Decision trees as a simple-to-use and reliable tool to identify individuals with impaired glucose metabolism or type 2 diabetes mellitus

European Journal of Endocrinology

Volumn 163, Issue 4, 2010, Pages 565-571

  Hische, Manuela ^a,b   Luis Dominguez, Olga ^c   Pfeiffer, Andreas F H ^a,d   Schwarz, Peter E ^c   Selbig, Joachim ^b   Spranger, Joachim ^a  

^a CHARITÉ UNIVERSITÄTSMEDIZIN BERLIN   (Germany)

^b UNIVERSITY OF POTSDAM   (Germany)

^c DRESDEN UNIVERSITY OF TECHNOLOGY   (Germany)

^d GERMAN INSTITUTE OF HUMAN NUTRITION   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

GLUCOSE;

ACCURACY; ADULT; ARTICLE; BLOOD PRESSURE MEASUREMENT; CARDIOVASCULAR RISK; CLINICAL DECISION MAKING; CONTROL GROUP; CONTROLLED STUDY; DECISION TREE; FEMALE; GLUCOSE BLOOD LEVEL; HUMAN; IMPAIRED GLUCOSE TOLERANCE; MACHINE LEARNING; MAJOR CLINICAL STUDY; MALE; METABOLIC SYNDROME X; NON INSULIN DEPENDENT DIABETES MELLITUS; ORAL GLUCOSE TOLERANCE TEST; OUTPATIENT DEPARTMENT; PREDICTIVE VALIDITY; PRIORITY JOURNAL; SENSITIVITY AND SPECIFICITY; SYSTOLIC BLOOD PRESSURE; AGED; ARTIFICIAL INTELLIGENCE; CROSS-SECTIONAL STUDY; DECISION SUPPORT SYSTEM; DIABETES MELLITUS, TYPE 2; GLUCOSE INTOLERANCE; MIDDLE AGED;

ADULT; AGED; ARTIFICIAL INTELLIGENCE; CROSS-SECTIONAL STUDIES; DECISION SUPPORT TECHNIQUES; DIABETES MELLITUS, TYPE 2; FEMALE; GLUCOSE INTOLERANCE; HUMANS; MALE; MIDDLE AGED;

EID: 77957124986     PISSN: 08044643     EISSN: 1479683X     Source Type: Journal    
DOI: 10.1530/EJE-10-0649     Document Type: Article

References (22)

