Background: A predictive model for biochemical recurrence (BCR) of prostate cancer (PCa) after neoadjuvant androgen deprivation therapy (nADT) has not been established. This study was aimed at determining multiparameter variables that could be used to construct a nomogram to predict the post-nADT BCR of PCa.
Methods: Overall, 43 radical prostatectomy specimens from PCa patients who had undergone nADT were collected. Multiparameter variables were analyzed by univariate and then multivariate logistic analyses to identify the independent prognostic factors for predicting BCR. The predictive model was established using Lasso regression analysis.
Results: Univariate logistic analysis revealed six variables, pathology stage; margins; categorization as group A, B, or C; nucleolus grading; percentage of tumor involvement (PTI); and PTEN status were significantly associated with the BCR of PCa (all p < 0.05). Multivariate logistic regression analysis suggested that categorization as group C, severe nucleolus grading, PTI less than or equal to 5%, and PTEN loss were positively correlated with BCR (all p < 0.05). A nomogram comprising the four variables predicting BCR was constructed, and it exhibited good discrimination (AUC: 0.985; specificity: 86.2%; sensitivity: 100%). Calibration plots for the probability of freedom from BCR at 1 and 2 years showed a good match between the prediction by the nomogram.
Conclusions: We constructed and validated a nomogram to predict the risk of BCR in PCa patients after nADT. This nomogram is a complement to the existing risk stratification systems for PCa, which could have marked implications for clinical decision-making for PCa patients after nADT.
Keywords: BCR; Nomogram; Predict; Prostate cancer; nADT.
© 2023. The Author(s).