David M Kent, MD, MS PACE Director, Tufts Medical Center

1. “Caring for the Individual Patient: Understanding Heterogeneous Treatment Effects”A Special Publication from the National Academy of MedicineClinical Effective Research: Project working group updatesSeptember 30, 2019 David M Kent, MD, MS PACE Director, Tufts Medical Center

2. Conference Overview • On May 31, 2018, NAM convened a workshop in Washington DC, to discuss approaches to examining HTE to personalize and improve patient care • Funded by PCORI (1900-TMC) • Part of PCORI’s broader mission to understand the current state of the science in the development and use of predictive approaches to analyze (or reanalyze) research data.

4. “The premise of traditional research is to put a treatment at the center of consideration and decide, Is this treatment helpful for an average patient? Trouble is, there aren’t very many average patients out there, and I, like most people, am not an average patient.” —Seth Morgan, neurologist, multiple sclerosis patient, and patient advocate

5. Conference Summary • Participants included patients and patient advocates, physicians, medical researchers, research funders, and health insurers, as well as representatives from pharmaceutical companies, federal agencies, professional associations, and medical journals • 67 in-person attendees (excluding Tufts / NAM staff)

6. Conference Summary • The full day discussion centered on the following motivating questions: • Potential: How can clinical trial data be analyzed to yield reliable patient-centered treatment effect estimates? • Risks: How can we be sure personalizing evidence will improve decision making? • Lessons learned: What can be learned from the challenges of genomics-based personalized medicineand other prior efforts? • Strategies: How should clinical research and clinical practice be redesigned to support the generation and the dissemination of patient-centered evidence?

7. Conference Agenda & Topics • Overview of heterogeneous treatment effects: Moving from evidence-based medicine to personalized/precision medicine • An equation-free presentation of new methods for prediction of treatment benefit and model evaluation • Discussion with Stakeholders • From Research into Practice: Implementation and oversight • Opportunities for collaborative action

8. Areas of Consensus • Prediction of heterogeneous treatment effects is hard (but important). • Need to move away from one-variable-at-a-time subgroup analysis. • Variations in baseline outcome risk can be expected to influence absolute treatment effects in treatment-eligible patients • Substantial variation in outcome risk is common even in clinical trial populations. • The clinical importance of effect heterogeneity is generally best examined on the absolute (risk difference) scale • The field must also determine best practices for implementing predictions tools in clinical practice. • Methods for modeling HTE and for implementing models in clinical care to personalize treatment decisions are still in their infancy.

9. Areas of Disagreement • Definition of HTE: • A change in the magnitude or direction of treatment effect across levels of a covariate • A scale dependent concept versus restricted to relative effect scales

10. Future Direction (selected) • Develop guidance on approaches for assessing the effectiveness or validity of predictive and prognostic models for evaluating HTE • Understand the comparative performance of machine learning methods that can be applied to understand HTE • Determine the role for observational data • Facilitate collaboration and leadership to create prioritized opportunities for large trial re-analyses to examine the HTE most likely to impact population health • Describe approaches to implementing risk models both at the point of care and at the level of the health care system

12. Thank you!