A Globally Applicable "Triple AAA" Risk Model for Essential Thrombocythemia Based on Age, Absolute Neutrophil Count, and Absolute Lymphocyte Count
Bibliographic record
Abstract
Abstract Background The detrimental effect of leukocytosis on survival in myeloproliferative neoplasms (MPN) has been well established for primary myelofibrosis (PMF), polycythemia vera (PV) and essential thrombocythemia (ET ) (JCO. 2018;36:310; BJH. 2020;189:291) Previous studies have also implicated leukocytosis as a risk factor for leukemic transformation (Mayo Clin Proc. 2017;92:1118) and thrombosis in MPN (Blood Adv. 2019;3:1729). However, it is currently not clear as to which component(s) of white blood cells is responsible for these observations. In the current study, we sought to examine the individual prognostic contribution of absolute neutrophil (ANC), lymphocyte (ALC) and monocyte (AMC) counts, on overall (OS), leukemia-free (LFS), and myelofibrosis-free (MFFS) survival and in ET. Methods Study patients (n=349) were retrospectively recruited from the Mayo Clinic MPN database of 1,249 WHO-defined ET patients, evaluated over five decades (1967-2021), based on availability of information on ANC, ALC and AMC. Conventional criteria were used for diagnosis and definitions of major complications, including leukemic or fibrotic transformation (Blood 2016;127:2391). Conventional statistical methods were applied using JMP Pro 14.0.0 software package, SAS Institute, Cary, NC. Multivariable analyses included previously established risk factors for survival. Results 349 patients (median age 57 years, range 18-89; females 61%) with ET were included in the study: 46% JAK2, 34% CALR, 16% triple-negative and 4% MPL mutated; IPSET risk category high 24%, intermediate 41%, and low 35%; presenting median (range) values were 13.8 g/dL (11.1-16.4) for hemoglobin, 8.2 x 10(9)/L (3.2-52) for leukocyte count, and 859 x 10(9)/L (451-3460) for platelet count; palpable splenomegaly was present in 48 (14%); median followup was 10 years (range 0-47), during which time 118 deaths, 52 fibrotic progressions, and 14 leukemic transformations were documented. Multivariable analysis identified older age (p<0.001), increased ANC (p<0.001), decreased ALC (p=0.03), and male sex (p=0.04), but not AMC (p=0.8), venous thrombosis (p=0.4), or arterial thrombosis (p=0.4), as independent risk factors for OS. ANC of ≥8 x 10(9)/L and ALC of <1.8 x 10(9)/L were determined as appropriate cut-off values by ROC analysis. Subsequent multivariable analysis using these cut-off values resulted in HR (95% CI) of 5.2 (3.4-7.9; p<0.001) for age >60 years, 3.1 (2.1-4.6; p<0.001) for ANC, and 2.0 (1.4-3.0; p<0.001) for ALC; male sex was no longer significant in this analysis (p=0.14). An operational HR-based risk score assigned 3 adverse risk points for older age (>60 years), 2 for increased ANC (≥8 x 10(9)/L) and 1 for ALC (<1.8 x 10(9)/L), resulting in an new Age Anc Alc (AAA; triple A) risk model for survival in ET with estimates of median survival ranging from 9.7 to 36.6 years (Figure 1). In addition, ALC <1.8 x 10(9)/L was associated with inferior LFS (p=0.06) and MFFS (p=0.07) while AMC as a continuous variable showed borderline significance for MFFS (p=0.18). In univariate analysis, JAK2V617F allele burden showed significant association with OS (p=0.02), LFS (p=0.05) and MFFS (p=0.001); however significance for OS was lost in mutivariable analysis that included ANC and ALC. An external validation cohort from the University of Florence (n=485) confirmed the independent survival risk contribution from age >60 years (p<0.001; HR 9.9, 95% CI 5.4-18.0), ANC ≥8 x 10(9)/L (p=0.02; 1.9, 1.1-3.5) and ALC <1.8 x 10(9)/L (p<0.001; 2.0, 1.3-3.0). The Triple A risk model was also effectively applied on the Florence validation cohort (Figure 1): median follow-up 8.4 years; 87 deaths; 43 fibrotic progression; 12 leukemic transformations. The association of ALC <1.8 x 10(9)/L (p=0.04) and AMC (p=0.002) with fibrotic transformation was also validated in the Florence cohort. Conclusions: The current study identifies increased ANC and decreased ALC as age-independent risk factors for survival in ET, thus allowing the development of a globally applicable simple to use "Triple A" risk model that is based on Age, ANC and ALC. Decreased ALC also predicted fibrotic and leukemic progression. Our observations suggest potential value for immune profiling as an additional prognostic tool in MPN. Figure 1 Figure 1. Disclosures Szuber: Novartis: Honoraria. Vannucchi: BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".