Psychiatric Clinical Trials Research Articles

Systematic reviews and meta-analyses on major depressive disorder: a bibliometric perspective.

There is a vast amount of evidence-based medicine research on the major depressive disorder (MDD) available in the literature, however, no studies on the overall performance, productivity and impact of such research have been published to date. This study explored and mapped the research outputs of MDD-related systematic reviews and meta-analyses (SR/MA) from a bibliometric perspective. Relevant data were retrieved with search terms on MDD, systematic review and meta-analysis. A total of 4,870 papers with 365,402 citations published from 1983 to 2022 were included in the analysis. The publication output has grown steadily over time with the most publications originating from the USA (1,020; 20.94%), the UK (516; 10.60%) and China (448; 9.20%). The research collaborations between countries were most frequent between the USA and UK (266; 5.46%). Journal of Affective Disorders (379; 7.78%) was the most productive journal, while Cuijpers P was the most productive author (121; 2.48%), and University of Toronto (569; 11.78%) was the most productive institution. The top 10 most cited articles on MDD-related SR/MA had citations ranging from 1,806 to 3,448. The high-frequency keywords were mainly clustered into four themes, including psychiatric comorbidities, clinical trials, treatment, and brain stimulation in MDD. The rapid increase in the number of SR/MA of MDD in recent years highlights the importance of this research field. Psychiatric comorbidities, clinical interventions, and treatment of MDD have been identified as hot topics, while biological mechanisms in MDD are likely to be an emerging research priority.

Real Time Quality Assurance of Depression Ratings in Psychiatric Clinical Trials

Real Time Quality Assurance of Depression Ratings in Psychiatric Clinical Trials

The field of psychiatry is in crisis. The case for causal modelling in observational data as a supplement to psychiatric epidemiology and clinical trials

IntroductionThe field of psychiatry is in a crisis. Developments in pharmacology and psychotherapy, reforms in services, increased spending and reduced treatment-gap have not substantially improved prognosis for patients in psychiatry. Mental disorder remains lethal short-term and disabling long term. In comparison, prognosis has improved dramatically in oncology and cardiology. Controversies in psychiatry are causing variation in clinical practice between hospitals, even within single-provider health systems. There is, for example, variation in rates of ADHD, use of coercive measures, and medication (type of drugs, dose and duration of medication). Current empirical methods are incapable of solving the major controversies in psychiatry. Epidemiology struggles with residual confounding, bias and reverse causality. Randomized controlled trials are expensive and time-consuming. Ethics may also be a barrier for clinical studies investigating variation in clinical practice. From a health management point of view, variation in clinical services within a single-provider system is usually indicative of variation in quality. However, the variability in service delivery caused by these controversies creates a lottery-like situation for the individual patient, who is generally unaware of the crisis in psychiatry, and blinded to the ongoing lottery.ObjectivesWe will present a third empirical approach beyond randomized controlled trials and epidemiology which may help solve the crisis.MethodsA systematic review of preference-based instrument variable analyses.ResultsWe identified relevant high quality 185 studies, though almost none in mental health.ConclusionsCausal modelling in observational data has potential as a third paradigm beyond RCTs and epidemiology, and may help solve the crisis in psychiatry.DisclosureNo significant relationships.

Assessing the impact of COVID-19 on psychiatric clinical trials

ObjectiveCOVID-19 and associated measures to control the spread of the COVID-19 has significantly impacted clinical research. This study aimed to determine the impact COVID-19 has had on psychiatric clinical trials and to assess whether certain trial areas or trial types were differentially affected. MethodsWe used information from ClinicalTrials.gov, the largest online database of clinical trial information, to examine changes in psychiatric clinical trials from January 2010–December 2020. ResultsClinical trial initiation decreased in 2020, with a year-on-year percent change in trial initiation of −5.4% versus an expected percent change based on forecasting observed trends from 2010 to 2019 of 8.6%. When broken down by disease area, the distribution of trials observed in 2020 was significantly different from the predicted distribution (p < 0.00001). The greatest decrease in trial initiation was seen in Schizophrenia-specific trials, with an observed percent change of −29.2% versus an expected percent change of 3.2%. Conversely, anxiety trials saw a significant increase in trial initiation during 2020, with an observed percent change of 24.6% versus an expected percent change of 16.0%. When assessing interventional versus observational studies, data showed a significant increase in initiation of observational psychiatric clinical trials (p < 0.05), and a significant decrease in initiation of interventional psychiatric clinical trials (p < 0.01). When data was analyzed on a month-by-month time scale, 7/12 months in 2020 showed significant decreases when compared to initiation during matching months over prior years, and a single month, June, showed a significant increase. ConclusionCOVID-19 has had significant impacts on the initiation of psychiatric clinical trials over 2020, and this decrease in trial initiation may have long-term impacts on the development and assessment of psychiatric treatments and therapeutics.

