0021-972X/99/$03.00/0
The Journal of Clinical Endocrinology & Metabolism
Copyright © 1999 by The Endocrine Society
Vol. 84, No. 9
Printed in U.S.A.
Appraisal of Growth Hormone (GH) Secretion:
Evaluation of a Composite Pharmacokinetic Model That
Discriminates Multiple Components of GH Input*
GEORGE M. BRIGHT, JOHANNES D. VELDHUIS, ALI IRANMANESH,
GERHARD BAUMANN, HIRALAL MAHESHWARI, AND JOHN LIMA
Division of Endocrinology (G.M.B.) and the Center for Pediatric Clinical Pharmacology (J.L.),
Nemours Children’s Clinic, Jacksonville, Florida 32207; the Division of Endocrinology and
Metabolism, University of Virginia Health Sciences Center (J.D.V.), Charlottesville, Virginia 22908;
Veterans Affairs Medical Center (A.I.), Salem, Virginia 24153; and Northwestern University Medical
School (G.B., H.M.), Chicago, Illinois 60611
ABSTRACT
Criteria for a diagnosis of GH deficiency include inadequate GH
secretion as assessed by provocative testing. The changes in serum
GH concentration in such tests, however, do not uniformly predict
treatment responses. We questioned whether the changes in serum
GH have a uniform dependence among subjects on the mass of secreted GH. We simulated spontaneous GH secretory events with bolus
infusions of recombinant human GH (rhGH) in 15 somatostatininfused adult subjects. Maximum serum GH responses, the GH areas
under the curve, and GH mass calculated from deconvolution techniques are all indexes of GH secretion influenced by GH clearance and
distribution volume. In this group, these indexes showed a nonuniform dependence on the known GH dose. Despite somatostatin infusion, we found evidence for low level basal GH secretion with oscillatory characteristics that may have influenced the GH concentration
dependence on GH dose. We then developed and evaluated a new
pharmacokinetic model to account for pulsatile, basal, and oscillatory
inputs to the serum GH concentration profile.
The new model is comprised of three terms. The first describes
plasma GH concentrations from exogenous administration of rhGH
according to a one- or a two-compartment model. The second term
accounts for basal GH secretion. The third is a cosinor function that
describes the oscillatory pattern of basal GH. The composite pharmacokinetic model predicted plasma GH concentrations well (r2 5
A
TIMELY and correct clinical diagnosis of endocrine
glandular normality or deficiency is critical to the
management of treatment outcomes. Indeed, diagnoses of
hormone deficiency states frequently lead to prolonged, and
occasionally expensive, hormone replacement therapies.
Hormone stimulation tests and frequent blood sampling are
common clinical strategies to help differentiate between
states of hormone deficiency and sufficiency. Yet the validity
of hormone production (mass per unit time) inferences from
measured plasma hormone concentrations (mass per unit
Received October 14, 1998. Revision received April 9, 1999. Accepted
May 21, 1999.
Address all correspondence and requests for reprints to: Dr. George
M. Bright, Novo Nordisk Pharmaceuticals, Inc., 100 Overlook Center,
Suite 200, Princeton, New Jersey 08540.
* This work was supported by grants from The Genentech Foundation for Growth and Development (to G.M.B.) and the NSF Center for
Biological Timing (to J.D.V.) and by NIH Grant RO1-AG-147991 (to
J.D.V.).
0.88 – 0.97); pharmacokinetic and cosinor parameters had high precision and narrow 95% confidence intervals. The pharmacokinetic
parameters were stable and independent.
The mean values and coefficients of variance (SD/mean) of GH
pharmacokinetic parameters in our 15 subjects were: clearance, 0.236
L/min (24%); volume of distribution, 3.46 L (30%); and terminal halflife, 12.3 min (37%). The values for the cosinor parameters were: basal
concentration, 0.22 ng/mL (85%); amplitude, 0.758 (50%); cycle, 121
min (27%); and time shift (acrophase), 60.3 min (53.6%). During the
9-h study, clearance decreased from 0.259 6 0.09 to 0.214 6 0.06
L/min (P , 0.03), and basal concentration increased from 0.20 6 0.22
to 0.33 6 0.33 ng/mL (P , 0.5).
