CLINICAL CHARACTERISTICS AND OUTCOME OF PATIENTS WITH HODGKIN'S LYMPHOMA OLDER THAN 60 YEARS TREATED IN SWITZERLAND OVER THE LAST 17 YEARS
Bibliographic record
Abstract
DNA samples of 166 and 152 patients were available for STAT3 and STAT5b mutations analysis, respectively.STAT3 mutations were detected in 47 patients (28.3%), with a higher frequency in CD8+ TαβLGLL towards Tγδ LGLL (60% vs 25%, p = 0.0232) and CLPD-NK (60% vs 5.8%, p<0.0001).At variance, STAT5b mutations were found in 15 patients (9.8%), in 12 case were CD4+ Tαβ LGLL and in 3 cases were Tγδ LGLL.With a median follow up of 8 years, median overall survival (OS) of our cohort was not reached.Major features associated to reduced OS were ANC<500/mm 3 (267 months vs not reached, p = 0.0297), severe anemia (144 months vs not reached, p<0.0001), treatment requirement (214 vs not reached, p = 0.0011) and presence of STAT3 mutations (267 months vs not reached, p = 0.0113). Conclusion: Our results confirmed the remarkable heterogeneity ofLGLL.We identified clinical and biological features associated to reduced OS in LGLL patients and, for the first time, we demonstrated the dismal impact of STAT3 mutations in patients' survival, suggesting that this marker should be regarded as a potential target of therapy.
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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 | 0.000 | 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".