Journal Club
Defronzo RA, Burant CF, Fleck P, Wilson C, Mekki Q, Pratley RE.
Efficacy and Tolerability of the DPP-4 Inhibitor Alogliptin Combined with
Pioglitazone, in Metformin-Treated Patients with Type 2 Diabetes.
J Clin Endocrinol Metab. 2012 Mar 14. [Epub ahead of print]
Tura A, Pacini G, Kautzky-Willer A, Gastaldelli A, DeFronzo RA, Ferrannini E,
Mari A.
Estimation of prehepatic insulin secretion: comparison between standardized
C-peptide and insulin kinetic models.
Metabolism. 2012 Mar;61(3):434-43. Epub 2011 Sep 23.
2012年4月12日 8:30-8:55
８階 医局
埼玉医科大学 総合医療センター 内分泌・糖尿病内科
Department of Endocrinology and Diabetes,
Saitama Medical Center, Saitama Medical University
松田 昌文
Matsuda, Masafumi
Key words:
Proinsulin/insulin ratio
ISR: insulin secretion rate
J Clin Endocrin Metab. First published ahead of print March 14, 2012 as doi:10.1210/jc.2011-2243
(J Clin Endocrinol Metab 97: 0000– 0000, 2012)
Abbreviations:
A12.5 and A25, Alogliptin at doses of 12.5 and 25 mg;
A12.5_P and A25_P, A12.5 and A25 plus any dose of pioglitazone;
AE, adverse event;
ANCOVA, analysis of covariance;
BG, blood glucose;
BMI, body mass index;
DPP-4, dipeptidyl-peptidase- 4;
FPG, fasting plasma glucose;
HbA1c, glycosylated hemoglobin;
HOMA-B, homeostasis model assessment of _-cell function;
HOMA-IR, homeostasis model assessment of insulin resistance;
LSM_, least-squares mean change;
OAD, oral antidiabetic drug;
P15, P30, and P45, pioglitazone at doses of 15, 30 and 45 mg;
PI:IRI, proinsulin-to-insulin ratio;
Pio alone, pioglitazone alone;
SAE, serious AE;
ZD, thiazolidinedione.
Context: Optimal management of type 2
diabetes remains an elusive goal.
Combination therapy addressing the core
defects of impaired insulin secretion and
insulin resistance shows promise in
maintaining glycemic control.
Objective: The aim of the study was to
assess the efficacy and tolerability of
alogliptin combined with pioglitazone in
metformin-treated type 2 diabetic patients.
Design, Setting, and Patients: We conducted a multicenter,
randomized, double-blind, placebo-controlled, parallel-arm
study in patients with type 2 diabetes.
Interventions: The study consisted of 26-wk treatment with
alogliptin (12.5 or 25 mg qd) alone or combined with
pioglitazone (15, 30, or 45 mg qd) in 1554 patients on stabledose metformin monotherapy (≧1500 mg) with inadequate
glycemic control.
Main Outcome Measure: The primary endpoint was change
in glycosylated hemoglobin (HbA1c) from baseline to wk26.
Secondary endpoints included changes in fasting plasma
glucose and β-cell function. Primary analyses compared
pioglitazone therapy [all doses pooled, pioglitazone alone
(Pio alone); n = 387] with alogliptin 12.5 mg plus any dose of
pioglitazone (A12.5＋P; n = 390) or alogliptin 25 mg plus any
dose of pioglitazone (A25＋P; n = 390).
This trial (NCT00328627) is registered with www. ClinicalTrials.gov.
Disclosure Summary: R.A.D. has been on speakers’ bureaus for Takeda
Pharmaceuticals, Amylin, and Eli Lilly & Co.; has consulted for Takeda,
Amylin Pharmaceuticals, Eli Lilly&Co., Roche Pharmaceuticals, Novartis
Pharmaceuticals, Bristol-Myers Squibb, Johnson & Johnson, and ISIS;
and has received research support from Takeda, Amylin
Pharmaceuticals, Eli Lilly & Co., Novartis Pharmaceuticals, and BristolMyers Squibb. C.F.B. receives a consultation fee from Takeda. P.F. and
C.W. are employees of Takeda Global Research & Development Center,
Inc. Q.M. is an employee of Takeda Global Research & Development
Center, Inc. and owns stock in Takeda Pharmaceutical Co. R.E.P. has
received research grants from and participated in clinical trials for
Takeda, GlaxoSmithKline, Novartis, Novo Nordisk, Merck, MannKind,
Roche, Lilly, and Sanofi-Aventis. He is on the consulting and advisory
boards of Takeda, Glaxo- SmithKline, Novartis, Roche, and
NovoNordisk. He owns stock in Novartis.