1. Harris MI & Eastman RC. Early detection of undiagnosed diabetes mellitus: a US perspective. Diabetes/Metabolism Research and Reviews 2000 16 230-236. (doi:10.1002/1520-7560(2000)9999:9999〈::AID-DMRR122〉3.0.CO;2- W)
2. Saudek CD, Herman WH, Sacks DB, Bergenstal RM, Edelman D & Davidson MB. A new look at screening and diagnosing diabetes mellitus. Journal of Clinical Endocrinology and Metabolism 2008 93 2447-2453. (doi:10.1210/jc.2007- 2174)
3. von Eckardstein A, Schulte H & Assmann G. Risk for diabetes mellitus in middle-aged Caucasian male participants of the PROCAM study: implications for the definition of impaired fasting glucose by the American Diabetes Association. Journal of Clinical Endocrinology and Metabolism 2000 85 3101-3108. (doi:10.1210/jc.85.9.3101)
4. Lindström J & Tuomilehto J. The diabetes risk score: a practical tool to predict type 2 diabetes risk. Diabetes Care 2003 26 725-731. (doi:10.2337/diacare.26.3.725)
5. Schulze MB, Hoffmann K, Boeing H, Linseisen J, Rohrmann S, Möhlig M, Pfeiffer AFH, Spranger J, Thamer C, Häring H, Fritsche A & Joost H. An accurate risk score ased on anthropometric, dietary, and lifestyle factors to predict the development of type 2 diabetes. Diabetes Care 2007 30 510-515. (doi:10.2337/dc06-2089)
6. Rahman M, Simmons RK, Harding AH, Wareham NJ & Griffin SJ. A simple risk score identifies individuals at high risk of developing type 2 diabetes: a prospective cohort study. Family Practice 2008 25 191-196. (doi:10.1093/fampra/ cmn024) (Pubitemid 351965938)
7. Manley SE, Sikaris KA, Lu ZX, Nightingale PG, Stratton IM, Round RA, Baskar V, Gough SC & Smith JM. Validation of an algorithm combining haemoglobin A(1c) and fasting plasma glucose for diagnosis of diabetes mellitus in UK and Australian populations. Diabetic Medicine 2009 26 115-121. (doi:10.1111/j.1464-5491.2008.02652.x)
8. Lin X, Song K, Lim N, Yuan X, Johnson T, Abderrahmani A, Vollenweider P, Stirnadel H, Sundseth SS, Lai E, Burns DK, Middleton LT, Roses AD, Matthews PM, Waeber G, Cardon L, Waterworth DM & Mooser V. Risk prediction of prevalent diabetes in a Swiss population using a weighted genetic score - the CoLaus Study. Diabetologia 2009 52 600-608. (doi:10.1007/s00125-008-1254-y)
9. Beerenwinkel N, Schmidt B, Walter H, Kaiser R, Lengauer T, Hoffmann D, Korn K & Selbig J. Diversity and complexity of HIV-1 drug resistance: a bioinformatics approach to predicting phenotype from genotype. PNAS 2002 99 8271-8276. (doi:10.1073/pnas.112177799)
10. Stern SE, Williams K, Ferrannini E, DeFronzo RA, Bogardus C & Stern MP. Identification of individuals with insulin resistance using routine clinical measurements. Diabetes 2005 54 333-339. (doi:10.2337/diabetes.54.2.333)
11. Möhlig M, Flöter A, Spranger J, Weickert MO, Schill T, Schlösser HW, Brabant G, Pfeiffer AFH, Selbig JC & Schöfl C. Predicting impaired glucose metabolism in women with polycystic ovary syndrome by decision tree modelling. Diabetologia 2006 49 2572-2579. (doi:10.1007/s00125- 006-0395-0)
12. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF & Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985 28 412-419. (doi:10.1007/BF00280883)
13. Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Report of the expert committee on the diagnosis and classification of diabetes mellitus. Diabetes Care 2003 26 S5-S20. (doi:10.2337/diacare.26.2007. S5)
14. Schwarz PE, Towers GW, Fischer S, Govindarajalu S, Schulze J, Bornstein SR, Hanefeld M & Vasseur F. Hypoadiponectinemia is associated with progression toward type 2 diabetes and genetic variation in the ADIPOQ gene promoter. Diabetes Care 2006 29 1645-1650. (doi:10.2337/dc05-2123)
15. Quinlan JR. C4.5: Programs for Machine Learning. San Mateo, CA: Morgan Kaufman Publ Inc., 1993.
16. Hastie T, Tibshirani R & Friedman J. In The Elements of Statistical Learning. New York: Springer, 2001.
17. Glümer C, Carstensen B, Sandbaek A, Lauritzen T, Jørgensen T & Borch-Johnsen K. A Danish diabetes risk score for targeted screening: the Inter99 study. Diabetes Care 2004 27 727-733. (doi:10.2337/diacare.27.3.727)
18. Al-Lawati JA & Tuomilehto J. Diabetes risk score in Oman: a tool to identify prevalent type 2 diabetes among Arabs of the Middle East. Diabetes Research and Clinical Practice 2007 77 438-444. (doi:10.1016/j.diabres.2007.01. 013) (Pubitemid 47211338)
19. Tuomilehto J, Lindström J, Eriksson JG, Valle TT, Hämäläinen H, Ilanne-Parikka P, Keinänen-Kiukaanniemi S, Laakso M, Louheranta A, Rastas M, Salminen V, Uusitupa M & Finnish Diabetes Prevention Study Group. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. New England Journal of Medicine 2001 344 1343-1350. (doi:10.1056/NEJM200105033441801)
20. Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, Nathan DM & Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. New England Journal of Medicine 2002 346 393-403. (doi:10.1056/NEJMoa012512)
21. Lindström J, Ilanne-Parikka P, Peltonen M, Aunola S, Eriksson JG, Hemiö K, Hämäläinen H, Härkönen P, Keinänen-Kiukaanniemi S, Laakso M, Louheranta A, Mannelin M, Paturi M, Sundvall J, Valle TT, Uusitupa M & Tuomilehto J. Sustained reduction in the incidence of type 2 diabetes by lifestyle intervention: follow-up of the Finnish Diabetes Prevention Study. Lancet 2006 368 1673-1679. (doi:10.1016/S0140- 6736(06)69701-8)
22. Schwarz PE, Li J, Reimann M, Schutte AE, Bergmann A, Hanefeld M, Bornstein SR, Schulze J, Tuomilehto J & Lindström J. The Finnish Diabetes Risk Score is associated with insulin resistance and progression towards type 2 diabetes. Journal of Clinical Endocrinology and Metabolism 2009 94 920-926. (doi:10.1210/jc.2007-2427)