Evidence map›Paper›PMID 32535855›Full record

ArticleInternational journal of hematology2020

Genomic characterization and prognostication applied to a Brazilian cohort of patients with myelofibrosis.

Alexandre Nonino, Paulo Vidal Campregher, Fabio Pires de Souza Santos, Juliana Forte Mazzeu, Rinaldo Wellerson Pereira

Abstract read
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In one paragraph

Article in International journal of hematology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 38% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Real-world genomic profiling of acute myeloid leukemia and the impact of European LeukemiaNet risk stratification 2022 update.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2023
    Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 1 country.

Alexandre NoninoSecretaria de Saude do Distrito Federal, Brasilia, Brazil. nonino@cettro.com.br.ORCID http://orcid.org/0000-0002-2430-9593
Paulo Vidal CampregherHospital Israelita Albert Einstein, São Paulo, Brazil.
Fabio Pires de Souza SantosHospital Israelita Albert Einstein, São Paulo, Brazil.
Juliana Forte MazzeuFaculdade de Medicina da Universidade de Brasilia, Brasilia, Brazil.
Rinaldo Wellerson PereiraEscola de Saude e Medicina da Universidade Catolica de Brasilia, Brasilia, Brazil.
Hospital Israelita Albert Einstein · BRGoverno do Distrito Federal · BRUniversidade Católica de Brasília · BRUniversidade de Brasília · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genomic characterization of patients with myeloproliferative neoplasms (MPN) may lead to better diagnostic classification, prognostic assessment, and treatment decisions. These goals are particularly important in myelofibrosis (MF). We performed target Next Generation Sequencing for a panel of 255 genes and Chromosome Microarray Analysis (CMA) in 27 patients with MF. Patients were classified according to genomic findings and we compared the performance of a personalized prognostication system with IPSS, MIPSS70 and MIPSS70 + v2. Twenty-six patients presented mutations: 11.1% had single driver mutations in either JAK2, CALR or MPL; 85.2% had mutations in non-restricted genes (median: 2 per patient). CMA was abnormal in 91.7% of the 24 cases with available data. Copy-Number-Neutral Loss-of-Heterozygosity was the most common finding (66.7%). Del13q was the most frequent copy number variation, and we could define a 2.4 Mb minimally affected region encompassing RB1, SUCLA2 and CLLS2 loci. The largest genomic subgroup consisted of patients with mutations in genes involved with chromatin organization and splicing control (40.7%) and the personalized system showed better concordance and accuracy than the other prognostic systems. Comprehensive genomic characterization reveals the striking genetic complexity of MF and, when combined with clinical data, led, in our cohort, to better prognostication performance.

Indexed as

DNA Copy Number VariationsGenomicsAdultAgedAged, 80 and overBrazilCalcium-Binding ProteinsCalreticulinCell Adhesion MoleculesCohort StudiesFemaleHigh-Throughput Nucleotide SequencingHumansJanus Kinase 2Loss of HeterozygosityMaleCalcium-Binding ProteinsCalreticulinCALR protein, humanCell Adhesion MoleculesEDIL3 protein, humanJAK2 protein, humanJanus Kinase 2Cancer genesDeveloping countriesMyeloproliferative neoplasmsPrimary myelofibrosisPrognostic factors

Identifiers

PMID32535855
OpenAlexW3035058406

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.