Predictors of Early Minimal Disease Activity in Patients with Psoriatic Arthritis Treated with Tumor Necrosis Factor-α Blockers
Bibliographic record
Abstract
OBJECTIVE: To identify predictors of early minimal disease activity in patients with psoriatic arthritis (PsA) receiving tumor necrosis factor-α (TNF-α) antagonists. METHODS: In total 146 consecutive patients with PsA eligible for anti-TNF-α therapy were enrolled. At baseline (T0) information about age, sex, PsA subset, disease duration, comorbidities, and treatments was collected. All subjects were tested for metabolic syndrome (MetS) and/or liver steatosis. A clinical and laboratory evaluation was performed at T0 and at 3 months (T3). Changes in all these variables were compared in subjects achieving minimal disease activity (MDA) and those who did not. RESULTS: Among 146 PsA subjects, 10 discontinued therapy before 3-month followup because of adverse events; thus 136 concluded the study. All clinical outcome measures changed significantly from T0 to T3. Erythrocyte sedimentation rate showed a significant reduction (p < 0.001). C-reactive protein (CRP), serum cholesterol, and triglycerides showed no significant variation (p > 0.05). The prevalence of MetS and liver steatosis showed no significant differences between subjects achieving MDA and those who did not (p = 0.347 and 0.053, respectively). Patients achieving MDA at T3 were younger than those not achieving MDA (p = 0.001). A lower baseline tender joint count (p = 0.001), swollen joint count (p = 0.013), Bath Ankylosing Spondylitis Disease Activity Index (p = 0.021), and Ritchie index (p = 0.006) were found in subjects achieving MDA. Age (OR 0.896, p = 0.003) and Bath Ankylosing Spondylitis Functional Index (BASFI) (OR 0.479, p = 0.007) inversely predicted, whereas CRP (OR 1.78, p = 0.018) directly predicted, achievement of MDA at T3. CONCLUSION: In patients with PsA, age, CRP, and BASFI at the beginning of treatment were found to be reliable predictors of MDA after 3 months of TNF-α blocker therapy.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".