Non-linear mixed effect models for the relationship between fasting plasma glucose and weight loss.
Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Diabetes is one of the most common diseases in modern time. Its connection to overweight and obesity is well established, and diet and exercise are therefore important parameters in the treatment. A commonly used biomarker to diagnose and follow disease progression in diabetics is via measurements of fasting plasma glucose, FPG. In this study, the relationship between weight loss and FPG in overweight diabetics was studied. Competing hypothesis regarding the connection between weight loss and reduced FPG was investigated by using nonlinear mixed effects modeling based on data gathered from a meta-analysis by Anderson et al (1). The hypotheses suggested that either  weight effected FPG directly by an intermediate effector, or  both weight and FPG were affected by an unknown underlying mechanism. The intermediate effector was presumed to be insulin sensitivity and the underlying mechanism the blood concentration of free fatty acids. The data was gathered from 8 different studies, all examining the results of very low energy diets (330-909 kcal/day) in overweight type 2 diabetics. Frequent measurements of weight and FPG were provided in each study with a range of 91-321 mg/dl for baseline FPG and 93-118 kg for baseline weight. The summarized studies consisted of 13 arms with 6-62 subjects in each arm.
Both hypotheses were modeled by using NONMEM 7.2. A stepwise effect was used for both weight and FPG. For hypothesis , an inhibitory effect affected the weight input which then affected the output for insulin sensitivity by a relative change in weight or the input for the insulin sensitivity by an absolute weight change. For hypothesis  the same inhibitory effect affected weight input and the input for insulin sensitivity. For both models the FPG drop was then proportional to the increase in insulin sensitivity. Hypothesis  had a significantly lower objective function value (OFV) than hypothesis  and had also better results from goodness of fit plots and VPCs. It was therefore concluded that hypothesis  indicated the more accurate explanation of the connection between FPG and weight loss. Moreover, a strong correlation between the caloric content of the diet and the rate of weight change was seen as a result of stepwise covariate modeling. An impact from baseline BMI on rate of change for insulin sensitivity was also seen.
Place, publisher, year, edition, pages
UPTEC K, ISSN 1650-8297 ; 13009
diabetes, pharmacometrics, modelling, NONMEM, FPG
IdentifiersURN: urn:nbn:se:uu:diva-205712OAI: oai:DiVA.org:uu-205712DiVA: diva2:642543
Master Programme in Chemical Engineering
Kjellson, MariaChoy, Steve
Karlsson, MatsHammarlund-Udenaes, Margareta