Epstein Mmws

Medco is a registered trademark of Medco Health Solutions, Inc.© 2010 Medco Health Solutions, Inc. All rights reserved.

Effect of Genotyping Warfarin Patients on Outcomes:Results from The National Community-based Medco-Mayo Warfarin Effectiveness Study (MM-WES)

Robert S Epstein MD MS, Thomas P. Moyer PhD, Ronald E. Aubert PhD, Dennis J. O’Kane PhD, Fang Xia PhD, Robert R. Verbrugge PhD, Brian F. Gage MD MS, J. Russell Teagarden DMH, RPh

Medco Health Solutions, Franklin Lakes, NJ;Mayo Clinic, Rochester, MN;Washington University, St Louis MO

Funding sources: Medco Health Solutions, Mayo Clinic Center for Individualized Therapy

Manuscript is “in press” in Journal of American College of Cardiology

2 © 2010 Medco Health Solutions, Inc. All rights reserved.

Background

Warfarin exhibits large inter-individual dosing requirements

Warfarin is a leading cause of morbidity and mortality

Two genes account for ~33% of variance in dosing

Cytochrome P450 2C9 (CYP2C9) – pharmacokinetics

VKORC1 – pharmacodynamics

Meta-analysis of 3 clinical trials of warfarin genotyping showed a 32% decrease in major bleeding (RR 0.68, CI 0.22-2.06)*

*Eckman MH, Rosand J, Geenberg SM, Gage BF: Cost-effectiveness of using pharmacogenetic information in warfarin dosing for patients with nonvalvular atrial fibrillation. Ann Int Med 2009;150(2):73-83.


Study question:

Does use of CYP2C9/VKORC1 testing reduce Does use of CYP2C9/VKORC1 testing reduce the risk of hospitalization during the first 6 the risk of hospitalization during the first 6

months of warfarin treatment?months of warfarin treatment?


23 benefit plan sponsors23 benefit plan sponsors

Primary comparison Comparison of general trends in practice

July 2006 –June 2007n=2688

Historical controlHistorical control

July 2007 –February 2009

n=896

Intervention Intervention groupgroup

56 benefit plan sponsors56 benefit plan sponsors

July 2006 –June 2007n=2688

ExternalExternalhistorical controlhistorical control

July 2007 –February 2009

n=2688

ExternalExternalconcurrent controlconcurrent control

Medco-MayoMedco-MayoWarfarin Effectiveness StudyWarfarin Effectiveness Study

Study design: Comparative effectiveness6 month follow-up on all patients initiating warfarin in all groups


Statistical Methods of Outcomes Comparisons

Unadjusted comparisons – Kaplan-Meier and log-rank tests

Adjusted comparisons – propensity scores to handle participant/non-participant differences, indications for therapy, specific concomitant drugs, medical conditions, prior history of hospitalization or history of bleed/thromboemboli.

ANALYSES

Intention-to-treat – all outcomes even if adverse event preceded genotype

Per-protocol – only those outcomes counted if post-genotype


Flow of the genotyping arm

Mayo completed lab test – supplied report to physician and results to Medco

Medco identified ‘new starts’ to

warfarin on any given day of

the week

Medco contacted ‘new starts’ to solicit verbal

informed consent

Medco contacted physician for

clinical information and consent for

patient to receive genotype test

First half of enrollment – Medco arranged for home

blood draw – received written

informed consent, sent blood to Mayo


Sample Mayo Clinic Laboratory Report

Sample Lab Report: Warfarin Genotype Results Medco Health Solutions Accession #: A1234567 Mayo/Medco Warfarin Protocol Patient Name: DOE, JANE Attn: Accounts Payable Birth Date: 09/13/1942 Age:65 Gender:F 100 Parsons Pond Drive Medical Rec #: 1234 Franklin Lakes, NJ 07417 Client Accn #: 123456789 Ordering Phys: SMITH, JOHN Collect Date: 11/07/2007 10:40 AM Received Date: 11/08/2007 7:19 AM ---------------------------------------------------------------------------------------------------------------

Test Requested Result Units Ref RangePerform Site *

-------------- ------ ----- --------- ------- Rapid DNA Extraction Comment Genomic DNA was extracted. MCR ============================================================================ CYP2C9 + VKORC1 Genotype, Warfarin CYP2C9 430C>T(*2) C/T MCR CYP2C9 1075A>C(*3) A/C MCR CYP2C9 1076T>C(*4) T/T MCR CYP2C9 1080C>G(*5) C/C MCR CYP2C9 818delA(*6) A/A MCR VKORC1 -1639G>A A/A MCR Interpretation MCR

This genotype is rare and has very high sensitivity to warfarin. Warfarin dose decrease and frequent INR monitoring should be considered.


