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Items: 1 to 20 of 42

1.

The lack of utility of circulating biomarkers of inflammation and endothelial dysfunction for type 2 diabetes risk prediction among postmenopausal women: the Women's Health Initiative Observational Study.

Chao C, Song Y, Cook N, Tseng CH, Manson JE, Eaton C, Margolis KL, Rodriguez B, Phillips LS, Tinker LF, Liu S.

Arch Intern Med. 2010 Sep 27;170(17):1557-65. doi: 10.1001/archinternmed.2010.312.

2.

Prediction models for incident type 2 diabetes mellitus
in the older population: KORA S4/F4 cohort study.

Rathmann W, Kowall B, Heier M, Herder C, Holle R, Thorand B, Strassburger K, Peters A, Wichmann HE, Giani G, Meisinger C.

Diabet Med. 2010 Oct;27(10):1116-23. doi: 10.1111/j.1464-5491.2010.03065.x.

PMID:
20854378
3.

Several methods to assess improvement in risk prediction models: extension to survival analysis.

Chambless LE, Cummiskey CP, Cui G.

Stat Med. 2011 Jan 15;30(1):22-38. doi: 10.1002/sim.4026.

PMID:
20827726
4.

Associations between leptin and the leptin / adiponectin ratio and incident Type 2 diabetes in middle-aged men and women: results from the MONICA / KORA Augsburg study 1984-2002.

Thorand B, Zierer A, Baumert J, Meisinger C, Herder C, Koenig W.

Diabet Med. 2010 Sep;27(9):1004-11. doi: 10.1111/j.1464-5491.2010.03043.x.

PMID:
20722673
5.

Improvement of risk prediction by genomic profiling: reclassification measures versus the area under the receiver operating characteristic curve.

Mihaescu R, van Zitteren M, van Hoek M, Sijbrands EJ, Uitterlinden AG, Witteman JC, Hofman A, Hunink MG, van Duijn CM, Janssens AC.

Am J Epidemiol. 2010 Aug 1;172(3):353-61. doi: 10.1093/aje/kwq122.

PMID:
20562194
6.

Contribution of 30 biomarkers to 10-year cardiovascular risk estimation in 2 population cohorts: the MONICA, risk, genetics, archiving, and monograph (MORGAM) biomarker project.

Blankenberg S, Zeller T, Saarela O, Havulinna AS, Kee F, Tunstall-Pedoe H, Kuulasmaa K, Yarnell J, Schnabel RB, Wild PS, Münzel TF, Lackner KJ, Tiret L, Evans A, Salomaa V; MORGAM Project..

Circulation. 2010 Jun 8;121(22):2388-97. doi: 10.1161/CIRCULATIONAHA.109.901413.

7.

Cardiovascular risk prediction: basic concepts, current status, and future directions.

Lloyd-Jones DM.

Circulation. 2010 Apr 20;121(15):1768-77. doi: 10.1161/CIRCULATIONAHA.109.849166. Review. No abstract available.

8.

Thirty-one novel biomarkers as predictors for clinically incident diabetes.

Salomaa V, Havulinna A, Saarela O, Zeller T, Jousilahti P, Jula A, Muenzel T, Aromaa A, Evans A, Kuulasmaa K, Blankenberg S.

PLoS One. 2010 Apr 9;5(4):e10100. doi: 10.1371/journal.pone.0010100.

9.

The effects of salsalate on glycemic control in patients with type 2 diabetes: a randomized trial.

Goldfine AB, Fonseca V, Jablonski KA, Pyle L, Staten MA, Shoelson SE; TINSAL-T2D (Targeting Inflammation Using Salsalate in Type 2 Diabetes) Study Team..

Ann Intern Med. 2010 Mar 16;152(6):346-57. doi: 10.7326/0003-4819-152-6-201003160-00004.

10.

Use of multiple metabolic and genetic markers to improve the prediction of type 2 diabetes: the EPIC-Potsdam Study.

Schulze MB, Weikert C, Pischon T, Bergmann MM, Al-Hasani H, Schleicher E, Fritsche A, Häring HU, Boeing H, Joost HG.

Diabetes Care. 2009 Nov;32(11):2116-9. doi: 10.2337/dc09-0197.

