Some FDA perspectives on data monitoring in clinical trials in drug development

Making what's advanced today routine tomorrow

Statistical principles and ongoing proliferation of novel statistical methodologies have dramatically improved the clinical drug development process. This journey over the last seven decades reshaped the pharmaceutical industry and regulatory agencies, highlighted the importance of statistical thinking in drug development and decision-making, and, most importantly, improved the lives of countless patients around the world. Some significant highlights in the history of this journey are recounted here as well as some exciting opportunities of what the future may hold for the science and profession of statistics.

Systematic qualitative review of the literature on data monitoring committees for randomized controlled trials

Aims To systematically review the published literature on data monitoring committees (DMCs) for randomized controlled trials (RCT) and summarize information and opinions on best practice. This was part of the DAMOCLES project. Methods A systematic and comprehensive search of five online bibliographic databases was performed, identifying 4007 potentially relevant articles. These were assessed in two stages by the authors. The 84 most relevant articles were agreed and were supplemented with extracts from 16 books: ultimately, 100 sources were reviewed. A series of 23 questions plus subquestions were developed to structure the data extraction and interpretation process.

Results Much has been written about DMCs but by a rather small community of authors. The papers included some results of surveys, but were mainly opinion pieces based on the authors' beliefs, practices and experiences. There is a lack of empirical evidence for many aspects of DMCs. There was a great range of detail in the literature relating to the prespecified questions. It was generally agreed that interim monitoring of accumulating data was necessary in some form for most trials. Questions such as membership of the DMC featured widely in the literature with opinions and practice ranging from 3–20 members, of whom between none and all should be independent. There was a consensus that formal statistical methods should be used as tools to guide decision making rather than as hard rules. Conversely, topics such as the training and experience required for DMC membership were discussed in very few papers.

Conclusions There is a consensus in the published literature in a number of areas, although there are many different models for structure and functions of a DMC. While uncertainty remains about some issues, it is strongly recommended that an explicit set of guidelines (Charter) is prepared for each DMC prior to the start of the trial specifying clearly how it will operate.

Independent data monitoring committees: an update and overview

An independent data monitoring committee׳s (IDMC's) duty is to ensure that the interests of the patients entered in the trial are being well served (i.e., the risk-benefit ratio is appropriate) and that the scientific integrity of the trial is maintained during the interim between trial initiation and trial completion. Industry sponsors form IDMCs to ensure an independent assessment to assure that the study participants are not exposed to unnecessary or unreasonable risks because of their trial participation and to ensure that the study is being conducted according to highest scientific and ethical standards. IDMCs are needed to analyze interim data for large randomized studies, in particular those that involve multiple sites and important clinical end points such as survival or disease progression. Ethical principles mandate that clinical trials begin with uncertainty as to which treatment is better (clinical equipoise). This uncertainty should be maintained during study conduct and analysis unless there are compelling data that emerge during the conduct of the trial. Group sequential statistical designs offer a mechanism to consider terminating a trial early and the results made public if the interim data become sufficiently compelling. Interim monitoring of safety and efficacy data is an integral part of modern clinical trials.

Continuous safety monitoring for randomized controlled clinical trials with blinded treatment information. Part 3: Design considerations

Ongoing safety monitoring of clinical trials of investigational treatments must operate at levels that range from the minute and detailed - namely, mathematical treatment of trial data - to the philosophical and societal - namely, ethical concerns for individuals and populations. Between those two poles lies a realm of environmental and pragmatic considerations that reflect the goals, biases, risk-tolerance, and constraints of study sponsors and organizers. These factors, while more difficult to quantify or, at times, to justify, also have a meaningful impact on the approach to safety monitoring and the resulting actions and outcomes. This paper considers the influence and interaction of two such factors, study design and statistical framework, on continuous safety monitoring procedures. Group sequential designs have been generally preferred for clinical trials over continuous sequential designs because of practical considerations. The group means and greater time for deliberation when using a group sequential procedure, as opposed to a continuous sequential procedure, can improve the quality of the analyses with minimal loss in sensitivity. However, undertaking any sequential analysis within a frequentist framework provokes considerable theoretical and practical difficulties. Continuous monitoring with a likelihood based method, on the other hand, has the advantages that all available information, including new data, can be used; sample sizes need not be fixed; and decisions can be made at any time without statistical penalty, irrespective of trial design. Such responsive statistical rules are needed to provide guidance to the human beings charged with trial monitoring.

