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Effectively measuring adherence to medications for systemic lupus erythematosus in a clinical setting.

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Arthritis & Rheumatism (Arthritis Care & Research)
Vol. 57, No. 6, August 15, 2007, pp. 1000 –1006
DOI 10.1002/art.22898
© 2007, American College of Rheumatology
ORIGINAL ARTICLE
Effectively Measuring Adherence to Medications
for Systemic Lupus Erythematosus in a Clinical
Setting
SRI KONERU,1 MICHAEL SHISHOV,2 AVIS WARE,1 YOLANDA FARHEY,1 ANNE-BARBARA MONGEY,1
T. BRENT GRAHAM,2 MURRAY H. PASSO,2 J. LAWRENCE HOUK,1 GLORIA C. HIGGINS,3AND
HERMINE I. BRUNNER2
Objective. To assess the reliability and concurrent validity of the Medication Adherence Self-report Inventory (MASRI)
when used in systemic lupus erythematosus (SLE), to investigate the predictive validity of the MASRI using pharmacy
refill information as the criterion standard, and to propose a sensible approach to the screening for nonadherence in a
clinical setting.
Methods. Adherence to 2 medications (hydroxychloroquine and prednisone) was measured in 55 patients using the
MASRI, pill counts, and physician ratings (MD scale). Adherence based on pharmacy refill information served as a
criterion standard with nonadherence defined as adherence rates <80%. To determine test–rest reliability of the MASRI,
20 patients completed the measure twice within a 2-week period.
Results. Using pharmacy information, 39% of the patients were nonadherent to prednisone and 51% to hydroxychloroquine. The MASRI had acceptable internal consistency (Cronbach’s ␣ 0.7) and good reliability. Irrespective of the drug
assessed, MASRI ratings were moderately correlated with patient adherence (pharmacy), supporting the concurrent
validity of the MASRI. The combination of adherence estimation by MD scale rating at <85% and by MASRI at <90% was
87% sensitive and 86% specific for identifying patients who were nonadherent to prednisone. These cutoff values also
appeared suitable for identifying nonadherence to hydroxychloroquine.
Conclusion. The MASRI is a reliable measure of adherence to medications in SLE. The measure has concurrent and
predictive validity. When combined with the MD scale, the MASRI appears to be a useful screening tool for nonadherence
in patients with SLE that could be suitable for clinical practice.
KEY WORDS. SLE; Adherence; Compliance; Lupus; Adults; Adolescents; MASRI.
Adherence to (or compliance with) medication regimens is
often defined as the extent to which patients take medications as prescribed by their health care providers (1). Rates
of adherence for individual patients are usually reported
as the percentage of the prescribed doses of medications
that are actually taken by the patients over a specified
period. Lack of adherence is a ubiquitous problem in the
management of chronic diseases, including systemic lupus
erythematosus (SLE) (1–3). Therefore, given the frequent
occurrence of nonadherence and its potential negative effects on patient prognosis (4,5), effective and easy-to-use
adherence measures are needed to identify patients at risk.
Despite the importance of adherence to the success of
medical interventions, there is no universally accepted
criterion standard for measuring medication adherence.
Various approaches to ascertain medication adherence are
Supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (grants P60-AR-47784, R03AR-049860, and U01-AR-51868) and the Columbus Medical
Research Foundation.
1
Sri Koneru, MD, Avis Ware, MD, Yolanda Farhey, MD,
Anne-Barbara Mongey, MD, J. Lawrence Houk, MD: University of Cincinnati Medical Center, Cincinnati, Ohio; 2Michael Shishov, MD, T. Brent Graham, MD, Murray H. Passo,
MD, Hermine I. Brunner, MD, MSc: Cincinnati Children’s
Hospital Medical Center, Cincinnati, Ohio; 3Gloria C. Hig-
gins, MD, PhD: Columbus Children’s Hospital, and Ohio
State University, Columbus.
Address correspondence to Hermine I. Brunner, MD,
MSc, Cincinnati Children’s Hospital Medical Center, University of Cincinnati, William Rowe Division of Rheumatology, E 4010, 3333 Burnet Avenue, Cincinnati, OH 452293039. E-mail: hermine.brunner@cchmc.org.
