Risk Factors for Relapse of Antineutrophil Cytoplasmic Antibody-associated Vasculitis in Japan: A Nationwide, Prospective Cohort Study
Bibliographic record
Abstract
OBJECTIVE: The aim was to elucidate the prognosis and risk factors associated with relapse during longterm remission maintenance therapy for antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV). METHODS: Patients with newly diagnosed AAV (n = 156) were registered in the Remission Induction Therapy in Japanese patients with ANCA-associated Vasculitides (RemIT-JAV) study, and among them, 83 patients who achieved remission were enrolled and followed up for 24 additional months in our nationwide, prospective cohort study (Co-RemIT-JAV; registration number UMIN 000006373). Patterns of maintenance therapy, effectiveness, and safety were evaluated from months 25 to 48 after the RemIT-JAV. The primary outcome measure was the rate of relapse. Secondary outcome measures included overall and renal survival, risk factors associated with relapse, and incidence rates of serious infections. RESULTS: The patients comprised 35 men and 48 women aged 65.3 ± 12.6 years. Between months 25 and 48, the survival rate was 95% (79/83). Causes of death included 1 thyroid cancer, 1 infection, and 2 unknown reasons. Four patients had developed endstage renal disease (ESRD) by Month 24; 1 developed ESRD beyond Month 25. The relapse rate was 24% (20/83) from months 25 to 48. Multivariable analysis revealed that oral prednisolone ≤ 2.5 mg/day at Month 24 was a significant risk factor for relapse between months 25 and 48 (HR = 3.1, 95% CI 1.1-8.5). CONCLUSION: One-quarter of patients with AAV relapsed during maintenance therapy, and relapse was associated with the dose of oral prednisolone 24 months after the initiation of remission induction therapy in Japan.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".