Antipsychotic drugs and diabetes--an application of the Austin Bradford Hill criteria

Antipsychotic-Related Risks of Type 2 Diabetes Mellitus in Enrollees With Schizophrenia in the National Basic Public Health Service Program in Hunan Province, China

BACKGROUND

Antipsychotics contribute to the development of type 2 diabetes mellitus (T2DM) in individuals with schizophrenia. However, the extent of the relationship between antipsychotic use and T2DM varies in different settings, and the magnitude of the drug-specific effects fluctuates widely. This study aimed to explore the association of T2DM with antipsychotic use among enrollees with schizophrenia in China's National Basic Public Health Service Program (NBPHSP) and the drug-specific relationship with T2DM among patients receiving antipsychotic monotherapy.

METHODS

We recruited diabetes-free patients with schizophrenia who were enrolled in the NBPHSP of Hunan Province from October 2009 to December 2018. The participants were classified into the following three groups: regular antipsychotic use, intermittent antipsychotic use, and antipsychotic-free groups. The patients were followed up until they received a T2DM diagnosis or until April 2019. Cox regression models were constructed to calculate the overall and drug-specific hazard ratios (HRs) to determine the antipsychotic-T2DM relationship. Interactive and subgroup analyses were performed to assess the heterogeneity of the effects across subgroups.

RESULTS

A total of 122,064 NBPHSP enrollees with schizophrenia were followed up for 1,507,829 cumulative person-years, and 2,313 (1.89%) patients developed T2DM. Patients who regularly and intermittently used antipsychotics had 117% (HR: 2.17, 95% CI: 1.83-2.57) and 53% (HR: 1.53, 95% CI: 1.23-1.90) higher risks of developing T2DM than antipsychotic-free patients, respectively. Regarding monotherapy, the T2DM risk increased by 66, 80, 62, and 64% after the regular use of clozapine, risperidone, chlorpromazine, and perphenazine, respectively. In addition, the antipsychotic-related risk of T2DM decreased as the patient's baseline body mass index, and baseline fasting plasma glucose level, as well as the dietary proportion of animal products, increased.

CONCLUSION

Antipsychotics, especially clozapine, risperidone, chlorpromazine, and perphenazine, increased the T2DM risk among NBPHSP enrollees with schizophrenia. Mental health officers should accurately identify enrollees at a high risk of T2DM and take appropriate preventive measures to reduce the incidence of T2DM among patients with schizophrenia.

The increasing challenge of the possible impact of ethnicity on psychopharmacology

Ethnic differences may significantly influence the outcome of psychopharmacological treatment, in terms of prescription, adherence, clinical response, emergence of side effects, as well as pharmacokinetics and pharmacodynamics. The purpose of this review was to explore the available literature in order to provide general suggestions to help clinicians in choosing the best therapeutic option for patients, taking into account ethnicity. Although findings are sometimes controversial, the overall published studies suggest that ethnicities other than Caucasians tend to show a lower response to antidepressants and a reduced compliance. Africans tend to be more prescribed with antipsychotics, probably due to cultural stereotypes, except with clozapine, probably for their chronic benign neutropenia. Asians usually require less antipsychotic dosages than Caucasians. The differential response and side effect profile of antidepressants and antipsychotics have been related to individual intrinsic factors, to genetic make-up, but also to cultural and contextual variables. Interestingly, albeit limited data suggest ethnic-related genetic heterogeneity at the level of the serotonin transporters, the cytochromes and some neuroreceptors. Taken together, no conclusive findings are available about the role and impact of ethnicity in psychopharmacology. One of the main problems is that the majority of the studies in psychopharmacology have been conducted on Caucasians, so that there is an urgent need to have data in other populations. Furthermore, in the era of precision medicine, the role of ethnicity may be also supported by genetic analysis.

Identifying determinants of diabetes risk and outcomes for people with severe mental illness: a mixed-methods study

Background

People with severe mental illness experience poorer health outcomes than the general population. Diabetes contributes significantly to this health gap.

Objectives

The objectives were to identify the determinants of diabetes and to explore variation in diabetes outcomes for people with severe mental illness.

Design

Under a social inequalities framework, a concurrent mixed-methods design combined analysis of linked primary care records with qualitative interviews.

Setting

The quantitative study was carried out in general practices in England (2000–16). The qualitative study was a community study (undertaken in the North West and in Yorkshire and the Humber).

Participants

The quantitative study used the longitudinal health records of 32,781 people with severe mental illness (a subset of 3448 people had diabetes) and 9551 ‘controls’ (with diabetes but no severe mental illness), matched on age, sex and practice, from the Clinical Practice Research Datalink (GOLD version). The qualitative study participants comprised 39 adults with diabetes and severe mental illness, nine family members and 30 health-care staff.