Submitted for publication July 13, 2006; accepted in revised form February 12, 2007.
INTRODUCTION
1000
Medication Adherence in SLE
currently in use but their implementation in daily clinical
practice appears difficult. For example, pill counts are
cumbersome, while electronic medication event-monitoring systems are costly; calculating adherence rates based
on pharmacy refill data is time intensive, and pharmacologic testing of the exposure to rheumatic medications is
often not available, making all of these adherence measures less suitable for use in routine clinical care. Physicians’ estimates of adherence, although readily available
in the clinic, are thought to be prone to inaccuracy (6,7).
We hypothesized that patient self-report may be an alternative feasible and useful approach to measuring adherence to medications in SLE. Self-report of medication adherence has been explored in the past. For example,
Morisky et al (8) published a generic Medication-Taking
Scale to predict blood pressure control, and more recently,
the disease-specific Compliance-Questionnaire-Rheumatology (CQR) was developed and validated (9). However,
neither the Medication-Taking Scale nor the CQR allow for
the determination of specific medication adherence rates.
Conversely, previous research suggests that the Medication Adherence Self-report Inventory (MASRI) is useful for
accurately measuring adherence to human immunodeficiency virus (HIV) medications in both clinic settings and
research (10). The MASRI is appealing for use in other
patient populations because it is concise and readily provides a numeric estimate of patients’ adherence rates (0 –
100%).
As an initial step toward the validation of the MASRI in
rheumatology at large, we assessed its usefulness in patients with SLE (3). The goals of our study were 1) to assess
the test–retest reliability and concurrent validity of the
MASRI when used in patients diagnosed with SLE, 2) to
assess the predictive validity of the MASRI using pharmacy refill information as the criterion standard, and 3) to
assess the usefulness of the MASRI alone or in combination with another measure of adherence to effectively
screen for drug nonadherence in a clinical setting.
PATIENTS AND METHODS
Patients. A convenience sample of patients with SLE (3)
was recruited from 4 rheumatology clinics affiliated with
the University of Cincinnati in Cincinnati, Ohio, and Ohio
State University in Columbus, Ohio. To be included in the
study, patients had to be age ⱖ16 years, have a disease
duration of at least 6 months, and be receiving medications
for SLE at the time of the study. Patients with a diagnosis
of neuropsychiatric SLE syndromes were excluded, as
were those with other chronic diseases that might impact
adherence as judged by the treating rheumatologist. The
protocol was approved by the respective institutional review board of each participating clinic, and all patients
signed informed consent documents.
Survey procedures and study visit. Dedicated research
personnel, rather than professionals participating in the
clinical care delivery, supervised the participants in the
completion of the study forms. The participants provided
information on the doses and types of medications recom-
1001
mended by their rheumatologists. This information was
compared with and supplemented with information available in the medical record. The study participants completed the MASRI independently and were assured that
their responses would not be shared with the medical
personnel involved in their SLE care. To assess the test–
retest reliability of the MASRI, the questionnaire was also
sent to the first 20 study participants 1 week after the
initial study interview via US mail. A prestamped envelope was enclosed to facilitate the return of the questionnaire. Reminder telephone calls were placed for questionnaires that were not returned within a 1-week period after
the expected receipt of the questionnaire.
Medication Adherence Self-report Inventory. The
MASRI is a 12-item questionnaire of self-reported medication adherence addressing the frequency (6 items, part A)
and the correct timing of medication intake (6 items, part
B) (10). Given that, unlike HIV therapy, the intake of medications at certain exact time intervals is an uncommon
demand for patients with SLE or patients with other rheumatic diseases, the MASRI part B was not completed by
the study participants. For analytical purposes, responses
of never or more than a month ago were grouped together.
Of note, only the visual analog scale (VAS) item of the
MASRI is used to determine a numeric estimate of the
adherence rate (0 –100%). The other items are added to
help patients develop this adherence estimate and are
possibly useful for identifying specific situations that interfere with medication adherence. Prior to the use of the
MASRI in this study, the questionnaire was piloted among
members of a local lupus support group.
