Evidence map›Paper›PMID 40814364›Full record

ArticleAmerican journal of cancer research2025

Transcripts of splicing factors with time-varying associations with survival outcomes in colorectal cancer.

Yajun Yu, Yingla Li, Lu Ma, Huilin Chen, Yiran Peng, Haiqiong Yang, Qiuting Li, Xiaoping Gao, Jianguo Feng, Yang Yu and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in American journal of cancer research, 2025. 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
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

1 citing paper in PubMed.

  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

14 authors.

Yajun YuKey Laboratory of Medical Electrophysiology, Ministry of Education, Institute of Cardiovascular Research and Institute of Metabolic Diseases, Southwest Medical University Luzhou 646000, Sichuan, China.
Yingla LiSchool of Pharmacy, Southwest Medical University Luzhou 646000, Sichuan, China.
Lu MaDepartment of Neonatology, Children's Medical Center, The Affiliated Hospital, Southwest Medical University Luzhou 646000, Sichuan, China.
Huilin ChenDepartment of Anesthesiology, The Affiliated Hospital, Southwest Medical University Luzhou 646000, Sichuan, China.
Yiran PengSchool of Pharmacy, Southwest Medical University Luzhou 646000, Sichuan, China.
Haiqiong YangDepartment of Cardiology, The Affiliated Hospital, Southwest Medical University Luzhou 646000, Sichuan, China.
Qiuting LiKey Laboratory of Medical Electrophysiology, Ministry of Education, Institute of Cardiovascular Research and Institute of Metabolic Diseases, Southwest Medical University Luzhou 646000, Sichuan, China.
Xiaoping GaoKey Laboratory of Medical Electrophysiology, Ministry of Education, Institute of Cardiovascular Research and Institute of Metabolic Diseases, Southwest Medical University Luzhou 646000, Sichuan, China.
Jianguo FengDepartment of Anesthesiology, The Affiliated Hospital, Southwest Medical University Luzhou 646000, Sichuan, China.
Yang YuDepartment of Cardiology, The Affiliated Hospital, Southwest Medical University Luzhou 646000, Sichuan, China.
Ying WanSchool of Basic Medical Science, Southwest Medical University Luzhou 646000, Sichuan, China.
Yan YangKey Laboratory of Medical Electrophysiology, Ministry of Education, Institute of Cardiovascular Research and Institute of Metabolic Diseases, Southwest Medical University Luzhou 646000, Sichuan, China.
Yan DengSchool of Basic Medical Science, Southwest Medical University Luzhou 646000, Sichuan, China.
Chunxiang ZhangKey Laboratory of Medical Electrophysiology, Ministry of Education, Institute of Cardiovascular Research and Institute of Metabolic Diseases, Southwest Medical University Luzhou 646000, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identifying variables with time-varying associations can help guide patient stratification and treatment strategies. Time-varying associations refer to the associations between variables of interest and the outcomes that change over time. Such associations of gene transcripts have never been examined in colorectal cancer (CRC). In the present study, we examined the transcripts of splicing factors and their associations with prognosis in CRC. We performed analyses using Cox PH models and Cox models with time-varying coefficients when appropriate. A transcript of pre-mRNA processing factor 38A (

Indexed as

Colorectal cancerprognosisproportional hazards (PH) assumptionPRPF38Asplicing factor transcriptstime-varying associations

Identifiers

PMID40814364
PMCPMC12344181

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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.