Abstract
Objectives
Medication adherence is a key determinant of treatment effectiveness in chronic inflammatory diseases but data in Behçet’s syndrome (BS) remain limited. This study evaluated medication adherence in a real-world cohort of patients with BS and explored demographic and clinical factors associated with reduced adherence.
Methods
We conducted a monocentric cross-sectional study including 125 patients with BS followed at a tertiary referral centre. Adherence was assessed using the validated 8-item Morisky Medication Adherence Scale (MMAS-8). Patients were classified as having high (score=8), intermediate (score 6–<8) or low adherence (score<6). Disease activity was evaluated using the Behçet’s Disease Current Activity Form and the Behçet’s Disease Activity Index. Associations between adherence and clinical variables were analysed using Spearman correlation and non-parametric tests.
Results
The mean MMAS-8 Score was 6.82±1.32. High adherence was observed in 29.6% of patients, intermediate adherence in 48.8% and low adherence in 21.6%. Lower adherence was more frequent among patients in the lower age quartiles. No significant associations were observed between adherence and sex, disease duration, disease activity indices or treatment class.
Conclusion
Medication adherence in BS appeared generally satisfactory, although a relevant proportion of patients reported suboptimal adherence. These findings confirm, in a BS-specific real-world setting, previously reported associations between age and medication adherence observed in chronic diseases. Routine adherence assessment may help identify patients at higher risk of poor treatment compliance and support personalised management strategies.
Keywords: Behcet Syndrome; Treatment; Rare Diseases; Outcome Assessment, Health Care
WHAT IS ALREADY KNOWN ON THIS TOPIC
Medication adherence is a major determinant of outcomes in chronic rheumatic diseases.
WHAT THIS STUDY ADDS
Lower medication adherence was more frequently observed among patients belonging to lower age quartiles.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
Routine adherence assessment may help identify patients requiring targeted adherence-support interventions.
Background
Behçet’s syndrome (BS) is a rare chronic multisystem inflammatory disorder characterised by a relapsing-remitting course and a heterogeneous clinical spectrum. Mucocutaneous manifestations such as oral and genital ulcers represent the clinical hallmark of the disease, while ocular, vascular, neurological and gastrointestinal involvement may lead to significant morbidity and, in severe cases, life-threatening complications.1,3 The complexity and variability of disease manifestations require long-term pharmacological management tailored to organ involvement and disease severity. Treatment strategies in BS frequently include prolonged use of immunomodulatory or immunosuppressive therapies aimed at controlling inflammation, preventing disease flares and reducing long-term organ damage.4 5 In this context, medication adherence represents a critical determinant of treatment effectiveness and long-term outcomes. Poor adherence has been consistently associated with increased disease activity, higher relapse rates and increased healthcare utilisation in chronic immune-mediated diseases. According to the WHO,6 adherence to long-term therapies in chronic conditions averages around 50% in developed countries, highlighting a major challenge for healthcare systems. Indeed, poor adherence is associated with increased disease activity, higher healthcare costs and worse long-term outcomes.
Reflecting its clinical relevance, the European Alliance of Associations for Rheumatology has developed points to consider for the prevention, screening, assessment and management of non-adherence in people with rheumatic and musculoskeletal diseases.7 Indeed, in rheumatic diseases, several factors may influence adherence to therapy, including patient-related characteristics, disease perception, treatment complexity and healthcare system factors. These determinants are particularly relevant in rare chronic diseases such as BS, where prolonged treatment regimens and fluctuating disease activity may influence patients’ behaviour towards therapy.8 9 Recent studies have highlighted that adherence in BS is a multifactorial phenomenon influenced not only by clinical variables but also by psychological, social and behavioural aspects.10 Despite the recognised importance of adherence in chronic inflammatory diseases, data specifically addressing medication adherence in BS remain limited. A cross-sectional survey conducted among Italian patients with BS identified heterogeneous adherence profiles and suggested that younger age, longer disease duration and psychological factors may influence treatment behaviour.11 However, most available studies rely on survey-based approaches exploring patients’ attitudes towards therapy rather than validated adherence instruments used in routine clinical practice.12 13 Therefore, real-world evidence assessing treatment adherence using validated tools in clinically characterised cohorts of patients with BS remains scarce. Better understanding adherence patterns and their clinical correlates may help identify patients at higher risk of poor adherence and inform strategies aimed at improving disease management. The aim of the present study was therefore to evaluate medication adherence in a real-world cohort of patients with BS followed at a tertiary referral centre, using the validated 8-item Morisky Medication Adherence Scale (MMAS-8), and to explore demographic and clinical factors associated with reduced adherence.