Other measures of adherence to medications. Pharmacy refill. Adherence estimates based on pharmacy refill
data were considered the criterion standard for measuring
adherence, the rationale being that pharmacy refill data
provide longer-term information about patient adherence
and do not rely on the participants remembering to bring
medication supplies to the study visit (less bias) (11), and
that physician ratings are considered less accurate than
other methods of adherence measurement (6,7). Specifically, the participants provided contact information for the
pharmacies where they filled their prescriptions. These
pharmacies were contacted and information about the 4
most recent medication refills was obtained. Adherence
based on pharmacy refill was defined as the percentage of
prescribed doses taken and was calculated as follows:
(total number of medication doses dispensed/total number
of prescribed doses) ⫻ 100%. For example, a patient obtained 90 doses of medication with the last 3 refills and
120 doses of medication with the last 4 refills, but he or she
was still taking pills dispensed with the fourth refill supply. The number of days between the first refill date and
the fourth refill was 110 days. Thus, for the 110 days
between refills the patient had only 90 medication doses
and therefore his or her adherence would be 90/110 ⫻
100% ⫽ 82%.
Physician rating of patient adherence. The treating
rheumatologist provided estimates of the participant’s ad-
1002
herence to each medication separately on an 11-point ordinal scale anchored with 0% (none of the time) and 100%
(all the time) as the lower and upper bounds, respectively,
and spaces for check marks in 10% intervals (MD scale).
The scale was presented with the sentence stem “How
frequently do you think the patient is taking the medication as prescribed during the preceding month?”
Pill counts. Participants were instructed to bring their
current supply of medications prescribed for SLE to the
study visit. Besides the physician’s prescription instructions and the number of remaining medication doses, adherence rates considered the time interval between the
study visit and the medication refill dates.
Statistical analysis. Calculation of adherence rates. Adherence to medication was expressed as a percentage value
and defined as the ratio of the number of medication doses
taken (numerator) and the number of doses prescribed for
the time between the study visit and the refill date of the
medication (denominator). Thus, adherence rates are a
continuum where 0% means that the participant never
takes the medication and 100% means that the medication
is taken as prescribed at all times.
Definition of sufficient adherence and nonadherence.
For the purpose of the analysis, we categorized adherence
as follows: patients with adherence rates ⱖ80% were considered to be sufficiently adherent to the medication, and
those with adherence rates ⬍80% were considered to be
nonadherent to the medication. These cutoff values have
been used in the past but are, in essence, chosen arbitrarily
(9). Adherence rates and the presence of sufficient adherence or nonadherence, respectively, were measured for
prednisone and hydroxychloroquine separately because
previous research suggests that medication adherence may
differ between different drugs taken for SLE (3).
Reliability and concurrent validity of the MASRI. Internal consistency of the MASRI items was assessed by Cronbach’s alpha, with values ⱖ0.7 representing acceptable
internal consistency (12). Kappa statistics and intraclass
correlation coefficients (ICCs) for categorical data and interval data, respectively, were calculated to assess the
test–retest reliability of the MASRI. ICC and kappa values
were interpreted as follows: ⬍0.01 represented poor reliability, 0.01– 0.20 represented slight reliability, 0.21– 0.40
represented fair reliability, 0.41– 0.60 represented moderate reliability, 0.61– 0.80 represented substantial reliability, and 0.81–1 represented almost perfect reliability (13).
Spearman’s correlation coefficients (rsp) and ICCs were
used to assess the concurrent validity of the MASRI, comparing MASRI VAS estimates with adherence rates based
on pharmacy refill data (criterion standard), pill counts,
and physician global assessments (MD scale). Spearman’s
correlation coefficients were interpreted as follows: unrelated: rsp ⬍ 0.2; weak: 0.2 ⱕ rsp ⬍ 0.4; moderate: 0.4 ⱕ
rsp ⬍ 0.6; strong: rsp ⱖ 0.6.
