Incidence and Risk of Infections in Patients With Radiographic Axial Spondyloarthritis Receiving Biologic Therapies: A Prospective Observational Study Using the KOBIO Registry
Bibliographic record
Abstract
OBJECTIVE: This study aimed to assess the occurrence of infection and risk factors among patients with radiographic axial spondyloarthritis (r-axSpA) treated with biologics in a real-world setting. METHODS: This prospective observational cohort study included patients with r-axSpA from the Korean College of Rheumatology Biologics (KOBIO) registry who initiated or switched to a biologic agent between December 2012 and December 2023. The primary outcome was the first occurrence of any infection, ranging from mild to severe, classified by organ system. The infection rates per 1000 person-years (PY), with 95% CI, were calculated using the Poisson distribution method. Cox proportional hazard regression models-adjusted for confounders-estimated hazard ratios for infection risk, considering only the first infection event. RESULTS: This analysis included 2129 patients with a total of 7107.67 PY of follow-up. The predominant infections observed were of the upper and lower respiratory tract (25.89/1000 PY), followed by herpes zoster (HZ; 6.13/1000 PY). Multivariate Cox regression analysis revealed significant risk factors for infection, including advanced age, ischemic heart disease (IHD), diabetes mellitus (DM) with complications, chronic kidney disease (CKD), and peripheral arthritis. In contrast, male sex was identified as a protective factor against the development of infections. CONCLUSION: The infection rate was 39.39 events/1000 PY, with respiratory tract infections being most common, followed by HZ. Significant risk factors for the occurrence of infection in patients with r-axSpA treated with biologics included advanced age, female sex, IHD, DM with complications, CKD, and peripheral arthritis. These findings emphasize infection risk assessment, particularly in high-risk patients, to optimize the safety of biologic therapy in r-axSpA.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".