Abstract
Purpose
To develop a novel Taiwanese prostate cancer (PCa) risk model for predicting PCa, comparing its predictive performance with that of two well-established PCa risk calculator apps.
Methods
1545 men undergoing prostate biopsies in a Taiwanese tertiary medical center between 2012 and 2019 were identified retrospectively. A five-fold cross-validated logistic regression risk model was created to calculate the probabilities of PCa and high-grade PCa (Gleason score ≧ 7), to compare those of the Rotterdam and Coral apps. Discrimination was analyzed using the area under the receiver operator characteristic curve (AUC). Calibration was graphically evaluated with the goodness-of-fit test. Decision-curve analysis was performed for clinical utility. At different risk thresholds to biopsy, the proportion of biopsies saved versus low- and high-grade PCa missed were presented.
Results
Overall, 278/1309 (21.2%) patients were diagnosed with PCa, and 181 out of 278 (65.1%) patients had high-grade PCa. Both our model and the Rotterdam app demonstrated better discriminative ability than the Coral app for detection of PCa (AUC: 0.795 vs 0.792 vs 0.697, DeLong’s method: P < 0.001) and high-grade PCa (AUC: 0.869 vs 0.873 vs 0.767, P < 0.001). Using a ≥ 10% risk threshold for high-grade PCa to biopsy, our model could save 67.2% of total biopsies; among these saved biopsies, only 3.4% high-grade PCa would be missed.
Conclusion
Our new logistic regression model, similar to the Rotterdam app, outperformed the Coral app in the prediction of PCa and high-grade PCa. Additionally, our model could save unnecessary biopsies and avoid missing clinically significant PCa in the Taiwanese population.
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Data availability
All data were retrospectively recorded via electronic medical records, merely by I-Hsuan Alan Chen. Following data collection, they were anonymized and then analyzed. The other authors could not get access to the identity of research participants.
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IAC: project development, data collection, manuscript writing; CC: data analysis; JL: manuscript editing; JT: manuscript editing; CY: manuscript editing; ANS: manuscript editing; MC: project development, manuscript editing; PS: project development, manuscript editing.
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Our study was performed in accordance with the principles of the 1964 Declaration of Helsinki. Ethics approval was granted by the Internal Review Board of a Taiwanese tertiary medical center (IRB No.: VGHKS19-CT3-13).
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Owing to the retrospective nature of our study, the informed consent was waived.
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Chen, I.H.A., Chu, CH., Lin, JT. et al. Comparing a new risk prediction model with prostate cancer risk calculator apps in a Taiwanese population. World J Urol 39, 797–802 (2021). https://doi.org/10.1007/s00345-020-03256-2
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DOI: https://doi.org/10.1007/s00345-020-03256-2