Antithrombotic drugs: Assessing the

benefits and harms in medically complex patients with cardiovascular

disease

Alexandra Hajduk, PhD, MPH Associate Research Scientist, Section of Geriatrics

Yale School of Medicine

Amgad Mentias, MD Cardiology Fellow, Division of Cardiovascular Medicine

University of Iowa Hospitals and Clinics

Mary Vaughan-Sarrazin, PhD Associate Professor, Department of Internal Medicine

University of Iowa

Gregory Ouellet, MD Instructor, Section of Geriatrics

Yale School of Medicine

HCSRN-OAICs AGING Initiative

October 25, 2018

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Today’s Speakers

Alexandra Hajduk, PhD, MPH

Amgad Mentias, MD

Mary Vaughan-Sarrazin, PhD

Gregory Ouellet, MD

For questions about the AGING Initiative or today’s webinar, please contact:

Kathryn.Anzuoni@meyersprimary.org

Thank you!

— 1 —

COMPARATIVE EFFECTIVENESS OF ORAL ANTICOAGULANTS IN PATIENTS WITH ATRIAL FIBRILLATION AND MULTIPLE CHRONIC CONDITIONS: A MEDICARE ANALYSIS

Aging Webinar 01/10/2019

Amgad Mentias, Mary Vaughan-Sarrazin University of Iowa

Disclosures

• No relevant financial disclosures • Dr. Sarrazin: This work is supported by a grant from the

Agency for Healthcare Research and Quality (AHRQ).

Background

Atrial fibrillation (AF) affects 3 million adults in the United States.(1)

AF increases stroke risk by 3 to 5 fold.(2)

Anticoagulation reduces risk of stroke.

Several agents are available for non valvular AF:

1. Warfarin

2. Direct oral anticoagulants (DOAC’s): Dabigatran, Apixaban,

Rivaroxaban and Edoxaban.

• Anticoagulation increases risk of dangerous bleeding.

Background

• AF prevalence increase with aging.(1)

• Elderly people usually suffer from multiple co-morbid

conditions (MCC).

• Age and age-related comorbidities are risk factors for

ischemic stroke and bleeding

Background

• In a study of ≈ 300,000 AF patients and 500,000 age-sex matched controls:

- Prevalence of any concomitant disease was 70% in AF compared to 28% in controls.

- Concomitant diseases included stroke, renal failure, COPD, hypertension, diabetes and neoplasms. (3)

Background

• In another study from UK: (4)

- AF with ≥4 co-morbidities had a 6-fold higher risk of mortality compared to participants without any long-term condition.

• Risk of mortality:

- CHF (HR 2.96, 95% CI 1.83-4.80)

- COPD (HR 3.31, 95% CI 2.14-5.11)

- Osteoporosis (HR 3.13, 95% CI 1.63-6.01)

Background

• In AF patients >75 years old, >50% are not prescribed any AC despite high stroke risk by CHA2DS2-Vasc score. (5)

• Frailty is an important factor that sway physicians from prescribing AC. (5,6)

• Cognitive impairment is specially important in warfarin and affects quality of AC by affecting time in INR therapeutic range. (6)

Background

• In two studies (one from France and one from US):

- DOAC’s were prescribed to younger, and healthier patients compared to warfarin.

- DOAC’s were less likely to be prescribed to patients with higher CHADS2Vasc, and HAS-BLED scores.

Background

• Randomized controlled trials are always limited in

generalizability and application to real world patients.

− In the ROCKET-AF (Rivaroxaban) trial, < 15% of the

study participants had CHADS2 score ≥5.(9)

− In the RELY trial (Dabigatran), less than 1/3rd of study

participants had a CHADS2 score ≥3.(10)

Aim of the study

• Compare the effectiveness of warfarin, rivaroxaban,

and dabigatran in stroke prevention in elderly patients

with AF and low, moderate, and high levels of

comorbidity.

• Compare the safety of warfarin, rivaroxaban, and

dabigatran in elderly patients with AF and low,

moderate and high levels of comorbidity.

Methods: Data and Patients Source of data: • Medicare inpatient, carrier, and pharmacy claims (2010-2013). Inclusion criteria: • Age 66 older • ICD-9 code 427.31 as primary diagnosis. • New AF diagnosis (One inpatient or two outpatient claims within 90

days and no AF in prior 12 months) • Started on dabigatran (150 mg) twice daily, rivaroxaban (20 mg) once

daily, or warfarin within 90 days after AF diagnosis. Exclusion criteria: • Enrolled in a Medicare managed care during the observation period, • Not enrolled in a Part D drug prescription plan at the time of AF

diagnosis.

