#JJ RISK ENGINE HOW TO#

Stefan Ma and Zheng Li Yau of the Ministry of Health of Singapore discussed the 5-year prediction model and statistical methods they used for all-cause mortality of Singaporean individuals with diabetes. He offered to re-estimate the model using the risk factors available on others’ datasets so that the Hong Kong risk model could potentially be used by other teams as well. His next step will be to monetize the value for improved survival in diabetes in Hong Kong.

#JJ RISK ENGINE HOW TO#

His work primarily looked at how the UKPDS risk engine predicted risk in Hong Kong populations as compared to a local Hong Kong risk engine and how to best calibrate the Hong Kong risk engine. The data sets from those two countries were best estimated by the JJ Risk Engine for the Japan data and the UKPDS model for the Netherlands data.Ĭhao Quan of the University of Hong Kong presented the risk model used for Hong Kong populations.

Karen Eggleston, director of the Asia Health Policy Program, delivered introductory remarks and shared current progress by the Japan and Netherlands research teams on calculating value and risk for diabetes with data from the Netherlands and Japan. On the first day, each research team presented its work, describing data sets and explaining the risk models that were used or developed. The goal is to create separate risk models specifically suited for populations from Hong Kong, Singapore, China, Taiwan and South Korea.ĭuring the workshop that spanned two days, the research teams had an opportunity to share updates on their individual projects and to discuss methods and ideas for future collaboration.

data and populations, are not very relevant for Asian populations. Previous models used to measure diabetic values and risks, such as the United Kingdom Prospective Diabetes Study (UKPDS) risk engine that was created from U.K. These calculations include monetizing the value of health benefits of new treatments and improvements in health, as well as avoided spending on treatments when prevention was effective, and associated mortality and probability of survival. The research teams from various Asian countries are attempting to calculate the net value of diabetes in those countries by observing the changes in diabetes value and spending. 2009 study with Mayo Clinic Data for Type 2 diabetes. Research teams from Hong Kong, Singapore, China, Taiwan, South Korea and the United States convened at the Stanford Center at Peking University (SCPKU) in Beijing to work on research that compares utilization and spending patterns on diabetes across different countries and to develop a method for measuring the net value of diabetes internationally, based on previous methods discussed in a Eggleston and Newhouse et al. Similar results were obtained with discordant higher Steno-Risk versus ACC/AHA-2013 ( P < 0.001).The Asia Health Policy Program at the Shorenstein Asia-Pacific Research Center hosted the Net Value in Diabetes Management Workshop in March to discuss progress on an international research collaboration. Finally, in polynomial regression models (with adjustment for lipid parameters and cardioprotective treatment), irrespective of the ESC/EASD-2019 category, high risk by Steno-Risk was directly associated with atherosclerosis (in moderate/high-risk by ESC/EASD-2019 odds ratio 2.91 and 4.94 for the presence of plaque and two or more plaques).

Steno-Risk identified individuals with plaques, unlike ESC/EASD-2019 (area under the curve 0.691, P < 0.001, vs. A stepped increase in the presence of plaques according to Steno-Risk category was seen (18.4%, 38.2%, and 64.1%, for low, moderate, and high risk, respectively P for trend <0.001), with no differences according to ESC/EASD-2019 ( P = 0.130). Concordance between T1D-specific scales was poor (κ = 0.19). We included 501 patients (53% men, mean age 48.8 years, median T1D duration 26.5 years, 41.3% harboring plaques).

Jj risk engine