1. MTPPI EPO Outcomes Research Presented to FDA /CDER Joint Meeting of the Cardiovascular and Renal Drugs & Drug Safety and Risk Management Advisory Committees September 11, 2007 Hilton Washington Gaithersburg, MD 1

2. Background and Context Dennis Cotter President of Medical Technology and Practice Patterns Institute (MTPPI) 4733 Bethesda Avenue #510 Bethesda, MD 20814 2

3. Decade-long study of EPO Identified Medicare and non-Medicare use of EPO Quantified total EPO use among dialysis patients Currently, PI on R01 grant focusing on the role of EPO dosing and patient outcomes 3

4. Hemoglobin values have increased steadily after EPO introduced Source: USRDS 2006 Annual Data Report 4

5. Widespread EPO use based on 2000 DOQI findings including: – Survival benefits – Decreased incidence of hospitalization – Partial regression of left ventricular hypertrophy (LVH) – Improved quality of life – Increased exercise capacity 5

6. However, survival findings might have been confounded by EPO treatment itself 6

7. Application of causal modeling techniques Received R01 grant (5R01DK066011-02 Epoetin Therapy and Survival of Hemodialysis Patients) to examine the role of EPO treatment in patient outcomes 7

8. Introduction to Causal Modeling Miguel Hernán Associate Professor of Epidemiology Department of Epidemiology Harvard School of Public Health 677 Huntington Avenue Boston, MA 02115 8

9. Goal To estimate the effect of EPO on hematocrit and survival among renal failure patients with anemia A RCT would be ideal Next best thing is an observational study that mimics an RCT 9

10. Problem with observational studies Patients with worse prognosis tend to receive higher EPO doses (confounding by indication) Not a problem in ITT analyses of RCTs 10

11. Actually, there are 2 problems 1. Confounding may be unmeasured 2. Confounding may be measured but inappropriately adjusted for 11

12. Problem 1 Unmeasured confounding THE fundamental problem Need measurements of all important prognosis factors that are also indications for treatment but can never prove you have all confounders 12

13. Problem 2 Inappropriately adjusting for confounding Conventional statistical methods cannot appropriately adjust for confounding When the prognosis factors (e.g., hematocrit) that affect treatment decisions (e.g., EPO dose) are themselves affected by prior treatment decisions A solvable problem: just use inverse probability weighting (IPW) 13

14. IPW: Utility Can be used to mimic an RCT using observational data Under the assumption of no unmeasured confounding Even in the presence of time-varying confounders affected by prior treatment 14

15. IPW: Technical details Each subject is weighted by the inverse of the estimated probability of receiving the EPO dose that he actually received Essentially equivalent to standardization The corresponding weighted models estimate the parameters of marginal structural models 15

16. IPW: Examples of application IPW extensively used in HIV/AIDS research In fact, NIH required expertise on IPW when requesting applications for estimating the effects of antiretrovirals from observational data IPW replicated estimates from RCTs in the HIV/AIDS field 16

17. IPW: Our application We used IPW to estimate the survival and mean hematocrit of subjects randomly assigned to different EPO doses We needed IPW because hematocrit is a time-dependent confounder (predicts both EPO dose and outcome) and is affected by prior EPO dose 17

18. Research Findings Yi Zhang Senior Analyst MTPPI 18

19. The effect of EPO dose on hematocrit response among elderly hemodialysis patients in the U.S. Cotter D, Zhang Y, Thamer M, Kaufman J, Hernán MA. Kidney International 2007 [in press] 19

20. Mean monthly hemoglobin and mean EPO dose per week 20

21. Prior research Dose response relationship has not been examined since Phase II trials –Stringent patient eligibility criteria –Limited dose Observational studies have shown an inverse relationship between EPO dose and hematocrit –Confounding by indication 21

22. Research goals To mimic an RCT in which subjects are randomly assigned to different arms, each receiving a different EPO dose To compare the achieved hematocrit in each arm 22

23. Data source United States Renal Data System (USRDS) –administrative database on ESRD patients whose care is covered by Medicare –include extensive baseline and follow-up demographic and clinical data –outpatient EPO claims include monthly total EPO dose and hematocrit values –most recent USRDS data available for researchers 23