Receiver operating characteristic curve analysis. Receiver operating characteristic (ROC) curve analysis was
performed (14), with adherence rates by pharmacy refill
data serving as the external standard. SAS proc logistic
and contingency table analyses (SAS Institute, Cary, NC)
Koneru et al
were used to determine the sensitivity and specificity of
the various measures of adherence as well as the most
appropriate cutoff values of the MASRI VAS that best
discriminated between adherent and nonadherent patients. Sensitivity (to identify nonadherence) of a measure
was calculated as follows: number of correctly identified
nonadherent patients divided by number of all nonadherent patients. Specificity of a measure (to identify nonadherence) was calculated as follows: number of correctly
identified adherent patients divided by number of all adherent patients. ROC curves were constructed, e.g., graphs
in which the x-axis depicts the values of (1 ⫺ specificity)
and the y-axis shows the sensitivity of the measure. We
repeated the analysis assessing the measurement properties of the MASRI when used in combination with other
measures of adherence used in this study (MD scale, pill
count).
RESULTS
Participants. Fifty-five patients (96% women) with a
mean ⫾ SD age of 31.7 ⫾ 14 years and mean ⫾ SD SLE
duration of 7.2 ⫾ 5.2 years participated in the study. Most
participants were white (n ⫽ 27 [49%]), 26 were African
American (47%), and 2 were Asian (4%). Forty-one patients were treated with prednisone and 37 with hydroxychloroquine. Twenty-three of the 55 patients were treated
with both hydroxychloroquine and prednisone.
Adherence estimates by pharmacy refill data. Nonadherence to prednisone, e.g., adherence of ⬍80% based on
pharmacy refill data, was common and occurred in 16
(39%) of 41 patients. Nonadherence to hydroxychloroquine was present in 19 (51%) of 37 patients. All patients
receiving prednisone completed MD scales and the
MASRI, but MASRI ratings were unavailable for 8 patients
treated with hydroxychloroquine. Only 28 patients
brought their medication supply to the study visit for the
pill count (Figure 1).
Irrespective of the medication assessed, adherence rates
based on the MD scale or the MASRI had a considerable
ceiling effect, and both scales were negatively skewed.
Using prednisone as an example, physicians assigned an
adherence rate of 100% to 16 (39%) of the 41 patients
(skewnessMD scale ⫽ ⫺1.97), whereas self-report (MASRI)
suggested that 20 (49%) of the 41 patients were fully
adherent to prednisone (skewnessMASRI ⫽ ⫺2.2). Conversely, pharmacy data supported that 100% adherence
was only present in 11 (27%) of the 41 patients (Figure 1).
Reliability of the MASRI. The internal consistency reliability of the MASRI was acceptable (Cronbach’s ␣ ⫽ 0.7)
with a minimum alpha coefficient between variables at
0.4, suggesting that none of the included items could be
easily removed to improve the scale. Information from 20
patients was available to assess the intrarater reliability of
the MASRI. The reliability of the MASRI was moderately
good, with a mean kappa value for the Likert scale items of
0.5 (item 1: ␬ ⫽ 0.8, item 2: ␬ ⫽ 0.3, items 3 and 5: ␬ ⫽ 0.5);
the test–retest reliability of the MASRI VAS was excellent
(ICC ⫽ 0.93).
Medication Adherence in SLE
1003
criterion standard of adherence (rsp ⱖ 0.55). Neither pill
counts nor the MD scale was as closely correlated with the
criterion standard as the MASRI (Table 1). There was
moderate agreement (ICC) between the MASRI and the
criterion standard (Table 2). Agreement between the
MASRI and the criterion standard was moderate for prednisone (ICC ⫽ 0.48) and somewhat lower for hydroxychloroquine (ICC ⫽ 0.39). Irrespective of the medication considered, none of the other adherence measures (pill count,
MD scale) was in higher agreement with the criterion
standard than the MASRI.
Predictive validity of the MASRI. MASRI adherence
rates ⱖ95% were 67% and 61% sensitive for identifying
patients who were nonadherent to prednisone and hydroxychloroquine, respectively. The specificity of the
MASRI for rates ⱖ95% was 68% for identifying prednisone nonadherence and 65% for hydroxychloroquine
nonadherence (Figure 2).
