This modification could be further evaluated, recalibrated, and validated using patient-level information derived from prospective clinical studies to yield greater predictability. Conclusion: A modified UKPDS model which includes adjustments for prior cardiovascular history has the potential for use as a tool for benchmarking and may be useful for predicting cardiovascular rates in clinical studies. However, cardiovascular risk predictions were more precise using a modified UKPDS model the ratio of predicted versus observed MACE events ranged from 1.8 to 2.4, with a mean of 2.1 0.25 and a coefficient of variation of 13% ( = 0.94). The ratio of predicted events versus observed MACE ranged from 0.9 to 2.0, with mean of 1.5 0.4 and a coefficient of variation of 26% ( = 0.80). Results: The original UKPDS model tended to overestimate event rates across studies. The consistency of the predicted rates derived from each model was then evaluated using descriptive statistics and linear regression. Simulation studies were then conducted using original (cardiovascular history excluded) and modified (cardiovascular history included) United Kingdom Prospective Diabetes Study (UKPDS) models the predicted event rates were then compared with the observed event rates for all studies. Overall observed rates for cardiovascular events/MACE were summarized, and the observed annualized event rates were calculated using linear approximation. Cardiovascular events/major adverse coronary events (CVE/MACE) were primary or safety end points. Patients in these studies spanned a wide spectrum of disease, from drug-naive to insulin-dependent. Methods: Data sources were summary demographic and risk factor data from the major type 2 diabetes mellitus outcomes studies, including ACCORD, ADVANCE, VADT, RECORD, PROactive, ADOPT, and BARI 2D. This modification could be further evaluated, recalibrated, and validated using patient-level information derived from prospective clinical studies to yield greater predictability.Abstract : Background: The aim of this study was to evaluate a modified UKPDS risk engine in order to establish a risk prediction benchmark for the general diabetes population. However, cardiovascular risk predictions were more precise using a modified UKPDS model the ratio of predicted versus observed MACE events ranged from 1.8 to 2.4, with a mean of 2.1 ± 0.25 and a coefficient of variation of 13% (R 2 = 0.94).Ĭonclusion: A modified UKPDS model which includes adjustments for prior cardiovascular history has the potential for use as a tool for benchmarking and may be useful for predicting cardiovascular rates in clinical studies. The ratio of predicted events versus observed MACE ranged from 0.9 to 2.0, with mean of 1.5 ± 0.4 and a coefficient of variation of 26% (R 2 = 0.80). Patients in these studies spanned a wide spectrum of disease, from drug-naïve to insulin-dependent. Modification of the UKPDS Risk Engine To Evaluate Cardiovascular Event Rates in Controlled Clinical Trials The UKPDS risk engine is effe The UKPDS risk. Fred Yang, 1 June Ye, 2 Kenneth Pomerantz, 3 Murray Stewart 1ġAlternative Development Program, GlaxoSmithKline, King of Prussia, PA, 2Discovery Biometrics, GlaxoSmithKline, Research Triangle Park, NC, 3Clinical Development and Medical Affairs, Boehringer-Ingelheim Pharmaceuticals, Inc, Ridgefield, CT, USAīackground: The aim of this study was to evaluate a modified UKPDS risk engine in order to establish a risk prediction benchmark for the general diabetes population.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |