussions, and a 2-day expert meeting aimed at achieving consensus opinions that form the foundation of our data monitoring committee recommendations. Results We define the role of the data monitoring committee as an advisor to the research sponsor on whether to continue, modify, or terminate a trial based on periodic assessment of trial data. Data monitoring committees should remain independent from the sponsor and be composed of members with no relevant conflicts of interest. Representation on a data monitoring committee generally should include at least one clinician with expertise in the therapeutic area being studied, a biostatistician, and a designated chairperson who has experience with clinical trials and data monitoring. Data monitoring committee meetings are held periodically to evaluate the unmasked data from ongoing trials, but the content and conduct of meetings may vary depending on specific goals or topics for deliberation. To guide data monitoring committee conduct and communication plans, a charter consistent with the protocol's research design and statistical analysis plan should be developed and agreed upon by the sponsor and the data monitoring committee prior to patient enrollment. We recommend concise and flexible charters that explain roles, responsibilities, operational issues, and how data monitoring committee recommendations are generated and communicated. The demand for data monitoring committee members appears to exceed the current pool of qualified individuals. To prepare a new generation of trained data monitoring committee members, we encourage a combination of didactic educational programs, practical experience, and skill development through apprenticeships and mentoring by experienced data monitoring committee members. Conclusion Our recommendations address data monitoring committee use, conduct, communication practices, and member preparation and training. Furthermore recommendations form the foundation for ongoing efforts to improve clinical trial oversight and enhance the safety and integrity of clinical research. These recommendations serve as a call to action for implementation of best practices that benefit study participants, study sponsors, and society.

Reporting of data monitoring boards in publications of randomized clinical trials is often deficient: ACTTION systematic review.

OBJECTIVE: To examine whether primary reports of randomized clinical trials (RCTs) in six high-impact, general medical journals reported (1) whether or not a Data Monitoring Committee/Data and Safety Monitoring Board (DMC/DSMB) was used and (2) the composition of the responsibilities of the reported DSMB/DMCs. STUDY DESIGN AND SETTING: Systematic review of RCTs published in 2014 in Annals of Internal Medicine, BMJ, NEJM, JAMA, JAMA Internal Medicine, and Lancet. RESULTS: Of the 294 articles identified, 174 (59%) mentioned using a DMC/DSMB. Of these 174, 126 (72%) indicated at least one responsibility of the DMC/DSMB, 26% listed the names of the DMC/DSMB members, and another 14% listed both their names and affiliations. Only one article stated that a DSMB was not used. The remaining 119 articles did not report whether or not a DMC/DSMB was used, although 59 had previously stated in a clinical trials registry entry or a published protocol that a DMC/DSMB was to be used. CONCLUSIONS: Considering the major role that DMC/DSMBs play in protecting participant safety, data quality, and interim analyses in RCTs, we recommend that authors of publications of RCTs report whether a DMC/DSMB was used and the responsibilities and members of DMC/DSMBs to increase transparency regarding study conduct.

Stopping guidelines for an effectiveness trial: what should the protocol specify?

BACKGROUND: Despite long-standing problems in decisions to stop clinical trials, stopping guidelines are often vague or unspecified in the trial protocol. Clear, well-conceived guidelines are especially important to assist the data monitoring committees for effectiveness trials. MAIN TEXT: To specify better stopping guidelines in the protocol for such trials, the clinical investigators and trial statistician should carefully consider the following kinds of questions: 1. How should the relative importance of the treatment benefits and hazards be assessed? 2. For decisions to stop a trial for benefit: (a) What would be the minimum clinically important difference for the study population? (b) How should the probability that the benefit exceeds that difference be assessed? (c) When should the interim analyses include data from other trials? (d) Would the evidence meet state-of-the-art standards for treatment recommendations and practice guidelines? 3. Should less evidence be required to stop the trial for harm than for benefit? 4. When should conventional stopping guidelines for futility be used for comparative effectiveness trials? CONCLUSION: Both clinical and statistical expertise are required to address such challenging questions for effectiveness trials. Their joint consideration by clinical investigators and statisticians is needed to define better stopping guidelines before starting the trial.