Risk Prediction of Prostate Cancer with Single Nucleotide Polymorphisms and Prostate Specific Antigen

Sam Li-Sheng Chen, Jean Ching-Yuan Fann, Csilla Sipeky, Teng Kai Yang, Sherry Yueh-Hsia Chiu, Amy Ming-Fang Yen, Virpi Laitinen, Teuvo L.J. Tammela, Ulf Håkan Stenman, Anssi Auvinen, Johanna Schleutker, Hsiu Hsi Chen

Research output: Contribution to journalArticle

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Abstract

PURPOSE: Combined information on single nucleotide polymorphisms and prostate specific antigen offers opportunities to improve the performance of screening by risk stratification. We aimed to predict the risk of prostate cancer based on prostate specific antigen together with single nucleotide polymorphism information. MATERIALS AND METHODS: We performed a prospective study of 20,575 men with prostate specific antigen testing and 4,967 with a polygenic risk score for prostate cancer based on 66 single nucleotide polymorphisms from the Finnish population based screening trial of prostate cancer and 5,269 samples of 7 single nucleotide polymorphisms from the Finnish prostate cancer DNA study. A Bayesian predictive model was built to estimate the risk of prostate cancer by sequentially combining genetic information with prostate specific antigen compared with prostate specific antigen alone in study subjects limited to those with prostate specific antigen 4 ng/ml or above. RESULTS: The posterior odds of prostate cancer based on 7 single nucleotide polymorphisms together with the prostate specific antigen level ranged from 3.7 at 4 ng/ml, 14.2 at 6 and 40.7 at 8 to 98.2 at 10 ng/ml. The ROC AUC was elevated to 88.8% (95% CI 88.6-89.1) for prostate specific antigen combined with the risk score based on 7 single nucleotide polymorphisms compared with 70.1% (95% CI 69.6-70.7) for prostate specific antigen alone. It was further escalated to 96.7% (95% CI 96.5-96.9) when all prostate cancer susceptibility polygenes were combined. CONCLUSIONS: Expedient use of multiple genetic variants together with information on prostate specific antigen levels better predicts the risk of prostate cancer than prostate specific antigen alone and allows for higher prostate specific antigen cutoffs. Combined information also provides a basis for risk stratification which can be used to optimize the performance of prostate cancer screening.

Original languageEnglish
Pages (from-to)486-495
Number of pages10
JournalThe Journal of Urology
Volume201
Issue number3
DOIs
Publication statusPublished - Mar 1 2019

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Prostate-Specific Antigen
Single Nucleotide Polymorphism
Prostatic Neoplasms
Early Detection of Cancer
Area Under Curve
Prospective Studies

ASJC Scopus subject areas

  • Urology

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Li-Sheng Chen, S., Ching-Yuan Fann, J., Sipeky, C., Yang, T. K., Yueh-Hsia Chiu, S., Ming-Fang Yen, A., ... Chen, H. H. (2019). Risk Prediction of Prostate Cancer with Single Nucleotide Polymorphisms and Prostate Specific Antigen. The Journal of Urology, 201(3), 486-495. https://doi.org/10.1016/j.juro.2018.10.015

Risk Prediction of Prostate Cancer with Single Nucleotide Polymorphisms and Prostate Specific Antigen. / Li-Sheng Chen, Sam; Ching-Yuan Fann, Jean; Sipeky, Csilla; Yang, Teng Kai; Yueh-Hsia Chiu, Sherry; Ming-Fang Yen, Amy; Laitinen, Virpi; Tammela, Teuvo L.J.; Stenman, Ulf Håkan; Auvinen, Anssi; Schleutker, Johanna; Chen, Hsiu Hsi.

In: The Journal of Urology, Vol. 201, No. 3, 01.03.2019, p. 486-495.

Research output: Contribution to journalArticle

Li-Sheng Chen, S, Ching-Yuan Fann, J, Sipeky, C, Yang, TK, Yueh-Hsia Chiu, S, Ming-Fang Yen, A, Laitinen, V, Tammela, TLJ, Stenman, UH, Auvinen, A, Schleutker, J & Chen, HH 2019, 'Risk Prediction of Prostate Cancer with Single Nucleotide Polymorphisms and Prostate Specific Antigen', The Journal of Urology, vol. 201, no. 3, pp. 486-495. https://doi.org/10.1016/j.juro.2018.10.015
Li-Sheng Chen, Sam ; Ching-Yuan Fann, Jean ; Sipeky, Csilla ; Yang, Teng Kai ; Yueh-Hsia Chiu, Sherry ; Ming-Fang Yen, Amy ; Laitinen, Virpi ; Tammela, Teuvo L.J. ; Stenman, Ulf Håkan ; Auvinen, Anssi ; Schleutker, Johanna ; Chen, Hsiu Hsi. / Risk Prediction of Prostate Cancer with Single Nucleotide Polymorphisms and Prostate Specific Antigen. In: The Journal of Urology. 2019 ; Vol. 201, No. 3. pp. 486-495.
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abstract = "PURPOSE: Combined information on single nucleotide polymorphisms and prostate specific antigen offers opportunities to improve the performance of screening by risk stratification. We aimed to predict the risk of prostate cancer based on prostate specific antigen together with single nucleotide polymorphism information. MATERIALS AND METHODS: We performed a prospective study of 20,575 men with prostate specific antigen testing and 4,967 with a polygenic risk score for prostate cancer based on 66 single nucleotide polymorphisms from the Finnish population based screening trial of prostate cancer and 5,269 samples of 7 single nucleotide polymorphisms from the Finnish prostate cancer DNA study. A Bayesian predictive model was built to estimate the risk of prostate cancer by sequentially combining genetic information with prostate specific antigen compared with prostate specific antigen alone in study subjects limited to those with prostate specific antigen 4 ng/ml or above. RESULTS: The posterior odds of prostate cancer based on 7 single nucleotide polymorphisms together with the prostate specific antigen level ranged from 3.7 at 4 ng/ml, 14.2 at 6 and 40.7 at 8 to 98.2 at 10 ng/ml. The ROC AUC was elevated to 88.8{\%} (95{\%} CI 88.6-89.1) for prostate specific antigen combined with the risk score based on 7 single nucleotide polymorphisms compared with 70.1{\%} (95{\%} CI 69.6-70.7) for prostate specific antigen alone. It was further escalated to 96.7{\%} (95{\%} CI 96.5-96.9) when all prostate cancer susceptibility polygenes were combined. CONCLUSIONS: Expedient use of multiple genetic variants together with information on prostate specific antigen levels better predicts the risk of prostate cancer than prostate specific antigen alone and allows for higher prostate specific antigen cutoffs. Combined information also provides a basis for risk stratification which can be used to optimize the performance of prostate cancer screening.",
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AU - Ching-Yuan Fann, Jean

