Multi-trajectories of antidepressant and antipsychotic use: a 11-year naturalistic study in a community-based sample

Optimizing antidepressant and clozapine co-prescription in clinical practice: A systematic review and expert recommendations

OBJECTIVES

To synthesize the information relevant for clinical practice on clozapine-antidepressant co-prescription concerning pharmacokinetic drug-drug interactions (DDI), adverse drug reactions (ADRs) associated with the co-prescription, antidepressant add-on for clozapine-resistant symptoms and antidepressant add-on for clozapine-induced ADRs.

METHODS

Articles were identified with MEDLINE, Web of Sciences and PsycINFO search from inception through April 2023. Data were synthesized narratively.

RESULTS

ADRs are most often induced by the co-prescription of antidepressants that inhibit CYP enzymes (fluvoxamine, fluoxetine, paroxetine). Fluvoxamine add-on is hazardous because of its potent inhibition of clozapine metabolism and has few indications (lowering daily number of clozapine tablets, reducing norclozapine-induced metabolic disturbances and other dose-dependent clozapine-induced ADRs). ADR frequency may be reduced by therapeutic drug monitoring and knowledge of other factors impacting clozapine metabolism (pneumonia, inflammation, smoking, etc.). Improvement of negative symptoms is the most documented beneficial effect of antidepressant add-on for clozapine-resistant psychotic symptoms. The add-on antidepressant should be chosen according to its safety profile regarding DDI with clozapine: antidepressants inhibiting clozapine metabolism or increasing the anticholinergic load should be avoided. Other indications of antidepressant add-on (affective or obsessive compulsive symptoms, sialorrhea, and enuresis) are poorly documented.

CONCLUSION

Antidepressant add-on to clozapine is associated with potential benefits in clozapine users as this strategy may contribute to reduce the burden of clozapine-resistant symptoms or of clozapine-induced ADRs. Further studies are needed to determine whether antidepressant add-on can reduce the risk of clozapine discontinuation.

Psychotropic medication use in people living with severe and persistent mental illness in the Australian community: a cross-sectional study

BACKGROUND

Psychotropic polypharmacy and high-dose prescribing may play a role in therapy, however, with associated risks. The aim of this study was to describe current prescribing practices and use of four psychotropic medication groups (antipsychotics, antidepressants, mood stabilisers and benzodiazepines), focusing on polypharmacy (across and within groups) and high-dose prescribing in adults experiencing severe and persistent mental illness (SPMI) in the Australian community.

METHODS

318 people taking psychotropic medication for SPMI had a medication review undertaken by a community pharmacist. Participants were recruited as part of an RCT from three Australian states/territories between September 2020-July 2021. All psychotropic medication and daily doses were recorded and reviewed for alignment with current clinical guidelines. Univariate and multiple logistic regression models investigated factors associated with antipsychotic, antidepressant, and mood stabiliser polypharmacy, and antipsychotic and antidepressant high-dose therapy. Variables included age, gender, geographic location, self- reported mental illness(es), hospital admission(s) in previous 6-months and prescriber type.

RESULTS

806 psychotropic medications were prescribed for the 318 participants. Mood stabiliser polypharmacy was recorded in 19.0% of participants prescribed mood stabilisers; antipsychotic polypharmacy in 18.4% of participants prescribed antipsychotics; antidepressant polypharmacy in 11.3% of those prescribed antidepressants; and three participants (5.1%) were prescribed two benzodiazepines concurrently. Almost 18.6% of the cohort was receiving high-dose treatment; 18 participants were prescribed high-dose antipsychotics and 39 high-dose antidepressants, with two participants prescribed both. Adjusted logistic regression for polypharmacy found male gender, psychiatrist as sole prescriber, or multiple prescribers, were associated with antipsychotic polypharmacy. The adjusted model for high-dose therapy found psychiatrist as sole prescriber was significantly associated with antipsychotic and antidepressant high-dose prescribing.

CONCLUSION

Psychotropic polypharmacy was common in this community cohort experiencing SPMI. Whilst polypharmacy is not always inappropriate, it is a complex construct with potential benefits alongside potential risks. Benefits and harms need to be balanced however this practice is not supported by clear guidance to assist health practitioners. This study highlights the important need for regular medication reviews and strengthened communication between consumers and all healthcare professionals involved in community mental health care, to support safe and effective use of psychotropic medications.

Characteristics associated with self-reported medication adherence in persons with psychosis referred to psychosocial rehabilitation centers

The aim of the present study was to explore the characteristics of psychotropic treatment and of psychosocial functioning associated with self-reported medication adherence in persons with psychosis engaged in rehabilitation. The study was performed in the REHABase cohort including persons referred to a French network of psychosocial rehabilitation centers. Treatment adherence was assessed using the Medication Adherence Rating Scale (MARS). The associations between MARS score (categorized as "low" < 7 vs. "high" ≥ 7) and functioning or psychotropic treatment characteristics were explored using multivariate analyses in 326 participants with schizophrenia spectrum disorders. Regarding psychotropic treatment, high anticholinergic load was the only characteristic associated with poor medication adherence (adjusted OR, aOR 1.98, 95% CI 1.07-3.66). Regarding functioning measures, participants with poor medication adherence were more likely to present with lower stage of recovery (aOR 2.38, 95% CI 1.31-4.32), poor quality of life (aOR 2.17, 95% CI 1.27-3.71), mental well-being (aOR 1.68, 95% CI 1.03-2.72) and self-esteem (aOR 1.74, 95% CI 1.05-2.87), and higher internalized stigma (aOR 1.88, 95% CI 1.09-3.23). Self-reported poor medication adherence is a marker of poor functioning in persons with psychosis. The MARS is a quick and simple measure of adherence that may be helpful in clinical and rehabilitation settings to identify persons with specific rehabilitation needs.

