What is the BRAVOTM Model?

The Building, Relating, Assessing, and Validating Outcomes (BRAVO) diabetes model is a person-level discrete-time microsimulation model. The model simulates the progression of diabetes complications on the basis of individuals’ dynamic characteristics and treatment regimens over a lifetime. The predicted outcomes include macrovascular events (i.e., Myocardial infarction, congestive heart failure, stroke, angina, revascularization), microvascular events (i.e., chronic kidney disease, end-stage renal disease, retinopathy, blindness, neuropathy, amputation), and adverse events (e.g., hypoglycemia, diabetic ketoacidosis) over a user-specified time horizon. It was internally validated across different age/race/complication subgroups and externally validated against 18 large diabetes clinical trials conducted after 2000. We calibrated the BRAVO diabetes model to a national representative sample of individuals with diabetes in the US, to enhance its capacity to assist national policy evaluation and economic burden surveillance. We’ve further developed our signature “Globalization Module” to calibrate the BRAVO model’s prediction capacity from the US population to numerous regions globally, using data from more than 100,000 individuals internationally.

Application Area includes but not limited to:

RISK STRATIFICATION

The BRAVO model can be linked to a health system/ insurance plan to conduct risk stratification in the covered people with diabetes. Each patient will be assigned to the corresponding risk strata based on their predicted short-term/long-term risks of cardiovascular diseases and mortality. Thus, the BRAVO model can help the health system/ insurance to maximize the effectiveness of diabetes management by pinpointing the high-risk population.

program evaluation

The BRAVO model can be used to evaluate the benefit and cost-effectiveness of a policy/program/guideline. We have applied the model to evaluate the Medicare PartD Senior Saving Mode, the ADA’s diabetes insight program, and the American College of Physicians’ guidance statement on glycemic control.

About BRAVO™ MODEL

A Diabetes Microsimulation Model that Simulate the Progression of Diabetes Complications

Save Life, Lower Cost, Answer Fast

person-level real-time microsimulation model
simulate diabetes complications and mortality
Estimate life expectancy, lifetime risks of events, life-time costs, and quality-adjusted life years gain
Decision Making Support

bravo™ model compares to other diabetes models

Publications and Presentations

Shao, Hui, Lizheng Shi, and Vivian A. Fonseca. “Using the BRAVO Risk Engine to Predict Cardiovascular Outcomes in Clinical Trials With Sodium–Glucose Transporter 2 Inhibitors.” Diabetes Care 43, no. 7 (July 1, 2020): 1530–36. https://doi.org/10.2337/dc20-0227.
Shao, Hui, Vivian Fonseca, Roy Furman, Luigi Meneghini, and Lizheng Shi. “Impact of Quality Improvement (QI) Program on 5-Year Risk of Diabetes-Related Complications: A Simulation Study.” Diabetes Care 43, no. 11 (November 1, 2020): 2847–52. https://doi.org/10.2337/dc20-0465.
Shao, Hui, Shuang Yang, Charles Stoecker, Vivian Fonseca, Dongzhe Hong, and Lizheng Shi. “Addressing Regional Differences in Diabetes Progression: Global Calibration for Diabetes Simulation Model.” Value in Health 22, no. 12 (December 1, 2019): 1402–9. https://doi.org/10.1016/j.jval.2019.08.007.
Shao, Hui, Shuang Yang, Vivian Fonseca, Charles Stoecker, and Lizheng Shi. “Estimating Quality of Life Decrements Due to Diabetes Complications in the United States: The Health Utility Index (HUI) Diabetes Complication Equation.” PharmacoEconomics 37, no. 7 (July 1, 2019): 921–29. https://doi.org/10.1007/s40273-019-00775-8.
Shao, Hui, Vivian Fonseca, Charles Stoecker, Shuqian Liu, and Lizheng Shi. “Novel Risk Engine for Diabetes Progression and Mortality in USA: Building, Relating, Assessing, and Validating Outcomes (BRAVO).” PharmacoEconomics 36, no. 9 (September 1, 2018): 1125–34. https://doi.org/10.1007/s40273-018-0662-1.
Shao, Hui, Hamed Kianmehr, Piaopiao Li, Vivian Fonseca, and Lizheng Shi. “364-P: Efficacy of IGlarLixi on Five-Year Risk of Diabetes-Related Complications: A Simulation Experiment.” Diabetes 70, no. Supplement 1 (June 1, 2021). https://doi.org/10.2337/db21-364-P.
Kianmehr, Hamed, Ping Zhang, Meda E. Pavkov, Kai M. Bullard, Vivian Fonseca, Lizheng Shi, and Hui Shao. “139-OR: ADA Presidents’ Select Abstract: Potential Gains in Life Expectancy (LE) Associated with Achieving Treatment Goals in People with Type 2 Diabetes (T2D) in the U.S.” Diabetes 70, no. Supplement 1 (June 1, 2021). https://doi.org/10.2337/db21-139-OR.
Shao, Hui, Hamed Kianmehr, Lizheng Shi, Vivian Fonseca, and Joshua D. Brown. “140-OR: Projected Impact of the Medicare Part D Senior Savings Model (SSM) on Diabetes-Related Health and Economic Outcomes among Insulin Users Covered by Medicare.” Diabetes 70, no. Supplement 1 (June 1, 2021). https://doi.org/10.2337/db21-140-OR.

Welcome to bravo™ diabetes simulation model

What is the BRAVOTM Model?

Application Area includes but not limited to:

RISK STRATIFICATION

Trial Simulation

COST EFFECTIVENESS ANALYSIS

program evaluation

About BRAVO™ MODEL

bravo™ model compares to other diabetes models

BW and BMI

Hypoglycemia

GLOBALIZATION

utility and cost

Publications and Presentations

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