Betamethasone in pregnancy: influence of maternal body weight and multiple gestation on pharmacokinetics Micaela Della Torre, MD, MS; Judith U. Hibbard, MD; Hyunyoung Jeong, PharmD, PhD; James H. Fischer, PharmD OBJECTIVE: The goals of the study were to estimate the pharmacokinetic parameters of standard dose betamethasone in a large obstetrics popula- tion and evaluate the effect of maternal body size and multiple gestation on the pharmacokinetic parameters and their observed variability. STUDY DESIGN: This was a prospective pharmacokinetic study. Liquid chromatography mass spectrometry was used to measure betametha- sone plasma concentrations. Pharmacokinetic parameters and signifi- cant clinical covariates were estimated with mixed effect modeling. Bootstrap analysis confirmed validity of the model. RESULTS: Two hundred seventy-four blood samples from 77 patients were obtained. The greatest effect on pharmacokinetic variability was observed with maternal lean body weight (LBW). The relationship be- tween the pharmacokinetic parameters and LBW remained linear over a wide range of maternal body sizes. Multiple gestations did not affect the pharmacokinetic parameters. CONCLUSION: Individualization of betamethasone dosing by maternal LBW reduces variability in drug exposure. Mutiple gestations do not re- quire betamethasone dosing adjustment, because pharmacokinetics are the same as singleton gestations. Key words: antenatal steroid, betamethasone, pharmacokinetics, prematurity Cite this article as: Della Torre M, Hibbard JU, Jeong H, Fischer JH. Betamethasone in pregnancy: influence of maternal body weight and multiple gestation on pharmacokinetics. Am J Obstet Gynecol 2010;203:254.e1-12. P regnancy is characterized by many physiologic changes that may alter the disposition of drugs and the preg- nant woman’s response. 1,2 To date phar- macokinetics during pregnancy are known only for a few drugs. Antenatal steroid therapy has been demonstrated to improve neonatal out- comes in premature neonates. 3 This treatment decreases the risk of respira- tory distress syndrome, reduces cere- broventricular hemorrhage, and im- proves overall neonatal survival. 4,5 In multiple gestations, there may be a less beneficial effect of antenatal corticoste- roid in reducing respiratory distress syn- drome and death. 6 Ballabh et al 7 re- ported a more rapid elimination half-life of betamethasone in twin, compared with singleton, pregnancies and believe a decrease in betamethasone exposure may explain the reduced effectiveness in twins. However, the lack of difference in this medication’s clearance and volume of distribution conflicts with this inter- pretation. Few data exist about whether betamethasone that is given to obese women has the same beneficial neonatal effects as in normal-weight women. Re- cently, a retrospective investigation of 1000 pregnant women who were re- ceiving antenatal steroid treatment and stratified by body mass index (BMI) found no difference among groups in composite neonatal morbidity and mor- tality rates. 8 Similar results were noted by another investigator. 9 Aims of this study were to (1) examine the pharmacokinetics of standard dose intramuscular betamethasone in women between 24 and 34 weeks of gestation, (2) determine whether body size indica- tors influence the variability in beta- methasone volume of distribution and clearance, and (3) determine whether multiple gestations affect these pharma- cokinetic parameters. MATERIALS AND METHODS Patients A prospective population pharmacoki- netic study was conducted from March, 2008 to November, 2008 at the Univer- sity of Illinois at Chicago. All pregnant women, between 24 and 34 weeks’ gesta- tion, 18 years old, and clinically eligi- ble for an inpatient antenatal corticoste- roid treatment course were approached for enrollment. Participating subjects received the standard regimen of beta- methasone (equal amounts of beta- methasone sodium phosphate and beta- methasone acetate at a dose of 12 mg every 24 hours for a total of 2 injections intramuscularly). A blood sample of 8 mL was collected from participants within each of the 5 sampling windows: 5-20 minutes, 1-3 hours, 5-8 hours, and 22-24 hours after the first intramuscular dose and 2-6 hours after the second in- tramuscular dose. Sampling windows were constructed from the D-optimal sample times that were determined with the ADAPT II software (Biomedical Simulations Resource, Los Angeles, CA). 10,11 Enrollment occurred 7 days a week, 24 hours daily. Participation in the From the Division of Maternal Fetal Medicine, Department of Obstetric and Gynecology (Drs Della Torre and Hibbard), and the Department of Pharmacy Practice (Drs Jeong and Fischer), University of Illinois at Chicago, Chicago, IL. Presented orally at the 30th Annual Meeting of the Society for Maternal-Fetal Medicine, Chicago, IL, Feb. 1-6, 2010. Received Feb. 27, 2010; revised May 4, 2010; accepted June 14, 2010. Reprints: Micaela Della Torre, MD, MS, 3000 N Halsted, Suite 209 A, Chicago, IL 60657. [email protected]. Authorship and contribution to the article is limited to the 4 authors indicated. There was no outside funding or technical assistance with the production of this article. 0002-9378/$36.00 Published by Mosby, Inc. doi: 10.1016/j.ajog.2010.06.029 SMFM Papers www. AJOG.org 254.e1 American Journal of Obstetrics & Gynecology SEPTEMBER 2010
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etamethasone in pregnancy: influence of maternal bodyeight and multiple gestation on pharmacokinetics
icaela Della Torre, MD, MS; Judith U. Hibbard, MD; Hyunyoung Jeong, PharmD, PhD; James H. Fischer, PharmD
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BJECTIVE: The goals of the study were to estimate the pharmacokineticarameters of standard dose betamethasone in a large obstetrics popula-ion and evaluate the effect of maternal body size and multiple gestation onhe pharmacokinetic parameters and their observed variability.
TUDY DESIGN: This was a prospective pharmacokinetic study. Liquidhromatography mass spectrometry was used to measure betametha-one plasma concentrations. Pharmacokinetic parameters and signifi-ant clinical covariates were estimated with mixed effect modeling.ootstrap analysis confirmed validity of the model.
ESULTS: Two hundred seventy-four blood samples from 77 patients
harmacokinetics. Am J Obstet Gynecol 2010;203:254.e1-12.
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54.e1 American Journal of Obstetrics & Gynecology SEPTEMBER 2010
bserved with maternal lean body weight (LBW). The relationship be-ween the pharmacokinetic parameters and LBW remained linear over aide range of maternal body sizes. Multiple gestations did not affect theharmacokinetic parameters.
