Make EBM Individualized and Smarter

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1 Make EBM Individualized and Smarter Hao-min Cheng, M.D., PhD. Department of Medical Education, Taipei Veterans General Hospital Division of Cardiology, Taipei Veterans General Hospital Faculty of Medicine, National Yang-Ming University, Taiwan 1

3 Presentation Outline Core epistemological principle of EBM The principal of EBM application Shared Decision Making Make EBM Individualized Why and how? Maker EBM smarter Learning on demand Medical calculation in EMR A better EBM inquiry system Take Home Messages 3

4 Presentation Outline Core epistemological principle of EBM The principal of EBM application Shared Decision Making Make EBM Individualized Why and how? Maker EBM smarter Learning on demand Medical calculation in EMR A better EBM inquiry system Take Home Messages 4

5 Benchmark of Clinical Research 5

6 Benchmark of Clinical Research 6

the best available evidence Clinical decision making requires consideration of patients values and preferences Effective decision making has to address

7 3 Epistemological Principles of EBM Not all evidence is created equal Practice of medicine should be based on the best available evidence. The pursuit of truth is best accomplished by evaluating the totality of the evidence Health claims should be based on systematic reviews that summarise the best available evidence Clinical decision making requires consideration of patients values and preferences Effective decision making has to address the consequences of importance to the decision maker Djulbegovic B, Guyatt GH. Progress in evidence-based medicine: a quarter century on. The Lancet; 390(10092):

8 Presentation Outline Core epistemological principle of EBM The principal of EBM application Shared Decision Making Make EBM Individualized Why and how? Maker EBM smarter Learning on demand Medical calculation in EMR A better EBM inquiry system Take Home Messages 8

9 實證醫學應用模式 Progress in evidence-based medicine: a quarter century on. The Lancet.390(10092):

10 Values & Context Patient-centered Scientific Evidence *HCP s Expertise *HCP: Health Care Providers 10

11 The SHARE Approach Essential Steps of Shared Decision Making

The SHARE Approach Step 1: Seek your patient s participation Step 2: Help your patient explore and compare treatment options You need the help of SR for

12 The SHARE Approach Step 1: Seek your patient s participation Step 2: Help your patient explore and compare treatment options You need the help of SR for decision aids Step 3: Assess your patient s values and preferences Step 4: Reach a decision with your patient Step 5: Evaluate your patient s decision 12

13 Step 2: Help your patient explore and compare treatment options Discuss the benefits and risks of each treatment option. Know the benefits and risks of each option Understand how they relate to your patient s situation and condition. Use evidence-based decision-making resources to compare the treatment options. Patient-centered outcomes research can help. 13

14 Effective Health Care Program activities Evidence synthesis Development of systematic reviews of existing evidence to compare treatment/intervention effectiveness and identifying relevant knowledge gaps Compare the benefits and harms of treatment options Explain what is known and what is not known 14

15 Health Decisions Good decisions Informed Supported by best evidence Compatible with patients values Considers patients preferences Weigh pros and cons Practical Poor decisions Objective data inadequate Too few options considered Alternatives unclear Values and preferences unexplored Roles unclear Communication is poor Cornelia Ruland

16 Decision Aids Designed to Provide information on options Help people participate in decision making Help clarify and communicate personal values NOT designed to Advise people to choose one option over another Not meant to replace physician consultation Prepare Patients to Make Informed, Valuebased Decisions with Their Physicians Cornelia Ruland

17 Presentation Outline Core epistemological principle of EBM The principal of EBM application Shared Decision Making Make EBM Individualized Why and how? Maker EBM smarter Learning on demand Medical calculation in EMR A better EBM inquiry system Take Home Messages 17

18 What do you mean by patient value? The patients preference can be related to Intervention options: it is subjective but important! Multiple outcomes resulting from intervention: it can be objective 18

19 Let us do a opinion poll! Which of the following outcomes you rate the most critical to you: A. Myocardial infarction 心肌梗塞 B. Stroke or systemic embolism 缺血性中風 C. Intracranial hemorrhage 顱內出血 D. Gastrointestinal bleeding 胃出血 E. All-cause death 死亡 19

20 Patients and clinical trialists did not weigh individual components of a composite end point equally. Whereas trialists are most concerned about avoiding death, patients place equal or greater importance on reducing myocardial infarction or stroke Circulation. 2014;130:

21 Adjusted end point weights according to patient age, race, and annual income Circulation. 2014;130:

22 End point weights of clinical trialist Circulation. 2014;130:

23 Stroke Prevention for Atrial Fibrillation 23

25 Effective anticoagulation with factor xa next GEneration in Atrial Fibrillation

Study design: ENGAGE AF-TIMI 48 Randomized, double-blind, double-dummy, event-driven study PATIENTS AF on electrical recording within last 12 months Intended oral anticoagulant CHADS 2 2 N=21,105

26 Study design: ENGAGE AF-TIMI 48 Randomized, double-blind, double-dummy, event-driven study PATIENTS AF on electrical recording within last 12 months Intended oral anticoagulant CHADS 2 2 N=21,105 RANDOMIZATION 1:1:1 randomization is stratified by CHADS 2 score 2 3 versus 4 6 and need for edoxaban dose reduction* Edoxaban 30 mg QD regimen Edoxaban 60 mg QD regimen Warfarin (INR ) Median duration of follow up 2.8 years *Dose reduced by 50% if CrCl ml/min, body weight 60 kg or patient receiving verapamil, quinidine or dronedarone AF=atrial fibrillation; CrCl=creatinine clearance INR=International Normalized Ratio; QD=once daily Giugliano et al. N Engl J Med 2013; DOI: /NEJMoa

27 Primary Endpoint: Stroke / SEE (2.8 years median f/u) Warfarin TTR 68.4% Edoxaban 60* mg QD vs warfarin Edoxaban 30* mg QD vs warfarin Noninferiority Analysis (mitt, On Treatment) Hazard ratio (97.5% CI) edoxaban noninferior Superiority Analysis (ITT, Overall) P Values Non-inferiority Superiority P< P=0.005 P=0.017 P=0.44 Edoxaban 60* mg QD vs warfarin Edoxaban 30* mg QD vs warfarin *Dose reduced by 50% in selected pts Hazard ratio (97.5% CI) 0.87 P= P= edoxaban better warfarin better P Value for Superiority Giugliano RP. NEJM 2013; 369:

28 Edoxaban 60* mg QD vs warfarin Hem. Stroke Ischemic Stroke *Dose reduced by 50% in selected pts Key Secondary Outcomes 2 EP: Stroke, SEE, CV death Death or ICH All-cause mortality CV death Myocardial infarction Giugliano RP. NEJM 2013; 369: Edoxaban 30* mg QD vs warfarin 0.33 Warfarin TTR 68.4% edoxaban better HR (95% CI) warfarin better P vs warfarin E-60 E-30 < <0.001 < <

29 Edoxaban 60* mg QD vs warfarin Key Safety Results - Safety Cohort on Treatment - Edoxaban 30* mg QD vs warfarin ISTH Major Bleeding Warfarin TTR 68.4% 0.47 Fatal Bleeding HR (95% CI) P Value vs warfarin P<0.001 P<0.001 P=0.006 P<0.001 Intracranial Hemorrhage *Dose reduced by 50% in selected pts 0.30 Gastrointestinal Bleeding Giugliano RP. NEJM 2013; 369: edoxaban better warfarin better Safety cohort=all patients who received at least 1 dose study drug P<0.001 P<0.001 P=0.03 P<0.001

30 You have so many choices and so many outcomes!!!

31 Net Clinical Outcomes Edoxaban 60* mg QD vs warfarin Edoxaban 30* mg QD vs warfarin Stroke, SEE, death, major bleeding Warfarin TTR 68.4% Hazard ratio (95% CI) P Value vs warfarin P=0.003 P<0.001 Disabling stroke, life-threatening bleeding, death P=0.008 P<0.001 Stroke, SEE, life-threatening bleeding, death *Dose reduced by 50% in selected pts SEE=systemic embolic event Giugliano RP. NEJM 2013; 369: edoxaban better P=0.003 P=0.007 Warfarin better31

33 Gap In the Shared Decision Process 33

mean to the patients Risks, benefits, and downsides of management options may be viewed differently at the level of

34 When applying population based evidence to individuals Problems faced Comorbidities Power struggle Viewpoints Scenarios RCT aimed for single condition Real patients have multiple conditions What mean to you doesn t necessary mean to the patients Risks, benefits, and downsides of management options may be viewed differently at the level of the population than from the perspective of an individual SDM SDM is not clearly enabled in contemporary practice BMJ 2016;353:i2452.

evaluated in real-world Short pressurised

35 Decision aids should be published in tandem with guidelines Guideline itself should be created and evaluated in real-world Short pressurised consultations may not be the best place for making choices: Coaching system 35

36 Users Guides to the Medical Literature XX. Integrating Research Evidence With the Care of the Individual Patient Threshold NNT Integrate the evidence on benefit or harm with patient values to reach treatment recommendations Challenges: Value data not available Substantial variation in values between individuals Decision analyses that rely on group averages for values may not always be applicable to a particular patient: close examination of the utility sensitivity analyses of a decision analysis may provide some guidance JAMA Jun 7;283(21):

37 Aim Desirability of differential weighting of clinical trial end points, but a widely acceptable weighting method has not been advanced We propose a novel method to generate a value-weighted composite end point

38 Data Extraction 9 RCTs that compared NOACs with VKAs in patients with nonvalvular AF 5 Outcomes : myocardial infarction, stroke or systemic embolism, intracranial hemorrhage, gastrointestinal bleeding, and all-cause death Preparation of End Point Weights The disability-adjusted life-years (DALYs) The lifetime cost of medical care The clinical end points preferences survey Incorporation of Preference Weights into Individual End Points Standardized preference-weight for individual end points Age-standardized DALYs per patient Lifetime medical spending per patient Mean predicted cost per case in acute phase Importance of individual end points for each subject Relative weight Mean predicted cost per case in subacute phase + + Mean predicted cost per case in chronic phase 1000 resampling iterations Constructing a preference-weight integrated composite end point Meta-analysis Mantel-Haenszel fixed-effects model DerSimonian and Laird random-effects model Summarization

39 Data Extraction 9 RCTs that compared NOACs with VKAs in patients with nonvalvular AF 5 Outcomes myocardial infarction stroke or systemic embolism intracranial hemorrhage gastrointestinal bleeding all-cause death

40 Main characteristics of included studies Study, year Trial design Sample size, n (Int/Comp) ARISTOTLE, 2011 ARISTOTLE -J, 2011 CHUNG, 2011 ENGAGE AF-TIMI 48, 2013 RE-LY, 2009 Multicenter & multinational (1034 centers in 39 countries), doubleblind, phase III RCT Multicenter (23 centers in Japan), double-blind, openlabel, phase II RCT Multinational (4 Asian countries), doubleblind, open-label, phase II RCT Multicenter & multinational (1393 centers in 46 countries), doubleblind, double-dummy, phase III RCT Multicenter & multinational (951 centers in 44 countries), open-label, phase III RCT 18,201 (9120 / 9081) 222 (74 for 2.5 mg, 74 for 5 mg / 74) 235 (79 for 30 mg, 80 for 60 mg / 76) 21,105 (7034 for 30 mg, 7035 for 60 mg / 7036) 18,113 (6015 for 110 mg, 6076 for 150 mg / 6022) Intervention Comparator Duration of treatment Apixaban 5 mg BID (or 2.5 mg BID if 2 criteria: age 80 years, body weight 60 kg, serum creatinine 1.5 mg/dl) Apixaban 2.5 mg BID, 5 mg BID Edoxaban 30 mg OD, 60 mg OD Edoxaban 30 mg OD, 60 mg OD Dabigatran 110 mg BID, 150 mg BID Warfarin (dose adjusted, target INR 2-3) Warfarin (dose adjusted, target INR 2-3 if age 70 years, or if age >70 years) Warfarin (dose adjusted, target INR 2-3) Warfarin (dose adjusted, target INR 2-3) Warfarin (dose adjusted, target INR 2-3) 1.8 years (median) 12 weeks (median) Duration of follow-up 1.8 years (median) NA TTR, % Mean age, year 62.2 (mean) 70 (median) Overall 60% of patients had INR within the 2-3 range for 60% of the treatment period Male, % months 3 months days (medium) 2 years (median) 1022 days (medium) 2 years (median) 64.9 (mean) 72 (median) (mean) Mean CHADS 2 score 40

Main characteristics of included studies (Cont'd) Study, year Trial design Sample size, n (Int/Comp) ROCKET AF, 2011 J-ROCKET AF, 2012 WEITZ, 2010 YAMASHITA, 2012 Multicenter & multinational (1178

41 Main characteristics of included studies (Cont'd) Study, year Trial design Sample size, n (Int/Comp) ROCKET AF, 2011 J-ROCKET AF, 2012 WEITZ, 2010 YAMASHITA, 2012 Multicenter & multinational (1178 clinical sites in 45 countries), doubleblind, doubledummy, phase III RCT Multicenter (167 sites in Japan), double-blind, double-dummy, phase III RCT Multicenter & multinational (91 centers in 12 countries), doubleblind, open-label, phase II RCT Multicenter (61 centers in Japan), double-blind, openlabel, phase II RCT 14,264 (7131 / 7133) 1,280 (640 / 640) 1,146 (235 for 30 mg OD, 245 for 30 BID, 235 for 60 mg OD, 180 for 60 BID / 251) 536 (135 for 30 mg, 135 for 45 mg, 132 for 60 mg / 134) Intervention Comparator Duration of treatment Rivaroxaban 20 mg OD (or 15 mg OD if CrCl ml/min) Rivaroxaban 15 mg OD (or 10 mg OD if CrCl ml/min) Edoxaban 30 mg OD, 30 mg BID, 60 mg OD, 60 mg BID Edoxaban 30 mg OD, 45 mg OD, 60 mg OD Warfarin (dose adjusted, target INR 2-3) Warfarin (dose adjusted, target INR 2-3 if age <70 years, or if age 70 years) Warfarin (dose adjusted, target INR 2-3) Warfarin (dose adjusted, target INR 2-3 if age <70 years, or if age 70 years) 590 days (median) 499 days for Rivaroxaba n, 481 days for Warfarin (median) Duration of follow-up 707 days (median) 1.3 years (median) TTR, % Mean age, year 55 (mean) 73 (median) Male, % Mean CHADS 2 score 12 weeks 12 weeks % CHADS 2 score of 2 = 63.3% 12 weeks 12 weeks 73% for age <70 years, 83% for age 70 years BID, twice daily; OD, once daily; INR, international normalized ratio; TTR, time in therapeutic range; CrCl, creatinine clearance; Int, intervention; Comp, comparator 41

42 Preparation of End Point Weights Three metrics The disability-adjusted life-years (DALYs) developed by WHO Global Burden of Disease Project (GBDP) The lifetime cost of medical care reimbursed by Taiwan's National Health Insurance The clinical endpoints preferences surveyed by questionnaire in the field

43 Disability-adjusted life-years (DALYs) A summary measure of population health widely used to quantify burden of disease 1 DALY = 1 lost year of "healthy" life in given population, due to combined effects of disability and premature death Formula

44 (Stroke. 2011;42: )

45 DALYs New version Open database Reference

46 Clinical endpoints preferences survey Demographic characteristics Disease history Importance of each end point to subjects themselves

50 Incorporation of Preference Weights into Individual End Points STEP 1: Standardized preference-weight for individual end points Age-standardized DALYs per patient Lifetime medical spending per patient Mean predicted cost per case in acute phase Mean predicted cost per case in subacute phase + + Mean predicted cost per case in chronic phase Clinical endpoints preferences for each subject

53 Data Extraction 9 RCTs that compared NOACs with VKAs in patients with nonvalvular AF 5 Outcomes : myocardial infarction, stroke or systemic embolism, intracranial hemorrhage, gastrointestinal bleeding, and all-cause death Preparation of End Point Weights Incorporation of Value Weights into Individual End Points Standardized value-weight for individual end points Age-standardized DALYs per patient Importance of individual end points for each subject The disability-adjusted life-years (DALYs) The clinical end points preferences survey Age standardized DALY rate (per 100,000) Age standardized prevalence (per 100,000) Relative weight Weight in each outcome Mean of weights of five outcomes 1000 resampling iterations Constructing a value-weight integrated composite end point Relative weight i Number of events i Meta-analysis Mantel-Haenszel fixed-effects model DerSimonian and Laird random-effects model Summarization

54 Data Extraction 9 RCTs that compared NOACs with VKAs in patients with nonvalvular AF 5 Outcomes myocardial infarction stroke or systemic embolism intracranial hemorrhage gastrointestinal bleeding all-cause death