24. Patient population Retrospective cohort study. 14,001 patients who started EPO and dialysis in 2003. –>=65 years of age –had first claim with 90 days of their first ESRD service date –had not used EPO before –did not have a kidney transplant, HIV or cancer before starting dialysis. –were not censored during the first complete dialysis month 24

25. Study variables Censoring events –change of dialysis modality, transplantation, 30 days after change of dialysis provider, gap in outpatient dialysis services, or death Exposure: Average EPO dose in the first 3 months of dialysis Outcome: HCT at month 4 25

26. Statistical methods Estimated inverse probability weights to adjust for measured confounders, and then fit a weighted regression model Constructed a dose-response curve Each hematocrit-EPO dose point in the curve shows the estimated average hematocrit if subjects had been randomly assigned to that EPO dose 95% CI were based on bootstrap techniques 26

27. Distribution of patients by initial EPO doses 27

28. Distribution of patients by hematocrit group 23,400 21,000 21,100 21,500 26,000 Average EPO dose (U/week) 28

29. 4 Dose response curve and 95% confidence intervals based on MSM 29

30. Dose response curve based on standard adjustment 30

31. Study limitations Potential for unmeasured confounding Monthly HCT and EPO dose Unobserved clinical factors (iron level, blood pressure, nutritional status...) EPO use in the hospital, route of EPO administration Did not consider dynamic EPO dosing regimes Restriction of study period and population 31

32. Conclusions Dose-response curve is S-shaped HCT plateaus at 38.5% for average EPO doses greater than 20,000 units/week Normal HCT target might not be achievable for dialysis population Starting doses recommended by FDA are appropriate and are in the linear portion of the curve 32

33. The relationship between EPO dose and survival among hemodialysis patients Zhang Y, Thamer, Cotter D, Kaufman J, Hernán MA Joint Statistical Meetings 2007 [Abstract] 33

34. Research goals To mimic an RCT in which subjects are randomly assigned to different arms, each receiving a different average dose of EPO To compare the survival in each arm 34

35. Previous research A plethora of observational studies have shown that higher hematocrit is associated with better survival for dialysis patients However, results of clinical trials demonstrated that patients targeted to higher hematocrit levels did not show survival benefits –led to a recent FDA black box warning The EPO dose-survival relationship has not been empirically determined 35

36. Study design 20,580 incident hemodialysis patients Eligibility criteria – Age 65 and older – First ESRD service in 2003 – Attend freestanding facilities – Complete baseline (first 3 months of dialysis) data Exposure: cumulative average EPO dose Outcome: death during months 4-12 Censored if change of provider/modality, or loss to follow-up 36

37. Methods Estimated inverse probability weights to adjust for measured confounders, and then fit a weighted Cox model Constructed survival curves for each EPO dose Each curve shows the survival if subjects had been randomly assigned to that EPO dose 95% CI were based on bootstrap techniques 37

38. Mortality hazard ratios by EPO dose (quartiles) 38

39. Mortality rate by EPO dose 39

40. Survival for EPO doses based on 3 different doses 40

41. Study limitations Potential for unmeasured confounding as always Did not consider dynamic EPO dosing regimes One-year survival only 41

42. Conclusions Lowest mortality found for average EPO doses of 8,500-15,000 units per week Treating all patients with higher EPO doses (>15,000 U/wk) might decrease average survival 42

43. Relevance of research findings to FDA labeling decisions INITIAL DOSE In our study cohort, 61% of all incident elderly dialysis patients received an initial EPO dose higher than the FDA-approved 50-100 U/kg range DOSE-RESPONSE Based on our dose-response model, a population average EPO dose higher than 12,000 U/week would result in exceeding the FDA-approved HCT target of 36% RISK Based on our dose-survival model, a population average EPO dose higher than 15,000 U/week would result in progressively higher mortality risks HYPORESPONSIVE PATIENTS The risk of increased mortality is greatest among hyporesponsive patients who receive the largest EPO doses 43 Return to Cotter