Clustering of physical health multimorbidity in people with severe mental illness: An accumulated prevalence analysis of United Kingdom primary care data.

BACKGROUND: People with severe mental illness (SMI) have higher rates of a range of physical health conditions, yet little is known regarding the clustering of physical health conditions in this population. We aimed to investigate the prevalence and clustering of chronic physical health conditions in people with SMI, compared to people without SMI. METHODS AND FINDINGS: We performed a cohort-nested accumulated prevalence study, using primary care data from the Clinical Practice Research Datalink (CPRD), which holds details of 39 million patients in the United Kingdom. We identified 68,783 adults with a primary care diagnosis of SMI (schizophrenia, bipolar disorder, or other psychoses) from 2000 to 2018, matched up to 1:4 to 274,684 patients without an SMI diagnosis, on age, sex, primary care practice, and year of registration at the practice. Patients had a median of 28.85 (IQR: 19.10 to 41.37) years of primary care observations. Patients with SMI had higher prevalence of smoking (27.65% versus 46.08%), obesity (24.91% versus 38.09%), alcohol misuse (3.66% versus 13.47%), and drug misuse (2.08% versus 12.84%) than comparators. We defined 24 physical health conditions derived from the Elixhauser and Charlson comorbidity indices and used logistic regression to investigate individual conditions and multimorbidity. We controlled for age, sex, region, and ethnicity and then additionally for health risk factors: smoking status, alcohol misuse, drug misuse, and body mass index (BMI). We defined multimorbidity clusters using multiple correspondence analysis (MCA) and K-means cluster analysis and described them based on the observed/expected ratio. Patients with SMI had higher odds of 19 of 24 conditions and a higher prevalence of multimorbidity (odds ratio (OR): 1.84; 95% confidence interval [CI]: 1.80 to 1.88, p < 0.001) compared to those without SMI, particularly in younger age groups (males aged 30 to 39: OR: 2.49; 95% CI: 2.27 to 2.73; p < 0.001; females aged 18 to 30: OR: 2.69; 95% CI: 2.36 to 3.07; p < 0.001). Adjusting for health risk factors reduced the OR of all conditions. We identified 7 multimorbidity clusters in those with SMI and 7 in those without SMI. A total of 4 clusters were common to those with and without SMI; while 1, heart disease, appeared as one cluster in those with SMI and 3 distinct clusters in comparators; and 2 small clusters were unique to the SMI cohort. Limitations to this study include missing data, which may have led to residual confounding, and an inability to investigate the temporal associations between SMI and physical health conditions. CONCLUSIONS: In this study, we observed that physical health conditions cluster similarly in people with and without SMI, although patients with SMI had higher burden of multimorbidity, particularly in younger age groups. While interventions aimed at the general population may also be appropriate for those with SMI, there is a need for interventions aimed at better management of younger-age multimorbidity, and preventative measures focusing on diseases of younger age, and reduction of health risk factors.

Associations of antidepressants and antipsychotics with lipid parameters: Do CYP2C19/CYP2D6 genes play a role? A UK population-based study.

BACKGROUND: Dyslipidaemia is an important cardiovascular risk factor for people with severe mental illness, contributing to premature mortality. The link between antipsychotics and dyslipidaemia is well established, while evidence on antidepressants is mixed. AIMS: To investigate if antidepressant/antipsychotic use was associated with lipid parameters in UK Biobank participants and if CYP2C19 and CYP2D6 genetic variation plays a role. METHODS: Review of self-reported prescription medications identified participants taking antidepressants/antipsychotics. Total, low-, and high-density lipoprotein cholesterol (L/HDL-C) and triglycerides derived from blood samples. CYP2C19 and CYP2D6 metabolic phenotypes were assigned from genetic data. Linear regression investigated aims, adjusted for key covariates. RESULTS: Of 469,739 participants, 36,043 took antidepressants (53% female, median age 58, 17% taking cholesterol-lowering medications) and 3255 took antipsychotics (58% female, median age 57, 27% taking cholesterol-lowering medications). Significant associations were found between use of each amitriptyline, fluoxetine, citalopram/escitalopram, sertraline, paroxetine and venlafaxine with higher total cholesterol, LDL-C, and triglycerides and lower HDL-C, compared to participants not taking each medication. Venlafaxine was associated with the worst lipid profile (total cholesterol, adjusted mean difference: 0.21 mmol/L, 95% confidence interval (CI): 0.17 to 0.26, p < 0.001). Antipsychotic use was significantly associated with lower HDL-C and higher triglycerides. In participants taking sertraline, CYP2C19 intermediate metabolisers had higher HDL-C (0.05 mmol/L, 95% CI: 0.01 to 0.09, p = 0.007) and lower triglycerides (-0.17 mmol/L, 95% CI: -0.29 to -0.05, p = 0.007), compared to normal metabolisers. CONCLUSIONS: Antidepressants were significantly associated with adverse lipid profiles, potentially warranting baseline and regular monitoring. Further research should investigate the mechanistic pathways underlying the protective effects of the CYP2C19 intermediate metaboliser phenotype on HDL-C and triglycerides in people taking sertraline.

