Daily activity level improvement with antidepressant medications predicts long-term clinical outcomes in outpatients with major depressive disorder

Reward Behavior Disengagement, a Neuroeconomic Model-Based Objective Measure of Reward Pathology in Depression: Findings from the EMBARC Trial

The probabilistic reward task (PRT) has identified reward learning impairments in those with major depressive disorder (MDD), as well as anhedonia-specific reward learning impairments. However, attempts to validate the anhedonia-specific impairments have produced inconsistent findings. Thus, we seek to determine whether the Reward Behavior Disengagement (RBD), our proposed economic augmentation of PRT, differs between MDD participants and controls, and whether there is a level at which RBD is high enough for depressed participants to be considered objectively disengaged. Data were gathered as part of the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study, a double-blind, placebo-controlled clinical trial of antidepressant response. Participants included 195 individuals with moderate to severe MDD (Quick Inventory of Depressive Symptomatology (QIDS-SR) score ≥ 15), not in treatment for depression, and with complete PRT data. Healthy controls (n = 40) had no history of psychiatric illness, a QIDS-SR score < 8, and complete PRT data. Participants with MDD were treated with sertraline or placebo for 8 weeks (stage I of the EMBARC trial). RBD was applied to PRT data using discriminant analysis, and classified MDD participants as reward task engaged (n = 137) or reward task disengaged (n = 58), relative to controls. Reward task engaged/disengaged groups were compared on sociodemographic features, reward-behavior, and sertraline/placebo response (Hamilton Depression Rating Scale scores). Reward task disengaged MDD participants responded only to sertraline, whereas those who were reward task engaged responded to sertraline and placebo (F(1293) = 4.33, p = 0.038). Reward task engaged/disengaged groups did not differ otherwise. RBD was predictive of reward impairment in depressed patients and may have clinical utility in identifying patients who will benefit from antidepressants.

The Individual and Societal Burden of Treatment-Resistant Depression: An Overview

Major depressive disorder is characterized by depressed mood and/or anhedonia with neurovegetative symptoms and neurocognitive changes affecting an individual's functioning in multiple aspects of life. Treatment outcomes with commonly used antidepressants remain suboptimal. Treatment-resistant depression (TRD) should be considered after inadequate improvement with two or more antidepressant treatments of adequate dose and duration. TRD has been associated with increased disease burden including higher associated costs (both socially and financially) affecting both the individual and society. Additional research is needed to better understand the long-term burden of TRD to both the individual and society.

Pharmacotherapy for Treatment-Resistant Depression: Antidepressants and Atypical Antipsychotics

Treatment-resistant depression (TRD) affects one in three patients with major depressive disorder and is associated with increased risk of all-cause mortality. Studies of real-world practices suggest that antidepressant monotherapy continues to be the most widely used treatment after inadequate response to a first-line treatment. However, rates of remission with antidepressants in TRD are suboptimal. Atypical antipsychotics are the most widely studied augmentation agent and aripiprazole, brexpiprazole, cariprazine, quetiapine extended-release, and olanzapine-fluoxetine combination are approved for depression. Benefits of using atypical antipsychotics for TRD has to be weighted against their potential adverse events, such as weight gain, akathisia, and tardive dyskinesia.

Biomarkers in Psychiatric Drug Development: From Precision Medicine to Novel Therapeutics

Burden of psychiatric disorders is compounded by their wide prevalence as well as the limited efficacy of currently available treatments and the current approaches for prescribing these treatments. The selection of treatments continues to be subjective and often results in a trial-and-error approach. Emerging research suggests that biological markers (or biomarkers) can be used to develop precision medicine approaches for psychiatric disorders. Furthermore, the biomarkers also promise to elucidate the underlying pathophysiological mechanisms which in turn can be used to develop novel therapeutic treatments. In this chapter we have focused on mood disorders and reviewed studies on electroencephalography (EEG), magnetic resonance imaging (MRI), and blood-based biomarkers that can guide selection of one treatment versus another (treatment-selection biomarker) as well as biomarkers that can guide the development of novel therapeutics. These studies suggest that the use of objective physiological data is poised to alter the landscape of psychiatric diagnosis and treatment. However, practical and economic barriers remain as major hurdles. The key to finding such translational diagnostic and therapeutic biomarkers is a better understanding of the underlying pathophysiology, and despite the tremendous advances in neuroscience, it is clear there remains much left to be elucidated.

