The use of composite outcomes is becoming widespread in clinical trials. By combining individual outcome measures into a composite, researchers claim a composite can increase statistical precision and trial efficiency, expediting the trial by reducing sample size and cost, and consequently enabling researchers to answer questions that could not otherwise be answered. Another rationale given for using a composite is that it provides a measure of the net effect of the intervention that is more patient-relevant than any single outcome measure. (...) Critics, on the other hand, argue that the use of composites threatens the scientific objectivity of the trial by introducing new risks, and that in practice components are inconsistently defined, unreasonably combined, and inadequately reported. Philosophical scrutiny can help shed light in these disagreements and disentangle ethical and epistemological issues of composites in clinical trials. I examine common use of composites in cardiovascular trials, and show how composite results can be problematic, even misleading, if the proper range of scientific decisions and their consequences are ignored when judging the composite. Philosophies of science that are principled on normative versions of the argument from inductive risk can help explicate issues with composites. I conclude by suggesting ways of remedying composite issues in clinical trials. (shrink)

Stopping rules — rules dictating when to stop accumulating data and start analyzing it for the purposes of inferring from the experiment — divide Bayesians, Likelihoodists and classical statistical approaches to inference. Although the relationship between Bayesian philosophy of science and stopping rules can be complex (cf. Steel 2003), in general, Bayesians regard stopping rules as irrelevant to what inference should be drawn from the data. This position clashes with classical statistical accounts. For orthodox statistics, stopping rules do matter to (...) what inference should be drawn from the data. "The dispute over stopping rule is far from being a marginal quibble, but is instead a striking illustration of the divergence of fundamental aims and standards separating Bayesians and advocates of orthodox statistical methods" (Steel 2004, 195) ... (shrink)

This paper analyzes statistical decisions during the interim analyses of clinical trials. After some general remarks about the ethical and scientific demands of clinical trials, I introduce the notion of a hard-case clinical trial, explain the basic idea behind it, and provide a real example involving the interim analyses of zidovudine in asymptomatic HIV-infected patients. The example leads me to propose a decision analytic framework for handling ethical conflicts that might arise during the monitoring of hard-case clinical trials. I use (...) computer simulations to show how the framework can assist in reconciling certain ethical conflicts. The framework is partial, lacking the precision of a complete systematization of statistical monitoring procedures in practice. (shrink)

Decision-making by a Data and Safety Monitoring Board (DSMB) regarding clinical trial conduct and termination is intricate and largely limited by cases and rules. Decision-making by legal jury is also intricate and largely constrained by cases and rules. In this paper, I argue by analogy that legal decision-making, which strives for a balance between competing demands of conservatism and innovation, supplies a good basis to the logic behind DSMB decision-making. Using the doctrine of precedents in legal reasoning as my central (...) analog will lead us to a decision-theoretic analogy for much more systematic documentation of decisions in clinical trials. My conclusion is twofold: every DSMB decision should articulate a clear general principle (a ratio decidendi) that gives reason for the decision; and all such decisions should be made public. I use Bartha’s (2010) theory of analogical arguments to both frame and assess my argument by analogy. (shrink)

Error statistics is an important methodological view in philosophy of statistics and philosophy of science that can be applied to scientific experiments such as clinical trials. In this paper, I raise two potential issues for ES when it comes to guiding, and explaining early stopping of randomized controlled trials : ES provides limited guidance in cases of early unfavorable trends due to the possibility of trend reversal; ES is silent on how to prospectively control error rates in experiments requiring multiple (...) interim analyses. The method of conditional power, together with a rationing principle for RCTs, can assist ES in addressing such issues. (shrink)

We advocate and share the same theoretical framework for empirical research in ethics as exemplified in Christina Bicchieri’s The Grammar of Society. Our research differs from Bicchieri’s in our approach to experimentation: where she relies on lab experiments, we have constructed an experimental platform based on an internet survey instrument; where she relies on rational reconstructions, we do not. In this paper we focus on four contrasts in our methods: (1) we provide a space to explore ethical influence and norm (...) transmission between participants, belief and choice revision, and reputation over time; (2) we provide ways for participants to expand the context of their and others’ decisions; (3) we focus on more realistic ethical decisions than is allowed by games; and (4) we explain why Bicchieri’s method of rational reconstructions presents challenges to her theory of social norms. Our methods are complementary to Bicchieri’s, and together we can work toward developing more comprehensive empirically informed ethics. †To contact the authors, please write to Peter Danielson, W. Maurice Young Centre for Applied Ethics, University of British Columbia, 227‐6356 Agricultural Road, Vancouver, V6T 1Z2, Canada; e‐mail: [email protected]. (shrink)