We conclude that our model can provide useful estimates of GH
pharmacokinetics in the presence of basal, oscillating, endogenous
concentrations without administering a dose of radiolabeled GH. The
substantial inter- and intrasubject variance in pharmacokinetic parameters between subjects negates the assumption of a uniform relationship between GH secretion and serum GH concentration and
detracts from the utility of a GH concentration cut-off point in GH
testing. These findings have implications to the valid appraisal of GH
deficiency states, selection of rhGH treatment candidates, and physiological regulation of the GH axis. (J Clin Endocrinol Metab 84:
3301–3308, 1999)
volume) is imperfectly established in many clinical test situations. For example, we have found a nonuniform dependence of plasma cortisol concentration on the doses of cortisol infused into a group of dexamethasone-suppressed
adults (1, 2).
An accurate diagnosis of GH deficiency is of increasing
significance, especially given that GH treatment indications
have been broadened recently to include both adults and
children. The serum GH responses to provocative testing
have not been uniformly accurate predictors of recombinant
human GH (rhGH) treatment responses in children (3– 6).
We, therefore, questioned the accuracy of assessing GH secretion from changes in serum GH concentration. Accordingly, we evaluated the serum GH concentration dependence
on GH dose by direct simulation of GH secretory events and
frequent sampling for serum GH in 15 healthy, adult, somatostatin-infused subjects. The infused rhGH masses were
poorly estimated by deconvolution methods using fixed or
variable GH half-lives. Additionally, we found poor corre-
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BRIGHT ET AL.
lations between the infused rhGH masses and both measured
GH areas under the curve and maximum GH concentration
responses (GHmax) (7). We considered that variance in the
GH clearances and volumes of distribution between subjects
might nullify any simple relationship between secreted GH
mass and serum GH. The need for a new GH pharmacokinetic model to assess these parameters was suggested when
inspection of the post-rhGH infusion concentration data appeared to contain nonsuppressed basal and oscillatory GH
components. There were detectable GH concentrations at
time zero and oscillating GH concentrations persisting
throughout the 180-min study period. Indeed, several investigators have reported that pulsatile secretion is superimposed upon a low basal pattern of secretion that may be
oscillatory rather than episodic (8 –11). We postulated that
serum GH concentrations in our subjects reflected multiple
components of GH input and that accurate estimation of each
subject’s pharmacokinetic parameters would require a composite pharmacokinetic model to account for pulsatile (infused), basal, and oscillatory components.
Subjects and Methods
Patient studies
Fifteen healthy adult volunteer subjects participated. After obtaining
approval from the Nemours Childrens’ Clinic research committee and
the Baptist Medical Center institutional review committee, written informed consent was obtained from 11 women and 4 men. Seven of the
women were taking daily oral contraceptives containing 0.025– 0.040 mg
ethinyl estradiol. The ages averaged 22.6 6 2.6 yr (mean 6 sd), heights
averaged 167 6 8 cm, weights averaged 59.7 6 10 kg, and body mass
indexes averaged 21.0 6 2.0 kg/m2. All women tested negatively for
pregnancy (urinary hCGb test) in the hour before the study.
Clinical procedures
Endogenous GH secretion was suppressed by iv infusion of somatostatin (Octreotide, Sandoz Pharmaceuticals Corp., Hannover, NJ), 100
mg between 0700 – 0800 h and then 20 mg/h until the completion of the
study at 1700 h. No other medications were used during the study. The
subjects fasted after midnight, but had water ad libitum during the study
hours (0700 –1700 h). At 1100 and 1400 h, each subject received an iv
rhGH bolus containing either a low (0.44 6 0.05 mg/kg) or a high (1.2 6
0.3 mg/kg) dose. Plasma was sampled at 0, 2, 4, 6, 8, 9, 10, 12, 15, 20, 25,
30, 35, 40, 50, 60, 80, 100, 120, 150, and 180 min after the bolus dose was
begun at time zero. Blood was collected in ethylenediamine tetraacetate
tubes and separated at 4 C, and plasma samples were stored at 280 C
until assay. The rhGH used for infusions was therapeutic grade (Nutropin, Genentech, Inc., South San Francisco, CA). Baseline infusions
were performed with precalibrated syringe pumps (Razel Scientific Instruments, Stamford, CT), and bolus rhGH doses were administered
with Baxter AS40A syringe infusion pumps (Baxter Healthcare Corporation, Deerfield, IL). To obtain accurate measurements of the dose of
GH, we weighed the syringes containing the bolus materials on an
analytical balance before and after dose administration. The bolus doses
were administered as square wave (zero order) pulses over 8 min, the
duration of which was selected to mimic that of spontaneously occurring
GH secretory events (8).
