Anetta Claussen1, Jonas B Møller2, Niels R Kristensen3, Søren Klim4, Maria C Kjellsson5, Steen H Ingwersen6, Mats O Karlsson5. 1. Current address: Certara Strategic Consulting, Basel, Switzerland; Quantitative Clinical Pharmacology, Novo Nordisk A/S, Søborg, Denmark. 2. New Product Planning, Novo Nordisk A/S, Søborg, Denmark. 3. Quantitative Clinical Pharmacology, Novo Nordisk A/S, Søborg, Denmark. 4. Biostatistics, Novo Nordisk A/S, Søborg, Denmark. 5. Department of Pharmaceutical Biosciences, The Pharmacometrics Group, Uppsala University, Uppsala, Sweden. 6. Quantitative Clinical Pharmacology, Novo Nordisk A/S, Søborg, Denmark. Electronic address: si@novonordisk.com.
Abstract
CONTEXT: Several studies have shown that the relationship between mean plasma glucose (MPG) and glycated haemoglobin (HbA1c) may vary across populations. Especially race has previously been referred to shift the regression line that links MPG to HbA1c at steady-state (Herman & Cohen, 2012). OBJECTIVE: To assess the influence of demographic and disease progression-related covariates on the intercept of the estimated linear MPG-HbA1c relationship in a longitudinal model. DATA: Longitudinal patient-level data from 16 late-phase trials in type 2 diabetes with a total of 8927 subjects was used to study covariates for the relationship between MPG and HbA1c. The analysed covariates included age group, BMI, gender, race, diabetes duration, and pre-trial treatment. Differences between trials were taken into account by estimating a trial-to-trial variability component. PARTICIPANTS: Participants included 47% females and 20% above 65years. 77% were Caucasian, 9% were Asian, 5% were Black and the remaining 9% were analysed together as other races. ANALYSIS: Estimates of the change in the intercept of the MPG-HbA1c relationship due to the mentioned covariates were determined using a longitudinal model. RESULTS: The analysis showed that pre-trial treatment with insulin had the most pronounced impact associated with a 0.34% higher HbA1c at a given MPG. However, race, diabetes duration and age group also had an impact on the MPG-HbA1c relationship. CONCLUSION: Our analysis shows that the relationship between MPG and HbA1c is relatively insensitive to covariates, but shows small variations across populations, which may be relevant to take into account when predicting HbA1c response based on MPG measurements in clinical trials.
CONTEXT: Several studies have shown that the relationship between mean plasma glucose (MPG) and glycated haemoglobin (HbA1c) may vary across populations. Especially race has previously been referred to shift the regression line that links MPG to HbA1c at steady-state (Herman & Cohen, 2012). OBJECTIVE: To assess the influence of demographic and disease progression-related covariates on the intercept of the estimated linear MPG-HbA1c relationship in a longitudinal model. DATA: Longitudinal patient-level data from 16 late-phase trials in type 2 diabetes with a total of 8927 subjects was used to study covariates for the relationship between MPG and HbA1c. The analysed covariates included age group, BMI, gender, race, diabetes duration, and pre-trial treatment. Differences between trials were taken into account by estimating a trial-to-trial variability component. PARTICIPANTS: Participants included 47% females and 20% above 65years. 77% were Caucasian, 9% were Asian, 5% were Black and the remaining 9% were analysed together as other races. ANALYSIS: Estimates of the change in the intercept of the MPG-HbA1c relationship due to the mentioned covariates were determined using a longitudinal model. RESULTS: The analysis showed that pre-trial treatment with insulin had the most pronounced impact associated with a 0.34% higher HbA1c at a given MPG. However, race, diabetes duration and age group also had an impact on the MPG-HbA1c relationship. CONCLUSION: Our analysis shows that the relationship between MPG and HbA1c is relatively insensitive to covariates, but shows small variations across populations, which may be relevant to take into account when predicting HbA1c response based on MPG measurements in clinical trials.
Authors: Emmanouil S Benioudakis; Evangelos D Georgiou; Eirini D Barouxi; Athanasios M Armagos; Vaia Koutsoumani; Faidra Anastasiou-Veneti; Eleni Koutsoumani; Maria Brokalaki Journal: Diabetol Int Date: 2020-11-16
Authors: Bashair K Alshahri; Manar Bamashmoos; Mona I Alnaimi; Shaykhah Alsayil; Shymaa Basaqer; Mohammed T Al-Hariri; Christopher Amalraj Vallaba Doss Journal: Cureus Date: 2020-12-05