A central issue confronting both philosophers and practitioners in formulating an analysis of causation is the question of what constitutes evidence for a causal association. From the 1950s onward, the biostatistician Jerome Cornfield put himself at the center of a controversial debate over whether cigarette smoking was a causative factor in the incidence of lung cancer. Despite criticisms from distinguished statisticians such as Fisher, Berkson and Neyman, Cornfield argued that a review of the scientific evidence supported the conclusion of a (...) causal association. Cornfield's odds ratio in case‐control studies — as a good estimate of relative risk — together with his argument of ''explanatory common cause'' became important tools to use in confronting the skeptics. In this paper, I revisit this important historical episode as recorded in the Journal of National Cancer Institute and the Journal of the American Statistical Association. More specifically, I examine Cornfield's necessary condition on the minimum magnitudes of relative risk in light of confounders. This episode yields important insight into the nature of causal inference by showing the sorts of evidence appealed to by practitioners in supporting claims of causal association. I discuss this event in light of the manipulationist account of causation. (shrink)

Despite efforts from regulatory agencies (e.g. NIH, FDA), recent systematic reviews of randomised controlled trials (RCTs) show that top medical journals continue to publish trials without requiring authors to report details for readers to evaluate early stopping decisions carefully. This article presents a systematic way of modelling and simulating interim monitoring decisions of RCTs. By taking an approach that is both general and rigorous, the proposed framework models and evaluates early stopping decisions of RCTs based on a clear and consistent (...) set of criteria. The framework allows decision analysts to generate and quickly answer ‘what-if’ questions by simulating alternate trial scenarios. I illustrate the framework with a case study of an RCT that was stopped early due to harm. This was a trial of vitamin A supplement in relation to HIV transmission from mother-to-child through breastfeeding. (shrink)

This article presents a quantitative way of modeling the interim decisions of clinical trials. While statistical approaches tend to focus on the epistemic aspects of statistical monitoring rules, often overlooking ethical considerations, ethical approaches tend to neglect key epistemic dimension. The proposal is a second-order decision theoretic framework. The framework provides means for retrospective assessment of interim decisions based on a clear and consistent set of criteria that combines both ethical and epistemic considerations. The framework is broadly Bayesian and addresses (...) a fundamental question behind many concerns about clinical trials: What does it take for an interim decision (e.g., whether to stop the trial, or continue) to be a good decision? I provide simulation illustrating the modeling of interim decisions counterfactually using the framework. (shrink)

When is clinical research ethical? The difficulty in answering this question lies in the dual nature of research on human subjects, which yields two somewhat conflicting sets of obligations. On the one hand, there is the traditional view of science that includes the idea of an obligation to learn about the world. On the other hand, there is the obligation of care on the part of researchers towards individual participants in the research ...

Philosophers subscribing to particular principles of statistical inference and evidence need to be aware of the limitations and practical consequences of the statistical approach they endorse. The framework proposed (for statistical inference in the field of medicine) allows disparate statistical approaches to emerge in their appropriate context. My dissertation proposes a decision theoretic model, together with methodological guidelines, that provide important considerations for deciding on clinical trial conduct. These considerations do not amount to more stopping rules. Instead, they are principles (...) that address the complexity of interpreting and responding to interim data, based on a broad range of epistemic and ethical factors. While they are not stopping rules, they would assist a Data Monitoring Committee in judging its position with regard to necessary precautionary interpretation of interim data. By vindicating a framework that accommodates a wide range of approaches to statistical inference in one important setting (clinical trials), my results pose a serious challenge for any approach that advocates a single, universal principle of statistical inference. (shrink)

Justice and Health Care: Selected Essays collects, in a systematic but non-chronological fashion, ten of Buchanan’s most significant essays on justice and health care, written over a period of almost three decades. As the Obama administration continues to struggle to implement much-needed comprehensive health care reform in the hopes of controlling rising health care costs and extending affordable health care to over 46 million uninsured Americans, there could hardly be a more appropriate time to read Buchanan’s selected essays.