Cross-Sectional Associations Among Symptoms of Pain, Irritability, and Depression and How These Symptoms Relate to Social Functioning and Quality of Life: Findings From the EMBARC and STRIDE Studies and the VitalSign6 Project

OBJECTIVE

The aim of this report was to evaluate the psychometric properties of the Pain Frequency, Intensity, and Burden Scale (P-FIBS), a brief measure of pain, as well as the association of pain with irritability and depression and how these symptoms relate to functional impairments.

METHODS

Participants of 2 randomized controlled trials (Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care [EMBARC; n = 251 with DSM-IV diagnosis of major depressive disorder; study duration: August 2011-December 2015] and STimulant Reduction Intervention Using Dosed Exercise [STRIDE; n = 302 with DSM-IV diagnosis of stimulant abuse or dependence; study-duration: July 2010-February 2013]) and treatment-seeking patients in primary care clinics from an ongoing quality-improvement project (VitalSign6; n = 4,370; project duration: August 2014-July 2019) were included. Psychometric properties of the P-FIBS were evaluated with confirmatory factor and item response theory analyses in EMBARC and VitalSign6. The approach of Baron and Kenny was used to assess whether irritability accounted for the effect of pain on depression.

RESULTS

Cronbach α (0.84-0.89) and model fits for single-factor structure of P-FIBS were acceptable. Pain was positively correlated with irritability (r = 0.22-0.29) and depression (r = 0.10-0.33). Irritability accounted for 40.7%-65.5% of the effect of pain on depression. Higher irritability and depression were associated with poorer social functioning, quality of life, and productivity in work- and non-work-related activities. Pain was associated with non-work-related activity impairments even after controlling for irritability and depression.

CONCLUSIONS

The P-FIBS is a brief and reliable measure of pain. Irritability is associated with pain and accounts for a large proportion of the effect of pain on depression. Symptoms of pain, irritability, and depression are associated with functional impairments.

TRIAL REGISTRATION

ClinicalTrials.gov identifiers: NCT01407094 (EMBARC), NCT01141608 (STRIDE).

Spotlight on Pimavanserin Tartrate and Its Therapeutic Potential in the Treatment of Major Depressive Disorder: The Evidence to Date

Major depressive disorder (MDD) is widely prevalent and one of the leading causes of disability. Treatment outcomes remain suboptimal with 1 in 3 patients with MDD responding inadequately to commonly used antidepressants. Pimavanserin, an atypical antipsychotic that modulates serotonergic neurotransmission by selectively binding to serotonin receptor (2A and 2C) subtypes and without dopaminergic activity, may have the potential as an adjunctive treatment for MDD. In a phase 2 trial (n=203), addition of pimavanserin, as compared to placebo, to stable treatment with antidepressants was associated with greater reduction in 17-item Hamilton Depression Rating Scale score [HAMD, least square means (95% confidence interval) of -1.7 (-0.03, -3.37), p=0.039]. Furthermore, treatment with pimavanserin was associated with significantly greater improvement in specific symptoms associated with depression such as impaired sexual function, anxiety, sleepiness, and irritability. However, the availability of pimavanserin for clinical care of patients with MDD remains uncertain. Top-line results of phase 3 studies (n=298) that were announced by the sponsor found similar reductions in HAMD (mean baseline-to-week-5 reduction of 9.0 and 8.1, p=0.296) and rates of adverse events (58.1% and 54.7%) with addition of pimavanserin and placebo respectively to stable treatment with antidepressants. Given the potential benefit for specific symptoms such as impaired sexual function, anxiety and sleep/wakefulness disturbances, future studies that enrich for these symptoms may be needed to clarify the utility of adjunctive pimavanserin in treatment of patients with MDD.