ONCLUSION: Individualization of betamethasone dosing by maternalBW reduces variability in drug exposure. Mutiple gestations do not re-uire betamethasone dosing adjustment, because pharmacokineticsre the same as singleton gestations.
ey words: antenatal steroid, betamethasone, pharmacokinetics,
ere obtained. The greatest effect on pharmacokinetic variability was prematurity
ite this article as: Della Torre M, Hibbard JU, Jeong H, Fischer JH. Betamethasone in pregnancy: influence of maternal body weight and multiple gestation on
cmc
MPAn2swtbrfrmmmeimw52dtwstSC
regnancy is characterized by manyphysiologic changes that may alter
he disposition of drugs and the preg-ant woman’s response.1,2 To date phar-acokinetics during pregnancy are
nown only for a few drugs.Antenatal steroid therapy has been
emonstrated to improve neonatal out-omes in premature neonates.3 Thisreatment decreases the risk of respira-ory distress syndrome, reduces cere-
rom the Division of Maternal Fetaledicine, Department of Obstetric andynecology (Drs Della Torre and Hibbard),
nd the Department of Pharmacy PracticeDrs Jeong and Fischer), University ofllinois at Chicago, Chicago, IL.
resented orally at the 30th Annual Meeting ofhe Society for Maternal-Fetal Medicine,hicago, IL, Feb. 1-6, 2010.
eceived Feb. 27, 2010; revised May 4, 2010;ccepted June 14, 2010.
eprints: Micaela Della Torre, MD, MS, 3000 Nalsted, Suite 209 A, Chicago, IL [email protected].
uthorship and contribution to the article isimited to the 4 authors indicated. There waso outside funding or technical assistance withhe production of this article.
002-9378/$36.00ublished by Mosby, Inc.
roventricular hemorrhage, and im-roves overall neonatal survival.4,5 Inultiple gestations, there may be a less
eneficial effect of antenatal corticoste-oid in reducing respiratory distress syn-rome and death.6 Ballabh et al7 re-orted a more rapid elimination half-lifef betamethasone in twin, comparedith singleton, pregnancies and believe aecrease in betamethasone exposureay explain the reduced effectiveness in
wins. However, the lack of difference inhis medication’s clearance and volumef distribution conflicts with this inter-retation. Few data exist about whetheretamethasone that is given to obeseomen has the same beneficial neonatal
ffects as in normal-weight women. Re-ently, a retrospective investigation of1000 pregnant women who were re-
eiving antenatal steroid treatment andtratified by body mass index (BMI)ound no difference among groups inomposite neonatal morbidity and mor-ality rates.8 Similar results were notedy another investigator.9
Aims of this study were to (1) examinehe pharmacokinetics of standard dosentramuscular betamethasone in womenetween 24 and 34 weeks of gestation,2) determine whether body size indica-ors influence the variability in beta-
f distribution and w
learance, and (3) determine whetherultiple gestations affect these pharma-
okinetic parameters.
ATERIALS AND METHODSatients
prospective population pharmacoki-etic study was conducted from March,008 to November, 2008 at the Univer-ity of Illinois at Chicago. All pregnantomen, between 24 and 34 weeks’ gesta-
ion, �18 years old, and clinically eligi-le for an inpatient antenatal corticoste-oid treatment course were approachedor enrollment. Participating subjectseceived the standard regimen of beta-ethasone (equal amounts of beta-ethasone sodium phosphate and beta-ethasone acetate at a dose of 12 mg
very 24 hours for a total of 2 injectionsntramuscularly). A blood sample of 8
L was collected from participantsithin each of the 5 sampling windows:-20 minutes, 1-3 hours, 5-8 hours, and2-24 hours after the first intramuscularose and 2-6 hours after the second in-ramuscular dose. Sampling windowsere constructed from the D-optimal
ample times that were determined withhe ADAPT II software (Biomedicalimulations Resource, Los Angeles,A).10,11 Enrollment occurred 7 days a
tudy was limited to the inpatient popu-ation to ensure compliance with bloodraws. Fewer than 5 patients refused toarticipate in the study; the main reason
or refusal was discomfort with the re-earch-related venous punctures. Thetudy was approved by the University ofllinois at Chicago Institutional Reviewoard, and written informed consentas obtained before any study-related
nterventions.Demographic and clinical characteris-
ics were recorded for each participantlong with betamethasone dosing andampling times. Blood samples were col-ected in evacuated tubes and were cen-rifuged; the plasma was separated. To
inimize hydrolysis of the esters, thelasma was transferred immediately toubes that contained 100 mmol/L so-ium arsenate and potassium fluoridend was stored at –20°C.12,13 Of note,ommon definitions used in pharmacol-gy language and utilized in this workre summarized in Appendix I for read-rs’ convenience.
etamethasone assayetamethasone plasma concentrationsere measured with a validated liquid
hromatography–tandem mass spec-rometry assay, which had been adaptedrom previously published proce-ures.12,14 Quality control data for thessay is described in Appendix II.
harmacokinetic analysishe pharmacokinetic methods are sum-arized below and described in greater
etail in Appendix II. Population phar-acokinetic analysis of betamethasone
lasma concentrations was performedy nonlinear mixed effect modeling withhe use of the first-order conditional es-imation method of the NONMEM soft-are (version VI; Icon Developmentolutions, Ellicott City, MD).15 Severallternative pharmacokinetic modelsere evaluated to describe the disposi-
ion of intramuscular betamethasone.odel selection was guided by visual in-
pection of diagnostic plots, standard er-or of the parameter estimates, and min-mum value of the objective function
OFV). t
ovariate analysisayesian estimates of the pharmacoki-etic parameters for individual patientsere obtained from the pharmacoki-etic model without covariates (baseodel), then graphic methods were used
o screen for potential relationships be-ween covariates and pharmacokineticarameters, with the use of the software-Plus (version 6.1; Insightful Corpora-ion, Seattle, WA). Variables that werevaluated were total body weight (TBW),ean body weight (LBW),16 body surfacerea (BSA),17 BMI,18 gestational agecalculated by last menstrual period, ifvailable and confirmed by first- or sec-nd-trimester ultrasound scans), race,ge, twin or multiple gestation, concur-ent liver or kidney disease, and presencef preeclampsia. The LBW was calcu-
ated as described by Janmahasatian etl16:
LBW(kg) �9270 � TBW(kg)
8780 � 244 � BMI(kg ⁄ m2)
(1)
ovariates identified in this equationere first added alone to the base model;
hose covariates that produced a signifi-ant decrease in OFV (P � .01) were en-ered into the model by a stepwise for-ard inclusion backward elimination
pproach. Continuous covariates thatere identified were normalized to an
ccepted population standard (70 kg forBW, 45 kg for LBW, and 1.73 m2 forSA) or study median (30 weeks’ gesta-
ional age). Linear and power functionsor continuous covariates and an indica-or function for categoric covariates werevaluated to relate the covariates with theharmacokinetic parameters.