55 Main characteristics of included studies Study, year Trial design Sample size, n (Int/Comp) ARISTOTLE, 2011 ARISTOTLE-J, 2011 CHUNG, 2011 ENGAGE AF- TIMI 48, 2013 RE-LY, 2009 Multicenter & multinational (1034 centers in 39 countries), double-blind, phase III RCT Multicenter (23 centers in Japan), double-blind, open-label, phase II RCT 18,201 (9120 / 9081) 222 (74 for 2.5 mg, 74 for 5 mg / 74) Multinational (4 Asian 235 countries), double-blind, (79 for 30 mg, open-label, phase II RCT 80 for 60 mg / 76) Multicenter & multinational (1393 centers in 46 countries), double-blind, doubledummy, phase III RCT Multicenter & multinational (951 centers in 44 countries), open-label, phase III RCT 21,105 (7034 for 30 mg, 7035 for 60 mg / 7036) 18,113 (6015 for 110 mg, 6076 for 150 mg / 6022) Intervention Comparator Duration of treatment Apixaban 5 mg BID (or 2.5 mg BID if 2 criteria: age 80 years, body weight 60 kg, serum creatinine 1.5 mg/dl) Apixaban 2.5 mg BID, 5 mg BID Edoxaban 30 mg OD, 60 mg OD Edoxaban 30 mg OD, 60 mg OD Dabigatran 110 mg BID, 150 mg BID Warfarin (dose adjusted, target INR 2-3) Warfarin (dose adjusted, target INR 2-3 if age 70 years, or if age >70 years) Warfarin (dose adjusted, target INR 2-3) Warfarin (dose adjusted, target INR 2-3) Warfarin (dose adjusted, target INR 2-3) 1.8 years (median) 12 weeks (median) Duration of follow-up 1.8 years (median) NA TTR, % Mean age, year Male, % 62.2 (mean) 70 (median) Overall 60% of patients had INR within the 2-3 range for 60% of the treatment period months 3 months days (medium) 2 years (median) 1022 days (medium) 2 years (median) 64.9 (mean) 72 (median) (mean) Mean CHADS 2 score

56 Main characteristics of included studies (Cont'd) Study, year Trial design Sample size, n (Int/Comp) ROCKET AF, 2011 J-ROCKET AF, 2012 WEITZ, 2010 YAMASHITA, 2012 Multicenter & multinational (1178 clinical sites in 45 countries), doubleblind, double-dummy, phase III RCT Multicenter (167 sites in Japan), doubleblind, double-dummy, phase III RCT Multicenter & multinational (91 centers in 12 countries), doubleblind, open-label, phase II RCT Multicenter (61 centers in Japan), double-blind, openlabel, phase II RCT 14,264 (7131 / 7133) 1,280 (640 / 640) 1,146 (235 for 30 mg OD, 245 for 30 BID, 235 for 60 mg OD, 180 for 60 BID / 251) 536 (135 for 30 mg, 135 for 45 mg, 132 for 60 mg / 134) Intervention Comparator Duration of treatment Rivaroxaban 20 mg OD (or 15 mg OD if CrCl ml/min) Rivaroxaban 15 mg OD (or 10 mg OD if CrCl ml/min) Edoxaban 30 mg OD, 30 mg BID, 60 mg OD, 60 mg BID Edoxaban 30 mg OD, 45 mg OD, 60 mg OD Warfarin (dose adjusted, target INR 2-3) Warfarin (dose adjusted, target INR 2-3 if age <70 years, or if age 70 years) Warfarin (dose adjusted, target INR 2-3) Warfarin (dose adjusted, target INR 2-3 if age <70 years, or if age 70 years) 590 days (median) 499 days for Rivaroxaban, 481 days for Warfarin (median) Duration of follow-up 707 days (median) 1.3 years (median) TTR, % Mean age, year Male, % 55 (mean) 73 (median) Mean CHADS 2 score 12 weeks 12 weeks % CHADS 2 score of 2 = 63.3% 12 weeks 12 weeks 73% for age <70 years, 83% for age 70 years BID, twice daily; OD, once daily; INR, international normalized ratio; TTR, time in therapeutic range; CrCl, creatinine clearance; Int, intervention; Comp, comparator

57 Preparation of End Point Weights Two metrics The disability-adjusted life-years (DALYs) developed by WHO Global Burden of Disease Project (GBDP) The clinical endpoints preferences surveyed by questionnaire in the field

58 Disability-adjusted life-years (DALYs) A summary measure of population health widely used to quantify burden of disease 1 DALY = 1 lost year of "healthy" life in given population, due to combined effects of disability and premature death Formula

