Introduction: There is a need for tools that are easy to use in clinical practice supporting decision making upon treatment in early rheumatoid arthritis (RA). Aim: The aim was to identify components of prognosticators in early RA and to identify individual patients with a poor prognosis as early as possible.

Methods: Two cohorts from the Swedish TIRA project including 320+408 patients with recent onset RA were included in the study. Disease activity was measured by C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and the 28-joint count disease activity score (DAS-28), and by the physicians’ global assessment of disease activity (PGA). Disability was assessed as activity limitation by the Swedish version of the Health Assessment Questionnaire (HAQ) and impairment was reported by pain on a visual analogue scale of 0–100 mm. Serological markers were rheumatoid factor (RF) and anti-CCP. RF was measured at the time for diagnosis, and anti-CCP at the time of diagnosis or at one or some of the follow-ups. If at least one anti-CCP test was positive, the patient was judged to be anti-CCP-positive. Assuming different clinical practice in the different cohorts, two different treatment strategies were assumed based on clinical practice in real-world settings. Principal Component Analysis and Multiple Linear Regression Analysis were used to identify prognosticators. Prediction rules were identified by data-driven approach, controlling for different treatment strategies.

Results: Progression of disease and disability measures and inflammation measures the first three months after inclusion predicted a considerable part of DAS-28 at the 1-year follow-up. Serological markers had a larger explanatory power for men than for women. Anti-CCP was a significant predictor for men, but not for women. Two versions of rules, one for women and one for men, predicting good or poor prognosis at one year after inclusion were produced by using measures of disability (Health Assessment Questionnaire), DAS-28, relative change in DAS-28 during first three months, sex, and test of anti-CCP. The rules demanded high prognostic specificity but the prognostic sensitivity was moderate.

Conclusion: A considerable part of DAS-28 at one year after inclusion could be explained by the first 3 months’ progression of disease, disability and inflammation. Anti-CCP was predictive for men but not for women, and needs further investigation. A decision tree predicting poor prognosis among individual early RA-patients showed high specificity and moderate sensitivity on a validationcohort. The medical informatics approach used, controlling for different treatment strategies, yields promising results and further studies will control for more specific differences in treatment strategies, e.g. different DMARDs initiated.

Identification of prognostic subgroups is of key clinical interest at the early stages of chronic disease. The aim of this study is to examine whether representation of physicians' expert knowledge in a simple heuristic model can improve data mining methods in prognostic assessments of patients with rheumatoid arthritis (RA). Five rheumatology consultants' experiences of clinical data patterns among RA patients, as distinguished from healthy reference populations, were formally represented in a simple heuristic model. The model was used in K-mean-clustering to determine prognostic subgroups. Cross-sectional validation using physician's global assessment scores indicated that the simple heuristic model performed better than crude data made in identification of prognostic subgroups of RA patients. A simple heuristic model of experts' knowledge was found useful for semi-automatic data mining in the chronic disease setting. Further studies using categorical baseline data and prospective outcome variables are warranted and will be examined in the Swedish TIRA-program.

Objective: To study whether there are differences between women and men, with regard to the reported level of fatigue, and to explore the strength of the relations between fatigue and disease activity, pain, sleep disturbance, mental health, and activity limitation in early rheumatoid arthritis, and also to explore the consistency of such findings.

Design: Analyses and comparisons of cross-sectional data.

Subjects. 276 patients, 191 women and 85 men, with early rheumatoid arthritis were included.

Method: Patients were examined with respect to 28-joint count disease activity score, and disability variables reflecting pain, sleep disturbance, fatigue, mental health, and activity limitation, at follow-ups at one, two and three years after diagnosis.

Results: Women reported somewhat more fatigue than men. Fatigue was closely and rather consistently related to disease activity, pain and activity limitation, and also to mental health and sleep disturbance.

Conclusion: Although this study does not permit conclusions about causal directions, statistical relationships may be related to clinical conceptions about causation: When disease activity can be significantly reduced by pharmacological treatment, this may have a positive effect on fatigue. Specific treatment with respect to the mentioned disability aspects that are related to fatigue is also a clinically reasonable strategy.

The aim of this study was to identify the social and organizational requirements for a decision support system (DSS) to be implemented in a clinical rheumatology setting, utilizing data-mining techniques. Field observations and focus group interviews were used for data collection. The decision-making was found to be situated, patient-focused, and long-term in nature. At the same time, the main part of peer-to-peer communication was informal. Patient records were involved in almost every decision. The conclusion is that the main challenges, when introducing a DSS at a rheumatology unit, are adapting the system to informal communication structures and integrating it with patient records. Considering incentive structures, understanding workflow and incorporating awareness are relevant issues when addressing these issues in future studies.