Improving Depression Outcome by Patient-Centered Medical Management

(Reprinted with permission from The American Journal of Psychiatry 2018; 175:1187-1198).

Clinical and Neurocognitive Predictors of Functional Outcome in Depressed Patients with Partial Response to Treatment: One Year Follow-Up Study

BACKGROUND

Cognitive dysfunction represents a distinct biological and clinical dimension in major depression disorders (MDD) and cognitive performance strongly affects psychosocial functioning in patients diagnosed with MDD.

OBJECTIVE

To assess which neurocognitive variables at baseline predict the functional outcome of MDD patients in a 1-year follow-up study as assessed by Functioning Assessment Short Test (FAST) and whether the improvement observed on affective and cognitive symptoms in our 12 week-prospective observational study after treatment with selective serotonin reuptake inhibitors (SSRIs) and selective noradrenalin reuptake inhibitors (SNRIs) can affect the following long-term psychosocial functional outcome at 1 year in the same MDD patients.

METHODS

We recruited a total of 31 patients (8 males; 23 females) with MDD who had previously completed a pharmacological treatment with SSRIs (n = 22) or SNRIs (n = 9) for 12 weeks, and then continued the same pharmacological treatment for 1 year. After an average 1-year follow-up, they were interviewed with the FAST to assess functional outcome. Multivariate analyses were applied to identify clinical and neurocognitive predictors of functional outcome.

RESULTS

Total Montreal Cognitive Assessment (MoCA), Digit Span forward (Span F) and backward (Span B), and 15 Rey words immediate recall (Rey I) scores significantly correlated with FAST. However, after performing regression models only Rey immediate recall score was useful to predict long-term functional outcome (Pearson correlation coefficient R= -0.68, p < 0.001) in four specific subdomains of FAST. When considering changes in affective and cognitive symptoms at the end of the 12 weeks of pharmacological treatment with SSRI or SNRIs (T1-T0) by multiple regression analysis, we found that Span F-test predicted scores in the FAST leisure domain, whereas, changes in Span F, Frontal Assessment Battery (FAB) and Rey I predicted psychosocial functioning in the specific "cognitive" subdomains of FAST.

CONCLUSION

Our data suggest that long-term psychosocial functioning can be influenced by neurocognitive performance at baseline, with verbal memory playing a key role in overall functioning. Furthermore, improvement in verbal memory can predict functional outcome at one year in MDD patients with a recent history of partial response to antidepressants.

Causes of drug discontinuation in patients with major depressive disorder in China

BACKGROUND

This research was designed to investigate patient-reported and doctor-reported reasons for the discontinuation of pharmacological treatment in Chinese patients with major depressive disorder (MDD), which was part of the National Survey on Symptomatology of Depression (NSSD) from 2014 to 2015.

METHODS

This cross-sectional study included 649 patients who had discontinued antidepressant medications and 711 patients who had remained on them, selected from a group of 3516 candidates who have had at least one depressive episode. Differences in the two groups' sociodemographic factors, clinical characteristics, medication use, and self-reported reasons for drug discontinuation were compared via Student's t-test or chi-square test. Logistic regression analysis was then used to determine the association of all non-subjective dichotomous and ordinal categorical variables, including the additional 63 items of our physician-evaluated symptomatic assessment, with drug compliance.

RESULTS

Compared to the spontaneous drug discontinuation (SDD) group, the drug adherence (DA) group had significantly lower rates of the following: family history of mental disease (9.0% vs 13.6%), highest level of education achieved being post-graduate or above (1.6% vs 4.7%), smoking (5.8% vs 9.7%), and other health problems (33.9% vs 42.4%) (p's < 0.05). On the other hand, first-episode depression (48.5% vs 21.9%) and taking of mood stabilizer(s) (8.3% vs 5.6%) were higher in the former group than in the latter (p's < 0.05). Logistic Regression Analysis showed that five symptoms, such as depressed mood, were correlated positively with SDD, while another six symptoms, such as psychomotor retardation, were correlated negatively with it. The receiver operating characteristic (ROC) curve of this model yielded an area under the curve (AUC) of 0.701 (95% CI, 0.673-0.729). Notably, there were three main reasons given by patients in the DA group as to why they discontinued their medication(s): (1) concern about long-term side effects (36.1%), (2) no perceived need for taking said medication(s) long-term (34.2%), and (3) believing oneself to have been cured completely (30.0%).

