Evidence map›Paper›PMID 27502092›Full record

ReviewCurrent hematologic malignancy reports2016

Improving Prognostic Modeling in Myelodysplastic Syndromes.

Aziz Nazha, Mikkael A Sekeres

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current hematologic malignancy reports, 2016. 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
0.5field-weighted citation impact, top 31% 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, 4 citations in OpenAlex.

  1. Review
  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

2 authors at 1 institution in 1 country.

Aziz NazhaLeukemia Program, Department of Hematology and Medical Oncology, Taussig Cancer Institute, Cleveland Clinic, Desk R35 9500 Euclid Ave, Cleveland, OH, 44195, USA. nazhaa@ccf.org.
Mikkael A SekeresLeukemia Program, Department of Hematology and Medical Oncology, Taussig Cancer Institute, Cleveland Clinic, Desk R35 9500 Euclid Ave, Cleveland, OH, 44195, USA.
Cleveland Clinic · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Myelodysplastic syndromes (MDSs) are a heterogeneous group of disorders characterized by the accumulation of complex genetic alterations that drive disease pathogenesis and outcome. Several prognostic models have been developed over the last two decades to risk stratify patients with MDS. These models mainly used clinical variables including blast percentage, cytopenias, cytogenetics, transfusion dependency, and age. Recently, somatic mutations in specific genes have been shown to impact overall survival in MDS and can be incorporated into established prognostic models to improve their predictive abilities. Here, we review the advantages and disadvantages of established prognostic models in MDS and the impact of emerging data regarding the incorporation of somatic mutations in risk stratification.

Indexed as

CytogeneticsDNA MethylationHigh-Throughput Nucleotide SequencingHumansMutationMyelodysplastic SyndromesPrognosisRNA SplicingTranscription FactorsTranscription FactorsCytogeneticsCytopeniasMyelodysplastic syndromesTransfusion dependency

Identifiers

PMID27502092
OpenAlexW2511882227

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.