Olanzapine and fluoxetine combination therapy for treatment-resistant depression: review of efficacy, safety, and study design issues

Treatment-resistant depression (TRD) is a common occurrence in clinical practice. Up to 30% of patients with major depression do not respond to conventional antidepressant treatment, while a significantly greater number of patients experience only partial symptom reduction. Numerous strategies may be applied by the practicing clinician to overcome limitations in the effectiveness of antidepressant monotherapy, including combining drug treatment with evidence-supported psychotherapies, combining antidepressants (combination pharmacotherapy), and combining antidepressants with other non-antidepressant psychotropic medications (augmentation treatment). One such augmentation strategy, the combination of the selective serotonin reuptake inhibitor, fluoxetine (FLX), with the atypical antipsychotic drug, olanzapine (OLZ), is supported by the results of four randomized, double-blind, acute phase studies of patients who had responded inadequately to antidepressant monotherapy. In each study, the FLX/OLZ combination caused rapid reduction in Montgomery-Asberg Depression Rating scale scores, with two of the four studies showing significantly greater improvement than antidepressant monotherapy at study endpoint. Effects of the FLX/OLZ combination were strongest in cases where failure to respond to two antidepressants prior to randomization was established during the current depressive episode. The FLX/OLZ combination was well-tolerated; however, body weight gain and increases in prolactin were greater than that of the antidepressant monotherapy groups, and were comparable to that of OLZ monotherapy. While effective during acute-phase treatment, questions remain regarding the long-term efficacy and safety of FLX/OLZ relative to antidepressant monotherapy and other combination strategies. Efforts aimed at determining the placement of FLX/OLZ among the available options for addressing TRD are limited by lack of comparison and sequential treatment studies. Important aspects of study design and directions for future research are discussed

Pharmacomicrobiomics of antidepressants in depression : a systematic review

This systematic review evaluated the animal and human evidence for pharmacomicrobiomics (PMx) interactions of antidepressant medications. Studies of gut microbiota effects on functional and behavioral effects of antidepressants in human and animal models were identified from PubMed up to December 2022. Risk of bias was assessed, and results are presented as a systematic review following PRISMA guidelines. A total of 28 (21 animal, 7 human) studies were included in the review. The reviewed papers converged on three themes: (1) Antidepressants can alter the composition and metabolites of gut microbiota, (2) gut microbiota can alter the bioavailability of certain antidepressants, and (3) gut microbiota may modulate the clinical or modeled mood modifying effects of antidepressants. The majority (n = 22) of studies had at least moderate levels of bias present. While strong evidence is still lacking to understand the clinical role of antidepressant PMx in human health, there is evidence for interactions among antidepressants, microbiota changes, microbiota metabolite changes, and behavior. Well-controlled studies of the mediating and moderating effects of baseline and treatment-emergent changes in microbiota on therapeutic and adverse responses to antidepressants are needed to better establish a potential role of PMx in personalizing antidepressant treatment selection and response prediction.https://www.mdpi.com/journal/jpmam2024Veterinary Tropical DiseasesSDG-03:Good heatlh and well-bein

Positive predictive value of automated database records for diabetic ketoacidosis (DKA) in children and youth exposed to antipsychotic drugs or control medications: a tennessee medicaid study

<p>Abstract</p> <p>Background</p> <p>Diabetic ketoacidosis (DKA) is a potentially life-threatening complication of treatment with some atypical antipsychotic drugs in children and <b>youth</b>. Because drug-associated DKA is rare, large automated health outcomes databases may be a valuable data source for conducting pharmacoepidemiologic studies of DKA associated with exposure to individual antipsychotic drugs. However, no validated computer case definition of DKA exists. We sought to assess the positive predictive value (PPV) of a computer case definition to detect incident cases of DKA, using automated records of Tennessee Medicaid as the data source and medical record confirmation as a "gold standard."</p> <p>Methods</p> <p>The computer case definition of DKA was developed from a retrospective cohort study of antipsychotic-related type 2 diabetes mellitus (1996-2007) in Tennessee Medicaid enrollees, aged 6-24 years. Thirty potential cases with any DKA diagnosis (ICD-9 250.1, ICD-10 E1x.1) were identified from inpatient encounter claims. Medical records were reviewed to determine if they met the clinical definition of DKA.</p> <p>Results</p> <p>Of 30 potential cases, 27 (90%) were successfully abstracted and adjudicated. Of these, 24 cases were confirmed by medical record review (PPV 88.9%, 95% CI 71.9 to 96.1%). Three non-confirmed cases presented acutely with severe hyperglycemia, but had no evidence of acidosis.</p> <p>Conclusions</p> <p>Diabetic ketoacidosis in children and youth can be identified in a computerized Medicaid database using our case definition, which could be useful for automated database studies in which drug-associated DKA is the outcome of interest.</p

Patterns of changes in bipolar depressive symptoms revealed by trajectory analysis among 482 patients with bipolar disorder

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149731/1/bdi12715_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149731/2/bdi12715.pd

Cytochrome P450 2C19 Poor Metabolizer Phenotype in Treatment Resistant Depression: Treatment and Diagnostic Implications

Background: Pharmacogenomic testing, specifically for pharmacokinetic (PK) and pharmacodynamic (PD) genetic variation, may contribute to a better understanding of baseline genetic differences in patients seeking treatment for depression, which may further impact clinical antidepressant treatment recommendations. This study evaluated PK and PD genetic variation and the clinical use of such testing in treatment seeking patients with bipolar disorder (BP) and major depressive disorder (MDD) and history of multiple drug failures/treatment resistance.Methods: Consecutive depressed patients evaluated at the Mayo Clinic Depression Center over a 10-year study time frame (2003–2013) were included in this retrospective analysis. Diagnoses of BP or MDD were confirmed using a semi-structured diagnostic interview. Clinical rating scales included the Hamilton Rating Scale for Depression (HRSD24), Generalized Anxiety Disorder 7-item scale (GAD-7), Patient Health Questionnaire-9 (PHQ-9), and Adverse Childhood Experiences (ACE) Questionnaire. Clinically selected patients underwent genotyping of cytochrome P450 CYP2D6/CYP2C19 and the serotonin transporter SLC6A4. PK and PD differences and whether clinicians incorporated test results in providing recommendations were compared between the two patient groups.Results: Of the 1795 patients, 167/523 (31.9%) with BP and 446/1272 (35.1%) with MDD were genotyped. Genotyped patients had significantly higher self-report measures of depression and anxiety compared to non-genotyped patients. There were significantly more CYP2C19 poor metabolizer (PM) phenotypes in BP (9.3%) vs. MDD patients (1.7%, p = 0.003); among participants with an S-allele, the rate of CYP2C19 PM phenotype was even higher in the BP (9.8%) vs. MDD (0.6%, p = 0.003). There was a significant difference in the distribution of SLC6A4 genotypes between BP (l/l = 28.1%, s/l = 59.3%, s/s = 12.6%) and MDD (l/l = 31.4%, s/l = 46.1%, s/s = 22.7%) patients (p &lt; 0.01).Conclusion: There may be underlying pharmacogenomic differences in treatment seeking depressed patients that potentially have impact on serum levels of CYP2C19 metabolized antidepressants (i.e., citalopram / escitalopram) contributing to rates of efficacy vs. side effect burden with additional potential risk of antidepressant response vs. induced mania. The evidence for utilizing pharmacogenomics-guided therapy in MDD and BP is still developing with a much needed focus on drug safety, side effect burden, and treatment adherence