FIG. 1. LSMΔ (±SE) from
baseline to last observation
in HbA1c (A) and FPG (B) in
patients receiving placebo or
increasing doses of
pioglitazone (open bars), or
pioglitazone in combination
with A12.5 (stippled bars) or
A25 (closed bars) (n ＝ 122
to 130 patients per group).
***, P ≦ 0.001 vs. both
component therapies.
FIG. 2. LSMΔ (±SE) from
baseline to last
observation in fasting
PI:IRI (A), HOMA-B (B)
and HOMA-IR (C) (n ≧
340 in each pooled group).
**, P ＜ 0.01; ***, P ＜
0.001, vs. Pio alone; for
HOMA-IR, differences
between either
combination group and Pio
alone were not statistically
significant.
Results: When added to metformin, the least squares mean
change (LSMΔ) from baseline HbA1c was ー0.9 ± 0.05% in
the Pio-alone group and ー1.4 ± 0.05% in both the A12.5＋
P and A25＋P groups (P ＜ 0.001 for both comparisons).
A12.5＋P and A25＋P produced greater reductions in fasting
plasma glucose (LSMΔ ＝ ー2.5 ± 0.1 mmol/liter for both)
than Pio alone (LSMΔ ＝ ー1.6 ± 0.1 mmol/liter; P ＜ 0.001).
A12.5＋P and A25＋P significantly improved measures of βcell function (proinsulin:insulin and homeostasis model
assessment of β-cell function) compared to Pio alone, but
had no effect on homeostasis model assessment of insulin
resistance. The LSM_ body weight was 1.8 ± 0.2, 1.9 ± 0.2,
and 1.5 ± 0.2 kg in A12.5＋P, A25＋P, and Pio-alone groups,
respectively. Hypoglycemia was reported by 1.0, 1.5, and
2.1% of patients in the A12.5＋P, A25＋P, and Pio-alone
groups, respectively.
Conclusions: In type 2 diabetic
patients inadequately controlled by
metformin, the reduction in HbA1c by
alogliptin and pioglitazone was additive.
The decreases in HbA1c with A12.5+P
and A25+P were similar. All treatments
were well tolerated.
Message
米国ではまだ未承認なのだが．．．
ただalogliptin とpioglitazoneを併用するときは
pioglitazoneは15mgでよさそう。
Diabetes 58:1595–1603, 2009
FIG. 1. Concentrations of glucose (A),
insulin (B), and C-peptide (C) in eight
individuals with NGT (□), 14
individuals with IFG and/or IGT (◇),
and 11 patients with diabetes (△) after
oral ingestion of 75 g glucose. Data are
the means _ SE. Statistics were carried
out using repeated-measures ANOVA
and denote differences between the
experiments (A), differences over time
(B), and differences due to the
interaction of experiment and time (AB).
*Significant (P <0.05) differences vs.
control subjects at individual time
points (one-way ANOVA and Duncan’s
post hoc test).
-5,0,15,30,60,90,120,150,180,210,240 min
Diabetes 58:1595–1603, 2009
AIM
Our aim was to compare
traditional C-peptide–based
method and insulin-based
method with standardized kinetic
parameters in the estimation of
prehepatic insulin secretion rate
(ISR).
METHOD
One-hundred thirty-four subjects with varying degrees of
glucose tolerance received an insulin-modified
intravenous glucose tolerance test and a standard oral
glucose tolerance test with measurement of plasma
insulin and C-peptide. From the intravenous glucose
tolerance test, we determined insulin kinetics
parameters and selected standardized kinetic
parameters based on mean values in a selected
subgroup. We computed ISR from insulin concentration
during the oral glucose tolerance test using these
parameters and compared ISR with the standard Cpeptide deconvolution approach. We then performed the
same comparison in an independent data set (231
subjects).
