European Bone Marrow Working Group trial on reproducibility of World Health Organization criteria to discriminate essential thrombocythemia from prefibrotic primary myelofibrosis
Bibliographic record
Abstract
BACKGROUND: The World Health Organization classification of myeloproliferative neoplasms discriminates between essential thrombocythemia and the prefibrotic phase of primary myelofibrosis. This discrimination is clinically relevant because essential thrombocythemia is associated with a favorable prognosis whereas patients with primary myelofibrosis have a higher risk of progression to myelofibrosis or blast crisis. DESIGN AND METHODS: To assess the reproducibility of the classification, six hematopathologists from five European countries re-classified 102 non-fibrotic bone marrow trephines, obtained because of sustained thrombocytosis. RESULTS: Consensus on histological classification defined as at least four identical diagnoses occurred for 63% of the samples. Inter-observer agreement showed low to moderate kappa values (0.28 to 0.57, average 0.41). The percentage of unclassifiable myeloproliferative neoplasms rose from 2% to 23% when minor criteria for primary myelofibrosis were taken into account. In contrast, the frequency of primary myelofibrosis dropped from 23% to 7%, indicating that the majority of patients with a histological diagnosis of primary myelofibrosis did not fulfill the complete criteria for this disease. Thus, over 50% of cases in this series either could not be reproducibly classified or fell into the category of unclassifiable myeloproliferative neoplasms. CONCLUSIONS: World Health Organization criteria for discrimination of essential thrombocythemia from prefibrotic primary myelofibrosis are poorly to only moderately reproducible and lead to a higher proportion of non-classifiable myeloproliferative neoplasms than histology alone.
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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 | 0.062 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".