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Daily Dose Effects of Risperidone on Weight and Other Metabolic Parameters: A Prospective Cohort Study

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Abstract

Background: Atypical antipsychotics can induce metabolic side effects, but whether they are dose-dependent remains unclear. Objective: To assess the effect of risperidone and/or paliperidone dosing on weight gain and blood lipids, glucose, and blood pressure alterations. Methods: Data for 438 patients taking risperidone and/or its metabolite (paliperidone) for up to 1 year were obtained between 2007 and 2018 from a longitudinal study monitoring metabolic parameters. Results: For each milligram increase in dose, we observed a weight increase of 0.16% at 1 month of treatment (P = .002) and increases of 0.29%, 0.21%, and 0.25% at 3, 6, and 12 months of treatment, respectively (P < .001 for each). Moreover, dose increases of 1 mg raised the risk of a ≥ 5% weight gain after 1 month (OR = 1.18; P = .012), a strong predictor of important weight gain in the long term. When we split the cohort into age categories, the dose had an effect on weight change after 3 months of treatment (up to 1.63%, P = .008) among adolescents (age ≤ 17 years), at 3 (0.13%, P = .013) and 12 (0.13%, P = .036) months among adults (age > 17 and < 65 years), and at each timepoint (up to 1.58%, P < .001) among older patients (age ≥ 65 years). In the whole cohort, for each additional milligram we observed a 0.05 mmol/L increase in total cholesterol (P = .018) and a 0.04 mmol/L increase in LDL cholesterol (P = .011) after 1 year. Conclusions: Although of small amplitude, these results show an effect of daily risperidone dose on weight gain and blood cholesterol levels. Particular attention should be given to the decision of increasing the drug dose, and minimum effective dosages should be preferred.

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Background Several psychotropic drugs can induce weight gain and metabolic alterations. The authors compared metabolic evolutions of patients switching versus continuing psychotropic treatments with different risk profiles. Methods Patients either switched from a high- to a medium- (N = 36) or low-risk drug (N = 27), from a medium- to a low-risk drug (N = 71), or to a same-risk drug (N = 61). Controls were kept using either a high- (N = 35), medium- (N = 155), or low-risk drug (N = 47). The evolution over 2 years of weight and metabolic parameters was analyzed using linear mixed-effect models, also examining the influence of polygenic risk scores for body mass index (BMI) or BMI and psychiatric disorders. Study Results High-, medium-, or low-risk controls gained on average 1.32%, 0.42%, and 0.36% more weight per month than patients switching from or within these risk categories (P < .001, P < .001, and P = .003, respectively). High-to-high or high-to-medium switches resulted in a greater weight increase than switching to lower-risk categories (+0.77% and + 0.39% respectively, P < .001). No difference was found between switching medium-to-medium and medium-to-low (P ≈ 1). Switching high-to-low resulted in 10% weight loss after 2 years, with the greatest loss occurring the first 6 months after the switch. Compared with high-risk controls, lower total cholesterol (−0.27 mmol/l, P = .043) in the high-to-low group, and lower glucose (−0.44 mmol/l, P = .032) and systolic blood pressure (−5.50 mmHg, P = .034) in the low-to-low group were found. Polygenic scores were not associated with weight changes in controls or after switching. Conclusion Psychotropic switches to a lower- or same-risk drug can attenuate weight gain, with only switching high to low resulting in weight loss.
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In April 2005, the US Food and Drug Administration (FDA) issued an advisory and subsequent black box warning regarding the risks of atypical anti psychotic use among elderly patients with dementia. The impact of these warnings on atypical drug use is unknown. We used quasi-experimental, interrupted time-series analyses to examine nationally representative data from IMS Health's National Disease and Therapeutic Index from January 2003 through December 2008. The primary measurement from this audit of office-based physicians was the use of an atypical antipsychotic agent. We quantified the impact of the advisory on atypical antipsychotic use among all individuals and those 65 years or older with dementia. From January 2003 to March 2005, mentions of total atypical antipsychotic drugs increased at an annual rate of 34%, and among patients with dementia, 16%. In the year prior to the FDA advisory, there were approximately 13.6 million atypical drug mentions, including 0.8 million among those with dementia. In the year following the advisory, atypical drug mentions fell 2% overall and 19% among those with dementia. In 2004, 19% (0.8 of 4.1 million) of drug mentions for dementia were for an atypical agent. By 2008, this proportion decreased to 9% (0.4 of 4.3 million). Atypical drug use slowed for both FDA-approved and off-label indications and declined through 2008 for all populations examined. The FDA advisory was associated with decreases in the use of atypical antipsychotics, especially among elderly patients with dementia.
