Evidence map›Paper›PMID 29890777›Full record

ReviewInternational journal of molecular sciences2018

Potential Clinical Application of Genomics in Multiple Myeloma.

Cinnie Yentia Soekojo, Sanjay de Mel, Melissa Ooi, Benedict Yan, Wee Joo Chng

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Journal of Cancer · 2019
    Article
  4. Future in the Past:International journal of molecular sciences · 2018
    Article
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.

Cinnie Yentia SoekojoDepartment of Hematology-Oncology, National University Cancer Institute, Singapore, National University Health System, 1E Kent Ridge Road, Singapore 119228, Singapore. cinnie_yentia_soekojo@nuhs.edu.sg.
Sanjay de MelDepartment of Hematology-Oncology, National University Cancer Institute, Singapore, National University Health System, 1E Kent Ridge Road, Singapore 119228, Singapore. sanjay_widanalage@nuhs.edu.sg.
Melissa OoiDepartment of Hematology-Oncology, National University Cancer Institute, Singapore, National University Health System, 1E Kent Ridge Road, Singapore 119228, Singapore. melissa_ooi@nuhs.edu.sg.
Benedict YanDepartment of Laboratory Medicine, National University Hospital, National University Health System, 5 Lower Kent Ridge Road, Singapore 119074, Singapore. benedict_yan@nuhs.edu.sg.
Wee Joo ChngDepartment of Hematology-Oncology, National University Cancer Institute, Singapore, National University Health System, 1E Kent Ridge Road, Singapore 119228, Singapore. mdccwj@nus.edu.sg.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple myeloma is a heterogeneous disease with different characteristics, and genetic aberrations play important roles in this heterogeneity. Studies have shown that these genetic aberrations are crucial in prognostication and response assessment; recent efforts have focused on their possible therapeutic implications. Despite many emerging studies being published, the best way to incorporate these results into clinical practice remains unclear. In this review paper we describe the different genomic techniques available, including the latest advancements, and discuss the potential clinical application of genomics in multiple myeloma.

Indexed as

GenomicsHumansLiquid BiopsyMultiple MyelomaNeoplasm, ResidualPrognosisSingle-Cell Analysisgene expression profilinggenomicsmultiple myeloma

Identifiers

PMID29890777
PMCPMC6032230

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.