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Objective To analyze the risk factors for biochemical recurrence in prostate cancer patients after radical prostatectomy (RP) and establish a risk prediction model for the recurrence. Methods A retrospective cohort study was conducted on 279 patients who underwent RP surgery in our hospital from September 2007 to March 2022. There were 21 clinical indicators collected and analyzed. After time factors were included, Lasso regression was applied to screen the indicators, Kaplan-Meier method was used to draw survival curve, univariate and multivariate Cox proportional risk regression models were employed to analyze the risk factors and establish a prediction model. Then receiver operating characteristic (ROC) curve were plotted to evaluate the discriminative performance of the model. Then a nomogram was draw based on the obtained risk factors. Calibration curve was used to evaluate the accuracy of prediction, and decision curve was employed to assess the clinical benefit. Results During a median follow-up time of 37.10 (17.60, 61.30) months, 86 cases (30.8%), at a median age of 68.00 (65.00, 72.00) years, experienced biochemical recurrence. Univariate analysis showed that 12 indicators were strongly associated with biochemical recurrence after RP (P < 0.05), and Lasso regression screening indicated 7 representative indicator sets, including nutritional risk index (NRI), clinical T-stage, pathological Gleason score, pathological T-stage, positive surgical margin, lymph node invasion, and seminal vesicle invasion. Further multifactorial analysis revealed that pathological high stage (≥pT3 stage) (HR=1.895, 95%CI: 1.045~3.435, P=0.035), positive surgical margin (HR=1.808, 95%CI: 1.006~3.25, P=0.048), lymph node invasion (HR=2.161, 95% CI: 1.118~4.175, P=0.022) and NRI ≤106.9 (HR=0.598, 95% CI: 0.378~0.946, P=0.028) were independent risk factors for biochemical recurrence. The predictive equation was established with an AUC of 0.743 (95% CI: 0.677~0.810, P < 0.001), a sensitivity of 0.826 and a specificity of 0.534. And the established nomogram has a C-index of 0.741 (95%CI: 0.677~0.805; P < 0.001), with good agreement indicated by calibration curve. Clinical decision curve displayed that there was a net benefit when the threshold probability was 15%~85%. Conclusion High pathological stage (≥pT3 stage), positive surgical margin, lymph node invasion, and NRI ≤106.9 are independent risk factors for biochemical recurrence of prostate cancer after RP. Our prediction model can make effective judgments and provide references for clinical decision making.

Metastasis is the primary culprit behind cancer‐related fatalities in multiple cancer types, including prostate cancer. Despite great advances, the precise mechanisms underlying prostate cancer metastasis are far from complete. By using a transgenic mouse prostate cancer model (TRAMP) with and without Phf8 knockout, we have identified a crucial role of PHF8 in prostate cancer metastasis. By complexing with E2F1, PHF8 transcriptionally upregulates SNAI1 in a demethylation‐dependent manner. The upregulated SNAI1 subsequently enhances epithelial‐to‐mesenchymal transition (EMT) and metastasis. Given the role of the abnormally activated PHF8/E2F1‐SNAI1 axis in prostate cancer metastasis and poor prognosis, the levels of PHF8 or the activity of this axis could serve as biomarkers for prostate cancer metastasis. Moreover, targeting this axis could become a potential therapeutic strategy for prostate cancer treatment. © 2024 The Pathological Society of Great Britain and Ireland. [ABSTRACT FROM AUTHOR]