Mortality risk from long-term treatment with antipsychotic polypharmacy vs monotherapy among adults with serious mental illness: A systematic review and meta-analysis of observational studies

Association of Antipsychotic Polypharmacy and Two-Year All-Cause Mortality: A Population-Based Cohort Study of 33,221 Italian Continuous Users

Background: Differences in survival between patients treated with antipsychotic monotherapy vs. polytherapy are debated. This study aimed to examine the association of antipsychotic polytherapy with 2-year all-cause mortality in a population-based cohort. Methods: Data were retrieved from healthcare databases of four local health units of Lombardy, Italy. Subjects aged 18-79 years who received continuous antipsychotic prescriptions in 2018 were identified. Overall survival among patients with antipsychotic monotherapy vs. polytherapy was compared. A multivariate Cox PH model was used to estimate the association between antipsychotic therapy, or antipsychotic use (continuous vs. non-continuous), and all-cause mortality. Adjustments were made for the presence of metabolic disturbances, total antipsychotic dosage amount (olanzapine equivalent doses), age, and sex. Results: A total of 49,875 subjects receiving at least one prescription of antipsychotics during 2018 were identified. Among the 33,221 patients receiving continuative antipsychotic prescriptions, 1958 (5.9%) experienced death from any cause at two years. Patients with continuous antipsychotic use had a 1.13-point increased mortality risk compared with non-continuous users. Patients treated with antipsychotic polytherapy showed an adjusted mortality risk increased by 17% (95% CI: 2%, 33%) compared to monotherapy. Conclusions: The study highlights the potential risks associated with antipsychotic polypharmacy, emphasizing the importance of optimizing drug prescriptions to improve patient safety and reduce mortality rates in individuals receiving antipsychotic therapy.

Antipsychotic polypharmacy and adverse drug reactions among adults in a London mental health service, 2008-2018

BACKGROUND

Antipsychotic polypharmacy (APP) occurs commonly but it is unclear whether it is associated with an increased risk of adverse drug reactions (ADRs). Electronic health records (EHRs) offer an opportunity to examine APP using real-world data. In this study, we use EHR data to identify periods when patients were prescribed 2 + antipsychotics and compare these with periods of antipsychotic monotherapy. To determine the relationship between APP and subsequent instances of ADRs: QT interval prolongation, hyperprolactinaemia, and increased body weight [body mass index (BMI) ⩾ 25].

METHODS

We extracted anonymised EHR data. Patients aged 16 + receiving antipsychotic medication at Camden & Islington NHS Foundation Trust between 1 January 2008 and 31 December 2018 were included. Multilevel mixed-effects logistic regression models were used to elucidate the relationship between APP and the subsequent presence of QT interval prolongation, hyperprolactinaemia, and/or increased BMI following a period of APP within 7, 30, or 180 days respectively.

RESULTS

We identified 35 409 observations of antipsychotic prescribing among 13 391 patients. Compared with antipsychotic monotherapy, APP was associated with a subsequent increased risk of hyperprolactinaemia (adjusted odds ratio 2.46; 95% CI 1.87-3.24) and of registering a BMI > 25 (adjusted odds ratio 1.75; 95% CI 1.33-2.31) in the period following the APP prescribing.

CONCLUSIONS

Our observations suggest that APP should be carefully managed with attention to hyperprolactinaemia and obesity.

Associations between the number of antipsychotics prescribed and metabolic parameters in Japanese patients with schizophrenia

Aim

There is little evidence on the effects of antipsychotic polypharmacy on metabolic parameters in patients with schizophrenia. Thus, this cross-sectional study explored the associations between the number of antipsychotics prescribed and metabolic parameters in Japanese patients with schizophrenia.

Methods

We obtained metabolic parameter data from 19,675 patients with schizophrenia. Of these, 1380 (7.0%), 8422 (42.8%), 6326 (32.2%), and 3547 (18.0%) were treated with none, one, two, and three or more antipsychotics, respectively. We compared eight metabolic parameters among the four groups using univariate analyses. We then performed multiple regression analysis to assess the effect of the number of antipsychotics prescribed on metabolic parameters after controlling for the effects of age, sex, type of care (outpatient/inpatient), chlorpromazine-equivalent dose, and antipsychotic type (aripiprazole, olanzapine, and risperidone).

Results

There were significant differences in body mass index (BMI), systolic and diastolic blood pressure (dBP), total cholesterol, low-density lipoprotein cholesterol, and triglycerides among the four groups. The multiple regression analysis showed that the number of antipsychotics prescribed was significantly correlated with BMI and dBP (standardized regression coefficient = 0.031 and 0.026, respectively).

Conclusion

Our results suggested that the number of antipsychotics prescribed adversely affects BMI and dBP. Clinicians should avoid inappropriate antipsychotic polypharmacy, especially polypharmacy involving three or more antipsychotics.

