CNS Prophylaxis and Treatment in Non-Hodgkin's Lymphoma: Variation in Practice and Lessons from the Literature
Bibliographic record
Abstract
Practices regarding central nervous system (CNS) prophylaxis and treatment for non-"high-grade" lymphomas are not standardized. We designed a survey to address the CNS surveillance, prophylaxis and treatment (S + P + T) habits of Ontario oncologists, to compare tertiary with community care and gauge interest in a randomized controlled trial (RCT). We mailed 145 questionnaires to oncologists/hematologists registered at the Royal College of Physicians and Surgeons of Ontario between 1980 and 1999. The questionnaire posed questions of S + P + T for a variety of histologies, locations and risk factors. Results showed that 49/77 respondents treated adult NHL, (19 community, 30 tertiary care). Surveillance LP's were commonly done in testicular, orbital, sinus and epidural sites of presentation (76, 69, 71, 80%, respectively), but these were less commonly prophylaxed (45, 33, 29 and 41%). HIV associated NHL received surveillance and prophylaxis by 51 and 33% of respondents. Stage IV disease, increased LDH and extranodal-sites warranted infrequent S + P. IT chemotherapy via LP was the most commonly used form of prophylaxis (74%) or treatment (84%). Twenty percent used systemic agents that cross the blood brain barrier for prophylaxis, and 45% for treatment. A vast heterogeneity of practice within and between tertiary care and community physicians' practices was documented. Ninety percent of physicians indicated willingness to participate in a RCT. In conclusion, CNS surveillance and prophylaxis in non-"high-grade" NHL is highly variable, probably because there are poorly defined risk factors, inconclusive prophylaxis efficacy and the inconvenience/toxicity of therapy. Patients at high risk by International prognostic index criteria are at an increased risk for CNS relapse. A RCT comparing standard chemotherapy with or without CNS prophylaxis in selected patients is needed.
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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 | 0.046 | 0.211 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".