Evidence map›Paper›PMID 31850193›Full record

ReviewFrontiers in oncology2019

A New Era of Prostate Cancer Precision Medicine.

Adil Malik, Srilakshmi Srinivasan, Jyotsna Batra

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
3.7field-weighted citation impact, top 6% 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

23 citing papers in PubMed, 48 citations in OpenAlex.

  1. Article
  2. Prostate Cancer Classification Using Quantum Machine Learning on Multi-parametric MRI.Proceedings of SPIE--the International Society for Optical Engineering · 2026
    Article
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  12. Biomarkers for Prostate Cancer: From Diagnosis to Treatment.Diagnostics (Basel, Switzerland) · 2023
    Review
  13. Review
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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

3 authors at 2 institutions in 1 country.

Adil MalikSchool of Biomedical Sciences, Queensland University of Technology, Institute of Health and Biomedical Innovation, Brisbane, QLD, Australia.
Srilakshmi SrinivasanSchool of Biomedical Sciences, Queensland University of Technology, Institute of Health and Biomedical Innovation, Brisbane, QLD, Australia.
Jyotsna BatraSchool of Biomedical Sciences, Queensland University of Technology, Institute of Health and Biomedical Innovation, Brisbane, QLD, Australia.
Translational Research Institute · AUQueensland University of Technology · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prostate cancer is the second most common male cancer affecting Western society. Despite substantial advances in the exploration of prostate cancer biomarkers and treatment strategies, men are over diagnosed with inert prostate cancer, while there is also a substantial mortality from the invasive disease. Precision medicine is the management of treatment profiles across different cancers predicting therapies for individual cancer patients. With strategies including individual genomic profiling and targeting specific cancer pathways, precision medicine for prostate cancer has the potential to impose changes in clinical practices. Some of the recent advances in prostate cancer precision medicine comprise targeting gene fusions, genome editing tools, non-coding RNA biomarkers, and the promise of liquid tumor profiling. In this review, we will discuss these recent scientific advances to scale up these approaches and endeavors to overcome clinical barriers for prostate cancer precision medicine.

Indexed as

biomarkersgene fusiongenome editingliquid biopsynon-coding genomeprecision medicineprostate cancerproteomic technologies

Identifiers

PMID31850193
PMCPMC6901987
OpenAlexW2990161511

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.