Shape information from glucose curves: Functional data analysis compared with traditional summary measures

BMC Medical Research Methodology

Marit B Veierød⁴  Tore Henriksen¹  Nanna Voldner¹  Jens Bollerslev³  Kristin Godang²  Elisabeth Qvigstad²  Jo Røislien⁴  Kathrine Frey Frøslie⁵ 

[1] Division of Obstetrics and Gynaecology, Oslo University Hospital, Rikshospitalet, Norway;Section of Specialised Endocrinology, Department of Medicine, Oslo University Hospital, Rikshospitalet, Norway;Faculty of Clinical Medicine, University of Oslo, Rikshospitalet, Norway;Department of Biostatistics, Institute of Basic Medical Sciences, University of Oslo, Boks 1122, Blindern, 0317, Oslo, Norway;Norwegian Resource Centre for Women's Health, Division of Obstetrics and Gynaecology, Oslo University Hospital, Rikshospitalet, Norway

关键词: Pregnancy;    Oral glucose tolerance test;    Glucose variability;    Glucose oscillations;    Glucose curve;    Gestational diabetes;    Functional principal component analysis;    Functional data analysis;    Curve shape;    Area under the curve;   

Others  :  1126251
DOI  :  10.1186/1471-2288-13-6

 received in 2012-09-13, accepted in 2013-01-08,  发布年份 2013

【 摘 要 】

Background

Plasma glucose levels are important measures in medical care and research, and are often obtained from oral glucose tolerance tests (OGTT) with repeated measurements over 2–3 hours. It is common practice to use simple summary measures of OGTT curves. However, different OGTT curves can yield similar summary measures, and information of physiological or clinical interest may be lost. Our mean aim was to extract information inherent in the shape of OGTT glucose curves, compare it with the information from simple summary measures, and explore the clinical usefulness of such information.

Methods

OGTTs with five glucose measurements over two hours were recorded for 974 healthy pregnant women in their first trimester. For each woman, the five measurements were transformed into smooth OGTT glucose curves by functional data analysis (FDA), a collection of statistical methods developed specifically to analyse curve data. The essential modes of temporal variation between OGTT glucose curves were extracted by functional principal component analysis. The resultant functional principal component (FPC) scores were compared with commonly used simple summary measures: fasting and two-hour (2-h) values, area under the curve (AUC) and simple shape index (2-h minus 90-min values, or 90-min minus 60-min values). Clinical usefulness of FDA was explored by regression analyses of glucose tolerance later in pregnancy.

Results

Over 99% of the variation between individually fitted curves was expressed in the first three FPCs, interpreted physiologically as “general level” (FPC1), “time to peak” (FPC2) and “oscillations” (FPC3). FPC1 scores correlated strongly with AUC (r=0.999), but less with the other simple summary measures (−0.42≤r≤0.79). FPC2 scores gave shape information not captured by simple summary measures (−0.12≤r≤0.40). FPC2 scores, but not FPC1 nor the simple summary measures, discriminated between women who did and did not develop gestational diabetes later in pregnancy.

Conclusions

FDA of OGTT glucose curves in early pregnancy extracted shape information that was not identified by commonly used simple summary measures. This information discriminated between women with and without gestational diabetes later in pregnancy.

【 授权许可】

   
2013 Frøslie et al.; licensee BioMed Central Ltd.

【 图 表 】

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