J Neurol (2008) 255 [Suppl 6]:87–92
`DOI 10.1007/s00415-008-6016-8
`
`Thomas Klauer
`Uwe K. Zettl
`
`Compliance, adherence, and the treatment
`of multiple sclerosis
`
`■ Abstract With the availability of
`disease-modifying, immunomodu-
`
`Dr. T. Klauer (쾷)
`Medizinische Fakultät der Universität
` Rostock
`Klinik und Poliklinik für Psychosomatik
`und Psychotherapeutische Medizin
`Gehlsheimer Str. 20
`18147 Rostock, Germany
`E-Mail: thomas.klauer@med.uni-rostock.de
`Prof. Dr. U. K. Zettl
`Medizinische Fakultät der Universität
` Rostock
`Klinik und Poliklinik für Neurologie
`Gehlsheimer Str. 20
`18147 Rostock, Germany
`
`latory therapies (DMT) for multi-
`ple sclerosis (MS) and the first
`long-term studies, it became obvi-
`ous that problems of compliance to
`complex treatment regimens under
`chronic conditions would also ap-
`ply to these approaches. In a selec-
`tive overview, problems and find-
`ings of adherence research are
`depicted. Based on a discussion of
`basic concepts, issues of operation-
`ally defining and measuring adher-
`ence are outlined. Descriptive find-
`ings on adherence to DMTs and
`empirical predictors of nonadher-
`
`ence are then discussed. Referring
`to theoretical models of treatment
`motivation, selected problems (e. g.,
`indication) and strategies of pro-
`moting adherence are described.
`Finally, implications of modern
`concepts of the patient-therapist
`relationship for the issue of patient
`adherence are considered.
`
`■ Key words multiple sclerosis ·
`compliance · adherence ·
`immunomodulatory treatment ·
`counseling
`
`for further morbidity and mortality and as a waste of
`health care resources. Nevertheless, it is a frequent phe-
`nomenon with proportions from 12 % (HIV disease) up
`to 33 % (diabetes) of nonadherent patients in various di-
`agnostic groups with an average nonadherence rate of
`nearly 25 % [6]. This estimate from a meta-analysis is
`similar to findings on adherence to immunomodulatory
`treatment (disease-modifying therapy, DMT) of multi-
`ple sclerosis (MS). According to a recent review [12], em-
`pirically observed nonadherence rates in DMTs vary be-
`tween 6 % and 43 %. Differences in definitions and
`measures of adherence considerably contribute to these
`variations.
`
`Definition and assessment of (non-)adherence
`
`JON 6016
`
`Adherent behavior may constitute a difficult task for pa-
`tients especially in chronic and complex conditions. Ac-
`cording to Meichenbaum and Turk [14], this task com-
`prises six domains of behavior, i. e., (1) utilization and
`consequent maintenance of therapy, (2) to keep treat-
`
`Introduction
`
`Even highly potent medical treatments may be limited
`in their effectiveness by the degree to which patients
`continue to exactly follow the treatment procedure (e. g.,
`medication) over the entire treatment course (compli-
`ance). Recently, the term “adherence” has been preferred
`over the concept of compliance because of the authori-
`tative and paternalistic connotations of the latter. Ad-
`herence has been defined as “the extent to which a per-
`son’s behaviour – taking medication, following a diet,
`and/or executing lifestyle changes, corresponds with
`agreed recommendations from a health care provider”
`([30], p. 3). Frequently, more specific aspects of adher-
`ence like persistence (i. e., the time interval between the
`first application of a medicament and withdrawal from
`continuous application contrary to the health care pro-
`vider’s recommendation) and performance quality (i. e.,
`stability regarding dosation scheme and mode of appli-
`cation) are further distinguished [4].
`Nonadherence is usually seen as an unnecessary risk
`
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`88
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`ment and aftercare appointments, (3) to take drugs cor-
`rectly, (4) to actively change health lifestyles, (5) to do
`treatment-related “homework” and (6) to reduce risk
`behaviors (e. g., smoking).
