Clinical Trials In Psychiatry Research Articles

Investigation of Psychoactive Medications: Challenges and a Practical and Scalable New Path.

In the last two decades the validity of clinical trials in psychiatry has been subject to discussion. The most accepted clinical study method in the medical area, randomized controlled trial (RCT), faces significant problems when applied to the psychiatric world. One of the causes for this scenario is the strict participant inclusion and exclusion criteria that may not represent the real world. The inconsistency of the different endpoint parameters that are used in the field is another cause. We think that psychiatric RCTs' challenges, together with the underlying complexity of psychiatry, lead to a problematic clinical practice. Today, psychoactive drugs are routinely tested not in an official clinical trial setting. Off-label psychoactive drugs are commonly prescribed, and other substances, such as herbal remedies, are also regularly consumed. Learning from those real-life experiments can teach us useful lessons. Real-world data (RWD) includes information about heterogeneous patient populations, and it can be measured with standardized parameters. Collecting RWD can also address the need for systematically documenting and sharing case reports' outcomes. We suggest using digital tools to capture objective and continuous behavioral data from patients passively. New conclusions will be constantly drawn, possibly allowing more personalized treatment outcomes. The relevant next-generation decision support tools are already available.

Unblinding and demand characteristics in the treatment of depression

Blinding of treatment allocation in clinical trials in psychiatry is regarded as an ideal. The potential impact of unblinding chimes with a general concern for psychological research: so-called demand characteristics can undermine confidence in findings from experimental and clinical studies. Scepticism can result in nihilism. The reliance on subjective report of symptoms in clinical trials of drug efficacy in depression provides an important example. It is regularly implied that if subjective effects, including specific adverse reactions, unblind participants to an active treatment then evidence for its efficacy is suspect. In fact, the strong association between dose and subjective effects does not translate into a strong relationship with efficacy in randomised controlled trials (RCTs) of conventional antidepressant drugs; this observation falsifies the proposition that unblinding is the principal mechanism driving RCT outcomes in studies of depression. Instead, changes in brain function, that occur soon after treatment starts, do predict treatment outcomes and align with our understanding of neurotransmitter effects from neuroscience. Psychedelic experience for the treatment of depression must be unblinding, but the effect results directly from serotonergic receptor activation and changes in brain connectivity. Where such effects are part of a novel mechanism of action, a strong dose response relationship would be expected, irrespective of unblinding. We highlight the importance of exploring blinding as a mechanism, confirming dose-related outcomes, and dissociating unblinding effects from efficacy. Unblinding does not necessarily invalidate the subjective experience of sustained recovery from depression.

Everyday transgressions of borderlines: the scandalization of clinical drug trials of the psychiatrist Roland Kuhn

"Experimental case Münsterlingen: clinical trials in psychiatry, 1940-1980" is the name of the report of acontrol commission established by the government of the Swiss Canton Thurgau in 2016, after several articles in the press after 2012 had criticized the drug tests carried out by Roland Kuhn, the former clinical director of the cantonal mental hospital in Münsterlingen. The report discusses "fine discrepancies in everyday borderline transgressions" "from today's viewpoint". These borderline transgressions were seen especially in the missing, inadequate or undocumented informed consent of patients and in the usage of test substances, which varied between the (mostly) accepted or not refused intake and the camouflaged or (seldom) threatened application via injection. Thus, the report shows on the one hand, the considerable development of the normative context of treatment of mentally ill patients in the past 70years and on the other hand, with its detailed descriptions, it can sensitize today's therapists to the pertinent context. But most of all this is the story of Roland Kuhn, the responsible psychiatrist and the drug testing discoverer of the antidepressive effect of imipramine. This story of the discovery is judged from very differing perspectives and is thus relativized, all the way from observations of a"provincial psychiatrist" to consideration for the Nobel Prize. At the same time critically evaluated traits of Kuhn's personality seem to have influenced the occasionally negative comments of the commission report. We should recognize, however, that with his qualitative and psychopathological individual case observations, Kuhn discovered the antidepressive effect of atest substance that as ahypothesis was verified by subsequent quantitative and statistical methods.

