Evidence map›Paper›PMID 33437216›Full record

ArticleInternational journal of medical sciences2021

Prognosis Prediction for Colorectal Cancer Patients: A Risk Score Based on The Metabolic-Related Genes.

Yongqu Lu, Xin Zhou, Zhenzhen Liu, Wendong Wang, Siyi Lu, Wei Fu

Abstract readValidation Study
In one paragraph

Article in International journal of medical sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Yongqu LuDepartment of General Surgery, Peking University Third Hospital, Beijing, 100191, China.
Xin ZhouDepartment of General Surgery, Peking University Third Hospital, Beijing, 100191, China.
Zhenzhen LiuDepartment of General Surgery, Peking University Third Hospital, Beijing, 100191, China.
Wendong WangDepartment of General Surgery, Peking University Third Hospital, Beijing, 100191, China.
Siyi LuDepartment of General Surgery, Peking University Third Hospital, Beijing, 100191, China.
Wei FuDepartment of General Surgery, Peking University Third Hospital, Beijing, 100191, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Risk assessment has high prognostic value in patients with colorectal cancer (CRC), and the use of proper models is an effective approach frequently used to evaluate cancer progression for further treatment plans. Alterations in metabolism are confirmed to be a significant feature of tumor cells and have been an intense focus in disease research. Here, we mined the genes that were differentially expressed in CRC tissues compared to paired normal samples from a public database and then constructed a novel assessment system for the prognosis of patients based on the value of a risk score considering the expression status of metabolism-related genes after screening. The score successfully stratified patients by risk and was externally verified in our study. Moreover, we built a nomogram combining the score and clinical parameters to predict patient survival using a visual method. The results suggested that the risk score was well fit and could provide assistance for the individual treatment of CRC patients in the clinic.

Indexed as

NomogramsBiomarkers, TumorColorectal NeoplasmsDatabases, GeneticDatasets as TopicDNA Copy Number VariationsGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimateMetabolic Networks and PathwaysMutationRisk AssessmentRisk FactorsRNA-SeqROC CurveBiomarkers, Tumorbioinformaticscolorectal cancermetabolic-related geneprediction modelrisk score

Identifiers

PMID33437216
PMCPMC7797536

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.