What to expect from a third step in treatment resistant depression: A prospective open study on escitalopram

Courses of treatment and risk factors for treatment-resistant depression in Finnish primary and special healthcare: A nationwide cohort study

OBJECTIVE

Investigate incidence, risk factors and courses of treatment for treatment-resistant depression (TRD) in primary and special healthcare.

METHODS

All patients identified from nationwide registers, aged 16-65 years, diagnosed with depression in Finland during 2004-2016 were included. New antidepressant users were identified with six-month washout period and followed-up for two years to observe for presence of TRD, which was defined as initiation of a third trial after having failed two pharmacological treatment trials with adequate duration.

RESULTS

During follow-up, 177,144 persons had their first registered antidepressant treated depression (mean age: 39.5, 62.5% women). Of them, 10.9% (N = 19,322) met TRD criteria. Among the TRD patients, most common first and second antidepressants trials were: SSRIs (44.6%), mirtazapine (19.0%) and SNRIs (16.5%). As the third treatment line, antidepressant monotherapy (44.2% of TRD patients) was most common, followed by a combination of ≥2 antidepressants (32.1%), antipsychotic or mood stabilizer augmentation and an antidepressant (15.8%), both combination of antidepressants and an augmentation with a mood stabilizer or antipsychotic (4.9%), antipsychotic or mood stabilizer monotherapy (2.7%) and ECT (0.3%). Of TRD patients, 16.5% (N = 3188) progressed to the fifth treatment line, in which the most common treatments were antidepressant monotherapy (33.4%), antidepressant combinations (27.5%) and augmentation (24.2%). Factors associated with higher risk of TRD included male gender, younger age, higher initial disease severity and hospitalization at initial onset of depression.

CONCLUSIONS

Antidepressant monotherapies were still the most common fifth line of depression treatment. Severe depression, hospitalization due to depression, young age and male gender may predispose to TRD.

Involvement of dopamine D2 and glutamate NMDA receptors in the antidepressant-like effect of amantadine in mice

The present study investigated the pharmacological mechanisms of the antidepressant-like effects of amantadine in mice and their influence on hippocampal neurogenesis. To improve the translational validity of preclinical results, reproducibility across laboratories and replication in other animal models and species are crucial. Single amantadine administration at doses of 50 and 75 mg/kg resulted in antidepressant-like effects in mice in the tail suspension test (TST), reflected by an increase in immobility time. The effects of amantadine were seen at doses that did not alter locomotor activity. The tyrosine hydroxylase inhibitor α-methyl-ρ-tyrosine did not influence the anti-immobility effect of amantadine in the TST. Pretreatment with the α₁ adrenergic receptor antagonist prazosin, β adrenergic receptor antagonist propranolol, α₂ adrenergic receptor antagonist yohimbine, and α₂ adrenergic receptor agonist clonidine did not alter the antidepressant-like effect of amantadine. However, amantadine's effect was blocked by the dopamine D₂ receptor antagonist haloperidol and glutamate receptor agonist N-methyl-D-aspartate (NMDA). Repeated amantadine administration (50 mg/kg) also exerted an antidepressant-like effect, paralleled by an increase in hippocampal neurogenesis. The present results demonstrate that the antidepressant-like effects of amantadine may be mediated by its actions on D₂ and NMDA receptors and likely involve hippocampal neurogenesis.

Cost-effectiveness of genetic and clinical predictors for choosing combined psychotherapy and pharmacotherapy in major depression

BACKGROUND

Predictors of treatment outcome in major depressive disorder (MDD) could contribute to evidence-based therapeutic choices. Combined pharmacotherapy and psychotherapy show increased efficacy but higher cost compared with antidepressant pharmacotherapy; baseline predictors of pharmacotherapy resistance could be used to identify patients more likely to benefit from combined treatment.

METHODS

We performed a proof-of-principle study of the cost-effectiveness of using previously identified pharmacogenetic and clinical risk factors (PGx-CL-R) of antidepressant resistance or clinical risk factors alone (CL-R) to guide the prescription of combined pharmacotherapy and psychotherapy vs pharmacotherapy. The cost-effectiveness of these two strategies was compared with standard care (ST, pharmacotherapy to all subjects) using a three-year Markov model. Model parameters were literature-based estimates of response to pharmacotherapy and combined treatment, costs (UK National Health System) and benefits (quality-adjusted life years [QALYs], one QALY=one year lived in perfect health).