Subjects: Vienna and San Antonio data sets
Calculation of insulin kinetic parameters from the IVGTT
where ⊗ is the convolution operator. This approach involves
an approximation, as it assumes that the time-varying hepatic
insulin fractional extraction, 1 − F(t), affects the peripheral
insulin delivery (through F[t]ISR[t]), but not insulin clearance
and h(t) (see “Discussion” for further comments).The insulin
kinetic impulse response was represented using the 2exponential function:
where ClINSPE is the peripheral (posthepatic) insulin
clearance andWis the relative contribution of the first
exponential term to the clearance (as the term in parentheses
has unit integral and W is the fraction due to the first
exponential).
Because the exogenous insulin infusion IINF(t) is known (1minute infusion of known dose at 20 minutes of the IVGTT) and
the prehepatic insulin secretion ISR(t) can be calculated fromCpeptide deconvolution using the method by Van Cauter et al [5],
it is possible to estimate the parameters of h(t) and F(t) from the
plasma insulin concentration by using least squares, with the
addition of a regularization term to obtain a smooth F(t)
(represented as a piecewise-linear function of time).
the insulin kinetic impulse response used for deconvolution of
the plasma insulin curve is the function:
Fig. 1 – Insulin secretion
from the plasma C-peptide
concentration during the
IVGTT in the Vienna data
set (mean ± SE); the inset
shows insulin secretion
during the first 20 minutes
from plasma C-peptide
(solid, thin line) and from
plasma insulin, with
individual kinetic
parameters (dashed line)
and mean kinetic
parameters (solid, thick
line) (top). Pattern of F(t)
parameter during the
IVGTT in the Vienna data
set (mean ± SE) (bottom).
Calculation of insulin secretion from OGTT plasma insulin values in the Vienna
data set and parameter determination for the standardized insulin kinetic model
Fig. 2 – Insulin secretion from
plasma C-peptide (dashed line)
and plasma insulin (solid line) in
the Vienna data set (top).
Plasma insulin concentration is
also reported (bottom). Data are
mean ± SE.
Fig. 3 – Basal (top panels) and total (bottom panels) insulin secretion from plasma Cpeptide and insulin concentrations in the subjects from the Vienna data set. The left
panels show the correlations (regression equations are reported); the right panels show
the corresponding Bland-Altman plots.
Fig. 4 – Insulin secretion
from plasma C-peptide
(dashed line) and plasma
insulin (solid line) in the San
Antonio data set (top).
Plasma insulin concentration
is also reported (bottom).
Data are mean ± SE.
Fig. 5 – Basal (top panels) and total (bottom panels) insulin secretion from plasma Cpeptide and insulin concentrations in the subjects from the San Antonio data set. The
left panels show the correlations (regression equations are reported); the right panels
show the corresponding Bland-Altman plots. Subjects are divided into diabetic (circle)
and nondiabetic (square) groups.
RESULTS
In the first data set, total ISRs from insulin and C-peptide
were highly correlated (R2 = 0.75, P < .0001), although
on average different (103 ± 6 vs 108 ± 3 nmol, P
< .001). Good correlation was also found in the second
data set (R2 = 0.54, P < .0001). The insulin method
somewhat overestimated total ISR (85 ± 5 vs 67 ± 3
nmol, P = .002), in part because of differences in insulin
assay. Similar results were obtained for fasting ISR.
Despite the modest bias, the insulin and C-peptide
methods were consistent in predicting differences
between groups (eg, obese vs nonobese) and
relationships with other physiological variables (eg, body
mass index, insulin resistance).
CONCLUSION
The insulin method estimated first-phase
ISR peak similarly to the C-peptide method
and better than the simple use of insulin
concentration. The insulin based ISR
method compares favorably with the Cpeptide approach. The method will be
particularly useful in data sets lacking Cpeptide to assess β-cell function through
models requiring prehepatic secretion.
Message
日本ではインスリン分泌は血中濃度をよく用い
るが、海外の文献では直接膵臓からの分泌率で
表示する。そのための研究が日本ではほとんど
行われていない。
C-peptideを測定し肝臓でトラップされない膵臓
からのインスリン分泌率を計算するのであるが、
インスリンからでも計算できそうである。
問題は日本人にその方法があてはまるかどうか
…