Antipsychotic Polypharmacy and High-Dose Antipsychotic Regimens in the Residential Italian Forensic Psychiatric Population (REMS)

Few data exist regarding treatment with antipsychotics in forensic psychiatric patient populations with high social dangerousness. We performed a secondary analysis of 681 patients treated with at least one antipsychotic, extracted from a 1-year observational retrospective study, conducted on 730 patients treated in the Italian Residencies for Execution of Security Measures (REMS) (96.4% of the REMS population). We aimed at investigating antipsychotic polypharmacy (prescription of two or more concomitant antipsychotics) and high dose/very high-dose antipsychotics, as well as the possible factors associated with such therapeutic regimens. High dose/very high-dose antipsychotics were defined as a prescribed daily dose to WHO-defined daily dose ratio greater than 1.5 or 3.0, respectively. Binary logistic regression analysis was used in three models to test possible predictors of antipsychotic polypharmacy, high-dose antipsychotics, and very high-dose antipsychotic prescription. Antipsychotic polypharmacy resulted in n = 308 (45.2%) of the patients, n = 346 (50.8%) received high-dose antipsychotics, and n = 96 (14.1%) very high-dose antipsychotics. The multivariate analysis disclosed an association between antipsychotic polypharmacy and male gender (odds ratio (OR): 2.75 and 95% CI: 1.34–5.65), long-acting injectable (LAI) antipsychotic prescription (OR: 2.62 and 95% CI: 1.84–3.74), and aggressive behavior in REMS (OR: 1.63 and 95% CI: 1.13–2.36). High-dose antipsychotics were also associated with male gender (OR: 2.01 and 95% CI: 1.02–3.95), LAI antipsychotic prescription (OR: 2.78 and 95% CI: 1.95–3.97), and aggressive behavior in REMS (OR: 1.63 and 95% CI: 1.12–2.36). The use of antipsychotic polypharmacy and high-dose antipsychotics is frequent in the REMS population. These results might depend on regulatory and organizational aspects of the REMS system, including variability in structures, lack of a common model of care, and lack of stratified therapeutic security.

COVID-19-Related Mortality Risk in People With Severe Mental Illness: A Systematic and Critical Review

Background: Increasing clinical evidence suggests that people with severe mental illness (SMI), including schizophrenia spectrum disorders, bipolar disorder (BD), and major depressive disorder (MDD), are at higher risk of dying from COVID-19. Several systematic reviews examining the association between psychiatric disorders and COVID-19-related mortality have recently been published. Although these reviews have been conducted thoroughly, certain methodological limitations may hinder the accuracy of their research findings. Methods: A systematic literature search, using the PubMed, Embase, Web of Science, and Scopus databases (from inception to July 23, 2021), was conducted for observational studies assessing the risk of death associated with COVID-19 infection in adult patients with pre-existing schizophrenia spectrum disorders, BD, or MDD. Methodological quality of the included studies was assessed using the Newcastle-Ottawa Scale (NOS). Results: Of 1,446 records screened, 13 articles investigating the rates of death in patients with pre-existing SMI were included in this systematic review. Quality assessment scores of the included studies ranged from moderate to high. Most results seem to indicate that patients with SMI, particularly patients with schizophrenia spectrum disorders, are at significantly higher risk of COVID-19-related mortality, as compared to patients without SMI. However, the extent of the variation in COVID-19-related mortality rates between studies including people with schizophrenia spectrum disorders was large because of a low level of precision of the estimated mortality outcome(s) in certain studies. Most studies on MDD and BD did not include specific information on the mood state or disease severity of patients. Due to a lack of data, it remains unknown to what extent patients with BD are at increased risk of COVID-19-related mortality. A variety of factors are likely to contribute to the increased mortality risk of COVID-19 in these patients. These include male sex, older age, somatic comorbidities (particularly cardiovascular diseases), as well as disease-specific characteristics. Conclusion: Methodological limitations hamper the accuracy of COVID-19-related mortality estimates for the main categories of SMIs. Nevertheless, evidence suggests that SMI is associated with excess COVID-19 mortality. Policy makers therefore must consider these vulnerable individuals as a high-risk group that should be given particular attention. This means that targeted interventions to maximize vaccination uptake among these patients are required to address the higher burden of COVID-19 infection in this already disadvantaged group.

The More, the Merrier…? Antipsychotic Polypharmacy Treatment Strategies in Schizophrenia From a Pharmacology Perspective

Antipsychotic polypharmacy/drug combination treatment (APP) is a remarkably common practice in the schizophrenia context, given the lack of general support in treatment Guidelines. There is also a vast literature on APP outcomes, but a paucity of high-quality evidence-based data to guide and optimize adequate use of APP. This seems particularly true regarding many pharmacology-based considerations involved in APP treatment strategies. This paper first briefly summarizes clinical literature related to the use of APP. Against this backdrop, the pharmacological target profile features are then described of frequently used antipsychotic agents, in relation to estimated free plasma exposure levels at clinically efficacious dosing. APP strategies based on the properties of these drugs are then scrutinized and gauged within the background literature framework. The anticipated usefulness of APP from the pharmacological standpoint is detailed regarding efficacy, adverse effect (AE)/tolerability, and safety perspective, including why, when, and how it may be used to its advantage. For the purpose, a number of theoretically beneficial combinations as well as instances with suboptimal-and even futile-APP approaches are exemplified and discussed from the rational pharmacodynamic and pharmacokinetic pros and cons point-of-view. In this exposé, particular attention is paid to the utility and features of 3rd Generation Antipsychotic dopamine (DA) D2-D3 agonists within an APP setting.