Symptom burden in myeloproliferative neoplasms: clinical correlates, dynamics, and survival impact—a study of 784 patients from the Quebec MPN research group
Bibliographic record
Abstract
Classic BCR::ABL1 -negative myeloproliferative neoplasms (MPN) include polycythemia vera (PV), essential thrombocythemia (ET) and primary myelofibrosis (PMF). While patients may benefit from extended survival, they also endure lifelong symptoms , ranging from mild to incapacitating [ 1 ]. These include physical manifestations related to hyperviscosity, bone pain, pruritus, constitutional symptoms, and consequences of splenomegaly, among others, as well as psychological symptoms (e.g., depression, anxiety) [ 2 , 3 ]. Ultimately, symptom burden impairs quality of life (QoL) [ 4 ], an independent predictor of mortality [ 5 ]. Addressing symptom burden in MPN patients is crucial in guiding and individualizing therapy; however, several important challenges remain, including obscure mechanistic underpinnings and scarcity of robust data to inform practice. While the current patient-reported symptom assessment tool was conceived as a universal instrument for the collective MPN population—facilitating its clinical application, distinct profiles across subtypes may not be captured. Cut-off values determining ‘significant’ scores may also warrant further evaluation. Furthermore, kinetics of symptom profiles over time and correlations with biological variables have not fully been explored. The objectives of the current study were to comprehensively characterize symptom burden in a large MPN cohort, determining: i) age/sex-associated differences; ii) longitudinal dynamics and treatment effects; iii) biologic correlatives; and iv) impact on overall survival (OS) in a real-world population-based setting.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".