Evidence-based medicine arose from a clear need and represents a major advance in the science of clinical decision making. Despite broad acceptance of evidence-based medicine, however, a fundamental issue remains unresolved: evidence is derived from groups of people, yet medical decisions are made by and for individuals. Despite persistent assertions from clinicians that determining the best therapy for each patient is a more complicated endeavor than just picking the best treatment on average, traditional approaches have been overly reliant on the average effects estimated from the outcomes of clinical trials.

This Special Publication is based on a workshop, held by the National Academy of Medicine, that considered patient and stakeholder perspectives on the importance of understanding heterogeneous treatment effects (HTE) and best practices for implementing clinical programs that take HTE into account. For evidence to be more applicable to individual patients, we need to combine methods for strong causal inference (first and foremost, randomization) with methods for prediction that permit inferences about which particular patients are likely to benefit and which are not. Better population-based outcomes will only be realized when we understand more completely how to treat patients as the unique individuals they are.

Contents

• ABOUT THE NATIONAL ACADEMY OF MEDICINE
• WORKSHOP PLANNING COMMITTEE
• REVIEWERS
• PREFACE
• SUMMARY
• 1. INTRODUCTION
  • OVERVIEW OF THE WORKSHOP
• 2. THE PROMISE OF PERSONALIZED EVIDENCE-BASED MEDICINE
  • USING RISK-BASED FORECASTING TO PERSONALIZE MEDICINE
  • DEVELOPMENT OF A DECISION SCORE TO OPTIMIZE TREATMENT DECISIONS
  • DESIGNING RANDOMIZED CONTROLLED TRIALS WITH HETEROGENEOUS TREATMENT EFFECTS IN MIND
  • REGULATORY UTILITY OF UNDERSTANDING HETEROGENEOUS TREATMENT EFFECTS
  • DISCUSSION
• 3. PATIENT PERSPECTIVES OF THE SIGNIFICANCE OF UNDERSTANDING HETEROGENEOUS TREATMENT EFFECTS
  • ENGAGING PATIENTS IN DISCUSSIONS ABOUT HETEROGENEOUS TREATMENT EFFECTS
  • THE PROBLEM WITH TREATMENTS AIMED AT THE “AVERAGE PATIENT”
  • TAKING PATIENT PREFERENCES INTO ACCOUNT
  • PROVIDING PATIENTS WITH DECISION-MAKING TOOLS
  • INSURERS AND HETEROGENEITY
  • DISCUSSION
• 4. NEW METHODS FOR THE PREDICTION OF TREATMENT BENEFIT AND MODEL EVALUATION
  • POLYGENIC RISK SCORES
  • PROMISE OF MACHINE LEARNING
  • METHODOLOGICAL ISSUES RELATED TO PREDICTIVE SCORES
  • ABSOLUTE RISK VERSUS RELATIVE RISK
• 5. NEXT STEPS FOR IMPLEMENTATION
  • USING HETEROGENEOUS TREATMENT EFFECTS IN ROUTINE CLINICAL CARE
  • APPLYING PHARMACOGENOMICS IN CLINICAL CARE
  • IMPROVING PERFORMANCE MEASURES
  • IDENTIFYING CLINICALLY MEANINGFUL HETEROGENEOUS TREATMENT EFFECTS
  • DISCUSSION
• 6. A RESEARCH AGENDA FOR PERSONALIZING CARE AND IMPROVING TREATMENT OUTCOMES
  • DESIGNING RESEARCH TO MEET THE NEEDS OF END-USERS
  • A RESEARCH AGENDA FOR UNDERSTANDING AND LEVERAGING TREATMENT HETEROGENEITY TO IMPROVE PATIENT CARE
  • DISCUSSION
  • CONCLUSIONS
• REFERENCES
• Appendix A. GLOSSARY
• Appendix B. WORKSHOP PARTICIPANTS, WEB PARTICIPANTS, AND STAFF
• Appendix C. WORKSHOP AGENDA

Suggested citation:

Kent, D., J. Paulus, M. Ahmed, and D. Whicher, Editors. 2019. Caring for the Individual Patient: Understanding Heterogeneous Treatment Effects. Washington, DC: National Academy of Medicine.

Support for this publication was provided by the Patient-Centered Outcomes Research Institute^® (PCORI^®), through two awards: a Patient-Centered Outcomes Research Institute (PCORI) Eugene Washington PCORI Engagement Award (1900-TMC) and the Predictive Analytics Resource Center (SA.Tufts.PARC.OCSCO.2018.01.25); and the Predictive Analytics and Comparative Effectiveness (PACE) Center at the Tufts Medical Center. The views presented in this publication are solely the responsibility of the editors and do not necessarily represent the views of the Patient-Centered Outcomes Research Institute^® (PCORI^®), its Board of Governors, or its Methodology Committee; or of the PACE Center and/or the Tufts Medical Center.

Library of Congress Control Number: 2019948398

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