Deconvolution studies
The deconvolution procedures included one- and two-compartment
fits with fixed or variable half-lives and volumes of distribution calculated from body surface area (12, 13). For the fixed half-lives, we used
estimates (3.5 min fast component; 20.9 min slow component; fractional
amplitude of slow component, 0.63) previously determined in GHRHstimulated and then somatostatin-suppressed adults (14).
FIG. 1. Scheme of the disposition of GH with different inputs of GH
according to one-compartment (top) and two-compartment (bottom)
models.
Pharmacokinetic model description
The scheme in Fig. 1 depicts the disposition of GH during and after
exogenous and endogenous input. Our model assumes that the only
source of endogenous input is a basal, oscillatory secretion of GH. Serum
GH concentrations (Cp) at various times (t) during and after the iv
infusion of rhGH were fitted using a one-compartment (Eq I) or a
two-compartment open model (Eq II) assuming elimination from the
central compartment (15). The latter compartmental assumption was
proposed previously (16).
Cp 5
Cp 5
R0(1 2 e2kTi) 2k(t 2 T )
i
e
VK
(I)
R0(l1 2 k21)(1 2 e2l1Ti) 2l (t 2 T )
R0(k21 2 lz)(1 2 e2lzTi) 2l (t 2 T
i
i
)1
)
(e 1
(e z
Vcl1(l1 2 lz)
Vclz(l1 2 lz)
(II)
R0 is the square wave infusion of a dose of rhGH over infusion time
T, K is the first order elimination rate constant of GH, and V is its
volume of distribution; the product, V 3 K, is the clearance of GH.
In the two-compartment model, k12 and k21 are the first order microconstants describing GH flux between the peripheral compartment and the volume of the central compartment (Vc). The first order
microconstant k10 describes irreversible elimination of GH. l1 and lz
are the first order macrorate constants describing distribution and
elimination of GH, respectively, and are related to the microconstants
by: l1 1 lz 5 k12 1 k21 1 k10 (15). It should be noted in Eq I and II
that during the infusion, t 5 Ti and that after the infusion ends, Ti
becomes a constant; the postinfusion time is t 2 Ti.
Endogenous serum concentrations of GH (CE) are:
SS D
CE 5 CB 1 ACBcos
D
2)
(t 2 tzero)
cycle
(III)
where CB is the basal concentration of GH (mesor), A is the amplitude
of the oscillation in serum GH concentrations and is expressed as a
fraction of CB, cycle (frequency) is the period of the oscillation, and tzero
is the shift of the peak time of the cycle (acrophase) (17). The application
of cosinor methods to solve problems involving circadian and other
rhythms is not new (17–19) and, hence, provides precedence for new
implementation in a model to determine the pharmacokinetics of a
hormone after the administration of a known unlabeled dose in the
presence of endogenous release. In preliminary studies, models were
formulated in which CB was fixed and time invariant. However, com-
COMPOSITE KINETIC MODEL OF GH
puter fits of the data were significantly inferior compared to the oscillatory model. Given the foregoing, the following equation was fitted to
serum GH:
C 5 Cp 1 CE
(IV)
using the computer program WinNonLin (WinNonlin, professional edition 1.5, Pharsight Corp., Palo Alto, CA).
The selection of a one- or two-compartment model was based on
visual examination of how well the fitted curve mimicked the observed
data, the reality and ses of the model parameters, and the Akaike
information criteria (20). The equation using a one-compartment open
model provided least square estimates and ses of six parameters: V, K,
CB, A, cycle, and tzero. The equation that used the two-compartment open
model provided estimates of eight parameters: Vc, l1, lz, k21, CB, A,
cycle, and tzero.
Calculation of derived pharmacokinetic parameters
The clearance (CL) of GH for the one-compartment model was: CL 5
V 3 K. CL from the two-compartment model was calculated by:
Cl 5 Vc 3 k10, where k10 5
l1 3 lz
k21
The volume of distribution at steady state (Vss) for the two-compartment
model (analogous to V of the one compartment model) is:
Vss 5 Vc 3 (1 1 k12/k21), where k12 5 l1 1 lz 2 k21 2 k10
A value for the mean endogenous secretion rate of GH (GHsec) was
estimated from GHsec 5 CB 3 CL.
3303
Statistical analyses
Multiple regression analyses (Statistica, StatSoft, Tulsa, OK) were
used to estimate any effects of time, dose, gender, body size, or GHBP
concentrations on the pharmacokinetic parameters. Values shown are
the mean 6 sd unless otherwise specified.
