Evidence map›Paper›PMID 28878809›Full record

ReviewCellular & molecular biology letters2017

Are online prediction tools a valid alternative to genomic profiling in the context of systemic treatment of ER-positive breast cancer?

Umar Wazir, Kinan Mokbel, Amtul Carmichael, Kefah Mokbel

Open access · goldAbstract readReview
In one paragraph

Review in Cellular & molecular biology letters, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 33% 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

5 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Correlation ofCancer genomics & proteomics
    Article
  5. 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

4 authors at 1 institution in 1 country.

Umar WazirThe London Breast Institute, Princess Grace Hospital, 45 Nottingham Place, London, W1U 5NY UK.ORCID 0000-0001-8979-692X
Kinan MokbelThe London Breast Institute, Princess Grace Hospital, 45 Nottingham Place, London, W1U 5NY UK.
Amtul CarmichaelThe London Breast Institute, Princess Grace Hospital, 45 Nottingham Place, London, W1U 5NY UK.
Kefah MokbelThe London Breast Institute, Princess Grace Hospital, 45 Nottingham Place, London, W1U 5NY UK.
The Princess Grace Hospital · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundClinicians use clinical and pathological parameters, such as tumour size, grade and nodal status, to make decisions on adjuvant treatments for breast cancer. However, therapeutic decisions based on these features tend to vary due to their subjectivity. Computational and mathematical algorithms were developed using clinical outcome data from breast cancer registries, such as Adjuvant! Online and NHS PREDICT. More recently, assessments of molecular profiles have been applied in the development of better prognostic tools.

methodsBased on the available literature on online registry-based tools and genomic assays, we evaluated whether these online tools could be valid and accurate alternatives to genomic and molecular profiling of the individual breast tumour in aiding therapeutic decisions, particularly in patients with early ER-positive breast cancer. RESULTS AND

conclusionsEarly breast cancer is currently considered a systemic disease and a complex ecosystem with behaviour determined by the complex genetic and molecular signatures of the tumour cells, mammary stem cells, microenvironment and host immune system. We anticipate that molecular profiling will continue to evolve, expanding beyond the primary tumour to include the tumour microenvironment, cancer stem cells and host immune system. This should further refine therapeutic decisions and optimise clinical outcome. This article was specially invited by the editors and represents work by leading researchers.

Indexed as

SoftwareBreast NeoplasmsFemaleGene Expression ProfilingGenomicsHumansOnline SystemsPrognosisBreast cancerGene expression regulationGenomic assayMolecular biotechnologyPrognosis

Identifiers

PMID28878809
PMCPMC5583984
OpenAlexW2751627529

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.