59 DALYs New version Open database Reference

60 Global age-standardized rates (per 100,000) of DALYs, YLDs, YLLs, prevalence, and mortality for five causes in 2013 DALYs (95% UI) YLDs (95% UI) YLLs (95% UI) Prevalence (95% UI) Mortality (95% UI) Ischemic heart disease ( ) 95.1 ( ) ( ) ( ) ( ) Ischemic stroke ( ) 43.0 ( ) ( ) ( ) 57.3 ( ) Hemorrhagic stroke ( ) 17.2 ( ) ( ) ( ) 52.8 ( ) Peptic ulcer disease ( ) 20.4 ( ) ( ) ( ) 4.9 ( ) Cardiovascular diseases ( ) ( ) UI, uncertainty interval; DALYs, disability-adjusted life years; YLDs, years lived with disability; YLLs, years of life lost

61 Clinical endpoints preferences survey Demographic characteristics Disease history Importance of each endpoint to subjects themselves

62 Distribution of endpoints preferences (N=172) Myocardial infarction Ischemic stroke Hemorrhagic stroke Gastrointestinal bleeding All-cause death Importance Score N (%) N (%) N (%) N (%) N (%) Minimal 1 2 (1.16) 2 (1.16) 2 (1.16) 5 (2.91) 15 (8.72) 2 4 (2.33) 2 (1.16) 1 (0.58) 3 (1.74) 10 (5.81) 3 2 (1.16) 2 (1.16) 0 (0.00) 13 (7.56) 9 (5.23) 4 0 (0.00) 1 (0.58) 2 (1.16) 12 (6.98) 8 (4.65) 5 10 (5.81) 8 (4.65) 6 (3.49) 34 (19.77) 12 (6.98) 6 6 (3.49) 4 (2.33) 4 (2.33) 28 (16.28) 6 (3.49) 7 4 (2.33) 11 (6.40) 9 (5.23) 21 (12.21) 0 (0.00) 8 25 (14.53) 32 (18.60) 28 (16.28) 24 (13.95) 7 (4.07) 9 22 (12.79) 35 (20.35) 31 (18.02) 4 (2.33) 4 (2.33) Maximal (56.40) 75 (43.60) 89 (51.74) 28 (16.28) 101 (58.72) E(score)

63 Incorporation of Value Weights into Individual End Points STEP 1: Standardized value-weight for individual end points Age-standardized DALYs per patient Age standardized DALY rate (per 100,000) Age standardized prevalence (per 100,000) Clinical endpoints preferences for each subject

64 STEP 2: Relative weight for individual end points Weight in each outcome Mean ofweights offive outcomes STEP 3: Constructing a value-weight integrated composite end point Relative weight i Number of events i

65 Comparison of end point weights from two metrics, DALYs and clinical endpoints preferences 1000 resampling iterations based on the appropriate distribution of weighting parameter DALYs, year (per event) Endpoints preference s, points (per subject) Weights MI SSE ICH GIB 1.56 ( ) 8.70 ( ) 2.64 ( ) 8.59 ( ) 8.66 ( ) 8.84 ( ) 0.16 ( ) 6.35 ( ) All-cause death ( ) 7.50 ( ) Relative Weights MI SSE ICH GIB ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) Values are expressed as mean (95% uncertainty interval). DALYs, disability-adjusted life years; MI, Myocardial infarction; SSE, Stroke or systemic embolism; ICH, Intracranial hemorrhage; GIB, Gastrointestinal bleeding All-cause death ( ) ( )

66 STEP 2: Relative weight for individual end points Weight in each outcome Mean ofweights offive outcomes STEP 3: Constructing a value-weight integrated composite end point Relative weight i Number of events i

67 Meta-analysis Two types of models were used to statistically combine results Mantel-Haenszel fixed-effects model DerSimonian and Laird random-effects model

