Evidence map›Paper›PMID 23316390›Full record

ArticleISRN oncology2012

Biological markers and response to neoadjuvant taxane-based chemotherapy in patients with locally advanced breast cancer.

Mohamed I El-Sayed, Doaa W Maximous, Madeha M Zakhary, Nabiel N H Mikhail

Open access · diamondAbstract read
In one paragraph

Article in ISRN oncology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact, top 92% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. 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.

Mohamed I El-SayedDepartment of Radiation Oncology, South Egypt Cancer Institute, Assiut University, Assiut, Egypt.
Doaa W Maximous
Madeha M Zakhary
Nabiel N H Mikhail
Assiut University · EG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction. Biological markers as Her2/neu, p53, and hormonal receptors (HmRs) may be reliable parameters for prognostic assessment of patients of locally advanced breast cancer (LABC). This work aims at assessing the potential value of these biological markers for the prediction of disease outcome after neoadjuvant taxane-based chemotherapy and its implication on the surgical role. Patients and Methods. From March 2006 to September 2011, 95 patients with LABC were treated by neoadjuvant taxane-based chemotherapy given at intervals of 3 weeks. Expression of Her2/neu and p53 was examined in the initial tissue biopsy by using ELISA technique. Status of HmRs was determined using a commercial enzyme immunoassay. Three weeks after the third cycle, patients underwent surgical resection followed by 3 more cycles of taxane-based chemotherapy and radiotherapy as an adjuvant therapy. Relations of Her2/neu overexpression to p53, HmRs, and conventional prognostic factors were analyzed. Results. Median followup was 61 months. The 5-year DFS and OAS rates were significantly higher in patients with positive HmRs than in those with negative HmRs, patients with Her2- than those with Her2+ breast cancer, and patients with intact p53 breast cancer than those with inactive p53. HER-2 overexpression was statistically significant associated with loss of HmR positive immunostaining (P < 0.0001), grade III breast cancer (P < 0.0001), advanced nodal status (P = 0.0039), and younger (<50 years) age (P = 0.0108). Conclusion. Her2/neu overexpression was associated with poor DFS and OAS rates, as it was significantly associated with negative HmR and high grade.

Identifiers

PMID23316390
PMCPMC3536061
OpenAlexW2005199440

What OpenQuestion holds

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Registered trials

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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.