Evidence map›Paper›PMID 36470668›Full record

ArticleAging2022

A risk score for the prognosis prediction of the muscle-invasive bladder cancer patients who received gemcitabine plus cisplatin chemotherapy.

Yupeng Guo, Jing Dong, Tao Ji, Xiaoxia Li, Shengzhong Rong, Hongjun Guan

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Aging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 72% 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

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. 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

6 authors at 1 institution in 1 country.

Yupeng GuoDepartment of Epidemiology and Statistics, School of Public Health of Mudanjiang Medical University, Mudanjiang, Heilongjiang Province 157011, China.
Jing DongDepartment of Epidemiology and Statistics, School of Public Health of Mudanjiang Medical University, Mudanjiang, Heilongjiang Province 157011, China.
Tao JiDepartment of Epidemiology and Statistics, School of Public Health of Mudanjiang Medical University, Mudanjiang, Heilongjiang Province 157011, China.
Xiaoxia LiDepartment of Epidemiology and Statistics, School of Public Health of Mudanjiang Medical University, Mudanjiang, Heilongjiang Province 157011, China.
Shengzhong RongDepartment of Epidemiology and Statistics, School of Public Health of Mudanjiang Medical University, Mudanjiang, Heilongjiang Province 157011, China.
Hongjun GuanDepartment of Epidemiology and Statistics, School of Public Health of Mudanjiang Medical University, Mudanjiang, Heilongjiang Province 157011, China.
Mudanjiang Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To develop an individualized gene-based risk score to predict the prognosis of muscle-invasive bladder cancer (MIBC) patients who received GC regimens. We downloaded transcriptome profiling data and clinical information from the Cancer Genome Atlas (TCGA) database. We identified 1854 survival-associated genes and then constructed the risk score based on six special genes selected from the survival-associated genes. We divided patients into high-risk and low-risk groups according to the median risk score. High-risk patients have significantly poorer overall survival than low-risk patients (log-rank test chi-square = 38.08,

Indexed as

CisplatinUrinary Bladder NeoplasmsGemcitabineHumansMusclesPrognosisRisk FactorsCisplatinGemcitabinebladder cancerchemotherapycisplatingemcitabineprognosis

Identifiers

PMID36470668
PMCPMC9792215
OpenAlexW4310782013

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.