Background Type 2 diabetes is associated with cognitive dysfunction and increases the risk of dementia in the elderly. The aim of this study was to explore, by means of magnetic resonance (MR) imaging, possible relationships among clinical profiles of diabetes, cognitive function, white matter hyperintensities (WMHs) and subcortical brain atrophy.

OBJECTIVE—The metabolic syndrome (MetS) is believed to be associated with an increased risk of cardiovascular disease (CVD). Although its prevalence is extremely high among diabetic patients, its prevalence in those with no history of CVD has not been determined. Moreover, prospective studies published on the association between MetS and cardiovascular events in diabetic populations have used only the World Health Organization (WHO) definition of MetS and included only white European subjects. The aim of this study was to determine the prevalence of MetS, as defined by both the WHO and the National Cholesterol Education Program (NCEP), and its predictive value for CVD in Asian diabetic patients in a long-term, prospective setting. RESEARCH DESIGN AND METHODS—The baseline characteristics and incidence/hazard ratio of cardiovascular events (coronary heart disease and stroke) were determined in 1,424 Japanese type 2 diabetic patients with and without MetS, as defined by WHO (WHO-MetS) or the NCEP. RESULTS—A high prevalence (38–53%, depending on sex and definition) of MetS was found among diabetic patients, even those with no history of CVD. During the 8-year study period, only WHO-MetS was a predictor for CVD in female patients. In male patients, although both definitions of MetS were significant predictors for CVD, individual components of MetS, such as hyperlipidemia or hypertension, were equivalent or better predictors. CONCLUSIONS—We found that MetS is relatively common in diabetic patients with no history of CVD. We suggest that the commonly used definitions of MetS, at least in their present forms, have limited clinical usefulness for Asian diabetic patients and may need some ethnic group−specific modifications for global use.

We suggest that the results of meta-regression analyses would not be as robust as those of regression analyses using IPD in examining potential modifiers of treatment effects. To investigate whether patient characteristics are related to treatment effects, we suggest that interaction tests and sensitivity analyses using IPD should be employed whenever possible.

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We developed a method to assess the similarity of pharmacokinetic data between ethnically different populations. An evaluation of confidence intervals for the mean difference in pharmacokinetic parameters, such as area under the concentration-versus-time curve (AUC), between populations is often used. We propose the use of the overlap coefficient (OC), which represents the proportion of overlap between two probability distributions, as a measure of the similarity between distributions. We considered five OC estimators--two parametric ones and three nonparametric ones. Simulation studies were conducted to compare the performance of the five OC estimators and their bootstrap confidence intervals. Results showed that nonparametric estimators with fixed-bandwidth kernel density estimation had a smaller mean squared error in almost all situations, and their coverage probabilities were close to the nominal level. The proposed method was applied to pharmacokinetic data from a bridging study of a combination therapy for metastatic colorectal cancer patients in the USA and Japan. From the analyses of this study, it was suggested that the distributions of the logarithmically transformed AUC for leucovorin and 5-fluorouracil were similar between the two populations.