The Clinical Significance of IDH Mutations in Essential Thrombocythemia and Primary Myelofibrosis
Bibliographic record
Abstract
BACKGROUND: Limited data exist regarding impact of IDH mutations in Philadelphia-negative myeloproliferative neoplasms (Ph-negative MPNs). Prognostic significance of IDH mutations was asessed in 184 Ph-negative MPN patients - 107 essential thrombocythemia (ET) and 77 primary myelofibrosis (PMF). METHODS: High-resolution melting (HRM) analysis was used to detect IDH1 and IDH2 mutations. RESULTS: PMF and ET patients showed no significant difference for prevalence of IDH mutations. Mutant IDH (IDH1 or IDH2) was documented in five of PMF (6.5%) and two of ET patients (1.9%). IDH mutations in ET patients included one IDH1 R132C and one IDH2 R140Q. Of the five IDH-mutated PMF patients, four (80%) displayed IDH1 (three IDH1 R132C and one IDH1 R132S) and one (20%) carried IDH2 (IDH2 R140Q) mutation. Sixty percent (three in five) of IDH-mutated PMF patients carried JAK2V617F with following allele burdens: 31-50%, 5-12.5% and 31-50%, respectively. Three of 77 PMF patients (3.9%) simultaneously harbored IDH and JAK2V617F mutations. IDH mutations in PMF showed a trend towards higher rate in females (100% and 52.8%, respectively). Bleeding complications were significantly higher in IDH-mutated PMF patients compared to IDH wild-type counterparts. Trend towards a lower prevalance of acetylsalicylic acid (ASA) use was present in IDH mutant PMF patients compared to wild-type counterparts (20% and 63.9%, respectively). Death rate was higher in IDH-mutated PMF patients compared to IDH wild-type PMF patients (60% and 15.3%). In univariate analysis, a significantly shorter leukemia-free survival (LFS) was observed in IDH-mutated PMF patients. CONCLUSIONS: We conclude that IDH mutations indicate a risk for leukemic transformation in PMF.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".