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Predicting impaired glucose metabolism in women with polycystic ovary syndrome by decision tree modelling

  • Aims/hypothesis Polycystic ovary syndrome (PCOS) is a risk factor of type 2 diabetes. Screening for impaired glucose metabolism (IGM) with an OGTT has been recommended, but this is relatively time-consuming and inconvenient. Thus, a strategy that could minimise the need for an OGTT would be beneficial. Materials and methods Consecutive PCOS patients (n=118) with fasting glucose < 6.1 mmol/l were included in the study. Parameters derived from medical history, clinical examination and fasting blood samples were assessed by decision tree modelling for their ability to discriminate women with IGM (2-h OGTT value >= 7.8 mmol/l) from those with NGT. Results According to the OGTT results, 93 PCOS women had NGT and 25 had IGM. The best decision tree consisted of HOMA-IR, the proinsulin:insulin ratio, proinsulin, 17-OH progesterone and the ratio of luteinising hormone:follicle-stimulating hormone. This tree identified 69 women with NGT. The remaining 49 women included all women with IGM (100% sensitivity, 74% specificity to detect IGM).Aims/hypothesis Polycystic ovary syndrome (PCOS) is a risk factor of type 2 diabetes. Screening for impaired glucose metabolism (IGM) with an OGTT has been recommended, but this is relatively time-consuming and inconvenient. Thus, a strategy that could minimise the need for an OGTT would be beneficial. Materials and methods Consecutive PCOS patients (n=118) with fasting glucose < 6.1 mmol/l were included in the study. Parameters derived from medical history, clinical examination and fasting blood samples were assessed by decision tree modelling for their ability to discriminate women with IGM (2-h OGTT value >= 7.8 mmol/l) from those with NGT. Results According to the OGTT results, 93 PCOS women had NGT and 25 had IGM. The best decision tree consisted of HOMA-IR, the proinsulin:insulin ratio, proinsulin, 17-OH progesterone and the ratio of luteinising hormone:follicle-stimulating hormone. This tree identified 69 women with NGT. The remaining 49 women included all women with IGM (100% sensitivity, 74% specificity to detect IGM). Pruning this tree to three levels still identified 53 women with NGT (100% sensitivity, 57% specificity to detect IGM). Restricting the data matrix used for tree modelling to medical history and clinical parameters produced a tree using BMI, waist circumference and WHR. Pruning this tree to two levels separated 27 women with NGT (100% sensitivity, 29% specificity to detect IGM). The validity of both trees was tested by a leave-10%-out cross-validation. Conclusions/interpretation Decision trees are useful tools for separating PCOS women with NGT from those with IGM. They can be used for stratifying the metabolic screening of PCOS women, whereby the number of OGTTs can be markedly reduced.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:M. Moehlig, A. Floeter, Joachim SprangerORCiDGND, Martin O. WeickertORCiD, T. Schill, H. W. Schloesser, G. Brabant, Andreas F. H. PfeifferORCiDGND, Joachim SelbigGND, C. Schoefl
DOI:https://doi.org/10.1007/s00125-006-0395-0
ISSN:0012-186X
Pubmed ID:https://pubmed.ncbi.nlm.nih.gov/16972044
Titel des übergeordneten Werks (Englisch):Diabetologia : journal of the European Association for the Study of Diabetes (EASD)
Verlag:Springer
Verlagsort:Berlin
Publikationstyp:Wissenschaftlicher Artikel
Sprache:Englisch
Datum der Erstveröffentlichung:14.09.2006
Erscheinungsjahr:2006
Datum der Freischaltung:04.05.2020
Freies Schlagwort / Tag:HOMA; decision tree; impaired glucose tolerance; insulin; insulin resistance; polycystic ovary syndrome; proinsulin; type 2 diabetes mellitus
Band:49
Seitenanzahl:8
Erste Seite:2572
Letzte Seite:2579
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Ernährungswissenschaft
DDC-Klassifikation:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit
Peer Review:Referiert
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