11.

Transforming growth factor-beta1 and incident type 2 diabetes: results from the MONICA/KORA case-cohort study, 1984-2002.

Herder C, Zierer A, Koenig W, Roden M, Meisinger C, Thorand B.

Diabetes Care. 2009 Oct;32(10):1921-3. doi: 10.2337/dc09-0476.

12.

Novel and conventional biomarkers for prediction of incident cardiovascular events in the community.

Melander O, Newton-Cheh C, Almgren P, Hedblad B, Berglund G, Engström G, Persson M, Smith JG, Magnusson M, Christensson A, Struck J, Morgenthaler NG, Bergmann A, Pencina MJ, Wang TJ.

JAMA. 2009 Jul 1;302(1):49-57. doi: 10.1001/jama.2009.943.

13.

Development of a type 2 diabetes risk model from a panel of serum biomarkers from the Inter99 cohort.

Kolberg JA, Jørgensen T, Gerwien RW, Hamren S, McKenna MP, Moler E, Rowe MW, Urdea MS, Xu XM, Hansen T, Pedersen O, Borch-Johnsen K.

Diabetes Care. 2009 Jul;32(7):1207-12. doi: 10.2337/dc08-1935.

14.

Are markers of inflammation more strongly associated with risk for fatal than for nonfatal vascular events?

Sattar N, Murray HM, Welsh P, Blauw GJ, Buckley BM, Cobbe S, de Craen AJ, Lowe GD, Jukema JW, Macfarlane PW, Murphy MB, Stott DJ, Westendorp RG, Shepherd J, Ford I, Packard CJ; Prospective Study of Pravastatin in the Elderly at Risk (PROSPER) Study Group..

PLoS Med. 2009 Jun 23;6(6):e1000099. doi: 10.1371/journal.pmed.1000099.

15.

Use of multiple biomarkers to improve the prediction of death from cardiovascular causes.

Zethelius B, Berglund L, Sundström J, Ingelsson E, Basu S, Larsson A, Venge P, Arnlöv J.

N Engl J Med. 2008 May 15;358(20):2107-16. doi: 10.1056/NEJMoa0707064.

16.

RANTES/CCL5 gene polymorphisms, serum concentrations, and incident type 2 diabetes: results from the MONICA/KORA Augsburg case-cohort study, 1984-2002.

Herder C, Illig T, Baumert J, Müller M, Klopp N, Khuseyinova N, Meisinger C, Poschen U, Martin S, Koenig W, Thorand B.

Eur J Endocrinol. 2008 May;158(5):R1-5. doi: 10.1530/EJE-07-0686.

17.

Novel biochemical risk factors for type 2 diabetes: pathogenic insights or prediction possibilities?

Sattar N, Wannamethee SG, Forouhi NG.

Diabetologia. 2008 Jun;51(6):926-40. doi: 10.1007/s00125-008-0954-7. Review.

PMID:
18392804
18.

Additional contribution of emerging risk factors to the prediction of the risk of type 2 diabetes: evidence from the Western New York Study.

Stranges S, Rafalson LB, Dmochowski J, Rejman K, Tracy RP, Trevisan M, Donahue RP.

Obesity (Silver Spring). 2008 Jun;16(6):1370-6. doi: 10.1038/oby.2008.59.

19.

Adipokines and incident type 2 diabetes in an Aboriginal Canadian [corrected] population: the Sandy Lake Health and Diabetes Project.

Ley SH, Harris SB, Connelly PW, Mamakeesick M, Gittelsohn J, Hegele RA, Retnakaran R, Zinman B, Hanley AJ.

Diabetes Care. 2008 Jul;31(7):1410-5. doi: 10.2337/dc08-0036. Erratum in: Diabetes Care. 2008 Aug;31(8):1713.

20.

Effect of macrophage migration inhibitory factor (MIF) gene variants and MIF serum concentrations on the risk of type 2 diabetes: results from the MONICA/KORA Augsburg Case-Cohort Study, 1984-2002.

Herder C, Klopp N, Baumert J, Müller M, Khuseyinova N, Meisinger C, Martin S, Illig T, Koenig W, Thorand B.

Diabetologia. 2008 Feb;51(2):276-84.

PMID:
17712545
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