CONCLUSIONS

The aforementioned factors may affect patient compliance and elicit maladaptive thinking even from patients with good educational backgrounds, increasing the risk of drug discontinuation. Compliance of pharmacological treatment might be improved by increasing clarification and elucidation of different symptom clusters to the patient and combating the main reasons for drug discontinuation.

Early change in reward and punishment sensitivity as a predictor of response to antidepressant treatment for major depressive disorder: a CAN-BIND-1 report

BACKGROUND

In an effort to optimize patient outcomes, considerable attention is being devoted to identifying patient characteristics associated with major depressive disorder (MDD) and its responsiveness to treatment. In the current study, we extend this work by evaluating whether early change in these sensitivities is associated with response to antidepressant treatment for MDD.

METHODS

Participants included 210 patients with MDD who were treated with 8 weeks of escitalopram and 112 healthy comparison participants. Of the original 210 patients, 90 non-responders received adjunctive aripiprazole for an additional 8 weeks. Symptoms of depression and anhedonia were assessed at the beginning of treatment and 8 weeks later in both samples. Reward and punishment sensitivity were assessed using the BIS/BAS scales measured at the initiation of treatment and 2 weeks later.

RESULTS

Individuals with MDD exhibited higher punishment sensitivity and lower reward sensitivity compared with healthy comparison participants. Change in reward sensitivity during the first 2 weeks of treatment was associated with improved depressive symptoms and anhedonia following 8 weeks of treatment with escitalopram. Similarly, improvement in reward responsiveness during the first 2 weeks of adjunctive therapy with aripiprazole was associated with fewer symptoms of depression at post-treatment.

CONCLUSIONS

Findings highlight the predictive utility of early change in reward sensitivity during antidepressant treatment for major depression. In a clinical setting, a lack of change in early reward processing may signal a need to modify a patient's treatment plan with alternative or augmented treatment approaches.

Irritability and Its Clinical Utility in Major Depressive Disorder: Prediction of Individual-Level Acute-Phase Outcomes Using Early Changes in Irritability and Depression Severity

OBJECTIVE

The authors evaluated improvement in irritability with antidepressant treatment and its prognostic utility in treatment-seeking adult outpatients with major depressive disorder.

METHODS

Mixed-model analyses were used to assess changes in irritability (as measured with the five-item irritability domain of the Concise Associated Symptom Tracking [CAST-IRR] scale) from baseline to week 4 after controlling for depression severity (as measured with the 16-item Quick Inventory of Depressive Symptomatology-Clinician Rated [QIDS-C]) in the Combining Medications to Enhance Depression Outcomes (CO-MED) trial (N=664). An interactive calculator for remission (QIDS-C score ≤5) and no meaningful benefit (<30% reduction in QIDS-C score from baseline) at week 8 was developed with logistic regression analyses in the CO-MED trial using participants with complete data (N=431) and independently replicated in the Suicide Assessment and Methodology Study (SAMS) (N=163).

RESULTS

In the CO-MED trial, irritability was significantly reduced (effect size=1.06) from baseline to week 4, and this reduction remained significant after adjusting for QIDS-C change (adjusted effect size=0.36). A one-standard-deviation greater reduction in CAST-IRR score from baseline to week 4 predicted a 1.73 times higher likelihood of remission and a 0.72 times lower likelihood of no meaningful benefit at week 8, independent of baseline QIDS-C and CAST-IRR scores and reduction in QIDS-C score from baseline to week 4. The model estimates for remission (area under the curve [AUC]=0.79) and no meaningful benefit (AUC=0.76) in the CO-MED trial were used to predict remission (AUC=0.80) and no meaningful benefit (AUC=0.84) in SAMS and to develop an interactive calculator.

