Journal Club 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 2012 年 4 月 12 日 8:30-8:55 ８階 医局 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 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 Mar;61(3): Epub 2011 Sep 23.

Key words: Proinsulin/insulin ratio ISR: insulin secretion rate

(J Clin Endocrinol Metab 97: 0000– 0000, 2012) J Clin Endocrin Metab. First published ahead of print March 14, 2012 as doi: /jc

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 stable- dose 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 (NCT ) 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 Bristol- Myers 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 ≦ 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 ＜ 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 β- cell 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。

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 C- peptide deconvolution approach. We then performed the same comparison in an independent data set (231 subjects).

Subjects: Vienna and San Antonio data sets

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 2- exponential 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). Calculation of insulin kinetic parameters from the IVGTT

Because the exogenous insulin infusion IINF(t) is known (1- minute infusion of known dose at 20 minutes of the IVGTT) and the prehepatic insulin secretion ISR(t) can be calculated fromC- peptide 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 C- peptide 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 C- peptide 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 C- peptide approach. The method will be particularly useful in data sets lacking C- peptide 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 …