Mirroring everyday clinical practice in clinical trial design: a new concept to improve the external validity of randomized double-blind placebo-controlled trials in the pharmacological treatment of major depression

Background: Randomized, double-blind, placebo-controlled trials constitute the gold standard in clinical research when testing the efficacy of new psychopharmacological interventions in the treatment of major depression. However, the blinded use of placebo has been found to influence clinical trial outcomes and may bias patient selection. Discussion: To improve clinical trial design in major depression so as to reflect clinical practice more closely we propose to present patients with a balanced view of the benefits of study participation irrespective of their assignment to placebo or active treatment. In addition every participant should be given the option to finally receive the active medication. A research agenda is outlined to evaluate the impact of the proposed changes on the efficacy of the drug to be evaluated and on the demographic and clinical characteristics of the enrollment fraction with regard to its representativeness of the eligible population. Summary: We propose a list of measures to be taken to improve the external validity of double-blind, placebocontrolled trials in major depression. The recommended changes to clinical trial design may also be relevant for other psychiatric as well as medical disorders in which expectations regarding treatment outcome may affect the outcome itself

Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation

The value of normative models in research and clinical practice relies on their robustness and a systematic comparison of different modelling algorithms and parameters; however, this has not been done to date. We aimed to identify the optimal approach for normative modelling of brain morphometric data through systematic empirical benchmarking, by quantifying the accuracy of different algorithms and identifying parameters that optimised model performance. We developed this framework with regional morphometric data from 37 407 healthy individuals (53% female and 47% male; aged 3–90 years) from 87 datasets from Europe, Australia, the USA, South Africa, and east Asia following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The multivariate fractional polynomial regression (MFPR) emerged as the preferred algorithm, optimised with non-linear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3000 study participants. This model can inform about the biological and behavioural implications of deviations from typical age-related neuroanatomical changes and support future study designs. The model and scripts described here are freely available through CentileBrain

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns

Phase IB dose escalation and expansion study of AKT inhibitor afuresertib with carboplatin and paclitaxel in recurrent platinum-resistant ovarian cancer

Purpose: Preclinically, AKT kinase inhibition restores drug sensitivity in platinum-resistant tumors. Here the pan-AKT kinase inhibitor afuresertib was given in combination with paclitaxel and carboplatin (PC) in patients with recurrent platinum-resistant epithelial ovarian cancer (PROC) and primary platinum-refractory ovarian cancer (PPROC). Patients and Methods: Part I was a combination 3+3 dose escalation study for recurrent ovarian cancer. Patients received daily continuous oral afuresertib at 50–150 mg/day with intravenous paclitaxel (175 mg/m2) and carboplatin (AUC5) every 3 weeks for six cycles followed by maintenance afuresertib at 125 mg/day until progression or toxicity. Part II was a single-arm evaluation of the clinical activity of this combination in recurrent PROC (Cohort A) or PPROC (Cohort B). Patients received oral afuresertib at the MTD defined in Part I in combination with PC for six cycles, followed by maintenance afuresertib. Primary endpoints were safety and tolerability of afuresertib in combination with PC (Part I, dose escalation), and investigator-assessed overall response rate (ORR) as per RECIST version 1.1 (Part II). Results: Twenty-nine patients enrolled into Part I, and 30 into Part II. Three dose-limiting toxicities of grade 3 rash were observed, one at 125 mg and two at 150 mg afuresertib. The MTD of afuresertib in combination with PC was therefore identified as 125 mg/day. The most common (≥50%) drug-related adverse events observed in Part I of the study were nausea, diarrhea, vomiting, alopecia, fatigue, and neutropenia and, in Part II, were diarrhea, fatigue, nausea, and alopecia. The Part II ORR in the intention to treat patients was 32% [95% confidence interval (CI), 15.9–52.4] by RECIST 1.1 and 52% (95% CI, 31.3–72.2) by GCIG CA125 criteria. Median progression-free survival was 7.1 months (95% CI, 6.3–9.0 months). Conclusions: Afuresertib plus PC demonstrated efficacy in recurrent PROC with the MTD of afuresertib defined as 125 mg/day