Figure 1. Relationship of adherence measurements for prednisone and hydroxychloroquine. Adherence rates based on all
examined measures are depicted in their relationship to the external standard (pharmacy refill data) for A, prednisone and B,
hydroxychloroquine. Patient self-report of adherence (Medication
Adherence Self-report Inventory [MASRI]) and physician ratings
of adherence (MD scale) showed a ceiling effect for both prednisone and hydroxychloroquine. VAS ⫽ visual analog scale.
Concurrent validity of the MASRI. Based on the MASRI
and irrespective of the type of medication assessed, patient
self-report was at least moderately correlated with the
Screening for nonadherence in the clinic: MD scale plus
MASRI. The combined consideration of adherence rates
using the MASRI and the MD scale resulted in a screening
tool that was superior to other combinations of adherence
measures completed in this study in discriminating adherent patients from nonadherent patients. For prednisone,
MD scale adherence rates ⱖ85% and MASRI rates ⱖ90%
were 87% sensitive and 86% specific for distinguishing
sufficiently adherent patients from those who were nonadherent. The presence of only 1 of these 2 criteria was
still highly specific (87%) but only 60% sensitive for identifying nonadherence. For hydroxychloroquine, these cutoff values were still 63% sensitive but were less specific
(57%) if both criteria were present (1 criterion: sensitivity
35%, specificity 100%) (Figure 3A). Estimates ⱖ80% for
both the MASRI and the MD scale would have been best
for identifying patients who were nonadherent to hydroxychloroquine (Figure 3B).
DISCUSSION
The MASRI is a reliable, valid, and concise self-report
measure of adherence to medications in patients with SLE.
Table 1. Correlation between adherence measure estimates*
MASRI
Prednisone
Pharmacy
MASRI
Pill counts
Hydroxychloroquine
Pharmacy
MASRI
Pill counts
Pill counts
Spearman’s
correlation
P
0.62
0.55
* MASRI ⫽ Medication Adherence Self-report Inventory.
† As measured by the 11-point physician rating scale.
Physician rating†
Spearman’s
correlation
P
Spearman’s
correlation
P
⬍ 0.001
0.20
0.14
0.38
0.53
0.39
0.26
0.17
0.02
0.11
0.43
0.002
0.35
0.15
0.09
0.58
0.28
0.15
0.32
0.10
0.42
0.13
1004
Koneru et al
Table 2. Intraclass correlation coefficients of various adherence measures*
Intraclass correlation coefficient†
Medication
MASRI
Pill count
Physician rating‡
Prednisone
Hydroxychloroquine
0.48
0.39
0.18
0.22
0.30
0.38
* MASRI ⫽ Medication Adherence Self-report Inventory.
† Compared with the adherence measured by pharmacy refill data (criterion standard).
‡ As measured by the 11-point physician rating scale.
Our results confirm a close relationship between the
MASRI and adherence rates estimated by pharmacy refill
data. This finding is in concordance with the findings of
previous studies, where the MASRI strongly correlated
with other measures of adherence rates including electronic medication event monitoring systems, pill counts,
pharmacy refill information, and biologic tests (15,16).
In contrast to unstructured approaches to obtaining patient-reported adherence, e.g., health care providers simply asking a patient “Are you taking your medicine?” (17),
the MASRI offers a structured approach to measuring adherence. The Likert scale items of the MASRI help the
patient more accurately judge monthly adherence on the
MASRI VAS. Besides being an aid to correctly estimating
adherence on the MASRI, the Likert scale items may be
useful to address specific problems with the adherence to
a particular medication regimen, such as difficulties with
taking medications more than once a day, or on weekends.
Therefore, different from unstructured approaches, structured patient self-report appears to provide adherence estimates that moderately to strongly correlate with pharmacy refill information, and the MASRI appears to be a
good predictor of the criterion standard in linear models
(see below).
