Evidence map›Paper›PMID 19537843›Full record

ReviewMolecular diagnosis & therapy2009

Genomic predictors of outcome and treatment response in breast cancer.

Lara Dunn, Angela Demichele

Abstract readReview
PubMed Publisher
In one paragraph

Review in Molecular diagnosis & therapy, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Article
  6. The metastasis-promoting roles of tumor-associated immune cells.Journal of molecular medicine (Berlin, Germany) · 2013
    Review
  7. Integrated genomic analysis of breast cancers.Balkan journal of medical genetics : BJMG · 2012
    Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Proteomics as a guiding tool for more effective personalized therapy.Annals of oncology : official journal of the European Society for Medical Oncology · 2010
    Review
  13. Review
  14. Article
  15. 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

2 authors.

Lara DunnAbramson Cancer Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Angela Demichele

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite advances in breast cancer treatment and outcome over the last two decades, women continue to relapse and die of advanced disease. Historically, estrogen and progesterone receptor expression, HER2 overexpression and clinico-pathologic parameters have guided therapeutic decision making. However, there are limits to the risk estimation provided by these parameters, leading to potential overtreatment of low-risk disease and undertreatment of poor-risk disease. Genomic technologies now provide the opportunity to refine our therapeutic approach by individualizing treatment to patients' individual tumor profiles. Gene profiles or signatures are groupings of genes that are differentially expressed between tumors, reflecting differences in biologic behavior. Prognostic gene signatures stratify breast cancer patients by tumor natural history, regardless of the treatment employed. Currently, there are three commercially available prognostic gene signatures: Oncotype DX (Genomic Health, Inc.), MammaPrint (Agendia BV), and the HOXB13/IL17BR (H/I) ratio; (Theros H/ISM; bioTheranostics). Others under development include the Intrinsic Gene Set, the Rotterdam Signature, the Wound Response Indicator, and the Invasive Gene Signature. Predicative signatures classify patients based on responsiveness to specific therapies. Of the prognostic signatures, Oncotype DX has been shown to have predictive value for the incremental benefit of chemotherapy when added to a hormonal therapy regimen. Additional genetic profiles under development predict response to specific hormonal therapies, anthracyclines, and taxanes. Gene signatures have the potential to transform breast cancer treatment as it becomes tailored to each patient's tumor expression profile and significantly improve the outcomes of this disease.

Indexed as

Gene Expression ProfilingAntineoplastic AgentsAntineoplastic Agents, HormonalBiomarkers, TumorBreast NeoplasmsChemotherapy, AdjuvantDrug Resistance, NeoplasmFemaleGene Expression Regulation, NeoplasticHumansTreatment OutcomeAntineoplastic AgentsAntineoplastic Agents, HormonalBiomarkers, Tumor

Identifiers

PMID19537843

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.