Whose depression deteriorates during acute phase antidepressant treatment?

Optimizing the individual dosing of paroxetine in major depressive disorder with therapeutic drug monitoring

INTRODUCTION

Previous studies have examined the correlation between paroxetine concentrations and therapeutic efficacy in patients diagnosed with major depressive disorder (MDD), but findings have been contradictory.

AIMS

This study aimed to investigate the relationships among plasma concentrations, severity of symptoms, and adverse drug reactions (ADRs) to optimize individual dosing.

METHODS

Eighty-seven MDD patients, after completing treatment with paroxetine, were divided into low-concentration (LC, n = 38), medium-concentration (MC, n = 27), and high-concentration (HC, n = 22) groups, based on cutoff value concentrations with the 50% response rate and the laboratory alert level from the 2017 consensus guidelines for therapeutic drug monitoring in neuropsychopharmacology. The severity of depression and anxiety was evaluated using a 17-item Hamilton Depression Scale (HAMD-17) and Hamilton Anxiety Scale (HAMA), respectively. Dosage, plasma concentrations, scale scores, and ADRs were recorded across the three groups at different treatment stages to define the therapeutic reference range.

RESULTS

The 4-week plasma concentration of paroxetine (65.00 ng/mL) could predict the clinical response in MDD patients at 8 weeks. Symptom relief in patients with 4-week paroxetine concentrations ranging from 65.00 to 120.00 ng/mL at 8 weeks was greater than in those with concentrations below 65.00 ng/mL, with no significant difference observed above this range. In addition, more cases of liver injury and weight gain were observed in patients with high paroxetine concentrations.

CONCLUSION

Our results support that early paroxetine concentration may predict clinical efficacy and the incidence of ADRs, thus improving individual dosing regimens for MDD patients.

Sequential link in depression, sleep and cognition: Longitudinal evidence from a serial multiple mediation analysis of older adults in China

BACKGROUND

A growing body of literature examines the link between depression, sleep and cognition, but little is known regarding the extent to which this relationship holds among older adults over time.

OBJECTIVE

This study examines how sleep duration mediates the relationship between depressive symptoms and cognitive performance, by utilizing partial least squares structural equation modelling (PLS-SEM) estimation.

METHODS

This study utilizes the 2013-18 China Health and Retirement Longitudinal Study (CHARLS) dataset, of which 3557 participants over the age of 50 satisfied inclusion criteria. Depressive symptoms and cognitive performance are measured by the Center for Epidemiological Studies Depression Scale (CESD) and the Mini-Mental State Examination (MMSE); sleep duration is assessed using the adapted Pittsburgh Sleep Quality Index (PSQI). A serial multiple mediation model was built to assess how depressive symptoms in 2013 and in 2018 are related, in addition to assessing their links with sleep duration and cognitive performance.

FINDINGS

Results indicate that early depression positively predicts depression progression (std.β = 0.564, 95 % Confidence Interval: 0.534, 0.594), but negatively predicts sleep duration (std.β = -0.081, 95 % CI: -0.128, -0.034) and cognitive performance (std.β = -0.118, 95 % CI: -0.165, -0.072). The sequential indirect effect of early depression operating via depression progression and sleep duration is evaluated to be -0.083 (95 % CI: -0.110, -0.056), representing as much as 41.29 % of the total effect.

CONCLUSIONS

Early depressive symptoms are directly associated with increased depressive symptoms and shortened sleep, which are identified as key channels through which early depression is linked with worsened cognition.

CLINICAL IMPLICATIONS

Many older adults may underestimate the adverse costs of early depression, since its net effects on cognition could be channeled indirectly and discretely via depression progression and sleep, which is worth highlighting in health guidelines and clinical recommendations.

Intranasal neuropeptide Y is most effective in some aspects of acute stress compared to melatonin, oxytocin and orexin

Objectives: In the current study, we compared the effects of a single intranasal administration of clomipramine with effects of four neuropeptides, melatonin, oxytocin, orexin, and neuropeptide Y, to compare them in an acute stress model.

