Ethics and statistics in randomized clinical trials

Practical considerations of utilizing propensity score methods in clinical development using real-world and historical data

In recent years, with the rapid increase in the volume and accessibility of Real-World-Data (RWD) and Real-World-Evidence (RWE), we have seen the unprecedented opportunities for their use in drug clinical development and life-cycle management. RWD and RWE have demonstrated the significant potential to improve the design, planning, and execution of clinical development. Furthermore, they can feature in the designs as either a substitute or compliment to traditional clinical trials. However, to utilize RWD and RWE appropriately and wisely, it is critical to apply rigorous statistical methodologies that enable the robustness of results to be characterized and ascertained. Several statistical methodologies including exact matching, propensity score methods, matching-adjusted indirect comparisons and meta-analysis have been proposed for analyzing RWD. Among them, propensity score method is one of the most commonly used methods for non-randomized trials with indirect comparison. Although massive methodologies and examples have been published and discussed since propensity score methods were introduced, systematic review and discussion of how to rigorously use propensity score methods in the practical clinical development is still deficient. This paper introduces commonly used and emerging propensity score methods with detailed discussions of their pros and cons. Three different case studies are presented to illustrate the practical considerations of utilizing propensity score methods in the study design and evaluation using real-world and historical data. Additional considerations including selection of patient populations, endpoints, baseline covariates, propensity score methods, sensitivity analysis and practical implementation flow in clinical development will be discussed.

Compound optimal allocations for survival clinical trials

The aim of the present paper is to provide optimal allocations for comparative clinical trials with survival outcomes. The suggested targets are derived adopting a compound optimization strategy based on a subjective weighting of the relative importance of inferential demands and ethical concerns. The ensuing compound optimal targets are continuous functions of the treatment effects, so we provide the conditions under which they can be approached by standard response-adaptive randomization procedures, also guaranteeing the applicability of the classical asymptotic inference. The operating characteristics of the suggested methodology are verified both theoretically and by simulation, including the robustness to model misspecification. With respect to the other available proposals, our strategy always assigns more patients to the best treatment without compromising inference, taking into account estimation efficiency and power as well. We illustrate our procedure by redesigning two real oncological trials.

Outcome-adaptive randomization in clinical trials: issues of participant welfare and autonomy

Outcome-adaptive randomization (OAR) has been proposed as a corrective to certain ethical difficulties inherent in the traditional randomized clinical trial (RCT) using fixed-ratio randomization. In particular, it has been suggested that OAR redresses the balance between individual and collective ethics in favour of the former. In this paper, I examine issues of welfare and autonomy arising in relation to OAR. A central issue in discussions of welfare in OAR is equipoise, and the moral status of OAR is crucially influenced by the way in which this concept is construed. If OAR is based on a model of equipoise that demands strict indifference between competing interventions throughout the trial, such equipoise is disturbed by accruing data favouring one treatment over another; OAR seeks to redress this by weighting randomization to the seemingly superior treatment. However, this is a partial response, as patients continue to be allocated to the inferior therapy. Moreover, it rests upon considerations of aggregate harms and benefits, and does not therefore uphold individual ethics. Issues of fairness also arise, as early and late enrollees are randomized on a different basis. Fixed-ratio randomization represents a fuller and more consistent response to a loss of equipoise, as so construed. With regard to consent, the complexity of OAR poses challenges to adequate disclosure and comprehension. Additionally, OAR does not offer a remedy to the therapeutic misconception-participants' tendency to attribute treatment allocation in an RCT to individual clinical judgments, rather than to scientific considerations-and, if anything, accentuates rather than alleviates this misconception. In relation to these issues, OAR fails to offer ethical advantages over fixed-ratio randomization. More broadly, the ethical basis of OAR can be seen to lie more in collective than in individual ethics, and overall it fares worse in this territory than fixed-ratio randomization.

