Monocytosis in polycythemia vera: Clinical and molecular correlates
Bibliographic record
Abstract
Abstract Monocytosis (absolute monocyte count, AMC ≥ 1 × 10 9 /L) might accompany a spectrum of myeloid neoplasms, other than chronic myelomonocytic leukemia (CMML). In the current study, we examined the prevalence, laboratory and molecular correlates, and prognostic relevance of monocytosis in polycythemia vera (PV). Among 267 consecutive patients with World Health Organization (WHO)‐defined PV, 55 (21%) patients displayed an AMC of ≥1 × 10 9 /L and 18 (7%) an AMC of ≥1.5 × 10 9 /L. In general, PV patients with monocytosis were significantly older and displayed higher frequencies of leukocytosis (81% vs. 50% at AMC ≥1 × 10 9 /L) and TET2 / SRSF2 mutations (57%/29% vs. 19%/1% at AMC ≥ 1.5 × 10 9 /L). In univariate analysis, AMC ≥1.5 × 10 9 /L adversely affected overall (OS; P = .004; HR 2.6, 95% CI 1.4‐4.8) and myelofibrosis‐free (MFFS; P = .02; HR 4.4, 95% CI 1.3‐15.1) survival; during multivariable analysis, significance was borderline sustained for OS ( P = .05) and MFFS ( P = .06). Other independent risk factors for OS included unfavorable karyotype ( P = .02, HR 3.39, 95% CI 1.17‐9.79), older age ( P < .0001, HR 3.34 95% CI 1.97‐5.65), and leukocytosis ≥15 × 10 9 /L ( P = .004, HR 2.04, 95% CI 1.26‐3.29). In conclusion, in the current study, we encountered a higher than expected prevalence of monocytosis in patients with PV and the mutation profile and age distribution of PV patients with monocytosis is akin to those of patients with CMML and might partly contribute to their worse prognosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".