Impact of time from diagnosis to initiation of curative-intent chemotherapy on clinical outcomes in patients with classical Hodgkin lymphoma
Bibliographic record
Abstract
The impact of treatment delays on outcomes in Hodgkin lymphoma (HL) is currently unknown. Time from definitive histologic diagnosis to first ABVD treatment (TDT) was calculated in 810 adults with HL: 365 (45%) TDT ≤4 weeks, 369 (46%) TDT 5-8 weeks, 76 (9%) TDT >8 weeks. The 5-year overall survival (OS) was 92% TDT ≤4 weeks, 92% TDT 5-8 weeks, and 83% TDT >8 weeks (p = 0.007). The 5-year disease-specific survival (DSS) was 93% TDT ≤4 weeks, 95% TDT 5-8 weeks, and 87% TDT >8 weeks (p = 0.094). The 5-year progression-free survival (PFS) was similar between groups (p = 0.139). In the multivariate analysis, TDT >8 weeks was not associated with worse OS, DSS, or PFS. Despite the univariate association between initiation of ABVD >8 weeks and worse OS, these data do not support such cut-off to improve outcomes. Nevertheless, clinicians should make every effort possible to initiate curative-intent chemotherapy as soon as a diagnosis of HL is established.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".