Data sources

The Clinical Practice Research Datalink (GOLD) individual patient data were linked to Hospital Episode Statistics, Office for National Statistics mortality data and the Index of Multiple Deprivation.

Results

People with severe mental illness were more likely to have diabetes if they were taking atypical antipsychotics, were living in areas of social deprivation, or were of Asian or black ethnicity. A substantial minority developed diabetes prior to severe mental illness. Compared with people with diabetes alone, people with both severe mental illness and diabetes received more frequent physical checks, maintained tighter glycaemic and blood pressure control, and had fewer recorded physical comorbidities and elective admissions, on average. However, they had more emergency admissions (incidence rate ratio 1.14, 95% confidence interval 0.96 to 1.36) and a significantly higher risk of all-cause mortality than people with diabetes but no severe mental illness (hazard ratio 1.89, 95% confidence interval 1.59 to 2.26). These paradoxical results may be explained by other findings. For example, people with severe mental illness and diabetes were more likely to live in socially deprived areas, which is associated with reduced frequency of health checks, poorer health outcomes and higher mortality risk. In interviews, participants frequently described prioritising their mental illness over their diabetes (e.g. tolerating antipsychotic side effects, despite awareness of harmful impacts on diabetes control) and feeling overwhelmed by competing treatment demands from multiple morbidities. Both service users and practitioners acknowledged misattributing physical symptoms to poor mental health (‘diagnostic overshadowing’).

Limitations

Data may not be nationally representative for all relevant covariates, and the completeness of recording varied across practices.

Conclusions

People with severe mental illness and diabetes experience poorer health outcomes than, and deficiencies in some aspects of health care compared with, people with diabetes alone.

Future work

These findings can inform the development of targeted interventions aimed at addressing inequalities in this population.

Study registration

National Institute for Health Research (NIHR) Central Portfolio Management System (37024); and ClinicalTrials.gov NCT03534921.

Funding

This project was funded by the NIHR Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 9, No. 10. See the NIHR Journals Library website for further project information.

Association Between Antipsychotic Medication Use and Diabetes

PURPOSE OF REVIEW

The prevalence of diabetes is 2-3-fold higher in people with severe mental illness than the general population. There are concerns that antipsychotics increase the risk of diabetes. This review will examine the latest epidemiological studies linking antipsychotics and diabetes, as well as the mechanisms underlying the association and the clinical implications to minimise the impact of antipsychotics on metabolic health.

RECENT FINDINGS

Although there is an increased risk of diabetes in people with first-episode psychosis, the prevalence increases rapidly after antipsychotics are started. Antipsychotics likely increase the risk of diabetes through weight gain and directly by adversely affecting insulin sensitivity and secretion. It is important to implement measures to prevent diabetes, to screen for diabetes to ensure prompt diagnosis and to provide effective diabetes care. Further research is needed to understand how antipsychotics cause diabetes and to improve the clinical management of diabetes in people with severe mental illness.

Efficacy of Capsaicin for the Treatment of Cannabinoid Hyperemesis Syndrome: A Systematic Review

Objective: Cannabinoid hyperemesis syndrome (CHS) is characterized by cyclic vomiting, abdominal pain, and alleviation of symptoms via hot showers in chronic cannabinoid users. Capsaicin is recommended as a reasonable first-line treatment approach for CHS despite limited clinical evidence regarding its use. The objective of this study is to systematically review the efficacy data for capsaicin in CHS. Data Sources: A literature search using keywords related to cannabinoids, emesis, and capsaicin was performed in MEDLINE, CINAHL, and EMBASE from inception through March 31, 2019. Study Selection and Data Extraction: Studies and published abstracts in which capsaicin was used for CHS and clinical outcomes were reported were eligible for inclusion. Data Synthesis: A total of 241 articles were screened, of which 5 full-text articles and 6 conference abstracts were included. Full-text case reports (n = 3) and case series (n = 2) found capsaicin to be effective in a total of 18 patients. Published abstracts were in the form of case reports (n = 1), case series (n = 3), and retrospective cohort studies (n = 2). Relevance to Patient Care and Clinical Practice: Capsaicin use was described as beneficial in all case series and case reports; however, both retrospective cohort studies were unable to find a significant benefit for capsaicin on primary outcomes (emergency department length of stay). Conclusion: Current data for capsaicin efficacy in CHS is of low methodological quality. However, the limited data on alternative antiemetic therapies and capsaicin’s favorable risk-benefit profile make it a reasonable adjunctive treatment option.

