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Biomarkers and Surrogate Endpoints in Randomized Clinical Trials
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    SPEAKER(S)

Prof. Marc Buyse - IDDI (International Drug Development Institute) & University of Hasselt, Belgium

Marc Buyse holds degrees from Brussels University, Cranfield University (UK) and a ScD in biostatistics from the Harvard School of Public Health. Prior to founding the International Drug Development Institute (IDDI) in 1991, he had worked for 12 years at the EORTC in Brussels and for 2 years at the Dana Farber Cancer Institute in Boston. He has held positions in statistical societies, including President of the International Society for Clinical Biostatistics, President of the Quetelet Society and Board Member of the Society for Clinical Trials. He is currently the Executive Director of IDDI and an Associate Professor of Biostatistics at Hasselt University in Belgium. He has published extensively on the methodology of clinical trials and meta-analysis in oncology.

Talk Online Publication: Oct 2007

TOPICS COVERED IN BIOMARKERS AND SURROGATE ENDPOINTS IN RANDOMIZED CLINICAL TRIALS

Definitions of biomarker, clinical endpoint, prognostic biomarker, predictive biomarker, and surrogate endpoint - Validation of prognostic, predictive and surrogate biomarker - Response as a surrogate endpoint for survival in advanced colorectal cancer - Progression-free survival as a surrogate endpoint for survival in advanced colorectal cancer - The surrogate threshold effect - Diseasefree survival as a surrogate endpoint for survival in resectable colorectal cancer - PSA as a surrogate endpoint for survival in advanced prostate cancer

How to cite this talk:
Buyse, M. (2007), "Biomarkers and Surrogate Endpoints in Randomized Clinical Trials", in Berger, V. (ed.), Design and Analysis of Randomized Clinical Trials: Design, Analysis & Theory, The Biomedical & Life Sciences Collection, Henry Stewart Talks Ltd, London (online at http://hstalks.com/bio)

Direct talk access link:
http://hstalks.com/lib.php?t=HST44.1532_1_2&c=252

    DETAILED SLIDE INDEX

1. Introduction
2. Outline
3. Clinical endpoint
4. Biomarker
5. Prognostic factor
6. Predictive factor
7. Prognostic factor vs. predictive factor
8. Surrogate endpoint
9. Need for surrogates
10. Efficacy and safety in a new tretment development
11. Statistical validation: prognostic biomarker
12. Statistical validation: predictive biomarker
13. Validation of surrogate biomarker: Prentice criteria
14. Validation of surrogate biomarker: Buyse criteria
15. Validation of surrogate endpoints: illustration
16. Prediction of clinical outcome
17. Validation of surrogate endpoints: meta analysis
18. Advanced colorectal cancer: response and survival
19. Response and survival trial design
20. Survival curves
21. Response rates
22. Survival curves by response
23. Treatment effects correlation: survival / response
24. Advanced colorectal cancer: PFS and survival
25. PFS and survival trial design
26. PFS and survival curves
27. The "surrogate threshold effect"
28. A related approach in advanced colorectal cancer
29. Treatment effects correlation: survival / PFS
30. A related "surrogate threshold effect"
31. Example in resected colorectal cancer
32. Example in early colorectal cancer
33. Correlation between endpoints
34. Treatment effects correlation: survival / DFS
35. Example in advanced prostate cancer
36. Example in advanced prostate cancer: 3 variants
37. Objectives of the experiment
38. PSA as a surrogate for survival: individual level
39. PSA as a surrogate for survival: trial level
40. Messages from examples on surrogate validation
41. Ideal requirements for surrogate endpoint validation
42. END