Maximizing power and minimizing treatment failures in clinical trials

Background Response-adaptive randomization procedures have a long history in the theoretical statistics literature over the past four decades. The main idea historically was to develop randomization procedures that place fewer patients on the inferior treatment. More recent research has changed the main focus to that of usual considerations in typical clinical trials: power, sample size, expected treatment failures, maintaining randomization, among others.

Methods We describe response-adaptive randomization procedures for simple clinical trials comparing two binomial success probabilities, including the randomized play-the-winner rule, the drop-the-loser rule, and a modification of the doubly-adaptive biased coin design. We treat as our principal goal minimizing expected treatment failures while preserving power and randomization. Based on some recent theoretical literature [1,8,14], the basic guidelines for selecting an appropriate procedure include targeting optimal allocation, having small variability, and preserving randomization. We use simulation to compare power and expected treatment failures according to these guidelines.

Results When the two treatments had high probabilities (>0.5) of success, the randomized play-the-winner rule was less powerful than complete randomization and the drop-the-loser rule by 1–3 percent with slightly larger expected number of treatment failures than the drop-the-loser rule. For all the success probabilities we examined, the drop-the-loser rule was within 1 percent of the power of complete randomization with a modest reduction of treatment failures. The doubly-adaptive biased coin design was as powerful or slightly more powerful than complete randomization in every case and expected treatment failures were always less, with modest reductions of the order of 0.3 percent to 8.3 percent.

Conclusions We conclude that the drop-the-loser rule and a modification of the doubly-adaptive biased coin design are the preferred procedures, and simulations show that these procedures yield a modest reduction in expected treatment failures while preserving power over complete randomization.

Clinical Research in Acute Fatal Illness

Clinical research to evaluate the effectiveness of life support systems in acute fatal illness has unique problems of logistics, ethics, and consent. There have been 10 prospective comparative trials of extracorporeal membrane oxygenation in acute fatal respiratory failure, utilizing different study designs. The trial designs were prospective controlled randomized, prospective adaptive randomized, sequential, and matched pairs. The trials were reviewed with regard to logistics, ethics, consent, statistical methods, economics, and impact. The matched pairs method is the best study design for evaluation of life support systems in acute fatal illness.

So You Have a Research Idea: A Survey of Databases Available for Plastic Surgery Research

Plastic surgery research using large databases has increased dramatically over the past 20 years. With the magnitude and breadth of information available in these databases, researchers are able to more easily answer a wide variety of research questions. This study sought to provide a comprehensive comparative analysis of the relevant databases for plastic surgery research. Database information, data collection methods, acquisition details, and variable availability were collected for 19 large databases. Examples of potential future research utility were ascribed to each database based on this comprehensive analysis. With a greater understanding of the content, strengths, and limitations of these databases, researchers will be better equipped to select the most appropriate database to answer a specific research question.

Are adaptive randomised trials or non-randomised studies the best way to address the Ebola outbreak in west Africa?

The Ebola outbreak that has devastated parts of west Africa represents an unprecedented challenge for research and ethics. Estimates from the past three decades emphasise that the present effort to contain the epidemic in the three most affected countries (Guinea, Liberia, and Sierra Leone) has been insufficient, with more than 24 900 cases and about 10 300 deaths, as of March 25, 2015. Faced with such an exceptional event and the urgent response it demands, the use of randomised controlled trials (RCT) for Ebola-related research might be both unethical and infeasible and that potential interventions should be assessed in non-randomised studies on the basis of compassionate use. However, non-randomised studies might not yield valid conclusions, leading to large residual uncertainty about how to interpret the results, and can also waste scarce intervention-related resources, making them profoundly unethical. Scientifically sound and rigorous study designs, such as adaptive RCTs, could provide the best way to reduce the time needed to develop new interventions and to obtain valid results on their efficacy and safety while preserving the application of ethical precepts. We present an overview of clinical studies registered at present at the four main international trial registries and provide a simulation on how adaptive RCTs can behave in this context, when mortality varies simultaneously in either the control or the experimental group.

