James P. AuBuchon, MD President & Chief Executive Officer Puget Sound Blood Center Professor of Medicine and of Labo

1. Decision Analysis in Transfusion Medicine With Specific Reference to Pathogen Inactivation James P. AuBuchon, MD President & Chief Executive Officer Puget Sound Blood Center Professor of Medicine and of Laboratory Medicine University of Washington Seattle, Washington

2. Definition: Decision Analysis Definition: Decision Analysis A mathematical method of projecting the effects of a A mathematical method of projecting the effects of a clinical decision. clinical decision. The model often allows projection of the (health) The model often allows projection of the (health) outcomes of a choice and the resource consumption outcomes of a choice and the resource consumption required in its delivery and consequences. required in its delivery and consequences.

3. Goals of Decision Analysis: I Goals of Decision Analysis: I Better Health Better Health Treatment A Treatment A ? Side Effect Side Effect Better Health Better Health Treatment B Treatment B Side Effect Side Effect Predict relative effect of alternative treatments Predict relative effect of alternative treatments

4. Goals of Decision Analysis: II Goals of Decision Analysis: II 1 1 1 1 One Dollar One Dollar 1 1 1 1 One Dollar One Dollar Determine relative benefit for resources expended Determine relative benefit for resources expended

5. Health Improvement Health Improvement Population Population Health Health Resources Utilized Resources Utilized

6. Forms of Economic Evaluation Cost minimization analysis Assumption: Similar outcomes Cost-benefit analysis Compilation of all costs and benefits Difficulty: Comparison Cost-effectiveness analysis

7. Cost-Effectiveness Analysis Cost-effectiveness analysis: a methodology for evaluating the Cost-effectiveness analysis: a methodology for evaluating the outcomes and costs of interventions designed to improve health. outcomes and costs of interventions designed to improve health. A cost-effectiveness analysis evaluates a given health intervention A cost-effectiveness analysis evaluates a given health intervention through the use of a cost-effectiveness ratio. through the use of a cost-effectiveness ratio. In this ratio, all health effects of the intervention (relative to a In this ratio, all health effects of the intervention (relative to a stated alternative) are captured in the denominator and changes in stated alternative) are captured in the denominator and changes in resource use (relative to the alternative) are captured in the resource use (relative to the alternative) are captured in the numerator and valued in monetary terms. numerator and valued in monetary terms.

8. Cost-Effectiveness Ratio Marginal cost-effectiveness Marginal cost-effectiveness = Difference in Resources = Difference in Resources Difference in Outcome Difference in Outcome = Costs - Costs = Costs - Costs A B A B Life expectancy *Quality - Life expectancy *Quality Life expectancy *Quality - Life expectancy *Quality A A B B A A B B

9. p2A p1A 1-p2A S = 1.00 1-p1A Probability = p1B * p2B p2B p1B 1-p2B S = 1.00 1-p1B Modeling the Decision Probability = p1A * p2A Outcome A-1 Intervention A Outcome A-2 Outcome A-3 Outcome A-4 Population Population Outcome B-1 Outcome B-2 Outcome B-3 Intervention B Outcome B-4

10. Assigning Values to Outcomes Outcome: Life expectancy (LE)

11. Life Expectancy Calculations Life Expectancy Calculations Gompertz Function Gompertz Function Exponential Function Exponential Function Probability Probability of of Survival Survival Years After Starting Treatment Years After Starting Treatment

12. Life Expectancy Calculations Life Expectancy Calculations The Declining Exponential Approximation of Life Expectancy The Declining Exponential Approximation of Life Expectancy (DEALE) (DEALE) S = S e -mt S = S e -mt t 0 t 0 m = average annual mortality rate = (-1/t) * ln(S /S ) m = average annual mortality rate = (-1/t) * ln(S /S ) t 0 t 0 m = m + m + m + ... m = m + m + m + ... TOTAL GENDER&AGE-SPECIFIC DISEASE1 DISEASE2 TOTAL GENDER&AGE-SPECIFIC DISEASE1 DISEASE2 LE = 1/m LE = 1/m TOTAL TOTAL Assumptions: Age has no effect on disease-specific mortality Assumptions: Age has no effect on disease-specific mortality Presence of second disease has no effect on mortality from first Presence of second disease has no effect on mortality from first Disease not common (i.e., not reflected in population statistics) Disease not common (i.e., not reflected in population statistics)

