ArticleAmerican journal of cancer research2025
Development of a predictive model for progression to castration-resistant prostate cancer in patients with high bone tumor burden.
Article in American journal of cancer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveTo identify key risk factors and construct a predictive model for the progression of high bone tumor burden prostate cancer (HBTB-PCa) to castration-resistant prostate cancer (CRPC).
methodsThis retrospective study included 367 HBTB-PCa patients treated between January 2018 and May 2021, with 286 cases progressed to CRPC (progression group) and 81 cases did not (non-progression group). Patients were randomly divided into training (n=257) and validation (n=110) sets at a 7:3 ratio. Logistic regression was used to identify independent risk factors, and a Nomogram was built to predict progression risk. Model performance was evaluated using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA).
resultsCompared with the non-progression group, patients in the progression group had significantly higher rates of perineural invasion (P=0.011), Gleason score ≥8 (P=0.002), and T4 stage (P=0.012). Laboratory markers including ALP (P<0.001) and LDH (P<0.001) were also elevated in the progression group. Multivariate analysis identified perineural invasion (P=0.032), Gleason score (P=0.002), initial PSA (P=0.025), ALP (P=0.011), LDH (P<0.001), and ALB (P=0.019) as independent predictors of progression to CRPC. The Nomogram demonstrated strong discrimination power (AUC=0.845 in the training set; AUC=0.746 in external validation), with LDH being the most influential predictor. DCA indicated a net clinical benefit up to 77.82%.
conclusionsPerineural invasion, Gleason score ≥8, and elevated ALP and LDH are closely associated with progression from HBTB-PCa to CRPC. The constructed Nomogram (internal AUC=0.845; external AUC=0.746) offers a practical tool for individualized risk assessment and guiding treatment planning in clinical settings.
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