Pharmacological management of neuropsychiatric symptoms in patients with major neurocognitive disorders

Sociodemographics and clinical factors associated with depression treatment outcomes in 65,741 first-time users of selective serotonin reuptake inhibitors: A Danish cohort study in older adults

OBJECTIVE

To investigate a wide range of sociodemographic and clinical factors associated with treatment outcomes in older adults who initiated an SSRI for depression treatment in a real-world setting.

METHODS

This cohort study used Danish registry data covering all older adults (aged ≥65) who initiated SSRIs for depression from 2006 to 2017, first-time (since 1995). We followed the individuals for one year after their SSRI prescription. Six different outcomes were analyzed, including treatment discontinuation, switching, augmentation, psychiatric hospital contacts for depression, psychiatric hospital admission, and suicide attempt/self-harm. Association analyses employed Poisson regression, estimating incidence rate ratios with 95 % confidence intervals.

RESULTS

The study included 65,741 individuals with a mean age of 78.23 years, and 55.6 % were females. During follow-up, 40.1 % discontinued, 4.8 % switched, 20.3 % received augmentation, 3.0 % had psychiatric hospital contacts for depression, 3.2 % had psychiatric admission, and 0.1 % had suicide attempt/self-harm records. Differential treatment outcomes were observed based on sociodemographic and clinical factors. For example, being female, residing predominantly in rural areas, having psychiatric or somatic diagnoses, and using medications acting on blood/blood-forming organs, the cardiovascular system, or musculo-skeletal systems were linked to fewer unfavorable clinical outcomes. Conversely, marital status as being single or separated and the use of nervous system drugs were associated with a higher risk of unfavorable outcomes.

LIMITATIONS

Confounding by indication might remain a problem, and depression severity data was not unavailable.

CONCLUSIONS

Our findings emphasize considering patient characteristics in clinical decisions, as they can influence the clinical course of those undergoing depression treatment.

Prediction of antipsychotics efficacy based on a polygenic risk score: a real-world cohort study

Background: Response to antipsychotics is subject to a wide interindividual variability, due to genetic and non-genetic factors. Several single nucleotide polymorphisms (SNPs) have been associated with response to antipsychotics in genome-wide association studies (GWAS). Polygenic risk scores (PRS) are a powerful tool to aggregate into a single measure the small effects of multiple risk alleles. Materials and methods: We studied the association between a PRS composed of SNPs associated with response to antipsychotics in GWAS studies (PRSresponse) in a real-world sample of patients (N = 460) with different diagnoses (schizophrenia spectrum, bipolar, depressive, neurocognitive, substance use disorders and miscellaneous). Two other PRSs composed of SNPs previously associated with risk of schizophrenia (PRSschizophrenia1 and PRSschizophrenia2) were also tested for their association with response to treatment. Results: PRSresponse was significantly associated with response to antipsychotics considering the whole cohort (OR = 1.14, CI = 1.03-1.26, p = 0.010), the subgroup of patients with schizophrenia, schizoaffective disorder or bipolar disorder (OR = 1.18, CI = 1.02-1.37, p = 0.022, N = 235), with schizophrenia or schizoaffective disorder (OR = 1.24, CI = 1.04-1.47, p = 0.01, N = 176) and with schizophrenia (OR = 1.27, CI = 1.04-1.55, p = 0.01, N = 149). Sensitivity and specificity were sub-optimal (schizophrenia 62%, 61%; schizophrenia spectrum 56%, 55%; schizophrenia spectrum plus bipolar disorder 60%, 56%; all patients 63%, 58%, respectively). PRSschizophrenia1 and PRSschizophrenia2 were not significantly associated with response to treatment. Conclusion: PRSresponse defined from GWAS studies is significantly associated with response to antipsychotics in a real-world cohort; however, the results of the sensitivity-specificity analysis preclude its use as a predictive tool in clinical practice.