Prostate cancer is the most common malignancy in men, and in patients with low-risk disease, active surveillance represents the preferred initial approach to avoid unnecessary treatments. However, up to 50% of men under active surveillance develop clinical progression or histological upgrading within five years, making improved risk stratification essential. A family history of prostate cancer is a well-established risk factor and reflects the importance of genetic predisposition. Genome-wide studies have identified numerous common variants associated with disease risk, enabling the development of polygenic risk scores (PRS) that integrate the effects of multiple genetic loci. Recent evidence suggests that these PRS may also correlate with tumor aggressiveness and the likelihood of progression in patients undergoing active surveillance. This study aims to analyze 185 patients, stratified according to the presence or absence of family history and progression during active surveillance, using germline DNA that has already been biobanked and analyzed with the Axiomâ„¢ PMDA array. PRS will be calculated as a weighted sum of risk variants. The objective is to identify PRS models capable of accurately predicting progression, with particular focus on men with a family history, thereby improving the personalization of clinical monitoring. By integrating genomic and clinical data, the study seeks to support a precision oncology approach in patients with early-stage prostate cancer.
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Disease progression
Timeframe: at confirmatory biopsy