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Nevin Manimala Statistics

Integrating Genomic Prostate Score with Preoperative and Postoperative Cancer of the Prostate Risk Assessment Scores to Predict Biochemical Recurrence after Radical Prostatectomy

Eur Urol Oncol. 2026 Apr 10:S2588-9311(26)00062-3. doi: 10.1016/j.euo.2026.03.003. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVE: Cancer of the Prostate Risk Assessment (CAPRA) score and its postsurgical variant (CAPRA-S) predict biochemical recurrence (BCR) after radical prostatectomy (RP) but do not capture tumor biology. We developed two integrated clinical scores, CAPRA-G and CAPRA-SG, combining CAPRA or CAPRA-S with Genomic Prostate Score (GPS).

METHODS: We analyzed 955 patients with Oncotype DX testing before RP. Associations between GPS, CAPRA, and CAPRA-S scores, and BCR were assessed using Cox models. CAPRA-G and CAPRA-SG were derived from β-coefficient weighting. Model discrimination was evaluated using Harrell’s C-index (3000 bootstrap resamples); differences were assessed with a nonparametric U-statistic. Decision-curve analysis compared CAPRA with CAPRA-G and CAPRA-S with CAPRA-SG.

KEY FINDINGS AND LIMITATIONS: Median follow-up was 60 mo (IQR 36-72). GPS predicted BCR independent of CAPRA or CAPRA-S (p < 0.001). Using log-hazard β-coefficients, one CAPRA and CAPRA-S point corresponded to » 6 and 10 GPS points, respectively, yielding CAPRA-G = CAPRA + GPS/6 and CAPRA-SG = CAPRA-S + GPS/10. Compared with CAPRA and CAPRA-S, CAPRA-G and CAPRA-SG showed a statistically significant improvement in C-indices, increasing from 0.67 to 0.76 (p < 0.001) and from 0.81 to 0.84 (p = 0.041), respectively. Decision-curve analysis demonstrated higher net benefit for CAPRA-G and CAPRA-SG at clinically relevant thresholds (» 0.05-0.45). Limitations included lack of external validation and under-representation of high-risk disease due to selective GPS prescription.

CONCLUSIONS AND CLINICAL IMPLICATIONS: GPS integration enhances BCR risk stratification in the RP setting. CAPRA-G and CAPRA-SG scores quantify genomic risk and translate GPS into simple, clinically applicable tools with improved clinical utility. External validation is warranted.

PMID:41966955 | DOI:10.1016/j.euo.2026.03.003

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