Project Summary Dr. Bannuru’s long-term career goal is to combine expertise in clinical medicine, clinical research and mind- body medicine, in a way that allows him to identify key clinical opportunities, and to lead multi-disciplinary research to develop models that allow for a more flexible evidence-base for the practice of personalized medicine. Dr. Bannuru received postdoctoral fellowship (T32 & F32) to train in clinical research and gain an introduction to comparative effectiveness research. The overall objective of this K23 proposal is to provide Dr. Bannuru protected time to acquire advanced skills and experience in mind-body medicine research necessary to achieve his long-term goal. The proposed career development plan will enable Dr. Bannuru to achieve his immediate career goal of refining and consolidating his research skills in the development of predictive models and risk stratification models, extending methods he has employed on one level (study level) to another level (patient-level) data, learning other modeling techniques (such as individual patient data (IPD) analysis), and increasing his fund of knowledge regarding Complementary and Integrative Medicine (CIM) so that the mind- body therapy evidence-base developed is more applicable to individual patients. Career Development Activities: This proposed plan builds logically on his training as a physician, as well as his research education and prior work as part of his F32. With his mentors, Dr. Bannuru has crafted a comprehensive training plan consistent with his career goals. The plan will engage him in robust training activities including: 1) structured mentorship; 2) specific training in mind-body medicine research; 3) constructing and managing the database for IPD analysis; 4) advanced training in IPD network meta-analysis, predictive modeling and responsive sub- group analysis; 5) research project; 6) workshops and seminars; 7) scientific writing and grantsmanship; and 8) responsible conduct of research. Dr. Bannuru has assembled a team of mentors with complementary expertise in the key areas of mind-body medicine, osteoarthritis, IPD methodology, predictive analytics and statistics. In addition to providing scientific guidance, his mentors will also offer career advice and facilitate new research collaborations which will allow him to broaden his professional network. Environment: Dr. Bannuru will benefit from the wealth of resources available to young investigators at the Tufts Medical Center. His association with Tufts Center for Complementary and Integrative Medicine, Tufts Clinical and Translational Science Institute and Brown University Evidence Practice Center provides an ideal environment for interaction with well-known researchers in the field of mind-body medicine and comparative effectiveness research which, going forward will help him to enhance his expertise in state-of-the-art research methods, and develop into an independent investigator. Research: Osteoarthritis (OA) affects more than 27 million people in the US, leading to chronic pain, disability, and substantial health-care costs. In the absence of effective disease-modifying treatments, current guidelines recommend a multimodal approach for treating OA, which integrates non-pharmacological treatments such as exercise, and mind-body therapies such as Tai Chi. There is evidence suggesting mind- body interventions are better than attention control but these therapies were rarely compared with active treatments. A network meta-analysis will enable us to determine the relative benefits of multiple interventions and will allow us to rank them. Furthermore, to ensure that the right patients receive the most effective treatment at the optimal dosage, it is essential to identify responsive subgroups, which individual trials are not usually powered a priori to identify. By combining patient-level data from 15 RCTs (1529 patients) conducted worldwide, and using IPD network meta-analysis approach Dr. Bannuru’s proposal aims: 1) to evaluate the effectiveness and safety of Mind-body therapies (Tai Chi, Yoga) vs. other CIM interventions (Exercise, Physical Therapy) and controls (Attention Control, Usual Care) in improving clinical symptoms (pain, function) and quality of life in OA patients (Aim 1); 2) to identify the patient (e.g. age, gender, BMI, baseline pain, depression, anxiety) characteristics which increase the likelihood of response to Mind-body therapies vs. other CIM interventions (Aim 2); and 3) to evaluate the optimal dosage and duration of CIM interventions in relation to pain, function and quality of life benefits in OA patients (Aim 3). This proposal is innovative because we are deploying novel network meta-analysis techniques to individual patient data to assess the relative benefits and risks of mind-body interventions. To the best of our knowledge, this kind of IPD database of OA patients has not been compiled in the CIM field. Results from this study have the potential to change clinical practice for OA patients, particularly since mid-body therapies are not covered by payers despite their equality/superiority to traditional interventions. In addition, the use of IPD network meta-analysis techniques to compare multiple interventions is an effective pragmatic alternative to a large-scale clinical trial. This methodology can be extended to multiple disease states; it is therefore highly scalable and of great impact. This advanced training is essential, and a productive step in Dr. Bannuru’s career to catalyze his transition to an independent mind- body medicine investigator capable of competing successfully for research funding.

Project Narrative Public Health Relevance: While mind-body practices, including Tai Chi are frequently used by individuals affected by osteoarthritis, rigorous research on the comparative effectiveness of these practices is lacking. Osteoarthritis affects more than 27 million people in the US, leading to chronic pain, disability, and substantial health-care costs. The proposed study will estimate the relative benefits of mind-body interventions for osteoarthritis, and determine which interventions work for whom and under what conditions.