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V.: 9/7/2007 AC Submit1 Statistical Review of the Observational Studies of Aprotinin Safety Part I: Methods, Mangano and Karkouti Studies CRDAC and DSaRM.

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Presentation on theme: "V.: 9/7/2007 AC Submit1 Statistical Review of the Observational Studies of Aprotinin Safety Part I: Methods, Mangano and Karkouti Studies CRDAC and DSaRM."— Presentation transcript:

1 v.: 9/7/2007 AC Submit1 Statistical Review of the Observational Studies of Aprotinin Safety Part I: Methods, Mangano and Karkouti Studies CRDAC and DSaRM Meeting September 12, 2007 Mark Levenson, Ph.D. Quantitative Safety & Pharmacoepidemiology Group Office of Biostatistics

2 2 Acknowledgements to Dr. Mangano and Dr. Karkouti

3 3 Outline 1.Review Objectives 2.Statistical Methods 3.Mangano Review 4.Karkouti Review 5.Summary

4 4 1. Review Objectives 1.To confirm the reported findings based on investigators’ methods 2.To evaluate the statistical robustness of the findings –FDA analyzed the 3 studies Same methods applied to all three studies Robust Diagnostics

5 5 Outline 1.Review Objectives 2.Statistical Methods 3.Mangano Review 4.Karkouti Review 5.Summary

6 6 Propensity Scores (PS) Adjust for differences in baseline risk factors between two treatment groups (Treatment A and Treatment B) Definition: Probability of assignment for a patient to Treatment A versus Treatment B based on measured risk factors Intuition: –Suppose Treatment A patient and Treatment B patient have the same PS. –Comparisons between these two patients are fair

7 7 Propensity Scores Practice Balance: similarity of distributions of a risk factor between treatment groups PS methods cannot account for unmeasured confounders The PS are estimated based on statistical modeling –Diagnostics important

8 8 Propensity Scores Practice (Cont.) Estimating treatment effects using PS –Matching (Karkouti) –Stratification (FDA) –Multivariate regression (Mangano, i3)

9 9 FDA Analysis Methods Pre-specified Propensity scores with stratification was used to adjust for baseline risk factors Medical, epidemiological, and statistical expertise was used to choose risk factors Diagnostics (analytical and graphical) were used to evaluate balance and explore findings

10 10 Outline 1.Review Objectives 2.Statistical Methods 3.Mangano Review 4.Karkouti Review 5.Summary

11 11 Mangano Study: Key Points Prospectively specified –Inclusion criteria –Outcome definitions –Subgroups –Analysis methods In-hospital outcomes (NEJM) Long-term mortality follow-up outcomes (JAMA) 7 of 69 centers did not participate in the long- term follow-up

12 12 Mangano Study: Key Points Analysis Methods Multivariate regression with and without propensity score as a covariate –Logistic for in-hospital outcomes –Cox PH for long-term mortality Propensity score for any active agent versus no agent for full analysis group No adjustment for geographical differences

13 13 Mangano Study: Patients by Geographical Region and Treatment Group Region No Agent N=1374 % Aprotinin N=1295 % Amino- caproic N=883 % Tran- examic N=822 % Europe5769049 North America 24299629 Other191422

14 14 Mangano Study: Long-Term Follow-up No Agent N=1374 % Aprotinin N=1295 % Completed 5-year follow-up or died 7383 No post-hospital follow-up 101 Lost to follow-up in the post- hospital period 1716

15 15 Mangano Study: Demographic Factors Characteristic No Agent N=1374 Aprotinin N=1295P-Value Age (mean ± sd)63 ± 1065 ± 9<.001 Male (%)81790.135 African American or Hispanic (%)440.542

16 16 Mangano Study: Selected Baseline Risk Factors Characteristic No Agent N=1374 (%) Aprotinin N=1295 (%)P-Value Surgical: CABG + Other1119<.001 Surgical: Non-Elective2115<.001 History of liver disease812<.001 History of renal disease1319<.001 Previous sternotomy313<.001 Preop: Creatinine >1.3 mg/dL14150.338 Preop: Ejection fraction ≤ 44%18150.071 Preop: MI15160.863

