Occurrence of metabolic diseases associated with antipsychotic use among Korean patients with schizophrenia.

OBJECTIVE: Metabolic side effects of antipsychotics significantly affect adherence to medication. We aimed to identify factors associated with the occurrence of metabolic diseases among Korean patients with schizophrenia (SCZ) from the national health insurance system database. We evaluated the frequency of antidiabetic and antihyperlipidemic use after diagnosis of SCZ according to typical or atypical antipsychotic use. MATERIALS AND METHODS: Among the 43,800 patients diagnosed with SCZ between 2008 and 2012, 29,591 patients who had no metabolic diseases before the diagnosis were included in the analysis to investigate the occurrence of metabolic diseases associated with antipsychotic use. The associations between the development of metabolic diseases and patient characteristics were evaluated using logistic regression analysis. RESULTS: Use of both typical and atypical antipsychotics (multivariate-adjusted odds ratio (OR), 1.2513; 95% confidence interval (CI), 1.0953 - 1.4294) was associated with higher incidence of metabolic diseases than without their use. Among the atypical antipsychotics, use of clozapine (multivariate-adjusted OR, 1.1959; 95% CI, 1.0086 - 1.4179) and quetiapine (multivariate-adjusted OR, 1.1284; 95% CI, 1.0446 - 1.2189) showed higher incidence of metabolic diseases compared to that without their use. Among the patients using ≥ 1 type of antidiabetic or antihyperlipidemic agents within 6 years after diagnosis of SCZ, the proportion of patients using only atypical antipsychotics was greater than those using only typical antipsychotics. CONCLUSION: The use of both typical and atypical antipsychotics, and clozapine and quetiapine treatment, may be associated with the occurrence of metabolic diseases in patients with SCZ. Additional prospective studies with accurate dosage information are needed to validate our findings.

On the finite sample distribution of the likelihood ratio statistic for testing heterogeneity in meta-analysis.

In meta-analysis, hypothesis testing is one of the commonly used approaches for assessing whether heterogeneity exists in effects between studies. The literature concluded that the Q-statistic is clearly the best choice and criticized the performance of the likelihood ratio test in terms of the type I error control and power. However, all the criticism for the likelihood ratio test is based on the use of a mixture of two chi-square distributions with 0 and 1 degrees of freedom, which is justified only asymptotically. In this study, we develop a novel method to derive the finite sample distribution of the likelihood ratio test and restricted likelihood ratio test statistics for testing the zero variance component in the random effects model for meta-analysis. We also extend this result to the heterogeneity test when metaregression is applied. A numerical study shows that the proposed statistics have superior performance to the Q-statistic, especially when the number of studies collected for meta-analysis is small to moderate.