Observational studyCell reports. Medicine2024
Development and validation of the utLIFE-PC algorithm for noninvasive detection of prostate cancer in urine: A prospective, observational study.
Observational study in Cell reports. Medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Development and validation of a two-gene urine DNA methylation assay for noninvasive prostate cancer detection: a prospective multicenter study.Molecular biomedicine · 2026Article
- Using interpretable machine learning model to predict lymph node metastasis in patients with localized prostate cancer.Frontiers in oncology · 2026Article
- SERS-powered precision: revolutionizing therapeutic drug monitoring with nanoscale sensitivity.Mikrochimica acta · 2025Review
- PSMA-based theranostics in diagnosing and treating prostate cancer in the Asian male population: a narrative review.Frontiers in oncology · 2025Review
- Integrative multi-omics analysis and machine learning refine global histone modification features in prostate cancer.Frontiers in molecular biosciences · 2025Article
Corrections and comments
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Authors and funding
27 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Overbiopsy is a serious health issue in prostate cancer (PCa) diagnostics. We have developed a urine tumor DNA multidimensional bioinformatic algorithm, utLIFE, to avoid unnecessary biopsy. The objective is to recognize all or clinically significant PCa. Of the 801 participants recruited in our study, 630 are selected for subsequent analysis. In the training cohort (n = 237), utLIFE-PC gets an area under the receiver operating characteristic curve (AUC) of 0.967 and a sensitivity of 85.57% at 95% specificity. In the independent prospective validation cohort (n = 343), utLIFE-PC has an AUC of 0.929, sensitivity of 84.24%, and specificity of 93.26%. Notably, in patients with ≥grade group (GG)2 and ≥GG3, the assay's sensitivity is still excellent (85.33% and 87.10%, respectively). The model shows better performance than prostate-specific antigen (PSA) (p < 0.001) or the single-dimensional biomarkers (methylation, p < 0.001; copy-number variations [CNVs], p < 0.001; mutation, p < 0.001). The utLIFE-PC model can potentially optimize the PCa diagnostic process and avoid unnecessary biopsies. This study was registered at Chinese Clinical Trial Registry: ChiCTR2300071837.
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