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The European Medicines Agency (EMA) and the US Food and Drug Administration (FDA) produce guidelines for the design of pivotal psychiatric drug trials used in new drug applications. It is unknown who are involved in the guideline development and what specific trial design recommendations they give.
Cross-sectional study of EMA Clinical Efficacy and Safety Guidelines and FDA Guidance Documents. Study outcomes: (1) guideline committee members and declared conflicts of interest; (2) guideline development and organisation of commenting phases; (3) categorisation of stakeholders who comment on draft and final guidelines according to conflicts of interest (‘industry’, ‘not-industry but with industry-related conflicts’, ‘independent’, ‘unclear’); and (4) trial design recommendations (trial duration, psychiatric comorbidity, ‘enriched design’, efficacy outcomes, comparator choice). Protocol registration https://doi.org/10.1101/2020.01.22.20018499 (27 January 2020).
We included 13 EMA and five FDA guidelines covering 15 psychiatric indications. Eleven months after submission, the EMA had not processed our request regarding committee member disclosures. FDA offices draft the Guidance Documents, but the Agency is not in possession of employee conflicts of interest declarations because FDA employees generally may not hold financial interests (although some employees may hold interests up to $15,000). The EMA and FDA guideline development phases are similar; drafts and final versions are publicly announced and everybody can submit comments. Seventy stakeholders commented on ten guidelines: 38 (54%) ‘industry’, 18 (26%) ‘not-industry but with industry-related conflicts’, six (9%) ‘independent’ and eight (11%) ‘unclear’. They submitted 1014 comments: 640 (68%) ‘industry’, 243 (26%) ‘not-industry but with industry-related conflicts’, 44 (5%) ‘independent’ and 20 (2%) ‘unclear’ (67 could not be assigned to a specific stakeholder). The recommended designs were generally for trials of short duration; with restricted trial populations; allowing previous exposure to the drug; and often recommending rating scale efficacy outcomes. EMA mainly recommended three arm designs (both placebo and active comparators), whereas FDA mainly recommended placebo-controlled designs. There were also other important differences and FDA's recommendations regarding the exclusion of psychiatric comorbidity seemed less restrictive.
The EMA and FDA clinical research guidelines for psychiatric pivotal trials recommend designs that tend to have limited generalisability. Independent and non-conflicted stakeholders are underrepresented in the guideline development. It seems warranted with more active involvement of scientists and independent organisations without conflicts of interest in the guideline development process.
Previous research on the depression scale of the Patient Health Questionnaire (PHQ-9) has found that different latent factor models have maximized empirical measures of goodness-of-fit. The clinical relevance of these differences is unclear. We aimed to investigate whether depression screening accuracy may be improved by employing latent factor model-based scoring rather than sum scores.
We used an individual participant data meta-analysis (IPDMA) database compiled to assess the screening accuracy of the PHQ-9. We included studies that used the Structured Clinical Interview for DSM (SCID) as a reference standard and split those into calibration and validation datasets. In the calibration dataset, we estimated unidimensional, two-dimensional (separating cognitive/affective and somatic symptoms of depression), and bi-factor models, and the respective cut-offs to maximize combined sensitivity and specificity. In the validation dataset, we assessed the differences in (combined) sensitivity and specificity between the latent variable approaches and the optimal sum score (⩾10), using bootstrapping to estimate 95% confidence intervals for the differences.
The calibration dataset included 24 studies (4378 participants, 652 major depression cases); the validation dataset 17 studies (4252 participants, 568 cases). In the validation dataset, optimal cut-offs of the unidimensional, two-dimensional, and bi-factor models had higher sensitivity (by 0.036, 0.050, 0.049 points, respectively) but lower specificity (0.017, 0.026, 0.019, respectively) compared to the sum score cut-off of ⩾10.
In a comprehensive dataset of diagnostic studies, scoring using complex latent variable models do not improve screening accuracy of the PHQ-9 meaningfully as compared to the simple sum score approach.
In the coronavirus disease 2019 (COVID-19) pandemic, a large number of non-pharmaceutical measures that pertain to the wider group of social distancing interventions (e.g. public gathering bans, closures of schools, workplaces and all but essential business, mandatory stay-at-home policies, travel restrictions, border closures and others) have been deployed. Their urgent deployment was defended with modelling and observational data of spurious credibility. There is major debate on whether these measures are effective and there is also uncertainty about the magnitude of the harms that these measures might induce. Given that there is equipoise for how, when and if specific social distancing interventions for COVID-19 should be applied and removed/modified during reopening, we argue that informative randomised-controlled trials are needed. Only a few such randomised trials have already been conducted, but the ones done to-date demonstrate that a randomised trials agenda is feasible. We discuss here issues of study design choice, selection of comparators (intervention and controls), choice of outcomes and additional considerations for the conduct of such trials. We also discuss and refute common counter-arguments against the conduct of such trials.