Study design and "evidence" in patient-oriented research

Individual studies in patient-oriented research, whether described as "comparative effectiveness" or using other terms, are based on underlying methodological designs. A simple taxonomy of study designs includes randomized controlled trials on the one hand, and observational studies (such as case series, cohort studies, and case-control studies) on the other. A rigid hierarchy of these design types is a fairly recent phenomenon, promoted as a tenet of "evidence-based medicine," with randomized controlled trials receiving gold-standard status in terms of producing valid results. Although randomized trials have many strengths, and contribute substantially to the evidence base in clinical care, making presumptions about the quality of a study based solely on category of research design is unscientific. Both the limitations of randomized trials as well as the strengths of observational studies tend to be overlooked when a priori assumptions are made. This essay presents an argument in support of a more balanced approach to evaluating evidence, and discusses representative examples from the general medical as well as pulmonary and critical care literature. The simultaneous consideration of validity (whether results are correct "internally") and generalizability (how well results apply to "external" populations) is warranted in assessing whether a study's results are accurate for patients likely to receive the intervention-examining the intersection of clinical and methodological issues in what can be called a medicine-based evidence approach. Examination of cause-effect associations in patient-oriented research should recognize both the strengths and limitations of randomized trials as well as observational studies.

Challenges of clinical trial design when there is lack of clinical equipoise: use of a response-conditional crossover design

Clinical equipoise is widely accepted as the basis of ethics in clinical research and requires investigators to be uncertain of the relative therapeutic merits of trial comparators. When clinical equipoise is in question, innovative trial designs are needed to reduce ethical tension while satisfying regulators' requirements. We report a novel response-conditional crossover study design used in a Phase 3, randomized, double-blind, placebo-controlled clinical trial of intravenous 10% caprylate-chromatography purified immunoglobulin for chronic inflammatory demyelinating polyradiculoneuropathy. During the initial 24-week period, patients crossed over to the alternative treatment at the first sign of deterioration or if they failed to improve or were unable to maintain improvement at any time after 6 weeks. This trial design addressed concerns about lack of equipoise raised by physicians interested in trial participation and proved acceptable to regulatory authorities. The trial design may be applicable to other studies where clinical equipoise is in question.

Analysis of large databases in vascular surgery

Large databases can be a rich source of clinical and administrative information on broad populations. These datasets are characterized by demographic and clinical data for over 1000 patients from multiple institutions. Since they are often collected and funded for other purposes, their use for secondary analysis increases their utility at relatively low costs. Advantages of large databases as a source include the very large numbers of available patients and their related medical information. Disadvantages include lack of detailed clinical information and absence of causal descriptions. Researchers working with large databases should also be mindful of data structure design and inherent limitations to large databases, such as treatment bias and systemic sampling errors. Withstanding these limitations, several important studies have been published in vascular care using large databases. They represent timely, "real-world" analyses of questions that may be too difficult or costly to address using prospective randomized methods. Large databases will be an increasingly important analytical resource as we focus on improving national health care efficacy in the setting of limited resources.

The epistemology and ethics of chronic disease research: further lessons from ECMO

Robert Truog describes the controversial randomized controlled trials (RCTs) of extracorporeal membrane oxygenation (ECMO) therapy in newborns. Because early results with ECMO indicated that it might be a great advance, saving many lives, Truog argues that ECMO should not have been tested using RCTs, but that a long-term, large-scale observational study of actual clinical practice should have been conducted instead. Central to Truog's argument, however, is the idea that ECMO is an unusual case. Thus, it is an open question whether Truog's conclusions can be extended to other areas of medical research. In this paper, I look at epistemological and ethical issues arising in the care of patients with chronic diseases, using ECMO as a starting point. Both the similarities and the dissimilarities of these two cases highlight important issues in biomedical research and support a conclusion similar to Truog's. Observational studies of clinical practice provide the best evidence to inform the treatment of patients with chronic disease.

