1. Surrogate Endpoints and Correlative Outcomes Hem/Onc Journal Club January 9, 2009

2. Today’s paper  A prognostic marker was identified  It has a strong association with survival  But what to do with it?  Should it: change treatment decisions? be used in designing new clinical trials? be used to help convey risks, benefits, prognosis to patients?  How different are the prognoses for patients with high vs. low levels of CA 19-9?

3. Prognostic and Predictive  A prognostic factor is any measurement available at the time of surgery that correlates with disease- free or overall survival in the absence of therapy and is able to correlate with the natural history of the disease.  A predictive factor is any measurement associated with response to a given therapy.

4. Association vs. Surrogate?  Strength of association  Association is much weaker  To show biomarker should be used as surrogate: it should distinguish between groups approach should involve sensitivity/specificity type measures Similar measure for survival data is C-index

5. Measuring “benefit”  Overall survival Pros: this is the “gold-standards” Problems: takes too long, too costly (in most cancers)  Biomarkers (“correlative” outcomes) Pros: feasible in the short-term Cons:  can be costly  might have many to measure  might not know all the relevant markers  might not know how they all “fit together”  If Biomarkers are used as “surrogates” for survival, then they need to be TRUE surrogates.  “Correlative” outcome is not good enough

6. “True” Surrogate Marker  Defining Characteristic: a marker must predict clinical outcome, in addition to predicting the effect of treatment on clinical outcome  Operational Definition establish an association between marker & clinical outcome establish an association between marker, treatment & clinical outcome, in which marker mediates relationship between clinical outcome and treatment

7. Surrogate Markers marker Clinical outcome treatment Clinical outcome 1) establish an association between marker & clinical outcome. 2) establish an association between marker, treatment & clinical outcome, in which marker completely mediates relationship between clinical outcome and treatment. marker

8. NOT Surrogate Markers marker treatment Clinical outcome treatment marker Clinical outcome

9. Commonly used surrogates  PSA  Any more?  Not really!

10. Median survival of 9 vs. 21 months

11. How predictive of outcome? Data generated according to observed data survival >1yr survival <1yr low CA 19-9 16555 (0.25) 220 high CA 19-9 1023 (0.70) 33 PPV =P(die<1 yr | high CA 19-9) = 23/33 = 0.70 NPV = P(die>1yr | low CA 19-9) = 165/220 = 0.75

12. why if medians are 9 and 21? Significant overlap of failure distributions:

13. Survival Data  hard to see how ‘diagnostic’ markers may be.  Other approaches (e.g. C-index) can be used  Nomograms: models where prognostic (and predictive) variables are used to obtain individualized predictions of survival. Very popular in prostate cancer with survival data idea is that the combination of predictors taken together may be very accurate even if each individual predictor is not precisely associated with survival

14. Copyright ©2007 American Association for Cancer Research Armstrong, A. J. et al. Clin Cancer Res 2007;13:6396-6403 Figure 3">

15. Relevance  Conclusions state: “In the postoperative setting, the CA 19- 9 level can be used as a predictor of overall survival. Patients with postoperative CA 19-9 level > 180 U/ml have a significantly worse survival than those patients with CA 19 lower than 180 U/ml.”  Looks more related to survival than margin status nodal involvement tumor size  But why didn’t they include any measure of stage?  And then: “These patients should be considered for alternative sytemic therapy or chemoradiotherapy protocols.”