17 17 Mangano Study: Study Reported Findings and Methods Primary findings of NEJM and JAMA based on investigators’ methods reproduced Imbalances in baseline risk factors and geographical regions between aprotinin and no-agent groups after PS adjustment Lack of overlap in propensity score distributions between aprotinin and no- agent groups

18 18 FDA Analysis Results

19 19 Mangano Study: FDA Analysis Baseline Risk Factors Before and After PS Adjustment Before PS AdjustmentAfter PS Adjustment No Agent % Aprotinin %P-Value No Agent % Aprotinin %P-Value Surgical: CABG + Other1119<.00115160.543 Surgical: Non-Elective2115<.00118190.651 History of liver disease812<.00110 0.913 History of renal disease1319<.00116 0.849 Previous sternotomy313<.001680.029 Preop: Elev. Creatinine14150.33814 0.943 Preop: Eject. Fr. ≤ 44%18150.07116 0.878 Preop: MI15160.86315 0.745

20 20 Mangano Study: FDA Analysis In-Hospital Outcome Adjusted Estimates Aprotinin vs. No Agent* Outcome No Agent (%) Aprotinin (%) Risk Ratio Aprotinin/No Agent (95% CI) Renal Composite4.87.81.63 (1.03, 2.60) Renal Failure2.55.12.05 (1.05, 3.99) Renal Dysfunction4.35.41.26 (0.76, 2.11) Cardiovascular Composite19.522.21.14 (0.94, 1.38) Myocardial Infarction14.816.41.10 (0.88, 1.39) Congestive Heart Failure8.48.81.05 (0.75, 1.47) Stroke2.02.81.36 (0.70, 2.64) Death (in-hospital)4.64.20.91 (0.54, 1.53) *Analysis based on 1307 no agent patients and 1222 aprotinin patients

21 21 Mangano Study: FDA Analysis Renal Composite

22 22 Mangano Study: FDA Analysis Long-Term Mortality Adjusted Estimates Aprotinin vs. No Agent* Outcome No Agent (%) Aprotinin (%) Risk Ratio Aprotinin/No Agent (95% CI) 6 Weeks5.24.80.93 (0.57, 1.51) 6 Months6.47.01.10 (0.73, 1.68) 1 Year7.18.21.16 (0.79, 1.71) 2 Years8.410.71.27 (0.90, 1.79) 3 Years9.713.01.34 (0.98, 1.83) 4 Years11.415.91.39 (1.05, 1.84) 5 Years14.318.11.26 (0.98, 1.62) *Analysis based on 1307 no agent patients and 1222 aprotinin patients

23 23 Mangano Study: FDA Analysis Long-Term Mortality Adjusted Estimates

24 24 North American Subgroup

25 25 Mangano Study: FDA Analysis by Region and Treatment Group

26 26 Mangano Study: FDA Analysis North America In-Hospital Outcome Adjusted Estimates Aprotinin vs. Aminocaproic* Outcome Amino. (%) Aprotinin (%) Risk Ratio Aprotinin/Amino. (95% CI) Renal Composite 2.49.43.90 (1.98, 7.70) Renal Failure 0.65.39.17 (3.10, 27.15) Renal Dysfunction 2.06.73.39 (1.54, 7.44) Cardiovascular Composite 17.722.51.28 (0.94, 1.74) Myocardial Infarction 12.114.91.23 (0.83, 1.81) Congestive Heart Failure 7.510.51.40 (0.84, 2.35) Stroke 1.53.22.10 (0.76, 5.81) Death (in-hospital) 2.14.72.21 (0.88, 5.52) *Analysis based on 789 aminocaproic patients and 342 aprotinin patients

27 27 Mangano Study: FDA Analysis North America: Long-Term Mortality Adjusted Estimates Aprotinin vs. Aminocaproic* Outcome Amino. (%) Aprotinin (%) Risk Ratio Aprotinin/Amino. (95% CI) 6 Weeks 2.44.71.91 (0.82, 4.47) 6 Months 3.57.32.11 (1.04, 4.28) 1 Year 5.19.91.96 (1.10, 3.47) 2 Years 7.313.71.89 (1.19, 3.00) 3 Years 10.018.41.84 (1.23, 2.73) 4 Years 15.121.91.45 (1.03, 2.04) 5 Years 19.824.61.24 (0.92, 1.67) *Analysis based on 789 aminocaproic patients and 342 aprotinin patients

