Toxicities and Financial Costs Associated with CNS Prophylaxis in Diffuse Large B-Cell Lymphoma: A Retrospective Analysis in Nova Scotia, Canada
Bibliographic record
Abstract
Background: Central nervous system (CNS) prophylaxis with high-dose methotrexate (HD-MTX) is a treatment administered to patients with high-risk diffuse large B-cell lymphoma (DLBCL) in attempt to prevent relapse or progression of lymphoma in the CNS. The quality of evidence for this therapy is weak and clinicians are increasingly uncertain about the benefit versus risk of using CNS prophylaxis. In healthcare, maximizing patient outcome at the lowest cost is essential, therefore our study aimed to identify the toxicities and financial costs associated with this therapy at our local institution in Halifax, Nova Scotia. Methods: A chart review of 52 patients with DLBCL receiving HD-MTX for CNS prophylaxis from 2010-2019. Toxicities were assessed for up to 1 month after receiving HD-MTX. We conducted a cost-consequence analysis using real-world data from a third-party payer perspective, comparing 53 patients with DLBCL who received R-CHOP and HD-MTX prophylaxis (treatment group) to 28 DLBCL patients who received R-CHOP or similar (control group). Results: 42/52 (80.8%) patients experienced at least 1 toxicity from IV HD-MTX. Notable toxicities included: mucositis (11/52, 21.2%), renal injury (12/52, 23.1%) with half of these patients having no improvement in creatinine prior to next cycle of chemotherapy, anemia (27/52, 51.9%) with 66.7% of these patients having a hemoglobin less than 80 g/L or requiring a blood transfusion, severe neutropenia with absolute neutrophil count (ANC) less than 500 x 10^9/L (3/52, 5.7%) and a single patient (1/52, 1.9%) experienced methotrexate-related pneumonitis. Total costs in the treatment group were higher than in the control group, with a statistically significant cost difference of $31,892. Conclusion: Toxicities were frequent after HD-MTX administration and although the majority were mild in severity, some serious adverse events occurred, including Grade 3 renal toxicity and pneumonitis. Our cost analysis indicates there is a significant financial cost associated with the use of CNS prophylaxis. With recent large retrospective studies questioning the benefit of this therapy, our data further supports allocating resources away from this toxic and expensive treatment. With this evolving data, each health institution needs to carefully consider their local guidelines for CNS prophylaxis in DLBCL.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".