Psychiatric aspect of most common used cardiological drugs

Introduction: The count of psychiatric patients is growing. The same trend it is observed among cardiovascular diseases and metabolic like diabetes. Many people take drugs which may affect on mental state. On the one hand that drugs could have pleotropic mechanism of action which are beginning to use in treatment of psychiatry. The other hand is showed undiscovered field of impact on brain working. Methods and Aim: Shown the psychiatric aspect, like side effects and unusual use, of the most used cardiological drugs. To do this, research of articles was done with the help of deta bases such as PubMed and Google Scholar.Results: The most used cardiological drugs are beta blockers, calcium canal blockers, ACE inhibtors, ARBs, nitrats, cilostazol, amiodarone and clonidine In this article it was shown current known about those drugs like mechanism of action and a report of psychiatric clinical trials. Beta-blockers are the most commonly used group of cardiological drugs as the one that significantly affects mental health. Their therapeutic importance has been noted in diseases such as: PTSD or stage fright. It was also long believed that they could make depression worse, but the latest research strongly contradicts this. A positive effect in the treatment of depression can also be obtained by usage of inhibitors of the RAA. Calcium channel blockers are another group of cardiac drugs that are important in the regulation of mood in bipolar disorder. To sum up, a large proportion of cardiac drugs can influence the flow of psychiatric diseases, and the use of them may be clinically desirable in patients with both - cardiac and psychiatric problems.

Randomization-based analysis of covariance for inference in the sequential parallel comparison design

ABSTRACTThe sequential parallel comparison design (SPCD), with sequence groups P:P, P:T, and T:T, together with the exclusion of the second-period information from placebo responders in the first period, can serve usefully for studies with highly favorable placebo response, for example, psychiatric clinical trials. This paper presents a methodology for the first-period treatment difference in the overall population and the second-period treatment difference in the placebo nonresponders for the first period, as well as other available sources of information that could be of potential interest. Without any assumptions, a hypothesis testing method is proposed based on the randomization distribution of comparisons using the covariance structure for the randomized population under the null hypothesis to control type I error. Randomization-based analysis of covariance (ANCOVA) is introduced to adjust for baseline and for the observations that serve as baselines for the second period. Related methods are proposed for the study population as a simple random sample of an almost infinite population. The statistical properties of the proposed methods are described with simulation studies; and the use of the methods is illustrated for an example based on the data from the ADAPT-A clinical trial.

Statistical inference problems in sequential parallel comparison design

ABSTRACTThe sequential parallel comparison designhas recently been considered to solve the problem with high placebo response and the required sample size in the psychiatric clinical trials. One feature with this design is that a difference between the placebo group and the drug group may also arise in the variance–covariance structure of the clinical outcome. Provided the heterogeneity of the second moment, the treatment effect estimation at the second stage can be biased for the entire randomized patient population that includes patient responders. Our work presented here aims at how the coverage probability of the interval estimation of treatment effect performs under the unstructured variance–covariance matrix. The interaction between the truncation after the first stage and the heterogeneity of the second moment causes a substantial coverage probability problem. The type I error probability may not be controlled under the weak null due to this bias. This bias can also cause spurious power evaluation under an alternative hypothesis. The coverage probability of the ordinary least square statistic is shown in different scenarios.

Deep brain stimulation of the internal capsule enhances human cognitive control and prefrontal cortex function

Deep brain stimulation (DBS) is a circuit-oriented treatment for mental disorders. Unfortunately, even well-conducted psychiatric DBS clinical trials have yielded inconsistent symptom relief, in part because DBS’ mechanism(s) of action are unclear. One clue to those mechanisms may lie in the efficacy of ventral internal capsule/ventral striatum (VCVS) DBS in both major depression (MDD) and obsessive-compulsive disorder (OCD). MDD and OCD both involve deficits in cognitive control. Cognitive control depends on prefrontal cortex (PFC) regions that project into the VCVS. Here, we show that VCVS DBS’ effect is explained in part by enhancement of PFC-driven cognitive control. DBS improves human subjects’ performance on a cognitive control task and increases theta (5–8Hz) oscillations in both medial and lateral PFC. The theta increase predicts subjects’ clinical outcomes. Our results suggest a possible mechanistic approach to DBS therapy, based on tuning stimulation to optimize these neurophysiologic phenomena.

