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Predicting adherence to therapy in rheumatoid arthritis, psoriatic arthritis or ankylosing spondylitis: a large cross-sectional study


Smolen JS1, Gladman D2, McNeil HP3, Mease PJ4, Sieper J5, Hojnik M6, Nurwakagari P7, Weinman J8. RMD Open. 2019 Jan 11;5(1):e000585. doi: 10.1136/rmdopen-2017-000585. eCollection 2019.

Author Information

1 Division of Rheumatology, Department of Medicine III, Medical University of Vienna and Hietzing Hospital, Vienna, Austria.

2 Department of Medicine, Toronto Western Hospital, Toronto, Ontario, Canada.

3 Department of Clinical Medicine, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, New South Wales, Australia.

4 Department of Rheumatology, Swedish Medical Center and University of Washington, Seattle, Washington, USA.

5 Department of Rheumatology, Charité Universitätsmedizin Berlin, Berlin, Germany.

6 Global Medical Affairs Rheumatology, AbbVie s.r.o., Ljubljana, Slovenia.

7 Medical Department, AbbVie Deutschland GmbH & Co. KG, Wiesbaden, Germany.

8 Institute of Pharmaceutical Science, King's College London, London, UK.



This analysis explored the association of treatment adherence with beliefs about medication, patient demographic and disease characteristics and medication types in rheumatoid arthritis (RA), psoriatic arthritis (PsA) or ankylosing spondylitis (AS) to develop adherence prediction models.


The population was a subset from ALIGN, a multicountry, cross-sectional, self-administered survey study in adult patients (n=7328) with six immune-mediated inflammatory diseases who were routinely receiving systemic therapy. Instruments included Beliefs about Medicines Questionnaire (BMQ) and 4-item Morisky Medication Adherence Scale (MMAS-4©), which was used to define adherence.


A total of 3390 rheumatological patients were analysed (RA, n=1943; PsA, n=635; AS, n=812). Based on the strongest significant associations, the adherence prediction models included type of treatment, age, race (RA and AS) or disease duration (PsA) and medication beliefs (RA and PsA, BMQ-General Harm score; AS, BMQ-Specific Concerns score). The models had cross-validated areas under the receiver operating characteristic curve of 0.637 (RA), 0.641 (PsA) and 0.724 (AS). Predicted probabilities of full adherence (MMAS-4©=4) ranged from 5% to 96%. Adherence was highest for tumour necrosis factor inhibitors versus other treatments, older patients and those with low treatment harm beliefs or concerns. Adherence was higher in white patients with RA and AS and in patients with PsA with duration of disease <9 years.


For the first time, simple medication adherence prediction models for patients with RA, PsA and AS are available, which may help identify patients at high risk of non-adherence to systemic therapies.