Real-world clinical predictors of manic/hypomanic episodes among outpatients with bipolar disorder

Background Bipolar disorder is a mental illness in which manic and depressive states are repeated, causing psychosocial dysfunction. Manic/hypomanic episodes cause problems with interpersonal, social and financial activities, but there is limited evidence regarding the predictors of manic/hypomanic episodes in real-world clinical practice. Methods The multicenter treatment survey on bipolar disorder (MUSUBI) in Japanese psychiatric clinics was administered in an observational study that was conducted to accumulate evidence regarding bipolar disorder in real-world clinical practice. Psychiatrists were asked to complete a questionnaire about patients with bipolar disorder who visited 176 member clinics of the Japanese Association of Neuro-Psychiatric Clinics by conducting a retrospective medical record survey. Our study extracted baseline patient characteristics from September to October 2016, including comorbidities, mental status, duration of treatment, Global Assessment of Functioning (GAF) score, and pharmacological treatment details. We investigated the presence or absence of manic/hypomanic episodes over the course of one year from baseline to September-October 2017. Results In total, 2231 participants were included in our study, 29.1% of whom had manic/hypomanic episodes over the course of one year from baseline. Binomial logistic regression analysis revealed that the presence of manic/hypomanic episodes was correlated with lower baseline GAF scores, rapid cycling, personality disorder, bipolar I disorder, and a mood state with manic or mixed features. Substance abuse was also a risk factor for manic episodes. There was no significant association between a baseline antidepressant prescription and manic/hypomanic episodes. Conclusions In Japan, 29.1% of outpatients with bipolar disorder had manic/hypomanic episodes over the course of one year. Our study suggested that a low GAF score, rapid cycling, personality disorder, bipolar I disorder, substance abuse, and baseline mood state could be predictors of manic/hypomanic episodes. Based on our findings, an antidepressant prescription is not a predictor of manic/hypomanic episodes.

Initial Antidepressant Choice by Non-Psychiatrists: Learning from Large-scale Electronic Health Records

Introduction. Pharmacological treatment of depression mostly occurs in non-psychiatric settings, but factors that determine the initial choice of antidepressant treatment in these settings are not well-understood. This study models how non-psychiatrists choose among four antidepressant classes at first prescription (selective serotonin reuptake inhibitors [SSRI], bupropion, mirtazapine, or serotonin-norepinephrine reuptake inhibitors [SNRI]), by analyzing electronic health record (EHR) data. Methods. EHR data were from the Mass General Brigham Healthcare System (Boston, Massachusetts, USA) for the period from 1990 to 2018. From a literature search and expert consultation, we selected 64 variables that may be associated with antidepressant choice. Patients who participated in the study were aged 18 to 65 at the time of first antidepressant prescription with a co-occurring International Classification of Diseases (ICD) code for a depressive disorder. Multinomial logistic regression with main effect terms for all 64 variables was used to model the choice of antidepressant. Using SSRI as the reference class, odds ratios, 95% confidence intervals (CI), and likelihood ratio-based p-values for each variable were reported. We used a false discovery rate (FDR) with the Benjamini-Hochberg procedure to correct for multiple comparisons. Findings. A total of 47,107 patients were included after application of inclusion/exclusion criteria. We observed significant associations for 36 of 64 variables after multiple comparison corrections. Many of these associations suggested that antidepressants' known pharmacological properties/actions guided choice. For example, there was a decreased likelihood of bupropion prescription among patients with epilepsy (adjusted OR 0.41, 95% CI: 0.33-0.51, p < 0.001), an increased likelihood of mirtazapine prescription among patients with insomnia (adjusted OR 1.58, 95% CI: 1.39-1.80, p < 0.001), and an increased likelihood of SNRI prescription among patients with pain (adjusted OR 1.22, 95% CI: 1.11-1.34, p = 0.001). Interpretation. Non-psychiatrists' selection of antidepressant class appears to be guided by clinically relevant pharmacological properties, indications, and contraindications, suggesting that broadly speaking they choose antidepressants based on meaningful differences among medication classes.

Pharmacogenetic-Guided Antidepressant Selection as an Opportunity for Interprofessional Collaboration: A Case Report

In the herein reported case of a 42-year-old woman diagnosed with anxiety and depression, a long history of antidepressant ineffectiveness and adverse drug reactions was decisive for an in-depth medication review including pharmacogenetic panel testing. In detail, treatment attempts with paroxetine and escitalopram were ineffective and discontinued due to subjective gastrointestinal intolerance. Due to the worsening of the depression after the failed treatment attempts, admission to our clinic became necessary. Herein, owing to the collaboration of psychiatrists with clinical pharmacists, individualized incorporation of pharmacogenetic data into the process of antidepressant selection was enabled. We identified vortioxetine as a suitable therapeutic, namely for being most likely pharmacokinetically unaffected as predicted by pharmacogenetic panel testing and taking into account the current comedication, as well as for its favorable action profile. Herein, our collaborative effort proved to be successful and resulted in the patient’s depression remission and clinic discharge with the interprofessionally selected pharmacotherapy. This exemplary case not only highlights the potential benefits and challenges of pre-emptive pharmacogenetic testing in antidepressant prescription, but also proposes an approach on how to put pharmacogenetics into practice.