Biomedical subjects

Robert J Straka

Publications and source records attributed to Robert J Straka.

5 recordsLinked to original sources

PubMed2006

Mixture models and subpopulation classification: a pharmacokinetic simulation study and application to metoprolol CYP2D6 phenotype.

Mixture models are applied in population pharmacometrics to characterize underlying population distributions that are not adequately approximated by a single normal or lognormal distribution. In addition to obtaining individualized maximum a posteriori Bayesian post hoc parameter estimates, the subpopulation to which an individual was classified can be determined. However, the accuracy of the classification of subjects to subpopulations is not well studied. We investigated the impact of several factors on the accuracy of classification in mixture models applied to pharmacokinetics using a simulation strategy. The availability of actual subject data allowed us to evaluate mixture model classification in a potentially common application, namely, the classification of clearance into poor metabolizer (PM) or extensive metabolizer (EM) subgroups with the known phenotype status in subjects receiving metoprolol. The factors explored in the simulation study were the magnitude of difference between the clearances in two subpopulations, the between subject variability in clearance, the mixing-fraction, and the population sample size. Populations were simulated at various levels of the above factors and analyzed with a mixture model using NONMEM. The population pharmacokinetics of metoprolol were modeled with the EM/PM phenotype as a known covariate, and without the phenotype covariate using a mixture model. Within the range of scenarios studied, the proportion of subjects classified into the correct subpopulation was high. The simulation-estimation study suggests that a greater separation between two subpopulations, a smaller variability in the parameter distribution, a larger sample size, and a smaller size subpopulation tend to be associated with a greater accuracy of subpopulation classification when a mixture model is applied to pharmacokinetic data. In a population pharmacokinetic analysis of metoprolol, a drug that undergoes polymorphic metabolism, it was possible to correctly identify phenotype status using a mixture model.

Administration, Oral↗

PubMed2006

Verified predominance of slow acetylator phenotype N-acetyltransferase 2 (NAT2) in a Hmong population residing in Minnesota.

Southeast Asians known as the Hmong have a high prevalence of tuberculosis and select cancers. The slow acetylation (SA) phenotype for N-acetyltransferase 2 (NAT2) has been associated with toxicity from the anti-tuberculosis drug, isoniazid and in increased risk of select cancers. Previous research indicates a 74.5% prevalence of SA in Hmong which differs from other Asian populations including the Japanese and Thai (range: 7%-45%). Given this contrast, the purpose of this study was to confirm or refute this unexpected predominance of the SA phenotype in Hmong. Unrelated, Minnesota Hmong between 18 and 65 years of age consented and participated by ingesting caffeine as the probe for NAT2. A urinary caffeine metabolic ratio AFMU/1X (<0.6) was used to classify subjects as slow acetylators. Among 51 analysable samples provided by 61 enrollees (27 male, 33 female, 1 sex unknown, age 30+/-11 years [mean+/-SD]) there were 47 (92.2%) slow and 4 (7.8%) rapid acetylators. The prevalence of the SA phenotype (92.2%) from this study exceeds the 74.5% (p<0.02 by chi-square test) previously noted in Minnesota Hmong (n=98). The predominance of the SA phenotype within Minnesota Hmong is confirmed. Further studies evaluating this unexpected prevalence, its genetic basis and potential clinical relevance to drug toxicity and disease are warranted.

Acetylation↗

PubMed2006

Discordance between N-acetyltransferase 2 phenotype and genotype in a population of Hmong subjects.

Polymorphisms of N-acetyltransferase 2 (NAT2) acetylation may influence drug toxicities and efficacy and are associated with a differential susceptibility to select cancers. Acetylation phenotype may have clinical implications. The purposes of this study were to determine the genetic basis of an apparent predominance of slow acetylation phenotype and to assess concordance with genotype in a population of Hmong residing in Minnesota. Urine and DNA obtained from unrelated Hmong 18 to 65 years of age were used to determine phenotype from caffeine metabolites, whereas direct nucleotide sequencing of the NAT2 coding region, followed by cloning, identified all known allelic variants. From 61 subjects (27 men, 30 +/- 11 years), analysis of 50 urine-DNA pairs identified 46 (92%) slow acetylators and 4 (8%) rapid acetylators by phenotype. Genotypic analysis inferred 5 (10%) slow acetylators and 45 (90%) rapid acetylators. There is 86% discordance between phenotype and genotype. A predominance of NAT2 slow acetylation phenotype in the Hmong is confirmed, and a significant discordance between NAT2 phenotype and genotype is identified. In this population, slow acetylation phenotype determined by a metabolic probe would not have been predicted by genotype alone. Environmental, genetic, or phenotypic anomalies that may contribute to this discordance should be considered and evaluated in future studies within this unique population.

