Prevalence and predictors of tumour necrosis factor inhibitor persistence in psoriatic arthritis
Bibliographic record
Abstract
Objectives: To evaluate TNF-α inhibitor (TNFi) persistence when used as first- or second-line biologic therapy for the management of PsA, and to determine baseline clinical and laboratory parameters associated with TNFi persistence. Methods: A retrospective single-centre cohort study was performed on all patients with PsA initiated on TNFi therapy between 2003 and 2015. Demographic, clinical and laboratory characteristics were compared with TNFi persistence, using Kaplan-Meier survival and Cox proportional hazards models. Results: One hundred and eighty-eight patients with PsA were prescribed TNFi therapy as first-line biologic therapy over a period of 635 person-years [46% male, mean (s.d.) age 47.3 (11.4) years; median (interquartile range) disease duration 11 (7-16) years]. At 12 months of follow-up 79% of patients persisted with TNFi therapy, and 73% at 24 months. Of those discontinuing TNFi, 35% stopped due to primary inefficacy, 22% secondary inefficacy and 43% adverse events. Multivariable analysis identified female sex (hazard ratio (HR) 2.57; 95% CI: 1.26, 5.24; P = 0.01) and the presence of metabolic syndrome-related co-morbidities (HR = 2.65, 95% CI: 1.24, 5.69; P = 0.01) as predictors of lower persistence. Of 32 cases treated with a second TNFi, persistence at 12 months was 56%. TNFi persistence was 2-fold less likely in these 32 cases compared with first-line TNFi users (HR = 2.02, 95% CI: 1.20, 3.42; P = 0.01). Conclusion: Patients with PsA who are female and have metabolic syndrome-related co-morbidities have lower TNFi persistence. Although persistence was lower in patients who had switched to a second TNFi, a substantial proportion of these cases responded, advocating switching to a second TNFi as a valid therapeutic strategy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".