To identify clinical features that predict the risk of meeting difficult-to-treat (D2T) rheumatoid arthritis (RA) definition in advance. This retrospective analysis included RA patients from the ATTRA registry who initiated biologic (b-) or targeted synthetic (ts-) disease-modifying anti-rheumatic drugs (DMARDs) between 2002 and 2023. Patients with D2T RA met the EULAR criteria, while controls achieved sustained remission, defined as a Simple Disease Activity Index (SDAI) < 3.3 and a Swollen Joint Count (SJC) ≤ 1, maintained across two consecutive visits 12 weeks apart. Patients were assessed at baseline and at one and two years before fulfilling the D2T RA definition. Predictive models were developed using machine learning techniques (lasso and ridge logistic regression, support vector machines, random forests, and XGBoost). Shapley additive explanation (SHAP) values were used to assess the contribution of individual variables to model predictions. Among 8,543 RA patients, 641 met the criteria for D2T RA, while 1,825 achieved remission. The machine learning models demonstrated an accuracy range of 0.606-0.747, with an area under the receiver operating characteristic curve (AUC) of 0.656-0.832 for predicting D2T RA. SHAP analysis highlighted key predictive variables, including disease activity measures (DAS28-ESR, CDAI, CRP), patient-reported outcomes (HAQ), and the duration of b/tsDMARD treatment. We identified clinical features predictive of D2T RA at baseline and up to one year before meeting the formal criteria. These findings provide valuable insights into early indicators of D2T RA progression and support the importance of earlier recognition and timely therapeutic intervention to improve long-term patient outcomes.

• Keywords
• Difficult-to-treat rheumatoid arthritis, Explainable artificial intelligence, Machine learning, Real-world data,
• MeSH
• Antirheumatic Agents * therapeutic use   MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Registries MeSH
• Retrospective Studies MeSH
• Arthritis, Rheumatoid * drug therapy   diagnosis   MeSH
• Aged MeSH
• Machine Learning * MeSH
• Severity of Illness Index MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Antirheumatic Agents * MeSH

OBJECTIVE: To develop evidence-based European Alliance of Associations for Rheumatology (EULAR) points to consider (PtCs) for the management of difficult-to-treat rheumatoid arthritis (D2T RA). METHODS: An EULAR Task Force was established comprising 34 individuals: 26 rheumatologists, patient partners and rheumatology experienced health professionals. Two systematic literature reviews addressed clinical questions around diagnostic challenges, and pharmacological and non-pharmacological therapeutic strategies in D2T RA. PtCs were formulated based on the identified evidence and expert opinion. Strength of recommendations (SoR, scale A-D: A typically consistent level 1 studies and D level 5 evidence or inconsistent studies) and level of agreement (LoA, scale 0-10: 0 completely disagree and 10 completely agree) of the PtCs were determined by the Task Force members. RESULTS: Two overarching principles and 11 PtCs were defined concerning diagnostic confirmation of RA, evaluation of inflammatory disease activity, pharmacological and non-pharmacological interventions, treatment adherence, functional disability, pain, fatigue, goal setting and self-efficacy and the impact of comorbidities. The SoR varied from level C to level D. The mean LoA with the overarching principles and PtCs was generally high (8.4-9.6). CONCLUSIONS: These PtCs for D2T RA can serve as a clinical roadmap to support healthcare professionals and patients to deliver holistic management and more personalised pharmacological and non-pharmacological therapeutic strategies. High-quality evidence was scarce. A research agenda was created to guide future research.

• Keywords
• arthritis, fibromyalgia, inflammation, rheumatoid, ultrasonography,
• MeSH
• Medication Adherence MeSH
• Antirheumatic Agents administration & dosage   therapeutic use   MeSH
• Exercise MeSH
• Hepatitis B complications   drug therapy   MeSH
• Hepatitis C complications   drug therapy   MeSH
• Cognitive Behavioral Therapy MeSH
• Comorbidity MeSH
• Humans MeSH
• Arthritis, Rheumatoid complications   diagnosis   drug therapy   therapy   MeSH
• Symptom Assessment MeSH
• Patient Education as Topic MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Practice Guideline MeSH
• Names of Substances
• Antirheumatic Agents MeSH