alidation of the modelhe validity of the final population phar-acokinetic model was evaluated by
ootstrap analysis. Resampling with re-lacement from the original dataset wassed to construct 1000 bootstrap data-ets. Each dataset was fit to the final pop-lation model.
ower analysiso determine the power of the design
hat was implemented in this study for
he identification of important differ- r
SEPTEMBER 2010 Americ
nces in the pharmacokinetic parame-ers between women with singleton and
ultifetal pregnancies, a simulation ap-roach was used. These simulations usedmodified form of the final populationodel that involved the addition of a co-
ariate in the expression for the beta-ethasone apparent clearance (CL/F).his covariate represented a propor-
ional increase (from 0-40% in incre-ents of 5%) in the apparent clearance
n women with multifetal pregnancies.or each incremental increase, 200 rep-
icate datasets were simulated and fit tohe modified model. The percentage ofhe 200 replications at each incrementalncrease that showed a significantlyigher apparent clearance in multifetalregnancies represented the power ofhe study to detect such a difference.
imulation of betamethasonelasma concentrationshe effect on betamethasone systemicxposure of different body size–adjustedosing schemes was examined by simu-
ation. Using the final population model,etamethasone plasma concentrationsrom time 0-24 hours after the dose wereimulated for 77 patients for each of theollowing doses: 12 mg (standard), 12
g per 45 kg LBW (LBW-adjustedose), and 12 mg per 70 kg TBW (TBW-djusted dose). Covariate values fromhe pharmacokinetic dataset were repro-uced in the simulation dataset. At eachose, 1000 replicates of the dataset wereimulated. The area under betametha-one plasma concentrations time curverom time 0 to infinity (AUC) was calcu-ated at each simulated plasma concen-ration profile. The findings were exam-ned graphically by the construction ofox-plots of the AUCs, categorized byosage regimen and BMI (�25 kg/m2,5-30 kg/m2, 31- 40 kg/m2, �40 kg/m2).
ESULTSighty-four pregnant women were en-olled in the study. However, 7 patientsad no evaluable betamethasone plasmaoncentrations and were not included inhe population analysis. Isolated plasmaamples from other patients were ex-luded from the dataset for the following
easons: 13 samples were outside the
an Journal of Obstetrics & Gynecology 254.e2
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uantifiable limit of the assay; 3 samplesad incomplete labeling, and 2 samplesere frozen before the red cells andlasma were separated. Thus, the finalharmacokinetic dataset consisted of 77regnant women who contributed 274lasma samples for analysis. Of the 274lasma samples, 233 samples (3.5 sam-les per patient) were from a singletonregnancy, and 51 samples (3.9 per pa-ient) were from multifetal pregnancies.he demographic and clinical character-
stics of subjects are summarized in Ta-le 1. Sixty-four women were carryingingleton pregnancies; 12 women werearrying twin pregnancies, and 1 womanas carrying a set of triplets. Gestational
ge ranged from 21-34 weeks. One pa-
TABLE 1Demographic characteristics of subCharacteristic
Other, %...................................................................................................................a Data are given as median (range).
Della Torre. Betamethasone in pregnancy. Am J Obstet G
ient received steroids at 21 weeks’ gesta- a
54.e3 American Journal of Obstetrics & Gynecolo
ion because of an error in the determi-ation of her gestational age at time ofdmission.
A 2-compartment model with first or-er of absorption and no lag time fit theetamethasone plasma concentrationrofile well. The pharmacokinetic pa-ameters that were estimated includedbsorption rate constant, apparent dis-ribution clearance (Q/F), CL/F, appar-nt volume of distribution of the centralompartment, and volume of distribu-ion at steady state (Vss/F). Data thatupported the structural and covariate
odel selection are provided in Appen-ix III. Table 2 lists the pharmacokineticarameters, covariate coefficients, inter-
harmacokinetic models with their rela-ive standard errors. The models in-luded estimates for the interindividualariability for CL/F, Q/F, Vss/F, and ab-orption rate constant along with a co-ariance term between CL/F and Vss/F.The covariate analysis identified LBW
or CL/F and gestational age and LBWor Vss/F as factors that significantly ex-lained their variability. The influence ofBW on the interindividual variability ofL/F was small, with variability reducedy 10.4%. On the other hand, LBW andestational age explained nearly 40% ofhe interindividual variability on Vss/F.o factors that significantly influenced
nterindividual variability in Q/F or ab-orption rate constant were identified.he final covariate models are provided
n Appendix III.Other descriptors of body size (TBW,
SA, and BMI), when individually inputnto the covariate models for CL/F andss/F, produced significant decreases in
he OFV. However, the decrease in OFVas less than with LBW, and their addi-
ion to covariate models that containedBW during the forward stepwise pro-ess produced no further improvementn the model fitting. They therefore wereot retained in the final covariate mod-ls. Interestingly, in contrast to the linearelationship between LBW and CL/F orss/F, a power function better described
he relationship of TBW with CL/F orss/F. The differences in the form of the
elationships with TBW, compared withBW, are apparent in Figure 1. As can beeen in Figure 1, the individual Bayesianstimates of CL/F and Vss/F that wereormalized by LBW remained constantver the range of observed body sizes,epresented by BMI. On the other hand,BW normalized CL/F and Vss decreaseith increasing BMI. The final popula-
ion pharmacokinetic model was vali-ated from 1000 bootstrap replicates.he bootstrapped medians for the fixednd random effect parameters are pro-ided in Table 2. The mean estimates forhe parameters from the final modelere within 15% of the bootstrappededians, which supported the stability
f the population model and accuracy ofhe parameter estimates. Additionally,
je
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arrow bootstrapped 95% confidencentervals (Table 2) confirm the precisionf the population parameters. Multiplesestation was not identified by the pop-lation analysis as significantly influenc-
ng the pharmacokinetics of betametha-one in pregnant women. Box plots ofhe individual CL/F, Vss/F, and elimina-ion half-life grouped by number of off-pring (single vs twin or triplet) arehown in Figure 2. No statistically signif-cant differences (P � .1, Student t test)ere observed for parameters between
ingle and multiple gestations. The
TABLE 2Population pharmacokinetic parambase model (no covariates), final (c
Typical value of the absorption rate consta..........................................................................................................
Typical value of apparent distribution clea..........................................................................................................
Typical value of apparent clearance (L/h)..........................................................................................................
Typical value of apparent clearance in a 4weight pregnant woman: lean body weighapparent clearance (L/h/45 kg)..........................................................................................................