RESULTS

CL-R was more cost-effective than PGx-CL-R: the cost of one-QALY improvement was £2341 for CL-R and £3937 for PGx-CL-R compared to ST. PGx-CL-R had similar or better cost-effectiveness compared to CL-R when 1) the cost of genotyping was £100 per subject or less or 2) the PGx-CL-R test had sensitivity ≥ 0.90 and specificity ≥ 0.85. The cost of one-QALY improvement for CL-R was £3664 and of £4110 in two independent samples.

LIMITATIONS

lack of validation in large samples from the general population.

CONCLUSIONS

Using clinical risk factors to predict pharmacotherapy resistance and guide the prescription of pharmacotherapy combined with psychotherapy could be a cost-effective strategy.

Social dysfunction in mood disorders and schizophrenia: Clinical modulators in four independent samples

INTRODUCTION

Social dysfunction is a common symptom of several neuropsychiatric disorders. However, only in the last few years research began to systematically investigate clinical aspects of this relevant outcome. Interestingly, its distribution and link with other clinical variables is still unclear. This study investigated social dysfunction in 4 different cohorts of patients affected by mood disorders and schizophrenia to evaluate 1) the degree of social dysfunction in these populations; 2) the associations among social dysfunction and socio-demographic and psychopathological features.

METHODS

Data from 4 independent studies (CATIE, GSRD ES1, ES2 and ES3, STAR*D, STEP-BD) were investigated. Behavioural and affective indicators of social dysfunction were derived and operationalized from scales or questionnaire items related to the interaction with relatives, friends and significant people in patients affected by schizophrenia (N = 765) and mood disorders (N = 2278 + 1954 + 1829). In particular the social dysfunction indicator was derived from Sheehan Disability Scale (SDS) for GSRD sample, from the Work and Social Adjustment Scale (WSAS) for STAR*D sample, from the Life-Range of Impaired Functioning Tool (LRIFT) for STEP-BD sample, and from the Quality of Life Scale (QOLS) for CATIE sample. The distribution of social dysfunction was described and association with socio-demographic and psychopathological characteristics were analysed.

RESULTS

Social dysfunction indicators showed a broad distribution in all samples investigated. Consistently across studies, social dysfunction was associated with higher psychopathological severity (all samples except CATIE) and suicide risk (GSRD ES1 and ES2, STAR*D, and STEP-BD) that explain up to 47% of the variance, but also to lower education level (GSRD ES2, STAR*D, CATIE, and STEP-BD), poorer professional/work status (GSRD ES2 and ES3, STAR*D, CATIE, and STEP-BD), marital status (STAR*D and CATIE), age (younger age in GSRD ES1 and STAR*D, older age in CATIE), higher BMI (GSRD ES2 and ES3, and STEP-BD), and smoking (GSRD ES2 and ES3).

CONCLUSION

Our results demonstrated that a significant percentage of patients affected by both mood disorders and schizophrenia shows relevant social dysfunction. Social dysfunction is related, but not completely explained by psychopathological severity. In several patients, it tends to persist also during remission state. Socio-demographic and lifestyle factors were also found to play a role and should therefore be taken into consideration in further studies investigating social dysfunction.

Results of the European Group for the Study of Resistant Depression (GSRD) - basis for further research and clinical practice

