SYSTEMATIC REVIEW AND NETWORK META-ANALYSIS OF INDUCTION TREATMENTS FOR LUPUS NEPHRITIS
Bibliographic record
Abstract
PV131 / #261 Poster Topic: AS15 - Lupus Nephritis-Clinical Background/Purpose This study aims to evaluate the comparative efficacy and safety of various initial treatments for lupus nephritis through a systematic review and network meta-analysis. Methods A comprehensive literature search was conducted across MEDLINE, EMBASE, Cochrane Library, and LILACS from inception to June 2024 in order to identify randomized controlled trials (RCTs) comparing initial treatments for lupus nephritis. Two reviewers independently performed data extraction and assessed the risk of bias. A frequentist random-effects network meta-analysis was conducted using the restricted maximum likelihood (REML) method to estimate heterogeneity. The certainty of evidence was evaluated using the GRADE approach. Results We included 38 RCTs encompassing 5,146 participants and 11 interventions. Mycophenolate mofetil was selected as the common comparator. The network meta-analysis revealed that voclosporin combined with Mycophenolate mofetil (RR 1.9 95% CI 1.47 to 2.47, RD 281.4, 95% CI 146.3 to 465.4; high certainty) and belimumab combined with Mycophenolate mofetil (RR 1.47, 95% CI 1.23 to 1.74, RD 145, 95% CI 72.7 to 230.9; high certainty) increased complete renal response compared to Mycophenolate mofetil alone. Tacrolimus combined with Mycophenolate mofetil (RR 1.24 95% CI 1.05 to 1.46, RD 113.7, 95% CI 25.2 to 217.7; low certainty) and Obinutuzumab combined with Mycophenolate mofetil (RR 1.57 95% CI 1.05 to 2.34, RD 270.4, 95% CI 22.7 to 640.5; low certainty) also showed potential benefits but with low certainty evidence. Cyclophosphamide was possibly associated with a small decrease in complete renal response compared to Mycophenolate mofetil (RR 0.90, 95% CI 0.77 to 1.04; low certainty). However, the effects of the assessed interventions on mortality and renal replacement therapy outcomes were highly uncertain. Conclusions Combination therapies, particularly voclosporin or belimumab with Mycophenolate mofetil, may provide enhanced outcomes for lupus nephritis initial treatment. Given the complexity of lupus nephritis, clinicians should weigh these findings alongside considerations such as drug availability, cost, and individual patient preferences to guide treatment decisions.
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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 | 0.026 | 0.061 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.042 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".