Evidence map›Paper›PMID 27365083›Full record

ArticleMolecular diagnosis & therapy2016

Genetic Biomarkers to Identify the Risk of Osteonecrosis in Children with Acute Lymphoblastic Leukemia.

Marissa A H den Hoed, Saskia M F Pluijm, André G Uitterlinden, Rob Pieters, Marry M van den Heuvel-Eibrink

Abstract read
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Article in Molecular diagnosis & therapy, 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
–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

2 citing papers in PubMed.

  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

5 authors.

Marissa A H den HoedDepartment of Pediatric Oncology/Hematology, Erasmus MC-Sophia Children's Hospital Rotterdam, Dr. Molewaterplein 60, 3015 GJ, Rotterdam, The Netherlands.
Saskia M F PluijmDepartment of Pediatric Oncology/Hematology, Erasmus MC-Sophia Children's Hospital Rotterdam, Dr. Molewaterplein 60, 3015 GJ, Rotterdam, The Netherlands.
André G UitterlindenDepartment of Internal Medicine, Erasmus University Medical Centre Rotterdam, 's-Gravendijkwal 230, 3015 CE, Rotterdam, The Netherlands.
Rob PietersPrincess Maxima Centre for Pediatric Oncology, Lundlaan 6, 3584 EA, Utrecht, The Netherlands.
Marry M van den Heuvel-EibrinkDepartment of Pediatric Oncology/Hematology, Erasmus MC-Sophia Children's Hospital Rotterdam, Dr. Molewaterplein 60, 3015 GJ, Rotterdam, The Netherlands. m.m.vandenheuvel-eibrink@prinsesmaximacentrum.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Osteonecrosis is a disabling complication of treatment for pediatric acute lymphoblastic leukemia, and much effort has been made to predict which patients are prone to develop this disease. Multiple clinical and genetic factors have already been identified as being associated with osteonecrosis; however, a prediction model that combines pretreatment genetic biomarkers and clinical factors has not yet been designed. Such a prediction model can only be developed with continuing international collaborations and research efforts, including large genome-wide association studies.

Indexed as

Genetic MarkersBone Morphogenetic Protein 7ChildGenome-Wide Association StudyHomeodomain ProteinsHumansModels, BiologicalOsteonecrosisPlasminogen Activator Inhibitor 1Polymorphism, Single NucleotidePrecursor Cell Lymphoblastic Leukemia-LymphomaProspero-Related Homeobox 1 ProteinReceptors, N-Methyl-D-AspartateRisk FactorsTumor Suppressor ProteinsBMP7 protein, humanBone Morphogenetic Protein 7Genetic MarkersGRIN3A protein, humanHomeodomain ProteinsPlasminogen Activator Inhibitor 1Prospero-Related Homeobox 1 ProteinReceptors, N-Methyl-D-AspartateSERPINE1 protein, humanTumor Suppressor Proteins

Identifiers

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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.