The spurious relationship between ecstasy use and neurocognitive deficits: A Bradford Hill review

Numerous studies have suggested that MDMA can cause neurocognitive deficits. However, the available data can only suggest an association - rather than a causal relationship - between MDMA use and neurocognitive deficits. The reliability and robustness of this association was evaluated using Bradford Hill's criteria for determining causation in epidemiology research. Several limitations in the literature were found. Studies have recruited people who abuse ecstasy - an illicit drug that does not always contain MDMA. There is inherent risk in consuming impure or falsely identified substances; and using this as a source as for scientific opinion may introduce biases in our understanding the actuals risks associated with MDMA. Importantly, given that ecstasy research is predominately retrospective, baseline functioning cannot be established; which may be influenced by a variety of preexisting factors. Many studies introduce statistical errors by inconsistently dichotomizing and comparing light and heavy ecstasy users, making dose-response relationships inconclusive. When interpreting the ecstasy literature effect sizes are a more meaningful indicator of neurocognitive functioning rather than relying on p-values alone. Most meta-analyses have failed to find clinically relevant differences between ecstasy users and controls. There is also consistent evidence of publication bias in this field of research, which indicates that the literature is both biased and incomplete. Finally, suggestions for improving the ecstasy literature are provided.

Review: Severe mental illness, antipsychotic drugs and the metabolic syndrome

The prevalence of the metabolic syndrome is increased 2—3-fold among people with severe mental illness (SMI) and may explain the high risk of cardiovascular disease in this patient group. The reason for the increase in the metabolic syndrome in people with SMI is unclear but is likely to be multifactorial, including both hereditary and environmental factors. There are concerns that antipsychotic medication may be responsible for the increased prevalence of diabetes, the metabolic syndrome and cardiovascular disease in people with SMI. While the evidence linking the antipsychotics with diabetes remains inconclusive, certain antipsychotics, notably olanzapine and clozapine are associated with weight gain and hypertriglyceridaemia. At present there is little systematic monitoring of cardiovascular risk factors in people with SMI and consequently there is a high prevalence of undiagnosed metabolic problems. The burden of cardiovascular disease and diabetes could be reduced in people with SMI if lifestyle intervention was instituted and pharmacotherapy used when indicated. The adverse effects of antipsychotic medication should be balanced with the therapeutic benefits which may be important in ensuring that patients are able to make the necessary changes to reduce the burden of diabetes and cardiovascular disease.

A supervised adverse drug reaction signalling framework imitating Bradford Hill's causality considerations

Big longitudinal observational medical data potentially hold a wealth of information and have been recognised as potential sources for gaining new drug safety knowledge. Unfortunately there are many complexities and underlying issues when analysing longitudinal observational data. Due to these complexities, existing methods for large-scale detection of negative side effects using observational data all tend to have issues distinguishing between association and causality. New methods that can better discriminate causal and non-causal relationships need to be developed to fully utilise the data. In this paper we propose using a set of causality considerations developed by the epidemiologist Bradford Hill as a basis for engineering features that enable the application of supervised learning for the problem of detecting negative side effects. The Bradford Hill considerations look at various perspectives of a drug and outcome relationship to determine whether it shows causal traits. We taught a classifier to find patterns within these perspectives and it learned to discriminate between association and causality. The novelty of this research is the combination of supervised learning and Bradford Hill's causality considerations to automate the Bradford Hill's causality assessment. We evaluated the framework on a drug safety gold standard known as the observational medical outcomes partnership's non-specified association reference set. The methodology obtained excellent discrimination ability with area under the curves ranging between 0.792 and 0.940 (existing method optimal: 0.73) and a mean average precision of 0.640 (existing method optimal: 0.141). The proposed features can be calculated efficiently and be readily updated, making the framework suitable for big observational data.

Diabetes mellitus and severe mental illness: mechanisms and clinical implications

The prevalence of diabetes mellitus is twofold to threefold higher in people with severe mental illness (SMI) than in the general population, with diabetes mellitus affecting ∼12% of people receiving antipsychotics. The consequences of diabetes mellitus are more severe and frequent in people with SMI than in those without these conditions, with increased rates of microvascular and macrovascular complications, acute metabolic dysregulation and deaths related to diabetes mellitus. Multiple complex mechanisms underlie the association between diabetes mellitus and SMI; these mechanisms include genetic, environmental and disease-specific factors, and treatment-specific factors. Although antipsychotics are the mainstay of treatment in SMI, a causative link, albeit of uncertain magnitude, seems to exist between antipsychotics and diabetes mellitus. The principles of managing diabetes mellitus in people with SMI are similar to those for the general population and should follow currently established treatment algorithms. Lifestyle interventions are needed to reduce incident diabetes mellitus. In addition, improved uptake of opportunities to screen for this disease will reduce the high prevalence of undiagnosed diabetes mellitus. Currently, people with SMI receive poorer treatment for diabetes mellitus than the general population. Thus, health-care professionals in primary care, diabetes mellitus services and mental health teams have a responsibility to ensure that patients with SMI are not disadvantaged.