Results
The dependencies of deconvoluted GH mass, GHmax, and
GH-AUC on infused rhGH doses are shown in Fig. 2. These
GH secretion indexes are influenced by the clearance and
distribution volume of GH, and all showed considerable
scatter around the mean responses. The values of r2 were
0.55– 0.64. The amount of variance in the GH measurement
index not accounted for by the dose of rhGH was then 100 3
(1 2 r2), or 36 – 45%. The lack of uniform dependencies of GH
concentrations on rhGH doses suggested dissimilar values of
GH clearance and distribution volume in this subject group.
The uniformity of the dependence may have been degraded by the presence of endogenous GH secretion during
our sampling times. Serum GH concentrations were detectable in all subjects at time zero (0.24 6 0.34 ng/mL; range,
0.01–1.7 ng/mL) and persisted in oscillatory patterns
throughout the 180 min of sampling time, i.e. for greater than
10 half-lives after completion of the bolus rhGH dose. Examples are shown in Figs. 3 and 4. The finding of basal and
Evaluation of model
Eq IV employing either one or two compartments was fitted to serum
GH concentrations as a function of time. Serum concentrations of GH
were weighted in the fit using 1/y2, where y is the serum concentration.
A battery of statistical tools was used to evaluate our model (19). We
evaluated the precision of our model by examining the parameter coefficients of variation (quotient of the computer-generated se and mean
of each parameter estimate) and the univariate 95% confidence intervals
of each parameter estimate. The goodness of fit was evaluated by visual
inspection of how well the model-predicted line mimicked the GH
serum concentration vs. time data and by examining the coefficient of
correlation and the mean sd (S) of the fit. S is defined as the square root
of WRSS/df, where WRSS is the weighted residual sum of squares, and
df is the degrees of freedom. WRSS refers to summed vertical distances
between the model-predicted and observed GH serum concentrations,
and df is the difference between the number of GH concentration
observations and number of parameters in the model (6 for Eq I, 8 for
Eq II).
Parameter identifiability is the property of the model that concerns
the uniqueness of a set of parameters estimated by the model (19, 21, 22).
Parameter identifiability was assessed in three ways. First, the initial
estimates of the parameters were varied to determine whether model
parameters were stable. Secondly, we assessed the statistical independence of our parameter estimates by examining parameter correlations.
These correlations are provided by WinNonLin; values greater than 0.95
suggest that one parameter is dependent on another (19). Thirdly, our
model was fitted to serum GH concentration vs. time data that were
simulated at increasing CB values. We were interested in determining
the CB at which our model could no longer accurately capture other
model parameters.
Clinical assays
GH concentrations were assayed in an ultrasensitive chemiluminescence assay with a lower limit of detectability of 0.002 ng/mL as previously described (11). GHBP was assayed at the start of each procedure
in each subject and assayed in a previously described gel filtration assay
(23).
FIG. 2. The dependencies of deconvoluted GH mass, GH-AUC, and
GHmax to iv bolus doses of rhGH in 15 subjects. As expected, the value
of each of these indexes increases with increasing dose. The unexplained variance of 36 – 45% suggested that the dependencies were
nonuniform among these subjects.
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JCE & M • 1999
Vol 84 • No 9
FIG. 4. Comparison of model fits. Serum concentrations of GH at
various times during and after an 8-min infusion of rhGH for dose 2
in subject 9. The lines are model fitted using a one-compartment open
model (top) and a two-compartment open model (bottom). Parameters
for these fits are given in Table 2.
FIG. 3. The model-predicted (smooth lines) vs. observed serum GH
concentrations (open circles) are shown for four doses of rhGH. The
rhGH dose was given as a square wave (zero order) infusion over 8
min.
oscillatory GH concentrations at times when only 0.1% of the
rhGH dose would have remained in serum suggested an
endogenous source of GH secretion during our sampling
times. We, therefore, fit the GH concentration time series data
to a new pharmacokinetic model that discriminates pulsatile,
basal, and oscillatory components of GH secretion into
serum.
The model predicted serum GH concentrations well (Table
1 and Figs. 3 and 4). The fits of time vs. GH concentrations
had a range of correlation coefficients (r2) of 0.88 – 0.99; unexplained variance in the fits was then 1–12% (mean, 5%).
The precision of the parameters estimated by the model was
acceptable. Parameter coefficients of variation (CV) were
low, and 95% confidence intervals were narrow (Table 1).
