Non‐Hodgkin lymphoma in Romania: a single‐centre experience
Bibliographic record
Abstract
Epidemiologic studies of non-Hodgkin lymphoma (NHL) in Eastern Europe are scarce in the literature. We report the experience of the "Ion Chiricuta" Institute of Oncology in Cluj-Napoca (IOCN), Romania, in the diagnosis and outcome of patients with NHL. We studied 184 consecutive NHL patients diagnosed in the Pathology Department of IOCN during the years 2004-2006. We also obtained epidemiological data from the Northwestern (NW) Cancer Registry. In the IOCN series, the most common lymphoma subtype was diffuse large B-cell lymphoma (43.5%), followed by the chronic lymphocytic leukaemia/small lymphocytic lymphoma (21.2%). T-cell lymphomas represented a small proportion (8.2%). The median age of the patients was 57 years, with a male-to-female ratio of 0.94. Patients with indolent B-cell lymphomas had the best overall survival, whereas those with mantle cell lymphoma had the worst survival. The NW Cancer Registry data showed that the occurrence of NHL in the NW region of Romania was higher in men [world age-standardized incidence rate/100 000 (ASR)-5.9; 95% CI 5.1-6.6] than in women (ASR-4.1; 95% CI 3.5-4.7) with age-standardized male-to-female ratio of 1.44 (p = 0.038). Chronic lymphocytic leukaemia/small lymphocytic lymphoma was the most common NHL in the NW region of Romania, accounting for 43% of all cases, followed by diffuse large B-cell lymphoma (36%). The 5-year, age-standardized cumulative relative survival for NHL in the County of Cluj in NW Romania, for the period of 2006-2010, was 51.4%, with 58.4% survival for men and 43.2% for women. Additional studies of NHL in Eastern Europe are needed. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".