Comparative Efficacy and Safety of Pharmacological Interventions for IgA Nephropathy: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background and Objectives: IgA nephropathy represents the most prevalent form of primary glomerulonephritis around the world, with significant heterogeneity in management strategies and outcomes. We conducted a systematic review and meta-analysis to evaluate the efficacy and safety of pharmacological interventions for IgA nephropathy. Materials and Methods: We searched multiple databases through June 2025, identifying randomized controlled trials and observational studies evaluating pharmacological treatments in biopsy-proven IgA nephropathy. Primary outcomes included proteinuria reduction and estimated glomerular filtration ration (eGFR) preservation. Secondary outcomes included hard kidney endpoints and safety parameters. Random-effects meta-analyses were performed with comprehensive risk–benefit assessments. Results: Twenty-five studies were included. B-cell/plasma-cell-targeted therapies showed significant proteinuria reduction (−34.0% [95% CI: −45.7, −22.3%]), complement pathway inhibitors demonstrated superior eGFR preservation (+5.8 mL/min/1.73 m2/year [95% CI: 2.4, 9.2]). Systemic corticosteroids showed observed hard outcome benefits (HR 0.37 [95% CI: 0.26, 0.52]) but highest adverse event risk (RR 3.28 [95% CI: 2.11, 5.09]). Novel agents showed projected favorable effects (B-cell: HR 0.38; complement: HR 0.42) pending validation. Conclusions: Novel targeted therapies, especially B-cell/plasma-cell-targeted agents and complement pathway inhibitors, show promising risk–benefit profiles. However, longer-term data and standardized eGFR slope reporting are needed to confirm these findings compared to other immunosuppressive agents.
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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 | 0.015 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.040 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".