Examination of a correlation matrix revealed no statistical
dependence among any of the parameter estimates (data not
shown).
In general, we obtained better fits with the two-compartment model, but at the expense of parameter precision. For example, fitting the two-compartment model to
serum GH concentrations from subject 9 provided a better
fit of the data than that obtained with the one-compartment model. The one-compartment model underestimated
GH concentrations during and just after the end the infusion and overestimated levels 25– 40 min after the start
of the infusion. In contrast, the two-compartment model
closely mimicked the serum concentration during and after rhGH administration (Fig. 4 and Table 2). This superior
fit afforded by the two-compartment model was evident
by the Akaike information criteria values (2117 vs. 2100)
and by the S values (0.0092 vs. 0.0146). However, parameter CV values were considerably higher and 95% confidence intervals wider (Table 2). The elimination half-life
obtained with the one-compartment model fit was a hybrid of the half-lives of distribution and elimination obtained with the two-compartment model fit. More importantly, GH clearances predicted by both models were
similar: 0.243 and 0.235 L/min for the one- and two-compartment model fits, respectively. Volumes of distribution
for the one- and two-compartment models were 3.8 and 3.9
L, respectively. Values for CB, cycle, and tzero were also
similar for the two models.
Figure 5 shows the serum GH concentration vs. time profile simulated using the pharmacokinetic parameters from
subject 1 and values of CB that were increased 10- and 100fold from an initial value of 0.042 to 0.42 and 4.2 ng/mL,
respectively. Fitting the two-compartment model to the simulated GH serum concentrations generated pharmacokinetic
parameters that were the same as our starting parameters.
We obtained different parameter estimates when CB values
were increased 1000-fold to 42 ng/mL. Yet the predicted
COMPOSITE KINETIC MODEL OF GH
3305
TABLE 1. Computed estimates of mean GH pharmacokinetic parameters and their precision for a single rhGH dose in four subjects
estimated by our one- and two-compartment models
Subject 1
Mean
V (L)
k (min21)
Vc (L)
1.87
l1 (min21)
0.157
21
k21 (min )
0.058
lz (min21)
0.0389
CB (ng/mL)
0.042
Amplitude
0.766
Cycle (min) 102
Tzero (min)
53
CV
6
11
12
6.3
13
12
10
23
Subject 6
CI
1.6–2.1
0.12– 0.19
0.04– 0.97
0.03– 0.04
0.03– 0.05
0.55– 0.98
80–124
27–79
Subject 8
Mean
CV
CI
Mean
CV
1.41
0.093
7.7
5.0
1.2–1.6
0.08– 0.10
2.80
0.082
9
8.8
0.400
0.687
95
71
7.8
7.8
3.6
3.2
0.17– 0.23
1.35
1.1–1.6
0.70
87–102 103
66–75
15
7.3
8.8
2.8
22
Subject 13
CI
Mean
2.2– 4.3
0.07– 0.10
1.75
0.092
1.13–1.56
0.035
0.56– 0.83
1.27
97–110 140
7.5–22
58
CV
CI
12
9
1.3–2.2
0.08– 0.11
16
24
7.9
9.5
0.02– 0.05
0.6–1.0
116–160
46–70
CV, Coefficient of variation, SE/mean; CI, univariate 95% confidence intervals.
The rhGH doses for these subjects were: subject 1, 85 mg; subject 6, 66.5 mg; subject 8, 101 mg; and subject 13, 21.8 mg.
TABLE 2. Comparison of GH pharmacokinetic parameters estimated from fitting the one- and two-compartment models to the serum GH
concentration time profiles in subject 9
One-compartment model
Parameter
V (L)
K (min21)
Vc (L)
l1 (min21)
k21 (min21)
lz (min21)
CB (ng/mL)
Amplitude
Cycle (min)
Tzero (min)
Two-compartment model
Mean
CV
CI
3.79
0.064
10
6.2
3.0– 4.6
0.06– 0.07
0.73
0.88
136
99
17
9.3
4.0
3.0
0.02– 0.05
1.4–2.1
123–148
93–106
Mean
CV
CI
2.93
0.133
0.070
0.043
0.037
0.84
116
107
11
50
92
54
192
40
88
40
2.2–3.6
0.072– 0.212
0.043– 0.973
0.007– 0.09
0.012– 0.091
0.11–1.6
109–341
13–200
CV, Coefficient of variance (SD/mean); CI, univariate 95% confidence limit.