Typical value of apparent volume of distribcompartment (L)..........................................................................................................
Typical value of apparent volume of distribstate (L)..........................................................................................................
Typical value of apparent volume of distribstate in a 45 kg lean body weight woman:of effect on apparent volume of distributio(L/45 kg)..........................................................................................................
Covariate for effect of gestational age on tapparent volume of distribution at steady-
Typical value of the absorption rate consta..........................................................................................................
Typical value of apparent distribution cleavariation (%)..........................................................................................................
Typical value of apparent clearance: coeffi(%)..........................................................................................................
Typical value of apparent volume of distribstate: coefficient of variation (%)..........................................................................................................
Covariance apparent clearance, apparentdistribution at steady-state: coefficient of..........................................................................................................
Residual variability: coefficient of variation...................................................................................................................
Della Torre. Betamethasone in pregnancy. Am J Obstet G
ower for detection of a statistically sig- d
ificant difference (P � .01) in CL/F be-ween singleton and multifetal pregnan-ies was 65% when CL/F was assigned aalue 25% higher in women with twin orriplet pregnancies, 78% when CL/F was0% higher in women with multifetalregnancies, and 86% when CL/F was5% higher in women with multifetalregnancies.Figure 3 summarizes the betametha-
one AUCs from the simulated datasets.he 12 mg (standard), 12 mg per 45 kgBW (LBW-adjusted), and 12 mg per 70g TBW (TBW-adjusted) doses pro-
r estimates of betamethasone fromariate) model, and bootstrap analysi
one AUCs (Figure 3, A). This findingeflects the similarity between medianBW and TBW in this study and typicalalues in women of this age. Variabilityn betamethasone AUC is less with theBW-adjusted dose. The reason for theiffering variability among dose groups
s illustrated by the box plots in Figure 3,and D. For the LBW-adjusted dose,edian betamethasone AUC is equiva-
ent among the 4 BMI groups (Figure 3,). On the other hand, the median AUC
or the other 2 dose groups varies withMI (Figure 3, B and D). For example,
g/m2, median AUC with the adminis-ration of the standard dose decreases bypproximately 35% (Figure 3, B) and,ith administration of TBW-adjustedose, increases by approximately 30%Figure 3, D).
OMMENT2-compartment model best described
he disposition of betamethasone afterntramuscular administration in preg-ant women at 21-34 weeks’ gestation.he CL/F and Vss/F for the typicaloman in the study of 30 weeks’ gesta-
ion and 48 kg LBW were 18.4 L/hr and02 L, respectively. These values areomparable with estimates that derivedrom the study reported by Peterson etl19 after intramuscular administrationf the same formulation to pregnantomen. Conversely, the betamethasoneL/F and distribution volume found byallabh et al7 in pregnant women aftern intramuscular injection of the sameormulation were lower. Potential fac-ors that could explain the discrepancymong Ballabh et al, our investigation,nd Peterson et al include their use of anmmunoassay vs a chemical assay byeterson et al and us for measuring beta-ethasone plasma concentrations, the
nability of their analysis to characterizehe absorption and distribution phasesf the betamethasone plasma concentra-ion-time curves, and their failure to sta-ilize the betamethasone esters in thelasma samples before storage.7,19 Anyf these factors may contribute to an ar-ifactual elevation of AUC and, as a re-ult, may explain the lower CL/F and vol-me of distribution described by Ballabht al.7
The betamethasone CL/F and Vss/F inur study are higher than observed intudies of nonpregnant women.13 Evenfter adjusting for a bioavailability of ap-roximately 70% for the betamethasonehosphate/acetate suspension in preg-ant women,19,20 our CL/F and Vss/Femain approximately 1.2- to 1.6-foldigher than values reported in nonpreg-ant women.13,19,20 Betamethasone is a
ow extraction ratio drug that was almostntirely eliminated by hepatic metabo-
ism.13 Factors that explain a higher CL/F
54.e5 American Journal of Obstetrics & Gynecolo
FIGURE 1Graphic evaluation of relationship between body size and apparentclearance and volume of distribution at steady-statenormalized by low or total body weight
A
B
12 20 28 36 44 52
Body Mass Index (kg/m2)
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, Individual Bayesian estimates of apparent clearance normalized to 45 kg low body weight (closedriangle) or to 70 kg total body weight (closed circle) vs body mass index. The solid line represents aess smoother fit to the 45 kg low body weight apparent clearance; the dashed line represents the fitf a less smoother to the 70 kg total body weight apparent clearance. B, Individual Bayesian estimatesf apparent volume of distribution at steady-state normalized to 45 kg low body weight (closedriangle) or to 70 kg total body weight (closed circle) vs body mass index. The solid line represents aess smoother fit to the 45 kg low body weight volume of apparent distribution at steady-state; theashed line represents a less smoother fit to the 70 kg total body weight apparent volume ofistribution at steady-state.ella Torre. Betamethasone in pregnancy. Am J Obstet Gynecol 2010.
gy SEPTEMBER 2010
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herefore include a decrease in the extentf absorption, a reduction in plasmarotein binding, or enhanced hepaticetabolism. Observations of the same
elative difference as we observed inL/F and Vss/F between pregnant andonpregnant women after intravenousdministration argues against a changen extent of absorption.13,19,20 An alter-tion in plasma protein binding is also annlikely explanation because the frac-
ion of betamethasone that is bound tolasma proteins is equivalent in preg-ant and nonpregnant women.13,19-21
onsequently, enhanced hepatic metab-lism represents the most probable ex-lanation for a pregnancy-related in-rease in CL/F. Although pathways thatediate the hepatic metabolism of beta-ethasone are not established, studiesith other corticosteroids suggest a pri-ary role for the cytochrome P450
soenzyme 3A4.22
Pregnancy-related increases in clear-nces of other 3A4 substrates have beenbserved.1,23An increase in tissue bind-
ng of betamethasone provides the mostpt explanation for the higher Vss/F inregnancy.19,20,24 Among the demo-raphic and clinical variables that werevaluated, the covariates that affectedetamethasone CL/F and Vss/F the mostere descriptors of body size, which in-
luded LBW, TBW, BSA, and BMI. Scal-ng of CL/F and Vss/F by LBW producedhe greatest reduction in the OFV andnterindividual variability. After LBWas incorporated into the population ofharmacokinetic models for CL/F andss/F, the addition of other body sizeeasures yielded no further improve-ent in the model fitting. The form of
he relationship with betamethasoneL/F or Vss/F also differed betweenBW and TBW and other body size in-icators. The CL/F and Vss/F increased
inearly with increasing LBW, but non-inearly with increasing TBW. Accord-ngly, betamethasone CL/F that wascaled to LBW remained constant and al-owed drug exposure to be satisfactorilystimated over a wide range of bodyompositions. On the other hand, CL/Fhat was scaled to TBW varies withhanging body size and, when directly
FIGURE 2Effect of single and multiple gestation on Bayesian estimates ofbetamethasone pharmacokinetic parameters for individual patients
Offspring for Current Pregnancy
App
aren
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45 k
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10
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, Box plots of apparent betamethasone clearance for singleton and multifetal pregnancies. B, Boxlots of apparent volume of distribution at steady-state for singleton and multifetal pregnancies. C,ox plots of betamethasone elimination half life for singleton and multifetal pregnancies. The limits of
he box represent the 25th to 75th percentile of the distribution; the solid line in the box is the medianalue; the whiskers represent the 10th and 90th percentiles of the distribution.ella Torre. Betamethasone in pregnancy. Am J Obstet Gynecol 2010.
