Baseline anxiety, and early anxiety/depression improvement in anxious depression predicts treatment outcomes with escitalopram: A CAN-BIND-1 study report

Clinical correlates of anxious depression in youth from the Texas Youth Depression and Suicide Research Network (TX-YDSRN)

BACKGROUND

Anxious depression is a prevalent subtype of depression associated with adverse outcomes such as higher depression severity and higher rates of suicidality. This study leveraged a state-wide research registry of depressed and/or suicidal youth to compare the prevalence, clinical correlates, and symptom patterns of those with versus without anxious depression.

METHODS

We included baseline data from 797 participants (ages 8-20) with a diagnosis of a depressive disorder. A score on the Generalized Anxiety Disorder Scale (GAD-7) ≥ 10 was used to define individuals with and without anxious depression. A structured battery was used to capture psychiatric diagnostic status, depression/anxiety severity, suicide risk, history of trauma, functioning, and resilience.

RESULTS

The prevalence of anxious depression among youth with depressive disorders was 59.5 % (n = 474). Youth with anxious depression had greater depression severity and anxiety symptoms, higher suicidality, and a higher prevalence of comorbid anxiety disorders than those without. Youth with anxious depression had greater impairment in functioning defined as worse pain interference, pain severity, fatigue, and social relationships compared to those without anxious depression. Youth with anxious depression also reported higher rates of depressive symptoms such as irritable mood, feelings of guilt, and psychomotor agitation compared to those without anxious depression.

CONCLUSION

Anxious depression is associated with worse depression severity, higher suicidality, and lower functioning. Longitudinal work is needed to examine long-term courses of anxious depression to explore its stability as a diagnostic subcategory.

Early improvement with cariprazine as a predictor of antidepressant, anxiolytic, and antimanic response in bipolar I mania and depression: A pooled post hoc analysis of randomized cariprazine trials

BACKGROUND

Early symptomatic improvement may predict treatment response in bipolar I disorder. Cariprazine has demonstrated early treatment effects in bipolar I depression and mania studies; therefore, we assessed whether early improvement with cariprazine predicts eventual treatment response.

METHODS

Post hoc analyses used pooled data from randomized, double-blind, placebo-controlled bipolar I depression (NCT02670538, NCT02670551) and mania (NCT00488618, NCT01058096, NCT01058668) trials. In depression studies (cariprazine 1.5 mg/d, 3 mg/d, or placebo), early improvement in Montgomery-Åsberg Depression Rating Scale (MADRS) and Hamilton Anxiety Rating Scale (HAM-A) total scores (≥25 % improvement at day 15) and subsequent depressive/anxiety symptom response status (≥50 % improvement at week 6) were assessed. In mania studies (cariprazine 3-12 mg/d or placebo), early improvement in Young Mania Rating Scale (YMRS) total scores (≥25 % improvement at day 7) and manic symptom response status (≥50 % improvement at week 3) were assessed.

RESULTS

Patients with bipolar I depression and early MADRS improvement were approximately 4- to 6-times as likely to achieve MADRS or HAM-A response than those without early improvement; patients with early HAM-A improvement were approximately 3- to 4-times as likely to achieve MADRS or HAM-A response. A subset of patients without early improvement with cariprazine 1.5 mg/d (20 %-31 %) subsequently responded following up-titration. Patients with mania and early YMRS improvement were approximately 5 times more likely to have manic symptom response than those without early improvement.

LIMITATIONS

Post hoc analysis; relatively short study durations; flexible-dosing (mania studies).

CONCLUSIONS

Early symptom improvement with cariprazine may inform therapeutic decisions for patients with bipolar I disorder.

Predicting Outcomes of Antidepressant Treatment in Community Practice Settings

OBJECTIVE

The authors examined whether machine-learning models could be used to analyze data from electronic health records (EHRs) to predict patients' responses to antidepressant medications.