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Introduction: Antipsychotic-induced weight-gain (AIWG) is a very important, yet often neglected side-effect in the treatment with first and second generation antipsychotics. AIWG can increase the risk of developing metabolic syndrome, diabetes and cardiovascular disease. Meta-analyses mostly concentrate on AIWG in schizophrenic and bipolar patients, even though antipsychotics are prescribed off-label across many other diagnostic groups (e.g. anxiety disorders, depression, autistic disorder). Areas covered: Pub Med and Web of Science were systematically searched for RCTs reporting on AIWG with a sample size of ≥ 100 published between 2014 and 2019. All diagnoses and ages were included. Expert opinion: Inclusion criteria were fulfilled by 27 RCTs. All antipsychotics led to significantly more weight-gain (p <.001) and most antipsychotics led to a significantly higher risk for a clinically relevant weight-gain of ≥7% compared to placebo (RR = 2.04). The results support previous findings that weight-gain occurs quickly. To efficaciously and efficiently tackle the problem of AIWG in clinical practice and trials, people at high risk need to be identified by predictive tools enabling the clinician to offer tailored adjunctive therapies (medication and/or lifestyle interventions). Most importantly, weight and metabolic monitoring ought to be consequently implemented in clinical routine in the treatment of any patient with any diagnosis when antipsychotics are prescribed.
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Atypical antipsychotics (AAPs) are the drug of choice in the management of mental illnesses by virtue of their advantage over typical antipsychotics i.e. least tendency of producing extrapyramidal motor symptoms (EPS) or pseudoparkinsonism. Despite the clinical efficacy, AAPs produces troublesome adverse effects, particularly hyperphagia, hyperglycemia, dyslipidemia weight gain, diabetes mellitus, insulin resistance and QT prolongation which further develops metabolic and cardiac complications with subsequent reduction in life expectancy, poor patient compliance, and sudden death. AAPs-induced weight gain and metabolic alterations are increasing at an alarming rate and became an utmost matter of concern for psychopharmacotherapy. Diverse underlying mechanisms have been explored such as the interaction of AAPs with neurotransmitter receptors, alteration in food reward anticipation behavior, altered expressions of hypothalamic orexigenic and anorexigenic neuropeptides, histamine H1 receptor-mediated hypothalamic AMP-activated protein kinase (AMPK) activation, increased blood leptin, ghrelin, pro-inflammatory cytokines. Antipsychotics induced imbalance in energy homeostasis, reduction in energy expenditure which is linked to altered expression of uncoupling proteins (UCP-1) in brown adipose tissue and reduced hypothalamic orexin expressions are emerging insights. In addition, alteration in gut-microbiota and subsequent inflammation, dyslipidemia, obesity, and diabetes after AAPs treatment are also associated with weight gain and metabolic alterations. Oral hypoglycemics and lipid-lowering drugs are mainly prescribed in the clinical management of weight gain associated with AAPs while many other pharmacological and nonpharmacological interventions also have been explored in different clinical and preclinical studies. In this review, we critically discuss the current scenario, mechanistic insights, biomarkers, and therapeutic alternatives for metabolic alterations associated with antipsychotics.
