ArticleBMC medicine2015
The need for a personalized approach for prostate cancer management.
Article in BMC medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
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.
Who cites it
3 citing papers in PubMed.
- In Vivo Prostate Cancer Modelling: From the Pre-Clinical to the Clinical Setting.Life (Basel, Switzerland) · 2026Review
- Mapping genetic variability in mature miRNAs and miRNA binding sites in prostate cancer.Journal of human genetics · 2021Article
- High throughput assessment of biomarkers in tissue microarrays using artificial intelligence: PTEN loss as a proof-of-principle in multi-center prostate cancer cohorts.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2021Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The stratification of patients for treatment of prostate cancer is based on very general parameters like prostate-specific antigen, Gleason score, and TNM classification. We use these rough parameters for selection of active surveillance, active treatment, and even for the treatment selection in metastasized or castration-resistant prostate cancers. Up to now, we have not used individualized genetic classifiers for detailed sub-stratification, thus treating all patients as equal, and being only moderately successful. With the expected increase in systemic treatments, there is an apparent need for such classifiers. We will address these needs in this short commentary.
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Registered trials
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.