BOOTSTRAPPING USED TO PROVIDE ROBUST MEAN AND VARIANCE ESTIMATES FOR COMPARING PATIENTS TREATED WITH LIRAGLUTIDE TO A LARGE COMPARISON COHORT
Author(s)
McAdam Marx C1, Ye X1, Bouchard J2, Aagren M2, Conner C3, Brixner D11University of Utah, Salt Lake City, UT, USA, 2Novo Nordisk, Inc., Princeton, NJ, USA, 3Novo Nordisk, Inc., Redmond, WA, USA
Presentation Documents
OBJECTIVES: In an analyses of patients with type 2 diabetes (T2DM) in a large electronic medical record (EMR) database, small differences were found to be statistically significant between N=1162 patients with liraglutide versus a comparison cohort due to the comparison group sample size (n=274,922). The purpose of this study is to evaluate a bootstrapping technique to provide robust mean and variance estimates for comparison patients, thereby helping to address the issue of being over-powered. METHODS: Study patients were age ≥18 years with T2DM, prescribed liraglutide or other antidiabetic drug January 1, 2010 to July 16, 2010 and with ≥13 months of EMR activity. Bootstrapping was used to provide cohort mean, standard deviation, and 95% CI estimates for the comparison cohort and were calculated as the mean of the mean values identified in 1000 random draws with replacement of 1162 comparison patients. Means (95% CI) were compared for continuous variables (age, HbA1c and blood pressure [BP]) for liraglutide versus the overall comparison group and to bootstrap estimates. RESULTS: Of 1162 liraglutide patients, mean (95% CI) age was 55.5 (54.9, 56.2) years versus 60.9 (60.8, 60.9) years for all comparison patients and 60.9 (60.1, 61.6) years for comparison patients per bootstrap estimates (both p<0.05). HbA1c was 8.12% (8.00, 8.24) for liraglutide versus 7.62% (7.61, 7.63) and 7.63% (7.49, 7.76) for all comparison patients and per bootstrap, respectively (both p<0.05). BP was 127.0 (126.1, 127.8)/75.8 (75.3, 76.4) mmHg for liraglutide versus 130.1 (130.0, 130.1)/75.4 (75.4, 75.5) mmHg and 130.1 (129.0, 131.2)/75.5 (74.8, 76.1) mmHg for all comparison patients and per bootstrap, respectively (p<0.05 except bootstrap diastolic BP p>0.05). CONCLUSIONS: A bootstrap analysis provided more robust variance and 95% CI estimates for a large comparison group. This technique can help researchers avoid identifying statistical significance when differences are not clinically meaningful when evaluating a large patient cohort.
Conference/Value in Health Info
2011-05, ISPOR 2011, Baltimore, MD, USA
Value in Health, Vol. 14, No. 3 (May 2011)
Code
EE4
Topic
Methodological & Statistical Research
Topic Subcategory
Confounding, Selection Bias Correction, Causal Inference
Disease
Diabetes/Endocrine/Metabolic Disorders