FIG. 5. Effects of increasing basal GH concentrations on model fits.
Simulated serum concentrations of GH at various times during and
after an 8-min infusion of rhGH in subject 1 using basal concentrations at 10 times (open squares) and 100 times (open circles) the
observed value of 0.042 ng/mL.
clearance of GH remained within 10% of the true clearance
even at these relatively high CB values. Although not
shown, varying the initial estimates had little effect on the
final estimates of Vc, l1, lz, or k21, suggesting that our
model is capable of accurately capturing the pharmacokinetic parameters of GH after the administration of rhGH,
and that these parameters are stable. Varying initial estimates of CB, amplitude, cycle, and/or tzero had little effect
on derived parameter of clearance or volume of distribution of GH.
Pharmacokinetics of GH
The pharmacokinetic and cosinor parameters are shown
in Table 3. Mean values for each subject’s two doses are
given because, except for clearance and CB (see below),
there were no differences in parameters between doses 1
and 2. The ranges in GH pharmacokinetic parameters in
the 15 subjects were: clearance, 0.131– 0.469 L/min; volume of distribution, 1.4 –3.9 L; and terminal half-lives,
6.87–24.4 min. The ranges of the cosinor parameters were:
basal concentration (CB), 0.024 – 0.331 ng/mL; amplitude,
0.06 –1.67; cycle 79 –191 minutes; and time shift (acrophase), 13–116 min. There were no significant differences in Vss, clearance, or half-lives by gender or estrogen
treatment group. In this group of subjects, clearance, Vss,
and elimination rate constants showed no significant dependence upon weight, height, body mass index, or surface area. The comparison of parameters for the two doses
was assessed by multiple regression analysis using dose
amount and dose number as the independent variables.
These analyses revealed a decrease in clearance (0.260 6
0.9 vs. 0.214 6 0.06 L/min; P , 0.03) and an increase in CB
(0.200 6 0.22 vs. 0.33 6 0.33 ng/mL; P , 0.05) during the
second dose of rhGH. By multiple regression analysis, the
differences were due to the dose number (i.e. dose 1 vs.
dose 2) more than to dose amount, suggesting that there
may be a temporal intrasubject variance in these parameters. In contrast, no differences (P . 0.05) between dose
1 and dose 2 were found for Vss (3.73 6 1.6 vs. 3.31 6 1.41
L) or the elimination rate constant, lz (0.0661 6 0.035 vs.
0.0603 6 0.022 min21).
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BRIGHT ET AL.
TABLE 3. The pharmacokinetic and cosinor parameters in the 15 adult subjects
Subject no.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Mean
CV (%)
Clearance
(L/min)
Half-life
(min)
Vol (L)
CB
(ng/mL)
Amplitude
Cycle (min)
T0
(min)
0.230
0.308
0.129
0.208
0.194
0.209
0.213
0.225
0.339
0.246
0.219
0.343
0.197
0.258
0.227
17.3
11.8
11.1
7.66
13.5
7.11
9.40
11.7
14.4
24.4
17.3
6.87
10.1
12.2
9.4
3.48
3.19
3.62
2.05
3.13
2.12
2.89
2.77
5.46
5.38
4.19
3.80
2.42
4.36
3.05
0.024
0.221
0.315
0.701
0.054
0.315
0.237
0.072
0.034
0.029
0.331
0.268
0.084
0.164
0.414
1.67
0.404
0.315
0.702
1.10
0.682
0.667
0.568
0.456
1.16
0.571
1.21
0.603
0.930
0.333
92.5
85.1
115
140
92.0
110
118
78.5
143
93.8
96
161
139
191
151
26.4
54.3
80.2
86.8
95.1
56.6
74.4
45.0
116
7.74
55.8
73.7
32.1
87.3
13.0
0.236
24.1
12.3
36.7
3.46
30.1
0.218
84.8
0.758
50.4
121
26.9
60.3
53.6
With two exceptions, (clearance and CB; see text), no differences in parameters were noted between dose 1 and dose 2; therefore, the reported
values are mean values of two doses in each subject (6coefficient of variance: CV 5 SD/mean).
Effects of GH-binding protein (GHBP)
GHBP concentrations were higher in estrogen-treated subjects (1.29 6 0.24 vs. 0.76 6 0.14 nmol/L; P , 1026). A
tendency for increased Vss with increasing levels of GHBP
was noted, but the relationship fell short of statistical significance (P 5 0.06). There were no significant correlations
between GHBP concentrations and clearances, plasma elimination rate constants, CB, amplitude, cycle, or tzero. With
increasing concentrations of GHBP and when adjusted for
dose, there were increases in GHmax (P , 0.037) and GHAUC (P , 0.048).
