Evidence map›Paper›PMID 27143933›Full record

ArticleOncoTargets and therapy2016

AEG-1 as a predictor of sensitivity to neoadjuvant chemotherapy in advanced epithelial ovarian cancer.

Yao Wang, Xin Jin, Hongtao Song, Fanling Meng

Open access · goldAbstract read
In one paragraph

Article in OncoTargets and therapy, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 15% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

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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.

Yao WangDepartment of Gynecology and Obstetrics, The General Hospital of Daqing Oil Field, Daqing, People's Republic of China.
Xin JinDepartment of Intensive Care Unit, The General Hospital of Daqing Oil Field, Daqing, People's Republic of China.
Hongtao SongDepartment of Pathology, The Affiliated Tumor Hospital, Harbin Medical University, Harbin, People's Republic of China.
Fanling MengDepartment of Gynecology, The Affiliated Tumor Hospital, Harbin Medical University, Harbin, People's Republic of China.
Daqing Oilfield General Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesAstrocyte elevated gene-1 (AEG-1) plays a critical role in tumor progression and chemoresistance. The aim of the present study was to investigate the protein expression of AEG-1 in patients with epithelial ovarian cancer (EOC) who underwent debulking surgery after neoadjuvant chemotherapy (NAC). MATERIALS AND

methodsThe protein expression of AEG-1 was analyzed using immunohistochemistry in 162 patients with EOC. The relationship between AEG-1 expression and chemotherapy resistance was assessed using univariate and multivariate logistic regression analyses with covariate adjustments.

resultsHigh AEG-1 expression was significantly associated with the International Federation of Gynecology and Obstetrics stage, age, serum cancer antigen-125 concentration, histological grade, the presence of residual tumor after the interval debulking surgery, and lymph node metastasis. Furthermore, AEG-1 expression was significantly higher in NAC-resistant disease than in NAC-sensitive disease (P<0.05). Multivariate analyses indicated that elevated AEG-1 expression predicted poor survival.

conclusionOur findings indicate that AEG-1 may be a potential new biomarker for predicting chemoresistance and poor prognoses in patients with EOC.

Indexed as

AEG-1epithelial ovarian cancerinterval debulking surgeryneoadjuvant chemotherapy

Identifiers

PMID27143933
PMCPMC4844502
OpenAlexW2340470623

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.