1. Real-World Evidence: What Is It and Why Is It so Important In MS?

3. This program will include a discussion of data that were presented in abstract form. These data should be considered preliminary until published in a peer-reviewed journal.

4. Introduction

6. Information Gained From RCTs and Observational Data

7. Information Gained From RCTs and Observational Data: Limitations

8. Sources of RWE: Advantages and Limitations

9. Checklist for High Quality RWE Studies

10. Summary of Key Points

11. Sources of RWE: Structured Databases

12. MSBase Registry

13. MSBase: Learnings About Effect of Early Treatment on Conversion to SPMS

14. Potential for Learning About Treatment Optimization

15. MS Registries and Cohorts: A Sample

16. Treatment-Related Data Collection in Germany: PANGAEA Observational Study

17. Need for Widespread Data Collection: Complementary to RCTs

18. Advantages and Challenges of RCTs and RWE

19. Propensity Score

20. Propensity Score Matching

21. Propensity Score Matching: Controlling for Variables

22. Propensity Score-Based Methods in Cardiology

23. Propensity Score-Based Method: Coffee and Mortality

24. Distribution of Propensity Scores Before and After Matching

25. MSBase Propensity-Matched Data: Escalation to Natalizumab vs Fingolimod in Active RRMS

26. Propensity-Matched Comparison of Sick Days: PEARL and PANGAEA Observational Studies

27. Bias in Observational Studies: Checklist

28. Smoking and MS Progression: Swedish National MS Registry

29. Swedish Registry Disability Outcomes: Developing an Age-Related MS Severity Score

30. Vast Amounts of Data Are Needed

31. Individualized Treatment and Big-Data RWE: A Combined Approach

32. Impactful RWE Requires Structured Data Collection

33. Concluding Remarks

34. Abbreviations