AU - Sipeky, Csilla

AU - Yang, Teng Kai

AU - Yueh-Hsia Chiu, Sherry

AU - Ming-Fang Yen, Amy

AU - Laitinen, Virpi

AU - Tammela, Teuvo L.J.

AU - Stenman, Ulf Håkan

AU - Auvinen, Anssi

AU - Schleutker, Johanna

AU - Chen, Hsiu Hsi

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N2 - PURPOSE: Combined information on single nucleotide polymorphisms and prostate specific antigen offers opportunities to improve the performance of screening by risk stratification. We aimed to predict the risk of prostate cancer based on prostate specific antigen together with single nucleotide polymorphism information. MATERIALS AND METHODS: We performed a prospective study of 20,575 men with prostate specific antigen testing and 4,967 with a polygenic risk score for prostate cancer based on 66 single nucleotide polymorphisms from the Finnish population based screening trial of prostate cancer and 5,269 samples of 7 single nucleotide polymorphisms from the Finnish prostate cancer DNA study. A Bayesian predictive model was built to estimate the risk of prostate cancer by sequentially combining genetic information with prostate specific antigen compared with prostate specific antigen alone in study subjects limited to those with prostate specific antigen 4 ng/ml or above. RESULTS: The posterior odds of prostate cancer based on 7 single nucleotide polymorphisms together with the prostate specific antigen level ranged from 3.7 at 4 ng/ml, 14.2 at 6 and 40.7 at 8 to 98.2 at 10 ng/ml. The ROC AUC was elevated to 88.8% (95% CI 88.6-89.1) for prostate specific antigen combined with the risk score based on 7 single nucleotide polymorphisms compared with 70.1% (95% CI 69.6-70.7) for prostate specific antigen alone. It was further escalated to 96.7% (95% CI 96.5-96.9) when all prostate cancer susceptibility polygenes were combined. CONCLUSIONS: Expedient use of multiple genetic variants together with information on prostate specific antigen levels better predicts the risk of prostate cancer than prostate specific antigen alone and allows for higher prostate specific antigen cutoffs. Combined information also provides a basis for risk stratification which can be used to optimize the performance of prostate cancer screening.

AB - PURPOSE: Combined information on single nucleotide polymorphisms and prostate specific antigen offers opportunities to improve the performance of screening by risk stratification. We aimed to predict the risk of prostate cancer based on prostate specific antigen together with single nucleotide polymorphism information. MATERIALS AND METHODS: We performed a prospective study of 20,575 men with prostate specific antigen testing and 4,967 with a polygenic risk score for prostate cancer based on 66 single nucleotide polymorphisms from the Finnish population based screening trial of prostate cancer and 5,269 samples of 7 single nucleotide polymorphisms from the Finnish prostate cancer DNA study. A Bayesian predictive model was built to estimate the risk of prostate cancer by sequentially combining genetic information with prostate specific antigen compared with prostate specific antigen alone in study subjects limited to those with prostate specific antigen 4 ng/ml or above. RESULTS: The posterior odds of prostate cancer based on 7 single nucleotide polymorphisms together with the prostate specific antigen level ranged from 3.7 at 4 ng/ml, 14.2 at 6 and 40.7 at 8 to 98.2 at 10 ng/ml. The ROC AUC was elevated to 88.8% (95% CI 88.6-89.1) for prostate specific antigen combined with the risk score based on 7 single nucleotide polymorphisms compared with 70.1% (95% CI 69.6-70.7) for prostate specific antigen alone. It was further escalated to 96.7% (95% CI 96.5-96.9) when all prostate cancer susceptibility polygenes were combined. CONCLUSIONS: Expedient use of multiple genetic variants together with information on prostate specific antigen levels better predicts the risk of prostate cancer than prostate specific antigen alone and allows for higher prostate specific antigen cutoffs. Combined information also provides a basis for risk stratification which can be used to optimize the performance of prostate cancer screening.

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