`The more complex the task of treatment adherence
`presents for patients, the more difficult it is to distin-
`guish nonadherence from incomplete adherence. For re-
`search purposes, operationally defined criteria have
`been introduced (e. g., taking correctly 80 % of the med-
`ication or more; 33 % missed applications over one
`month [19, 28]). When comparing different medication
`schedules and preparations (e. g., in the immunomodu-
`latory treatment of MS; [29]), operational standard mea-
`sures of adherence also have to be developed.
`In contrast to complete adherence, nonadherent be-
`havior is a manifold phenomenon. Major types of non-
`adherence are (1) complete refusal of therapy, (2) refusal
`of specific treatment options and (3) arbitrary or unin-
`tended modification of prescriptions. Moreover, several
`subtypes can be distinguished which include intentional
`clandestine (“covert”) noncompliance, but also supple-
`mentation of medication by commercially available
`drugs as well as drug intake without an indication (“hy-
`percompliance”; [19]).
`A number of instruments has been developed to as-
`sess adherence, which are usually divided into the cate-
`gories of direct and indirect measures. The most fre-
`quently applied and, at the same time, most unreliable
`assessment approach, i. e., the patient self-report, is sub-
`sumed among the indirect approaches in which adher-
`ence is inferred from indicator variables. Even when
`compared to other indirect measures like, e. g., pill
`counts, prescriptions and pharmacy files, patients (as
`well as their physicians) tend to overestimate adherence
`so much that this procedure is widely seen as inappro-
`priate. Among the indirect measures, electronic registra-
`tion of medication consumption by Medical Event Mon-
`
`Table 1 Adherence to immunomodulatory treatment of MS in selected studies
`
`itoring systems (e. g., electronic pill-boxes) are preferred
`especially in naturalistic studies and have been devel-
`oped for a wide range of medication modalities in inter-
`nal medicine, neurology, and ophthalmology.
`In clinical studies, direct measures of adherence are
`indispensable in which medication intake is assessed in
`an unmediated way. This is accomplished either by di-
`rect surveillance of intake, which can only rarely be re-
`alized in practical care, or by verification of the active
`agent or its metabolites, but also of marker substances in
`the blood or urine. These approaches require sensitive
`biochemical detection methods in order to avoid false
`negative findings.
`
`Adherence to immunomodulatory treatment of MS
`
`Immunomodulators like interferon beta (IFNβ-) 1a,
`IFNβ-1b, and glatiramer acetate are central components
`of MS platform therapy which should reduce the devel-
`opment of new lesions in the central nervous system, the
`frequency of exacerbations, and both physical and cog-
`nitive impairment. The most severe demand that immu-
`nomodulatory treatment imposes upon patients is that
`it involves medication that must be injected highly fre-
`quent (every day, every other day, or once a week) over
`an extended period of time (months or even years) sub-
`cutaneously or intramuscularly. Benefits of DMTs will
`not be positively experienced by the patients, but should
`appear as reduced frequency of exacerbations. Instead,
`flu-like side effects including flushing, chest pain, palpi-
`tations and dyspnea are frequent and challenge the pa-
`tient's adherence.
`In empirical studies of DMT adherence (Table 1),
`these side-effects and perceived lack of treatment effi-
`cacy were most frequently mentioned as reasons for dis-
`continuation by patients [12]. As in adherence studies in
`
`Sample
`size
`
`Course
`of MS
`
`Type of study
`
`Time frame
`
`Nonadherence %
`
`Remarks
`
`12.9
`15.3 – 41.1
`39.3
`27
`21.2
`30.2
`14 (RRMS)
`23 (SPMS)
`13.5 (RRMS)
`30 (SPMS)
`12.9
`45.8
`
`Trained patients
`
`Trained patients
`
`Switchers included
`
`Study
`
`Mohr et al. [17]
`Milanese et al. [15]
`Ruggieri et al. [23]
`Tremlett & Oger [28]
`Fraser et al. [[8]
`Haas & Firzlaff [9]
`O'Rourke & Hutchinson [18]
`
`Year
`
`2001
`2003
`2003
`2003
`2004
`2005
`2005
`
` 101
`1481
` 122
` 844
` 108
` 308
` 394
`
`RR
`RR
`RR
`RR
`RR, SP
`RR
`RR, SP
`
`Prospective, telephone report
`Prospective
`Prospective
`Retrospective, hospital charts
`Prospective
`Prospective
`Retrospective, hospital charts
`
`6 months
`3 years
`5 years
`6 months
`6 months
`2 years
`3 years
`
`Rio et al. [22]
`
`2005
`
` 622
`
`RR, SP
`
`Retrospective
`
`Md = 47 months
`
`Turner et al. [29]
`Portaccio et al. [20]
`
`2007
`2008
`
` 90
` 225
`
`n.a.
