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Phi-based risk calculators performed better in the prediction of prostate cancer in the Chinese population


1 Department of Urology, Huashan Hospital, Fudan University, Shanghai 200040, China
2 Urology Research Center, Fudan University, Shanghai 200040, China
3 Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL 60201, USA
4 Department of Surgery, Huashan Hospital, Fudan University, Shanghai 200040, China
5 Department of Urology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China
6 Department of Urology, Shanghai Cancer Center, Fudan University, Shanghai 200032, China
7 Department of Urology, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200092, China
8 Department of Urology, Changhai Hospital, The Second Military Medical University, Shanghai 200433, China

Correspondence Address:
Jianfeng Xu,
Urology Research Center, Fudan University, Shanghai 200040, China; Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL 60201, USA

Qiang Ding,
Department of Urology, Huashan Hospital, Fudan University, Shanghai 200040, China; Urology Research Center, Fudan University, Shanghai 200040, China

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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/aja.aja_125_18

PMID: 30924451

Risk prediction models including the Prostate Health Index (phi) for prostate cancer have been well established and evaluated in the Western population. The aim of this study is to build phi-based risk calculators in a prostate biopsy population and evaluate their performance in predicting prostate cancer (PCa) and high-grade PCa (Gleason score ≥7) in the Chinese population. We developed risk calculators based on 635 men who underwent initial prostate biopsy. Then, we validated the performance of prostate-specific antigen (PSA), phi, and the risk calculators in an additional observational cohort of 1045 men. We observed that the phi-based risk calculators (risk calculators 2 and 4) outperformed the PSA-based risk calculator for predicting PCa and high-grade PCa in the training cohort. In the validation study, the area under the receiver operating characteristic curve (AUC) for risk calculators 2 and 4 reached 0.91 and 0.92, respectively, for predicting PCa and high-grade PCa, respectively; the AUC values were better than those for risk calculator 1 (PSA-based model with an AUC of 0.81 and 0.82, respectively) (all P < 0.001). Such superiority was also observed in the stratified population with PSA ranging from 2.0 ng ml−1to 10.0 ng ml−1. Decision curves confirmed that a considerable proportion of unnecessary biopsies could be avoided while applying phi-based risk calculators. In this study, we showed that, compared to risk calculators without phi, phi-based risk calculators exhibited superior discrimination and calibration for PCa in the Chinese biopsy population. Applying these risk calculators also considerably reduced the number of unnecessary biopsies for PCa.


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