Bandit solutions provide unified ethical models for randomized clinical trials and comparative effectiveness research

As electronic medical records enable increasingly ambitious studies of treatment outcomes, ethical issues previously important only to limited clinical trials become relevant to unlimited whole populations. For randomized clinical trials, adaptive assignment strategies are known to expose substantially fewer patients to avoidable treatment failures than strategies with fixed assignments (e.g., equal sample sizes). An idealized adaptive case--the two-armed Bernoulli bandit problem--can be exactly optimized for a variety of ethically motivated cost functions that embody principles of duty-to-patient, but the solutions have been thought computationally infeasible when the numbers of patients in the study (the "horizon") is large. We report numerical experiments that yield a heuristic approximation that applies even to very large horizons, and we propose a near-optimal strategy that remains valid even when the horizon is unknown or unbounded, thus applicable to comparative effectiveness studies on large populations or to standard-of-care recommendations. For the case in which the economic cost of treatment is a parameter, we give a heuristic, near-optimal strategy for determining the superior treatment (whether more or less costly) while minimizing resources wasted on any inferior, more expensive, treatment. Key features of our heuristics can be generalized to more complicated protocols.

Adaptive designs for randomized trials in public health

In this article, we present a discussion of two general ways in which the traditional randomized trial can be modified or adapted in response to the data being collected. We use the term adaptive design to refer to a trial in which characteristics of the study itself, such as the proportion assigned to active intervention versus control, change during the trial in response to data being collected. The term adaptive sequence of trials refers to a decision-making process that fundamentally informs the conceptualization and conduct of each new trial with the results of previous trials. Our discussion below investigates the utility of these two types of adaptations for public health evaluations. Examples are provided to illustrate how adaptation can be used in practice. From these case studies, we discuss whether such evaluations can or should be analyzed as if they were formal randomized trials, and we discuss practical as well as ethical issues arising in the conduct of these new-generation trials.

Data and safety monitoring boards: some enduring questions

Data Safety and Monitoring Boards (DSMBs) have been referred to as a "growth industry," and this trend continues to be fueled by recent FDA guidance and the NIH's requirement that DSMBs be employed in virtually all phase III clinical trials. The widening role of DSMBs has been sporadically questioned on ethical grounds, but growth has continued, despite the fact that many of the questions endure, unanswered, save for repeated references to safeguarding the scientific integrity of trials. This may be about to change. The recently appointed director of the Office for Human Research Protections (OHRP), Jerry Menikoff, is on record as regarding current practices--where consent forms often promise what the DSMB has been assembled to specifically not provide--as constituting fraudulent behavior. That is, a subject may inherently rely on, to their detriment, information that has been misrepresented in the consent document. In this paper, we assemble some of the enduring questions and top them off with Menikoff's tour de force to present what we hope will be a compelling argument to require that consent forms fairly represent what the DSMB will do--and not do--with trial data as they accumulate. We argue that DSMBs should be used only in rare circumstances, and question the practice of precluding principal investigators from DSMB membership, but our main thrust is to ensure that DSMBs, when used at all, are properly described in trial consent forms.

Power and sample size simulations for Randomized Play-the-Winner rules

Response-adaptive randomization procedures, such as the Randomized Play-the-Winner (RPW), are treatment allocation rules for clinical trials that use available information on treatment outcomes to skew the allocation probability in favor of the treatment performing better thus far in the trial. Such allocation rules are based on the ethically desirable aim of reducing the share of patients allocated to the inferior treatment. This noble intent is overcome by statistical and logistical issues. One practical implementation obstacle of the RPW method is the estimation of required sample size and expected allocation shares. Unfortunately, this information is not readily available or easy to calculate. We present simulation results to provide a realistic assessment of the power and sample size required for successful implementation of the RPW rule for a study with primary outcome variable that is binary. Additionally, we discuss some practical approaches for sample size determination based on the RPW.