Methods
Study design and setting
We conducted a monocentric cross-sectional observational study including patients with BS followed at the Behçet Clinic of the Rheumatology Unit, Azienda Ospedaliero-Universitaria Pisana, a tertiary referral centre for systemic autoimmune diseases, between March 2025 and January 2026.
Study population
Adult patients (≥18 years of age) with a diagnosis of BS according to the International Classification Criteria for Behçet’s Disease14 were eligible for inclusion. A total of 125 patients followed at our Behçet Clinic were included in the analysis. Patients were recruited consecutively during scheduled outpatient visits at our Behçet Clinic; during the same visit, patients completed the MMAS-8 questionnaire and underwent routine clinical assessment, including disease activity evaluation and treatment review.
For each patient, demographic and clinical information were collected, including age, sex and disease duration (years since diagnosis). Clinical phenotype was characterised according to the pattern of organ involvement, including mucocutaneous, ocular, articular, vascular, neurological and gastrointestinal manifestations, either isolated or in combination. Information regarding ongoing pharmacological treatment at the time of evaluation was also recorded. Treatments were classified into major therapeutic categories including colchicine, conventional immunosuppressive agents (eg, azathioprine and cyclosporine), biologic therapies (mainly tumour necrosis factor (TNF) inhibitors) and other targeted therapies such as apremilast.
Assessment of medication adherence
Medication adherence was assessed using the MMAS-8, a validated self-reported questionnaire widely used for the evaluation of adherence in chronic diseases. The MMAS-8 was used under licence from the scale developer.
The MMAS-8 consists of seven dichotomous questions (yes/no) exploring common medication-taking behaviours and one final item with a Likert-type response assessing the frequency of difficulties in remembering medication intake. The total score ranges from 0 to 8, with higher scores indicating better adherence.
According to the standard scoring system, patients were classified into three adherence categories:
High adherence: score=8.
Intermediate adherence: score 6 to <8.
Low adherence: score<6.
Although self-reported questionnaires may be affected by social desirability bias, the MMAS-8 represents a practical and widely adopted tool for the assessment of adherence in routine clinical practice.
Assessment of disease activity
Disease activity was assessed during the same outpatient visit using validated clinical instruments for BS. The Behçet’s Disease Current Activity Form (BDCAF) was used to evaluate disease activity in the 4 weeks preceding the visit. Both the patient perspective and the clinician perspective of BDCAF were collected. In addition, the Behçet’s Disease Activity Index was recorded as an overall measure of disease activity.
Statistical analysis
Descriptive statistics were used to summarise the characteristics of the study population. Continuous variables were expressed as mean±SD or as median and IQR depending on the distribution of the data. Categorical variables were reported as absolute frequencies and percentages.
The distribution of medication adherence levels according to the MMAS-8 classification was analysed across the study population. The association between MMAS-8 Score (considered as a continuous variable) and quantitative variables such as age and disease duration was assessed using Spearman’s rank correlation coefficient. Comparisons between adherence groups were performed using non-parametric statistical tests due to the non-normal distribution of the variables. Continuous variables were compared using the Mann-Whitney U test or Kruskal-Wallis test, as appropriate. Categorical variables were analysed using the χ² test or Fisher’s exact test. In addition, patients were dichotomised according to adherence status using a predefined cut-off (MMAS-8 ≥6 indicating adequate adherence and MMAS-8 <6 indicating low adherence) to explore differences in demographic and clinical characteristics between adherent and non-adherent patients.