Stress and Coping With the COVID-19 Pandemic: A Survey of Psychiatric Patients at Clinical Trial Sites

Recent research on the COVID-19 pandemic suggests that individuals who suffer with serious mental illness (SMI) is at heightened risk of infection and have increased mortality, due to their illness or lack of access to healthcare. As a consequence, progress in developing new treatments for the SMI have been disrupted, with many interruptions and holds places on clinical trials in psychiatry due to concerns regarding the pandemic and its risks to SMI patients.

Closed-Loop Transcranial Alternating Current Stimulation: Towards Personalized Non-invasive Brain Stimulation for the Treatment of Psychiatric Illnesses

This review introduces closed-loop transcranial alternating current stimulation (tACS), which has the potential to become an effective and safe treatment modality for psychiatric illnesses such as schizophrenia and depression. The weak electric fields delivered to the brain by transcranial current stimulation interact in a synergistic manner with endogenous rhythmic brain activity patterns. As a result, the effect of stimulation on neuronal network dynamics is state dependent. Therefore, closed-loop paradigms that measure brain activity and apply targeted stimulation based on these measurements may allow effective modulation by targeted low-amplitude stimulation that is tuned to modulate the measured activity. Few initial studies of such closed-loop tACS have recently documented successful target engagement, mostly for applications that target specific activity patterns during sleep. Given the urgent need of novel therapeutic interventions for psychiatric disorders and the recent promising data from initial tACS clinical trials in psychiatry, we propose that closed-loop tACS deserves attention as a promising personalized medicine strategy in psychiatry.

Biomarkers in Neuropsychiatry: A Prospect for the Twenty-First Century?

The search for biomarkers to aid in the diagnosis and prognosis of psychiatric conditions and predict response to treatment is a focus of twenty-first century medicine. The current lack of biomarkers in routine use is attributable in part to the existing way mental health conditions are diagnosed, being based upon descriptions of symptoms rather than causal biological evidence. New ways of conceptualizing mental health disorders together with the enormous advances in genetic, epidemiological, and neuroscience research are informing the brain circuits and physiological mechanisms underpinning behavioural constructs that cut across current diagnostic DSM-5 categories. Combining these advances with 'Big Data', analytical approaches offer new opportunities for biomarker development. Here we provide an introductory perspective to this volume, highlighting methodological strategies for biomarker identification; ranging from stem cells, immune mechanisms, genomics, imaging, network science to cognition. Thereafter we emphasize key points made by contributors on affective disorders, psychosis, schizophrenia, and autism spectrum disorder. An underlying theme is how preclinical and clinical research are informing biomarker development and the importance of forward and reverse translation approaches. In considering the exploitation of biomarkers we note that there is a timely opportunity to improve clinical trial design informed by patient 'biological' and 'psychological' phenotype. This has the potential to reinvigorate drug development and clinical trials in psychiatry. In conclusion, we are poised to move from the descriptive and discovery phase to one where biomarker panels can be evaluated in real-life cohorts. This will necessitate resources for large-scale collaborative efforts worldwide. Ultimately this will lead to new interventions and personalized medicines and transform our ability to prevent illness onset and treat complex psychiatric disorders more effectively.

Factors influencing participation of psychiatry inpatients in clinical trials.

Serious concerns have arisen in recent years regarding the unethical and illegal practices resorted to during clinical trials. Clinical trials in psychiatry are further complicated by issues such as 'validity of consent' and 'decision making capacity' of patients. This study was planned to explore the factors determining patient participation in clinical trials. A random sample of 123 consenting psychiatry inpatients were provided the information and consent-form of a hypothetical clinical drug trial. They were interviewed regarding their decision, the decision maker and factors that led to the decision. Family members tended to be the decision makers when patients were females, had low-income, were from rural background or had severe illnesses. Anticipated side effects and not wanting to interfere with existing treatment were the common reasons for refusal to participate while hope of betterment of the patient and benefit to humanity were cited for consent. The educated, urban, affluent class had more awareness regarding unethical trials and tended to be mistrustful of the medical community leading to higher rates of non-participation. Those who were adherent with ongoing treatment were also unwilling to participate. The lesser educated, low-income patients and rural domicile patients on the other hand had lesser awareness regarding clinical trials, trusted doctors and were more likely to participate. A good doctor-patient relationship, detailed explanations and clarification regarding the study and its conduct, and building awareness regarding clinical trials among vulnerable groups is necessary to ensure a valid consent involving no coercion, removal of prejudices, and ethical conduct of trials.

