Clinical findings in a large cohort of adult patients (pts) with Hodgkin’s disease (Hd) in Argentina: A report from two institutions
Bibliographic record
Abstract
17570 Background: More than 20,000 new cases of HD are diagnosed each year all over Europe, Canada and the United States. Nevertheless, there are few reports in current literature showing data from large series in developing countries. Methods: The medical records of adult pts with an oncohaematologic diagnosis in two large oncological centers (HMC and IOHM) were reviewed. A period spanning the past 10 years was considered with the objective of measuring the incidence of HD. Oncologists in charge were asked to fill a form with the relevant clinical data. Results: Three hundred and fifty eight out of 1,884 medical records of pts with HD (19%) were retrieved (M: 55.2%/F: 44.8%). Seven pts were HIV positive. Bulky disease was present in 7,4%. The following table shows the main topics (See table ): Conclusions: Incidence of HD in our serie was similar to the published report. However, two important differences arose: it was not possible to notice neither the double curve described nor the usual histological subtype distribution (more MC than the expected frequency). According to previous reports, prevalence of NS was associated with mediastinal locations and younger pts. Actuarial survival must be presented. [Table: see text] No significant financial relationships to disclose.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".