Inefficacy interim monitoring procedures in randomized clinical trials: the need to report

If definitive evidence concerning treatment effectiveness becomes available from an ongoing randomized clinical trial, then the trial could be stopped early, with the public release of results benefiting current and future patients. However, stopping an ongoing trial based on accruing outcome data requires methodological rigor to preserve validity of the trial conclusions. This has led to the use of formal interim monitoring procedures, which include inefficacy monitoring that will stop a trial early when the experimental treatment appears not to be working. For participants, inefficacy monitoring is especially important as it ensures that they are not being treated worse than if they had not enrolled on the trial. We discuss the importance of reporting with trial results the formal interim inefficacy monitoring guidelines that were utilized, and, if none were used, the reasons for their absence. A survey of two leading medical journals suggests that this is not current practice.     

Cluster randomized trials with treatment noncompliance

Cluster randomized trials (CRTs) have been widely used in field experiments treating a cluster of individuals as the unit of randomization. This study focused particularly on situations where CRTs are accompanied by a common complication, namely, treatment noncompliance or, more generally, intervention nonadherence. In CRTs, compliance may be related not only to individual characteristics but also to the environment of clusters individuals belong to. Therefore, analyses ignoring the connection between compliance and clustering may not provide valid results. Although randomized field experiments often suffer from both noncompliance and clustering of the data, these features have been studied as separate rather than concurrent problems. On the basis of Monte Carlo simulations, this study demonstrated how clustering and noncompliance may affect statistical inferences and how these two complications can be accounted for simultaneously. In particular, the effect of the intervention on individuals who not only were assigned to active intervention but also abided by this intervention assignment (complier average causal effect) was the focus. For estimation of intervention effects considering noncompliance and data clustering, an ML-EM estimation method was employed.     

The augment effect of negative affective background on positive stimulus: Two randomized controlled trials

Based on the affective endowment-contrast theory, negative affect (NA) is hypothesized to augment positive affect (PA). Study 1 examined this contrast effect (augment effect) in a laboratory setting. Participants (n?=?94) were assigned into positive, negative or neutral affective background conditions through false feedback procedure, and then a same positive stimulus was given to all participants. Results indicated that participants in negative condition experienced more feelings of PA and less NA after receiving the positive stimulus compared to the other two conditions. Study 2 investigated this augment effect under naturalistic context. Participants (n?=?150) were classified into high positive, high negative, or mild positive affective background groups based on their naturally occurred affects. Then a positive manipulation was giving to all participants. Results indicated that participants in the high negative group experienced the most decrease in feelings of NA after receiving the positive manipulation. Results from the two studies provided evidence to the endowment-contrast theory, indicating that the valance of positive stimulus was augmented under negative affective background.     

Statistical power and optimal design for multisite randomized trials

The multisite trial, widely used in mental health research and education, enables experimenters to assess the average impact of a treatment across sites, the variance of treatment impact across sites, and the moderating effect of site characteristics on treatment efficacy. Key design decisions include the sample size per site and the number of sites. To consider power implications, this article proposes a standardized hierarchical linear model and uses rules of thumb similar to those proposed by J. Cohen (1988) for small, medium, and large effect sizes and for small, medium, and large treatment-by-site variance. Optimal allocation of resources within and between sites as a function of variance components and costs at each level are also considered. The approach generalizes to quasiexperiments with a similar structure. These ideas are illustrated with newly developed software.     

Placebo and criminal law

This article considers issues concerning cases where the use of placebo is lawful or is not lawful under aspects of German criminal law. It will differentiate between cases of individual therapy and cases of supervised experiments within the scope of medical tests. Thereby, it reveals that a medication of placebo with regard to an individual patient seems to be lawful if there is no alternative possibility of a better treatment using a chemically effective medicine and if the limits of presumed consent are complied with. On the other hand, in the context of the supervised experiment, the assignment of a patient to a group treated with placebo is only lawful if the patient has been fully informed about the possibilities of a treatment and if the patient has given consent to it. An earlier version of this paper was presented at an international conference, “Placebo: Its Action and Place in Health Research Today,” held in Warsaw, Poland on 12–13 April, 2003. The author’s interests include International Criminal Law, Comparative Criminal Law and Philosophy of Law.     

Placebo Effects and Informed Consent

The concepts of placebos and placebo effects refer to extremely diverse phenomena. I recommend dissolving the concepts of placebos and placebo effects into loosely related groups of specific mechanisms, including (potentially among others) expectation-fulfillment, classical conditioning, and attentional-somatic feedback loops. If this approach is on the right track, it has three main implications for the ethics of informed consent. First, because of the expectation-fulfillment mechanism, the process of informing cannot be considered independently from the potential effects of treatment. Obtaining informed consent influences the effects of treatment. This provides support for the authorized concealment and authorized deception paradigms, and perhaps even for outright deceptive placebo use. Second, doctors may easily fail to consider the potential benefits of conditioning, leading them to misjudge the trade-off between beneficence and autonomy. Third, how attentional-somatic feedback loops play out depends not only on the content of the informing process but also on its framing. This suggests a role for libertarian paternalism in clinical practice.     

Government initiatives in autism clinical trials

Randomized clinical trials remain the most valid method of testing the efficacy and safety of treatments. While efforts to elucidate the genetic and neurodevelopmental bases of autism are underway, clinicians and families are in need of scientifically valid information on how to best treat patients with autism. The effectiveness of many interventions currently used in communities has not been adequately tested. Given the high public health relevance of autism treatment research and the low interest of the pharmaceutical industry in autism, the role of the National Institutes of Health in supporting this research is paramount. Among recently launched initiatives in autism clinical trials, there are the Research Units on Pediatric Psychopharmacology Autism Network and the network of centers for Studies to Advance Autism Research and Treatment. These and other government activities in the area of autism clinical trials are here briefly reviewed.