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Background: The introduction of second-generation antipsychotics (SGAs) over the past 2 decades generated considerable optimism that better antipsychotic treatments for schizophrenia and bipolar disorder were possible. SGAs offer several tolerability benefits over first-generation antipsychotics (FGAs), particularly with respect to extrapyramidal symptoms. However, SGAs can induce serious metabolic dysregulations, especially in drug-naive, first-episode, and child and adolescent populations, with olanzapine and clozapine having the highest propensity to cause these abnormalities. In this context, newer SGAs were developed to further improve the adverse effect burden of available agents. However, until now, the metabolic risk profile of the newly approved SGAs - asenapine, iloperidone, lurasidone and paliperidone (paliperidone extended release and paliperidone palmitate) - has not been compared. Objective: The objective of this systematic review and exploratory meta-analysis was to assess the effects of asenapine, iloperidone, lurasidone and paliperidone on body weight and other metabolic parameters (cholesterol, triglycerides and glucose), as this information is relevant to guide clinical decision making. Method: A systematic literature search (1966-March 2012), using the Cochrane Central Register of Controlled Trials and MEDLINE, CINAHL and EMBASE databases, was conducted for randomized, placebo-controlled and head-to-head clinical trials of asenapine, iloperidone, lurasidone and paliperidone. Published and unpublished data on changes in body weight and glucose and lipid metabolism parameters were extracted. For placebo-controlled, short-term (<= 2 weeks) and longer-term (>12 weeks) trials with available data on >= 7% weight increase compared with pre-treatment weight, or mean weight change with standard deviation, a formal meta-analysis was performed, estimating the pooled effect size (represented as relative risk [RR], numbers-needed-to-harm [NNH] and weighted mean difference [WMD]). An exploratory meta-analysis was also performed for the other metabolic variables (cholesterol, triglycerides and glucose). Data from active- and placebo-controlled studies were used for a pooled comparison of simple mean changes in weight, cholesterol, triglyceride and glucose levels. Results: Fifty-six trials (n = 21 691) in schizophrenia (N = 49, n = 19 299) or bipolar disorder (N = 7, n = 2392) were identified (asenapine: N = 9, iloperidone: N = 11, lurasidone: N = 8, paliperidone: N = 28). Most of the trials (64.3%) were of <= 12 weeks' duration. In the short-term trials, compared with placebo, a >= 7% weight increase was statistically significantly (p < 0.05) most prevalent for asenapine (5 trials, n = 1360, RR = 4.09, 95% confidence interval [CI] 2.25, 7.43, NNH = 17), followed by iloperidone (4 trials, n = 1931, RR = 3.13, 95% CI 2.08, 4.70, NNH = 11) and paliperidone (12 trials, n = 4087, RR = 2.17, 95% CI 1.64, 2.86, NNH = 20). The effect of lurasidone on body weight (6 trials, n = 1793, RR = 1.42, 95% CI 0.87, 2.29) was not statistically significant. Short-term weight gain was statistically significantly (p < 0.001) greater than placebo with iloperidone (I trial, n = 300, +2.50 kg, 95% CI 1.92, 3.08), paliperidone (15 trials, n = 3552, +1.24 kg, 95% CI 0.91, 1.57), asenapine (3 trials, n = 751, +1.16 kg, 95% CI 0.83, 1.49), as well as with lurasidone (5 trials, n = 999, +0.49 kg, 95% CI 0.17, 0.81, p < 0.01). Sufficient meta-analysable, longer-term, weight change data were only available for asenapine and paliperidone, showing statistically significantly (p < 0.001) greater weight gain versus placebo for both drugs (asenapine, 3 trials, n = 311, +1.30 kg, 95% CI 0.62, 1.98; paliperidone, 6 trials, n = 1174, +0.50 kg, 95% CI 0.22, 0.78). Although statistically significant, in general, no clinically meaningful differences were observed between the four newly approved SGAs and placebo regarding the mean change from baseline to endpoint in cholesterol levels in short-term trials, with the exception of iloperidone for total cholesterol (1 trial, n = 300, +11.60 mg/dL, 95% CI 4.98, 18.22, p 0.001), high-density cholesterol (1 trial, n = 300, +3.6 mg/dL, 95% CI 1.58, 5.62, p < 0.001) and low-density cholesterol (1 trial, n = 300, +10.30 mg/dL, 95% CI 4.94, 15.66, p < 0.001) and with the exception of lurasidone for high-density cholesterol (5 trials, n = 1004, +1.50 