The MASRI is not the only patient-completed measure
of adherence. One measure is the Medication-Taking Scale
(8), the usefulness of which has not been validated for
antirheumatic therapies, and exact adherence rates cannot
be calculated from its raw scores. Another recently validated self-report measure for patients with rheumatic diseases is the CQR. The CQR consists of 19 items, rated on
4-point Likert scales, where reversely scored CQR items
can be used to derive a CQR raw score that requires mathematical transformation into a discrete adherence rate between 0% and 100% (9). Although CQR cutoff values can
be defined that have moderate sensitivity (62%) and high
specificity (95%) for detecting nonadherence, an advantage of the MASRI may be that its adherence rates are good
statistically significant predictors of medication adherence
(prednisone: R2 ⫽ 46%, df ⫽ 38, F ⫽ 29.5, P ⬍ 0.0001;
hydroxychloroquine: R2 ⫽ 22%, df ⫽ 27, F ⫽ 7.24, P ⫽
0.01), whereas CQR summary scores are unrelated to pharmacy refill-based adherence rates. An added advantage of
the MASRI over the CQR may be that the former provides
adherence rates that can be instantly read from the MASRI
VAS, and no calculations or transformations of scores are
necessary, likely adding to the suitability of the MASRI for
clinic practice. Nonetheless, a more comprehensive validation of adherence self-report measures for rheumatology
is warranted to study benefits and shortfalls of the various
self-report tools that have been developed. Therefore, the
Figure 2. Receiver operating characteristic (ROC) curve for detecting nonadherence to A,
prednisone and B, hydroxychloroquine. ROC curves show the relationship of the sensitivity
and (1 ⫺ specificity) to identify nonadherent patients. Pharmacy refill information was used
to define nonadherence to medications (criterion standard), with sufficient adherence being
defined as an adherence rate ⱖ80%, while nonadherence was defined as an adherence rate
⬍80%. Adherence measures whose curves approach the upper left corner of the graph are
best for discriminating adherent from nonadherent patients.
Medication Adherence in SLE
1005
Figure 3. Receiver operating characteristic (ROC) curve of the Medication Adherence Self-report Inventory (MASRI) and physician (MD)
estimates of nonadherence to A, prednisone and B, hydroxychloroquine. ROC curves show the relationship of the sensitivity and (1 ⫺
specificity) to discriminate between adherent and nonadherent patients. Pharmacy refill information was used to define adherence and
nonadherence to medications (criterion standard), with sufficient adherence being defined as adherence rates ⱖ80% and nonadherence as
rates ⬍80%. Definitions whose curves approach the upper left corner of the graph are most suitable for discriminating adherent from
nonadherent patients. VAS ⫽ visual analog scale.
MASRI should be compared directly with the MedicationTaking Scale (8) and the CQR (9).
At present, adherence measurement in clinical practice
is likely sporadic at best. Occasionally used approaches for
detecting nonadherence are physician proxy ratings of patient adherence, pill counts, and adherence estimates
based on pharmacy refill information; the latter 2 methods
are relatively time intensive, with pill counts relying on
the patients to bring the medications to the clinic visit. Pill
counts in such selected subgroups of patients may confer
more optimistic estimates of adherence.
There is only limited information about the accuracy of
adherence estimates performed by rheumatologists (18).
However, when used as the sole measure of adherence,
ratings by other groups of physicians are insensitive and
nonspecific for estimating patient adherence (6,7,19).
Based on correlation analysis in this study, physician estimates were not as closely correlated with the criterion
standard as the MASRI, suggesting that patients’ self-report may provide somewhat more valuable information,
and based on ROC analysis rheumatologists’ adherence
ratings by themselves cannot be considered proficient
measures of patient adherence. Nonetheless, when combined with the MASRI, physician ratings appear to facilitate the identification of nonadherence and, in contrast to
performing pill counts and obtaining pharmacy refill information, the MASRI and the physician rating of adherence can be readily performed in clinics. When combined
with the MD scale, the MASRI was highly sensitive and
specific for identifying nonadherence among patients,
with the prediction of nonadherence to prednisone being
somewhat better than that of hydroxychloroquine.
For reasons that were not entirely clear, both the physicians and the patients themselves had more difficulty estimating adherence rates for hydroxychloroquine than for
prednisone. A possible explanation could be that, compared with prednisone, hydroxychloroquine has less immediate effects and side effects, decreasing the clues for
the physicians to detect nonadherence and making it more
difficult for the patients to perform adherence self-reports.