68 Summarization 1000 pooled estimates calculated by metaanalysis DALYs

69 NOACs VKAs DALYs-weighted (1000 bootstraps) Events Total Events Total RR (95% CI) RR, range 95% LL, range 95% UL, range Apixaban ARISTOTLE (0.77, 0.89) ARISTOTLE-J (0.01, 1.11) Subtotal Fixed-effects 0.83 (0.76, 0.89) (0.844, 0.860) (0.797, 0.816) (0.892, 0.906) Random-effects 0.45 (0.08, 2.52) (0.845, 0.861) (0.799, 0.817) (0.894, 0.907) Dabigatran RE-LY (0.84, 0.97) Subtotal Fixed-effects 0.91 (0.84, 0.97) (0.848, 0.867) (0.803, 0.824) (0.896, 0.913) Edoxaban CHUNG (0.02, 2.56) ENGAGE AF (0.85, 0.95) WEITZ (0.55, 2.25) YAMASHITA (0.25, 2.82) Subtotal Fixed-effects 0.90 (0.86, 0.95) (0.866, 0.881) (0.834, 0.850) (0.900, 0.913) Random-effects 0.90 (0.86, 0.95) (0.866, 0.880) (0.833, 0.849) (0.900, 0.913) Rivaroxaban J-ROCKET AF (0.53, 1.13) ROCKET AF (0.89, 1.03) Subtotal Fixed-effects 0.95 (0.89, 1.02) (0.901, 0.909) (0.853, 0.864) (0.952, 0.957) Random-effects 0.93 (0.82, 1.07) (0.901, 0.909) (0.853, 0.864) (0.952, 0.956) Total Fixed-effects 0.90 (0.87, 0.93) (0.865, 0.879) (0.844, 0.859) (0.887, 0.899) Random-effects 0.90 (0.85, 0.94) (0.866, 0.879) (0.844, 0.860) (0.887, 0.900)

70 Cumulative probability (%) Cumulative ranking curve for DALYs-weighted results Apixaban Dabigatran SUCRA = 1.0 SUCRA = Best 2nd 3rd Worst 0 Best 2nd 3rd Worst Edoxaban Rivaroxaban SUCRA = 0.3 SUCRA = Best 2nd 3rd Worst 0 Best 2nd 3rd Worst SUCRA, surface under the cumulative ranking 72

71 NOACs VKAs Preferences-weighted (1000 bootstraps) Events Total Events Total RR (95% CI) RR, range 95% LL, range 95% UL, range Apixaban ARISTOTLE (0.77, 0.89) ARISTOTLE-J (0.01, 1.11) Subtotal Fixed-effects 0.83 (0.76, 0.89) (0.811, 0.822) (0.750, 0.762) (0.878, 0.886) Random-effects 0.45 (0.08, 2.52) (0.370, 0.407) (0.044, 0.060) (2.768, 3.093) Dabigatran RE-LY (0.84, 0.97) Subtotal Fixed-effects 0.91 (0.84, 0.97) (0.885, 0.897) (0.823, 0.834) (0.952, 0.965) Edoxaban CHUNG (0.02, 2.56) ENGAGE AF (0.85, 0.95) WEITZ (0.55, 2.25) YAMASHITA (0.25, 2.82) Subtotal Fixed-effects 0.90 (0.86, 0.95) (0.897, 0.902) (0.849, 0.855) (0.946, 0.952) Random-effects 0.90 (0.86, 0.95) (0.897, 0.902) (0.849, 0.855) (0.946, 0.952) Rivaroxaban J-ROCKET AF (0.53, 1.13) ROCKET AF (0.89, 1.03) Subtotal Fixed-effects 0.95 (0.89, 1.02) (0.932, 0.941) (0.869, 0.878) (1.000, 1.010) Random-effects 0.93 (0.82, 1.07) (0.933, 0.941) (0.869, 0.877) (1.001, 1.017) Total Fixed-effects 0.90 (0.87, 0.93) (0.885, 0.892) (0.856, 0.863) (0.915, 0.922) Random-effects 0.90 (0.85, 0.94) (0.883, 0.890) (0.837, 0.846) (0.930, 0.938)

72 Cumulative probability (%) Cumulative ranking curve for preferences-weighted results Apixaban Dabigatran SUCRA = 1.0 SUCRA = Best 2nd 3rd Worst 0 Best 2nd 3rd Worst Edoxaban Rivaroxaban SUCRA = 0.3 SUCRA = Best 2nd 3rd Worst 0 Best 2nd 3rd Worst SUCRA, surface under the cumulative ranking 74