Are we failing clinical trials? A case for strong aggregate outcomes.

Clinical trials in psychiatry inherit methods for design and statistical analysis from evidence-based medicine. However, trials in other clinical disciplines benefit from a more specific relationship between instruments that measure disease state (e.g. biomarkers, clinical signs), the underlying pathology and diagnosis such that primary outcomes can be readily defined. Trials in psychiatry use diagnosis (i.e. a categorical label for a syndrome) as a proxy for the underlying disorder, and outcomes are defined, for example, as a percentage change in a univariate total score on some clinical instrument. We label this approach to defining outcomes weak aggregation of disease state. Univariate measures are necessary, because statistical methodology is both tractable and well-developed for scalar outcomes, but we show that weak aggregate approaches do not capture disease state sufficiently, potentially leading to loss of information about response to intervention. We demonstrate how multivariate disease state can be captured using geometric concepts of spaces defined over routine clinical instruments, and show how clinically meaningful disease states (e.g. representing different profiles of symptoms, recovery or remission) can be defined as prototypes (geometric locations) in these spaces. Then, we show how to derive univariate (scalar) measures, which capture patient's relationships to these prototypes and argue these represent strong aggregates of disease state that may be a better basis for outcome measures. We demonstrate our proposal using a large publically available dataset. We conclude by discussing the impact of strong aggregates for analyses in traditional and novel trial designs.

Que peut-on attendre des essais cliniques en psychiatrie ?

Clinical trials in psychiatry allow to build the regulatory dossiers for market authorization but also to document the mechanism of action of new drugs, to build pharmacodynamics models, evaluate the treatment effects, propose prognosis, efficacy or tolerability biomarkers and altogether to assess the impact of drugs for patient, caregiver and society. However, clinical trials have shown some limitations. Number of recent dossiers failed to convince the regulators. The clinical and biological heterogeneity of psychiatric disorders, the pharmacokinetic and pharmacodynamics properties of the compounds, the lack of translatable biomarkers possibly explain these difficulties. Several breakthrough options are now available: quantitative system pharmacology analysis of drug effects variability, pharmacometry and pharmacoepidemiology, Big Data analysis, brain modelling. In addition to more classical approaches, these opportunities lead to a paradigm change for clinical trials in psychiatry.

Quel est le rôle des tests et examens complémentaires dans un essai clinique en psychiatrie ?

As in the usual care of patients, paraclinical investigations have today only a very modest role in clinical trials in psychiatry, mainly to complete the pre-therapeutical assessments prior to inclusion of subjects or to monitor treatment tolerance. Yet, the accumulation of data in neurosciences suggests the next emergence of biomarkers, whose interest is that they are closely associated to the biological disturbances underlying psychiatric illnesses, and that they are accessible by means of technological tools such as imaging devices. These tools allow to explore the effects on brain of psychotropic medications, such as antidepressants, antipsychotics, or mood stabilizers, in relation to their therapeutic action. The obtained results allow to consider the use of such biomarkers in clinical trials in addition to more conventional approaches. In particular, they could be used as targets to measure brain response to treatment in association with clinical response, to predict a therapeutic response from the neurofunctional characteristics of patients, or to establish the safety profile of drugs on the nervous system. The use of such biomarkers in clinical trials would help to better define the explored populations and their characteristics, as well as the variables to assess, and to better measure the impact of the treatments and their potential harmful effects on the nervous system.

