BAHAMA: A Bayesian Hierarchical Model for the Detection of MedDRA®-Coded Adverse Events in Randomized Controlled Trials.

INTRODUCTION: Patients participating in randomized controlled trials (RCTs) are susceptible to a wide range of different adverse events (AE) during the RCT. MedDRA® is a hierarchical standardization terminology to structure the AEs reported in an RCT. The lowest level in the MedDRA hierarchy is a single medical event, and every higher level is the aggregation of the lower levels. METHOD: We propose a multi-stage Bayesian hierarchical Poisson model for estimating MedDRA-coded AE rate ratios (RRs). To deal with rare AEs, we introduce data aggregation at a higher level within the MedDRA structure and based on thresholds on incidence and MedDRA structure. RESULTS: With simulations, we showed the effects of this data aggregation process and the method's performance. Furthermore, an application to a real example is provided and compared with other methods. CONCLUSION: We showed the benefit of using the full MedDRA structure and using aggregated data. The proposed model, as well as the pre-processing, is implemented in an R-package: BAHAMA.

Association of hemoglobin A1C with circulating metabolites in Dutch with European, African Surinamese and Ghanaian background.

BACKGROUND: The prevalence of type 2 diabetes mellitus (T2DM) varies significantly across ethnic groups. A better understanding of the mechanisms underlying the variation in different ethnic groups may help to elucidate the pathophysiology of T2DM. The present work aims to generate a hypothesis regarding "why do subjects with African background have excess burden of T2DM?". METHODS: In the current study, we performed metabolite profiling of plasma samples derived from 773 subjects of three ethnic groups (Dutch with European, Ghanaian and African Surinamese background). We performed Bayesian lognormal regression analyses to assess associations between HbA1c and circulating metabolites. RESULTS: Here we show that subjects with African Surinamese and Ghanaian background had similar associations of HbA1c with circulating amino acids and triglyceride-rich lipoproteins as subjects with European background. In contrast, subjects with Ghanaian and African Surinamese background had different associations of HbA1c with acetoacetate, small LDL particle and small HDL particle concentrations, compared to the subjects with European background. CONCLUSIONS: On the basis of the observations, we hypothesize that the excess burden of T2DM in subjects with African background may be due to impaired cholesterol efflux capacity or abnormal cholesterol uptake.

Genetic factors are relevant and independent determinants of antihypertensive drug effects in a multiracial population.

BACKGROUND: The success of antihypertensive drugs may be improved by better prediction of their efficacy in individual patients. The objective of our study was to determine whether genetic variation predicts the individual systolic blood pressure (SBP) response to antihypertensive drugs and to assess to what extent the individual treatment response could be explained by the combined effects of known demographic, environmental, and genetic factors. METHODS: A population-based, crossover, open-label randomized treatment study stratified for ethnicity in 102 mildly hypertensive patients aged 35-60 years in an outpatient hypertension clinic (the ROTATE study). Patients underwent five successive 6-week treatment episodes of single-drug treatment in a randomized order with representatives of the major antihypertensive drug classes. The primary outcome measure was the DeltaSBP after 6-week drug therapy. RESULTS: Participants (n = 97) completed 407 treatment episodes. The estimated unpredictable natural variation of SBP within individuals was 65% of the total study variance. The primary analysis model that considered the effects of environmental, demographic, and genetic factors and their interactions to SBP response to antihypertensive drugs, explained 23% of the total variance accounting for 66% of the predictable variance. Ethnicity, low sodium intake, and ADD1 614G-->T polymorphism were the only drug-related predictors. A number of genetic variants (ADD1 614G-->T, ADRB1 145A-->G, ADRB2 79C-->G, CYP11B2 -344C-->T, and SLC12A3 78G-->A) contributed significantly (9%) to the total variance of the SBP response. The contribution of each individual single-nucleotide polymorphism (SNP) ranged from 1.1 to 2.4%. CONCLUSIONS: Genetic factors are relevant and independent determinants of antihypertensive drug effects in a multiracial population.