NIDDK international conference report on diabetes and depression: current understanding and future directions

Comorbid diabetes and depression are a major clinical challenge as the outcomes of each condition are worsened by the other. This article is based on the presentations and discussions during an international meeting on diabetes and depression convened by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) in collaboration with the National Institute of Mental Health and the Dialogue on Diabetes and Depression. While the psychological burden of diabetes may contribute to depression in some cases, this explanation does not sufficiently explain the relationship between these two conditions. Shared biological and behavioral mechanisms, such as hypothalamic-pituitary-adrenal axis activation, inflammation, autonomic dysfunction, sleep disturbance, inactive lifestyle, poor dietary habits, and environmental and cultural risk factors, are important to consider in understanding the link between depression and diabetes. Both individual psychological and pharmacological depression treatments are effective in people with diabetes, but the current range of treatment options is limited and has shown mixed effects on glycemic outcomes. More research is needed to understand what factors contribute to individual differences in vulnerability, treatment response, and resilience to depression and metabolic disorders across the life course and how best to provide care for people with comorbid diabetes and depression in different health care settings. Training programs are needed to create a cross-disciplinary workforce that can work in different models of care for comorbid conditions.

Course of weight gain and metabolic abnormalities in first treated episode of psychosis: the first year is a critical period for development of cardiovascular risk factors

Data on the long-term metabolic side-effects associated with antipsychotics are scarce. Prospective longitudinal studies in medication-naive patients with a first episode of psychosis are a valuable source of information as they provide an assessment prior to the antipsychotic exposure and minimize the effect of potential confounding factors. The aim of this study was to assess the course of weight gain and the incidence of metabolic abnormalities during the first 3 yr of antipsychotic treatment. Data were collected from a cohort of 170 first-episode psychosis patients. They were randomly assigned to haloperidol (32%); olanzapine (32%) and risperidone (36%). The dose used was flexible. The initial antipsychotic treatment was changed when required, based on clinical response and tolerability. The results showed that the mean weight gain at 3 yr was 12.1 kg (s.d. = 10.7). It appeared to increase rapidly during the first year (85% of the total mean weight gain) and then stabilized gradually over time. Total cholesterol, LDL-cholesterol and triglyceride levels followed a similar trajectory with a significant increase only during the first year. No significant changes were detected in the mean values of glycaemic parameters. Two patients with a family history of diabetes developed diabetes type II. At short-term the factors positively associated with weight gain were lower body mass index, male gender and olanzapine treatment. At long-term, functional status and clinical response were the main predictors. The results of our study indicate that the first year of antipsychotic treatment is a critical period for weight gain and metabolic changes. Identification of weight gain patterns may help to inform studies that aim to prevent or mitigate the metabolic adverse events associated with antipsychotic therapy.

Dopamine-mediated autocrine inhibitory circuit regulating human insulin secretion in vitro

We describe a negative feedback autocrine regulatory circuit for glucose-stimulated insulin secretion in purified human islets in vitro. Using chronoamperometry and in vitro glucose-stimulated insulin secretion measurements, evidence is provided that dopamine (DA), which is loaded into insulin-containing secretory granules by vesicular monoamine transporter type 2 in human β-cells, is released in response to glucose stimulation. DA then acts as a negative regulator of insulin secretion via its action on D2R, which are also expressed on β-cells. We found that antagonism of receptors participating in islet DA signaling generally drive increased glucose-stimulated insulin secretion. These in vitro observations may represent correlates of the in vivo metabolic changes associated with the use of atypical antipsychotics, such as increased adiposity.

Arriving at correct conclusions: the importance of association, causality, and clinical significance

Declaring that a causal and not solely a correlative relation exists between a risk factor and a disease creates significant implications for patients and physicians. No matter the forum, when investigators or clinicians make such a claim, it is essential to explain how this determination was made so that appropriate recommendations are made in all areas of our professional practice. When we review the medical literature it is similarly crucial to understand this distinction between causality and association. The Bradford Hill criteria of strength of association, consistency, temporality, biological gradient, biological plausibility, coherence, experimental evidence, and analogy can be used to help establish causality. It is also important to understand the distinction between clinical and statistical significance to complete our appraisal of the implications of a clinical study. Statistically significant results, although not the result of chance, may be clinically insignificant. Statistically insignificant results, conversely, may not exclude the possibility of a clinically important relation. This article reviews the concepts of causality and association and clinical versus statistical significance and provides examples from the literature.

