Evidence map›Paper›PMID 32143723›Full record

ReviewJournal of translational medicine2020

Data-driven translational prostate cancer research: from biomarker discovery to clinical decision.

Yuxin Lin, Xiaojun Zhao, Zhijun Miao, Zhixin Ling, Xuedong Wei, Jinxian Pu, Jianquan Hou, Bairong Shen

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
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  14. The Emerging Roles of LINC00665 in Human Cancers.Frontiers in cell and developmental biology · 2022
    Review
  15. Article
  16. Review
  17. 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

8 authors.

Yuxin LinDepartment of Urology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
Xiaojun ZhaoDepartment of Urology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
Zhijun MiaoDepartment of Urology, Suzhou Dushuhu Public Hospital, Suzhou, 215123, China.
Zhixin LingDepartment of Urology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
Xuedong WeiDepartment of Urology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
Jinxian PuDepartment of Urology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
Jianquan HouDepartment of Urology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China. xf192@163.com.
Bairong ShenInstitutes for Systems Genetics, West China Hospital, Sichuan University, Chengdu, 610041, China. bairong.shen@scu.edu.cn.ORCID 0000-0003-2899-1531

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prostate cancer (PCa) is a common malignant tumor with increasing incidence and high heterogeneity among males worldwide. In the era of big data and artificial intelligence, the paradigm of biomarker discovery is shifting from traditional experimental and small data-based identification toward big data-driven and systems-level screening. Complex interactions between genetic factors and environmental effects provide opportunities for systems modeling of PCa genesis and evolution. We hereby review the current research frontiers in informatics for PCa clinical translation. First, the heterogeneity and complexity in PCa development and clinical theranostics are introduced to raise the concern for PCa systems biology studies. Then biomarkers and risk factors ranging from molecular alternations to clinical phenotype and lifestyle changes are explicated for PCa personalized management. Methodologies and applications for multi-dimensional data integration and computational modeling are discussed. The future perspectives and challenges for PCa systems medicine and holistic healthcare are finally provided.

Indexed as

Artificial IntelligenceProstatic NeoplasmsBiomarkersHumansMalePrecision MedicineTranslational Research, BiomedicalBiomarkersBiomarker discoveryClinical applicationProstate cancerSystems medicineTranslational informatics

Identifiers

PMID32143723
PMCPMC7060655

What OpenQuestion holds

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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.