CONCLUSIONS

Irritability is an important symptom domain of major depressive disorder that is not fully reflected in depressive symptom severity measures. Early reductions in irritability, when combined with changes in depressive symptom severity, provide a robust estimate of likelihood of remission or no meaningful benefit in outpatients with major depression.

Prediction of Acute-Phase Treatment Outcomes by Adding a Single-Item Measure of Activity Impairment to Symptom Measurement: Development and Validation of an Interactive Calculator from the STAR*D and CO-MED Trials

BACKGROUND

Day-to-day functioning is impaired in major depressive disorder. Yet there are no guidelines to systematically assess these functional changes. This report evaluates prognostic utility of changes in activity impairment to inform clinical decision-making at an individual level.

METHODS

Mixed model analyses tested changes in activity impairment (sixth item of Work and Activity Impairment scale, rated 0-10) at mid-point (week 6) and end of step 1 (weeks 12-14) in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial (n = 2697) after controlling for depression severity [Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR)]. Interactive calculators for end of step 1 remission (QIDS-SR ≤5) and no meaningful benefit (<30% QIDS-SR reduction from baseline) were developed for participants with complete data (n = 1476) and independently replicated in the Combining Medications to Enhance Depression Outcomes trial (n = 399).

RESULTS

Activity impairment improved independently with acute-phase treatment in STAR*D (F = 7.27; df = 2,2625; P < .001). Baseline to mid-point activity impairment change significantly predicted remission (P < .001, model area under the curve = 0.823) and no meaningful benefit (P < .001, area under the curve = 0.821) in the STAR*D trial. Adding activity impairment variables to depression severity measures correctly reclassified 28.4% and 15.8% remitters and nonremitters (net reclassification improvement analysis, P < .001), and 11.4% and 16.8% of those with no meaningful benefit and meaningful benefit (net reclassification improvement analysis, P < .001). The STAR*D trial model estimates accurately predicted remission (area under the curve = 0.80) and no meaningful benefit (area under the curve = 0.82) in the Combining Medications to Enhance Depression Outcomes trial and was used to develop an interactive calculator.

CONCLUSION

A single-item self-report measure of activity impairment changes independently with antidepressant treatment. Baseline to week 6 changes in activity impairment and depression severity can be combined to predict acute-phase remission and no meaningful benefit at an individual level.

Personalized Antidepressant Selection and Pathway to Novel Treatments: Clinical Utility of Targeting Inflammation

Major depressive disorder (MDD) is a chronic condition that affects one in six adults in the US during their lifetime. The current practice of antidepressant medication prescription is a trial-and-error process. Additionally, over a third of patients with MDD fail to respond to two or more antidepressant treatments. There are no valid clinical markers to personalize currently available antidepressant medications, all of which have similar mechanisms targeting monoamine neurotransmission. The goal of this review is to summarize the recent findings of immune dysfunction in patients with MDD, the utility of inflammatory markers to personalize treatment selection, and the potential of targeting inflammation to develop novel antidepressant treatments. To personalize antidepressant prescription, a c-reactive protein (CRP)-matched treatment assignment can be rapidly implemented in clinical practice with point-of-care fingerstick tests. With this approach, 4.5 patients need to be treated for 1 additional remission as compared to a CRP-mismatched treatment assignment. Anti-cytokine treatments may be effective as novel antidepressants. Monoclonal antibodies against proinflammatory cytokines, such as interleukin 6, interleukin 17, and tumor necrosis factor α, have demonstrated antidepressant effects in patients with chronic inflammatory conditions who report significant depressive symptoms. Additional novel antidepressant strategies targeting inflammation include pharmaceutical agents that block the effect of systemic inflammation on the central nervous system. In conclusion, inflammatory markers offer the potential not only to personalize antidepressant prescription but also to guide the development of novel mechanistically-guided antidepressant treatments.

