ARV Pharmacy Refill Adherence

• Robert Grossberg, MD

• Montefiore Medical Center

• Albert Einstein College of Medicine

1

Objectives

• Understand the importance of antiretroviral adherence in HIV

• Evaluate various adherence measurement methods

• Review the use of pharmacy refill adherence methodology in HIV

2

Virologic Control falls sharply with diminished adherence

0

10

20

30

40

50

60

70

80

90

95-100% 90-95% 80-90% 70-80% < 70%

Adherence, by prescription refill

% A

chie

ving

<50

0 co

pies

/mL

N = 504 pts on HAART

Montessori, V, et al. XII International Conference on AIDS, Durban, South Africa, 2000. Abstract MoPpD1056.3

0

20

40

60

80

100

>95 90-95 80–90 70-80 <70

Pat

ient

s w

ith

HIV

RN

A<

400

cop

ies/

mL

, %

Protease Inhibitor adherence, % (electronic bottle caps)

Paterson, et al. 6th Conference on Retroviruses and Opportunistic Infections; 1999; Chicago, IL. Abstract 92.

Virologic Control falls sharply with diminished adherence

4

10% Adherence difference = 21% reduction in risk of AIDSAdherence and AIDS-Free Survival

Bangsberg D, et al. AIDS. 2001:15:1181

Pro

port

ion

AID

S-F

ree

Months from entry

P = .0012

0 5 10 15 20 25 30

0.00

0.25

0.50

0.75

1.00

AdherenceO 90–100%O 50–89%O 0–49%

5

Sub-Optimal Adherence Predisposes to Resistance

• Sub-optimal adherence ==> sub-therapeutic drug levels ==> incomplete viral suppression ==> generation of resistant HIV strains by selection for mutant viruses

• Association between poor adherence and antiretroviral resistance is well-documented1,2

1. Vanhove G, et al. JAMA. 1996;276:1955-1956.

2. Montaner JS, et al. JAMA. 1998;279:930-937. 6

Adherence, Antiviral Activity & Risk of Resistance Mutations

Incr

easi

ng p

roba

bili

tyof

sel

ecti

ng m

utat

ion

Increasing Adherence

Low Risk of Resistance:Inadequate Drug Exposure

Low

Risk

of Resistan

ce:C

omp

lete Viral

Su

pp

ressionHigh Risk of

Resistance:Drug

PressureSustains

Replication of Poorly Fit Virus

How do we Measure Adherence?

• Provider Estimates • Patient self-report• Diaries• Pill Count• Laboratory Markers• Electronic Devices• Prescription refill data

8

Measuring Adherence: Patient Self-Report

• patients tend to report what they think the provider wants to hear1

• patients are unlikely to misrepresent low levels of adherence3 - hence, patient-reported poor adherence is specific but not sensitive

• patient-reported adherence tends to exceed adherence by more objective measurements (such as pill count or electronic monitoring) 2

• Nevertheless, studies have documented an association between patient-reported adherence and viral outcome 4-6

• Patient-reported adherence may be a useful tool to evaluate adherence at a group level but not so much on an individual level1. DiMatteo MR, DiNicola DD, eds. Achieving Patient Compliance. New York: Pergamon Press; 1982:1-28.

2. Golin C et al. 6th Conference on Retroviruses and Opportunistic Infections; 1999; Chicago. Abstract 95.

3. Bond W, Hussar DA, Am J Public Health 1991;81:1978-1988.4 Bangsberg DR, et al. 6th Conference on Retroviruses and Opportunistic Infections; 1999; Chicago. Abstract 93.5. Duong M, et al. 39th ICAAC; 1999; San Francisco. Abstract 20696. Demasi R, et al. 6th Conference on Retroviruses and Opportunistic Infections; 1999; Chicago. Abstract 94.9

Measuring Adherence: Electronic Bottle Caps

MEMScaps, Aardex Corp.10

http://www.aardex.ch/QRChronology.htm

QuickRead software, for use with MEMScaps system

11

Measuring Adherence: Electronic Bottle Caps

• Advantages– more difficult for patients

to exaggerate their adherence

– reveals patterns of non-adherence (i.e., what time of day pills are taken)

– studies using these devices have documented relationship between adherence & dosing

• Disadvantages– too expensive for

routine use outside of research studies

– cannot be used for patients who use pillboxes

12

Pharmacy Refill Data

• Advantages– only choice for retrospective studies– can assess short or long-term behavior

• Disadvantages– less intra-interval variability – further removed from actual drug taking– may not capture (legitimate) prescriptions from other

sources– if automatic refills, data are useless

13

Sources of Refill Data• Automated database

–Medicaid–VA System Pharmacies–Pharmacy Benefit Managers

• Ad hoc data collection–Call pharmacies–HIPAA barriers?