`RR
`
`Prospective
`Retrospective
`
`6 months
`M = 4.2 years
`
`M mean; Md median; RR relapse-remitting; SP secondary-progressive
`
`MYLAN PHARMS. INC. EXHIBIT 1048 PAGE 2
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`89
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`other diagnostic groups, proportions of nonadherent
`patients vary within a broad range between nearly 13
`and nearly 46 % of patients, depending on type of study,
`follow-up interval, definition of nonadherence, course
`of MS, and immunomodulators. Results from pivotal
`clinical studies (which are not considered here) mostly
`yielded results below this range.
`While differences between the various immunomod-
`ulators are not consistent and confounded with type of
`study, adherence seems to be higher in patients with re-
`lapse-remitting (RR) than with secondary-progressive
`(SP) course [18, 22]. Most drop-outs seem to occur within
`the first two years of treatment [12]. Most studies con-
`verge in that the risk of nonadherence grows with higher
`extended disability scale scores (EDSS). Moreover, non-
`adherence rates are higher in studies from clinical prac-
`tice as compared to large-scale prospective studies.
`Besides selection biases, a reason for this observation
`might be that in clinical practice switches between im-
`munomodulatory drugs are common [18] and may have
`been erroneously categorized as cases of nonadherent
`behavior in some studies. Differences between studies
`may also result from differences in the amount of train-
`ing and information patients had received before enter-
`ing immunomodulatory treatment (e. g., [17]).
`
`Determinants of adherence
`
`Missing treatment effects or undesirable side effects em-
`pirically explain only medium amounts of variance in
`adherence. Besides characteristics of treatment, (1) dis-
`ease characteristics, (2) patient variables, (3) quality of
`the patient-therapist relationship, (4) treatment setting
`and (5) influences from the social environment can be
`distinguished as important determinants of adherent
`behavior [19].
`Among patient characteristics, informational defi-
`cits, motivational deficits, and psychological disorders
`have most frequently been discussed. Obviously, adher-
`ence is most strongly threatened by disorders that spe-
`cifically and directly interfere with medication applica-
`tion like, e. g. injection phobia in the immunomodulatory
`treatment of multiple sclerosis [17] or treatment of dia-
`betes. Depression represents a more general risk to ad-
`herent behavior.
`Informational deficits in the patients which can lead
`to problems like, e. g., instable intake contingencies, have
`long been regarded as a result of an inaccurate patient-
`physician communication. In many areas of medicine,
`attempts have been undertaken to optimize communi-
`cation and to place it on a more cooperative foundation
`(e. g., shared decision-making; [10]). In psychological
`approaches to subjective theories of illness [13], it is as-
`sumed that uncommunicated, dissenting lay concepts of
`patients lead to a selective encoding of illness-related in-
`
`formation and to biased information processing. Subse-
`quently, patients might avoid confronting therapists
`with their diverging ideas. In this process of developing
`nonadherence, risks of abandoning intake are frequently
`underestimated.
`Psychological models of adherence mostly refer to
`motivational factors like degree of suffering, lay etiology
`or treatment expectations [24]. Usually, it is assumed
`that higher levels of suffering and more positive expec-
`tations regarding treatment effectiveness should go
`along with greater adherence. However, the concept of
`treatment expectations is multidimensional: subjective
`probabilities of desired and undesired consequences of
`adherent and nonadherent behavior should similarly
`determine compliance to somatic as well as psychologi-
`cal treatment; these probabilities have been systemati-
`cally described within expectancy-values approaches
`(e. g., [19]).