Anticoagulant Type defined by first AC received after AF diagnosis.

Methods: Outcomes

• Primary outcome:

Acute admission for acute ischemic stroke

Acute admission for major bleeding event

• Secondary outcomes:

− Gastrointestinal Bleeding (GIB)

− Non-GI major hemorrhage (including intracranial hemorrhage)

− Acute myocardial infarction (MI)

− All-cause mortality death

Methods: Comorbidity Assessment Three scoring systems to assess MCC burden:

1. CHA2DS2-Vasc Stroke Risk score:

Scored as: 1 point: congestive heart failure hypertension age 65-74 years diabetes vascular disease female gender.

2 points: history of stroke age ≥75 years.

- Ranges from 0 to 9 (Minimum score in our study was 1).

- Categorized as: 1-3 Low, (4-5) Moderate, (≥6) High

Methods: Comorbidity Assessment

2) HAS-BLED Bleeding Risk score: - Score as: 1 point: hypertension

prior stroke history or predisposition towards bleeding age ≥65 years alcohol/drug use that increases bleeding risk Liver and renal diseases. History of labile international normalized ratio (INR) (not relevant for our study)

- Ranges from 0 to 9 (minimum score = 1 in our study)

- Categorized as: (=1) Low, (=2) moderate, (≥3) high.

Methods: Comorbidity Assessment

3) Gagne Comorbidity Score: - All-cause mortality risk

- Weighted Scoring representing: unexplained weight loss, hemiplegia, alcohol abuse, tumor, renal disease, metastatic cancer, dementia, arrhythmia, pulmonary disease, coagulopathy, complicated diabetes, anemia, electrolyte imbalance, liver disease, peripheral vascular disease, psychosis, pulmonary circulatory disorder, HIV/AIDS, and heart failure.

- Categorized as: (0-2) Low, (3-4) Moderate, (≥5) High.

Methods: Statistical analysis

- Patients divided into low, moderate and high MCC using alternative comorbidity scores

- Analysis used three-way propensity score matching

3-way match

rivaroxaban dabigatran

warfarin

Methods: Statistical analysis

• Matching conducted separately by MCC level, by three scores

9 matching algorithms.

• Analysis of matched samples used Cox Proportional Hazards Regression for time to key outcomes.

• Censoring events included:

1) End of observation (December 31, 2013)

2) Cessation of the initial AC (last fill date + days supplied)

3) Death.

Results: Demographics

Results: Comorbid Conditions

Results: MCC Level by drug

Results: Ischemic Stroke

Results: Major bleeding

Results: Gastrointestinal bleeding

Results: All-cause mortality

Conclusion

• Rivaroxaban, Dabigatran and warfarin are similarly effective for stroke prevention in AF patients with MCC.

• Dabigatran use is associated with a lower bleeding risk whereas rivaroxaban use is associated with a higher bleeding risk compared to warfarin use in high-risk patients

• Both DOAC’s were associated with lower all-cause mortality compared to warfarin, regardless of MCC level.

Limitations

1. Possible residual confounding from unmeasured factors even after propensity matching.

2. All of our patients were older than 65 years, which might limit generalizability to younger patients.

3. Lack of information on type of AF (paroxysmal vs. permanent), INR levels, and time in therapeutic range in warfarin users.

References

1. Naccarelli G V, Varker H, Lin J, Schulman KL. Increasing Prevalence of Atrial Fibrillation and Flutter in the United States. Am J Cardiol. 2009;104(11):1534-1539. doi:10.1016/j.amjcard.2009.07.022.

2. Wolf PA, Abbott RD, Kannel WB. Atrial fibrillation as an independent risk factor for stroke: the Framingham Study. Stroke. 1991;22(8):983-988. doi:10.1161/01.STR.22.8.983.

3. Andersson T, Magnuson A, Bryngelsson I-L, et al. All-cause mortality in 272 186 patients hospitalized with incident atrial fibrillation 1995–2008: a Swedish nationwide long-term case–control study. Eur Heart J. 2013;34(14):1061-1067. doi:10.1093/eurheartj/ehs469.

4. Jani BD, Nicholl BI, McQueenie R, et al. Multimorbidity and co-morbidity in atrial fibrillation and effects on survival: findings from UK Biobank cohort. EP Eur. November 2017. doi:10.1093/europace/eux322.