Antipsychotic drugs and the risk of hyperglycemia in older adults without diabetes: a population-based observational study

OBJECTIVE

To determine whether current antipsychotic use among older persons without diabetes is associated with a higher risk of hospital visits for hyperglycemia, as previous studies in this population have yielded conflicting results.

DESIGN, SETTING AND PARTICIPANTS

A nested case-control study within a population-based cohort of persons aged 66 years or older without diabetes, who initiated antipsychotic therapy between April 1, 2002, and March 31, 2006. Cohort members were identified using health databases from Ontario, Canada, and were followed from treatment start until March 31, 2007.

MEASUREMENTS

Cases were patients with a hospital visit (emergency department visit or hospital admission) for hyperglycemia. We matched each case with up to 10 controls. We compared the risk of hyperglycemia among current antipsychotic users to that of remote users (discontinued > 180 days).

RESULTS

The cohort consisted of 44,121 subjects, mean age of 78.3 years, followed for a mean of 2.2 years. Compared to remote antipsychotic use, current treatment with any antipsychotic was associated with a significantly increased risk of hospital visits for hyperglycemia (adjusted odds ratio [aOR]: 1.52; 95% confidence interval [CI]: 1.07-2.17). The risk was elevated for both atypical (aOR: 1.44; 95% CI: 1.01-2.07) and typical (aOR: 2.86; 95% CI: 1.46-5.59) antipsychotic agents.

CONCLUSIONS

Current use of either atypical or typical antipsychotic agents was associated with a significantly increased risk of hospital visits for hyperglycemia among older persons without diabetes. These findings highlight the need for close glucose monitoring during antipsychotic therapy in older populations.

Physical health management in psychiatric settings

Severe mental disorders have a chronic course associated with a high risk for co-morbid somatic illnesses and premature mortality, but despite this increased risk, general health care needs in this population are often neglected. Over recent years, several groups have developed screening and monitoring guidelines for metabolic and cardiovascular risk assessment in patients treated with antipsychotics. The psychiatrist needs to be aware of the potential metabolic side-effects of antipsychotic medication and to include them in the risk/benefit assessment when choosing a specific antipsychotic. He should also be responsible for the implementation of the necessary screening assessments and referral for treatment of any physical illness. Multidisciplinary assessment of psychiatric and medical conditions is needed. The somatic treatments offered to people with severe and enduring mental illness should be at par with general health care in the non-psychiatrically ill population. In our University Centre, a structured and elaborate screening and monitoring protocol was introduced in late 2003. This paper describes the practical aspects of this monitoring protocol and the results obtained 4 years after its implementation.

Metformin for atypical antipsychotic-induced weight gain and glucose metabolism dysregulation: review of the literature and clinical suggestions

Individuals receiving certain atypical antipsychotic medications are at risk of gaining weight and developing metabolic problems. There are no established drug treatments to prevent or counter these problems. However, the antihyperglycaemic agent metformin appears promising in some recent studies and we review the literature that evaluates metformin for limiting or reversing atypical antipsychotic drug-induced weight gain and glucose metabolism dysregulation. These studies suggest that metformin is beneficial if started early in antipsychotic drug treatment. Metformin has also been shown to prevent or delay the onset of type 2 diabetes mellitus in high-risk individuals from the general population. Based on these findings, we identify antipsychotic drug-treated patients who might benefit from metformin therapy and offer clinical guidelines for its use. Further long-term studies are needed to extend our observations and improve this strategy.

Cardiovascular disease and diabetes in people with severe mental illness position statement from the European Psychiatric Association (EPA), supported by the European Association for the Study of Diabetes (EASD) and the European Society of Cardiology (ESC)

People with severe mental illnesses, such as schizophrenia, depression or bipolar disorder, have worse physical health and reduced life expectancy compared to the general population. The excess cardiovascular mortality associated with schizophrenia and bipolar disorder is attributed in part to an increased risk of the modifiable coronary heart disease risk factors; obesity, smoking, diabetes, hypertension and dyslipidaemia. Antipsychotic medication and possibly other psychotropic medication like antidepressants can induce weight gain or worsen other metabolic cardiovascular risk factors. Patients may have limited access to general healthcare with less opportunity for cardiovascular risk screening and prevention than would be expected in a non-psychiatric population. The European Psychiatric Association (EPA), supported by the European Association for the Study of Diabetes (EASD) and the European Society of Cardiology (ESC) published this statement with the aim of improving the care of patients suffering from severe mental illness. The intention is to initiate cooperation and shared care between the different healthcare professionals and to increase the awareness of psychiatrists and primary care physicians caring for patients with severe mental illness to screen and treat cardiovascular risk factors and diabetes.

