A C R Simon1, G B Bolli2, M-P Dain3, E Wang4, F Holleman5. 1. Department of Internal Medicine, Academic Medical Center, Amsterdam, The Netherlands. Electronic address: a.c.simon@amc.uva.nl. 2. Department of Internal Medicine, University of Perugia, Perugia, Italy. 3. Sanofi, Paris, France. 4. Sanofi, Bridgewater, NJ, USA. 5. Department of Internal Medicine, Academic Medical Center, Amsterdam, The Netherlands.
Abstract
BACKGROUND AND AIMS: The possibility to predict final insulin dose based on patient's characteristics would allow for efficient titration for patients with higher dose needs. The primary aim of this post-hoc analysis of the L2T3 study was to determine predictors for final dose. Specifically, we focused on the relationship between BMI and dose. The secondary aims were to investigate (i) the predictive value of BMI and age on final dose and (ii) the possibility to tailor the starting dose of insulin based on BMI and age. METHODS AND RESULTS: We performed two stepwise regression analyses, one using all baseline characteristics, and one using physical characteristics and FPG which can be assessed "at the bedside" only. Furthermore, median [min, max] final doses of groups stratified according to BMI and age were calculated. BMI clearly correlated with final dose in IU (Pearson correlation 0.42 [0.37; 0.48], p < 0.001). Characteristics which can be assessed "at the bedside" that predict high final dose were allocation to detemir, absence or discontinuation of insulin secretagogues, high BMI, low age, male gender and high FPG. Final dose varied among strata (BMI ≥30 kg/m(2): 64 IU; BMI <30 kg/m(2): 38 IU, p < 0.001 and age <59 years: 52 IU; age ≥59 years: 44 IU, p < 0.001). All groups stratified for both BMI and age showed similarly low minimal final dose (5-17 IU). CONCLUSION: Our data showed a high predictive value of BMI on final dose. However, it does not seem possible to tailor starting dose based on BMI and age.
BACKGROUND AND AIMS: The possibility to predict final insulin dose based on patient's characteristics would allow for efficient titration for patients with higher dose needs. The primary aim of this post-hoc analysis of the L2T3 study was to determine predictors for final dose. Specifically, we focused on the relationship between BMI and dose. The secondary aims were to investigate (i) the predictive value of BMI and age on final dose and (ii) the possibility to tailor the starting dose of insulin based on BMI and age. METHODS AND RESULTS: We performed two stepwise regression analyses, one using all baseline characteristics, and one using physical characteristics and FPG which can be assessed "at the bedside" only. Furthermore, median [min, max] final doses of groups stratified according to BMI and age were calculated. BMI clearly correlated with final dose in IU (Pearson correlation 0.42 [0.37; 0.48], p < 0.001). Characteristics which can be assessed "at the bedside" that predict high final dose were allocation to detemir, absence or discontinuation of insulin secretagogues, high BMI, low age, male gender and high FPG. Final dose varied among strata (BMI ≥30 kg/m(2): 64 IU; BMI <30 kg/m(2): 38 IU, p < 0.001 and age <59 years: 52 IU; age ≥59 years: 44 IU, p < 0.001). All groups stratified for both BMI and age showed similarly low minimal final dose (5-17 IU). CONCLUSION: Our data showed a high predictive value of BMI on final dose. However, it does not seem possible to tailor starting dose based on BMI and age.