mg/dL, 95% CI 0.56, 2.44, p < 0.01). Asenapine increased total cholesterol statistically significantly (p < 0.05) during longer-term treatment (1 trial, n = 194, +6.53 mg/dL, 95% CI 1.17, 11.89). Regarding triglycerides, only short-term (3 trials, n = 1152, +1.78 mg/dL, 95% CI 0.40, 3.17, p < 0.01) and longer-term treatment with paliperidone (4 trials, n = 791, -0.20 mg/dL, 95% CI 0.40, -0.01, p < 0.05) had a statistically, but not clinically, significant effect. Statistically significant changes in glucose levels were noticed during short-term treatment with asenapine (2 trials, n = 379, -3.95 mg/dL, 95% CI -7.37, -0.53, p < 0.05) and iloperidone (1 trial, n = 300, +6.90 mg/dL, 95% CI 2.48, 11.32, p < 0.01), and during long-term treatment with paliperidone (6 trials, n = 1022, +3.39 mg/dL, 95% CI 0.42, 6.36, p < 0.05). Conclusion: While preliminary data suggest the lowest weight gain potential with lurasidone and potentially relevant short-term metabolic effects for asenapine and iloperidone, data are still too sparse to comprehensively evaluate the metabolic safety of the newly approved SGAs. Therefore, there is a clear need for further controlled studies to evaluate whether these agents are less problematic regarding treatment-emergent weight gain and metabolic disturbances than other currently available antipsychotics.
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Article
Antipsychotic medications can induce cardiovascular and metabolic abnormalities (such as obesity, hyperglycemia, dyslipidemia and the metabolic syndrome) that are associated with an increased risk of type 2 diabetes mellitus and cardiovascular disease. Controversy remains about the contribution of individual antipsychotic drugs to this increased risk and whether they cause sudden cardiac death through prolongation of the corrected QT interval. Although some drug receptor-binding affinities correlate with specific cardiovascular and metabolic abnormalities, the exact pharmacological mechanisms underlying these associations remain unclear. Antipsychotic agents with prominent metabolic adverse effects might cause abnormalities in glucose and lipid metabolism via both obesity-related and obesity-unrelated molecular mechanisms. Despite existing guidelines and recommendations, many antipsychotic-drug-treated patients are not assessed for even the most easily measurable metabolic and cardiac risk factors, such as obesity and blood pressure. Subsequently, concerns have been raised over the use of these medications, especially pronounced in vulnerable pediatric patients, among whom their use has increased markedly in the past decade and seems to have especially orexigenic effects. This Review outlines the metabolic and cardiovascular risks of various antipsychotic medications in adults and children, defines the disparities in health care and finally makes recommendations for screening and monitoring of patients taking these agents.
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Article
Weight gain is a common side effect of antipsychotic medications and is of particular concern with most of the newer "atypical" antipsychotics. It is, therefore, increasingly important to understand the impact of obesity and perceived weight problems on compliance with these medications. A survey of treatment and health issues was mailed to local chapters of the National Alliance for the Mentally Ill (NAMI) and National Mental Health Association (NMHA), who distributed them to people with schizophrenia. Noncompliance was defined as a self-report of missing any antipsychotic medication in the previous month. The primary independent variables were (1) body mass index (BMI; weight [kg]/height [m2])-categorized as normal (< 25, n = 73), overweight (25-30, n = 104), or obese (> 30, n = 100)-and (2) subjective distress over weight gain. Other independent variables included demographics, medication attitudes, and treatment satisfaction. BMI status and subjective distress from weight gain were predictors of noncompliance. Obese individuals were more than twice as likely as those with a normal BMI to report missing their medication (OR = 2.5; CI 1.1-5.5). A comprehensive model suggested that the primary mediator of noncompliance was distress over weight gain. There appears to be a significant, positive association between obesity and subjective distress from weight gain and medication noncompliance, even when accounting for other possible confounding factors.