Predictors of Achieving Remission among Patients with Psoriatic Arthritis Initiating a Tumor Necrosis Factor Inhibitor
Bibliographic record
Abstract
OBJECTIVE: To examine predictors of remission among patients with psoriatic arthritis (PsA) initiating a tumor necrosis factor (TNF) inhibitor. METHODS: Patients with PsA enrolled in the Corrona Registry between 2005 and 2013 were followed from initiation of a TNF inhibitor (TNFi; etanercept, adalimumab, infliximab, certolizumab, or golimumab) to the visit closest to 12 months. Additional inclusion criteria included 3 tender or 3 swollen joints. Outcomes of interest were Clinical Disease Activity Index (CDAI) ≤ 2.8 (remission), low disease activity (LDA; CDAI ≤ 10), change in the modified Health Assessment Questionnaire (mHAQ) ≥ 0.35 and achievement of mHAQ < 0.30. Predictors were measured on or before TNFi initiation. Covariates significant in univariable logistic regression models and ≤ 5% missing values were included in a multivariable model and removed individually until all remaining variables were significant (p < 0.05). RESULTS: Among 1832 TNFi initiations, 774 initiations (624 patients) met inclusion criteria. Median age at initiation was 52 years [interquartile range (IQR) 44-60], 56% were female, median PsA duration was 4 years (IQR 2-11), and median CDAI at baseline was 20 (IQR 14.5-28). Remission was achieved by 14% and LDA (or remission) by 37%. Achieving remission was positively associated with college education (OR 1.88, 95% CI 1.11-3.19) but negatively associated with female sex (0.62, 95% CI 0.40-0.97), obese body mass index (0.51, 95% CI 0.32-0.81), hypertension (0.55, 95% CI 0.32-0.95), previous biologic use (0.41, 95% CI 0.26-0.65), and baseline pain (0.80 per 10 mm visual analog scale, 95% CI 0.73-0.87). Predictors for LDA, mHAQ < 0.30, and mHAQ change were similar. CONCLUSION: Few patients with PsA in a US-based registry achieved remission by CDAI criteria. Female sex, obesity, comorbidities, and education influence achievement of remission on a TNFi.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".