xtrapolated from normal to obese indi-
an Journal of Obstetrics & Gynecology 254.e6
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iduals, underpredicts drug exposure inubjects with large BMIs. Figure 3, B-D,llustrates how these relationships im-act the administration of betametha-one doses. Compared with the use of atandard (unadjusted) or TBW-adjustedose, a milligram per kilogram–LBW ap-roach for dosing betamethasone offershe advantage of yielding consistentlasma concentrations across individu-ls of varying body compositions, whichs represented by BMI.
Doubts about the clinical benefit ofdjusting betamethasone doses for LBWere raised by recent retrospective anal-
ses that failed to show any relationshipetween neonatal outcomes and mater-al body size after standard courses ofntenatal betamethasone.8,9 However,he assertion of Jobe and Soll25 that stan-ard regimens deliver too high a doseuggests an alternative reason for the lackf differences in response between bodyomposition groups, namely that every-ne received a supratherapeutic dosef betamethasone. The standard beta-ethasone regimen for treatment of pre-aturity derives from a 1995 National
nstitutes of Health Consensus Panel,26
ith the dose, timing, and frequency se-ected from empiric rather than scientif-cally derived evidence.27 Support for aower dose is provided by a recent com-arison of 4 different betamethasoneegimens for the induction of fetal lungaturation in sheep.28 Induction of fetal
ung maturation was comparable amonghe 4 treatments, including a single doseegimen of intramuscular betametha-one acetate. Notably, the single-doseetamethasone acetate regimen pro-uced no detectable betamethasonelasma concentrations in 2 of 3 fetusesnd maternal betamethasone plasmaoncentrations were approximately one-enth of those seen after the standardegimen. The results of Jobe and Soll25
uggest the potential for unnecessaryrug exposure during pregnancy withhe current dosing regimen and empha-ize the need to better understand theharmacodynamic properties of beta-ethasone in the mother and fetus, par-
icularly with respect to lung maturationnd adverse effects on fetal growth.
hether individualized doses by LBW T
54.e7 American Journal of Obstetrics & Gynecolo
ffer any clinical advantages is uncertain.nce the range of effective betametha-
one doses and plasma concentrationsre identified, studies such as ours pro-ide a framework for individualizationf doses.Studies that involve other drugs sub-
tantiate the superiority of LBW com-ared with TBW for describing the effectf size on drug clearance across a broadange of body compositions.29-31 From aiologic perspective, these findings sug-est that LBW more directly mirrors theunctional capacity of the liver than
FIGURE 3Effects of dosage regimen and bod
Dose
12 mg per 45 kg LBW 12 mg 12 mg per 70 kg TBW
AU
C (
ng
-h/m
l)0
250
500
750
1000
1250
1500
1750
2000
Body Mass Index (kg/m2)
< 25 25 - 30 >30 - 40 > 40
AU
C (
ng
-h/m
l)
0
250
500
750
1000
1250
1500
1750
2000
C
rea under the plasma concentration-time curveates of the final population model for each of theody weight (LBW; LBW-adjusted dose), or 12ose). A, Box plot of simulated betamethasone AUetamethasone AUCs after a 12-mg dose (not ad25 kg/m2, 25-30 kg/m2, �30-40 kg/m2, or �
UCs after a 12-mg/45 kg LBW dose (adjusted b5-30 kg/m2, �30-40 kg/m2, or �40 kg/m2. D2 mg/70 kg TBW dose (adjusted by TWB) group30-40 kg/m2, or �40 kg/m2. The limits of th
istribution; the solid line in the box is the mediaercentiles of the distribution.ella Torre. Betamethasone in pregnancy. Am J Obstet Gyne
BW. In contrast to our results, other c
gy SEPTEMBER 2010
tudies generally have found TBW to behe best body size descriptor for volumef distribution of lipophilic drugs likeetamethasone.29 We are uncertain ofhe reason for this discrepancy, but theack of pregnant subjects in the othertudies may offer an explanation. Finally,lthough we demonstrated that LBWas the best body size indicator among
hose evaluated in the current study,one of the body size indicators, includ-
ng LBW, were developed specifically forregnancy. Development and evaluationf pregnancy-specific measures of body
ize on betamethasone exposure
Body Mass Index (kg/m2)
< 25 25 - 30 >30 - 40 > 40
AU
C (
ng
-h/m
l)
0
250
500
750
1000
1250
1500
1750
2000
Body Mass Index (kg/m2)
< 25 25 - 30 >30 - 40 > 400
250
500
750
1000
1250
1500
1750
2000
Cs) were determined by simulating 1000 repli-owing doses: standard 12 mg, 12 mg/45 kg low/70 kg total body weight (TBW; TBW-adjustedfor each of the 3 doses. B, Box plot of simulateded) grouped by the patients’ body mass indices:kg/m2. C, Box plot of simulated betamethasoneBW) grouped by body mass index: �25 kg/m2,x plot of simulated betamethasone AUCs after aby body mass index: �25 kg/m2, 25-30 kg/m2,ox represent the 25th to 75th percentile of thealue; the whiskers represent the 10th and 90th
Gestational age also significantly con-ributed to variability in Vss/F, withss/F increasing as a power function ofestational age. The time profile of thishange and relatively minor impact onss/F, approximately 18% from 24-34eeks’ gestation, suggest pregnancy-in-uced increases in extracellular fluid as aossible factor.1
Higher order of pregnancy was notound to alter the maternal pharmacoki-etics of betamethasone. The study hadufficient power to detect at least a 30%ifference in CL/F. The only other studyo compare pharmacokinetics in single-on and twin pregnancies found a sig-ificantly faster elimination half-life inomen with twin pregnancies.7 Compa-
able with our findings, neither clearanceor volume of distribution significantlyiffered for the 2 groups. The more rapidlimination was interpreted by the inves-igators as having the potential to loweretamethasone plasma concentrationsnd thus to explain the poorer responseo antenatal betamethasone in twinregnancies. This interpretation ignoreshat clearance and volume of distribu-ion, not elimination half-life, are therimary determinants of the plasmaoncentration-time profile. Future in-estigations should focus on alternativexplanations for decreased efficacy of be-amethasone in twin pregnancies andhould include reduced fetal bioavail-bility because of enhanced activity oflacental drug metabolizing enzymes,fflux transporter, or altered pharmaco-ogic responsiveness to betamethasonen fetuses of twin or triplet pregnancies.2
lso, more pharmacodynamic studies ofetamethasone that is given antenatallyhould focus on the identification of ef-ective betamethasone maternal dosesnd relative therapeutic plasma concen-rations in mothers and fetuses beforendividualization of dosing by LBW cane used clinically.In summary, we estimated pharmacoki-
etic parameters for betamethasone foromen between 21 and 34 weeks’ gesta-
ion at standard dosages. We demon-trated that, across a wide range of mater-al body size, individualization ofetamethasone dosage by LBW may be
referable to limit the risk of overdosing s
lim mothers and underdosing mothersith larger body size. However, therapeu-
ic levels must be identified, and we mustain a better understanding of its fetal andaternal pharmacodynamics. Because we
ould not demonstrate any difference inaternal pharmacokinetics with multife-
al pregnancies, further work should focusn alternative reasons for that betametha-one does not provide the same beneficialffects in babies who are born of multiplesestation, compared with their singletonounterparts. f
CKNOWLEDGMENTSe thank all the individuals who contributed to
he data collection without whom the projectould not have been completed: Maria Colon,D; Cecilia Gambala, MD; Dennie Rogers, MD,
nd all the Obstetrics and Gynecology residentsnd Labor and Delivery/Mother Baby staff.