Practical Bayesian adaptive randomisation in clinical trials

While randomisation is the established method for obtaining scientifically valid treatment comparisons in clinical trials, it sometimes is at odds with what physicians feel is good medical practice. If a physician favours one treatment over another based on personal experience or published data, it may be more appropriate ethically for that physician to use the favoured treatment, rather than enrolling patients on a randomised trial. Still, the randomised trial may later show the physician's favoured treatment to be inferior. This paper reviews a statistical method, Bayesian adaptive randomisation, that provides a practical compromise between the scientific ideal of conventional randomisation and choosing each patient's treatment based on a personal preference that may prove to be incorrect. The method will first be illustrated by a simple hypothetical example, then by a recent trial in which patients with unresectable soft tissue sarcoma were adaptively randomised between two chemotherapy regimens.

Randomization in Controlled Clinical Trials: Why the Flip of a Coin Is So Important

The randomized controlled trial (RCT) is considered the highest level of medical evidence. In this brief overview, we discuss several key principles of the RCT. First, balance is paramount. Comparison groups must have similar proportions of participants with "important" prognostic and confounding factors. Randomization may or may not achieve this balance; if it does not, statistical adjustments should be used. Second, a statistical analysis should emphasize comparability and not mask dissimilarity. If the trial was indeed randomized, certain analysis techniques, such as an intention to treat analysis, should always be presented. Third, additional bias-reducing techniques, such as concealing treatment assignments from treating physicians and participants (i.e., masking) and using clearly defined exclusion and inclusion criteria, should be used wherever possible.

The development and use of extracorporeal membrane oxygenation in neonates

Extracorporeal membrane oxygenation (ECMO) is the utilization of a modified heart-lung machine to provide temporary support for patients with severe respiratory or cardiac failure. In contrast to patients managed with traditional cardiopulmonary bypass, patients on ECMO undergo cannulation of relatively accessible blood vessels, are maintained at normal body temperature, and only require partial anticoagulation with heparin. Although first developed for use in adults, ECMO has been most successful in the treatment of newborn infants with life-threatening pulmonary failure. Since 1974, over 17,000 infants have received ECMO with a 78% survival rate. There is a 15%-20% incidence of neurodevelopmental disabilities among ECMO survivors.

Ethical problems of evaluating a new treatment for melioidosis

When mortality from melioidosis fell sharply after multiple changes in management at an Australian hospital, doctors wanted to identify whether a new drug was responsible. But designing a trial that was ethically acceptable proved impossible

The randomized controlled trial in studies using biomarkers

The randomized controlled trial (RCT) is a scientific experiment during which observations on the effects of therapy or a preventive action are conducted by the researcher under rigorous control. The purpose of the experiment is to clear the uncertainties surrounding a clinical/research issue and involves isolating the 'treatment' and 'end result' variables from external influences. RCTs therefore make use of scientific method standards: measuring, which includes the possibility of reproducing observations; controlling factors unconnected to the cause-effect relationship of interest; and the external verification or 'falsification' of the cause-effect relationship. Many RCTs are now including biomarkers to answer scientific questions in a more accurate way. In the present methodological paper, the main aspects involved in the design and conduction of a trial are discussed, with special emphasis on the use of biomarkers. Aspects that are often overlooked by scientists involved in the design of trials include multiple comparisons, subgroup analysis, the duration of the observations, the use of surrogate endpoints, and ethical issues. This review summarizes the main issues that should be addressed in a protocol, and illustrates these with an example.

Ethics, data-dependent designs, and the strategy of clinical trials: time to start learning-as-we-go?

The seeds of modern clinical trials were unwittingly sown with the first use of randomization in a 1920s agricultural field experiment. The historical development of trials is briefly reviewed here, as are multifarious pressures and problems faced by those involved with clinical trials today. These challenges include recruitment difficulties, the emerging role of patient support groups, and legal threats over informed consent, to name three. Fundamentally, they reflect an overall shift towards patient-centred, individual ethics. I suggest many problems may be overcome by increased implementation of hitherto neglected, data-dependent designs for clinical trials. Over a dozen arguments against their use are countered, primarily through ethical considerations. Benefits and costs of refining clinical trials strategy are explored hypothetically under enhanced use of such 'learn-as-you-go' designs, in contrast to traditional, equal-allocation, fixed-sample-size and frequentist-based designs. These latter methods mirror crop field trials in which one cannot make scientific progress until after gathering objective data at harvest time. Some attempts to alleviate certain problems, such as Zelen randomization to boost recruitment, or over-reliance on 'large and simple trials' to detect moderate-sized treatment effects, are discussed and found inadequate. A proposal for wider discussion is made to assist the selective introduction of 'small and complex trials,' which could simultaneously expedite medical research, satisfy the concerns of regulators, statisticians, and doctors alike, and help address the growing demands of 21st-century patients.