Breast cancer risks following antipsychotic use in women with bipolar disorder versus schizophrenia: A territory-wide nested case-control study spanning two decades.

Accrued epidemiologic data largely support an association of antipsychotic use with breast cancer in women with schizophrenia. No studies have specifically investigated such risks in women with bipolar disorder. This study aims to examine the association between antipsychotics and breast cancer in women with bipolar disorder and compare it against schizophrenia. We conducted a nested case-control study using a territory-wide public healthcare database in Hong Kong examining women aged ≥18 years with bipolar disorder or schizophrenia. Using incidence density sampling, women with a breast cancer diagnosis were matched by up to 10 control participants. In total, 672 case participants (109 with bipolar disorder) and 6,450 control participants (931 with bipolar disorder) were included. Results show a significant association of first-generation antipsychotics with breast cancer in both women with schizophrenia [adjusted odds ratio (aOR) 1.49, 95% confidence interval (CI) 1.17-1.90] or bipolar disorder (aOR 1.80, 95% CI 1.11-2.93). Second-generation antipsychotics was associated with breast cancer only in women with bipolar disorder (aOR 2.49, 95% CI 1.29-4.79), with no significant association found in women with schizophrenia (aOR 1.10, 95% CI 0.88-1.36). In conclusion, further research on breast cancer risks is warranted for women with bipolar disorder on antipsychotics.

Association between quetiapine use and self-harm outcomes among people with recorded personality disorder in UK primary care: A self-controlled case series analysis.

BACKGROUND: Quetiapine is frequently prescribed to people with personality disorder diagnoses, but this is not supported by evidence or treatment guidelines. AIMS: To examine associations between periods of quetiapine prescribing and self-harm events in people with personality disorder. METHOD: Self-controlled case series using linked primary care and hospital records covering the period 2007-2017. We calculated incidence rates and incidence rate ratios (IRRs) for self-harm events during periods when people were prescribed (exposed to) quetiapine, as well as periods when they were unexposed or pre-exposed to quetiapine. RESULTS: We analysed data from 1,082 individuals with established personality disorder diagnoses, all of whom had at least one period of quetiapine prescribing and at least one self-harm episode. Their baseline rate of self-harm (greater than 12 months before quetiapine treatment) was 0.52 episodes per year. Self-harm rates were elevated compared to the baseline rate in the month after quetiapine treatment was commenced (IRR 1.85; 95% confidence interval (CI) 1.46-2.34) and remained raised throughout the year after quetiapine treatment was started. However, self-harm rates were highest in the month prior to quetiapine initiation (IRR 3.59; 95% CI 2.83-4.55) and were elevated from 4 months before quetiapine initiation, compared to baseline. CONCLUSION: Self-harm rates were elevated throughout the first year of quetiapine prescribing, compared to the baseline rate. However, rates of self-harm reduced in the month after patients commenced quetiapine, compared to the month before quetiapine was initiated. Self-harm rates gradually dropped over a year of quetiapine treatment. Quetiapine may acutely reduce self-harm. Longer-term use and any potential benefits need to be balanced with the risk of adverse events.

Psychiatric hospitalization following antipsychotic medication cessation in first episode psychosis.