EFERENCES. Anderson GD. Pregnancy-induced changes inharmacokinetics: a mechanistic-based ap-roach. Clin Pharmacokinet 2005;44:989-1008.. Hodge LS, Tracy TS. Alterations in drug dis-osition during pregnancy: implications for drugherapy. Expert Opin Drug Metab Toxicol007;3:557-71.. Antenatal corticosteroids revisited: repeatedourses. NIH Consens Statement Online 2000ugust 17-18;17:1-10.. The effect of corticosteroids for fetal lung ma-urity on perinatal outcomes. NIH Consensustatement Online 1994 February 28-March;12:1-24.. Roberts D, Dalziel SR. Antenatal corticoste-oids for accelerating fetal lung maturation foromen at risk of preterm labor. Cochrane Da-
ion on prevention of respiratory distress syn-rome in twin pregnancies. J Perinatol986;6:304-8.. Ballabh P, Lo ES, Kumari J, et al. Pharmacoki-etics of betamethasone in twin and single-on pregnancy. Clin Pharmacol Ther 2002;71:9-45.. Della Torre M, Hibbard J. Antenatal steroids
or prematurity and maternal obesity: does obe-ity decrease the beneficial effects? Poster pre-ented at: 29th Annual Meeting of the Society ofaternal-Fetal Medicine; San Diego, CA; Janu-
ry 31, 2009.. Hashima J. The effect of maternal obesity oneonatal outcome in women receiving a singleourse of antenatal corticosteroids. Poster pre-
ented at: 29th Annual Meeting of the Society of 1
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aternal-Fetal Medicine; San Diego, CA; Janu-ry 31, 2009.0. D’Argenio D. Optimal sampling times forharmacokinetic experiments. J Pharmacoki-et Biopharm 1981;9:739-56.1. D’Argenio D, Schumitzky A. ADAPT II user’suide: pharmacokinetic/pharmacodynamic sys-ems analysis software. Los Angeles, CA: Bio-edical Simulations Resource; 1997.2. Samtani MN, Lohle M, Grant A, NathanielszW, Jusko WJ. Betamethasone pharmacoki-etics after two prodrug formulations in sheep:
mplications for antenatal corticosteroid use.rug Metab Dispos 2005;33:1124-30.3. Petersen MC, Nation RL, Mc Bride WG,shley JJ, Moore RG. Pharmacokinetics of be-
amethasone in healthy adults after intravenousdministration. Eur J Clin Pharmacol 1983;25:43-50.4. Luo Y, Uboh CE, Soma LR, Guan F, Rudy JA,sang DS. Resolution, quantification and confir-ation of betamethasone and dexamethasone in
quine plasma by liquid chromatography/tandemass spectrometry. Rapid Commun Mass Spec-
rom 2005;19:825-32.5. Beal SL, Sheiner LB. NONMEM usersuide, 2006. Ellicott City, MD: Icon Develop-ent Solutions;1989-2006.6. Janmhasatian S, Duffull SB, Ash S, Ward LC,yrne NM, Green B. Quantification of lean body-eight. Clin Pharmacokinet 2005;44;1051-65.7. DuBois D, DuBois EF. Clinical calorimetry: a
ormula to estimate the approximate surfacerea if height and weight be known. Arch Interned 1916;17:863-71.8. Keys A, Fidanza F, Karvonen M, Kimura N,aylor H. Indices of relative weight and obesity.Chronic Dis 1972;25:329-43.9. Petersen MC, Ashley JJ, McBride WG, Na-ion RL. Disposition of betamethasone in partu-ient women after intramuscular administration.r J Clin Pharmacol 1984;18:383-92.0. Petersen MC, Collier CB, Ashley JJ,cBride WG, Nation RL. Disposition of beta-ethasone in parturient women after intrave-
ous administration. Eur J Clin Pharmacol983;25:803-10.1. Rasmussen BB, Larsen LS, Senderovitz T.harmacokinetic interaction studies of atosibanith labetalol or betamethasone in healthy fe-ale volunteers. BJOG 2005;112:14929.2. McCrea JB, Majumdar AK, Goldberg MR,t al. Effects of the neurokinin1 receptor antag-nist aprepitant on the pharmacokinetics ofexamethasone and methylprednisolone. Clinharmacol Ther 2003;74:17-24.3. Tracy TS, Venkataramanan R, Glover DD, et al.emporal changes in drug metabolism (CYP1A2,YP2D6 and CYP3A activity) during pregnancy.m J Obstet Gynecol 2005;192:633-9.4. Gibaldi M, McNamara PJ. Apparent vol-mes of distribution and drug binding to plasmaroteins and tissues. Eur J Clin Pharmacol
978;13:373-8.
