Real-world Longterm Effectiveness of Tumor Necrosis Factor Inhibitors in Psoriatic Arthritis Patients from the Rheumatic Diseases Portuguese Register
Bibliographic record
Abstract
OBJECTIVE: To assess longterm effectiveness of tumor necrosis factor inhibitors (TNFi) in patients with psoriatic arthritis (PsA) registered in the Rheumatic Diseases Portuguese Register, exposed to at least 1 TNFi, prospectively followed between 2001 and 2017. METHODS: Kaplan-Meier analysis was performed for first-, second-, and third-line TNFi. Responses included European League Against Rheumatism (EULAR) criteria, Disease Activity Index for Psoriatic Arthritis (DAPSA), minimal disease activity (MDA), and Ankylosing Spondylitis Disease Activity Score (ASDAS) at 3 and 6 months. Baseline predictors of discontinuation and response were studied using Cox and multivariable multinomial/logistic regression models. RESULTS: The 750 patients with PsA showed drug retention of 4.1 ± 3.4 years (followup 5.8 ± 3.8 yrs) for first TNFi. Switching to a second (189 patients) or third (50 patients) TNFi further decreased survival by 1.1 years. Female sex, higher baseline 28-joint count Disease Activity Score, and infliximab were predictors of first TNFi discontinuation. After 6 months of the first TNFi, 48.7% of patients achieved a good EULAR criteria response and 20.9% were in DAPSA remission. There were 11.4% in MDA, and 56.4% had a good ASDAS. Responses to the second TNFi were significantly inferior compared to responses to the first TNFi. Female sex and higher baseline Health Assessment Questionnaire-Disability Index were negatively associated with good EULAR response at 3 months, and obesity decreased the chance of response at 6 months. CONCLUSION: In this study, switching to a second or third TNFi was associated with significantly lower drug survival and response rates for patients with axial and peripheral PsA subtypes. More successful therapeutic approaches will require considering the effect of sex and obesity on TNFi effectiveness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.009 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".