Outcomes in Adolescents and Young Adults with Hodgkin Lymphoma Treated with and without Radiation Therapy On CCG 5942: A Report From the Children's Oncology Group
Bibliographic record
Abstract
Abstract Abstract 3659 Background Combined modality therapy with chemotherapy and radiation (RT) has resulted in excellent cure rates for Hodgkin Lymphoma (HL) but is associated with significant late effects. Modern therapeutic protocols attempt to limit cumulative doses of chemotherapy and minimize radiation therapy where possible. There is also growing attention to the optimal management of specific patient populations, including the adolescent and young adult (AYA) population. The CCG trial 5942 provides an opportunity to assess the role of RT in disease control for the AYA population (15–21 years of age) compared with a younger cohort (<15 years of age). Methodology The CCG 5942 study included 826 eligible patients (339 AYA) accrued during the years 1995–1998. Patients were assigned to risk-adapted chemotherapy based on stage and presence or absence of unfavourable risk factors (B symptoms, bulk disease, hilar lymphadenopathy, number of involved nodal sites). Disease response was assessed at the completion of chemotherapy and patients in CR were eligible for randomization to receive 21 Gy IFRT or no further therapy. We conducted a retrospective analysis of the CCG 5942 data to compare demographics, treatment response and survival outcomes of children and AYA. Results Patient demographics are shown in Table 1. The AYA patients were more likely to present with nodular sclerosing histology (NS), B symptoms, mediastinal bulk disease, and higher stage. The CR rates for children and AYA were 393/487 (80.7%) and 243/339 (71.7%) (p=.003). Of the 636 patients in CR, 498 (181 AYA) participated in the randomization. The AYA patients were less likely to be compliant with randomization to no further therapy (2/165 children vs 5/84 AYA, p=.045). The 8y EFS and OS for all children compared to AYA were 85.7% vs 80.2% (p=.052) and 94.3% vs 90.7% (p=.060) respectively. The 8y EFS and OS for all randomized children compared to AYA were 89.8 vs 81.3 (p=.011) and 97.2% vs 95.1% (p=0.30). A Cox model adjusting for both age group and histology (NS vs. lymphocyte predominant (LP) and mixed cellularity (MC)) demonstrated age to be an insignificant predictor (p=0.30) and NS histology to be a significant predictor (p=.001, HR 2.6) of worse EFS. EFS for all randomized patients with NS histology by age group and treatment received are shown in Figure 1. There is a significant difference among the groups in the overall comparison (p=0.018). There was no difference in OS with all pairwise comparisons p>0.5. Conclusions The AYA were more likely to present with higher risk disease and less likely to enter CR compared to younger children on the CCG 5942 trial. Among randomized patients with NS histology, both young and AYA populations show an EFS advantage with RT, though this advantage does not reach statistical significance for the AYA group. There was no difference in OS for randomized patients with NS histology in either age group. This analysis is limited by the retrospective methodology but supports further study of therapy assignment of the AYA population. Elimination of RT from AYA with NS histology may prove more challenging than for younger children. Analysis of current protocols using a uniform chemotherapy backbone and early disease response assessment with PET/CT will be particularly informative. Disclosures: No relevant conflicts of interest to declare.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".