METHODS

EHR data from a Washington State health system identified patients ages ≥13 years who started an antidepressant medication in 2016 in a community practice setting and had a baseline Patient Health Questionnaire-9 (PHQ-9) score of ≥10 and at least one PHQ-9 score recorded 14-180 days later. Potential predictors of a response to antidepressants were extracted from the EHR and included demographic characteristics, psychiatric and substance use diagnoses, past psychiatric medication use, mental health service use, and past PHQ-9 scores. Random-forest and penalized regression analyses were used to build models predicting follow-up PHQ-9 score and a favorable treatment response (≥50% improvement in score).

RESULTS

Among 2,469 patients starting antidepressant medication treatment, the mean±SD baseline PHQ-9 score was 17.3±4.5, and the mean lowest follow-up score was 9.2±5.9. Outcome data were available for 72% of the patients. About 48% of the patients had a favorable treatment response. The best-fitting random-forest models yielded a correlation between predicted and observed follow-up scores of 0.38 (95% CI=0.32-0.45) and an area under the receiver operating characteristic curve for a favorable response of 0.57 (95% CI=0.52-0.61). Results were similar for penalized regression models and for models predicting last PHQ-9 score during follow-up.

CONCLUSIONS

Prediction models using EHR data were not accurate enough to inform recommendations for or against starting antidepressant medication. Personalization of depression treatment should instead rely on systematic assessment of early outcomes.

Efficacy of acupuncture for depression: a systematic review and meta-analysis

Introduction

Depression is a pervasive mental health challenge with substantial global ramifications. Contemporary therapeutic strategies predominantly consist of psychological interventions and pharmacological treatments. Acupuncture, deeply rooted in ancient traditions and bolstered by a plethora of clinical trials, demonstrates considerable efficacy in depression. This study aims to elucidate the efficacy and safety of acupuncture as a standalone therapy for depression patients by reviewing randomized controlled trials that compare acupuncture treatment with conventional drug therapy.

Methods

Comprehensive searches were conducted across six databases in both Chinese and English: CNKI, Wanfang, VIP, Embase, Medline, and CENTRAL. The literature search spanned from 1 July 2013, to 1 July 2023. Two researchers independently carried out literature screening and data extraction. Review Manager 5.4 was utilized for data analysis and bias risk assessment. A total of 20 randomized controlled trials were included in the qualitative synthesis, involving 1,376 participants and 43 relevant acupoints.

Results

The Meta-analysis results, based on the HAMD scale scores, revealed that acupuncture regimens (RR: -1.63; 95% CI: -2.49 to -0.76; P = 0.0002; I2 = 86%; n = 1,668) were significantly more effective compared to standalone medication. Moreover, efficacy metrics from the HAMD highlighted a substantial advantage of acupuncture (RR: 2.6; 95% CI: 1.6 to 4.23; P = 0.0001; I2 = 0; n = 614). Further assessments utilizing SERS and TESS demonstrated a lower incidence of side effects and adverse outcomes in the acupuncture group.

Conclusions

Acupuncture, when compared to conventional pharmacotherapy, exhibits significant efficacy as a standalone treatment after four weeks of intervention, with fewer side effects and adverse reactions. However, further investigation is needed to determine the most effective acupoints and appropriate types of acupuncture techniques for treating depression.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42023443711.

Neurobiology of Treatment in Pediatric Anxiety Disorders

Both pharmacologic and psychotherapeutic treatment-related changes increase activity in brain regions implicated in prefrontal regulatory circuits, and the functional connectivity of these regions with the amygdala is enhanced following pharmacological treatment. This may suggest overlapping mechanisms of action across therapeutic modalities. The existing literature is best viewed as a partially constructed scaffold on which to construct a vigorous understanding of biomarkers in pediatric anxiety syndromes. As the field approaches leveraging "fingerprints" in neuroimaging with "outputs" in neuropsychiatric tasks and scale, we can move beyond one-size-fits-all selection of psychiatric interventions toward more nuanced therapeutic strategies that recognize individual differences.