Evidence map›Paper›PMID 15095022›Full record

ReviewEuropean journal of nuclear medicine and molecular imaging2004

Biomolecular features of clinical relevance in breast cancer.

Maria Grazia Daidone, Angelo Paradiso, Massimo Gion, Nadia Harbeck, Fred Sweep, Manfred Schmitt

Abstract readReview
PubMed Publisher
In one paragraph

Review in European journal of nuclear medicine and molecular imaging, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

1 citing paper in PubMed, 19 citations in OpenAlex.

  1. 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

6 authors at 5 institutions in 3 countries.

Maria Grazia DaidoneResearch Unit # 10, Department of Experimental Oncology, Istituto Nazionale Tumori, Via Venezian 1, 20133 Milan, Italy. mariagrazia.daidone@istitutotumori.mi.it
Angelo Paradiso
Massimo Gion
Nadia Harbeck
Fred Sweep
Manfred Schmitt
Technical University of Munich · DEFondazione IRCCS Istituto Nazionale dei Tumori · ITIstituto Oncologico Veneto · ITOspedale Civile di Venezia · ITRadboud University Medical Center · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer is a heterogeneous disease and its consequent complexity is a major challenge for physicians and biologists. Notwithstanding its potential curability due to the availability of treatment modalities which are effective in the presence of favourable clinical or pathobiological features, there is still a great deal of controversy over its clinical management. In recent decades, tumour biomarkers that are indicative of or related to cell traits characterising malignancy--that is self-sufficiency in proliferative growth signals, insensitivity to growth inhibitory signals, evasion of apoptosis, limitless replicative potential, and activation of pathways leading to neo-angiogenesis, invasion and metastasis--have provided information that has been proven to be associated with disease progression. However, when these biomarkers have been analysed individually, their prognostic relevance has been found to be modest, the only remaining clinically useful biomarkers being cell proliferation and plasminogen activation-related factors for prognosis, and steroid hormone receptors and the oncogene HER2/neu for prediction of response to hormonal therapy or to the novel targeted anti-HER2/neu therapy. It therefore remains necessary to reduce the intrinsic complexity of breast cancer in order to improve its clinical outcome. One way to achieve this objective derives directly from the concept that cancer is a genetic disease at the somatic level and from the recent availability of high-throughput post-genomic analytical tools such as gene and protein expression techniques for global gene expression analysis. Following these novel approaches, a number of recent studies have produced gene expression profiles in breast cancer that are markedly associated with disease progression and directed to answer different clinical and biological questions. However, the outcome of these novel studies still needs to be validated, which will entail cooperation between different specialists and integration of all the different skills involved in translational research in oncology.

Indexed as

Biomarkers, TumorBreast NeoplasmsClinical MedicineFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMolecular BiologyNeoplasm ProteinsTechnology Assessment, BiomedicalTechnology TransferBiomarkers, TumorNeoplasm Proteins

Identifiers

PMID15095022
OpenAlexW2028909185

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.