Clinical Implications of the STAR*D Trial

This chapter provides a synopsis of the clinically relevant findings derived from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study and selected ancillary studies appended to the primary trial. The chapter describes the participants, their recruitment and treatment, and the study design, primary outcomes, and clinically informative results. In particular, the chapter describes acute phase response and remission rates from each of the five treatment steps which entail antidepressant monotherapies and combinations, and psychotherapy alone or in combination with an antidepressant. In addition, longer-term outcomes beyond the 12 week acute trial are described for each treatment step. The treatment challenges described include patient retention and relapse, and longer-term follow-up. The chapter discusses the use of measurement-based care for delivering high-quality care, describes "treatment-resistant" depression and discusses its implications for clinical practice, and discusses the contributions of STAR*D to patient-oriented research and patient care.

The potential of predictive analytics to provide clinical decision support in depression treatment planning

PURPOSE OF REVIEW

To review progress developing clinical decision support tools for personalized treatment of major depressive disorder (MDD).

RECENT FINDINGS

Over the years, a variety of individual indicators ranging from biomarkers to clinical observations and self-report scales have been used to predict various aspects of differential MDD treatment response. Most of this work focused on predicting remission either with antidepressant medications versus psychotherapy, some antidepressant medications versus others, some psychotherapies versus others, and combination therapies versus monotherapies. However, to date, none of the individual predictors in these studies has been strong enough to guide optimal treatment selection for most patients. Interest consequently turned to decision support tools made up of multiple predictors, but the development of such tools has been hampered by small study sample sizes. Design recommendations are made here for future studies to address this problem.

SUMMARY

Recommendations include using large prospective observational studies followed by pragmatic trials rather than smaller, expensive controlled treatment trials for preliminary development of decision support tools; basing these tools on comprehensive batteries of inexpensive self-report and clinical predictors (e.g., self-administered performance-based neurocognitive tests) versus expensive biomarkers; and reserving biomarker assessments for targeted studies of patients not well classified by inexpensive predictor batteries.

Worsening Anxiety, Irritability, Insomnia, or Panic Predicts Poorer Antidepressant Treatment Outcomes: Clinical Utility and Validation of the Concise Associated Symptom Tracking (CAST) Scale

BACKGROUND

We report on the psychometric properties of the 16-item Concise Associated Symptom Tracking Scale self-report scale and its clinical utility.

METHODS

The 5-domain (irritability, anxiety, mania, insomnia, and panic) structure of Concise Associated Symptom Tracking Scale was validated with confirmatory factor analysis in Combining Medications to Enhance Depression Outcomes trial participants at baseline (n=664). Correlations with other clinical measures were used for convergent and divergent validity. In participants with at least one postbaseline visit (n=630), worsening in each Concise Associated Symptom Tracking Scale domain was defined as ≥1.28 SD increase from baseline for each visit (weeks 1, 2, 4, and 6) only. Worsening in any domain (except mania) was defined as overall worsening. Association of domain-specific and overall worsening with remission was tested with logistic regression analyses.

RESULTS

The 5-domain structure had adequate model fit on confirmatory factor analysis (GFI=0.93, CFI=0.89, and RMSEA=0.07). Scores on anxiety, panic, insomnia, and mania significantly correlated with Hamilton Rating Scale for Depression anxiety subscale (rs=0.27), Psychiatric Diagnostic Screening Questionnaire-panic scale (rs=0.35), sum of 3 Quick Inventory of Depressive Symptomatology Self-Report insomnia items (rs=0.55), and Altman Self-Rating Mania scale (rs=0.41), respectively. From baseline to week 6, 5.2%, 7.5%, 47.6%, 15.6%, 6.2%, and 27.6% participants (n=630) experienced irritability, anxiety, mania, insomnia, panic, and overall worsening, respectively. Participants with overall worsening were less likely to remit (31.6%) than those without any worsening (43.9%; odds ratio=0.53, 95% CI=0.36, 0.78).

CONCLUSION

The 16-item Concise Associated Symptom Tracking Scale self-report has acceptable psychometric properties. Clinically significant worsening of irritability, anxiety, insomnia, or panic with antidepressant treatment is associated with poorer outcomes.