an Journal of Obstetrics & Gynecology 254.e8
2ts2tsto2D
crR2Kdt22d
t13Bp3bc4
SMFM Papers www.AJOG.org
2
5. Jobe AH, Soll RF. Choice and dose of cor-icosteroid for antenatal treatments. Am J Ob-tet Gynecol 2004;190:878-81.6. Anonymous. Effect of corticosteroids for fe-al maturation on perinatal outcomes: NIH Con-ensus Development panel on the effect of cor-icosteroids for fetal maturation on perinatalutcomes. JAMA 1995;273:413-8.7. Brownfoot FC, Crowther CA, Middleton P.ifferent corticosteroids and regimens for ac-
Della Torre. Betamethasone in pregnancy. Am J Obstet Gynec
54.e9 American Journal of Obstetrics & Gynecolo
elerating fetal lung maturation for women atisk of preterm birth. Cochrane Database Systev 2008;4:CD006764.8. Jobe AH, Nitsos I, Pillow J, Polglase GR,allapur SG, Newnham JP. Betamethasoneose and formulation for induced lung matura-ion in fetal sheep. Am J Obstet Gynecol009;201:611.e1-7.9. Green B, Duffull SB. What is the best sizeescriptor to use for pharmacokinetic studies in
Definition
Time course of drug absorption, distribution, m.........................................................................................................................
Application of pharmacokinetics principles to sdrugs in an individual
Fraction of a given drug dose that reaches the.........................................................................................................................
Total body weight (kilograms)......................................................................................................................
Body surface area (square meters): calculatedpurposes body surface area is a better indicatoit is less affected by abnormal adipose mass)......................................................................................................................
Body mass index (kilograms/square meter): we......................................................................................................................
Lean body weight (kilograms) includes the weiwater in the body; everything except fat tissue
ol 2010.
gy SEPTEMBER 2010
he obese? Br J Clin Pharmacol 2004;58:19-33.0. Han PY, Duffull SB, Kirkpatrick CMJ, Green. Dosing in obesity: a simple solution to a bigroblem. Clinl Pharmacolo Ther 2007;82:505-8.1. Anderson BJ, Holford NHG. Mechanism-ased concepts of size and maturity in pharma-okinetics. Annu Rev Pharmacol Toxicol 2008;8:303-32.
bolism, and excretion in the body..................................................................................................................
e of action and resultant effect; includesse effects..................................................................................................................
ed on the assumption that, after 1 dose of ato all body areas
time is directly proportional to the amountnated over a set time period changes, butgiven time remains constant..................................................................................................................
Clearance Rate of drug removal from the plasma, expressed as volume of plasma per given unit of time................................................................................................................................................................................................................................................................................................................................................................................
Volume of distribution Extent of drug distribution into body fluids and tissues minus volume required to account forall of the drug in the body, if the concentration in all tissues is the same as plasmaconcentration
Rate of drug moving back and forth between the central compartment and the tissues andfluid of the peripheral compartment, to maintain a status of pseudoequilibrium
Area formed under the curve when plasma concentration is plotted vs time; expressed also astotal drug exposure: clearance � dose/area under the plasma concentration
PPENDIX IIetamethasone assayetamethasone plasma concentrationsere measured with validated liquid
hromatography-tandem mass spec-rometry assay that was adapted fromreviously published procedures.12,13
he lower limit of quantitation was 1.05g/mL. Samples with concentrationsbove the upper limit of quantita-ion,105 ng/mL, were analyzed after be-ng diluted 1:4 with blank plasma. Theetween-run precision, based on the rel-tive standard deviation of replicateuality control (n � 7) was 1.3% at 402g/mL, 4.7% at 80.5 ng/mL, 4.2% at 40.2/mL, 5.5% at 4.02 ng/mL, and 2.9% at.05 ng/mL. The assay was specific foretamethasone, with resolution of beta-ethasone base from the acetate and
hosphate esters.
xplanation of equations utilizedor pharmacokinetic modelingetamethasone plasma concentrationsere analyzed with NONMEM software
version VI, level 1.0; Globomax LLC,anover, MD). Model building first fo-
used on identification of an appropriatetructural (base) model, that consistedf a pharmacokinetic compartmentalodel and expressions for describing the
nter- and intraindividual (residual)ariabilities. The best model was selectedased on (1) goodness of fit plots (suchs those that were observed vs the model-redicted population betamethasonelasma concentrations and weighted re-iduals vs predicted plasma concentra-ions; (2) precision of the parameter es-imates, as indicated by the relativetandard error from the model fitting;3) minimum OFV (OFV; ie, the mini-ization criteria in NONMEM), and (4)
hysiologic relevance of the parameterstimates. The difference in the OFV be-ween competing models is approxi-
ately �2-distributed with the degrees ofreedom equal to the difference in theumber of parameters between theodels.One- and two-compartment modelsith first order absorption and elimina-
ion were evaluated to describe the dis-
osition of betamethasone and provide i
stimates of the fixed effect pharmacoki-etic parameters. Models were testedith and without an absorption lag time.he first-order conditional estimationethod was selected for fitting the phar-acokinetic data.A log normal distribution was as-
umed for the pharmacokinetic parame-ers; variability among individuals (ie,nterindividual variability) for the phar-
acokinetic parameters was describedith the use of exponential random ef-
ects. This relationship is illustrated forlearance (CL) by the following equa-ion:
CL/Fi � TVCL � ei (1)
here CL/Fi is the estimated CL for indi-idual i, typical value of clearanceTVCL) is the typical population valueor CL, and �i is the random effect thatepresents the deviation of CLi fromLTV. The �s are assumed to be distrib-ted normally with a mean of zero andariance �2. The �2 is an estimate of thenterindividual variance for the pharma-okinetic parameter.
