Journal Club

1. Journal Club 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. 2011 Sep 22. [Epub ahead of print] Neuman J, Korenstein D, Ross JS, Keyhani S. Prevalence of financial conflicts of interest among panel members producing clinical practice guidelines in Canada and United States: cross sectional study. BMJ. 2011 Oct 11;343:d5621. doi: 10.1136/bmj.d5621. 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 2011年10月20日8:30-8:55 ８階　医局

3. doi:10.1016/j.metabol.2011.08.001

4. 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). 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.

5. METHOD 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).

6. Calculation of insulin kinetic parameters from the IVGTT in the Vienna data set The posthepatic insulin delivery, ISRPE(t), is a fraction of prehepatic insulin secretion, ISR(t); that is, ISRPE(t) = F(t)ISR(t), with F(t) between 0 and 1. We described insulin kinetics with a linear model relating the plasma insulin concentration to peripheral insulin appearance, that is, the sum of exogenous insulin infusion, IINF(t), and posthepatic insulin delivery, ISRPE(t). Thus, insulin concentration, IC(t), is the convolution of the impulse response of the linear insulin kinetic model, h(t), and IINF(t) + F(t)ISR(t): where ⊗ is the convolution operator. 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).

9. 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).

10. 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.

11. 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.

12. 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.

13. 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.

15. 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 vsnonobese) and relationships with other physiological variables (eg, body mass index, insulin resistance). The insulin method estimated first-phase ISR peak similarly to the C-peptide method and better than the simple use of insulin concentration.

16. CONCLUSION 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.

17. Message/Comments インスリン分泌の測定では、 ISR がよい 血中インスリン濃度やC-peptide濃度で議論するのは日本くらい？

20. Objective To determine the prevalence of financial conflicts of interest among members of panels producing clinical practice guidelines on screening, treatment, or both for hyperlipidaemia or diabetes.

21. Design Cross sectional study. Setting Relevant guidelines published by national organisations in the United States and Canada between 2000 and 2010. Participants Members of guideline panels. Main outcome measures Prevalence of financial conflicts of interest among members of guideline panels and chairs of panels.

22. Table 1| Clinical practice guidelines for diabetes and hyperlipidaemia: panel members’ conflicts of interest (COI)*. Values are numbers (percentages) unless stated otherwise

23. NA=no panel chair identified; VA/DoD=Veterans Administration/Department of Defense. *Defined as direct compensation of guideline author by drug company in form of grants, speakers’ fees, honorariums, consultant/adviser/employee compensation, and stock ownership 2 years before and including year of guideline release. †Classified exactly as listed on National Guidelines Clearinghouse website, except for Canadian Diabetes Association and Canadian Cardiovascular Association, which were not included on website; designations of US organisations most similar to them used—American Diabetes Association and American Heart Association. ‡Canadian guidelines. §Drug company sponsors included GlaxoSmithKline, Novo, Sanofi, Servier Canada, Astra Zeneca, Bayer, Eli Lilly, Merck, Pfizer, and Hoffman-LaRoche, although document states that none of the authors was compensated in any way. ¶Drug company sponsors included Abbott Laboratories, Bayer, Bristol-Myers Squibb, KOS Pharmaceuticals, Merck, Parke-Davis Pharmaceuticals, and Sankyo Parke-Davis. **Other sponsoring organisations included councils on cardiovascular nursing, arteriosclerosis, thrombosis, vascular biology, basic cardiovascular sciences, cardiovascular disease in the young, clinical cardiology epidemiology and prevention, nutrition, physical activity and metabolism, and stroke and Preventive Cardiovascular Nurses Association. ††No official COI document in guideline, but one author was noted to have been excused from voting because of his employment at Merck Pharmaceuticals. No commercial

25. Of the 211 panellists who had an opportunity to publicly declare COI, 73 stated that they had no COI, among whom 11% (n=8) had undeclared COI identified through our search strategy (fig 1). All 73 panel members received speakers’ fees, honorariums, or employee/adviser/consultancy payments or held stock ownership. Among the 77 panel members who did not have an opportunity to publicly declare COI, we found 5% (4) to have COI through our search strategy (fig 1). Of the 12 undeclared COI, we found one through our Google search and the remainder through our Medline search. In summary, among 288 members of guideline panels, 52% (n=150) had COI, of which 138 were declared and 12 undeclared. Four undeclared conflicts were among panel members of guidelines without an opportunity to declare COI.

26. Results Fourteen guidelines met our search criteria, of which five had no accompanying declaration of conflicts of interest by panel members. 288 panel members had participated in the guideline development process. Among the 288 panel members, 138 (48%) reported conflicts of interest at the time of the publication of the guideline and 150 (52%) either stated that they had no such conflicts or did not have an opportunity to declare any. Among 73 panellists who formally declared no conflicts, 8 (11%) were found to have one or more. Twelve of the 14 guideline panels evaluated identified chairs, among whom six had financial conflicts of interest. Overall, 150 (52%) panel members had conflicts, of which 138 were declared and 12 were undeclared. Panel members from government sponsored guidelines were less likely to have conflicts of interest compared with guidelines sponsored by non-government sources (15/92 (16%) v 135/196 (69%); P<0.001).

27. Conclusions The prevalence of financial conflicts of interest and their under-reporting by members of panels producing clinical practice guidelines on hyperlipidaemia or diabetes was high, and a relatively high proportion of guidelines did not have public disclosure of conflicts of interest. Organisations that produce guidelines should minimise conflicts of interest among panel members to ensure the credibility and evidence based nature of the guidelines' content.

28. Message/Comments 2000-10年発行の脂質異常症または糖尿病治療ガイドラインの委員会メンバーを対象に、金銭的利害対立の発生率を横断的研究で調査。ガイドライン作成に関わった288人中150人が金銭的利害対立を有しており、その中の138人は対立を報告、12人は未報告だった。比較的多くのガイドラインで利益相反に関する情報公開をしていなかった。 日本の糖尿病治療ガイドラインのメンバーは？ ただしCOIのないメンバーだと医療コストを安くする選択のみをする可能性があるかもしれない。（private opinion）