Skip to main content

Dr. Rebecca Cleveland’s research involves identifying predictors of osteoarthritis (OA) outcomes including joint changes, pain and disability. Pain and disability are leading consequences of OA, and are conditions associated with a number of comorbidities and even death.

A particular interest of Dr. Cleveland has been carrying out research to investigate how OA and comorbid conditions lead to premature mortality.

Other interests include social determinants, BMI, physical activity and physical functioning as predictors of OA outcomes.

Dr. Cleveland’s team uses statistical methods to support various projects across TARC and its affiliates with regard to their biostatistical needs, including consultation on design, conduct, analysis and dissemination.

The team is particularly interested in using statistical techniques that have traditionally not been used in OA research such as data reduction methods, machine learning and precision medicine for outcome prediction. This includes using these methods to identify of those at high risk for developing OA, dying, or transitioning into another comorbid state.

Core Team Members:

Carolina Alvarez, MS

Liubov Arbeeva, MS