Small Sample Sizes and a False Economy for Psychiatric Clinical Trials

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Enhancing the Utility of Preclinical Research in Neuropsychiatry Drug Development.

Most large pharmaceutical companies have downscaled or closed their clinical neuroscience research programs in response to the low clinical success rate for drugs that showed tremendous promise in animal experiments intended to model psychiatric pathophysiology. These failures have raised serious concerns about the role of preclinical research in the identification and evaluation of new pharmacotherapies for psychiatry. In the absence of a comprehensive understanding of the neurobiology of psychiatric disorders, the task of developing "animal models" seems elusive. The purpose of this review is to highlight emerging strategies to enhance the utility of preclinical research in the drug development process. We address this issue by reviewing how advances in neuroscience, coupled with new conceptual approaches, have recently revolutionized the way we can diagnose and treat common psychiatric conditions. We discuss the implications of these new tools for modeling psychiatric conditions in animals and advocate for the use of systematic reviews of preclinical work as a prerequisite for conducting psychiatric clinical trials. We believe that work in animals is essential for elucidating human psychopathology and that improving the predictive validity of animal models is necessary for developing more effective interventions for mental illness.

A Review of Methods for Monitoring Adverse Events in Pediatric Psychopharmacology Clinical Trials.

Pediatric psychotropic prescription rates are rising, emphasizing the need for careful monitoring of drug safety in this population. Currently, no standardized assessments are used in clinical trials for adverse event (AE) elicitation focused on long-term drug treatment in pediatric patients. Despite a lack of standardized AE elicitation methods in psychiatric clinical trials, it is clear that psychiatric medications have developmentally dependent AEs that differ from those observed in adults. In this review, we discuss the use of general inquiry elicitation, drug-specific checklists, and systematic elicitation scales for AE reporting in pediatric psychopharmacology trials. The checklists evaluated include the Barkley Side Effect Rating Scales (SERS), the Pittsburg side effect rating scale, and the Systematic Monitoring of Adverse events Related to TreatmentS (SMARTS) checklist. The systematic assessment scales discussed include the Systematic Assessment for Treatment of Emergent Events (SAFTEE) and the Safety Monitoring Uniform Report Form (SMURF). We review the advantages and disadvantages of each method and discuss the need for optimal assessment of AEs. AE instruments that are created and utilized for pediatric psychiatric trials must begin to incorporate symptoms that are relevant to this population and account for the nature of the disorders to better characterize treatment-emergent AEs and monitor long-term safety.

Transdiagnostic Clinical Global Impression Scoring for Routine Clinical Settings.

Although there is great interest in the improving the ability to track patients’ change over time in routine clinical care settings, no standardized transdiagnostic measure is currently available for busy clinicians to apply. The Clinical Global Impression (CGI) scales are simple measures widely used as outcomes in psychiatric clinical trials. However, the CGI suffers from poorly defined scoring anchors. Efforts to improve the anchors by enhancing the anchor descriptions have proven useful but are limited by being disease-specific, thereby acting as a barrier to the routine clinical adoption of the CGI. To inform the development of more broadly applicable CGI scoring anchors, we surveyed 24 clinical trial investigators, asking them to rank-order seven elements that inform their CGI-Severity (CGI-S) scoring. Symptom severity emerged as the most important element in determining CGI-S scores; the functional status of the patient emerged as a second element. Less importance was given to self-report symptom scores, staff observations, or side effects. Relative rankings of the elements’ importance did not differ by investigators’ experience nor time usually spent with patients. We integrated these results with published illness-specific CGI anchors to develop the Transdiagnostic CGI (T-CGI), which employs standardized scoring anchors applicable across psychiatric illnesses. Pending validity and reliability evaluations, the T-CGI may prove well-suited for inclusion in routine clinical settings and for incorporation into electronic medical records as a simple and useful measure of treatment efficacy.

Semiparametric Inference of the Complier Average Causal Effect with Nonignorable Missing Outcomes

Noncompliance and missing data often occur in randomized trials, which complicate the inference of causal effects. When both noncompliance and missing data are present, previous papers proposed moment and maximum likelihood estimators for binary and normally distributed continuous outcomes under the latent ignorable missing data mechanism. However, the latent ignorable missing data mechanism may be violated in practice, because the missing data mechanism may depend directly on the missing outcome itself. Under noncompliance and an outcome-dependent nonignorable missing data mechanism, previous studies showed the identifiability of complier average causal effect for discrete outcomes. In this article, we study the semiparametric identifiability and estimation of complier average causal effect in randomized clinical trials with both all-or-none noncompliance and outcome-dependent nonignorable missing continuous outcomes, and propose a two-step maximum likelihood estimator in order to eliminate the infinite dimensional nuisance parameter. Our method does not need to specify a parametric form for the missing data mechanism. We also evaluate the finite sample property of our method via extensive simulation studies and sensitivity analysis, with an application to a double-blinded psychiatric clinical trial.

