Evidence map›Paper›PMID 33365318›Full record

ArticleFrontiers in medicine2020

Integrating Tumor Stroma Biomarkers With Clinical Indicators for Colon Cancer Survival Stratification.

Yong Chen, Wenlong Wang, Bo Jiang, Lei Yao, Fada Xia, Xinying Li

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 26% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
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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

6 authors at 2 institutions in 1 country.

Yong ChenDepartment of General Surgery, Xiangya Hospital, Central South University, Changsha, China.
Wenlong WangDepartment of General Surgery, Xiangya Hospital, Central South University, Changsha, China.
Bo JiangDepartment of General Surgery, Xiangya Hospital, Central South University, Changsha, China.
Lei YaoDepartment of General Surgery, Xiangya Hospital, Central South University, Changsha, China.
Fada XiaDepartment of General Surgery, Xiangya Hospital, Central South University, Changsha, China.
Xinying LiDepartment of General Surgery, Xiangya Hospital, Central South University, Changsha, China.
Xiangya Hospital Central South University · CNCentral South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The tumor stroma plays an important role in tumor progression and chemotherapeutic resistance; however, its role in colon cancer (CC) survival prognosis remains to be investigated. Here, we identified tumor stroma biomarkers and evaluated their role in CC prognosis stratification. Four independent datasets containing a total of 1,313 patients were included in this study and were divided into training and testing sets. Stromal scores calculated using the estimation of stromal and immune cells in malignant tumors using expression data (ESTIMATE) algorithm were used to assess the tumor stroma level. Kaplan-Meier curves and the log-rank test were used to identify relationships between stromal score and prognosis. Tumor stroma biomarkers were identified by cross-validation of multiple datasets and bioinformatics methods. Cox proportional hazards regression models were constructed using four prognosis factors (age, tumor stage, the ESTIMATE stromal score, and the biomarker stromal score) in different combinations for prognosis prediction and compared. Patients with high stromal scores had a lower overall survival rate (

Indexed as

colon cancerimmune cellsmicroenvironmentprognosis stratificationtumor stroma

Identifiers

PMID33365318
PMCPMC7750539
OpenAlexW3112180660

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.