Handling clinical comorbidity in randomized clinical trials in psychiatry

The purpose of this paper is to a) outline the importance of including patients with clinical comorbidities in Randomized Clinical Trials (RCTs) of psychiatric treatments; and b) to propose a specific approach for best handling, analyzing and interpreting the data on clinical comorbidities in terms of their impact on treatment outcomes. To do this we first define and describe clinical comorbidity and differentiate it from other forms of comorbidity. We then describe the methodological and analytical problems associated with excluding patients with clinically comorbid conditions from RCTs, including the impact on the outcomes of RCTs in psychiatry and the impact on evidence-based clinical decision-making. We then address the challenges inherent to including patients with clinical comorbidities in RCTs. Finally, we propose a methodological and analytic approach to deal with these issues in RCTs which aims to significantly improve the information yielded from RCTs in psychiatry, and thus improve clinical decision-making.

Use of the experience sampling method in the context of clinical trials

ObjectiveThe experience sampling method (ESM) is a structured diary technique to appraise subjective experiences in daily life. It is applied in psychiatric patients, as well as in patients with somatic...

Joint modeling of dropout and outcome in three pivotal clinical trials of schizophrenia

BackgroundDropout is a serious challenge to clinical trials in psychiatry, yet standard outcome analyses with mixed models do not account for dropout, while joint modeling uses dropout from a survival model to adjust the outcome from a mixed model, but is untested in clinical trials of schizophrenia. AimsTo compare mixed and joint modeling in three acute phase pivotal placebo controlled trials of schizophrenia. MethodData were reanalyzed on 611 in-patients with acute schizophrenia who participated in three pivotal randomized controlled trials that compared placebo with olanzapine or risperidone (dropout rates placebo: 62.6% and medication: 37.4%). The outcome measures were BPRS or PANSS total change scores. Mixed-effects models for repeated measures and joint models were computed and compared to examine the time-treatment interaction. Effect size comparisons were made. ResultsAntipsychotic treatment was superior to placebo across analyses. Time treatment interactions were significant (p<.05) for the mixed (beta=2.33) and joint models (beta=2.62). Compared with mixed modeling, joint modeling reduced the estimated change score for treatment (21.24 vs 19.74) and placebo (1.64 vs −1.11). The effect size differences between placebo and treatment groups were greater for joint (ES=.89) than mixed modeling (ES=0.83). Sensitivity analysis replicated this trend of results in each of the three trials. ConclusionCompared to mixed modeling, joint modeling results in a greater separation between treatment and placebo groups. This offers preliminary evidence that joint modeling may be useful in the analysis of antipsychotic placebo controlled RCTs.

Clinical Trials in Psychiatry and Clinical Psychology: Science or Product Testing?

During the recent era of evidence-based medicine, the randomized controlled trial (RCT) has been regarded as the most authoritative method of evaluating interventions. The methodology is utilized not only in medicine, but in other fields such as economics, education, and agriculture. In psychiatry and clinical psychology, RCTs have been utilized extensively in conjunction with the Diagnostic and Statistical Manual of the American Psychiatric Association (DSM) [1]. This RCT/DSM combination has produced somewhat limited progress, both in identifying efficacious treatments and in facilitating progress in better understanding the scientific foundations of clinical intervention in these fields. This unhappy circumstance results not from limitations of the RCT as a tool of inductive logic, but rather its use with data that are neither theoretically grounded nor psychometrically sound, under background conditions in which publication bias and economic interest converge to distort the rational, impartial use of the RCT. Until the biases due to human interests are reduced and the fields of psychiatry and clinical psychology are more scientifically advanced, the RCT will be of limited use.

Transcranial direct current stimulation in psychiatric disorders.

The interest in non-invasive brain stimulation techniques is increasing in recent years. Among these techniques, transcranial direct current stimulation (tDCS) has been the subject of great interest among researchers because of its easiness to use, low cost, benign profile of side effects and encouraging results of research in the field. This interest has generated several studies and randomized clinical trials, particularly in psychiatry. In this review, we provide a summary of the development of the technique and its mechanism of action as well as a review of the methodological aspects of randomized clinical trials in psychiatry, including studies in affective disorders, schizophrenia, obsessive compulsive disorder, child psychiatry and substance use disorder. Finally, we provide an overview of tDCS use in cognitive enhancement as well as a discussion regarding its clinical use and regulatory and ethical issues. Although many promising results regarding tDCS efficacy were described, the total number of studies is still low, highlighting the need of further studies aiming to replicate these findings in larger samples as to provide a definite picture regarding tDCS efficacy in psychiatry.

