Pediatric classical Hodgkin lymphoma
Bibliographic record
Abstract
Over the past century, classical Hodgkin lymphoma (HL) has been transformed from a uniformly fatal disease to one of the most curable cancers. Given the high cure rate, a major focus of classical HL management is reducing the use of radiation therapy (RT) and chemotherapy agents such as procarbazine and doxorubicin to minimize long-term toxicities. In both North America and Europe, an important philosophy in the management of classical HL is to guide the intensity of treatment according to the risk category of the disease. The main factors used for risk classification are tumor stage, bulk of disease, and the presence of B symptoms. Response to chemotherapy is an important factor guiding the utilization of RT in ongoing Children's Oncology Group (COG) and European Network Pediatric Hodgkin Lymphoma (EuroNet-PHL) trials. Both trial groups have transitioned to reduced RT volumes that target the highest risk sites using highly conformal techniques, along with standard or intensified chemotherapy regimens to improve outcomes in higher risk patients. However, given the potential acute toxicities of intensified chemotherapy, immunoregulatory drugs are being investigated in upcoming trials. The purpose of this review is to summarize current approaches to treating pediatric classical HL according to the COG and EuroNet-PHL.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".