Very Elderly Patients with Myeloproliferative Neoplasms: Phenotypic Distinctions and Prognostic Determinants of Complications and Mortality
Bibliographic record
Abstract
Abstract Background and methods: Increasing life expectancy has had the impact of increasing the proportion of patients with myeloproliferative neoplasms (MPN) aged ≥75 years (very elderly patients; VEP). However, few studies have evaluated the phenotype and prognostic factors specific to this population. This is a retrospective multicenter chart review (11 Quebec centers) of VEP with polycythemia vera (PV), essential thrombocytosis (ET), and myelofibrosis (MF) diagnosed between 1978 and 2019, enrolled in the CML-MPN Quebec Research Group registry. All diagnoses were made according to World Health Organization 2016 criteria (Blood. 2016;127:2391), with exemption of bone marrow biopsies in select patients. Standard statistical methods were used for all analyses. Results: Of the 753 patients studied in the registry, 114 patients (15%) were ≥75 years old (VEP) (Table 1). These subjects had a median age of 79 years (range 75-95) with incidence of PV, ET and MF of 38%, 51% and 11% respectively. Compared to patients <75 years old, VEP were less likely to be male (35% vs 45%, p = 0.05), had more frequent and higher levels of leukocytosis (11.4 vs 9.7 x 10 9 / L, p <0.0001), were more frequently "triple negative" and less commonly CALR-mutated (p = 0.0005), and presented significantly higher allelic burdens (45% vs 36%, p = 0.03). VEP also had more cardiovascular comorbidities (p <0.0001) and were more often classified as "high risk" (86% vs. 43%, <0.0001). A history of arterial thrombosis prior to/at diagnosis was more common in VEP vs younger patients (14% vs 7.2%, p = 0.02), as was a global history of arterial and/or venous thrombosis at any time during the follow up (25% vs 18%, p = 0.05). Sites of venous events were specifically skewed towards lower extremity deep vein thrombosis in VEP (75%) vs variously distributed in younger patients (p = 0.05). Bleeding rates were similar among the two groups (16% VEP and 17% non-VEP, p = 0.7) while fewer fibrotic (3% vs 8%, p = 0.03) and leukemic transformations (0 vs 2%, p = 0.04) were recorded in VEP. Significantly fewer bone marrow biopsies were performed in VEP (41% versus 54%, p = 0.01). This cohort was, however, more likely to receive cytoreductive therapy (76% vs 67%, p = 0.05), predominantly hydroxyurea (70% vs 59%, p = 0.02). Multivariate analysis revealed the presence of splenomegaly (HR 4.5; 1.2-17.1, p = 0.03) and smoking status (active/former vs never smokers) (HR 5.2; 1.1-24.9, p = 0.03) as predictors of shortened overall survival for the VEP population (Table 2). It also disclosed higher leukocyte count (p = 0.005) and the presence of diabetes mellitus (p = 0.05) as significant risk factors for shortened hemorrhage-free survival. Platelet count (p = 0.03) and smoking status (p = 0.02) were found to be significant determinants of thrombosis-free survival in univariate analysis but did not maintain their significance in multivariate testing. Kaplan-Meier survival data examining age-stratified outcomes in VEP vs younger patients revealed significantly shorter overall survival in VEP (14.2 years vs not reached, p < 0.0001) (Figure 1). The VEP cohort also displayed significantly reduced arterial thrombosis-free survival (incidence of 6.1% vs 3.9%, p = 0.01). There was no significant difference in event data for venous thrombosis-free (4% in both, p = 0.2) and myelofibrosis-free (2.6% versus 7.8%, p = 0.6) survival. Conclusion: This data addressing VEP with MPN exposes, for the first time: i) a characteristic phenotype (predominantly female, higher leukocyte counts, higher allele burden), ii) distinct adverse outcome patterns, particularly with regard to arterial thrombosis, and iii) unique and independent prognostic factors for survival, suggesting that VEP with MPN constitute a biologically, phenotypically, and prognostically distinct population. Figure 1 Figure 1. Disclosures Busque: Novartis: Consultancy. Szuber: Novartis: Honoraria.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".