Evidence map›Paper›PMID 38589358›Full record

ArticleNature communications2024

Integration of pathologic characteristics, genetic risk and lifestyle exposure for colorectal cancer survival assessment.

Junyi Xin, Dongying Gu, Shuwei Li, Sangni Qian, Yifei Cheng, Wei Shao, Shuai Ben, Silu Chen, Linjun Zhu, Mingjuan Jin and 6 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.1field-weighted citation impact, top 7% 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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Frontiers in pharmacology · 2024
    Review
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

16 authors at 4 institutions in 2 countries.

Junyi Xin *Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China.
Dongying Gu *Department of Oncology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
Shuwei Li *Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China.
Sangni Qian *Department of Epidemiology and Biostatistics at School of Public Health, Zhejiang University School of Medicine, Hangzhou, China.
Yifei ChengDepartment of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China.
Wei ShaoDepartment of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China.
Shuai BenDepartment of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China.
Silu ChenDepartment of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China.
Linjun ZhuDepartment of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Mingjuan JinDepartment of Epidemiology and Biostatistics at School of Public Health, Zhejiang University School of Medicine, Hangzhou, China.
Kun ChenDepartment of Epidemiology and Biostatistics at School of Public Health, Zhejiang University School of Medicine, Hangzhou, China.
Zhibin HuDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.ORCID http://orcid.org/0000-0002-8277-5234
Zhengdong ZhangDepartment of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China.
Mulong DuDepartment of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.ORCID http://orcid.org/0000-0002-2733-6490
Hongbing ShenDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.ORCID http://orcid.org/0000-0002-2581-5906
Meilin WangDepartment of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China. mwang@njmu.edu.cn.ORCID http://orcid.org/0000-0002-4996-958X
Nanjing Medical University · CNSecond Affiliated Hospital of Zhejiang University · CNJiangsu Province Hospital · CNMinistry of Education · KR

Funding

National Natural Science Foundation of China (National Science Foundation of China) 81822039National Natural Science Foundation of China (National Science Foundation of China) 82073631
6 · The paper itself

Abstract

The development of an effective survival prediction tool is key for reducing colorectal cancer mortality. Here, we apply a three-stage study to devise a polygenic prognostic score (PPS) for stratifying colorectal cancer overall survival. Leveraging two cohorts of 3703 patients, we first perform a genome-wide survival association analysis to develop eight candidate PPSs. Further using an independent cohort with 470 patients, we identify the 287 variants-derived PPS (i.e., PPS

Indexed as

Colorectal NeoplasmsHumansLife StyleProportional Hazards ModelsRisk FactorsSurvival Rate

Identifiers

PMID38589358
PMCPMC11002003
OpenAlexW4394565604

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.