Additional exploratory analyses were performed by stratifying patients according to age quartiles and disease activity quartiles, including BDCAF patient perspective, BDCAF clinician perspective and Behçet Disease Activity Index. The distribution of MMAS-8 adherence categories across quartiles was compared using χ² or Fisher’s exact test, as appropriate. Furthermore, exploratory subgroup analyses were performed among patients receiving colchicine and anti-TNF therapies.
Statistical significance was defined as a two-sided p value<0.05. All analyses were performed using standard statistical software.
Results
Patient characteristics
A total of 125 patients with BS followed at the tertiary referral Behçet Clinic of the Rheumatology Unit in Pisa were included in the study. The mean age of the cohort was 45.4±12.6 years, and the majority of patients were female (68%, n=85), while 32% (n=40) were male. The median disease duration was 11 years (IQR 8–15). The cohort included patients with heterogeneous clinical phenotypes, including mucocutaneous, ocular, articular, vascular, neurological and gastrointestinal involvement, either isolated or in combination. The distribution of organ involvement across adherence categories is reported in table 1.
Table 1. Comparison of demographic and clinical characteristics across the three 8-item Morisky Medication Adherence Scale (MMAS-8) adherence categories.
| Variable | High adherence (MMAS-8=8) n=37 |
Intermediate adherence (MMAS-8=6 to <8) n=61 |
Low adherence (MMAS-8<6) n=27 |
P value |
|---|---|---|---|---|
| Age, years (mean±SD) | 47.2±11.7 | 47.1±13.3 | 38.9±10.3 | 0.01 |
| Female sex, n (%) | 25 (67.6%) | 40 (65.6%) | 20 (74.1%) | ns |
| Disease duration, years median (IQR) | 12 (8–16) | 11 (8–14) | 11 (8–14) | ns |
| BDCAF, patient perspective median (IQR) | 1 (0–3) | 2 (1–4) | 1 (0–2) | ns |
| BDCAF, clinician perspective median (IQR) | 1 (0–2) | 2 (1–3) | 1 (0–2) | ns |
| Behçet Disease Activity Index, median (IQR) | 0 (0–2) | 1 (0–3) | 0 (0–2) | ns |
| Mucocutaneous involvement, n (%) | 29 (78.4%) | 50 (82.0%) | 21 (77.8%) | ns |
| Ocular involvement, n (%) | 7 (18.9%) | 12 (19.7%) | 4 (14.8%) | ns |
| Articular involvement, n (%) | 10 (27.0%) | 18 (29.5%) | 7 (25.9%) | ns |
| Vascular involvement, n (%) | 3 (8.1%) | 5 (8.2%) | 2 (7.4%) | ns |
| Neurological involvement, n (%) | 2 (5.4%) | 3 (4.9%) | 1 (3.7%) | ns |
| Gastrointestinal involvement, n (%) | 1 (2.7%) | 2 (3.3%) | 1 (3.7%) | ns |
| Colchicine use, n (%) | 22 (59.5%) | 32 (52.5%) | 17 (63.0%) | ns |
| Anti-TNF therapy, n (%) | 10 (27.0%) | 17 (27.9%) | 7 (25.9%) | ns |
ns indicates not statistically significant (p≥0.05).
BDCAF, Behçet’s Disease Current Activity Form.
Current treatments
Information regarding ongoing therapy was available for all 125 patients. As patients could receive more than one medication simultaneously, treatments were not mutually exclusive. The distribution of ongoing therapies for BS is reported in table 2. No statistically significant differences in medication adherence were observed across the different therapeutic classes.
Table 2. Ongoing pharmacological treatments for BS in the study population (n=125).
| Therapy | n (%) |
|---|---|
| Colchicine | 71 (56.8) |
| Anti-TNF agents | 34 (27.2) |
| Azathioprine | 24 (19.2) |
| Apremilast | 6 (4.8) |
| Cyclosporine | 3 (2.4) |
Patients could receive more than one treatment.