14

Examples of Refill Data• Antihypertensives

–Taken chronically• Disease process over years/decades• Drugs infrequently changed

–Metric: number of refills obtained over year

• Ratio of number of refills/12

15

Examples of Refill Data• Antiretrovirals

–Taken chronically• Disease process over months/years• Drugs frequently changed

–Metric: number of days to obtain 4 refills (3 months)

• Ratio of 90 days supply/# of days to obtain supply

• Time to event approach• Allows for more variability over shorter

interval

16

Prior Work using Refills in HIV• Low-Beer et al. (Vancouver)

– 886 subjects– Median cd4 count 290 cells/cm3 (IQR 130-440)– Median viral load 130K (47K-310K)– Follow up-median 19 mo (IQR 13-24mo)– Adherence defined as

• # refills obtained/# months on therapy over 1 year

– Outcome-viral load <500 c/ml

17

Low-Beer et al. JAIDS 2000

12%

24%

47%

64%

84%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

<70% 70-<80% 80-<90% 90-<95% >95%Pro

port

ion

Und

etec

tabl

e (V

L<50

0 c/

ml)

n=n= 232 232 37 37 51 51 6464 502 502 18

Issues with Refill Data• Variety of other approaches possible–Assessment of time to refill–Assessment of duration of gaps–Others

• Limitations–Unclear how they will operate on short term–For example, 3 months of follow-up allows

only for 2, 3, or 4 fills using Low-Beer method

19

Choice of Pharmacy Metric–Metric: number of days to obtain 4 refills (3 months)

• 90 days supply/# of days to obtain supply

• Time to event approach

• Allows for more variability over shorter (clinically relevant) interval

20

Time to 4 refills (3 Time to 4 refills (3 months)months)

Fourth fill

} } }First fill Second fill Third fill

First interval Second interval Third interval

Adherence metric: Σ intervals/(4th fill date-1st fill date)

21

VA Pharmacy Refill Study

• Specific aim–To compare validity of self-reported

measure and pharmacy refill measure of adherence to antiretroviral therapy in HIV

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VA Refill Study Design

• Observational Study (n=110) conducted in the Philadelphia VA HIV Clinic

• Outcomes– Change in HIV viral load from baseline to study date– HIV viral load undetectable or not (dichotomized)

• Exposures– Adherence measured via self-report (ACTG

measure)– Adherence measured using refill data (time to

obtaining 90 days supply)

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Setting/Study Patients

• Subjects on therapy at least 3 months

• Philadelphia VA Medical Center–Veterans obtain all HIV Rx here–Electronic pharmacy records–Mailed medications require telephone call

24

01

23

45

0 20 40 60 80 100 120 140 0 20 40 60 80 100 120 140

Self -reported measure Pharmacy-based measure

Change in Log Viral Load (c/ml) Fitted values

Cha

nge

in L

og V

iral

Loa

d (c

/ml)

/Fitt

ed v

alue

s

Percent Adherence

Entire cohort, N=11025

VA Pharmacy Study Results

• Spearman correlation coefficient (95% CI)• Adherence and change in viral load

Pharmacy refill = 0.22 (0.01 to 0.40)

Self-report = 0.10 (-0.08 to 0.32)

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VA Pharmacy Study Results

Change in plasma viral loadRank sum

test

Method Study group Adherence >85% Adherence <85% p value

Pharmacy Entire cohort N=572.4 log c/ml

(IQR 1.4 - 3.2)

N=531.5 log c/ml

(IQR 0.7 - 2.4)0.005

Self-report Entire cohort N=962.1 log c/ml

(IQR 1.1 - 3.0)

N=141.4 log c/ml (IQR 0.4 -1.9)

0.04

Pharmacy 100% by self-report

N=442.4 log c/ml

(IQR 1.4 - 3.4)

N=301.5 log c/ml

( IQR 0.8 - 2.4)0.03

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Conclusions of Refill Study• Time to refill is a valid adherence

measure–may perform better than self-report

• Generalizability outside of VA?

• Unclear function over shorter intervals (e.g., 1 or 2 months)

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Time to 4 refills (90 days)Time to 4 refills (90 days)

Fourth fill

} } }First fill Second fill Third fill

First interval Second interval Third interval

90d

60d

60d

30d

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Correlation of shorter interval adherence measures Correlation of shorter interval adherence measures and change in viral loadand change in viral load

Fourth fill

} } }First fill Second fill Third fill

First interval Second interval Third interval

0.250 (0.059-0.423)

0.150 (-0.045-0.334)

0.144 (-0.050-0.327)

0.229 (0.036-0.405)

0.184 (-0.007-0.362)

0.265 (0.078-0.434)

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Correlation of shorter interval adherence measures Correlation of shorter interval adherence measures and change in viral loadand change in viral load

Fourth fill

} } }First fill Second fill Third fill

First interval Second interval Third interval

0.250 (0.059-0.423)

0.150 (-0.045-0.334)

0.144 (-0.050-0.327)

0.229 (0.036-0.405)

0.184 (-0.007-0.362)

0.265 (0.078-0.434)

31

Conclusions regarding shorter interval measurements of refill adherence

• Shorter interval measurements of refill adherence are associated with virologic outcome.

• The “upstream” interval is the best predictor of outcome.

32

Summary

• Refill adherence is a valid method for measuring adherence.

• Refill adherence correlates with outcome.• Short interval measurements of refill adherence

are valid, but only if measured 60-90 days in advance of the point of interest.

• Clinical use of refill data to inform providers about medication adherence is evolving.

33