Rationale and design of the randomised clinical trial comparing early medication change (EMC) strategy with treatment as usual (TAU) in patients with Major Depressive Disorder - the EMC trial

<p>Abstract</p> <p>Background</p> <p>In Major Depressive Disorder (MDD), the traditional belief of a delayed onset of antidepressants' effects has lead to the concept of current guidelines that treatment durations should be between 3-8 weeks before medication change in case of insufficient outcome. Post hoc analyses of clinical trials, however, have shown that improvement usually occurs within the first 10-14 days of treatment and that such early improvement (Hamilton Depression Rating Scale [HAMD] decrease ≥20%) has a substantial predictive value for final treatment outcome. Even more important, non-improvement (HAMD decrease <20%) after 14 days of treatment was found to be highly predictive for a poor final treatment outcome.</p> <p>Methods/Design</p> <p>The EMC trial is a phase IV, multi-centre, multi-step, randomized, observer-blinded, actively controlled parallel-group clinical trial to investigate for the first time prospectively, whether non-improvers after 14 days of antidepressant treatment with an early medication change (EMC) are more likely to attain remission (HAMD-17 ≤7) on treatment day 56 compared to patients treated according to current guideline recommendation (treatment as usual; TAU). In level 1 of the EMC trial, non-improvers after 14 days of antidepressant treatment will be randomised to an EMC strategy or TAU. The EMC strategy for this study schedules a first medication change on day 15; in case of non-improvement between days 15-28, a second medication change will be performed. TAU schedules the first medication change after 28 days in case of non-response (HAMD-17 decrease <50%). Both interventions will last 42 days. In levels 2 and 3, EMC strategies will be compared with TAU strategies in improvers on day 14, who experience a stagnation of improvement during the course of treatment. The trial is supported by the German Federal Ministry of Education and Research (BMBF) and will be conducted in cooperation with the BMBF funded Interdisciplinary Centre Clinical Trials (IZKS) at the University Medical Centre Mainz and at six clinical trial sites in Germany.</p> <p>Discussion</p> <p>If the EMC strategies lead to significantly more remitters, changes of clinical practice, guidelines for the treatment of MDD as well as research settings can be expected.</p> <p>Trial Registration</p> <p><b>Clincaltrials.gov Identifier</b>: NCT00974155; <b>EudraCT</b>: 2008-008280-96.</p

Three-Armed Trials Including Placebo and No-Treatment Groups May Be Subject to Publication Bias: Systematic Review

Background: It has been argued that placebos may not have important clinical impacts in general. However, there is increasing evidence of a publication bias among trials published in journals. Therefore, we explored the potential for publication bias in randomized trials with active treatment, placebo, and no-treatment groups. Methods: Three-armed randomized trials of acupuncture, acupoint stimulation, and transcutaneous electrical stimulation were obtained from electronic databases. Effect sizes between treatment and placebo groups were calculated for treatment effect, and effect sizes between placebo and no-treatment groups were calculated for placebo effect. All data were then analyzed for publication bias. Results: For the treatment effect, small trials with fewer than 100 patients per arm showed more benefits than large trials with at least 100 patients per arm in acupuncture and acupoint stimulation. For the placebo effect, no differences were found between large and small trials. Further analyses showed that the treatment effect in acupuncture and acupoint stimulation may be subject to publication bias because study design and any known factors of heterogeneity were not associated with the small study effects. In the simulation, the magnitude of the placebo effect was smaller than that calculated after considering publication bias. Conclusions: Randomized three-armed trials, which are necessary for estimating the placebo effect, may be subject t

Two Proofs of Convergence for the Combination Technique for the Efficient Solution of Sparse Grid Problems

. For a simple model problem --- the Laplace equation on the unit square with a Dirichlet boundary function vanishing for x = 0, x = 1, and y = 1, and equaling some suitable g(x) for y = 0 --- we present a proof of convergence for the combination technique, a modern, efficient, and easily parallelizable sparse grid solver for elliptic partial differential equations that recently gained importance in fields of applications like computational fluid dynamics. For full square grids with meshwidth h and O(h \Gamma2 ) grid points, the order O(h 2 ) of the discretization error using finite differences was shown in [5], if g(x) 2 C 2 [0; 1]. In this paper, we show that the finite difference discretization error of the solution produced by the combination technique on a sparse grid with only O \Gamma (h \Gamma1 \Delta log 2 (h \Gamma1 ) \Delta grid points is of the order O \Gamma h 2 \Delta log 2 (h \Gamma1 ) \Delta , if the Fourier coefficients b k of ~ g, the 2-periodic ..

Covariation of spectral and nonlinear EEG measures with alpha biofeedback

This study investigated how different spectral and nonlinear EEG measures covaried with alpha power during auditory alpha biofeedback training, performed by 13 healthy subjects. We found a significant positive correlation of alpha power with the largest Lyapunov-exponent, pointing to an increased dynamical instability of the EEG accompanying alpha enhancement. Alpha power amplification, moreover, was significantly correlated with a decrease of spectral entropy within the alpha range. This outcome reflects a sharpening of the alpha peak during biofeedback training. The fact that the sharpening effect clearly preceded the increase of alpha amplitude could be exploited in future biofeedback settings

Covariation of spectral and nonlinear EEG measures with alpha biofeedback

This study investigated how different spectral and nonlinear EEG measures covaried with alpha power during auditory alpha biofeedback training, performed by 13 healthy subjects. We found a significant positive correlation of alpha power with the largest Lyapunov-exponent, pointing to an increased dynamical instability of the EEG accompanying alpha enhancement. Alpha power amplification, moreover, was significantly correlated with a decrease of spectral entropy within the alpha range. This outcome reflects a sharpening of the alpha peak during biofeedback training. The fact that the sharpening effect clearly preceded the increase of alpha amplitude could be exploited in future biofeedback settings

Brief communication: Human scalp recorded sigma activity is modulated by slow EEG oscillations during deep sleep

The EEG during deep sleep exhibits a distinct cortically generated slow oscillation of around and below 1 Hz which can be distinguished from other delta (0.5-3.5 Hz) activity. Intracranial studies showed that this slow oscillation triggers and groups cortical network firing. In the present study, we examined whether the phases of the slow oscillation during sleep stage 4 are correlated with the magnitude of sigma (12-16 Hz) and gamma (>20 Hz) scalp activity. For this purpose, 10-min segments of uninterrupted stage 4 sleep EEG from 9 subjects were analyzed by applying wavelet techniques. We found that scalp recorded sigma, but not gamma, activity is modulated by the phases of the slow oscillation during deep sleep. Enhancement of sigma activity was observed to be triggered by the peak of the surface positive slow wave component, whereas reduction of sigma activity started around the peak of the negative component