Evidence map›Paper›PMID 24881041›Full record

ArticleHaematologica2014

Clinical and genetic predictors of prognosis in myelodysplastic syndromes.

Rafael Bejar

Abstract read
In one paragraph

Article in Haematologica, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
–field-weighted citation impact
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

45 citing papers in PubMed.

  1. Trial
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  11. Clinical and Genomic Profiles of Korean Patients withAnnals of laboratory medicine · 2022
    Article
  12. Article
  13. Circulating tumor DNA: a noninvasive biomarker for tracking ovarian cancer.Reproductive biology and endocrinology : RB&E · 2021
    Review
  14. Molecular Targeted Therapy and Immunotherapy for Myelodysplastic Syndrome.International journal of molecular sciences · 2021
    Review
  15. Review
  16. Somatic mosaicism in inherited bone marrow failure syndromes.Best practice & research. Clinical haematology · 2021
    Review
  17. Review
  18. Review
  19. Article
  20. 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

1 author.

Rafael BejarMoores Cancer Center, Division of Hematology and Oncology, University of California, San Diego, La Jolla, CA, USA rabejar@ucsd.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Myelodysplastic syndromes are a collection of clonal hematopoietic disorders with a wide range of clinical manifestations and eventual outcomes. Accurate prediction of a patient's prognosis is useful to define the risk posed by the disease and which treatment options are most appropriate. Several models have been created to help predict the prognosis for patients with myelodysplastic syndromes. The International Prognostic Scoring System (IPSS) has been the standard tool used to risk stratify MDS patients since its publication in 1997. Other models have since been created to improve upon the IPSS, including the recent Revised International Prognostic Scoring System. Most models include the presence or severity of peripheral blood cytopenias, the proportion of bone marrow blasts, and specific karyotype abnormalities. Other factors including age, performance status, co-morbidities, transfusion dependence, and molecular biomarkers can further refine the prediction of prognosis in some models. Novel, disease specific biomarkers with prognostic value in myelodysplastic syndromes including cell surface markers, gene expression profiles, and high resolution copy number analyses have been proposed but not yet adopted clinically. Somatic abnormalities in recurrently mutated genes are the most informative prognostic biomarkers not currently considered by clinical risk models. Mutations in specific genes have independent prognostic significance and, unlike cytogenetic abnormalities, are present in the majority of myelodysplastic syndrome cases. However, mutational information can be complex and there are challenges to its clinical implementation. Despite these limitations, DNA sequencing can refine the prediction of prognosis for myelodysplastic syndrome patients and has become increasingly available in the clinic where it will help improve the care of patients with myelodysplastic syndromes.

Indexed as

Genetic MarkersHumansMyelodysplastic SyndromesPrognosisGenetic Markers

Identifiers

PMID24881041
PMCPMC4040892

What OpenQuestion holds

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Registered trials

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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.