An additive model (equation 2) wasvaluated when problems occurred withhe exponential model:
CL ⁄ Fi � TVCL � �i (2)
A full variance-covariance matrix (ie,nclusion of the off-diagonal elementshat represent the covariance betweenandom effects and indicate their degreef correlation) was implemented forodeling the interindividual random ef-
ects.Residual (error) variability was de-
cribed as a proportional error (equation):
Yij � Yij � (1 � �ij) (3)
here Yij is the jth observed betametha-one plasma concentration in individ-al i, Yij is the jth predicted betametha-o n e p l a s m a c o n c e n t r a t i o n i nndividual i, and �ij denotes the ran-om error between the measured andredicted jth observation in individual
. The �s are assumed to be distributedormally with a mean of zero and vari-nce of 2. The 2 is an estimate of the
ntraindividual variance. A diagonal
SEPTEMBER 2010 American
ariance-covariance matrix (ie, covari-nce between random effects set to 0)as used for modeling the residual
ariability.After the base model was determined,
he next step in the modeling processnvolved identification of clinically mean-ngful covariates for explaining the interin-ividual variability in the pharmacokineticarameters. Bayesian estimates of theharmacokinetic parameters for individ-al patients were obtained from the baseodel. Graphic and generalized additiveodeling methods (S-Plus, version 6.1;
nsightful Corporation, Seattle, WA) weresed to screen for relationships betweenovariates and pharmacokinetic parame-ers. The covariates that were evaluatedere total body weight (TBW), lean bodyeight,15body surface area,16 body mass
ndex,17 gestational age (calculated by lastenstrual period, if available, and con-
rmed by first or second trimester ultra-ound scan), race, age, multifetal (twin orriplet) gestation, concurrent liver or kid-ey disease, and presence of preeclampsia.ovariates that were identified in the
creening analysis were first added alone toxpressions for the pharmacokinetic pa-ameters in the base model with the use ofONMEM. Covariates that produced aecrease inOFV�3.84(P� .05;degreesof
reedom � 1) in the univariate analysisere entered in a stepwise fashion into an
ntermediate multivariate model and re-ained if their addition decreased the OFVy �3.84. A backward elimination stepollowed; the covariates that were enterednto the model during the forward addi-ion step were eliminated individually andetained in the final population pharmaco-inetic model if their removal increasedhe OFV by �6.6 (P � .01; degrees of free-om � 1).Continuous covariates were normal-
zed to an accepted population standard70 kg for TBW; 45 kg for lean bodyeight; 1.73 m2 for body surface area) or
tudy median (30 weeks’ gestationalge); linear (equation 4) or power (equa-ion 5) functions were used to assessheir influence:
CLi � TVCL � (TBW ⁄ 70) � (4)
Journal of Obstetrics & Gynecology 254.e10
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2
CLi � TVCL � (TBW ⁄ 70) (5)
here represents the effect of the co-ariate on the TVCL.Categoric covariates were input as in-
icator variables:
CL ⁄ F � TVCL � I � (6)
here I is an indicator variable with aalue of 1, if the trait is present, and 0therwise.The simulations to determine the power
f the design for the identification of im-ortant differences in apparent CL (CL/F)etween women with single and multifetaltwin or triplet) gestations were performedith a modified form of the final popula-
ion model. The modification is describedn the following equation:
L ⁄ Fi � CL ⁄ Ffinal model
� twin pregnancy � e (7)
here CL/Fi is the estimated CL/F for indi-idual i, CL/Ffinal model is the CL/F based onhe final population pharmacokinetic andovariate model, twin pregnancy is an addi-ional covariate for the simulation thatepresents a proportional increase in CL/Fn women with a twin or higher orderregnancy. twin pregnancy was varied from-40% in increments of 5%. The percent-ge of the 200 replications at each incre-ental increase that shows a significantly
igher CL/F in multifetal pregnancies rep-esented the power of the study to detecthis difference. The increase in CL/F wasonsidered significant if the decrease in theFV was �6.6 and the lower 95% asymp-
otic confidence limit for the coefficienthat represented the effect of multifetalregnancies on CL (ie, twin pregnancy) was0.For the simulations that were per-
ormed to examine the effect of differentody size–adjusted dosing schemes onetamethasone exposure, the area underhe betamethasone plasma concentra-ion-time curve from time zero to infin-ty was calculated for each simulatedlasma concentration profile by therapezoidal rule from time 0-24 hours af-er the dose was administered, with therea from 24 hours to infinity extrapo-ated by dividing the betamethasonelasma concentration at 24 hours by the
egative of the terminal slope. d
54.e11 American Journal of Obstetrics & Gyneco
PPENDIX IIIata that support the selection of thetructural pharmacokinetic model
2-compartment model with first-or-er absorption and no lag time fit the be-amethasone plasma concentration pro-le well (delta objective function, –183;� .001; degrees of freedom � 2), com-ared with a 1-compartment model.harmacokinetic parameters of theodel included absorption rate con-
tant, clearance (CL/F), apparent distri-ution clearance, apparent volume of
oodness of fit plots for betamethasone plasma codels with first-order absorption and eliminatio
lasma concentrations from the 1-compartmentetamethasone plasma concentrations from thredicted betamethasone plasma concentrationiduals vs model-predicted betamethasone plasmhe solid line in A and C represents the line ofero-intercept line.ella Torre. Betamethasone in pregnancy. Am J Obstet Gyne
istribution of the central compartment, w
logy SEPTEMBER 2010
nd volume of distribution at steadytate (Vss/F). The less varied and moreymmetric distribution of data aroundhe line of identity in the Supplementaligure, C compared with A and the zero
ntercept line in D compared with B sup-ort the suitability of the 2-compart-ent model. The model included esti-ates for the interindividual variability
IIV) for CL/F, Vss/F, and absorptionate constant along with a covarianceerm between CL/F and Vss/F. The IIV inbsorption rate constant was modeled
entrations with the use of 1- and 2-compartment, Observed vs model-predicted betamethasonedel. B, Weighted residuals vs model-predicted-compartment model. C, Observed vs model-m the 2-compartment model. D, Weighted re-
concentrations from the 2-compartment model.ntity. The solid line in B and D represents the
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onential model best described IIV forhe other parameters. The data did notupport allocation of IIV to apparentolume of distribution of the centralompartment. Residual variability wasxpressed with a proportional errorodel. A linear relationship was se-
ected for the description of the rela-ionship between low body weightLBW) and CL/F or Vss/F. The use of aower equation did not improve the fitnd yielded power coefficients that in-
luded 1 within the 95% confidence a
imits, which strongly suggested a lin-ar relationship. After hypothesis test-ng was completed, the effect of LBWn CL/F and Vss/F was simplified fromlinear expression to a direct propor-
ion for the final model. This transfor-ation provided a more clinically ap-
licable expression and did not affectither the fit or amount of variabilityxplained by LBW.
Covariate models for CL/F and Vss/FThe final covariate models for CL/F
nd Vss/F were L
SEPTEMBER 2010 American
L ⁄ F (L ⁄ hr) � TVCL45kg woman
(L ⁄ h ⁄ 45) � LBW ⁄ 45 kg
ss ⁄ F (L) � (TVVss45kg woman
[L ⁄ 45 kg] � �gestational age [wks]⁄40)
� LBW ⁄ 45 kg
VCL45kg woman and TVVss45kg woman
epresent typical values of CL/F andss/F for a pregnant woman of 45 kg
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