Comparative Effectiveness of Mycophenolate Mofetil for the Treatment of Juvenile‐Onset Proliferative Lupus Nephritis
Bibliographic record
Abstract
OBJECTIVE: Although juvenile-onset proliferative lupus nephritis (PLN) leads to significant morbidity and mortality, there is no clinical trials-based evidence to support the treatment effectiveness of any therapy for juvenile-onset PLN. Marginal structural models enable us to estimate treatment effectiveness using observational data while accounting for confounding by indication. METHODS: We used prospectively collected data to examine the effect of mycophenolate mofetil (MMF), compared to the use of other therapies, on the long-term outcome of a juvenile-onset PLN cohort (age at PLN onset <18 years). The major outcome variable was the estimated glomerular filtration rate (GFR) using the revised Schwartz formula. Confounding by indication was corrected for marginal structural model. RESULTS: A total of 172 subjects with juvenile-onset PLN, with a mean followup duration of approximately 4 years, were included. Overall, MMF was superior to other therapies, with a relative effect estimate for MMF of 1.06, i.e., 6% better estimated GFR on average (95% confidence interval 0.7, 11.3), corrected for potential confounding by indication. We found that beginning in year 4 there was a significant improvement in estimated GFR in the patients who were treated with MMF versus other therapies. This improvement was maintained until the end of the study. CONCLUSION: MMF was more beneficial than other therapies in improving/maintaining long-term renal function in patients with juvenile-onset PLN up to a maximum followup of 7 years. This finding is consistent with evidence from adult PLN clinical trials.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".