Induction Therapy and Kidney Outcomes in Pediatric Lupus Nephritis: A Prospective Study from the Pediatric Nephrology Research Consortium
Bibliographic record
Abstract
Background: Pediatric lupus nephritis (pLN) occurs in 30-50% of children with SLE and is usually more severe compared to adults. Despite that, treatment protocols and outcome data have been limited, mostly constructed using adult studies. In this study, we aim to evaluate the management and outcome of pLN in a large prospective observational multi-center study. Methods: Patients <21 years of age with new diagnosis of pLN were enrolled at 8 sites across the United States between 2011 and 2019. Induction therapy was determined by the treating practioner. We evaluated 6, 12, and 24-month remission rates, using the American College of Rheumatology guidelines, and kidney outcomes based on induction therapy with Mycophenolate Mofetil (MMF) or Cyclophosphamide (CYC). Results: Study included 107 patients. The median age at diagnosis was 14 years (range 7-19 years), and 81% of patients were female. Induction treatment varied significantly across institutions, but most patients received MMF (38%) or CYC (21%). 48 patients with proliferative pLN (III, IV, and V + III or IV) received either MMF or CYC. Combined complete and partial remission rates at 6, 12, and 24 months in proliferative pLN with MMF vs CYC induction therapies are listed in table 1. There were no differences in eGFR, proteinuria, or infection rate between CYC vs MMF at 6, 12, or 24 months. Propensity analysis showed that patients with pLN class IV and lower albumin were more likely to receive CYC. Conclusion: Remission rates and kidney outcomes were similar between children who received induction MMF vs CYC in proliferative pLN. There were significant variations in induction therapy used to manage pLN, which highlights the need for pediatric-focused LN studies to develop standardized treatment regimens and provide equitable care to patients.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".