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Record W4389229148 · doi:10.1182/blood-2023-174076

<i>Calr</i> Variant Allele Frequency in Essential Thrombocythemia: Molecular Associations and Impact on Disease Phenotype and Outcome

2023· article· en· W4389229148 on OpenAlexaffabout
Paola Guglielmelli, Natasha Szuber, Naseema Gangat, Giulio Capecchi, Chiara Maccari, Lambert Busque, Omer Karrar, Maymona Abdelmagid, Manjola Balliu, Alessandro Atanasio, Ilaria Sestini, Audrey Désilets, Giuseppe Gaetano Loscocco, Giada Rotunno, Marie‐Christine Meunier, Michaël Harnois, Ayalew Tefferi, Alessandro M. Vannucchi

Bibliographic record

VenueBlood · 2023
Typearticle
Languageen
FieldMedicine
TopicMyeloproliferative Neoplasms: Diagnosis and Treatment
Canadian institutionsQuebec - Clinical Research Organization in CancerUniversité de MontréalMPB Technologies & Communications (Canada)Hôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsEssential thrombocythemiaMyelofibrosisMedicineInternal medicineLeukocytosisGastroenterologyThrombocytosisMyeloproliferative neoplasmCalreticulinMyeloidMyeloid leukemiaAllelePolycythemia veraOncologyGeneticsBiologyGenePlateletBone marrow

Abstract

fetched live from OpenAlex

Background. A mutation in calreticulin ( CALRm) is found in 30-35% of patients (pts) with Essential Thrombocythemia (ET). There are 2 main CALRm mutation types, Type 1/Type 1 like (T1) a 52bp deletion, and Type 2/Type 2 like (T2) a 5bp insertion. Other atypical mutations (T3) occur in a minority of pts. Recent study ( Guglielmelli P et al, BCJ 2023) in pts with myelofibrosis (MF) showed that higher CALR variant allele frequency (VAF) was associated with anemia at diagnosis and during FU, and to features of more advanced disease (CD34 + cell counts, ASXL1 mutation (mut), >2 mutated myeloid genes, and shorter leukocytosis-free survival. Aim. To evaluate whether the CALRm VAF in pts with ET was associated with predefined major clinical outcomes: evolution to MF, transformation to acute leukemia (AML), thrombosis, major bleeding, and survival (OS). Patients and Methods. Diagnosis of ET was strictly according to 2023 WHO and ICC to avoid mis-inclusion of prefibrotic MF. CALRm VAF was determined by capillary gel electrophoresis as the ratio (%) of areas under the curve of CALRm/ CALRm+ CALRwt. A panel of 45 myeloid neoplasm-associated genes was sequenced by NGS. Results. A total of 281 CALRm ET pts were identified from CRIMM (Florence, I), Quebec MPN Research Group centers' (Canada) and Mayo Clinic (Rochester, US) databases; 152 (54%), 101 (36%) and 28 (10%) were T1, T2 and T3 CALRm, respectively. Overall FU was 8.6y (0.3-39.4), median survival was not reached. Rate of death at 10y, 20y and 30y was 8%, 15% and 25%. MF transformation occurred in 50 pts (18%), AML in 2 (0.7%), 25 pts (8.9%) died. A major thrombotic event before or at ET diagnosis occurred in 17 (6.0 %) pts (14 arterial and 3 venous), whereas 28 pts (10.0%) had >1 major thrombosis during follow-up (53.6% arterial, 46.4% venous). Major bleeding occurred in 19 pts (6.8%; 16 at or before diagnosis). Ascertainment of correlation of CALRm VAF with predefined outcomes by continuous variable analysis (ROC curve) highlighted a significant correlation of VAF >60% with MF-free survival (MFS), with HR of 2.85 (95%CI, 1.4-5.6; P= .002. Fig. 1A). On the contrary, there was no impact of CALRm VAF as continuous variable on AML, thrombosis, bleeding and OS. We therefore used a threshold of >60% to compare main clinical and hematologic characteristics at diagnosis and outcomes during FU in pts categorized as CALR-high and CALR-low. Of all pts, 21 (7.5%) harbored a VAF >60%; of these, 52%, 19% and 29% were T1, T2, T3, respectively, compared to 54%, 37%, 8% of CALR-low (P= .008). We found no difference in age, gender, constitutional symptoms, splenomegaly, arterial and venous thrombosis at diagnosis and FU, IPSET revised risk stratification, and bleeding events. Hemoglobin was lower (12.8 g/dL (8.4-14.0) versus 13.6 (10.1-16.0); P=.02), while leukocytes and platelets did not differ. The proportion of pts with additional mutations in myeloid genes was significantly greater in CALR-high pts compared to CALR-low (66.7% vs 30.2%; P=0.01), as it was the proportion of pts with >2 mut myeloid genes (25% vs 11.6%, P=0.04). During FU, 52% of CALR-high pts (n=11) transformed to MF compared to 15% (n=39) of CALR-low (P<.0001); AML and death not differ. Anemia (<10g/dL) during the FU developed in 69% of CALR-high pts vs 18%, leukocytosis (>15x10 9/L) in 46% vs 8% and splenomegaly (greater than 5 cm from LCM) in 50% vs 12% (P<.0001 for all). The HR for anemia-free survival was 2.87 (95%CI, 1.3-6.3), for leukocytosis HR 3.71 (95%CI, 1.3-10.5) and splenomegaly HR 3.40 (95%CI, 1.2-9.2), all P<.01. MFS was significantly shorter in T1 (HR 2.0; P=0.04) or T3 (HR 2.7; P=0.03) using T2 as reference. Finally, we compared C ALR-mut, JAK2V617F mut and triple-negative (TN) ET pts. ROC analysis indicated a JAK2VAF >35% ( JAK2-high) as the best cutoff for shorter MFS. As in Fig. 1B, the MFS survival of CALR-high and JAK2-high was superimposable, and significantly shorter that in CALR/JAK2-low and TN pts. Conclusions. A CALR VAF >60% in pts with ET is associated with greater risk and shorter time to MF progression, development of anemia and splenomegaly. Similar findings in JAK2-high pts reinforce that that accumulation of mutated CALR and JAK2 alleles, evident since diagnosis, is detrimental for evolution to post-ET myelofibrosis. Longitudinal studies after diagnosis might provide further information about the kinetics of allele accumulation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.015
GPT teacher head0.304
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations1
Published2023
Admission routes2
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