Evidence map›Paper›PMID 15646650›Full record

ReviewInternational journal of hematology2004

Molecular signatures of lymphoma.

Kerry J Savage, Randy D Gascoyne

Abstract readReview
PubMed Publisher
In one paragraph

Review in International journal of hematology, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. The use of microarray technologies in clinical oncology.Journal of translational medicine · 2006
    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.

Kerry J SavageDivision of aMedical Oncology, British Columbia Cancer Agency, Vancouver, British Columbia, Canada. ksavage@bccancer.bc.ca
Randy D Gascoyne

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hematologic malignancies have historically been characterized by morphologic, immunophenotypic, molecular, and genetic features. However, morphologically identical tumors can have clearly distinct clinical outcomes, suggesting underlying biological heterogeneity. Recent advances in microarray technology have helped the classification of lymphoid malignancies evolve to a new refined level. In addition to the discovery of new disease subclasses defined by unique molecular profiles, gene expression patterns can be correlated with specific genetic abnormalities and prognoses. Furthermore, the discovery of new disease subtypes has provided further insight into lymphoma biology and pathogenesis. Unique gene signatures can highlight key deregulated pathways that are active in molecular disease categories, and in some cases these findings have elucidated new targets for novel therapeutic approaches. This review summarizes the current status of molecular profiling in non-Hodgkin lymphomas. In this review, we have endeavored to include data from multiple investigator groups and tried to cover the breadth of lymphoid tumors, excluding acute and chronic leukemias.

Indexed as

Gene Expression ProfilingOligonucleotide Array Sequence AnalysisBiomarkers, TumorGene Expression Regulation, LeukemicHumansLymphoma, Non-HodgkinPrognosisBiomarkers, Tumor

Identifiers

PMID15646650

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.