OA17 Factors associated with biologics treatment response at 1 year amongst patients with psoriatic arthritis - results from the British Society of Rheumatology Psoriatic Arthritis Register (BSR-PsA)
Bibliographic record
Abstract
Abstract Background/Aims Biologic and targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) can significantly improve outcomes in psoriatic arthritis (PsA), but not all patients respond. Our aim was to characterise patients most likely to respond to b/tsDMARDs. Methods Participants were members of the BSR-PsA register (August 2024) commencing any b/tsDMARD that they had not previously received. Data was gathered from medical records, plus participant questionnaires. Univariable logistic regression was used to estimate the odds of treatment response at 12-months - defined using the PsARC criteria, a composite outcome comprising tender/swollen joints, and patient/physician global assessment. Factors associated with response at p ≤ 0.20 were then offered to a stepwise multivariable model to identify independent predictors. Results At baseline, 684 patients were commencing b/tsDMARDs: median age 52yrs (inter-quartile range [IQR] 45-61), 34% male, 55% had BMI>30, another 27% BMI 25-30, and 61% had ≥1 comorbidity. Median disease duration was 7yrs (3-14), Physician Global Assessment 4.8 (2.4-6.5), and swollen and tender joints 5 (3-9) and 12 (7-25), respectively. 12-month PsARC data was available from 164 participants, of whom 56 (34%) met the response criteria. Employed participants were more likely to satisfy PsARC criteria than those not employed (odds ratio: 2.97; 95%CI: 1.35-6.51) as were those with psoriasis (2.11; 0.74-6.05), nail pitting (1.72; 0.85-3.46) erosions (2.07; 0.77-5.58) and better physical health (1.12; 0.98-1.28 per unit on the PROMIS global physical health score). Factors associated with decreased odds of response included higher pain (0.85; 0.71-1.03), disability (Health Assessment Questionnaire) (0.66; 0.40-1.11), and anxiety (PROMIS anxiety scale) (0.94; 0.86-1.02), all shown as odds ratio per 1 unit increase, and features of fibromyalgia (0.82; 0.62-1.08 per five unit increase in Polysymptomatic Distress Scale). Four independent predictors of response were identified (Table 1). Model specificity was good: 75% of patients who failed to respond to treatment were correctly identified. Conclusion In this real-world cohort, the proportion of patients meeting response criteria was low. Future work should attempt to replicate our findings with other outcomes (e.g., drug survival). Meanwhile, we have identified four factors that, in combination, predict patients unlikely to respond to therapy in whom additional approaches to management should be considered. Disclosure G.T. Jones: Honoraria; UCB. Member of speakers’ bureau; Janssen. Grants/research support; AbbVie, GSK, Pfizer, Shionogi, UCB. O. Rotariu: None. L. Xu: None. S. Lembke: None. S. Siebert: Honoraria; AbbVie, Amgen, AstraZeneca, Janssen, Syncona, Teijin Pharma, UCB. Member of speakers’ bureau; AbbVie, GSK, Janssen, Novartis, Pfizer, UCB. Grants/research support; Eli Lilly, GSK, Janssen, UCB. P. Helliwell: Member of speakers’ bureau; Novartis. R.J. Hollick: None. G.J. Macfarlane: None.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".