`One of the first theoretical accounts for compliant be-
`havior was the Health Beliefs Model (HBM; [1]). Accord-
`ing to the HBM, the individual tendency to engage in
`preventive health behaviors as well as compliant behav-
`iors under treatment is influenced by four types of ex-
`pectations: (1) the perceived severity of an illness, (2)
`the perceived vulnerability to that illness, (3) the per-
`ceived benefits expected from a specific health behavior
`and (4) the perceived barriers to engage in a specific
`health behavior. Recently, the HBM has been applied to
`immunomodulatory treatment of MS [29] using one of
`the three beta interferon (IFNβ) preparations or glati-
`ramer acetate. Treatment adherence as well as satisfac-
`tion at the 2-, 4-, and 6-month follow-ups were consis-
`tently predicted only by perceived benefits but not by
`the other model variables. However, expectations re-
`garding treatment outcomes may also be unrealistically
`positive, and patients holding them are at risk to discon-
`tinue treatment because of frustration and disappoint-
`ment.
`Since treatment adherence over longer periods of
`time has turned out to be a dynamic and probably un-
`stable phenomenon, process or stage models of health
`behavior change have also been proposed to explain in-
`terindividual differences. In the Transtheoretical Model
`(TTM) of health behavior change [21] it is assumed that
`patients pass through a progressive sequence of stages
`of readiness for change. As defined in the model, these
`stages include (1) precontemplation (i. e., not thinking
`about changing behavior in the next six months), (2)
`contemplation (thinking about changing the behavior
`in the next six months but not in the next 30 days), (3)
`preparation (ready to change in the next 30 days), (4) ac-
`tion (changed fewer than six months ago) and (5) main-
`tenance (changed the behavior more than six months
`ago). Since empirical tests of the model challenged dis-
`tinctiveness of the stages as well as unidirectionality of
`the change process [7], criteria were reformulated less
`
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`

`
`90
`
`restrictively, and additional variables were integrated
`like, e. g., "pros" and "cons" of changing as well as per-
`ceived barriers. The TTM has been applied to the dis-
`continuation of immunomodulatory treatment of MS
`with IFNβ-1a and was found to correctly identify 82 %
`of the nonadherent and 81 % of the adherent patients to-
`gether with level of education and disability as predic-
`tors [2].
`Self-efficacy is another type of expectancy that has
`been frequently shown to predict a wide range health
`behaviors [25]. It is defined as the subjective probability
`to be able to perform a health-related behavior or, more
`specifically, concrete action in support of medical treat-
`ment. Self-efficacy expectations should be especially rel-
`evant in the "post-intentional" phase of treatment moti-
`vation when compliant behavior has to be maintained in
`the face of barriers and obstacles like, e. g., negative side
`effects [26]. Mohr et al. [17] found self-injection self-ef-
`ficacy before and during IFNβ-1a therapy to predict
`treatment adherence after six months. In a prospective
`study on glatiramer acetate [8], adherent and nonadher-
`ent patients significantly differed on the Multiple Scle-
`rosis Self-Efficacy Scale (MSSE; [27]).
`A comprehensive model of treatment adherence
`should not only integrate patient, therapist, illness and
`treatment factors but also exogenous influences espe-
`cially from the social environment. Social support from
`spouses and friends may contribute much to the adher-
`ent behavior of the patients: According to meta-analytic
`results [5], patients lacking instrumental social support
`(e. g., material aid, assistance in practical problem-solv-
`ing) bear a 3.6-fold higher risk of nonadherence. Thus,
`it might be useful to include patients' relatives in adher-
`ence-related interventions.
`
`Interventions to promote adherence
`
`Because determinants of nonadherence are manifold and
`heterogeneous, patients at risk should undergo detailed
`assessment along the above mentioned categories of vari-
`ables to ensure that adequate strategies of compliance
`promotion are assigned. For example, patient education
`focusing on illness-related information should not be ap-
`propriate to resolve motivational deficits which interfere
`with regular intake of medication. Following the identifi-
`cation of patients at risk by certain key features (e. g., neg-
`ative experiences with similar treatments; difficult social
`environment; [19]), a diagnostic sequence assessing defi-
`cits in illness-related knowledge (indication for informa-
`tion), deficits in practical skills (indication for education)
`and, finally, motivational deficits (indication for motiva-
`tional intervention) has been suggested [11]. More spe-
`cific diagnostic procedures may then be used to identify
`target variables for intervention in individual patients
`(e. g., unrealistic treatment expectations).