Causal criteria and the problem of complex causation

Nancy Cartwright begins her recent book, Hunting Causes and Using Them, by noting that while a few years ago real causal claims were in dispute, nowadays "causality is back, and with a vengeance." In the case of the social sciences, Keith Morrison writes that "Social science asks 'why?'. Detecting causality or its corollary-prediction-is the jewel in the crown of social science research." With respect to the health sciences, Judea Pearl writes that the "research questions that motivate most studies in the health sciences are causal in nature." However, not all data used by people interested in making causal claims come from experiments that use random assignment to control and treatment groups. Indeed, much research in the social and health science depends on non-experimental, observational data. Thus, one of the most important problems in the social and health sciences concerns making warranted causal claims using non-experimental, observational data; viz., "Can observational data be used to make etiological inferences leading to warranted causal claims?" This paper examines one method of warranting causal claims that is especially widespread in epidemiology and the health sciences generally-the use of causal criteria. It is argued that cases of complex causation generally, and redundant causation-both causal overdetermination and causal preemption-specifically, undermine the use of such criteria to warrant causal claims.

The role of causal criteria in causal inferences: Bradford Hill's "aspects of association"

As noted by Wesley Salmon and many others, causal concepts are ubiquitous in every branch of theoretical science, in the practical disciplines and in everyday life. In the theoretical and practical sciences especially, people often base claims about causal relations on applications of statistical methods to data. However, the source and type of data place important constraints on the choice of statistical methods as well as on the warrant attributed to the causal claims based on the use of such methods. For example, much of the data used by people interested in making causal claims come from non-experimental, observational studies in which random allocations to treatment and control groups are not present. Thus, one of the most important problems in the social and health sciences concerns making justified causal inferences using non-experimental, observational data. In this paper, I examine one method of justifying such inferences that is especially widespread in epidemiology and the health sciences generally - the use of causal criteria. I argue that while the use of causal criteria is not appropriate for either deductive or inductive inferences, they do have an important role to play in inferences to the best explanation. As such, causal criteria, exemplified by what Bradford Hill referred to as "aspects of [statistical] associations", have an indispensible part to play in the goal of making justified causal claims.

Glucose and lipid disturbances after 1 year of antipsychotic treatment in a drug-naïve population

OBJECTIVE

This study examined the main metabolic side effects induced by antipsychotic treatment in a cohort of first episode drug-naïve subjects after the first year of treatment.

METHODS

A randomized, open-label, prospective clinical trial was conducted. Participants were 164 consecutive subjects included in a first episode program and never treated with antipsychotic medication. Patients were assigned to haloperidol, olanzapine or risperidone. The main outcome measures were changes at 1 year in fasting glucose parameters (glucose, insulin levels and insulin resistance index) and changes in fasting lipid parameters (total cholesterol, triglycerides, LDL cholesterol, HDL cholesterol).

RESULTS

144 of the total sample were evaluated at 1 year. There was a statistically significant increase in the mean values of insulin levels, insulin resistance index, total cholesterol, LDL-cholesterol and triglycerides. No pathological values in fasting glucose plasma levels were found at baseline and there were no changes after 1 year. Weight gain was positively correlated with changes in insulin levels, insulin resistance index and triglyceride levels. We did not detect statistically significant differences between treatments in any of the parameters evaluated.

CONCLUSIONS

Fasting glycaemia and insulin concentrations at baseline do not support the hypothesis that schizophrenia is associated with an underlying abnormality in glucose metabolism. The changes in insulin and lipid parameters at 1 year seem to be related to the magnitude of weight gain. There were no significant differences between haloperidol, olanzapine and risperidone concerning metabolic adverse effects after the first year of treatment.

Clinical monitoring and management of the metabolic syndrome in patients receiving atypical antipsychotic medications

Individuals with major mental illness are a high-risk group for cardio-metabolic derangements due to genetic predisposition, developmental and environmental stressors, and lifestyle. This risk is compounded when they receive antipsychotic medications. Guidelines for screening, monitoring, and managing these patients for metabolic problems have been in place for several years. Despite this, recent reports document that this population continues to receive poor care in this regard. In this article, we review the metabolic profile of atypical antipsychotic medications and offer guidelines to reduce the metabolic complications of these agents.