Objectives: The overview outlines two decades of research from the European Group for the Study of Resistant Depression (GSRD) that fundamentally impacted evidence-based algorithms for diagnostics and psychopharmacotherapy of treatment-resistant depression (TRD). Methods: The GSRD staging model characterising response, non-response and resistance to antidepressant (AD) treatment was applied to 2762 patients in eight European countries. Results: In case of non-response, dose escalation and switching between different AD classes did not show superiority over continuation of original AD treatment. Predictors for TRD were symptom severity, duration of the current major depressive episode (MDE), suicidality, psychotic and melancholic features, comorbid anxiety and personality disorders, add-on treatment, non-response to the first AD, adverse effects, high occupational level, recurrent disease course, previous hospitalisations, positive family history of MDD, early age of onset and novel associations of single nucleoid polymorphisms (SNPs) within the PPP3CC, ST8SIA2, CHL1, GAP43 and ITGB3 genes and gene pathways associated with neuroplasticity, intracellular signalling and chromatin silencing. A prediction model reaching accuracy of above 0.7 highlighted symptom severity, suicidality, comorbid anxiety and lifetime MDEs as the most informative predictors for TRD. Applying machine-learning algorithms, a signature of three SNPs of the BDNF, PPP3CC and HTR2A genes and lacking melancholia predicted treatment response. Conclusions: The GSRD findings offer a unique and balanced perspective on TRD representing foundation for further research elaborating on specific clinical and genetic hypotheses and treatment strategies within appropriate study-designs, especially interaction-based models and randomized controlled trials.

Attrition in treatment-resistant depression: predictors and clinical impact

The aim of this study was to investigate attrition (dropout) during a second antidepressant trial in treatment-resistant depression. Three hundred forty-two outpatients with major depressive disorder and lack of response to a prior antidepressant were treated with venlafaxine for 6 weeks. Sociodemographic and clinical characteristics were compared between the attrition and non-attrition groups. Attrition was reported in 65 patients (19%), of whom 30 patients (46%) dropped out within week 4. The characteristics of dropout patients included a longer duration of depressive episode (P = 0.011) and lower antidepressant doses (P < 0.0001) as a consequence of a faster decrease (week 2) in depressive symptoms (P = 0.028). However, by controlling for early improvement, dropout subjects were associated with a smaller probability of antidepressant response (odds ratio = 0.16▪.83). A decrease of at least 30% in Montgomery Asberg Depression Rating Scale on day 14 predicted subsequent dropout with high specificity (81.9%▪1.0%) but lower sensitivity (19.6%▪2.8%) for clinical use. Patients who have been depressed for a longer period and show an initial improvement of symptoms after changing their antidepressant may be at increased risk for drop out. Further studies are necessary to ascertain the usefulness of these characteristics for predicting attrition.

High occupational level is associated with poor response to the treatment of depression: A replication study

Major depressive disorder (MDD) is a leading cause of disability and inability to work. There is evidence that occupational factors may precipitate a MDD episode and interfere with the recovery process. In a previous investigation, we found that those employed in high occupational levels had a worse outcome after treatment for depression (Mandelli et al., 2016). The aim of the present study was to further investigate response to treatments for depression according to occupational status on an independent sample of MDD patients. Six hundred and forty-seven (647) subjects with a stable working occupation were taken from a larger independent sample of MDD patients evaluated for response and resistance to treatment for depression, after at least one adequate treatment trial. Three broad occupational categories were considered: 'manager', 'white-collar', 'blue-collar' and 'self-employed'. Managers had the highest rate of non-response and resistance to treatments. White-collar workers also had high non-response and resistance rates. At the opposite, Blue-collar workers had significantly lower rates of non-response and resistance. Self-employed were in between White- and Blue-collar workers and did not significantly differ from the other occupational categories. The findings of this replication study substantially support our previous observations. MDD patients employed in high-middle occupations may have a less favorable outcome after standard treatments of depression. Working stressful condition and other psychosocial factors at work should be investigated more closely in relation to treatment outcomes in MDD.

Clinical factors predicting treatment resistant depression: affirmative results from the European multicenter study

OBJECTIVES

Clinical variables were investigated in the 'treatment resistant depression (TRD)- III' sample to replicate earlier findings by the European research consortium 'Group for the Study of Resistant Depression' (GSRD) and enable cross-sample prediction of treatment outcome in TRD.

EXPERIMENTAL PROCEDURES

TRD was defined by a Montgomery and Åsberg Depression Rating Scale (MADRS) score ≥22 after at least two antidepressive trials. Response was defined by a decline in MADRS score by ≥50% and below a threshold of 22. Logistic regression was applied to replicate predictors for TRD among 16 clinical variables in 916 patients. Elastic net regression was applied for prediction of treatment outcome.

