A comparison of mantle versus involved-field radiotherapy for Hodgkin's lymphoma: reduction in normal tissue dose and second cancer risk
Bibliographic record
Abstract
BACKGROUND: Hodgkin's lymphoma (HL) survivors who undergo radiotherapy experience increased risks of second cancers (SC) and cardiac sequelae. To reduce such risks, extended-field radiotherapy (RT) for HL has largely been replaced by involved field radiotherapy (IFRT). While it has generally been assumed that IFRT will reduce SC risks, there are few data that quantify the reduction in dose to normal tissues associated with modern RT practice for patients with mediastinal HL, and no estimates of the expected reduction in SC risk. METHODS: Organ-specific dose-volume histograms (DVH) were generated for 41 patients receiving 35 Gy mantle RT, 35 Gy IFRT, or 20 Gy IFRT, and integrated organ mean doses were compared for the three protocols. Organ-specific SC risk estimates were estimated using a dosimetric risk-modeling approach, analyzing DVH data with quantitative, mechanistic models of radiation-induced cancer. RESULTS: Dose reductions resulted in corresponding reductions in predicted excess relative risks (ERR) for SC induction. Moving from 35 Gy mantle RT to 35 Gy IFRT reduces predicted ERR for female breast and lung cancer by approximately 65%, and for male lung cancer by approximately 35%; moving from 35 Gy IFRT to 20 Gy IFRT reduces predicted ERRs approximately 40% more. The median reduction in integral dose to the whole heart with the transition to 35 Gy IFRT was 35%, with a smaller (2%) reduction in dose to proximal coronary arteries. There was no significant reduction in thyroid dose. CONCLUSION: The significant decreases estimated for radiation-induced SC risks associated with modern IFRT provide strong support for the use of IFRT to reduce the late effects of treatment. The approach employed here can provide new insight into the risks associated with contemporary IFRT for HL, and may facilitate the counseling of patients regarding the risks associated with this treatment.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".