Ethical issues in oncology biostatistics

A medical statistician's routine professional activities are likely to have important ethical consequences. This is due in part to the fact that good medical practice and scientifically valid medical research both require as precursors high quality statistical design and data analysis. In this paper I discuss various ethical issues that I have encountered while working as a biostatistician at M.D. Anderson Cancer Center. I describe particular experiences and the ethical issues involved. Topics include medical decision making, benefit-harm trade-offs, safety monitoring, adaptive randomization, informed consent, and publication bias.

Evidence, belief, and action: the failure of equipoise to resolve the ethical tension in the randomized clinical trial

Clinical research employing the randomized clinical trial has, traditionally, been understood to pose an ethical dilemma. On the one hand, each patient ought to get the treatment that best meets her needs, as judged by the patient in consultation with her doctor. On the other hand, the method most helpful to advancing our understanding about what treatments are indeed best able to meet patient needs is the randomized trial, which necessitates that each patient's care is decided not by physician judgment or patient choice but instead by random assignment. The tension can be described as a conflict between the interests of individual patients who are sick today, and the interests of the group of people who will become sick in the future and would benefit from advances in medical understanding. How one ought to balance these important and often competing interests is an important ethical question that resists easy resolution.

Adaptive designs for binary treatment responses in phase III clinical trials: controversies and progress

In phase III clinical trials the problem is to compare two treatments or therapies for their effects. The randomized 50:50 allocation to the two competing treatments is popular in most of the cases. In contrast there is a class of adaptive designs available in literature for this purpose. The object is to treat a larger number of patients by the eventual better treatment. A few such adaptive designs were conducted out in practical applications and consequently a lot of controversy arose. In spite of that there is steady theoretical progress in this area over the past three decades. The present paper reviews some of the real-life adaptive clinical trials and discusses some logistics of such trials.

Adaptive designs, informed consent, and the ethics of research

The ethical tension in research design is often characterized as that between individual and collective ethics. While adaptive clinical trials (ACTs) are generally considered to be more sensitive to individual ethics, the concomitant loss of statistical power associated with them is often used to justify randomized clinical trials (RCTs). This paper challenges this characterization of the central ethical problem in research design. It argues that the key consideration in clinical research hinges on the process of informed consent. When the research context is such that the subject is able to provide informed consent, RCTs can be justified and may be required. However, in desperate medical situations the process of informed consent is often undermined. It is argued that in such situations ACTs are ethically required. We introduce "the principle of interchangeability" and argue that it must be satisfied if research in desperate medical situations is to be justified.

Quantifying and documenting prior beliefs in clinical trials

Collecting and documenting subjective prior beliefs from knowledgeable clinicians about the potential results of a clinical trial has many advantages. Two large trials of prophylactic treatments in an HIV-positive population are used as examples. The trials recruited patients of primary care physicians and compared treatments which were in use in clinical practice. Opinions about these trials were elicited from 58 practising HIV clinicians. It is shown how the documented opinions can be used to augment the monitoring process; the prior opinions are updated with interim data using approximate Bayesian methods to give posterior opinions incorporating interim results. These posterior opinions can be used by the monitoring board to anticipate the clinicians' reaction to the results. Eliciting prior beliefs is also ethically important for documenting the nature of the uncertainty or equipoise. Important information is provided for the informed consent process and Institutional Review Board (IRB).

