Rituximab treatment for lupus nephritis: A systematic review
Bibliographic record
Abstract
PURPOSE: We used the Cochrane systematic review to analyze the effectiveness and safety of rituximab for lupus nephritis. METHODS: Systematic search was performed among Cochrane clinical controlled trials database, MEDLINE, MEDLINE-IN-Process and Other Non-Indexed Citations, EMBASE, EBSCO CINAHL, CNKI, VIP and Wanfang database from the establishment of the database to February 2016. The effectiveness and safety were evaluated in terms of the complete remission rate, total remission rate, urinary protein, Systemic Lupus Erythematosus Disease Activity Index changes and adverse events rate. Data were analyzed by the Review Manager Software version 5.3. RESULTS: Five RCTs that met the inclusion criteria, including a total of 238 patients, were enrolled in our study. The results showed that the complete remission rate in rituximab group was a significantly higher than that of cyclophosphamide group. The difference between the two groups was statistically significant (OR=2.80, 95%CI(1.08,7.26), P=0.03). But there was no significant difference between the two groups in partial and total remission rate. The complete remission rate, partial remission rate and total remission rate in rituximab treatment group was similar compared with mycophenolate mofetil group and rituximab combined with cyclophosphamide group. The adverse reaction rate was also similar among the groups. CONCLUSION: The study systematically analyzed the effectiveness and safety of rituximab for lupus nephritis, which suggested that the complete remission rate of rituximab in the treatment of lupus nephritis was a significantly higher than that of cyclophosphamide group, while the effectiveness and safety was of no difference compared with cyclophosphamide and mycophenolate mofetil.
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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 | 0.010 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.009 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".