5. Induruwa I, Evans NR, Aziz A, Reddy S, Khadjooi K, Romero-Ortuno R. Clinical frailty is independently associated with non-prescription of anticoagulants in older patients with atrial fibrillation. Geriatr Gerontol Int. April 2017. doi:10.1111/ggi.13058.

6. Gorzelak-Pabiś P, Zyzak S, Krewko Ł, Broncel M. Assessment of the mean time in the therapeutic INR range and the SAME-TT2R2 score in patients with atrial fibrillation and cognitive impairment. Polish Arch Intern Med. 2016;126(7-8):494-501. doi:10.20452/pamw.3475.

Reference (continued)

7. Huiart L, Ferdynus C, Renoux C, et al. Trends in initiation of direct oral anticoagulant therapies for atrial fibrillation in a national population-based cross-sectional study in the French health insurance databases. BMJ Open. 2018;8(3):e018180. doi:10.1136/bmjopen-2017-018180.

8. Desai NR, Krumme AA, Schneeweiss S, et al. Patterns of Initiation of Oral Anticoagulants in Patients with Atrial Fibrillation— Quality and Cost Implications. Am J Med. 2014;127(11):1075-1082.e1. doi:10.1016/j.amjmed.2014.05.013.

9. Patel MR, Mahaffey KW, Garg J, et al. Rivaroxaban versus Warfarin in Nonvalvular Atrial Fibrillation. N Engl J Med. 2011;365(10):883-891. doi:10.1056/NEJMoa1009638.

10. Connolly SJ, Ezekowitz MD, Yusuf S, et al. Dabigatran versus Warfarin in Patients with Atrial Fibrillation. N Engl J Med. 2009;361(12):1139-1151. doi:10.1056/NEJMoa0905561.

Thank you

Haddad F, et al. Circulation. 2008;117:1436-1448.

Evaluating Benefits & Harms of Triple Antithrombotic Therapy in Medically Complex

Older Adults with AMI and AF GIG Initiative Pilot

AGING Initiative Pilot Plus+ Webinar January 10, 2019

1

Atrial Fibrillation (AF) in Acute Myocardial Infarction (AMI)

AF affects ~20% of AMI survivors Predicts worse outcomes: Readmission Stroke Death

Rathore, et al., Circ 2000; Jabre, et al., Circ 2011; Kundu, et al., Int J Cardiol 2016 2

Guideline-recommended treatments for AMI and AF

Aspirin (ASA)

Oral anticoagulant

Antiplatelet (P2Y12 I)

AMI: Aspirin & P2Y12 Inhibitor Minimum one year

AF: Oral anticoagulant indefinitely

Triple therapy 3

THROMBOSIS

4

What do guidelines say about AF+AMI?

(Levine 2016)

“In patients with long-standing AF or a moderate-to-high CHA2DS2-VASc score, efforts should be directed to minimize duration of triple therapy, and decisions about stent insertion should consider the potential requirement for long-term anticoagulant therapy.”

(January 2014)

2016 ACC/AHA Update on dual antiplatelet therapy in coronary artery disease

2014 ACC/AHA Atrial fibrillation guideline

5

Triple Therapy and Bleeding Risk

Hess, et al., JACC 2015 6

Triple Therapy and Stroke Risk

Hess et al., JACC 2015 7

Triple Therapy and Cardiac Events

D’Ascenzo 2015 Zhao 2011

8

Geriatric Conditions, AMI, & AF

• Medically complex older patients: • Less included in drug clinical trials • Benefit less from treatments/interventions • ↑ risk of drug-drug or drug-disease interactions

• Geriatric conditions affect outcomes in AMI & AF • Prevalence in older adults with AMI+AF? • Influence on outcomes? • Moderating influence on treatments?

Lorgunpai, et al., PLoS One 2014, Fried, et al., JAGS 2014 9

Project Aims

1. Characterize prevalence of and factors associated with receipt of triple therapy

2. Examine association of antithrombotic therap with MACE and bleeding

3. Examine MCCs and frailty as moderators of antithrombotic therapy and outcomes

10

Clinical

Psychosocial

Demographic

Geriatric 3000 AMI patients ≥75 years old

Dataset and Analytic Sample

831 patients with comorbid AF 11

Aim 1- Factors Associated with Receipt of Triple Therapy

Outcome: Receipt of triple therapy vs. alternatives at hospital discharge after AMI Factors: Multimorbidity (Charlson) Frailty (Fried) Baseline stroke (CHA2DS2-VASC) and bleeding risk (HAS-BLED) Demographics In-hospital procedures/events Other geriatric vulnerabilities (mobility, falls) Lifestyle & Psychosocial Analysis: multivariable-adjusted logistic regression of all factors associated with antithrombotic therapy at p<.05

12

Sample Composition

Mean age= 82.4 (±5.3) years

58% male

8% non-White

80% underwent cardiac cath

66% pre-existing Afib (34% diagnosed during index admission)

Median Charlson score: 3 (IQR 2-5), 49% ≥4

Frailty (Fried Criteria): 15% non-frail, 54% pre-frail, 31% frail

13

20% of sample was on triple therapy at discharge.