A multitude of risk/protective factors for anxiety and obsessive-compulsive disorders have been proposed. We conducted an umbrella review to summarize the evidence of the associations between risk/protective factors and each of the following disorders: specific phobia, social anxiety disorder, generalized anxiety disorder, panic disorder, and obsessive-compulsive disorder, and to assess the strength of this evidence whilst controlling for several biases.
Publication databases were searched for systematic reviews and meta-analyses examining associations between potential risk/protective factors and each of the disorders investigated. The evidence of the association between each factor and disorder was graded into convincing, highly suggestive, suggestive, weak, or non-significant according to a standardized classification based on: number of cases (>1000), random-effects p-values, 95% prediction intervals, confidence interval of the largest study, heterogeneity between studies, study effects, and excess of significance.
Nineteen systematic reviews and meta-analyses were included, corresponding to 216 individual studies covering 427 potential risk/protective factors. Only one factor association (early physical trauma as a risk factor for social anxiety disorder, OR 2.59, 95% CI 2.17–3.1) met all the criteria for convincing evidence. When excluding the requirement for more than 1000 cases, five factor associations met the other criteria for convincing evidence and 22 met the remaining criteria for highly suggestive evidence.
Although the amount and quality of the evidence for most risk/protective factors for anxiety and obsessive-compulsive disorders is limited, a number of factors significantly increase the risk for these disorders, may have potential prognostic ability and inform prevention.
Neurobiology-based interventions for mental diseases and searches for useful biomarkers of treatment response have largely failed. Clinical trials should assess interventions related to environmental and social stressors, with long-term follow-up; social rather than biological endpoints; personalized outcomes; and suitable cluster, adaptive, and n-of-1 designs. Labor, education, financial, and other social/political decisions should be evaluated for their impacts on mental disease.
The presumed dominance of “original discovery” over replication is an anomaly. Original discovery has more value than replication primarily when scientific investigation can immediately generate numerous discoveries most of which are true and accurate. This scenario is uncommon. A model shows how original discovery claims typically have small or even negative value. Science becomes worthy mostly because of replication.
Different diagnostic interviews are used as reference standards for major depression classification in research. Semi-structured interviews involve clinical judgement, whereas fully structured interviews are completely scripted. The Mini International Neuropsychiatric Interview (MINI), a brief fully structured interview, is also sometimes used. It is not known whether interview method is associated with probability of major depression classification.
To evaluate the association between interview method and odds of major depression classification, controlling for depressive symptom scores and participant characteristics.
Data collected for an individual participant data meta-analysis of Patient Health Questionnaire-9 (PHQ-9) diagnostic accuracy were analysed and binomial generalised linear mixed models were fit.
A total of 17 158 participants (2287 with major depression) from 57 primary studies were analysed. Among fully structured interviews, odds of major depression were higher for the MINI compared with the Composite International Diagnostic Interview (CIDI) (odds ratio (OR) = 2.10; 95% CI = 1.15–3.87). Compared with semi-structured interviews, fully structured interviews (MINI excluded) were non-significantly more likely to classify participants with low-level depressive symptoms (PHQ-9 scores ≤6) as having major depression (OR = 3.13; 95% CI = 0.98–10.00), similarly likely for moderate-level symptoms (PHQ-9 scores 7–15) (OR = 0.96; 95% CI = 0.56–1.66) and significantly less likely for high-level symptoms (PHQ-9 scores ≥16) (OR = 0.50; 95% CI = 0.26–0.97).
The MINI may identify more people as depressed than the CIDI, and semi-structured and fully structured interviews may not be interchangeable methods, but these results should be replicated.
Declaration of interest
Drs Jetté and Patten declare that they received a grant, outside the submitted work, from the Hotchkiss Brain Institute, which was jointly funded by the Institute and Pfizer. Pfizer was the original sponsor of the development of the PHQ-9, which is now in the public domain. Dr Chan is a steering committee member or consultant of Astra Zeneca, Bayer, Lilly, MSD and Pfizer. She has received sponsorships and honorarium for giving lectures and providing consultancy and her affiliated institution has received research grants from these companies. Dr Hegerl declares that within the past 3 years, he was an advisory board member for Lundbeck, Servier and Otsuka Pharma; a consultant for Bayer Pharma; and a speaker for Medice Arzneimittel, Novartis, and Roche Pharma, all outside the submitted work. Dr Inagaki declares that he has received grants from Novartis Pharma, lecture fees from Pfizer, Mochida, Shionogi, Sumitomo Dainippon Pharma, Daiichi-Sankyo, Meiji Seika and Takeda, and royalties from Nippon Hyoron Sha, Nanzando, Seiwa Shoten, Igaku-shoin and Technomics, all outside of the submitted work. Dr Yamada reports personal fees from Meiji Seika Pharma Co., Ltd., MSD K.K., Asahi Kasei Pharma Corporation, Seishin Shobo, Seiwa Shoten Co., Ltd., Igaku-shoin Ltd., Chugai Igakusha and Sentan Igakusha, all outside the submitted work. All other authors declare no competing interests. No funder had any role in the design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review or approval of the manuscript; and decision to submit the manuscript for publication.
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