Discussion
The results of GH stimulation tests remain an integral part
of the decision process leading to rhGH treatment. The evaluation of GH treatment registries, however, suggests that the
GH concentration response to provocative stimulation may
lack sensitivity and specificity as a treatment outcome predictor (3– 6). Several potential reasons for this are discussed
in a recent review (24). Here we specifically question why
stimulated serum GH concentrations are poor predictors. Is
it because they fail to uniformly estimate the mass of GH that
causes the concentration changes and, thereby, are inadequate indicators of the ability of the pituitary to release GH?
Indeed, we have found a nonuniform dependence of GHmax,
GH-AUC, and deconvoluted GH mass on the dose of rhGH
infused in our subjects. This lack of similar dependencies is
best explained by significant intra- and intersubject variances
in GH clearances (CV 5 24%) and distribution volumes
(CV 5 30%). From this, we infer that any given GH concentration cut-off point will reflect different GH secretion in
different subjects and thus obscure the interpretation of a GH
stimulation test. This finding detracts from the validity of
such interpretations, but suggests that the relationship between secreted GH mass and serum GH concentrations could
be more accurately known with the use of subject-specific
pharmacokinetic parameters. Additionally, we have learned
that the actual serum GH response to a simulated GH se-
cretory event is best explained by a model that not only
includes the known GH pulse but also provides for basal and
oscillatory GH inputs.
Visual examination of serum GH concentration vs. time
profiles at times before and after the rhGH bolus dose revealed the presence of endogenous, oscillating GH concentrations. Multiple, contemporaneous components of GH input into the serum can confound the estimates of GH
pharmacokinetic parameters when using models allowing
for only single GH inputs. To obtain accurate estimates we
formulated a composite model that discriminates pulsatile,
basal, and oscillatory GH inputs and used it to fit the GH
concentration-time profiles in our subjects. The examples
given in Table 1 and Figs. 2 and 3 indicate that our model fit
the observed serum GH concentration vs. time data quite
well. The correlation coefficients (r2) for the fits ranged between 0.88 – 0.99. The models generated stable parameters
with acceptable precision and relatively narrow 95% confidence intervals. The parameters were not interdependent.
Despite increasing basal concentrations by 100-fold, the
model still accurately captured the other model parameters,
thus suggesting that our model is stable.
A main goal was to develop a model that enabled us to
obtain accurate estimates of the pharmacokinetics of GH
from exogenous administration of rhGH. As we did not
administer a labeled dose of rhGH, we cannot unequivocally
determine the accuracy of the pharmacokinetic parameters
estimated by our model. However, our model predictions are
in excellent agreement with GH parameters published previously. GH clearances from the 30 individual GH boluses
ranged from 0.131– 0.469 L/min, with a mean overall value
of 0.236 L/min, similar to that reported with radioisotopic
and nonisotopic methods using bolus or continuous GH
infusions (16, 25–30). Likewise, the volumes of distribution
(Vd) ranged between 1.4 –3.9 L (mean, 3.46 6 1.5 L) and were
also in good agreement with published values. We therefore
conclude that the use of our model can provide useful estimates of the pharmacokinetics of GH in the presence of basal,
COMPOSITE KINETIC MODEL OF GH
oscillating endogenous concentrations without administering a dose of radiolabeled GH.
Elimination half-lives in this study ranged between 6.7–
25.1 min. The mean half-life was 12.3 6 4.5 min. These
values span those previously reported (8, 14, 27, 30, 31).
The half-lives were model dependent. That is, GH halflives calculated from the one-compartment model were
shorter than those calculated from the terminal slope of the
two-compartment model. Half-lives calculated from the
elimination rate constant, K, for a one-compartment model
are probably hybrids of the half-lives of distribution and
elimination of the two-compartment model. This raises the
question of whether and when to use one or two compartments when fitting serum GH concentration vs. time
data. The importance of fitting the one- vs. the two-compartment model to fit serum GH concentration vs. time
data depends upon the question asked. To accurately estimate the mass of GH secreted during a pulse or after the
administration of a GH secretagogue, one has to know the
clearance. Therefore, so long as clearance is accurately
estimated, either model can be used.
