Nonparametric Expectation Maximisation (NPEM) Population Pharmacokinetic Analysis of Caffeine Disposition from Sparse Data in Adult Caucasians: Systemic Caffeine Clearance as a Biomarker for Cytochrome P450 1A2 Activity
Clinical Pharmacokinetics, ISSN: 0312-5963, Vol: 42, Issue: 15, Page: 1393-1409
2003
- 10Citations
- 17Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Metrics Details
- Citations10
- Citation Indexes10
- 10
- CrossRef4
- Captures17
- Readers17
- 15
Article Description
Objective: To explore the ability of the nonparametric expectation maximisation (NPEM) method of population pharmacokinetic modelling to deal with sparse data in estimating systemic caffeine clearance for monitoring and evaluation of cytochrome P450 (CYP) 1A2 activity. Design and participants: Nonblind, single-dose clinical investigation in 34 non-related adult Bulgarian Caucasians (18 women and 16 men, aged between 18 and 62 years) with normal and reduced renal function. Methods: Each participant received oral caffeine 3 mg/kg. Two blood samples per individual were taken according to the protocol for measuring caffeine plasma concentrations. A total of 67 measured concentrations were used to obtain NPEM estimates of caffeine clearance. Paraxanthine/caffeine plasma ratios were calculated and correlated with clearance estimates. Graphical methods and tests for normality were applied and parametric and nonparametric statistical tests were used for comparison. Results: NPEM median estimates of caffeine absorption and elimination rate constants, ka = 4.54 h and k = 0.139 h, as well as of fractional volume of distribution and plasma clearance, V = 0.58 L/kg and CL = 0.057 L/h/kg, agreed well with reported values from more 'data rich' studies. Significant correlations were observed between paraxanthine/caffeine ratios at 3, 8 and 10 hours and clearance (Spearman rank correlation coefficients, r, >0.74, p ≤ 0.04). Sex or renal function caused no significant differences in clearance. Heavy smokers and drinkers showed 2-fold higher CYP1A2 activity. Normality tests and graphical methods of analysing caffeine clearance supported a non-Gaussian and multicomponent distribution of CYP1A2 activity. Conclusions: Collectively, the results show that the NPEM method is suitable and relevant for large-scale epidemiological studies of population phenotyping for cancer susceptibility and for abnormal liver function by monitoring CYP1A2 activity based on sparse caffeine data.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=0347990348&origin=inward; http://dx.doi.org/10.2165/00003088-200342150-00006; http://www.ncbi.nlm.nih.gov/pubmed/14674790; http://link.springer.com/10.2165/00003088-200342150-00006; https://dx.doi.org/10.2165/00003088-200342150-00006; https://link.springer.com/article/10.2165/00003088-200342150-00006
Springer Nature
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