One limitation of the MASRI may be that, in its current
form, it does not allow the assessment of medication overuse. Two patients receiving prednisone in our study reported taking 50 –100% more prednisone than was prescribed, and based on our qualitative data 5 of the 41
patients treated with prednisone reported taking more
prednisone than prescribed on some days. Importantly,
overuse was not reported for any other SLE medication.
Therefore an adaptation of the MASRI VAS to allow reporting of medication overuse may even improve the usefulness of the MASRI, especially with respect to prednisone. However, even in its current version the MASRI
correlated well with pharmacy refill information for both
prednisone and hydroxychloroquine.
Additionally, estimates of a measure’s sensitivity and
specificity depend on the prevalence of the condition considered in the population, and are therefore prone to
change when the tool is used in other SLE cohorts with
more or less frequent adherence problems. However, the
prevalence of prednisone and hydroxychloroquine in the
1006
Koneru et al
study participants is similar to what has been reported in
some other rheumatology cohorts, adding to the validity of
our findings and likely supporting the usefulness of the
MASRI (20).
A limitation of our study may be that patients completed
the MASRI with the assurance that the results would not
be shared with the treating physician. This might have led
to more accurate self-reported adherence than if patients
expected that their rheumatologist would review the
MASRI responses. However, this notion is not supported
by previous studies using the MASRI in other patient
populations (21,22).
Based on this pilot study, patient self-report of medication adherence using the MASRI offers a reliable and valid
approach to measuring the extent to which patients follow
prescribed medication regimens. In combination with
physician-estimated adherence, the MASRI has the potential to be a useful measure of adherence suited for daily
clinical practice. The MASRI appears to be useful for estimating adherence to different types of medications, and
research in HIV suggests that the same holds true for
combinations of drugs. Additional research is required to
confirm the usefulness of the MASRI in larger populations
and its responsiveness to change over time. As is recommended by the American College of Rheumatology, multiple levels and ongoing validation are necessary prior to
the routine clinical use of the MASRI for measuring adherence to medications in patients with SLE (23).
7.
8.
9.
10.
11.
12.
13.
14.
15.
AUTHOR CONTRIBUTIONS
Dr. Brunner had full access to all of the data in the study and
takes responsibility for the integrity of the data and the accuracy
of the data analysis.
Study design. Koneru, Ware, Farhey, Brunner.
Acquisition of data. Koneru, Shishov, Ware, Farhey, Mongey,
Graham, Passo, Houk, Higgins.
Analysis and interpretation of data. Koneru, Shishov, Passo,
Houk, Brunner.
Manuscript preparation. Koneru, Graham, Passo, Houk, Higgins,
Brunner.
Statistical analysis. Shishov, Brunner.
16.
17.
18.
19.
REFERENCES
1. Haynes RB, McDonald HP, Garg AX. Helping patients follow
prescribed treatment: clinical applications. JAMA 2002;288:
2880 –3.
2. Hochberg MC. Updating the American College of Rheumatology revised criteria for the classification of systemic lupus
erythematosus [letter]. Arthritis Rheum 1997;40:1725.
3. Shishov M, Koneru S, Graham TB, Houk LJ, Mongey AB,
Passo M, et al. The Medication Adherence Self-Report Inventory (MASRI) can accurately estimate adherence with medications in systemic lupus erythematosus (SLE) [abstract]. Arthritis Rheum 2005;52 Suppl 9:S188.
4. Uribe AG, Alarcon GS, Sanchez ML, McGwin G Jr, Sandoval
R, Fessler BJ. Systemic lupus erythematosus in three ethnic
groups. XVIII. Factors predictive of poor compliance with
study visits. Arthritis Rheum 2004;51:258 – 63.
5. Rojas-Serrano J, Cardiel MH. Lupus patients in an emergency
unit: causes of consultation, hospitalization and outcome: a
cohort study. Lupus 2000;9:601– 6.
6. Wagner JH, Justice AC, Chesney M, Sinclair G, Weissman S,
20.
