Long-term Safety and Effectiveness of Tacrolimus in Patients With Lupus Nephritis: 5-year Interim Postmarketing Surveillance Study in Japan (TRUST)
Bibliographic record
Abstract
Objective. To assess the long-term safety and effectiveness of tacrolimus for treating lupus nephritis (LN) in the real-world clinical setting. Methods. This is an ongoing, open-label, noncomparative, observational, postmarketing surveillance study conducted across 275 sites in Japan. Registered patients with LN were followed for 10 years. Here we report data relating to 5 years of tacrolimus maintenance therapy at the interim data cutoff in August 2016. Results. Of 1395 registered patients, 1355 received tacrolimus maintenance therapy for LN and provided safety data. The most common serious adverse drug reactions (ADR) included pneumonia (1.1%), herpes zoster (1.0%), cellulitis (1.0%), and diabetes mellitus (1.0%). ADR occurred mainly within the first 28 weeks of tacrolimus treatment, and no marked increase was observed during the follow-up period. Subgroup analyses suggested that risk factors for commonly observed ADR associated with tacrolimus included inpatient management, LN disease severity, increasing age, abnormal renal or hepatic function, and comorbid or previous disease. The cumulative rate of progression to renal failure (based on the attending physician’s assessment) was 0.8% at Year 1 and 6.6% at Year 5. Cumulative relapse rates were 7.8% and 30.6%, respectively. Urine protein:creatinine ratio, serum anti-dsDNA antibody levels, complement C3 levels, and steroid-sparing effects were all significantly improved from 4 weeks after tacrolimus treatment initiation (P < 0.001) and were sustained over 5 years. Conclusion. Long-term tacrolimus maintenance treatment over 5 years in the real-world clinical setting was well tolerated and effective in a large population of patients with LN ( www.ClinicalTrials.gov : NCT01410747 ).
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".