28 28 Mangano Study: Review Summary Renal outcomes (particularly renal failure) effect in a range of patients and in North American region subgroup Effects for cardiovascular, cerebrovascular, and in-hospital death outcomes not statistically demonstrated Long-term mortality effects in a range of patients and in North American region subgroup

29 29 Outline 1.Statistical Review Objectives 2.Statistical Methods 3.Mangano Review 4.Karkouti Review 5.Summary

30 30 Karkouti Study: Key Points Retrospective study of 5 years of patient data from a single center Patient population: Cardiac surgery (CABG and non-CABG) with cardio- pulmonary bypass Aprotinin used for high risk patients, tranexamic acid used for other patients Used propensity scores with 1-1 matching –449 of 586 aprotinin patients matched

31 31 Karkouti Study: Demographic Factors Characteristic Tranexamic Acid N=10251 Aprotinin N=586P-Value Age (mean ± sd)63 ± 1255 ± 17<.001 Male (%)7565<.001

32 32 Karkouti Study: Selected Baseline Risk Factors Characteristic Tranexamic Acid N=10251 (%) Aprotinin N=586 (%)P-Value Surgical: Not CABG only3389<.001 Surgical: Non-Elective819<.001 Previous sternotomy561<.001 Preop: Creatinine abnormal1926<.001 Preop: Ejection fraction <40%20230.148 Preop: MI177<.001

33 33 Karkouti Study: Study Reported Findings and Methods Primary findings using investigators’ methods reproduced Observed risk factors balanced with propensity score matching approach

34 34 Karkouti Study: FDA Analysis A subgroup of patients with overlap in propensity scores was defined to enable treatment comparison Subgroup contained –553/586 (94%) of the aprotinin patients –3759/10251 (37%) of tranexamic patients Baseline risk factors more similar between treatment groups in subgroup than full group

35 35 Karkouti: FDA Analysis Analysis Subgroup, Baseline Risk Factors Before and After PS Adjustment Before PS AdjustmentAfter PS Adjustment Tran. % Aprotinin %P-Value Tran. % Aprotinin %P-Value Surgical: Not CABG only8392<.00183 0.873 Surgical: Non-Elective16180.13716190.366 Previous sternotomy1464<.00119220.126 Preop: Elev. Creatinine350.010330.950 Preop: Eject. Fr. <40%21220.42621190.693 Preop: MI1170.00310160.036

36 36 Karkouti Study: FDA Analysis Treatment Effect Estimates Aprotinin vs. Tranexamic Acid* Outcome FDA Analysis Risk Ratio Aprotinin/Tran. Matched-Pair Odds Ratio Aprotinin/Tran. Renal dysfunction1.53 (1.11, 2.12) Renal failure1.38 (0.86, 2.23)1.85 (0.94, 3.63) Myocardial Infarction1.42 (0.71, 2.83)1.22 (0.51, 2.95) Stroke1.72 (0.93, 3.19)1.15 (0.55, 2.43) Death (in-hospital)1.18 (0.79, 1.76)0.90 (0.54, 1.51) *Analysis based on 3759 tran. patients and 553 aprotinin patients

37 37 Karkouti Study: FDA Analysis Renal Failure

38 38 Karkouti Study: Review Summary Renal dysfunction effect statistically significant Some evidence for renal failure effect Effects for myocardial infarction, stroke, and in-hospital death outcomes not statistically demonstrated

39 39 Outline 1.Review Objectives 2.Statistical Methods 3.Mangano Review 4.Karkouti Review 5.Summary

40 40 Summary Evidence for renal effect, including renal failure consistent Effects for cardiovascular, cerebrovascular, and in-hospital death outcomes not statistically demonstrated Evidence for long-term mortality effect Potential for unadjusted confounders between the treatment groups which may bias the treatment effect estimates


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