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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".