1. Alexandre Quadros, Dulce Welter, Fernanda Camozzatto, Áurea Chaves, Rajendra Mehta, Carlos Gottschall, Renato D. Lopes Identifying Patients at Risk for Premature Discontinuation of Thienopyridine After Coronary Stent Implantation Cardiology Institute of Rio Grande do Sul, Porto Alegre, BRAZIL Duke Clinical Research Institute, Durham, NC, USA

2. Low Drug Adherence Extremely frequent May lead to serious complications Increases in health systems costs Osterberg. NEJM 2005; 353: 487

4. Spertus. Circulation 2006; 103: 2803 Discontinuation of Thienopyridine After DES: PREMIER Registry 30-day discontinuation rate = 14%

6. The predictors for discontinuation of the thienopyridines are not well established yet. Identification of these predictors, and the use of a risk score for their exact assessment, could provide an important tool to improve treatment adherence. The Problem

7. The importance of risk scores in cardiology TIMI risk score GRACE score Risk scores to assess mortality after CABG or PCI

8. Objective  To identify predictors of discontinuation of thienopyridines after coronary stent implantation  Development of a predictive risk score for discontinuation of thienopyridines after coronary stent implantation

9. Methods Prospective cohort study Inclusion criteria : – Coronary stenting between Nov/2007 and March 2008 Exclusion criteria: – Participation in studies involving antiplatelet treatment – Unsuccessful procedures – In-hospital MACE – Refuse to sign the informed consent

10. Methods Clinical, socioeconomic and angiographic characteristics were included in a dedicated database Procedural aspects of stent implantation were left at discretion of each operator

11. Methods: Follow-up Follow-up – 30 day interview to assess adherence to the medical treatment. – Non-adherent were questioned about the reasons – Morisky’s Questionnaire was applied to all patients Outcomes – Discontinuation of the thienopyridines – Adherence, assessed by Morisky Questionnaire

12. Morisky Questionnaire Assess adherence in an objective and standardized way: 0 to 4 – 0 = totally adherent – Higher grades = the less adherent 4 questions – Forgetfulness – Negligence – Interrupting after clinical improvement – Reuse if worsening of the symptoms Goldberg Morisky. Med Care 1986; 24: 67.

13. Statistical Analysis Sample size: – discontinuation of 20% – 3.5% variation – Confidence Interval of 95% – 400 patients Characteristics of the patients who discontinued the thienopyridine treatment were compared to those who continued SPSS 11.0

14. Statistical Analysis Multiple logistic regression models: variables with statistical significance or classified as predictors in previous studies Hosmer-Lemeshow goodness-of-fit test. Points attributed proportionately to the odds ratios. The continuous variables were categorized according to the cutting points that allowed the best prediction of the primary outcome. c statistic

15. Results Discontinuation of thienopyridine16.5 % Adherence problems25 %

16. Patient causes to discontinue thienopyridine treatment in the 30-day follow-up % High price62 Insuficient information17 Orientation from another physician15 Allergy1.5 Urinary bleeding1.5 CVA1.5 Refuse to follow medical advice1.5

17. Characteristics of Patients Taking and Not Taking Thienopyridines at 30 Days Overall n= 400 Taking Thienopyridines n = 334 Not Taking Thienopyridines n = 66 P value Age, years61 ± 10.360.8 ±10.361.7 ±10.5 0.77 Male, %656467 0.83 Current Smoker, %28 27 0.99 Hypertension, %78 74 0.52 Dyslipidemia, %56 53 0.69 Diabetes Mellitus, %252715 0.06 Familiar History, %52 56 0.59

18. Characteristics of Patients Taking and Not Taking Thienopyridines at 30 Days Overall n= 400 Taking Thienopyridines n = 334 Not Taking Thienopyridines n = 66 P value Depression, %11 120.83 Heart failure, %3280.02 COPD, %3410.70 Renal failure, %2210.99 Emergency procedure, %2219380.01 ACS, %454162 0.01 Depression, %11 12 0.83

19. Characteristics of Patients Taking and Not Taking Thienopyridines at 30 Days Overall n= 400 Taking Thienopyridines n = 334 Not Taking Thienopyridines n = 66 P value Unmarried, %75150.02 Education, yrs7.48 ± 4.647.72 ± 4.756.26 ± 3.900.008 Salary< 0.001 < 2 min. wages, % 524680 2-3 min wages, %15 14 > 3 min. wages, % 33396 Lack private insur, % 82 79 97 < 0.001

20. Multiple Logistic Regression Analysis of Candidate Variables Associated with Thienopyridine Discontinuation CharacteristicBOdds Ratio 95% CIp Unmarried 0.9082.481.01 - 6.070.046 Lack of private health insurance 1.5434.681.05 - 20.700.041 Education (years) -.1120.890.42 - 1.860.76 Acute coronary syndrome 0.8382.311.28 - 4.140.004 Diabetes Mellitus -.7882.201.02 - 4690.041 Salary < to 2 minimum wages 2.1088.232.70 – 25.04< 0.001 2 to 3 minimum wages 1.7954.461.25 - 15.85 0.021 > to 3 minimum wages 1 Constant - 5.709

21. Multiple Logistic Regression Analysis of Candidate Variables Associated with Thienopyridine Discontinuation CharacteristicBOdds Ratio 95% CIp Unmarried0.9082.481.01 - 6.070.046 Lack of private health insurance1.5434.681.05 - 20.700.041 Education (years) -.1120.890.42 - 1.860.76 Acute coronary syndrome0.8382.311.28 - 4.140.004 Diabetes Mellitus -.7882.201.02 - 4690.041 Salary < to 2 minimum wages2.1088.232.70 – 25.04< 0.001 2 to 3 minimum wages1.7954.461.25 - 15.85 0.021 > to 3 minimum wages1 Constant- 5.709 Hosmer-Lemeshow: א2=1.92, p=0.96

22. Risk score for adherence to thienopyridine Patient CharacteristicPoints Unmarried1 Acute coronary syndrome 1 Non-diabetic1 Lack of private health insurance 4 Salary Under to 2 minimum wages Under to 2 minimum wages7 2 to 3 minimum wages 2 to 3 minimum wages3

23. Thienopyridine Discontinuation Rates According to the Risk Score Points 0 % 7 % 20 % 37 % % % P < 0.001 c-statistic = 0.76

24. Thienopyridine Adherence (Morisky) Rates According to the Risk Score Points 84 % 64 % 53 % 37 % % % P < 0.001 c-statistic = 0.73

25. Bootstrap analysis (1000 samples)

26. Conclusions  A risk score based on variables obtained before stent implantation accurately predicts thienopyridine discontinuation and treatment adherence.  This information can enhance compliance in vulnerable subgroups of patients, and also aid in the decision of implanting a DES or a BMS in those at the highest risks for thienopyridine discontinuation.

27. Limitations  Adherence as told by the patients  Relative low number of individuals  Lack of validation  Score relies heavily on cost issues

28. Strengths  Prospective study  Standardized Questionnaire, Morisky  High c-statistic, p-value  Score predicts discontinuation and low adherence

29. ALEXANDRE QUADROS, DULCE WELTER, FERNANDA CAMOZZATTO, ROGERIO SARMENTO LEITE, CARLOS GOTTSCHALL A Risk Score Predicts Thienopyridine Compliance After Coronary Stent Implantation Cardiology Institute of Rio Grande do Sul Universitary Foundation of Cardiology Porto Alegre, BRAZIL alesq@terra.com.br