[CATEGORY NAME], 33%

[CATEGORY NAME], [PERCENTAGE]

[CATEGORY NAME], [PERCENTAGE]

[CATEGORY NAME], [PERCENTAGE]

Antplat + Anticoag 4%

Anticoag only 3%

None 2%

[CATEGORY NAME] 1%

14

We retained the most common 4 groups for analysis (91% of cohort)

[CATEGORY NAME], 33%

[CATEGORY NAME], [PERCENTAGE]

[CATEGORY NAME], [PERCENTAGE]

[CATEGORY NAME], [PERCENTAGE]

Antplat + Anticoag 4%

Anticoag only 3%

None 2%

[CATEGORY NAME] 1%

15

Factors associated with antithrombotic treatment (ref: triple therapy)

Relative Risk Ratio (95% Confidence Interval)

Charlson score

Frailty

CHA2DS2-VASC score (per pt)

HAS-BLED score (per pt)

Education (≤12 years)

Admission Year (2013-16)

Pre-existing AF (vs. new onset)

Percutaneous Intervention

GRACE (higher cardiac risk)

Mobility Impairment Included in model but not associated with any outcome at p<.05: age, sex, marital status, acute kidney injury, GRACE score, cognition, fall history, social support

ASA + Anticoag 0.84 (0.73-0.96)

0.61 (0.29-1.28)

0.85 (0.60-1.20)

1.25 (0.80-1.94)

1.35 (0.72-0.96)

0.78 (0.59-1.04)

0.79 (0.38-1.64)

0.013 (0.00-0.039)

1.02 (1.01-1.04)

1.44 (1.03-2.02)

DAPT 1.04 (0.94-1.15)

0.69 (0.40-1.18)

0.77 (0.61-0.99)

1.41 (1.03-1.91)

1.41 (0.90-2.19)

0.77 (0.63-0.95)

0.47 (0.28-0.78)

0.50 (0.21-1.21)

1.00 (0.99-1.01)

1.25 (0.99-1.59)

ASA only 0.96 (0.83-1.10)

1.15 (0.52-2.54)

0.58 (0.39-0.85)

1.90 (1.16-3.11)

2.02 (1.02-3.97)

0.76 (0.56-1.04)

0.58 (0.26-1.27)

0.004 (0.001-0.017)

1.00 (0.98-1.01)

1.16 (0.80-1.68) 16

Drivers of antithrombotic therapy choice:

Baseline risk of thrombosis and bleeding Percutaneous coronary intervention (i.e., stents) If you got a stent, you’re on antiplatelet

Multimorbidity associated with ↓ use of ASA+anticoagulant Frailty not predictive of therapy choice

17

Project Aims

1. Characterize prevalence of and factors associated with receipt of triple therapy

2. Examine association of antithrombotic therapy with MACE and bleeding

18

Methods

Analytic sample AMI+AF patients on 4 most common antithrombotic regimens

Outcomes Major adverse cardiovascular event (MACE) at 6 months CV death, MI, stroke, revascularization Clinically significant bleeding at 6 months Bleeding event necessitating ED visit or hospitalization

Analysis inverse probability of treatment-weighted logistic regression

19

More intensive antithrombotic therapy associated with ↓MACE, ↑ bleeds

02468

101214161820

MACE Bleed

Perc

ent e

xper

ienc

ing

outc

ome

by 6

mon

ths

ASA only DAPT ASA + Anticoagulant Triple Therapy

MACE (CV death, MI, stroke, revascularization) at 6 months: 8%

Clinically significant bleeding at 6 months: 12%

P=.036

P=.034

20

Increased risk of MACE associated with non-triple therapy regimens attenuated after adjustment/weighting*

*adjusted and/or weighted for age, sex, education, marital status, Charlson score, frailty, cognition, fall risk, hospitalization year, atrial fibrillation type, revascularization, acute kidney injury, cardiac risk, thrombosis risk, bleeding risk, mobility

