The Prostate · 2026
GenProb-PCSM: A Simplified Weighted Germline Score for Prostate Cancer-Specific Mortality.
СтатьяНазвание и аннотация: Перевод в очереди
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Wei Jun, Shi Zhuqing, Lu Lucy, Wang John, Xu Julian, Mulford Ashley J, Tran Huy, Ashworth Annabelle, Lilly Zheng S, Sanders Alan R, Issacs William B, Luo Jun, Helfand Brian, Lu Jim, Xu Jianfeng
Аннотация
BACKGROUND: We previously developed a tier-based germline classification using the National Comprehensive Cancer Network (NCCN)-recommended DNA damage repair (DDR) genes and KLK3 I179T to predict prostate cancer (PCa)-specific mortality (PCSM). To provide an easier-to-use single inherited risk score while preserving gene-specific effects, we developed GenProb-PCSM.
METHODS: We analyzed 14,644 men with incident PCa from the UK Biobank. The cohort was randomly divided into training (60%) and independent testing (40%) datasets. GenProb-PCSM was developed in the training cohort by integrating pathogenic variants in ten NCCN-recommended DDR genes and the KLK3 I179T variant using gene-specific weights derived from Fine-Gray competing-risk models. Performance was evaluated in the independent testing cohort by discrimination, calibration, and risk stratification. Secondary analyzes evaluated metastatic progression and the composite endpoint of metastatic progression and/or PCSM.
RESULTS: Among 14,644 men with incident PCa, 1,581 died from PCa. GenProb-PCSM remained significantly associated with PCSM in the independent testing cohort (HR per SD, 1.18; 95% CI, 1.12-1.24; p < 0.001). Using predefined risk thresholds derived from the training cohort, patients in the intermediate- and high-risk groups had significantly increased risks of PCSM compared with the low-risk group (HR 1.49, 95% CI 1.22-1.84; and HR 4.04, 95% CI 2.58-6.33, respectively). GenProb-PCSM also predicted independent metastatic progression and the composite endpoint of metastatic progression and/or PCSM.
CONCLUSIONS: GenProb-PCSM transforms complex germline findings into a single inherited risk score for PCSM and metastatic progression. Its simplicity and preservation of gene-specific effects may facilitate clinical implementation of germline prognostic assessment in PCa.
METHODS: We analyzed 14,644 men with incident PCa from the UK Biobank. The cohort was randomly divided into training (60%) and independent testing (40%) datasets. GenProb-PCSM was developed in the training cohort by integrating pathogenic variants in ten NCCN-recommended DDR genes and the KLK3 I179T variant using gene-specific weights derived from Fine-Gray competing-risk models. Performance was evaluated in the independent testing cohort by discrimination, calibration, and risk stratification. Secondary analyzes evaluated metastatic progression and the composite endpoint of metastatic progression and/or PCSM.
RESULTS: Among 14,644 men with incident PCa, 1,581 died from PCa. GenProb-PCSM remained significantly associated with PCSM in the independent testing cohort (HR per SD, 1.18; 95% CI, 1.12-1.24; p < 0.001). Using predefined risk thresholds derived from the training cohort, patients in the intermediate- and high-risk groups had significantly increased risks of PCSM compared with the low-risk group (HR 1.49, 95% CI 1.22-1.84; and HR 4.04, 95% CI 2.58-6.33, respectively). GenProb-PCSM also predicted independent metastatic progression and the composite endpoint of metastatic progression and/or PCSM.
CONCLUSIONS: GenProb-PCSM transforms complex germline findings into a single inherited risk score for PCSM and metastatic progression. Its simplicity and preservation of gene-specific effects may facilitate clinical implementation of germline prognostic assessment in PCa.