RESULTS

Symptom severity (odds ratio (OR) = 3.31), psychotic symptoms (OR = 2.52), suicidal risk (OR = 1.74), generalized anxiety disorder (OR = 1.68), inpatient status (OR = 1.65), higher number of antidepressants administered previously (OR = 1.23), and lifetime depressive episodes (OR = 1.15) as well as longer duration of the current episode (OR = 1.022) increased the risk of TRD. Prediction of TRD reached an accuracy of 0.86 in the independent validation set, TRD-I.

CONCLUSION

Symptom severity, suicidal risk, higher number of lifetime depressive episodes, and comorbid anxiety disorder were replicated as the most prominent risk factors for TRD. Significant predictors in TRD-III enabled robust prediction of treatment outcome in TRD-I.

Pleiotropic genes in psychiatry: Calcium channels and the stress-related FKBP5 gene in antidepressant resistance

A candidate gene and a genome-wide approach were combined to study the pharmacogenetics of antidepressant response and resistance. Investigated genes were selected on the basis of pleiotropic effect across psychiatric phenotypes in previous genome-wide association studies and involvement in antidepressant response. Three samples with major depressive disorder (total=671) were genotyped for 44 SNPs in 8 candidate genes (CACNA1C, CACNB2, ANK3, GRM7, TCF4, ITIH3, SYNE1, FKBP5). Phenotypes were response/remission after 4weeks of treatment and treatment-resistant depression (TRD). Genome-wide data from STAR*D were used to replicate findings for response/remission (n=1409) and TRD (n=620). Pathways including the most promising candidate genes were investigated in STAR*D for involvement in TRD. FKBP5 polymorphisms showed replicated but nominal associations with response, remission or TRD. CACNA1C rs1006737 and rs10848635 were the only polymorphisms that survived multiple-testing correction. In STAR*D the best pathway associated with TRD included CACNA1C (GO:0006942, permutated p=0.15). Machine learning models showed that independent SNPs in this pathway predicted TRD with a mean sensitivity of 0.83 and specificity of 0.56 after 10-fold cross validation repeated 100 times. FKBP5 polymorphisms appear good candidates for inclusion in antidepressant pharmacogenetic tests. Pathways including the CACNA1C gene may be involved in TRD and they may provide the base for developing multi-marker predictors of TRD.

Early improvement and response to antidepressant medications in adults with major depressive disorder. Meta-analysis and study of a sample with treatment-resistant depression

BACKGROUND

Initial improvement in the first weeks of antidepressant (AD) treatment is a useful early predictor of complete AD response. We performed a meta-analysis of AD studies to investigate whether a partial decrease in depressive symptoms by week 4 was associated with response and remission by weeks 6-14 in major depressive disorder (MDD). Finally, we focused on treatment-resistant depression (TRD: lack of response to prior AD) to test the impact of early improvement on a second AD treatment outcome and to compare different switching strategies.

METHODS

Meta-analysis was conducted on AD naturalistic studies published between 01.01.2000 and 06.30.2017. TRD was an exclusion criterion. TRD was analyzed in 407 MDD patients treated with venlafaxine for 6 weeks. The MADRS was used to define very early improvement (VEI: > 20% decrease at week 2), early improvement (EI: > 30% decrease at week 4) and remission (week 6 MADRS < 10). A theoretical model was used to simulate AD switch in TRD patients who failed to achieve remission (Algorithm A), VEI (Algorithm B) or EI (Algorithm C).

RESULTS

Our meta-analysis (9 studies; N = 6185) showed significant associations between early improvement, response (OR: 3.28 95% C.I: 2.06-5.20) and remission (OR: 2.10 95% C.I: 1.53-2.87). 24.6% of TRD sample remitted. VEI was a poor outcome predictor: sensitivity = 0.52 (0.40-0.63); specificity = 0.82 (0.76-0.86); AUC = 0.67 (0.62-0.71). EI had a moderate predictive power: sensitivity = 0.87 (0.77-0.93); specificity = 0.71 (0.66-0.77); AUC = 0.76 (0.71-0.80). The best treatment scenario was Algorithm C (switch after 4 weeks) in which remission rate was marginally increased (35.1% vs 33.7% of Algorithm A). Algorithm B (switch after 2 weeks) led to a 4.3% decrease in remission compared to Algorithm A.

