ReviewInternational journal of hematology2004
Molecular signatures of lymphoma.
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.
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.
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.
Who cites it
3 citing papers in PubMed.
- Non-Hodgkin lymphoma in women: reproductive factors and exogenous hormone use.American journal of epidemiology · 2008Article
- Applications of machine learning in cancer prediction and prognosis.Cancer informatics · 2007Article
- The use of microarray technologies in clinical oncology.Journal of translational medicine · 2006Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
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
Identifiers
15646650What OpenQuestion holds
Registered trials
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.