Chang Lab | Department of Surgery | Washington University in St. Louis

The Chang Lab is focused on the health and economic burden of obesity and obesity-related multimorbidity, prevention of multiple myeloma, surgical treatment for obesity, transplant outcomes research, and health disparities.

The lab is led by Su-Hsin Chang, PhD, an associate professor of surgery in the Division of Public Health Sciences at WashU Medicine.

Dr. Chang is an applied econometrician and a health economist. Dr. Chang’s research focuses on health and economic consequences of obesity and surgical treatments of obesity, multiple myeloma prevention, transplant outcomes, and health disparities. Her research uses economic and econometric/statistical modeling to evaluate program and treatment effects. Dr. Chang’s research areas include treatment effect and policy evaluation; cost-effectiveness analysis; meta-analysis; and comparative effectiveness.

In addition to leading the Chang Lab, Dr. Chang teaches the course “Decision Analysis for Clinical Investigation and Economic Evaluation” in the Master of Population Health Sciences (MPHS) degree program.

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Principal investigator

Su-Hsin Chang, PhD

Associate Professor of Surgery
Division of Public Health Sciences

Phone: 314-362-5298

Contact

600 S Taylor Ave, 2nd Floor
St. Louis, MO 63110
314-362-8623
[email protected]

Opportunities

The Chang Lab welcomes postdoctoral research associates, statistical data analysts, PhD and graduate students, research assistants, and research scientists. For inquiries, please contact:

[email protected]

Current research

Multiple myeloma

Dr. Chang serves as leader of the coordinating center for the Cancer Intervention and Surveillance Modeling Network (CISNET) Multiple Myeloma Incubator Program at WashU Medicine.

In the CISNET Multiple Myeloma Incubator Program, the Washington University Modeling Group has constructed and calibrated a discrete event simulation (DES) tailored to model the natural history of multiple myeloma (WUMM-DES), from no disease, the pre-malignant condition (i.e., MGUS) development, progression of MGUS to multiple myeloma, and death for the U.S. population aged 20 years or older. The developed WUMM-DES can be tailored to set research priorities and design clinical trials, including assessing sample sizes and power, evaluating the impact of treatment adherence of the participants, and determining the optimal treatment strategies. It can also be used to predict trial results and set policy goals.

The group has also constructed and calibrated a discrete-time, multi-state compartmental model of the natural history of multiple myeloma. This model follows birth cohorts of individuals as they progress from no disease to monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM). The developed WUMM-CM model can be tailored to set research priorities and design clinical trials, including assessing sample sizes and power, evaluating the impact of treatment adherence of the participants, and determining the optimal treatment strategies. It can also be used to predict trial results and set policy goals.