Pros and cons of permutation tests in clinical trials

Hypothesis testing, in which the null hypothesis specifies no difference between treatment groups, is an important tool in the assessment of new medical interventions. For randomized clinical trials, permutation tests that reflect the actual randomization are design-based analyses for such hypotheses. This means that only such design-based permutation tests can ensure internal validity, without which external validity is irrelevant. However, because of the conservatism of permutation tests, the virtues of permutation tests continue to be debated in the literature, and conclusions are generally of the type that permutation tests should always be used or permutation tests should never be used. A better conclusion might be that there are situations in which permutation tests should be used, and other situations in which permutation tests should not be used. This approach opens the door to broader agreement, but begs the obvious question of when to use permutation tests. We consider this issue from a variety of perspectives, and conclude that permutation tests are ideal to study efficacy in a randomized clinical trial which compares, in a heterogeneous patient population, two or more treatments, each of which may be most effective in some patients, when the primary analysis does not adjust for covariates. We propose the p-value interval as a novel measure of the conservatism of a permutation test that can be defined independently of the significance level. This p-value interval can be used to ensure that the permutation test have both good global power and an acceptable degree of conservatism.

Randomized play-the-winner clinical trials: review and recommendations

The randomized play-the-winner rule is an adaptive randomized design, based on an urn model, that is used occasionally in clinical trials. This paper discusses practical and theoretical issues arising from its use, including stratification, delayed response, operating characteristics, selection of urn parameters, and inference. The paper also discusses recent experience with adaptive clinical trials within the pharmaceutical industry. The author concludes that the randomized play-the-winner rule is appropriate for some clinical trials, but intense and thoughtful planning must take place in the design phase. Such planning should incorporate considerations of variability, power, and appropriate techniques.

Ethics and practice: alternative designs for phase III randomized clinical trials

For decades, biostatisticians have developed and refined the methodology for clinical trials with the intent of giving trial participants a better representation than traditional, equal-allocation, fixed sample-size designs. Despite these methodologic advances and ethical advantages, alternative or data-dependent designs for phase III clinical trials, including sequential designs, Bayesian methods, and adaptive designs, have not been widely adopted in practice. We attempt to characterize situations under which these designs are feasible and desirable from ethical and logistical standpoints. In particular, we describe the role of individual and collective ethics in designing clinical trials and argue that greater attention should be paid to the former. We give examples of those alternative designs that have been used in practice, including discussion of their strengths and shortcomings. We conclude that alternative designs are applicable in limited classes of trials and that investigators should consider them more often when planning clinical trials.

Clinical and prophylactic trials with assured new treatment for those at greater risk: I. A design proposal

OBJECTIVES

The accepted sine qua non for estimating the difference in efficacy between a new and a standard treatment is a randomized controlled clinical trial. Yet in some situations it is either practically or ethically impossible to conduct such a trial. For example, patients who are desperately ill may decline to participate when they learn they may not receive the new treatment, especially when that treatment is readily available outside the experimental protocol. Likewise, in a prophylactic trial of a promising vaccine, recruitment of persons at greater risk may falter or fail. Our objective is to demonstrate that a rigorous comparison of treatments may still be attainable.

METHODS

The features of a controlled clinical or prophylactic trial are reviewed from the perspectives of Food and Drug Administration regulations, ethical considerations, and practical problems.

RESULTS

An explicit risk-based allocation method of design and analysis is proposed, one guaranteeing that all subjects at greater risk will receive the new treatment.

CONCLUSIONS

Under certain conditions, a risk-based allocation trial can furnish consistent estimates of both standard and experimental treatment effects for those at greater risk while avoiding certain difficulties caused by randomized treatment allocation.

Randomised consent designs in cancer clinical trials

In 1977, Zelen proposed a new design for clinical trials with the aim of increasing recruitment by avoiding some of the problems associated with obtaining informed consent. These 'randomised consent' designs have proved controversial, and have not often been used. This paper explains the statistical aspects of single and double randomised consent designs and reviews some of the ethical issues. All identified published cancer treatment trials using a randomised consent design are considered in some detail. Reasons for and against the use of these designs are summarised.