73 In Clinical Practice S c e n ar MI SS E IC H GI B Allcaus e death Relative Weights Apixaban Dabigatran Edoxaban Rivaroxaban i o X Y Z P Q X Y Z P Q RR (95% CI) RR (95% CI) RR (95% CI)* RR (95% CI) (0.768, 0.936)1.065 (0.971, 1.168)1.193 (0.634, 2.242)0.941 (0.864, 1.025) (0.741, 0.861)0.825 (0.768, 0.887)0.967 (0.919, 1.019)0.901 (0.844, 0.961) (0.575, 0.706)0.659 (0.597, 0.727)0.786 (0.515, 1.198)0.832 (0.754, 0.918) (0.775, 0.937)1.106 (1.020, 1.198)0.919 (0.777, 1.085)1.170 (1.084, 1.264) (0.843, 0.928)0.905 (0.863, 0.948)0.900 (0.872, 0.929)0.931 (0.889, 0.975) (0.765, 0.890)0.907 (0.844, 0.974)0.902 (0.855, 0.951)0.950 (0.887, 1.018) *Estimates were calculated with a random-effects model because more than three studies were included.

74 Future Plans Establish interactive decision support system incorporating our proposed preferenceweighted SR method 76

75 Summary Diseases and their treatment can influence many organs in diverse ways Composite end points (Net clinical outcomes) are increasingly used in RCTs To capture the number of patients who have 1 or more of several events of interest Can index the overall impact of therapeutic interventions and reduce sample size requirements Have well-recognized limitations Common practice of weighting all end point components equally, irrespective of their relative impact on the life of the patient

76 Presentation Outline Core epistemological principle of EBM The principal of EBM application Shared Decision Making Make EBM Individualized Why and how? Maker EBM smarter Learning on demand Medical calculation in EMR A better EBM inquiry system Take Home Messages 78

77 院內建置 UpToDate 實證連結有效節省臨床工作時間! 79

78 Learning on Demand 功能擴充 80

79 Presentation Outline Core epistemological principle of EBM The principal of EBM application Shared Decision Making Make EBM Individualized Why and how? Maker EBM smarter Learning on demand Medical calculation in EMR A better EBM inquiry system Take Home Messages 81

80 醫學計算機展示 - 首頁 82

81 選擇計算機 83

82 自動抓取病歷資料 1 84

83 自動抓取病歷資料 2 85

84 自動抓取病歷資料 3 86

85 參數有誤提醒 87

86 計算結果與儲存 88

87 儲存紀錄瀏覽 1 89

88 儲存紀錄瀏覽 2 90

89 Presentation Outline Core epistemological principle of EBM The principal of EBM application Shared Decision Making Make EBM Individualized Why and how? Maker EBM smarter Learning on demand Medical calculation in EMR A better EBM inquiry system Take Home Messages 91

90 前瞻願景實證醫學與教學研究發展的嶄新思維臺北榮總實證醫學中心的核心理念與前瞻遠見, 不只是展現出實證醫學 5A 的流程需求, 更洞見了實證醫學在臨床和教研上的相互關聯, 這將開創出國內首創的實證醫學與互動交流的創新改革臨床實務實證醫學中心同儕互動

91 規劃理念 Future Leaders in EBM Clinicians & Healthcare Professionals Discussion, Interaction, Analysis. Resources, Tools, Case Studies 實證醫學模組知識互動模組

92 實證醫學模組 5A 流程系統的具體實踐 Ask: 臨床情境 PICO 查詢 Acquire: 查詢策略結果去重書目收藏 SFX 全文鏈結 Appraise: 評讀及發表工具下載結果 PDF 匯入評讀表單 Apply: 決策輔助工具下載 PDAs 表單 Audit: 評估表單填寫及儲存 Case Studies: 成果紀錄單預覽下載及公開 02 使用者 ( 會員 )

100 Presentation Outline Core epistemological principle of EBM The principal of EBM application Shared Decision Making Make EBM Individualized Why and how? Maker EBM smarter Learning on demand Medical calculation in EMR A better EBM inquiry system Take Home Messages 102

101 Take Home Message EBM is a useful and powerful clinical tool for clinicians Shared decision making is the core of patient-centered care In the era of AI, technology and environment embedded with augmented intelligence is important for a better clinical care Facing the many clinical outcomes, including benefit and risk endpoints, it is hard to incorporate patients value in the decision making process. We propose a novel method to generate a preferenceweighted composite endpoint which may better the informed decision process 103

102 Q & A 謝謝聆聽敬請指教

Edoxaban in Atrial Fibrillation

Edoxaban in Atrial Fibrillation Glenn Gormley, MD, PhD Senior Executive Officer and Global Head of R&D, Daiichi Sankyo Co., Ltd Nov. 4, 2014 Tuesday Background Based on the results of ENGAGE AF-TIMI 48,