Chemical modulation of mutant mGlu1 receptors derived from deleterious GRM1 mutations found in schizophrenics.

Schizophrenia is a complex and highly heterogeneous psychiatric disorder whose precise etiology remains elusive. While genome-wide association studies (GWAS) have identified risk genes, they have failed to determine if rare coding single nucleotide polymorphisms (nsSNPs) contribute in schizophrenia. Recently, two independent studies identified 12 rare, deleterious nsSNPS in the GRM1 gene, which encodes the metabotropic glutamate receptor subtype 1 (mGlu1), in schizophrenic patients. Here, we generated stable cell lines expressing the mGlu1 mutant receptors and assessed their pharmacology. Using both the endogenous agonist glutamate and the synthetic agonist DHPG, we found that several of the mutant mGlu1 receptors displayed a loss of function that was not due to a loss in plasma membrane expression. Due to a lack of mGlu1 positive allosteric modulators (PAM) tool compounds active at human mGlu1, we optimized a known mGlu4 PAM/mGlu1 NAM chemotype into a series of potent and selective mGlu1 PAMs by virtue of a double “molecular switch”. Employing mGlu1 PAMs from multiple chemotypes, we demonstrate that the mutant receptors can be potentiated by small molecules and in some cases efficacy restored to that comparable to wild type mGlu1 receptors, suggesting deficits in patients with schizophrenia due to these mutations may be amenable to intervention with an mGlu1 PAM. However, in wild type animals, mGlu1 negative allosteric modulators (NAMs) are efficacious in classic models predictive of antipsychotic activity, whereas we show that mGlu1 PAMs have no effect to slight potentiation in these models. These data further highlight the heterogeneity of schizophrenia and the critical role of patient selection strategies in psychiatric clinical trials to match genotype with therapeutic mechanism.

A sequential enriched design for target patient population in psychiatric clinical trials.

High placebo response is widely believed to be one major reason why many psychiatric clinical trials fail to demonstrate drug efficacy. In order to alleviate this problem, research has developed several enrichment designs, including the parallel design with a placebo lead-in phase, the sequential parallel design, and a recently proposed two-way enriched design. While these designs have been evaluated and discussed individually, their effectiveness against each other has not been rigorously compared. The current study examines the various enrichment designs simultaneously. Building on their strengths, we introduce a new improved design named' sequential enriched design' (SED) aimed at removing not only patients with high placebo response but also patients who do not respond to any treatment from the study. The SED begins with a double-blind placebo lead-in phase followed by a traditional parallel design in the first stage. Only patients who respond to the drug in the first stage are re-randomized to the drug or placebo at the second stage. We simulate data for a mixed population composed of four subgroups of patients who are predetermined as to whether they respond to drug or not as well as to placebo or not. By focusing on the target patients whose responses reflect the drug's efficacy,we evaluate the bias, mean squared error, and power for different designs. We demonstrate that the SED produces a less biased estimate for the target treatment effect and yields reasonably high power in general compared with the other designs.

Ethical Issues In Pediatric Psychiatric Clinical Trials

Abstract Background: Over the last decade, the number of research trials investigating psychiatric medications for children and adolescents has increased dramatically. However, this research brings to light ethical concerns regarding the doubly vulnerable population of children with psychiatric disorders. This article summarizes some of the practices established to reduce the risks this population may incur from participating in clinical trials research. Methods: A narrative synthesis was developed after a review of several summary articles focused on the issue of ethical issues in pediatric psychiatric clinical trials. Results: Federal regulations have been established to ensure that the rights and safety of children are protected during research participation, such as the four levels of risk to which every research protocol is assigned. This assignment is made based on all of the potential risks and benefits associated with participation. Safeguards exist to ensure that risks are minimized or eliminated whenever possible. The consent process and the requirement of assent (if applicable) is an opportunity to ensure that legal guardians and participants alike understand the meaning of their participation in the research and are not under a “therapeutic misconception” of benefit from research. All studies are required to receive approval from an Investigational Review Board before starting any study-related procedures, and some studies receive additional oversight from data safety and monitoring boards if they involve a highly vulnerable population, such as pediatric psychiatric clinical trials. Conclusions: Even with safeguards like these in place, many concerns still remain regarding the ethics surrounding this area of research. However, these obstacles should not discourage researchers from exploring the issues that need to be addressed in order to provide the best care possible for children and adolescents with psychiatric disorders.

