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pkexamine — Calculate pharmacokinetic measures
pkexamine time concentration      , options  use # points to estimate AUC0,∞; default is fit(3) use trapezoidal rule; default is cubic splines graph the linear extension graph the log extension plot the exponential fit for the AUC0,∞ affect rendition of plotted points connected by lines change look of markers (color, size, etc.) add marker labels; change look or position add other plots to the generated graph Y axis, X axis, Titles, Legend, Overall any options other than by() documented in by is allowed; see Statistics > Epidemiology and related > Other > Pharmacokinetic measures pkexamine calculates pharmacokinetic measures from time-and-concentration subject-level data.
pkexamine computes and displays the maximum measured concentration, the time at the maximummeasured concentration, the time of the last measurement, the elimination time, the half-life, and thearea under the concentration-time curve (AUC). Three estimates of the area under the concentration-timecurve from 0 to infinity (AUC0,∞) are also calculated.
pkexamine is one of the pk commands. Please read before reading this entry.
— Calculate pharmacokinetic measures
fit(#) specifies the number of points, counting back from the last measurement, to use in fitting the extension to estimate the AUC0,∞. The default is fit(3), or the last three points. This valueshould be viewed as a minimum; the appropriate number of points will depend on your data.
trapezoid specifies that the trapezoidal rule be used to calculate the AUC. The default is cubic splines, which give better results for most functions. When the curve is irregular, trapezoid maygive better results.
graph tells pkexamine to graph the concentration-time curve.
line and log specify the estimates of the AUC0,∞ to display when graphing the AUC0,∞. These options are ignored, unless they are specified with the graph option.
exp(#) specifies that the exponential fit for the AUC0,∞ be plotted. You must specify the maximum time value to which you want to plot the curve, and this time value must be greater than themaximum time measurement in the data. If you specify 0, the curve will be plotted to the pointat which the linear extension would cross the x axis. This option is not valid with the line orlog option and is ignored, unless the graph option is also specified.
cline options affect the rendition of the plotted points connected by lines; see marker options specify the look of markers. This look includes the marker symbol, the marker size, and its color and outline; see marker label options specify if and how the markers are to be labeled; see addplot(plot) provides a way to add other plots to the generated graph. See Y axis, X axis, Titles, Legend, Overall twoway options are any of the options documented in excluding by(). These include options for titling the graph (see ) and for saving the graph to disk (see Remarks and examples
pkexamine computes summary statistics for a given patient in a pharmacokinetic trial. If by idvar: is specified, statistics will be displayed for each subject in the data.
, 13) present data on a study examining primidone concentrations versus time for a subject over a 32-hour period after dosing.
— Calculate pharmacokinetic measures
. use . list, abbrev(14) We use pkexamine to produce the summary statistics: . pkexamine time conc, graph Maximum concentration = Time of maximum concentration = Time of last observation (Tmax) = Elimination rate = Area under the curve Linear of log conc.
Fit based on last 3 points.
— Calculate pharmacokinetic measures
The maximum concentration of 4.7 occurs at time 3, and the time of the last observation (Tmax) is32. In addition to the AUC, which is calculated from 0 to the maximum value of time, pkexaminealso reports the area under the curve, computed by extending the curve with each of three methods:a linear fit to the log of the concentration, a linear regression line, and a decreasing exponentialregression line. See for details on these three methods.
By default, all extensions to the AUC are based on the last three points. Looking at the graph for these data, it seems more appropriate to use the last seven points to estimate the AUC0,∞: . pkexamine time conc, fit(7) Maximum concentration = Time of maximum concentration = Time of last observation (Tmax) = Elimination rate = Area under the curve Linear of log conc.
Fit based on last 7 points.
This approach decreased the estimate of the AUC0,∞ for all extensions. To see a graph of the AUC0,∞using a linear extension, specify the graph and line options.
. pkexamine time conc, fit(7) graph line Maximum concentration = Time of maximum concentration = Time of last observation (Tmax) = Elimination rate = Area under the curve Linear of log conc.
Fit based on last 7 points.
— Calculate pharmacokinetic measures
pkexamine stores the following in r(): area under the concentration curve half-life of the drug time at last concentration measurement maximum concentration time of maximum concentration AUC0,∞ estimated with a linear fit AUC0,∞ estimated with an exponential fit AUC0,∞ estimated with a linear fit of the natural log Methods and formulas
Let i index the observations sorted by time, let k be the number of observations, and let f be the number of points specified in the fit(#) option.
where Ct is the concentration at time t. By default, the integral is calculated numerically using cubicsplines. However, if the trapezoidal rule is used, the AUC0,t — Calculate pharmacokinetic measures
The AUC0,∞ is the AUC0,t When using the linear extension to the AUC0,t , the integration is cut off when the line crosses the x axis. The log extension is a linear extension on the log concentration scale. The area for theexponential extension is e−(β0+tβ1)dt = − The elimination rate Keq is the negative of the slope from a linear regression of log concentration on time fit to the number of points specified in the fit(#) option: Chow, S.-C., and J.-P. Liu. 2009. Design and Analysis of Bioavailability and Bioequivalence Studies. 3rd ed. Boca Raton, FL: Chapman & Hall/CRC.
— Pharmacokinetic (biopharmaceutical) data


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