Management of Adolescent Low-Risk Classical Hodgkin Lymphoma: Which Chemotherapy Backbone Gives the Best Chance of Omitting Radiotherapy Safely
Bibliographic record
Abstract
Even though more than 90% of adolescents with low-risk classical Hodgkin lymphoma (LRcHL) will be cured with first-line therapy, many will suffer serious late toxic effects from radiotherapy (RT). The goals for care have shifted toward minimizing late toxic effects without compromising the outstanding cure rates by adapting a risk and response-based therapy. Recent published and ongoing randomized clinical trials, using functional imaging, may allow for better identification of those patients for whom RT may be safely omitted while maintaining excellent cure rates. To evaluate the best chemotherapy regimens with a reasonable toxicity profile and that are expected to have a high chance of omitting RT based on a response-directed therapy while maintaining high cure rates, a mini review was conducted of the recent clinical trials in pediatric and adult LRcHL. The UK RAPID trial chemotherapy backbone (3 × ABVD) followed by a response-based positron emission tomography scan offers up to a 75% chance of safely omitting RT without compromising the cure rate, which remained well above 90%.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".