Evidence map›Paper›PMID 32194666›Full record

ArticleOncology letters2020

Increased ski expression levels are associated with a higher risk and poor prognosis in patients with gastrointestinal stromal tumors.

Qiu-Shi Wang, Yu Zhai, Ping Li, Hua-Liang Xiao, Yuan-Guo Zhou

Abstract read
In one paragraph

Article in Oncology letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Qiu-Shi WangMolecular Biology Center, State Key Laboratory of Trauma, Burn and Combined Injury, Research Institute of Surgery and Daping Hospital, The Army Medical University, Chongqing 400042, P.R. China.
Yu ZhaiMolecular Biology Center, State Key Laboratory of Trauma, Burn and Combined Injury, Research Institute of Surgery and Daping Hospital, The Army Medical University, Chongqing 400042, P.R. China.
Ping LiMolecular Biology Center, State Key Laboratory of Trauma, Burn and Combined Injury, Research Institute of Surgery and Daping Hospital, The Army Medical University, Chongqing 400042, P.R. China.
Hua-Liang XiaoDepartment of Pathology, Daping Hospital and Research Institute of Surgery, The Army Medical University, Chongqing 400042, P.R. China.
Yuan-Guo ZhouMolecular Biology Center, State Key Laboratory of Trauma, Burn and Combined Injury, Research Institute of Surgery and Daping Hospital, The Army Medical University, Chongqing 400042, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gastrointestinal stromal tumors (GISTs) are the most commonly diagnosed primary mesenchymal tumors of the gastrointestinal tract and 30% of GISTs are associated with a high recurrence risk or metastasis. The current risk classification criteria of the National Comprehensive Cancer Network are based on tumor size, mitotic activity and localization. Investigating additional biomarkers associated with clinical risk may aid in the diagnosis of GIST and improves prediction of patient prognosis. In the present study, the value of using the expression levels of the oncoprotein ski as a prognostic predictor for GISTs was investigated. The results demonstrated that high ski expression levels were correlated with high risk and recurrence rates and indicated poor prognosis regarding median disease-free survival. Overall, the present study suggests that ski expression levels may serve as a predictor for clinical risk and prognosis of patients with GISTs.

Indexed as

gastrointestinal stromal tumorsprognosisrisk classificationski

Identifiers

PMID32194666
PMCPMC7039079

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.