Outcomes Following Coronary Stenting: A National Study of Long Term, Real-World Outcomes of Bare-Metal and Drug-Elutin

1. Outcomes Following Coronary Stenting:A National Study of Long Term, Real-World Outcomes of Bare-Metal and Drug-Eluting Stents Pamela S. Douglas, J. Matthew Brennan, Kevin J. Anstrom, Eric L. Eisenstein, David Dai, Ghazala Haque, David F. Kong, Ralph Brindis, Art Sedrakyan, David Matchar, Eric D. Peterson Duke Clinical Research Institute Duke University Medical Center

2. Disclosures:( See www.dcri.duke.edu for full information) Pamela S. Douglas: Nonerelevant J. Matthew Brennan: None Kevin Anstrom: Research Support from AstraZeneca, Bristol Myers Squibb, Eli Lilly and Medtronic; consultant for Johnson & Johnson and Pfizer. Eric L. Eisenstein: Research Support from Medtronic Vascular and Eli Lilly David Dai: None Ghazala Haque: None David F. Kong: Nonerelevant Ralph Brindis: None Art Sedrakyan: None David Matchar: None relevant Eric D. Peterson: Research Support from BMS/Sanofi and Merck/Schering Sponsor and funding: AHRQ CV Research Consortium Additional support: ACC-NCDR Funding and Disclosures

3. Background • Clinical trials demonstrate reduced restenosis with drug eluting coronary stents (DES) compared to bare metal stents (BMS) • However, some trials and registries have reported late stent thrombosis and higher mortality with DES • Questions remain regarding the effectiveness and safety of DES in the real world and among understudied patient populations

4. Goal and Population • Goal • To examine comparative effectiveness and safety of DES vs BMS in a national PCI cohort • Study population • All PCI pts > 65 yo in NCDR CathPCI 1/04-12/06 • Follow up obtained through linkage to CMS inpatient claims data using indirect identifiers; 76% matched • Final cohort • 262,700 pts • 83% DES; 46% Cypher, 55% Taxus

5. Analysis • 30 month outcomes • Death, MI, Stroke, Revascularization, Major bleeding • Overall and in important subgroups • Outcomes adjustments • Inverse propensity weighted model (102 covariates) • Cox proportional hazards model (60 covariates) • Sensitivity analyses • Results in ‘RCT-like’ population • Non-CV ‘cause’ of death

6. Patient CharacteristicsDES (217,675) vs BMS (45,025) *p<0.0001 DES vs BMS

7. DES and BMS Event Rates:30-month Unadjusted Rate / 100 patients Events Requiring Rehospitalization

8. DES and BMS Event Rates:30-month Adjusted Rate / 100 patients HR = 0.76 (0.72,0.80) HR = 0.91 (0.89,0.94) HR = 0.91 (0.85,0.98) HR = 0.96 (0.88,1.04) HR = 0.75 (0.73,0.77)

9. Landmark Display: Mortality

10. Landmark Display: Mortality

11. Landmark Display: Mortality

12. Landmark Analysis: MI STEMI HR = 0.78 NSTEMI HR = 0.73

13. Subgroup Analyses Death MI Revasc Favors DES

14. Sensitivity Analysis:Patient Selection • RCT - like population • N = 49,355 (19%) • ‘Inclusion’ criteria • Elective PCI, < 2 stents • Native vessel, de novo • Class A or B lesions • Lesion length, diameter • ASA, clopidogrel OK • No CKD Favors DES

15. Sensitivity Analysis: Device Selection ‘Cause of Death’ in DES v BMS • Using 1º hosp dx, ‘cause’ extracted in 90% deaths • HR 0.80 favoring DES for CHF/MI death • HR 0.74 favoring DES Non CV death • ‘Sicker’ patients may preferentially receive BMS Unadjusted rates/ 100

16. Potential Limitations • Medicare, NCDR data sources • All patients were > 65 yo, inpatients, NCDR sites (n=650) • No clinical data available for bleeding, revascularization, stent thrombosis • No information on follow-up medications • Observational data: potential for bias, unmeasured confounders

17. Conclusions • Linkage of clinically rich NCDR data to claims data is feasible; Data analysis allows a robust, longitudinal assessment of clinical effectiveness • Comparing outcomes of DES to BMS at 30 mo: • No major DES safety concerns • Lower death and MI rates in DES patients • Slightly lower revascularization, bleeding rates • Similar stroke rates • Results consistent among all patient subgroups • Caveat: The apparent ‘benefit’ of DES may be affected by selection bias and unmeasured confounders present in this real world cohort

18. THANK YOU

19. Study Population All PCI admissions for patients who had some stent implantation 450,242 PCI admissions, 662 sites, 390,973 patients CMS Matched 290,438 PCI admissions, 650 sites, 290,438 patients Exclude patients w index stent application w not during Fee- For-Service (FFS) enrollment 14,225 PCI admissions, 597 sites, 14,225 pts Patients w index stent application during FFS enrollment 276,213 PCI admissions, 650 sites, 276,213 pts Exclude admissions with both DES and BMS 12,822 PCI admissions, 583 sites, 12,822 pts Admissions with either DES only or BMS only 263,391 PCI admissions, 650 sites, 263,391 pts Final study population 262,700 PCI admissions, 650 sites, 262,700 patients Exclude records with missing candidate variables and time-to-censor out of range [0-1096 days]

20. CMS Matched vs Not MatchedPatient Clinical Characteristics

21. CMS Match vs Not Matched Patient Clinical Characteristics

22. Unmeasured Confounder: Post-PCI Clopidogrel Use • Used published Duke data for clopidogrel use and survival benefit to correct HR for death: • Prevalence DES use = 50%, BMS use = 20% @ 12 mo • Clopidogrel benefit: 50%  death @ 12 mo in DES, BMS • HR death corrects from 0.75 to 0.90 JAMA 2007 297:159 Biometrics 1998 54:948 With use @ 50%, 20% cHR = 0.90 W/o clopidogrel use HR = 0.75 BMS family of curves: 0 to 50% use

23. Comparability with OtherRegistry Data – Mortality Favors DES Favors BMS