Evidence map›Paper›PMID 30504292›Full record

ReviewHematology. American Society of Hematology. Education Program2018

Challenges and implications of genomics for T-cell lymphomas.

Eric D Jacobsen, David M Weinstock

Open access · bronzeAbstract readReview
In one paragraph

Review in Hematology. American Society of Hematology. Education Program, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

8 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Emerging strategies in peripheral T-cell lymphoma.Hematology. American Society of Hematology. Education Program · 2019
    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

2 authors at 2 institutions in 1 country.

Eric D JacobsenDepartment of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA; and.
David M WeinstockDepartment of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA; and.
Broad Institute · USDana-Farber Cancer Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Treatment outcomes for patients with peripheral T-cell lymphomas (PTCLs) and advanced-stage cutaneous T-cell lymphomas (CTCLs) remain poor. The past few years have witnessed an explosion in our understanding of the genetics of these diverse malignancies. Many subtypes harbor highly recurrent mutations, including single-nucleotide variants, insertions/deletions, and chromosomal rearrangements, that affect T-cell receptor signaling, costimulatory molecules, JAK/STAT and phosphatidylinositol 3-kinase pathways, transcription factors, and epigenetic modifiers. An important subset of these mutations is included within commercially available, multigene panels and, in rare circumstances, indicate therapeutic targets. However, current preclinical and clinical evidence suggests that only a minority of mutations identified in TCLs indicate biologic dependence. With a few exceptions that we highlight, mutations identified in TCLs should not be routinely used to select targeted therapies outside of a clinical trial. Participation in trials and publication of both positive and negative results remain the most important mechanisms for improving patient outcomes.

Indexed as

MutationGenomicsHumansLymphoma, T-Cell, PeripheralNeoplasm ProteinsReceptors, Antigen, T-CellSignal TransductionNeoplasm ProteinsReceptors, Antigen, T-Cell

Identifiers

PMID30504292
PMCPMC6246015
OpenAlexW2902280735

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.