13. Estimating Outcomes with Multiple States The Markov Process Multiple states of disease defined. Multiple states of disease defined. Probability of transition from one to another (or no transition) Probability of transition from one to another (or no transition) defined per cycle. defined per cycle. Transition probability unaffected by previous history. Transition probability unaffected by previous history. Cycles repeated for defined period or until all patients are dead. Cycles repeated for defined period or until all patients are dead. p:1-4 p:1-4 p:1-3 p:1-3 p:2-4 p:2-4 p:1-2 p:3-4 p:1-2 p:2-3 p:3-4 p:2-3 Status 4 Status 2 Status 3 Status 1 (Death) p:2-1 p:3-2 p:2-1 p:3-2 p:3-1 p:3-1

14. Next Step: Assigning Values to Outcomes Outcome: Life expectancy (LE) - and – Quality of Life (QoL)

15. 100% 100% Reduced area under curve = reduced quality-adjusted life years Quantitating Quality and Quantity of Life 100% Health-related quality of life DEATH Maximum: x years 100% quality

16. D = QALY WITH INTERVENTION WITHOUT INTERVENTION Longevity Improvement Quantitating Quality and Quantity of Life Health-related quality of life

17. Health Outcome Quantitation: QALYs Quality Adjustment Quality Adjustment QALY = Quality-Adjusted Life Year QALY = Quality-Adjusted Life Year Good health: 100% 2 years, good health: 2.0 QALYs Good health: 100% 2 years, good health: 2.0 QALYs 2 years, fatigue: 1.6 QALYs Fatigue: 80% 2 years, fatigue: 1.6 QALYs Fatigue: 80% 2 years, severe illness: 0.2 QALYs Severe illness: 10% 2 years, severe illness: 0.2 QALYs Severe illness: 10%

18. Quantitating Costs Healthcare resources consumed by or because of the intervention Micro-costing analysis Labor+ supply + equipment expense for each step Fixed (capital) costs change: Will they change? Cost – NOT charge

19. Frequency Marginal Cost-effectiveness ratio Cost-effectiveness ratio Cost of Intervention Dealing with Uncertainty Sensitivity Analysis Vary applied value of a variable across possible range Monte Carlo Analysis Define distribution of possible values for variable(s) Randomly assign variable(s) for individual calculations Output: Range of possible outcomes

20. Cost-Effectiveness Comparisons Medical Practice Cost per Year of Life Saved Medical Practice Cost per Year of Life Saved RhIG prophylaxis for HDN $2,000 RhIG prophylaxis for HDN $2,000 Pneumococcal vaccine for elderly $11,400 Pneumococcal vaccine for elderly $11,400 Annual mammography < 50 year old $68,000 Annual mammography < 50 year old $68,000 CABG (left main disease with angina) $6,000 CABG (left main disease with angina) $6,000 CABG (one vessel disease with angina) $46,000 CABG (one vessel disease with angina) $46,000 Propranolol for hypertension $12,000 Propranolol for hypertension $12,000 Captopril for hypertension $79,000 Captopril for hypertension $79,000 Kidney transplantation $18,000 Kidney transplantation $18,000 Hemodialysis for ESRD $48,000 Hemodialysis for ESRD $48,000 Heart transplantation $30,000 Heart transplantation $30,000 Most commonly accepted interventions: < $50,000/QALY

21. Decision Analysis: Overview Strong Points Comparison of alternative treatments Objectivity Limitations Valuation of intangibles Current vs. future value Application to a particular patient Assumptions of the model

22. Decision Analysis: Commentary Resource Management Resource Management Society must decide. Society must decide. We must participate. We must participate. Decision analysis is an incomplete decision assistance Decision analysis is an incomplete decision assistance tool as it cannot capture all relevant elements. tool as it cannot capture all relevant elements.