Although early studies favored the idea that interpulse
secretion rates of GH fall to zero (8), more recent studies have
a basal, oscillatory secretion rate (9 –12). Thus, our model is
consistent with recent studies regarding GH secretion in
humans, as monitored during this short term study. The
detection of endogenous GH release during the somatostatin
infusion and after the administration of rhGH was unexpected and raises several important questions. Is the basal,
oscillatory pattern of GH secretion a consequence of administering insufficient doses of somatostatin? Does somatostatin preferentially suppress the secretion of episodic pulses of
GH secretion, but suppress to a lesser degree the basal, oscillating pattern? We favor the latter explanation because of
earlier studies using somatostatin infusions (32) and because
we found no evidence of clearly pulsatile secretion of GH in
any of our subjects during the duration of the study. However, the mean periodicity of 121 min approximates that of
endogenous GH pulsatility, about 90 min (8), thus allowing
the speculation that these oscillations represent dampened
GH pulse frequency and amplitude due to somatostatin infusion and/or GH autonegative feedback (33). What are the
origin and regulation of this basal, oscillating pattern of GH
secretion, and is it physiologically relevant? What neural
pathways might subserve this secretion? Finally, what patterns of GH secretion continue in patients receiving GH
replacement? These questions may be addressed using the
present composite pharmacokinetic model.
We assessed the effects of GHBP on the GH concentration
responses to rhGH bolus infusions. The peak serum GH
concentration was also found to be directly related to the
GHBP concentration. This finding is in general agreement
with our previous studies with cortisol (1, 2). Similarly,
plasma GH responses to computer-modeled secretory events
are also GHBP concentration dependent (34). The dissociation constants indicate that at physiological concentrations
the majority of cortisol (35, 36) and GH (37, 38) is bound to
their respective binding proteins. The mechanism(s) by
which binding proteins may affect the disposition of secreted hormone remains unclear. The half-life of bolus-
3307
injected cortisol is directly related to the corticosteroidbinding globulin (CBG) concentration (2). CBG, therefore,
increases the mean plasma residence time of cortisol. We
find no relationship here between the half-life of GH and
the GHBP concentration. Rather, a weak and not quite
statistically significant (P 5 0.06) increase in the steady
state GH volume of distribution was noted with increasing
GHBP concentrations. GHBP is the proteolytically cleaved
extracellular domain of the GH receptor (39), whereas CBG
is not known to reflect any portion of the glucocorticoid
receptor or uptake pathway. We postulate that GHBP is a
marker of GH receptor activity in the liver and other
tissues. Accordingly, high plasma GHBP concentrations
probably reflect greater GH receptor availability in various target/uptake tissues, with consequently greater uptake and immediate removal of GH from the blood space.
This apparent loss of GH from plasma by receptor uptake,
as correlated to and reflected by high GHBP levels, would
tend to expand the apparent Vss and thereby produce a
positive correlation between apparent GH Vss after injection and GHBP. In contrast, higher amounts of CBG simply
increase the amount of cortisol retained in the plasma
space and decrease the apparent distribution space for
cortisol. In the rat, coinjection of GH and GHBP decreases
the apparent distribution volume for GH, at least in experiments in which GH was prebound to GHBP and was
thereby less able to distribute to those GH receptors
and/or other uptake tissues available at the time (40, 41).
The present study was conducted in healthy young adults.
The results suggest that the relationships between secreted
GH and serum GH profiles are dissimilar among subjects,
and that the dissimilarities are most likely due to variances
in GH clearance and distribution volumes. The relationship
between secreted GH mass and serum GH concentration is
best elucidated with a pharmacokinetic model capable of
discerning pulsatile, basal and oscillatory inputs and by the
use of subject-specific pharmacokinetic parameters. If further
evaluation were also to suggest a diurnal, or other, variability
in GH clearance, then subject- and time-specific parameters
would be required as well. Further investigation is required
to understand how basal and oscillatory GH parameters may
change with time, GH pulses, age, various levels of GH
sufficiency, and hepatic or renal disorders; in subjects with
the everwidening spectrum of GH insensitivity syndromes
(42); or with the use of hormonal or other medicinal
therapies.
The presence of basal, oscillating, and pulsatile GH inputs
and the wide range of intra- and intersubject variance in GH
pharmacokinetic parameters negate the assumption of a uniform relationship between GH secretion and serum GH concentration and detracts from the utility of a GH concentration
cut-off point in GH testing. These findings have implications
for the valid appraisal of GH deficiency states, selection of
rhGH treatment candidates, and physiological regulation of
the GH axis.
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