Evidence mapPaperPMID 42434282Full record

ArticleJournal of gastrointestinal oncology2026

Identification and preliminary examination of prognostic genes linked to calcium metabolism in colorectal cancer.

Chao Liang, Xiao-Jiang Yi, Jia-Li Liu, Hai-Peng Huang, Tian-Ming Jiang, Jing-Fang Diao

Abstract read
In one paragraph

Article in Journal of gastrointestinal oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

6 authors.

Chao Liang *Department of Colorectal Surgery, Guangdong Provincial Hospital of Chinese Medicine (The Second Affiliated Hospital of Guangzhou University of Chinese Medicine), Guangzhou, China.
Xiao-Jiang Yi *Department of Colorectal Surgery, Guangdong Provincial Hospital of Chinese Medicine (The Second Affiliated Hospital of Guangzhou University of Chinese Medicine), Guangzhou, China.
Jia-Li Liu *Department of Colorectal Surgery, Guangdong Provincial Hospital of Chinese Medicine (The Second Affiliated Hospital of Guangzhou University of Chinese Medicine), Guangzhou, China.
Hai-Peng HuangDepartment of Colorectal Surgery, Guangdong Provincial Hospital of Chinese Medicine (The Second Affiliated Hospital of Guangzhou University of Chinese Medicine), Guangzhou, China.
Tian-Ming JiangDepartment of Colorectal Surgery, Guangdong Provincial Hospital of Chinese Medicine (The Second Affiliated Hospital of Guangzhou University of Chinese Medicine), Guangzhou, China.
Jing-Fang DiaoDepartment of Colorectal Surgery, Guangdong Provincial Hospital of Chinese Medicine (The Second Affiliated Hospital of Guangzhou University of Chinese Medicine), Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Colorectal cancer (CRC) is a substantial global health challenge due to high mortality rates. This study focused on constructing and validating a calcium metabolism-related genes (CAMRGs) signature for CRC outcome prediction. Methods: Transcriptomic and clinical data for CRC were integrated from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A prognostic risk model was constructed using least absolute shrinkage and selection operator (LASSO)-Cox regression analysis. The predictive performance of the model was validated using an external dataset (GSE17536). Furthermore, the expression levels of the identified prognostic genes were preliminarily assessed via reverse transcription-quantitative polymerase chain reaction (RT-qPCR) in clinical specimens. Results: Conclusions: A CAMRG signature was developed and preliminary examination of CRC prognosis prediction. This model might assist in risk assessment and inform individualized treatment strategies.

Indexed as

calcium metabolismclinical relevanceColorectal cancer (CRC)prognosissurvival prediction

Identifiers

PMID42434282
PMCPMC13350268

What Socratic holds

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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 Socratic graph.