Hyperuricemia and Progression of Chronic Kidney Disease: A Review from Physiology and Pathogenesis to the Role of Urate-Lowering Therapy

The relationship between hyperuricemia, gout, and renal disease has been investigated for several years. From the beginning, kidney disease has been considered a complication of gout; however, the viewpoints changed, claiming that hypertension and elevated uric acid (UA) levels are caused by decreased urate excretion in patients with renal impairment. To date, several examples of evidence support the role of hyperuricemia in cardiovascular or renal diseases. Several mechanisms have been identified that explain the relationship between hyperuricemia and chronic kidney disease, including the crystal effect, renin-angiotensin-aldosterone system activation, nitric oxide synthesis inhibition, and intracellular oxidative stress stimulation, and urate-lowering therapy (ULT) has been proven to reduce renal disease progression in the past few years. In this comprehensive review, the source and physiology of UA are introduced, and the mechanisms that explain the reciprocal relationship between hyperuricemia and kidney disease are reviewed. Lastly, current evidence supporting the use of ULT to postpone renal disease progression in patients with hyperuricemia and gout are summarized.

Use of the French national health insurance information system for research in the field of mental health: Systematic review and perspectives

PURPOSE

This systematic review registered in PROSPERO (CRD42021225296) aimed to describe the use of the French national health insurance information system, which covers the entire French population (67 million inhabitants), for research in the field of mental health.

METHODS

Three electronic databases and a journal hand-search identified 15 265 articles from January 1, 2003 (year of creation of the database) to October 31, 2020. Studies of any design were eligible for inclusion provided that they (i) made use of at least one component of the French health insurance database and (ii) focused on a topic in near and far connection with the field of mental health in France. Database used, design and methods, study period, population, key findings, and type of use for medical research were described.

RESULTS

A total of 152 studies were included in the review analysis. There was an increase in the number of published articles over time throughout the studied period. Studies focusing on adults (n = 139) largely outnumbered those focusing on children and adolescents (n = 11). Pharmacoepidemiological studies were by far the most frequent (n = 123), followed by methodological studies (n = 23), epidemiological studies (n = 17), and health economics studies (n = 3). The most studied psychotropic drugs were antidepressants (n = 27), anxiolytics (n = 27), and opioids (n = 25) while fewer studies focused on methylphenidate (n = 6) and on mood stabilizers (n = 5). Few studies specifically focused on psychiatric disorders, mainly depression (n = 4), suicide (n = 4), and psychotic disorders (n = 3).

CONCLUSION

This systematic review highlighted a relatively poor exploitation of the Système national des données de santé database in the field of psychiatric research with regard to the great possibilities it offers, with a clear lag in certain fields such as epidemiological or health economics studies and in specific populations, in particular children and adolescents.

Use of sequence analysis for classifying individual antidepressant trajectories to monitor population mental health

BACKGROUND

Over the past decade, antidepressant prescriptions have increased in European countries and the United States, partly due to an increase in the number of new cases of mental illness. This paper demonstrates an innovative approach to the classification of population level change in mental health status, using administrative data for a large sample of the Scottish population. We aimed to identify groups of individuals with similar patterns of change in pattern of prescribing, validate these groups by comparison with other indicators of mental illness, and characterise the population most at risk of increasing mental ill health.

METHODS

National Health Service (NHS) prescription data were linked to the Scottish Longitudinal Study (SLS), a 5.3% sample of the Scottish population (N = 151,418). Antidepressant prescription status over the previous 6 months was recorded for every month for which data were available (January 2009-December 2014), and sequence dissimilarity was computed by optimal matching. Hierarchical clustering was used to create groups of participants who had similar patterns of change, with multi-level logistic regression used to understand group membership.

RESULTS

Five distinct prescription pattern groups were observed, indicating: no prescriptions (76%), occasional prescriptions (10%), continuation of prior use of prescriptions (8%), a new course of prescriptions started (4%) or ceased taking prescriptions (3%). Young, white, female participants, of low social grade, residing in socially deprived neighbourhoods, living alone, being separated/divorced or out of the labour force, were more likely to be in the group that started a new course of antidepressant prescriptions.

CONCLUSIONS

The use of sequence analysis for classifying individual antidepressant trajectories offers a novel approach for capturing population-level changes in mental health risk. By classifying individuals into groups based on their anti-depressant medication use we can better identify how over time, mental health is associated with individual risk factors and contextual factors at the local level and the macro political and economic scale.