Non-Hodgkin lymphoma in the developing world: review of 4539 cases from the International Non-Hodgkin Lymphoma Classification Project
Bibliographic record
Abstract
The distribution of non-Hodgkin lymphoma subtypes varies around the world, but a large systematic comparative study has never been done. In this study, we evaluated the clinical features and relative frequencies of non-Hodgkin lymphoma subtypes in five developing regions of the world and compared the findings to the developed world. Five expert hematopathologists classified 4848 consecutive cases of lymphoma from 26 centers in 24 countries using the World Health Organization classification, and 4539 (93.6%) were confirmed to be non-Hodgkin lymphoma, with a significantly greater number of males than females in the developing regions compared to the developed world (P<0.05). The median age at diagnosis was significantly lower for both low- and high-grade B-cell lymphoma in the developing regions. The developing regions had a significantly lower frequency of B-cell lymphoma (86.6%) and a higher frequency of T- and natural killer-cell lymphoma (13.4%) compared to the developed world (90.7% and 9.3%, respectively). Also, the developing regions had significantly more cases of high-grade B-cell lymphoma (59.6%) and fewer cases of low-grade B-cell lymphoma (22.7%) compared to the developed world (39.2% and 32.7%, respectively). Among the B-cell lymphomas, diffuse large B-cell lymphoma was the most common subtype (42.5%) in the developing regions. Burkitt lymphoma (2.2%), precursor B- and T-lymphoblastic leukemia/lymphoma (1.1% and 2.9%, respectively) and extranodal natural killer/T-cell lymphoma (2.2%) were also significantly increased in the developing regions. These findings suggest that differences in etiologic and host risk factors are likely responsible, and more detailed epidemiological studies are needed to better understand these differences.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".