Continuous safety monitoring for randomized controlled clinical trials with blinded treatment information. Part 1: Ethical considerations

The protection of patient safety is the principal responsibility of clinical trial investigators, and must be assured even if that were to prevent successful completion of a trial. Yet, the decision to prematurely stop a blinded, randomized controlled clinical trial can be extremely complicated, involving a tangle of ethical, statistical, and practical issues. Questions are quickly answered when conclusive evidence of harm has been established for trial participants, or when the potential for harm exceeds an acceptable limit of comfort for an oversight body. Less readily addressed are those situations in which early alarms warn of possible harm, but the data are too preliminary or incomplete to reach a satisfactory decision as to whether or not to stop the study. Early study termination without sufficient evidence disallows the study question from being answered and may allow an inferior treatment to remain in use, or prevent a superior one from being discovered. Even without early stopping, as a study proceeds, worrisome trends may lead to overzealous (or overly cautious) looks at study data which could jeopardize the integrity of the findings. Trial investigators and safety monitoring groups, aided by objective statistical rules and thoughtful deliberations, share responsibility for patient welfare. Statistical guidelines must not frustrate ethical concerns, but, rather, should be designed to promote the highest ethical and scientific outcomes possible, safeguarding both trial participants and the public - the ultimate beneficiaries of clinical trials.

Release of data from an ongoing randomized clinical trial for sample size adjustment or planning

The determination of an appropriate sample size is a key issue in planning and designing randomized clinical trials. In settings with time-to-event or binary outcomes, the required sample size depends on the control-arm event (response) rate. An accurate estimate of this rate is not often available at the planning stage. Therefore, non-comparative control-arm or pooled-arm event rates from an ongoing trial are sometimes released for sample size adjustment or planning purposes. It is shown that such non-comparative data release may still contain information on the relative treatment benefit and may thus adversely affect the ongoing trial. A simple approach to minimizing the effect of the data release is suggested.

Regulatory perspectives on data monitoring

Data monitoring is a critical component of the conduct of clinical trials that provide the evidence of efficacy and safety of investigational drugs. These trials may be conducted either by a pharmaceutical sponsor or by the government, especially those large trials that assess the impact of therapies on serious morbidity and/or mortality. While not extensive, I will review a regulatory history of FDA's evolving concerns and positions on data monitoring. I will review the key aspects of data monitoring and interim analysis of clinical trials contained in the recently published International Conference on Harmonization's statistical guidance as well as some other issues being considered for a draft guidance on data monitoring. Finally, some suggestions for improving and enhancing tools and statistical methods for monitoring clinical trials for safety assessment will be offered. This latter area deserves more consideration by statisticians than it has received to date.

Independent data monitoring committees: rationale, operations and controversies

Data monitoring committees (DMCs) have become an increasingly common component of randomized clinical trials in recent years. As experience has accumulated, and more individuals and organizations have become involved in such activities, a variety of approaches to the operation of such committees has inevitably arisen. Because these committees play such a critical role in the process of new drug development, it is important to consider the implications of the different approaches that are being used. It is also timely to consider the present and possible future regulatory status of data monitoring committees. Published in 2001 by John Wiley & Sons, Ltd.

Early stopping of clinical trials in lupus and other uncommon rheumatologic diseases

Use of statistical methods for early stopping of clinical trials allows more efficient and ethical utilization of subjects. In uncommon diseases, where the pool of potential subjects is limited, these methods provide a way to maximize the information gathered from trials. For trials in lupus, methods for early stopping should be more widely utilized. We discuss the ethics, practical aspects, pros and cons, and statistical foundations of some established methods for early stopping, with an emphasis on those that have available implementation in computer software. An example of the design and analysis of a treatment trial in systemic lupus erythematosus with the triangular test method of early stopping is also given.