Clinical Trials for Comparative Effectiveness Research

1. Clinical Trials for Comparative Effectiveness Research Mark Hlatky MD Stanford University January 10, 2012

2. What is CER? • Generation and synthesis of evidence that • compares the benefits and harms • of alternative methods to prevent, diagnose, treat, and monitor a clinical condition • or to improve the delivery of care. • The purpose of CER is to • assist consumers, clinicians, purchasers, and policy makers • make informed decisions • that will improve health care • at both the individual and population levels. Institute of Medicine, 2009

3. CER Methods • CER can use very different research design • Randomized trials • Observational studies using registries, claims, or electronic health records • Simulations, models, meta-analysis • Randomized trials accepted as best approach because of control of confounding

4. RCT Limitations • Most trials due for regulatory approvals, and not good for CER • Use placebo, not “next best therapy” • Use ideal patients, not typical ones • Lab measures as endpoints • Safety poorly assessed

5. CER Trials • Limitations of RCTs for CER are not inherent • Can compare new therapy with an active control • Can enroll representative patients • Can focus on patient-centered outcomes

6. Representative trials • Generalizability of RCT results is always controversial • Inclusion/exclusion criteria can be minimized to broaden patient selection • Also important to include representative practice sites, particularly for trials of procedures • Volume-outcome relationship • Centers of excellence vs typical practice locations

7. Large Practical Trials • Larger sample sizes needed for CER trials • Use of active controls narrows expected superiority margin • “Equivalence trials ”need large sample sizes to narrow confidence intervals • Analysis of subgroups requires more patients • Trials need to be simpler and less expensive to be practical for CER

8. Reducing Trial Costs • Data collection is expensive, so minimize trial-specific data • Compact, simple data forms • Rely on existing mechanisms to capture data at baseline and during follow-up (hybrid trials) • Clinical registries (esp baseline data) • Electronic health records • Claims data

9. Clinical Registries • Registries are a middle ground between RCTs and regular care • Data elements standardized, collected as part of routine care • e.g., ACC PCI registry, STS CABG registry • Could use registry to collect clinical data, and just add randomization

10. Follow-Up Data • Registries typically collect data from acute care or procedures • Long-term follow-up needed • Link to claims, EHRs, or mortality files • Is elaborate adjudication of non-fatal outcomes necessary, or could claims be used instead? • Web follow-up for symptoms, functional status?

11. Cluster RCTs • CER also interested in quality of care, health delivery mechanisms, etc. • Can randomize practice sites to alternative care approaches (e.g., disease management) • Could also use cluster trials for “strategy trials” or default management approaches to common conditions (eg diabetes, hypertension)

12. Practical, Cluster RCT: Systems Approach to Heart Failure Care

13. Conclusions • RCT is one of several designs for CER studies • Larger trials generally needed for CER • Newer designs for RCTs needed to keep costs down and make CER feasible