The use of clinical trials in comparative effectiveness research on mental health

ObjectivesA large body of comparative effectiveness research (CER) focuses on the use of observational and quasi-experimental approaches. We sought to examine the use of clinical trials as a tool for CER, particularly in mental health. Study Design and SettingExamination of three ongoing randomized clinical trials in psychiatry addressing issues that would pose difficulties for nonexperimental CER methods. ResultsExisting statistical approaches to nonexperimental data appear insufficient to compensate for biases that may arise when the pattern of missing data cannot be properly modeled such as when there are no standards for treatment, when affected populations have limited access to treatment, or when there are high rates of treatment dropout. ConclusionClinical trials should retain an important role in CER, particularly in cases of high disorder prevalence, large expected effect sizes, difficult-to-reach populations, or when examining sequential treatments or stepped-care algorithms. Progress in CER on mental health will require careful consideration of appropriate selection between clinical trials and nonexperimental designs and on allocation of research resources to optimally inform key treatment decisions for each patient.

Response to Hasin et al. Letter

Response to Hasin et al. Letter

DSM-5 and clinical trials in psychiatry: challenges to come?

The publication of the fifth version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) in 2013 raises important questions for clinical trials and associated regulatory decisions on new drugs for psychiatric disorders.

Independent Data and Safety Monitoring in Psychiatric Intervention Research

A data and safety monitoring board (DSMB) is a multidisciplinary group of scientists that monitors a randomized clinical trial. Although DSMBs have been used for clinical trials in cardiology, oncology, and infectious disease for decades, it was not until the late 1990s that the National Institute of Mental Health (NIMH) initially required a DSMB for some of its larger trials. The NIMH mandate expanded during the succeeding decade to require DSMBs for many of the clinical trials in psychiatry. In turn, the need for board members has grown quickly. The objective of this commentary is to consider the purpose of a DSMB and to describe its roles, responsibilities, composition, and implementation. The rationale for a DSMB is to ensure the integrity and validity of the trial and, most importantly, to protect the safety of trial participants. A board conducts comprehensive reviews of accumulating unblinded data for safety and, in some trials, for efficacy. Reviewers examine adverse events and serious adverse events at regular intervals during the course of the trial. In addition, a DSMB monitors recruitment, randomization, retention, adherence, and follow-up in an effort to evaluate the validity of a trial. Because it is unethical to expose a participant to the risks of an experiment that will be unable to answer the scientific question that was postulated, a board should also evaluate the study protocol prior to trial commencement. Ultimately, a DSMB's responsibilities are broader than that of the trial being monitored. It will protect potential study participants and eventually could affect patients seeking clinical treatment for the disorder being studied.

A Brief History of Placebos and Clinical Trials in Psychiatry

The history of placebos in psychiatry can be understood only in the context of randomized controlled trials (RCTs). Placebo treatments are as old as medicine itself, and are particularly effective in dealing with psychosomatic symptoms. In psychiatry, placebos have mainly been featured in clinical drug trials. The earliest controlled trial in psychiatry (not involving drugs) occurred in 1922, followed by the first crossover studies during the 1930s. Meanwhile the concept of randomization was developed during the interwar years by British statistician Ronald A Fisher, and introduced in 3 trials of tuberculosis drugs between 1947 and 1951. These classic studies established the RCT as the gold standard in pharmaceutical trials, and its status was cemented during the mid-1950s. Nevertheless, while the placebo became established as a standard measure of drug action, placebo treatments became stigmatized as unethical. This is unfortunate, as they constitute one of the most powerful therapies in psychiatry. In recent years, moreover, the dogma of the placebo-controlled trial as the only acceptable data for drug licensing is also being increasingly discredited. This backlash has had 2 sources: one is the recognition that the US Food and Drug Administration has been too lax in permitting trials controlled with placebos alone, rather than also using an active agent as a test of comparative efficacy. In addition, there is evidence that in the hands of the pharmaceutical industry, the scientific integrity of RCTs themselves has been degraded into a marketing device. The once-powerful placebo is thus threatened with extinction.