ReviewWorld journal of urology2020
Multivariate risk prediction tools including MRI for individualized biopsy decision in prostate cancer diagnosis: current status and future directions.
Review in World journal of urology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled 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.
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
29 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Clinical impact of MRI-based risk calculators for prostate cancer diagnosis: a systematic review and meta-analysis.Prostate cancer and prostatic diseases · 2026Pooled it
- Magnetic Resonance Imaging, Clinical, and Biopsy Findings in Suspected Prostate Cancer: A Systematic Review and Meta-Analysis.JAMA network open · 2024Pooled it
- The effects of prostate volume and PI-RADS category on optimal PSA-density thresholds for biopsy decision-making.European radiology · 2026Article
- Predictors of false-positive results in men with Prostate Imaging-Reporting and Data System 4 lesions.Prostate international · 2026Article
- Impact of Approach Routes in MRI-Ultrasound Fusion Prostate Biopsy on Post-Biopsy Complications: A Propensity Score-Matched Analysis.International journal of urology : official journal of the Japanese Urological Association · 2026Article
- Combining Serum PVT1 Exon 4A and Exon 9 with Serum Prostate-Specific Antigen Shows Potential for Improving Identification and Risk Stratification of Prostate Cancer.Cancer management and research · 2026Article
- AI-powered prostate cancer detection: a multi-centre, multi-scanner validation study.European radiology · 2025Article
- External validation and comparison of magnetic resonance imaging-based risk prediction models for prostate biopsy stratification.World journal of urology · 2024Article
- Cancer-specific risk prediction with a serum microRNA signature.Cancer science · 2024Article
- Article
- PI-RADS upgrading as the strongest predictor for the presence of clinically significant prostate cancer in patients with initial PI-RADS-3 lesions.World journal of urology · 2024Article
- Risk score model to automatically detect prostate cancer patients by integrating diagnostic parameters.Frontiers in oncology · 2024Article
- Development and validation of a nomogram prediction model for clinically significant prostate cancer combined with PI-RADS V2.1, MRI quantitative parameters and clinical indicators: a two-center study.Frontiers in oncology · 2024Article
- Developing a predictive model for clinically significant prostate cancer by combining age, PSA density, and mpMRI.World journal of surgical oncology · 2023Article
- Magnetic Resonance Imaging-Based Predictive Models for Clinically Significant Prostate Cancer: A Systematic Review.Cancers · 2022Review
- Reducing prostate biopsies and magnetic resonance imaging with prostate cancer risk stratification.BJUI compass · 2022Article
- Article
- Risk-based MRI-directed diagnostic pathway outperforms non-risk-based pathways in suspected prostate cancer biopsy-naïve men: a large cohort validation study.European radiology · 2022Article
- Article
- The impact of multiparametric MRI features to identify the presence of prevalent cribriform pattern in the peripheral zone tumors.La Radiologia medica · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and purposeIndividualized risk-adapted algorithms in prostate cancer (PCa) diagnosis using predictive prebiopsy variables in addition to prostate-specific antigen value may result in a considerable reduction of unnecessary systematic biopsies. Multi-parametric magnetic resonance imaging (mpMRI) has emerged as a secondary prediction tool that can further improve the detection of clinically significant prostate cancer (csPCa). This review explores the performance of new MRI risk models for indicating a biopsy for prostate cancer diagnosis. RESULTS AND CONSIDERATIONS: The area under the receiver-operating characteristic curve for detecting csPCa varies between 0.64 and 0.91 in biopsy-naïve men, and between 0.78 and 0.93 in men with a previous negative biopsy. The utility of multivariate risk prediction tools including MRI suspicion scores as an extra input parameter has the potential to avoid a notable number of biopsies and detection of clinically insignificant PCa at a low price of missing some csPCa. The trade-off depends on the risk threshold that is chosen. In biopsy-naïve men a net benefit was obtained at a risk threshold of above 10% for csPCa in most MRI risk prediction models. All constructed MRI risk models used (referral) patient cohorts with high prevalence of csPCa. Using more representative cohorts from daily clinical screening, net benefit may attenuate at lower risk thresholds. Strengths and limitations of these models are discussed. FUTURE DIRECTIONS: To assess their wider applicability, in-depth analysis of mpMRI predictive qualities should be further investigated, in combination with required external validation of these models in a multicenter setting with large prospective datasets.
Indexed as
Identifiers
What OpenQuestion holds
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.