Acetylation↗

PubMed2005

Effect of influenza vaccine on markers of inflammation and lipid profile.

Despite wide use of the influenza vaccine, relatively little is known about its effect on the measurement of inflammatory markers. Because inflammatory markers such as C-reactive protein (CRP) are increasingly being used in conjunction with lipids for the clinical assessment of cardiovascular disease and in epidemiologic studies, we evaluated the effect of influenza vaccination on markers of inflammation and plasma lipid concentrations. We drew blood from 22 healthy individuals 1 to 6 hours before they were given an influenza vaccination and 1, 3, and 7 days after the vaccination. Plasma CRP, interleukin (IL)-6, monocyte chemotactic protein 1, tumor necrosis factor alpha, IL-2 soluble receptor alpha, and serum amyloid A were measured, and differences in mean concentrations of absolute and normalized values on days 1, 3, and 7 were compared with mean baseline values. There was a significant increase in mean IL-6 (P < .01 absolute values, P < .001 normalized values) on day 1 after receiving the influenza vaccine. The mean increases in normalized high sensitivity CRP values were significant on day 1 (P < .01) and day 3 (P = .05), whereas the mean increase in normalized serum amyloid A was significant only on day 1 (P < .05). No significant changes were seen in mean concentrations of IL-2 soluble receptor alpha, monocyte chemotactic protein-1, or tumor necrosis factor-alpha. Of the lipids, significant decreases in mean concentrations of normalized triglyceride values were seen on days 1 (P < .05), 3 (P < .001), and 7 (P < .05) after vaccination. Our findings show that the influenza vaccination causes transient changes in select markers of inflammation and lipids. Consequently, clinical and epidemiologic interpretation of the biomarkers affected should take into account the possible effects of influenza vaccination.

Adult↗

PubMed2005

Achieving cholesterol target in a managed care organization (ACTION) trial.

STUDY OBJECTIVES: To objectively compare the results of a collaborative approach using pharmacists with the results of usual care for achieving a low-density lipoprotein cholesterol (LDL) goal of 100 mg/dl or less in outpatients with documented coronary heart disease (CHD) who are not at goal, and to document the effect on LDL after removal of such a collaborative model from the study population. DESIGN: Prospective, multiclinic, controlled study. SETTING: Four clinics of a 19-clinic staff model health maintenance organization in Minneapolis and St. Paul, Minnesota. Two clinics treated the intervention patients, two the controls; one clinic for each group was suburban, and one for each was urban. PATIENTS: Four hundred eighty-one patients aged 18 years or older with CHD and whose LDL levels were not at goal. INTERVENTION: Clinical pharmacists implemented the physician-approved care plan for each intervention patient; activities included managing lipid-lowering drug therapy and educating patients on cardiovascular risk reduction. MEASUREMENTS AND MAIN RESULTS: Primary outcomes were changes in LDL level and the proportion of patients achieving goal LDL in the intervention versus the usual care (control) group. Secondary outcomes were the sustainability of the impact observed up to 18 months after discontinuation of the intervention. Mean+/-SD baseline LDL levels were 131+/-28 and 131+/-26 mg/dl (p=NS) for the intervention and control groups, respectively. After a mean of 6.5 months follow-up, 107 (72%) patients in the intervention group and 61 (18%) patients in the control group had attained their LDL goal (p<0.001). Mean LDL levels were reduced by 35.6 mg/dl (27.5%) and 6.7 mg/dl (4.6%) in the intervention and control groups, respectively (p<0.001). When the active program was discontinued, results of the 18-month follow-up indicated that 85 (65%) intervention patients remained at goal compared with 96 (42%) controls (p<0.001). CONCLUSION: This trial provides quantitative evidence to support the effectiveness of the collaborative approach as an intervention to optimize management of patients with CHD whose LDL levels are not at goal; this approach is specifically called for in the executive summary of the National Cholesterol Education Program Adult Treatment Panel III. Furthermore, this study documents both the magnitude and sustainability of the impact collaborative care models can have in managed care environments.

Aged↗