Metabolic syndrome in people with schizophrenia: a review

Metabolic syndrome and other cardiovascular risk factors are highly prevalent in people with schizophrenia. Patients are at risk for premature mortality and overall have limited access to physical health care. In part these cardio-metabolic risk factors are attributable to unhealthy lifestyle, including poor diet and sedentary behaviour. But over recent years it has become apparent that antipsychotic agents can have a negative impact on some of the modifiable risk factors. The psychiatrist needs to be aware of the potential metabolic side effects of antipsychotic medication and to include them in the risk/benefit assessment when choosing a specific antipsychotic. He should also be responsible for the implementation of the necessary screening assessments and referral for treatment of any physical illness. Multidisciplinary assessment of psychiatric and medical conditions is needed. The somatic treatments offered to people with severe and enduring mental illness should be at par with general health care in the non-psychiatrically ill population.

Antipsychotics for the treatment of schizophrenia: likelihood to be helped or harmed, understanding proximal and distal benefits and risks

Benefit-risk decisions are the central part of the philosophy of evidence-based medicine. Although number needed to treat (NNT) and number needed to harm (NNH) can quantify differences between two antipsychotics in terms of benefits and risks for the treatment of schizophrenia, these benefits and risks can take on greatly differing degrees of importance or relevance depending on the subjective point of view of the patient and clinician, baseline risks, severity of the underlying illness, as well as the time horizon when these effects emerge. The metric of likelihood to be helped or harmed, the ratio NNH to NNT, can be helpful in quantifying the benefit:risk ratio, provided that the outcomes are carefully matched in terms of both importance to the clinician and the patient and whether they are proximal or distal. The examples provided are extensions to the initially published NNT and NNH analyses conducted by the first author.

Antipsychotics and diabetes: an age-related association

BACKGROUND

Previous studies have reported an association between anti-psychotic medications and diabetes.

OBJECTIVE

To explore the association between antipsychotic medications and diabetes in patients of different ages.

METHODS

A retrospective analysis of a large health maintenance organization's drug claim database (3.7 million members) was performed. All patients treated with antipsychotic drugs during 1998-2004 were identified. Patients with diabetes were defined by a record of antidiabetic drug use during 2004. The prevalence of diabetes in different age groups treated with antipsychotics was compared with the prevalence of diabetes among enrollees in the same age groups not treated with antipsychotics.

RESULTS

Among 82,754 patients treated with antipsychotics, the association between diabetes and consumption of antipsychotics was strongest in the younger age groups and decreased with increasing age: for patients aged 0-24 years, OR 8.9 (95% CI 7.0 to 11.3); 25-44 years, OR 4.2 (95% CI 3.8 to 4.5); 45-54 years, OR 1.9 (95% CI 1.8 to 2.1); 55-64 years, OR 1.3 (95% CI 1.2 to 1.4); and 65 years or older, OR 0.93 (95% CI 0.9 to 1.0). However, the risk associated with atypical antipsychotics was lower than the risk associated with typical antipsychotics, with ORs ranging from 0.7 in patients 0-24 years old to 0.3 in those 65 years or older.

CONCLUSIONS

Antipsychotic drug use was associated with diabetes mellitus. This association was stronger in younger patients. In older adults, the difference was much smaller and, in some cases, there was no association. A lower risk was associated with atypical agents, as compared with typical antipsychotics. Clinicians should be aware that young adults treated with antipsychotics are at increased risk for diabetes.

A prospective study of glycaemic status in anti-psychotic-treated patients

Anti-psychotic drugs, particularly the second generation, or ;atypical' agents, have been implicated in the development of metabolic dysfunction such as diabetes mellitus. There is a paucity of longitudinal data on the natural history of glucose homeostasis in anti-psychotic-treated patients, and there are no universally accepted strategies for managing worsening glycaemic control in this population. Notwithstanding, several guidelines recommend switching to a ;lower risk' agent if patients develop worsening glycaemic control during anti-psychotic treatment. We prospectively followed a cohort of 106 anti-psychotic-treated patients from across the diagnostic spectrum, and investigated changes in glycaemic status. Between baseline and follow-up assessment (mean follow-up time, 599.3 [SD+/-235.4] days glycaemic status was unchanged in 78 (86.7%) patients; 5 (5.6%) reverted from impaired fasting glucose (IFG) to normoglycaemia in the absence of any pharmacological or lifestyle intervention and all were taking a ;high risk' drug (clozapine or olanzapine). These preliminary data suggest that progression to overt diabetes mellitus is not inevitable in patients who develop IFG during anti-psychotic treatment. Switching to another agent simply on the basis of the development of IFG may not offer any advantage, especially if the mental state is stable.