Participants were from 49 US states


Results: Baseline characteristics

CharacteristicHistorical control

(n=2688)Intervention group

(n= 896) P-valueMean age, yrs (SD) 65.2 (8.0) 65.2 (8.3) 0.921Male(%) 60.5% 60.5% 1.000Medications (%)

Amiodarone 4.0% 3.2% 0.313Statins 14.5% 16.9% 0.071Sulfamethoxazole 4.4% 5.2% 0.268Fluconazole 2.4% 2.6% 0.803NSAID 19.6% 19.9% 0.865Clopidogrel 10.8% 10.2% 0.574Steroids 12.4% 13.6% 0.354

Conditions (%)GI bleed 3.6% 4.0% 0.539Atrial fibrillation 40.4% 41.1% 0.709Pulmonary embolism 11.0% 11.8% 0.501Deep vein thrombosis 24.6% 25.8% 0.489Hypertension 47.0% 54.2% <0.001Diabetes 15.3% 11.6% 0.007

Prior hospitalizations (%)Any cause 54.4% 52.8% 0.405Bleeding or thromboembolism 23.6% 24.8% 0.469


Results: (n=424)Warfarin Rxs within 21 days post-genotyping

Warfarin sensitivity % patients

Mean weekly dose change (SE) P-value

< Normal 29.0% +6.65 mg (1.98) <0.01

Normal 28.1% +1.10 mg (1.40) 0.50

Mild 11.6% +3.21 mg (3.41) 0.21

Moderate 25.0% -3.65 mg (1.56) <0.01

High 4.0% -10.14 mg (3.18) 0.04

Very high 2.4% -17.33 mg (4.54) <0.01


25.52

18.45

8.13

5.97

Results: Six month hospitalization rates>=1 hospitalization per 100 patients/6months

Genotyping associated with 28% decrease in all-cause hospitalizations and 27% decrease in bleed or thrombo-emboli

All cause Bleed or thromboembolism

p-value <0.001 0.039

Intention to treat (ITT)

Intervention group (n=896)

Historical control (n=2688)


0%

5%

10%

15%

20%

25%

30%

0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180

Days after treatment onset

Hosp

itali

zati

on

ris

k

IGHC

Results: All-cause hospitalization rateIntention-to-treat analyses

All cause

HR: 0.69 (CI: 0.58, 0.82)P<0.001

Controlled for age, comorbid conditions, drugs, propensity score, indications, prior GI bleed or VTE, history of prior hospitalization


0%

2%

4%

6%

8%

10%

0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180

Days after treatment onset

Hosp

itali

zati

on

ris

k

IGHC

Results: Hospitalization rate for bleed / thrombo-embolism. Intention-to-treat analysis.

Bleed or thromboembolism

HR: 0.72 (CI: 0.53, 0.97)P=0.029

Controlled for age, comorbid conditions, drugs, propensity score, indications, prior GI bleed or VTE, history of prior hospitalization


Results: Same time frames External control group comparison – pre vs. post

Hospitalization rates (unadjusted) Any cause 22.8% vs. 22.7% Bleeds/thromboemboli 7.8% vs. 7.2%

Hospitalization rates (adjusted) H.R. (95% CI) Any cause HR 0.98 (0.88-1.1) Bleeding or thromboemboli HR 0.92 (0.76-1.1)

No difference in hospitalization rates over the No difference in hospitalization rates over the same 2 time periods in the external controlssame 2 time periods in the external controls


Limitations

Non-randomized trial design Entire population comparison before and after population

intervened upon (quasi-experiment) Intention-to-treat biased against genotyping by including events

that occurred before genotype conducted Participation rate high – by both participants and physicians

Hawthorne effect Kept the intervention to a minimum No payment to providers who participated

Administrative Claims Data for endpoints Peer-reviewed literature for algorithm with ICD-9 codes


Conclusions

Genotyping warfarin patients resulted in ~30% risk reduction in hospitalizations for all-cause and for bleeds/thromboemboli

Having genotyping closer to therapy initiation was even better

Physicians changed warfarin prescriptions in the direction suggested by the Mayo genotype laboratory report

Physicians were very willing (75% agreement) to order the genotype tests


Future Suggestions

Further research warranted to confirm and extend our findings

Elderly vs. non-elderly

Role of genotyping to prevent bleeds or thromboemboli as individual endpoints

Impact of genotyping on INR measurements

Economic evaluation of genotyping vs. usual care

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