21

Project Aims

1. Characterize prevalence of and factors associated with receipt of triple therapy

3. Explore MCCs and frailty as moderators of antithrombotic therapy and outcomes

22

Methods

Analytic sample AMI+AF patients with 4 most common antithrombotic regimens

Outcomes Major adverse cardiovascular event (MACE) at 6 months Clinically significant bleeding at 6 months Moderators Frailty status (Fried score ≥3) MCC status (Charlson score ≥4) Analysis Exploratory 23

Frailty, MCCs, and Antithrombotic Therapy Type

0102030405060708090

100

Frail Charlson >/=4

Perc

ent w

ith C

ondi

tion

ASA Only DAPT ASA + Anticoagulant Triple Therapy

NS

NS

24

Frailty, MCCs, and 6-month Outcomes

0

2

4

6

8

10

12

14

16

18

20

MACE Bleed

Perc

ent

Frailty and Outcomes

Not frail Frail

0

2

4

6

8

10

12

14

16

18

20

MACE Bleed

Perc

ent

Multimorbidity and Outcomes

Charlson <4 Charlson ≥4

P= .20

P= .08

P= .07

P<.001

25

Frailty, antithrombotic therapy, and MACE

02468

1012141618

Not Frail FrailPerc

ent e

xper

ienc

ing

MAC

E w

ithin

6 m

onth

s

Frailty Status ASA only DAPT ASA + Anticoagulant Triple Therapy

Interaction of Antithrombotic therapy type x Frailty status= NS 26

MCC status, antithrombotic therapy, and MACE

02468

1012141618

Charlson <4 Charlson >/=4

Perc

ent e

xper

ienc

ing

MAC

E w

ithin

6 m

onth

s

MCC Status

ASA only DAPT ASA + Anticoagulant Triple Therapy

Interaction of Antithrombotic therapy type x MCC status= NS 27

Frailty, antithrombotic therapy, and bleeding

0

5

10

15

20

25

Not Frail FrailPerc

ent e

xper

ienc

ing

blee

ding

with

in 6

mon

ths

Frailty Status

ASA only DAPT ASA + Anticoagulant Triple Therapy

Interaction of Antithrombotic therapy type x frailty status= NS 28

MCC status, antithrombotic therapy, and bleeding

0

5

10

15

20

25

Charlson <4 Charlson >/=4

Perc

ent e

xper

ienc

ing

blee

d w

ithin

6 m

onth

s

MCC Status

ASA only DAPT ASA + Anticoagulant Triple Therapy

Interaction of Antithrombotic therapy type x frailty status= NS 29

Takeaways

Current antithrombotic treatment decisions are driven largely by thrombosis and bleeding risk Geriatric and functional characteristics not influential

More intensive antithrombotic treatment ↑ risk for bleeding Questionable benefit for thrombosis prevention

30

Takeaways, continued

Frailty and multimorbidity are associated with worse outcomes Both exacerbate risk of MACE More so with less intensive antithrombotic therapy

Both exacerbate risk of bleeding More so with more intensive antithrombotic therapy

31

Strengths and Limitations

Contemporary dataset Rigorous operationalization of variables

Limited power to explore MCCs and frailty as moderators Unable to investigate anticoagulant subclasses (i.e, warfarin vs. novel)

32

Implications and Future Directions

Providers should consider geriatric conditions when deliberating antithrombotic treatment choices among older adults Expand analyses to larger datasets Explore “dual antithrombotic therapy” subgroup Investigate effects of use of direct oral anticoagulants vs. warfarin

Mixed methods inquiry into clinical decision making about antithrombotic prescribing in medically complex older adults

33

Thank you!

Our Study Team Sarwat Chaudhry, MD (Yale) Jerry Gurwitz (UMass) Mary Tinetti, MD (Yale) Mayra Tisminetzky, MD, PhD (UMass)

34

Additional Slides

35

0

2

4

6

8

10

12

14

16

18

20

ASA Only DAPT ASA + Antiplatelet Triple Therapy

Perc

ent

Death within 180 Days of AMI, by Antithrombotic Therapy Type

36

CHA2DS2-VASC

37

38

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Then type your questions in the Q&A box:

Questions

For a recording of today’s webinar or to learn more about the AGING Initiative, go to:

https://theaginginitiative.wordpress.com

For questions about the AGING Initiative or today’s webinar, please contact:

Kathryn.Anzuoni@meyersprimary.org

As you leave, please fill out the brief survey with your thoughts and opinions on today’s webinar!

Thank you!