First- v. second-generation antipsychotics and risk for diabetes in schizophrenia: systematic review and meta-analysis

BACKGROUND

The increased prevalence of diabetes in schizophrenia is partly attributed to antipsychotic treatment, in particular second-generation antipsychotics, but the evidence has not been systematically reviewed.

AIMS

Systematic review and meta-analysis comparing diabetes risk for different antipsychotics in people with schizophrenia.

METHOD

We searched MEDLINE, PsycINFO, EMBASE, International Pharmaceutical Abstracts, CINAHL and Web of Knowledge until September 2006. Studies were eligible for inclusion if the design was cross-sectional, case-control, cohort or a controlled trial in individuals with schizophrenia or related psychotic disorders, where second-generation antipsychotics (defined as clozapine, olanzapine, risperidone and quetiapine) were compared with first-generation antipsychotics and diabetes was an outcome. Data were pooled using random effects inverse variance weighted meta-analysis.

RESULTS

Of the studies that met the inclusion criteria (n=14), 11 had sufficient data to include in the meta-analysis. Four of these were retrospective cohort studies. The relative risk of diabetes in patients with schizophrenia prescribed one of the second-generation v. first-generation antipsychotics was 1.32 (95% CI 1.15-1.51). There were insufficient data to include aripiprazole, ziprasidone and amisulpride in this analysis.

CONCLUSIONS

There is tentative evidence that the second-generation antipsychotics included in this study are associated with a small increased risk for diabetes compared with first-generation antipsychotics in people with schizophrenia. Methodological limitations were found in most studies, leading to heterogeneity and difficulty interpreting data. Regardless of type of antipsychotic, screening for diabetes in all people with schizophrenia should be routine.

Typical and atypical antipsychotics differentially affect long-term incidence rates of the metabolic syndrome in first-episode patients with schizophrenia: a retrospective chart review

The presence of the metabolic syndrome (MetS) is an important risk factor for cardiovascular disease and diabetes. There are limited data on the prevalence of MetS in patients with schizophrenia at the onset of the disorder and specifically no data on patients treated in the era when only first-generation antipsychotics were available.

METHODS

Data from a historic cohort of consecutively admitted first-episode patients with schizophrenia treated with first-generation antipsychotics (FGAs) were compared with an age and sex matched series of consecutive first-episode patients treated only with second-generation antipsychotics (SGAs). Rates of MetS were compared at baseline and after on average 3 years of treatment exposure.

RESULTS

At first episode there was no difference in the prevalence of MetS between the historic and the current cohort. Rates of MetS increased over time in both groups, but patients started on SGAs had a three times higher incidence rate of MetS (Odds Ratio 3.6, CI 1.7-7.5). The average increase in weight and body mass index was twice as high in patients started on SGA. The difference between the FGA and SGA group was no longer significant when patients started on clozapine and olanzapine were excluded.

CONCLUSION

Rates of MetS at the first episode of schizophrenia today are not different from those of patients 15 to 20 years ago. This finding counters the notion that the high rates of metabolic abnormalities in patients with schizophrenia currently reported are mainly due to lifestyle changes over time in the general population. Some SGAs have a significantly more negative impact on the incidence of MetS compared to FGAs in first-episode patients.

Abnormal glucose metabolism in patients treated with antipsychotics

Second-generation (atypical) antipsychotic medications are of great benefit to a wide variety of people with psychiatric disorders, especially patients with schizophrenia. However, one constellation of adverse effects is an increased risk of obesity, diabetes, and metabolic syndrome. Increasing numbers of reports concerning impaired glucose tolerance, diabetes, and ketoacidosis have raised concerns about a possible association between abnormal glucose metabolism and treatment with atypical antipsychotics, although the question is still debated because of the presence of many confounding factors. A close relationship between drug-induced weight gain and risk of diabetes has been reported, emphasizing the role of insulin resistance. However, some cases of diabetes developed independently of weight gain, rather rapidly and possibly progressing to ketoacidosis, thus arguing for a severe impairment of insulin secretion. Another debated question is whether diabetes risk is a class action or a differential action. Although not fully scientifically proven yet, available evidence suggests that clozapine and olanzapine have a higher propensity to induce diabetes and metabolic syndrome compared with other atypical antipsychotic drugs, risperidone and quetiapine. Despite more limited available data, amisulpride, aripiprazole and ziprazidone showed less likelihood of precipitating diabetes. Interestingly, reversibility of drug-related diabetes has been reported with aripiprazole. The choice of atypical antipsychotic medication for a specific patient depends on many factors, but the likelihood of developing diabetes should become an important consideration. When prescribing an atypical antipsychotic, a commitment to careful baseline screening and follow-up monitoring is essential in order to mitigate the risk of developing diabetes and associated complications.