`
`While MS patients are often well equipped with in-
`formation and skills (e. g., by self-injection training),
`only few motivational interventions have been proposed
`for this group. To enhance treatment motivation and ad-
`herence, interventions have to be tailored to the specific
`deficits of the patients and to consider the more general
`aims and incentives patients are committed to in their
`lives as well as the stage of change patients are actually
`in. Group intervention approaches to promote adher-
`ence, thus, should be designed flexible as well as compre-
`hensive and involve informational, behavioral, and mo-
`tivational components.
`An initial aim of such interventions is to encourage
`patients to take responsibility for their treatment. For
`example, self-commitment to change is a central con-
`cept of motivational interviewing (MI), a counseling
`strategy which has been transferred from addiction
`therapy to many other areas of medicine and clinical
`psychology [16]. Basic principles of MI are cooperation,
`activation of intrinsic motivation, and autonomy. These
`principles are reflected in an empathetic style of coun-
`seling, active listening, abandonment of reasoning to
`avoid patient resistance and addressing the patients’
`ambivalence regarding treatment continuation. Specific
`strategies of MI are, e. g., enhancement of problem rec-
`ognition, the promotion of self-efficacy, and the config-
`uration of change plans with respect to time criteria.
`Some specific aspects of MI were integrated into a soft-
`ware-based telephone counseling intervention [3]; in a
`study with 366 patients, it could be shown that adher-
`ence to IFNβ treatment was remarkably higher in the in-
`tervention group (98.8 %) compared to standard care
`controls (91.3 %).
`
`Conclusions
`
`In many cases, treatment of chronic disease challenges
`the patients’ self-management skills and motivational
`resources by demanding medication intake, following a
`diet, and changing the individual lifestyle. This applies
`also to standard immunomodulatory therapies of mul-
`tiple sclerosis which require the careful maintenance of
`(self-)injection schedules and, sometimes, the tolerance
`of undesired side effects. As in other chronic conditions,
`a substantial proportion of patients does not adhere to
`treatment at least for some time.
`Nonadherence rates reported from studies with MS
`patients vary within a broad range between nearly 13
`and nearly 46 % of patients, depending on type of study,
`follow-up interval, definition of nonadherence, course
`of MS, and immunomodulators. Current evidence indi-
`cates that a progressive course of MS, higher disability,
`lower self-efficacy, lower motivation to change, and
`lower perceived benefits predict nonadherence to DMTs
`in multiple sclerosis. One of the few studies on adher-
`
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`91
`
`ence interventions in MS patients showed that tele-
`phone-based counseling using a motivational interview-
`ing strategy contributed to a reduction of discontinuation
`rates. Nevertheless, nonadherence remains a serious
`problem in the treatment of MS.
`Usually, nonadherence is regarded as a risk for pa-
`tient morbidity and mortality and as an unnecessary
`economical burden for the health care system. Nonad-
`herent behavior has mostly been attributed to deficits in
`cognitive or motivational characteristics of the patient,
`in the patient-therapist communication, in the treat-
`ment setting or in the social support networks of the pa-
`tients. However, in modern reformulations of the pa-
`tient-therapist relationship preferring strategies like
`empowerment and shared decision-making, the concept
`of nonadherence has also undergone a change of mean-
`ing [10]: From the perspective of the expert patient, who
`
`is well informed about the limitations of treatment ef-
`fectiveness, nonadherent behavior may well be the result
`of critical reflection of treatment options against the
`background of more general aspirations and aims in life.
`The heterogeneity of variations of (post-)intentional
`nonadherence suggests that the simple dichotomy of ad-
`herent and nonadherent patients might be too simple
`and not helpful in modern health care. Open communi-
`cation between patients and health-care providers as
`well as shared decision-making should help to “uncover”
`intentional nonadherence of the clandestine type and,
`thus, to make the treatment process more efficient with
`regard to medical and economical outcomes.
`
`■ Conflict of interest The authors have no conflict of interest to de-
`clare.
`
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