Evidence map›Paper›PMID 33151129›Full record

ArticleCancer biology & therapy2020

A novel prognostic biomarker for muscle invasive bladder urothelial carcinoma based on 11 DNA methylation signature.

Yueyi Feng, Yiqing Jiang, Qingting Feng, Lingkai Xu, Yun Jiang, Fang Meng, Xiaochen Shu

Open access · bronzeAbstract read
In one paragraph

Article in Cancer biology & therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 35% 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

3 citing papers in PubMed, 4 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

7 authors at 3 institutions in 1 country.

Yueyi FengDepartment of Epidemiology, School of Public Health, Medical College of Soochow University , Suzhou, China.
Yiqing JiangDepartment of General Surgery, Harrison International Peace Hospital , Hengshui, China.
Qingting FengDepartment of Epidemiology, School of Public Health, Medical College of Soochow University , Suzhou, China.
Lingkai XuDepartment of Epidemiology, School of Public Health, Medical College of Soochow University , Suzhou, China.
Yun JiangDepartment of Epidemiology, School of Public Health, Medical College of Soochow University , Suzhou, China.
Fang MengCentre of Systems Medicine, Chinese Academy of Medical Sciences , Beijing, China.
Xiaochen ShuDepartment of Epidemiology, School of Public Health, Medical College of Soochow University , Suzhou, China.
Soochow University · CNHarrison International Peace Hospital · CNSuzhou Institute of Systems Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Muscle-invasive bladder urothelial carcinoma (MIBC) is a highly invasive cancer, which leads to prevalent recurrence and poor prognosis. Exploring the association of DNA methylation and the prognosis of MIBC will thus be of important value in clinical management and treatment. Bumphunter method and adaptive lasso regression were used to explore the relationship between different methylation regions (DMRs) and the prognosis of MIBC. Next, we constructed a risk prognosis model and validated this model. Moreover, the performance of this risk model was examined by using time-dependent receiver operating characteristic curve (ROC). We identified 58,449 different methylation sites and 490 different methylation regions. Among them, 11 DMRs were associated with the prognosis of MIBC through rigorous screening. Through the linear combination of 11 DMRs, a putative marker was developed, which can distinguish the survival risk in both the training dataset (HR = 2.58, 95% CI = (1.64, 4.05)) and the verification dataset (HR = 2.77, 95% CI = (1.25, 6.15)). Relatively high predictive values were observed from this model for training dataset (AUC = 0.791) and verification dataset (AUC = 0.668). Stratified analysis showed that the association was independent of gender. A nomogram was additionally generated to predict 5-year survival probability containing risk score and pathological stage. Its performance was evaluated by applying calibration curve. The methylation signature risk model based on 11 DMRs may be a reliable prognostic signature for MIBC, which provides new insights into development of individualized therapy for MIBC.

Indexed as

Biomarkers, TumorDNA MethylationHumansMiddle AgedPrognosisRisk FactorsSurvival AnalysisUrinary Bladder NeoplasmsBiomarkers, TumormethylationMuscle invasive bladder urothelial carcinoma (MIBC)nomogramprognosticrisk model

Identifiers

PMID33151129
PMCPMC7722798
OpenAlexW3096243273

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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.