ArticleAdipocyte2022
MRI-measured adipose features as predictive factors for detection of prostate cancer in males undergoing systematic prostate biopsy: a retrospective study based on a Chinese population.
Article in Adipocyte, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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.
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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.
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Who cites it
6 citing papers in PubMed, 5 citations in OpenAlex.
- Article
- Development and internal validation of a noninvasive predictive model based on iron and fat measurements for pathologic risk stratification in prostate cancer.Translational andrology and urology · 2026Article
- A novel composite index of PSA and periprostatic adipose tissue quantification for enhancing high-grade prostate cancer prediction.BMC urology · 2025Article
- Radiologic Assessment of Periprostatic Fat as an Indicator of Prostate Cancer Risk on Multiparametric MRI.Bioengineering (Basel, Switzerland) · 2025Article
- Progressive Approaches in Adipose Radio Imaging: Cancer Utilization and Necessity for Advancements.Infectious disorders drug targets · 2025Article
- Periprostatic Adipose Tissue: A New Perspective for Diagnosing and Treating Prostate Cancer.Journal of Cancer · 2024Review
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this study, we retrospectively evaluated the data of 901 men undergoing ultrasonography-guided systematic prostate biopsy between March 2013 and May 2022. Adipose features, including periprostatic adipose tissue (PPAT) thickness and subcutaneous fat thickness, were measured using MRI before biopsy. Prediction models of all PCa and clinically significant PCa (csPCa) (Gleason score higher than 6) were established based on variables selected by multivariate logistic regression and prediction nomograms were constructed. Patients with PCa had higher PPAT thickness (4.64 [3.65-5.86] vs. 3.54 [2.49-4.51] mm,
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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.