COST‐EFFECTIVENESS AND COST‐UTILITY ANALYSIS OF MULTIPLE TREATMENT STRATEGIES USING ABVD AND/OR BEACOPP IN THE TREATMENT OF ADVANCED‐STAGE HODGKIN LYMPHOMA
Bibliographic record
Abstract
Introduction: Consolidation Radiotherapy (cRT) was originally proposed for ABVD-treated advanced stage Hodgkin Lymphoma (aHL) presenting with bulky or a residual mass (RM) after ABVD.However, very few published data exist on the role of cRT on RM in patients (pts) with a negative end-of treatment PET (EoT-PET) after ABVD.Methods: In the HD0607 clinical trial (Gallamini JCO 2018) aHL pts (stage IIB-IVB) were treated with 2 ABVD courses, followed by an interim PET (PET-2).PET-2 positive pts were randomized to 4 BEACOPP escalated + 4 BEACOPP baseline cycles ± rituximab before each cycle.PET-2 negative pts were treated with 4 more ABVD and a EoT-PET was performed afterwards.PET-2 and EoT-PET negative pts were randomized to either cRT on the sites where a large nodal mass (LNM) was detected at baseline, or no further therapy (NFT).LNM was defined as single or a conglomerated nodal mass with the largest diameter ≥ 5 cm in baseline CT.Results: After ABVD, 47/630 (7%) PET2 negative pts with a positive EoT-PET, 27/630 off study pts for disease progression or consent withdrawal and 260 pts without LNM were not suitable for the random, while 296 were randomized to cRT (148) or NFT (148).In this pts cohort the largest diameter of LNM was 5-7 cm in101 (34%) 8-10 cm in 96 (32%), while a classical bulky (diameter >10 cm) was detected in 99 (33%) pts.Prognostic factors, age, sex, stage, IPS, Performance status, extra-nodal sites, bulky disease were well balanced between the two cohorts.In pts presenting with one (265) or more (31) LNM, the most common nodal region was mediastinum (82%), followed by cervical (14%), abdominal (6%) or axillary (3%) regions.A post-ABVD RM was detected in 260 (88%) of 296 pts presenting with a LNM and in 92/99 pts with classical bulky.The median dose of RT was 30.6 (24.0-113.6)Gy, by involved field (88%) involved node (1%) or involved site (11%) technique.After a median follow-up of 5.9 (0.5-10) years the 6-year PFS for RT versus NFT in an intention to treat analysis was 92% (95% CI, 88-97%) versus 90% (95% CI, 85-95%) p = .48(Figure ) and a 6-year OS 99% (95% CI, 97-100%) versus 98% (95% CI, 96-100%), respectively.When the analysis was limited to patients with a classical bulky lesion, the 6-year PFS was 89% (95% CI, 81-99%) for consolidation RT and 86% (95% CI, 77-96%) for NFT (p = .53).The 6-year PFS of the 260 non-randomized pts without LNM at baseline, was 92% (95% CI, 88-95%).When the analysis was limited to those with RM, the relapse rate of patients treated or not with cRT was 7% versus 9%, with a 6-year PFS of 93% (95% CI, 88% to 97%) versus 89% (95% CI, 84% to 95%) (P = .41).Conclusions: cRT could be safely omitted in aHL pts presenting with a LNM and both a negative PET-2 and EoT-PET, irrespective from the LNM size.As in more than 80% of the pts the site of LNM at baseline was in mediastinum, this could translate in a significant reduction of late-onset treatment related mortality for secondary tumours and coronary arterial disease.
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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".