Evidence map›Paper›PMID 37939258›Full record

ReviewAnnals of medicine2023

Molecular classifications of prostate cancer: basis for individualized risk stratification and precision therapy.

Qintao Ge, Jiawei Li, Feixiang Yang, Xuefeng Tian, Meng Zhang, Zongyao Hao, Chaozhao Liang, Jialin Meng

Open access · goldAbstract readReview
In one paragraph

Review in Annals of medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
4.1field-weighted citation impact, top 5% 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

16 citing papers in PubMed, 16 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Identification of Hub Neutrophil Coexpressed Genes in Acute PancreatitisEndocrine, metabolic & immune disorders drug targets · 2026
    Article
  5. Article
  6. JUNB and JUND in Urological Cancers: A Literature Review.Current issues in molecular biology · 2025
    Review
  7. Article
  8. Current Evidence on Cabazitaxel for Prostate Cancer Therapy: A Narrative Review.International journal of urology : official journal of the Japanese Urological Association · 2025
    Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. A Review with a Focus onPlants (Basel, Switzerland) · 2024
    Review
  15. Review
  16. 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

8 authors at 2 institutions in 1 country.

Qintao GeDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, P.R. China.
Jiawei LiDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, P.R. China.
Feixiang YangDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, P.R. China.
Xuefeng TianAnhui Medical University, Hefei, P.R. China.
Meng ZhangDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, P.R. China.
Zongyao HaoDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, P.R. China.
Chaozhao LiangDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, P.R. China.
Jialin MengDepartment of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, P.R. China.
Anhui Medical University · CNFirst Affiliated Hospital of Anhui Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tumour classifications play a pivotal role in prostate cancer (PCa) management. It can predict the clinical outcomes of PCa as early as the disease is diagnosed and then guide therapeutic schemes, such as active monitoring, standalone surgical intervention, or surgery supplemented with postoperative adjunctive therapy, thereby circumventing disease exacerbation and excessive treatment. Classifications based on clinicopathological features, such as prostate cancer-specific antigen, Gleason score, and TNM stage, are still the main risk stratification strategies and have played an essential role in standardized clinical decision-making. However, mounting evidence indicates that clinicopathological parameters in isolation fail to adequately capture the heterogeneity exhibited among distinct PCa patients, such as those sharing identical Gleason scores yet experiencing divergent prognoses. As a remedy, molecular classifications have been introduced. Currently, molecular studies have revealed the characteristic genomic alterations, epigenetic modulations, and tumour microenvironment associated with different types of PCa, which provide a chance for urologists to refine the PCa classification. In this context, numerous invaluable molecular classifications have been devised, employing disparate statistical methodologies and algorithmic approaches, encompassing self-organizing map clustering, unsupervised cluster analysis, and multifarious algorithms. Interestingly, the classifier PAM50 was used in a phase-2 multicentre open-label trial, NRG-GU-006, for further validation, which hints at the promise of molecular classification for clinical use. Consequently, this review examines the extant molecular classifications, delineates the prevailing panorama of clinically pertinent molecular signatures, and delves into eight emblematic molecular classifications, dissecting their methodological underpinnings and clinical utility.

Indexed as

Prostatic NeoplasmsHumansMaleNeoplasm GradingPrognosisProstate-Specific AntigenRisk AssessmentTumor MicroenvironmentProstate-Specific Antigenmolecular classificationprecision treatmentprognosis predictionProstate cancer

Identifiers

PMID37939258
PMCPMC10653710
OpenAlexW4388487249

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.