Diastereoselective Synthesis of 2‑Phenyl-3-(trifluoromethyl)piperazines as Building Blocks for Drug Discovery

The synthesis of enantiomerically pure <i>cis</i>- and <i>trans</i>-2-phenyl-3-(trifluoromethyl)­piperazines is described. It involved, as the key step, a diastereoselective nucleophilic addition of the Ruppert–Prakash reagent (TMSCF₃) to α-amino sulfinylimines bearing Ellman’s auxiliary. This methodology allows an entry into hitherto unknown trifluoromethylated and stereochemically defined piperazines, key scaffold components in medicinal chemistry

MRI-Based Intelligence Quotient (IQ) Estimation with Sparse Learning

In this paper, we propose a novel framework for IQ estimation using Magnetic Resonance Imaging (MRI) data. In particular, we devise a new feature selection method based on an extended dirty model for jointly considering both element-wise sparsity and group-wise sparsity. Meanwhile, due to the absence of large dataset with consistent scanning protocols for the IQ estimation, we integrate multiple datasets scanned from different sites with different scanning parameters and protocols. In this way, there is large variability in these different datasets. To address this issue, we design a two-step procedure for 1) first identifying the possible scanning site for each testing subject and 2) then estimating the testing subject's IQ by using a specific estimator designed for that scanning site. We perform two experiments to test the performance of our method by using the MRI data collected from 164 typically developing children between 6 and 15 years old. In the first experiment, we use a multi-kernel Support Vector Regression (SVR) for estimating IQ values, and obtain an average correlation coefficient of 0.718 and also an average root mean square error of 8.695 between the true IQs and the estimated ones. In the second experiment, we use a single-kernel SVR for IQ estimation, and achieve an average correlation coefficient of 0.684 and an average root mean square error of 9.166. All these results show the effectiveness of using imaging data for IQ prediction, which is rarely done in the field according to our knowledge

Child Behavior Checklist-Mania Scale (CBCL-MS):Development and Evaluation of a Population-Based Screening Scale for Bipolar Disorder

<p>Context: Early identification of Bipolar Disorder (BD) remains poor despite the high levels of disability associated with the disorder.</p><p>Objective: We developed and evaluated a new DSM orientated scale for the identification of young people at risk for BD based on the Child Behavior Checklist (CBCL) and compared its performance against the CBCL-Pediatric Bipolar Disorder (CBCL-PBD) and the CBCL-Externalizing Scale, the two most widely used scales.</p><p>Methods: The new scale, CBCL-Mania Scale (CBCL-MS), comprises 19 CBCL items that directly correspond to operational criteria for mania. We tested the reliability, longitudinal stability and diagnostic accuracy of the CBCL-MS on data from the TRacking Adolescents' Individual Lives Survey (TRAILS), a prospective epidemiological cohort study of 2230 Dutch youths assessed with the CBCL at ages 11, 13 and 16. At age 19 lifetime psychiatric diagnoses were ascertained with the Composite International Diagnostic Interview. We compared the predictive ability of the CBCL-MS against the CBCL-Externalising Scale and the CBCL-PBD in the TRAILS sample.</p><p>Results: The CBCL-MS had high internal consistency and satisfactory accuracy (area under the curve = 0.64) in this general population sample. Principal Component Analyses, followed by parallel analyses and confirmatory factor analyses, identified four factors corresponding to distractibility/disinhibition, psychosis, increased libido and disrupted sleep. This factor structure remained stable across all assessment ages. Logistic regression analyses showed that the CBCL-MS had significantly higher predictive ability than both the other scales.</p><p>Conclusions: Our data demonstrate that the CBCL-MS is a promising screening instrument for BD. The factor structure of the CBCL-MS showed remarkable temporal stability between late childhood and early adulthood suggesting that it maps on to meaningful developmental dimensions of liability to BD.</p>