Methods: The anti-stress effect was evaluated in the sucrose preference and forced swimming tests. Serum corticosterone level in rats was measured to evaluate the stress response.

Results: Neuropeptide Y reduced immobilization time in the Porsolt test and decreased corticosterone levels, but increased the anhedonia. Orexin had no positive effect on animal behavior, but decreased corticosterone levels. Oxytocin decreased immobilization time, maintained anhedonia at the level of control, but did not affect corticosterone levels. Melatonin demonstrated no positive effects in any of the tests.

Conclusion: The intranasal administered neuropeptide Y could be a promising compound for the treatment of stress disorders.

Frequency analysis of symptomatic worsening following ketamine infusions for treatment resistant depression in a real-world sample: Results from the canadian rapid treatment center of excellence

Antidepressants are associated with symptomatic worsening in a subgroup of patients. Replicated evidence has demonstrated rapid and robust antidepressant effects with intravenous (IV) ketamine in treatment resistant depression (TRD); however, the risk of ketamine worsening depressive symptoms in a subgroup of patients remains unknown. Herein we report a retrospective analysis on the rates of symptomatic worsening during an acute course of IV ketamine in individuals with unipolar (n = 142) and bipolar (n = 22) TRD. Adults (N = 164; mean age = 45.97) with TRD underwent four sub-anesthetic infusions (0.5-0.75 mg/kg over 40 min) of IV ketamine over two weeks, and were assessed with the Quick Inventory for Depression Symptomatology-Self Report-16 (QIDS-SR₁₆) at baseline and after each infusion. The primary outcome was the proportion of patients experiencing clinically significant worsening of depressive symptoms (≥20% increase on the QIDS-SR₁₆) at each time point relative to baseline. Secondary analyses explored trends in the results. The frequency of clinically significant worsening fluctuated between 1.83% to 5.49%, with no identifiable trend across time. Zero individuals with bipolar TRD reported symptomatic worsening. Limitations include the single-centered, uncontrolled, retrospective nature of this study. Rates of symptomatic worsening associated with IV ketamine therapy for TRD appear to be very low and similar to conventional antidepressants.

An individualized treatment rule to optimize probability of remission by continuation, switching, or combining antidepressant medications after failing a first-line antidepressant in a two-stage randomized trial

BACKGROUND

There is growing interest in using composite individualized treatment rules (ITRs) to guide depression treatment selection, but best approaches for doing this are not widely known. We develop an ITR for depression remission based on secondary analysis of a recently published trial for second-line antidepression medication selection using a cutting-edge ensemble machine learning method.

METHODS

Data come from the SUN(^_^)D trial, an open-label, assessor blinded pragmatic trial of previously-untreated patients with major depressive disorder from 48 clinics in Japan. Initial clinic-level randomization assigned patients to 50 or 100 mg/day sertraline. We focus on the 1549 patients who failed to remit within 3 weeks and were then rerandomized at the individual-level to continuation with sertraline, switching to mirtazapine, or combining mirtazapine with sertraline. The outcome was remission 9 weeks post-baseline. Predictors included socio-demographics, clinical characteristics, baseline symptoms, changes in symptoms between baseline and week 3, and week 3 side effects.

RESULTS

Optimized treatment was associated with significantly increased cross-validated week 9 remission rates in both samples [5.3% (2.4%), p = 0.016 50 mg/day sample; 5.1% (2.7%), p = 0.031 100 mg/day sample] compared to randomization (30.1-30.8%). Optimization was also associated with significantly increased remission in both samples compared to continuation [24.7% in both: 11.2% (3.8%), p = 0.002 50 mg/day sample; 11.7% (3.9%), p = 0.001 100 mg/day sample]. Non-significant gains were found for optimization compared to switching or combining.

CONCLUSIONS

An ITR can be developed to improve second-line antidepressant selection, but replication in a larger study with more comprehensive baseline predictors might produce stronger and more stable results.