BACKGROUND: There are questions about the risk-benefit balance of longer-term antipsychotic medication treatment following first episode psychosis, especially in relation to relapse because of dopamine supersensitivity following treatment cessation. AIM: The purpose of this study was to determine whether hospitalization rates in first episode psychosis patients are associated with length of initial oral antipsychotic medication exposure. METHODS: We examined psychiatric hospitalization rates in patients experiencing first episode of psychosis from the total population of Sweden between 1 January 2007-31 December 2016 ( n=7043). We categorised patients by the length of first antipsychotic treatment (<6 months, 6 months to <1 year, 1 year to <2 years, 2 years to <5 years and ⩾5 years). RESULTS: Compared to those treated for <6 months, individuals receiving oral antipsychotic medications for ⩾5 years had less than half the cumulative incidence of hospitalization at all times between 1-4 years after treatment cessation. CONCLUSION: We found no evidence that hospitalization rates increased with increasing baseline antipsychotic exposure.

Weight change over two years in people prescribed olanzapine, quetiapine and risperidone in UK primary care: Cohort study in THIN, a UK primary care database.

BACKGROUND: Follow-up studies of weight gain related to antipsychotic treatment beyond a year are limited in number. We compared weight change in the three most commonly prescribed antipsychotics in a representative UK General Practice database. METHOD: We conducted a cohort study in United Kingdom primary care records of people newly prescribed olanzapine, quetiapine or risperidone. The primary outcome was weight in each six month period for two years after treatment initiation. Weight changes were compared using linear regression, adjusted for age, baseline weight and diagnosis. RESULTS: N = 6338 people received olanzapine, 12,984 quetiapine and 6556 risperidone. Baseline weight was lowest for men treated with olanzapine (80.8 kg versus 83.5 kg quetiapine, 82.0 kg risperidone) and women treated with olanzapine (67.7 kg versus 71.5 kg quetiapine 68.4 kg risperidone. Weight gain occurred during treatment with all three drugs. Compared with risperidone mean weight gain was higher with olanzapine (adjusted co-efficient +1.24 kg (95% confidence interval: 0.69-1.79 kg per six months) for men and +0.77 kg (95% confidence interval: 0.29-1.24 kg) for women). Weight gain with quetiapine was lower in unadjusted models compared with risperidone, but this difference was not significant after adjustment. CONCLUSION: Olanzapine is more commonly prescribed to people with lower weight. However, after accounting for baseline weight, age, sex and diagnosis, olanzapine is still associated with greater weight gain over two years than risperidone or quetiapine. Baseline weight does not ameliorate the risks of weight gain associated with antipsychotic medication. Weight gain should be assertively discussed and managed for people prescribed antipsychotics, especially olanzapine.

Severe mental illness and chronic kidney disease: a cross-sectional study in the United Kingdom.

OBJECTIVE: We investigated the burden of chronic kidney disease (CKD) among patients with severe mental illness (SMI). METHODS: We identified patients with SMI among all those aged 25-74 registered in the UK Clinical Practice Research Datalink as on March 31, 2014. We compared the prevalence of CKD (two measurements of estimated glomerular filtration rate <60 mL/min/1.73 m2 for ≥3 months) and renal replacement therapy between patients with and without SMI. For patients with and without a history of lithium prescription separately, we used logistic regression to examine the association between SMI and CKD, adjusting for demographics, lifestyle characteristics, and known CKD risk factors. RESULTS: The CKD prevalence was 14.6% among patients with SMI and a history of lithium prescription (n = 4,295), 3.3% among patients with SMI and no history of lithium prescription (n = 24,101), and 2.1% among patients without SMI (n = 2,387,988; P < 0.001). The prevalence of renal replacement therapy was 0.23%, 0.15%, and 0.11%, respectively (P = 0.012). Compared to patients without SMI, the fully adjusted odds ratio for CKD was 6.49 (95% CI 5.84-7.21) for patients with SMI and a history of lithium prescription and 1.45 (95% CI 1.34-1.58) for patients with SMI and no history of lithium prescription. The higher prevalence of CKD in patients with SMI may, in part, be explained by more frequent blood testing as compared to the general population. CONCLUSION: CKD is identified more commonly among patients with SMI than in the general population.