Incidence and Predictors of Secondary Failure to Biologic Therapy in Patients with Psoriatic Arthritis
Bibliographic record
Abstract
Objectives Secondary failure to biologic therapy is challenging and contributes to the complexity of managing psoriatic arthritis (PsA). In this study, we aimed to define the incidence of secondary failure to biologic therapy in patients with PsA and identify the factors associated with its occurrence. Methods We retrieved data on patients with PsA followed at our prospective observational cohort who commenced and remained on biologic therapy for at least 1 year. We assessed response at the 1-year point as achievement of ≥40% reduction in the swollen joint count (SJC) and ≥50% reduction in the PASI, or PASI ≤2. We defined secondary failure as the clinician’s judgment of loss of efficacy over time or failure to maintain the response criteria. Patients with secondary failure were compared to those with maintained response in terms of demographic and disease-related characteristics. For factors associated with the development of secondary failure, we used univariate and multivariate Cox regression analyses, adjusting for calendar year (8-year intervals from 2002 to 2024). Results Of the 482 patients who commenced treatment with biologics after clinic enrollment, 264 (54.8%) were classified as responders to therapy at 1 year. 236 (89.4%) responders received tumor necrosis factor inhibitors (TNFi). 94 (35.6%) responders developed secondary biologic failure at a median [IQR] of 2.7 [1.7, 4.8] years. The incidence rate of secondary failure was 5.96 per 100 person-years. Golimumab had the lowest 5-year prevalence of secondary failure (11.1%). In the reduced multivariate model, higher SJC (HR 1.40, p=0.01) and PASI (HR 1.15, p=0.02) at the time of response (1-year point) were associated with the development of secondary failure. Use of TNFi (HR 0.37, p=0.02) and initiation as the first-ever biologic (HR 0.52, p=0.049) were associated with a lower incidence of secondary failure (Table 1). Table 1. Univariate and multivariate Cox proportional hazards regression analysis of factors associated with secondary biologic failure. Conclusion Secondary biologic failure is common in PsA. A more complete clinical response, use of TNFi, and commencement as the first-ever biologic are all associated with persistence of 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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".