21.
22.
23.
Rodriguez-Barradas M, and the VACS 3 Project Team. Patientand provider-reported adherence: toward a clinically useful
approach to measuring antiretroviral adherence. J Clin Epidemiol 2001;54 Suppl 1:S91– 8.
Finney JW, Hook RJ, Friman PC, Rapoff MA, Christophersen
ER. The overestimation of adherence to pediatric medical
regimens. Child Health Care 1993;22:297–304.
Morisky DE, Green LW, Levine DM. Concurrent and predictive validity of a self-reported measure of medication adherence. Med Care 1986;24:67–74.
De Klerk E, van der Heijde D, Landewe R, van der Tempel H,
van der Linden S. The compliance-questionnaire-rheumatology compared with electronic medication event monitoring: a
validation study. J Rheumatol 2003;30:2469 –75.
Walsh JC, Mandalia S, Gazzard BG. Responses to a 1 month
self-report on adherence to antiretroviral therapy are consistent with electronic data and virological treatment outcome.
AIDS 2002;16:269 –77.
Choo PW, Rand CS, Inui TS, Lee ML, Cain E, CordeiroBreault M, et al. Validation of patient reports, automated
pharmacy records, and pill counts with electronic monitoring of adherence to antihypertensive therapy. Med Care
1999;37:846 –57.
Cronbach LJ. Essentials of psychological testing. 5th ed. New
York: HarperCollins; 1990.
Landis JR, Koch GG. The measurement of observer agreement
for categorical data. Biometrics 1977;33:159 –74.
Hanley JA, Negassa A, Edwardes MD, Forrester JE. Statistical analysis of correlated data using generalized estimating equations: an orientation. Am J Epidemiol 2003;157:
364 –75.
Hugen PW, Langebeek N, Burger DM, Zomer B, van Leusen R,
Schuurman R, et al. Assessment of adherence to HIV protease
inhibitors: comparison and combination of various methods,
including MEMS (electronic monitoring), patient and nurse
report, and therapeutic drug monitoring. J Acquir Immune
Defic Syndr 2002;30:324 –34.
Rapoff MA, Belmont JM, Lindsley CB, Olson NY. Electronically monitored adherence to medications by newly diagnosed patients with juvenile rheumatoid arthritis. Arthritis
Rheum 2005;53:905–10.
Stephenson BJ, Rowe BH, Haynes RB, Macharia WM, Leon G.
Is this patient taking the treatment as prescribed? JAMA 1993;
269:2779 – 81.
Deyo RA, Inui TS, Sullivan B. Noncompliance with arthritis
drugs: magnitude, correlates, and clinical implications.
J Rheumatol 1981;8:931– 6.
Liu H, Golin CE, Miller LG, Hays RD, Beck CK, Sanandaji S, et
al. A comparison study of multiple measures of adherence to
HIV protease inhibitors [published erratum appears in Ann
Intern Med 2002;136:175]. Ann Intern Med 2001;134:968 –77.
De Klerk E, van der Heijde D, Landewe R, van der Tempel H,
Urquhart J, van der Linden S. Patient compliance in rheumatoid arthritis, polymyalgia rheumatica, and gout [published
erratum appears in J Rheumatol 2003;30:423]. J Rheumatol
2003;30:44 –54.
Duong M, Piroth L, Grappin M, Forte F, Peytavin G, Buisson
M, et al. Evaluation of the Patient Medication Adherence
Questionnaire as a tool for self-reported adherence assessment in HIV-infected patients on antiretroviral regimens. HIV
Clin Trials 2001;2:128 –35.
Duong M, Piroth L, Peytavin G, Forte F, Kohli E, Grappin M,
et al. Value of patient self-report and plasma human immunodeficiency virus protease inhibitor level as markers of adherence to antiretroviral therapy: relationship to virologic
response. Clin Infect Dis 2001;33:386 –92.
Classification and Response Criteria Subcommittee of the
American College of Rheumatology Committee on Quality
Measures. Development of classification and response criteria
for rheumatic diseases. Arthritis Rheum 2006;55:348 –52.
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