Levels of medication adherence
The mean MMAS-8 Score in the overall cohort was 6.82±1.32, with a median score of 7 (IQR 6–8). Based on the MMAS-8 classification, 37 patients (29.6%) showed high adherence, 61 (48.8%) intermediate adherence and 27 (21.6%) low adherence (table 3). Exploratory analyses stratified by age quartiles confirmed that lower adherence was more frequent among patients belonging to the lower age quartiles, supporting the association observed between age and MMAS-8 Score in the overall cohort (online supplemental table 1).
Table 3. Distribution of medication adherence according to the 8-item Morisky Medication Adherence Scale (MMAS-8).
| Adherence category | n (%) |
|---|---|
| High adherence (MMAS-8=8) | 37 (29.6) |
| Intermediate adherence (MMAS-8=6 to <8) | 61 (48.8) |
| Low adherence (MMAS-8<6) | 27 (21.6) |
Factors associated with medication adherence
Correlation analysis showed a significant positive association between age and MMAS-8 Score (Spearman rho=0.225, p=0.012), indicating that patients who were relatively younger within this cohort tended to have lower adherence levels. Analysis across the original three MMAS-8 adherence categories confirmed age as the main variable associated with adherence status, whereas no significant differences emerged for disease duration, disease activity indices, organ involvement or treatment class (table 1). No significant trend towards lower adherence with increasing disease activity was observed across disease activity quartiles, including BDCAF patient perspective, BDCAF clinician perspective and Behçet Disease Activity Index (online supplemental table 2).
Finally, exploratory subgroup analyses among colchicine-treated patients and anti-TNF-treated patients did not identify significant differences in adherence distribution according to treatment subgroup, although these analyses were limited by sample size.
Discussion
In this real-world study conducted in a tertiary referral centre, we evaluated medication adherence in a well-characterised cohort of patients with BS using the validated MMAS-8. Overall, adherence levels in our cohort were relatively high, with nearly 80% of patients classified as having high or intermediate adherence. However, a clinically meaningful proportion of patients (approximately one in five) exhibited low adherence, highlighting that suboptimal treatment behaviour remains a relevant issue even in specialised care settings. These findings are consistent with previous evidence from chronic autoimmune diseases, where adherence is frequently suboptimal despite close clinical follow-up. In line with prior studies,11 15 our results support the notion that adherence should not be assumed even in tertiary centres and requires systematic assessment as part of routine care.
The most relevant finding of our study is the significant association between relatively younger age and lower adherence levels. Age was the only variable significantly correlated with MMAS-8 scores, suggesting that patients who were relatively younger within this cohort represented a subgroup at higher risk of suboptimal adherence. The association between relatively younger age and lower adherence is not novel across chronic diseases; however, BS-specific evidence remains limited. Therefore, our findings should be interpreted as disease-specific confirmation derived from a clinically characterised real-world cohort assessed with a validated adherence instrument. This observation is in line with previous reports in BS and other chronic rheumatic diseases, where younger individuals consistently show lower adherence and higher rates of treatment discontinuation.11 Several mechanisms may underlie this association. Younger patients may perceive their disease as less severe, may prioritise social and professional commitments or may experience greater difficulty integrating long-term pharmacological regimens into daily life. These behavioural and psychosocial factors likely play a central role and should be specifically addressed in clinical practice.
Interestingly, in our cohort no significant associations were observed between adherence and sex or disease duration. The lack of correlation with disease duration suggests that longer experience with the disease does not necessarily translate into improved adherence. On the contrary, it is possible that some patients develop a form of ‘treatment fatigue’ over time, particularly in chronic conditions requiring prolonged therapy.
