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Medical care is delivered one-patient-at-a-time. But the evidence for practicing is derived by aggregating many patients—typically thousands or tens of thousands of patients--into groups. This group-derived evidence would be highly informative for medical practice if all patients were identical. The dissimilarity of individual patients, however, potentially undermines clinical research as a scientific basis for the practice of medicine. The Predictive Analytics and Comparative Effectiveness (PACE) Center seeks to better understand and address the limitations of using group-derived evidence as the basis for decision making in individual patients. Our approach is based on the close integration of clinical and statistical reasoning. Our goal is to provide clinicians and patients with evidence better tailored to their particular circumstances; we have expertise in clinical medicine, risk modeling, individual patient meta-analysis, and observational comparative effectiveness studies.
David Kent, MD, CM, MSc Director and Professor of Medicine
June C. Baglione Senior Research Administrator
Riley Brazil Research Fellow
Gaurav Gulati, MD Research Fellow
Mike Hughes Assistant Professor of Computer Science
David van Klaveren, PhD, MSc Research Associate
Benjamin Koethe, MPH Statistician
Lester Y. Leung, MD, MSc Director, Comprehensive Stroke Center; Director, Stroke and Young Adults (SAYA) Program
Christine Lundquist Research Associate
Jennifer Lutz, MA Research Assistant
Rebecca Maunder Project Coordinator
Hannah L. McGinnes, MPH Research Assistant Jason Nelson, MPH Statistician
Jinny Park, MPH Research Project Coordinator Jessica Paulus, ScD Research Director and Assistant Professor of Medicine
Bridget Perry, PhD Research Fellow
Robin Ruthazer, MPH Statistician and Assistant Professor of Medicine
Jenica Upshaw, MD Medical Director, Cardio-Oncology Program; Attending Physician, Advanced Heart Failure
Esmee Venema, MD, MSc Visiting Research Fellow
Benjamin S. Wessler, MD Staff Cardiologist and Assistant Professor of Medicine
This project aims to conduct a large-scale validation of cardiovascular clinical prediction models (CPMs).
Setting up a PCORI Predictive Analytics Resource Center (PARC) to provide various professional services including development of a portfolio of research activities in the area of predictive analytics.
View Dr. Kent’s recent publications on PubMED>
View Mr. Nelson’s recent publications on PubMED>
View Dr. Paulus’ recent publications on PubMED>
View Ms. Ruthazer’s recent publications on PubMED>
View Dr. van Klaveren’s recent publications on PubMED>
View Dr. Wessler’s recent publications on PubMED>
“Heterogeneity of treatment effect and risk-stratified approach for reporting/ implementing clinical trial results.” 16th Global Cardiovascular Clinical Trialists (CVCT) Forum. Washington, DC. December 7, 2019.
“Prediabetes Predictive Model to Personalize Diabetes Risk.” OptumLabs Research and Translation Forum. Boston, MA. November 20, 2019.
“Improving Diabetes Prevention Based on Predicted Benefits of Treatment.” What’s Right For Me? Practical Approaches to Personalized Medicine. PCORI Annual Meeting. Washington, DC. September 18, 2019.
“Personalized evidence based medicine: predictive approaches to heterogeneous treatment effects in randomized trials.” Society for Clinical Trials Annual Meeting. New Orleans, LA. May 19, 2019.
“Point-Hemoglobin A1c Goals: Is Lower Better? ” Tufts Medical Center Point-Counterpoint Grand Rounds. Boston, MA. October 12, 2018.
“Evidence and the Individual Patient: Understanding Heterogeneous Treatment Effects for Patient-Centered Care.” National Academy of Medicine. Washington, DC. May 31, 2018.
"Selecting patients for lung cancer screening by personalized risk offers limited long term gains" Tufts Medical Center. Boston, MA. February 1, 2018
“Personalized Risk Information in Cost Effectiveness Studies (PRICES).” Chapter 14. Health Economics Common Fund Research Symposium. Bethesda, MD. September 25, 2017.
“Moving Beyond Averages” Patient-Centered Outcomes Research Institute. January 2017
“PACE Symposium: Using Group Data to Treat Individuals” Tufts Medical Center, Boston, MA. June 4, 2015.
“Getting it Right the First Time: Can We Predict Who is Likely to Respond?” The Myth of Average: Why Individual Patient Differences Matter Conference. Omni Shoreham Hotel, Washington DC, Nov 30, 2012.
“An index to identify stroke-related versus incidental patent foramen ovale in cryptogenic stroke.” Neurology Podcast. August 13 2013 Issue.
Jennifer Lutz, MA Program Coordinator II, Predictive Analytics and Comparative Effectiveness (PACE) Center Phone: 617-636-7405 Fax: 617-636-0022 https://twitter.com/Tufts_PACE