23. $$ The Physician as Rationer The Physician as Rationer Decision Analysis: Commentary X The Physician as The Physician as Patient Advocate Patient Advocate

24. Small differences Poor cost-effectiveness Large differences Poor cost-effectiveness Alternatives in Transfusion: Cost-Effectiveness Considerations Marginal cost-effectiveness Marginal cost-effectiveness Difference in Resources Difference in Resources = = Difference in Outcome Difference in Outcome Costs Costs - Costs - Costs Costs Costs - Costs - Costs = = A A B B A A B B Life expectancy Life expectancy *Quality *Quality - Life expectancy - Life expectancy *Quality *Quality Life expectancy Life expectancy *Quality *Quality - Life expectancy - Life expectancy *Quality *Quality A A A A B B B B A A A A B B B B

25. Anti- HIV ALT Testing SD NAT HCV Look- back p24 Ag Testing PAD- CABG SD FP Cost-Effectiveness Comparisons Cost-effectiveness Cost-effectiveness ($/YLE) ($/YLE) 8,000,000 8,000,000 6,000,000 6,000,000 Transfusion Safety Interventions Transfusion Safety Interventions 4,000,000 4,000,000 2,000,000 2,000,000 600,000 600,000 400,000 400,000 200,000 200,000 Commonly Accepted Medical Practices Commonly Accepted Medical Practices RhIg/HDN Prophy- laxis HTN Therapy Annual Mammo- gram CABG Cardiac Trans- plantation

26. Cost-effectiveness of PI: Platelets DISTRIBUTION OF PATIENTS Setting: Groningen, The Netherlands DISTRIBUTION OF TRANSFUSIONS Postma MJ et al. Transf Med 2005;15:379-87.

27. Cost-effectiveness of PI: Platelets (1/3200) MCER = $720,000/YLE Range (based on bacterial threat): ± 14% Postma MJ et al. Transf Med 2005;15:379-87.

28. Cost-effectiveness of PI vs. Bacterial Culturing 90% SENSITIVITY Little impact on model Cost-Effectiveness Ratios Culturing vs. nothing $91,000/QALY PI vs. nothing $500,000/QALY Culturing + PI vs. culturing $3,500,000/QALY “No individual should be exposed to an activity imposing a risk of death greater than one in a million (10-6) per year.” Dutch Government, 1989 COST-BENEFIT ANALYSES Janssen MP et al. Transfusion 2006;46:956-65.

29. Cost-Effectiveness Analysis of Pathogen Inactivation Risks assessed HIV HBV HCV HTLV-I/II Syphilis Bacteria Chikungunya virus T. cruzi CMV GvHD Febrile reactions Immunomodulation • Protocol • Additive, not replacement • Setting • Canada • - Available ID data • - Available cost data • - Active hemovigilance • - Interest • Immunosuppressed: 25% • Post-transfusion mortality: +50% Not emerging agents Custer B et al. Transfusion 2010;50:2461-73.

30. Cost-Effectiveness Analysis of Pathogen Inactivation Whole-blood Pathogen Inactivation $1,300,000/QALY Platelet/Plasma Pathogen Inactivation $1,400,000/QALY Custer B et al. Transfusion 2010;50:2461-73.

31. Cost-Effectiveness Analysis of Pathogen Inactivation Whole-blood Pathogen Inactivation Base case: 1/47,000 (0.0002) Custer B et al. Transfusion 2010;50:2461-73.

32. Cost-Effectiveness Analysis of Pathogen Inactivation Where Are the Risks? Agent causing chronic disease Number of Transmissions Agent causing acute disease PRT: None Plt FP Plt+FP PRT: None Plt FP Plt+FP Kleinman S et al. Transfusion 2010;50:2592-606.

33. Cost-Effectiveness Analysis of Pathogen Inactivation Where Are the Risks? With PI, healthcare costs subsequent to a “catastrophic” agent’s emergence would decrease by 20%. [Assumptions: Canada] Wait for RBC PI? Number of Transmissions Plasma Platelets 40% Red Cells 60% Kleinman S et al. Transfusion 2010;50:2592-606.

34. Cost-Effectiveness Analysis of Pathogen Inactivation PI: Substantial cost, small effect with current risks (except perhaps bacterial contamination)  Poor marginal cost-effectiveness

35. Pathogen Inactivation of Blood Components Why? Why not? Reduction in pathogen transmission Reduction in current testing Avoidance of new testing Avoidance of GvHD Reduction in TRALI risk √ √ √ √ ± √ Safety ? Poor cost-effectiveness The question – for society: How to allocate healthcare resources? How safe should the blood supply be?