Cost Comparison Between Mycophenolate Mofetil and Cyclophosphamide-Azathioprine in the Treatment of Lupus Nephritis
Bibliographic record
Abstract
OBJECTIVE: To compare the healthcare expenditure associated with mycophenolate mofetil (MMF)-based immunosuppression in contrast to conventional therapy in patients with lupus nephritis. METHODS: Our retrospective single-center study compared the major healthcare costs during the first 24 months of treatment incurred by immunosuppressive medications, hospitalization, and complications in patients with severe lupus nephritis who had been treated with prednisolone and either MMF or sequential cyclophosphamide induction followed by azathioprine maintenance (CTX-AZA). RESULTS: Forty-four patients were studied (22 in each group). Baseline demographic and clinical measures, and remission rates after treatment, were similar between the 2 groups. Immunosuppressive drug cost was 13.6-fold higher in the MMF group (US$4168.3+/-1176.5 per patient, compared with $285.0+/-70.6 in the CTX-AZA group, mean difference $3883.2+/-251.3; p<0.001). MMF treatment was associated with a lower incidence of infections (12.0 episodes/1000 patient-months, compared with 32.4 in the CTX-AZA group; p=0.035). Combined cost of hospitalization and treatment of infections was 82.5% lower in the MMF group (mean difference -2208.7+/-1700.6; p=0.120). Overall treatment expenditure on immunosuppressive drugs, hospitalization, and treatment of infections was 1.57-fold higher in the MMF group (mean US $4635.9 compared with $2961.5 in the CTX-AZA group; p<0.001). CONCLUSION: While the cost of MMF treatment for severe lupus nephritis is much higher compared with CTX-AZA, the increased drug cost is partially offset by savings from the reduced incidence of complications.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".