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Can a nomogram predict apical prostate cancer pathology upgrade from fusion biopsy to final pathology? A multicenter study.

Authors :
Feng, Tianrui
Liang, Zhen
Xiao, Yu
Pan, Boju
Zhou, Yi
Ma, Chengquan
Zhou, Zhien
Yan, Weigang
Zhu, Ming
Source :
Cancer Medicine; Jun2024, Vol. 13 Issue 11, p1-12, 12p
Publication Year :
2024

Abstract

Background: This study evaluates the efficacy of a nomogram for predicting the pathology upgrade of apical prostate cancer (PCa). Methods: A total of 754 eligible patients were diagnosed with apical PCa through combined systematic and magnetic resonance imaging (MRI)‐targeted prostate biopsy followed by radical prostatectomy (RP) were retrospectively identified from two hospitals (training: 754, internal validation: 182, internal–external validation: 148). A nomogram for the identification of apical tumors in high‐risk pathology upgrades through comparing the results of biopsy and RP was established incorporating statistically significant risk factors based on univariable and multivariable logistic regression. The nomogram's performance was assessed via the receiver operating characteristic (ROC) curve, calibration plots, and decision curve analysis (DCA). Results: Univariable and multivariable analysis identified age, targeted biopsy, number of targeted cores, TNM stage, and the prostate imaging‐reporting and data system score as significant predictors of apical tumor pathological progression. Our nomogram, based on these variables, demonstrated ROC curves for pathology upgrade with values of 0.883 (95% CI, 0.847–0.929), 0.865 (95% CI, 0.790–0.945), and 0.840 (95% CI, 0.742–0.904) for the training, internal validation and internal–external validation cohorts respectively. Calibration curves showed good consistency between the predicted and actual outcomes. The validation groups also showed great generalizability with the calibration curves. DCA results also demonstrated excellent performance for our nomogram with positive benefit across a threshold probability range of 0–0.9 for the training and internal validation group, and 0–0.6 for the internal–external validation group. Conclusion: The nomogram, integrating clinical, radiological, and pathological data, effectively predicts the risk of pathology upgrade in apical PCa tumors. It holds significant potential to guide clinicians in optimizing the surgical management of these patients. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20457634
Volume :
13
Issue :
11
Database :
Complementary Index
Journal :
Cancer Medicine
Publication Type :
Academic Journal
Accession number :
177929497
Full Text :
https://doi.org/10.1002/cam4.7341