Another relevant observation is the absence of a significant relationship between medication adherence and disease activity indices. Patients with low adherence did not show higher disease activity compared with adherent patients according to BDCAF or the Behçet’s Disease Activity Index. Several explanations may account for this finding. First, the cross-sectional design of the study does not allow the evaluation of the long-term impact of adherence behaviour on disease outcomes. The consequences of suboptimal adherence may become evident only over longer periods, particularly in diseases characterised by a relapsing–remitting course such as BS. Second, disease activity was assessed at a single time point and may therefore not fully capture the cumulative effect of irregular treatment intake. We also did not observe differences in adherence across different therapeutic classes. This suggests that treatment adherence in BS may be influenced more strongly by patient-related behavioural factors than by the specific pharmacological regimen. Given the heterogeneity of treatment strategies in BS, which may include colchicine, conventional immunosuppressive agents and biologic therapies, understanding the determinants of adherence beyond pharmacological factors is essential for optimising disease management.
The results of our study should also be interpreted in light of the broader concept of patient empowerment in chronic diseases. Increasing evidence suggests that adherence is strongly influenced by patients’ perception of their disease, their understanding of treatment goals and the quality of communication with healthcare professionals. Recent initiatives promoted by the International Society for Behçet’s Disease have emphasised the importance of patient education, shared decision-making and empowerment strategies to improve treatment adherence and overall disease management.10
From a clinical perspective, our findings emphasise the importance of systematically assessing medication adherence in patients with BS. Simple and validated tools such as the MMAS-8 Questionnaire can be easily implemented in routine practice and may facilitate early identification of patients at higher risk of poor adherence. In particular, younger patients may represent a priority target for tailored adherence-support interventions. Strategies aimed at improving adherence may include structured patient education, shared decision-making approaches, behavioural interventions and the use of digital health tools. Integrating adherence assessment into routine follow-up may therefore represent a key step towards more personalised and effective management strategies in BS.16,20
This study has several limitations. First, its monocentric design may limit the generalisability of the findings. Second, adherence was assessed exclusively through a self-reported instrument, which may be affected by social desirability and recall bias and may therefore overestimate actual adherence. Objective measures such as pharmacy refill data, electronic monitoring systems or drug-level assessment were not available. Third, the relatively small number of patients with low adherence limited the possibility of performing adequately powered multivariable analyses; therefore, independent predictors of poor adherence could not be established. Information regarding the total number of medications, including therapies prescribed for comorbid conditions, was not systematically collected; therefore, the potential impact of treatment burden and polypharmacy on medication adherence could not be evaluated. Furthermore, longitudinal data regarding flare frequency, remission status and cumulative disease activity were not systematically collected, preventing assessment of their potential relationship with medication adherence. Finally, the cross-sectional design precludes causal inference and longitudinal assessment of adherence behaviour over time, particularly in a relapsing-remitting disease such as BS. Despite these limitations, our study provides real-world data derived from a clinically characterised cohort of patients with BS assessed using a validated adherence tool in a routine tertiary-care setting, addressing a relevant gap in the current literature. Taken together, these findings highlight the importance of systematically assessing medication adherence in patients with BS during routine clinical care. Simple and validated tools such as the MMAS-8 may facilitate the identification of patients at higher risk of poor adherence, particularly among younger individuals. Integrating adherence assessment into routine follow-up may represent an important step towards more personalised management strategies in BS.
In conclusion, medication adherence in BS appears overall satisfactory in a tertiary care setting; however, a substantial proportion of patients exhibit suboptimal adherence. Patients who were relatively younger within this cohort emerged as the main factor associated with lower adherence, identifying a subgroup that may benefit from targeted interventions. Routine assessment of adherence, combined with tailored patient-centred strategies, may represent a key component of optimising long-term disease management in BS. Future studies should explore longitudinal adherence patterns and incorporate qualitative patient-based approaches to better understand the determinants of non-adherence and inform targeted interventions.
Supplementary material
Footnotes
Funding: The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Provenance and peer review: Not commissioned; externally peer reviewed.
Patient consent for publication: Consent obtained directly from patient(s).
Ethics approval: This study involves human participants. The study was conducted in accordance with the Declaration of Helsinki and received approval from the Tuscany Regional Ethics Committee, protocol code n. 122/2024, approved on 09 July 2024. Participants gave informed consent to participate in the study before taking part.
Data availability statement
All data relevant to the study are included in the article or uploaded as supplementary information.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
All data relevant to the study are included in the article or uploaded as supplementary information.