LIMITATIONS

Inclusion of a naturalistic sample without a control arm; simulation of treatments.

CONCLUSION

Although literature data suggest a correlation between an initial improvement of depressive symptoms and later response and remission during AD treatment, our analysis shows that such an early improvement is not a reliable outcome predictor in TRD. The nature of TRD is complex and different biological mechanisms and treatments might be necessary for TRD patients.

Neuroplasticity and second messenger pathways in antidepressant efficacy: pharmacogenetic results from a prospective trial investigating treatment resistance

Genes belonging to neuroplasticity, monoamine, circadian rhythm, and transcription factor pathways were investigated as modulators of antidepressant efficacy. The present study aimed (1) to replicate previous findings in an independent sample with treatment-resistant depression (TRD), and (2) to perform a pathway analysis to investigate the possible molecular mechanisms involved. 220 patients with major depressive disorder who were non-responders to a previous antidepressant were treated with venlafaxine for 4-6 weeks and in case of non-response with escitalopram for 4-6 weeks. Symptoms were assessed using the Montgomery Asberg Depression Rating Scale. The phenotypes were response and remission to venlafaxine, non-response (TRDA) and non-remission (TRDB) to neither venlafaxine nor escitalopram. 50 tag SNPs in 14 genes belonging to the pathways of interest were tested for association with phenotypes. Molecular pathways (KEGG database) that included one or more of the genes associated with the phenotypes were investigated also in the STAR*D sample. The associations between ZNF804A rs7603001 and response, CREB1 rs2254137 and remission were replicated, as well as CHL1 rs2133402 and lower risk of TRD. Other CHL1 SNPs were potential predictors of TRD (rs1516340, rs2272522, rs1516338, rs2133402). The MAPK1 rs6928 SNP was consistently associated with all the phenotypes. The protein processing in endoplasmic reticulum pathway (hsa04141) was the best pathway that may explain the mechanisms of MAPK1 involvement in antidepressant response. Signals in genes previously associated with antidepressant efficacy were confirmed for CREB1, ZNF804A and CHL1. These genes play pivotal roles in synaptic plasticity, neural activity and connectivity.

Milnacipran treatment and potential biomarkers in depressed patients following an initial SSRI treatment failure: a prospective, open-label, 24-week study

BACKGROUND

We assessed the effect of switching patients with major depressive disorder to milnacipran following an initial selective serotonin reuptake inhibitor treatment failure, and explored potential biomarkers in their blood.

METHODS

We conducted a prospective, open-label, 24-week trial. Depression was assessed with the 17-item Hamilton Depression Rating Scale. Patients showing a ≥50% reduction in Hamilton Depression Rating Scale scores from baseline to final visit were considered responders. Regarding adverse effects (AEs), moderate-to-severe AEs were specifically identified as effects that required any medical treatment or that induced treatment withdrawals. We also measured blood levels of various molecules including inflammatory cytokines.

RESULTS

Of the 30 participants who enrolled, 17 completed this study. The responder rate was 30% (n=10). Baseline serum levels of interleukin-6 (Z=-2.155; P=0.031) and interleukin-8 (Z=-2.616; P=0.009) were significantly higher when moderate-to-severe AEs were present (n=13 patients with moderate-to-severe AEs). Serum levels of macrophage inflammatory protein-1β showed a significant continuous decrease from the baseline level (Friedman's test: χ (2)=23.9, df=4, P<0.001) only in non-responders.

CONCLUSION

These results demonstrate that serum levels of interleukin-6, interleukin-8, and macrophage inflammatory protein-1β as potential blood biomarkers could be utilized to identify the responsiveness of patients to serotonin and norepinephrine reuptake inhibitor like milnacipran, or to identify those patients who may experience AEs strong enough to warrant discontinuation of treatment.