How to define intermediate stage in Hodgkin's lymphoma?
Bibliographic record
Abstract
BACKGROUND: Intermediate or unfavourable stage Hodgkin's lymphoma (HL) definition relies upon at least three different scoring systems defined by cooperative groups (EORTC, GHSG and Canadian-ECOG). We aimed to investigate their efficacy and their correlation with International Prognostic Score (IPS) for advanced HL. PATIENTS AND METHODS: We studied a population of 1156 patients with localized stage HL treated prospectively within GELA centres in H8 (518 patients) and H9 (638 patients) protocols. Median age: 30 yr, 18%, Female 50%; stage I: 25%; stage II: 75%. According to scoring systems 70% had 0-1 EORTC factors; 60% 0-1 GHSG factors and 82% 0-1 Canadian factors. The IPS for advanced stages was available only in H9 study with 64% 0-1 factor. RESULTS: Survival curves according to each of the different scoring systems could significantly discriminate the subgroup populations. When a multivariate Cox analysis was performed for overall survival (OS) including all the scoring system variables: age > 45 yr, sex male, Haemoglobin < 10.5 g/dL, lymphocytes < 600/microL, B symptoms with elevated ESR, extra nodal sites did retain an independent significant value. Probability of OS was 99%, 98%, 92%, 82% and 73% for patients with 1-5 factors, respectively P < 0.0001. CONCLUSION: These factors are similar for most of them with those described in the IPS when stages III and IV are replaced by extra nodal localization. This new score should be validated in other prospective trials, as it will simplify the Hodgkin prognostic scoring systems for localized and advanced stages.
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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 | 0.003 | 0.009 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".