Pažeidžiamų asmenų dalyvavimo ir psichikos ligonių sutikimo dalyvauti klinikiniuose vaistinių preparatų tyrimuose teisinio reguliavimo problemos Lietuvoje

EU and national legal acts regulate authorization, conduction and control of clinical trials of medicinal products (CTMP). The purpose of legal norms regulating CTMP is to ensure that data generated in these trials is of a good quality and that rights and wellbeing of trial participants are protected. Individuals whose consent to participate in a clinical trial may be unduly influenced by the external circumstances are regarded as vulnerable subjects. This article analyses international, EU, and Lithuanian legal acts, judicial practice and the doctrine of law in order to assess whether Lithuanian regulations of vulnerable subjects participation in CTMP and the procedure of informed consent in psychiatric clinical trials provide sufficient protection of rights and interests of trial subjects and does not place unfounded obstacles to the conduction of CTMP. The problematic aspects of analyzed regulation are emphasized and possible solutions are given in the article. The analysis leads to a few main conclusions. The lists of vulnerable populations provided in Law on Ethics of Biomedical Research of the Republic of Lithuania, Good clinical practice and Clinical trial Application Form endorsed at EU and national levels disagree. It would be purposeful to include pregnant, nursing women and women of child bearing potential into the vulnerable subjects list provided in Law on Ethics of Biomedical Research. In comparison to other countries and international documents Lithuanian legal regulation establishes strict rules of protection of these subjects. According to Law on Ethics of Biomedical Research clinical trials involving vulnerable subjects shall be permitted only where: 1) such biomedical research may be undertaken only on vulnerable subjects; 2) the results of the biomedical research may be of direct and real benefit to the health of these subjects; 3) the biomedical research will not pose a risk to the health or life of the subject. Law on Ethics of Biomedical Research should be changed to allow in exceptional cases to conduct nontherapeutic CTMP with vulnerable subjects and to clarify the acceptable level of risk to the health of the vulnerable subject in biomedical research. Complex regulation of the informed consent procedure in psychiatric research also has to be improved as it posses difficulties not only for the conduction but also for control of CTMP and does not provide sufficient protection of psychiatric patients.

Nick Craddock: a world leader in psychiatric genetics

Nick Craddock: a world leader in psychiatric genetics

Something fishy: The issue of omega-3 blinding in psychiatric clinical trials

Something fishy: The issue of omega-3 blinding in psychiatric clinical trials

Increasing trial efficiency by early reallocation of placebo nonresponders in sequential parallel comparison designs: Application to antidepressant trials

The sequential parallel comparison (SPC) design was proposed to improve the efficiency of psychiatric clinical trials by reducing the impact of placebo response. It consists of two consecutive placebo-controlled comparisons of which the second is only entered by placebo nonresponders from the first. Previous studies suggest that in antidepressant trials, nonresponse to placebo can already be predicted after 2 weeks of follow-up. This would allow to reduce the first phase of the SPC design to further increase its efficiency. To compare the sample size requirements of an 8-week randomized controlled trial (RCT(8)) and alternative SPC designs with equal or longer total follow-up duration (SPC(2+6), SPC(4+4), and SPC(6+6)). Scenarios for response and dropout rates were defined. Sample sizes to achieve 80% power were determined for the various designs. Three treatment functions assumed either a smaller, equal, or larger effect at the early stage of the trial as compared with that at the end. Two dropout models described either predominantly early or linearly increasing dropout, and dropout was considered as nonresponse. The relative efficiency of the different designs was evaluated across these scenarios and for a specific scenario based on empirical antidepressant trial data. The different SPC designs (i.e., SPC(2+6), SPC(4+4), and SPC(6+6)) were generally more efficient than the RCT(8) design when the treatment effect at the early stage of the trial was equal or larger than the effect at the end. In this case, the advantage of the SPC designs increased in the presence of dropout. The SPC(2+6) design was usually more efficient than the SPC(4+4) design and was relatively less affected by dropout when it occurred predominantly early. For the scenario that was based on antidepressant trial data, the SPC(2+6) and SPC(4+4) designs required 51% and 53% fewer patients than the RCT(8) design. A limited variety of scenarios was evaluated. Parameter values resembled those observed in antidepressant trials. This study suggests that SPC designs are highly efficient alternatives to a conventional RCT in indications where placebo response is high and substantial treatment effects are established after a relatively short follow-up period (i.e., after the first SPC design phase). We conclude that SPC designs can reduce sample size requirements and increase success rates of antidepressant trials.