Biomarker models as surrogates for the disposition index in the Insulin Resistance Atherosclerosis Study
Article first published online: 7 OCT 2012
© 2012 The Authors. Diabetic Medicine © 2012 Diabetes UK
Volume 29, Issue 11, pages 1399–1406, November 2012
How to Cite
Watkins, S. M., Rowe, M. W., Kolberg, J. A., Wagenknecht, L. E. and Bergman, R. N. (2012), Biomarker models as surrogates for the disposition index in the Insulin Resistance Atherosclerosis Study. Diabetic Medicine, 29: 1399–1406. doi: 10.1111/j.1464-5491.2012.03625.x
- Issue published online: 7 OCT 2012
- Article first published online: 7 OCT 2012
- Accepted manuscript online: 13 MAR 2012 06:20AM EST
- Accepted 6 March 2012
Aims Insulin sensitivity and acute insulin response measure key components of Type 2 diabetes aetiology that contribute independently to risk in the Insulin Resistance Atherosclerosis Study. As insulin sensitivity and acute insulin response are not routinely measured in a clinical setting, we evaluated three fasting biomarker models, homeostasis model assessment of insulin sensitivity (HOMA-%S), β-cell function (HOMA-%B) and a Diabetes Risk Score, as potential surrogates for risk associated with insulin sensitivity, acute insulin response and the interaction of these two measures, the disposition index.
Methods Models were calculated from baseline plasma biomarker concentrations for 664 participants who underwent a frequently sampled intravenous glucose tolerance test. To assess relationships among biomarker models and test measures, we calculated improvement in risk estimation gained by combining each fasting measure with each frequently sampled intravenous glucose tolerance test measure using logistic regression.
Results The strongest correlates of acute insulin response, insulin sensitivity and disposition index were HOMA-%B (rs2 = 0.23), HOMA-%S (rs2 = 0.48) and Diabetes Risk Score (rs2 = 0.34), respectively. Individual areas under the curves for prediction of diabetes were 0.549 (HOMA-%B), 0.694 (HOMA-%S), 0.700 (insulin sensitivity), 0.714 (acute insulin response), 0.756 (Diabetes Risk Score) and 0.817 (disposition index). Models combining acute insulin response with Diabetes Risk Score (area under the curve 0.798) or HOMA-%S (area under the curve 0.805) nearly equalled disposition index, outperforming other individual measures (P < 0.05). Insulin sensitivity plus Diabetes Risk Score (area under the curve 0.760) was better than insulin sensitivity (P = 0.03), but not better than Diabetes Risk Score alone. HOMA-%S plus insulin sensitivity (area under the curve 0.704) was not significantly better than either alone.
Conclusions The Diabetes Risk Score and HOMA-%S were excellent surrogates for insulin sensitivity, capturing the predictive power of insulin sensitivity. Diabetes Risk Score captured some of the additional predictive power of acute insulin response, but the HOMA models did not. No fasting model was as predictive as disposition index, but the Diabetes Risk Score was the best surrogate.