Research Article

Basic factors predicting prostate cancer in Prostate Imaging Reporting and Data System-3 lesions

Volume: 16 Number: 2 June 29, 2021
TR EN

Basic factors predicting prostate cancer in Prostate Imaging Reporting and Data System-3 lesions

Abstract

Objective: We aimed to investigate the role of the digital rectal examination, PSA density, regional location of the lesion and prostate size in predicting prostate cancer in Prostate Imaging and Data Reporting System (PI-RADS)-3 lesions.

Material and Methods: A total of 236 patients with multiparametric MRI performed for clinical suspicion of prostate cancer and reported PI-RADS-3 enrolled between January 2016 and July 2019 in this retrospective study. The datas were extracted from the hospital’s electronic records, patient files and outpatient clinic records. Multiparametric MRI was performed patients to whom have elevated PSA level and/or suspicious digital rectal examination. Patients diagnosed with and without prostate cancer were compared in terms of age, PSA, PSA density, prostate size, pathological results, lesion localization and DRE findings.

Results: One hundred thirty- independent predictor seven patients with an initial score of PI-RADS-3 were subjected to further analysis. Prostat cancer detection rate in overall and clinically significant prostate cancer detection rate was 26.2% and 4.3%, respectively. There was a significant difference regarding DRE findings (p=0.001) and PZ location of the lesion (p=0.005) between PCa and no PCa groups. Digital rectal examination (p=0.001) was an independent predictor of prostate cancer in multivariate logistic regression analysis.

Conclusion: Digital rectal examination is a practical and important parameter in clarifying the suspicion of prostate cancer in PI-RADS-3 lesions.

Keywords

References

  1. 1. Center MM, Jemal A, Lortet-Tieulent J, et al. International variation in prostate cancer incidence and mortality rates. Eur Urol. 2012;61:1079-92. DOI:10.1016/j.eururo.2012.02.054.
  2. 2. Trabulsi EJ HE, Gomella LG. Ultrasonography and biopsy of the prostate. 10 ed. Philadelphia: Saunders; 2011 2011. 2735-47 p.
  3. 3. Pinkhasov GI, Lin YK, Palmerola R, et al. Complications following prostate needle biopsy requiring hospital admission or emergency department visits - experience from 1000 consecutive cases. BJU Int. 2012;110:369-74. DOI:10.1111/j.1464-410X.2011.10926.x.
  4. 4. Scheenen TW, Rosenkrantz AB, Haider MA, Futterer JJ. Multiparametric Magnetic Resonance Imaging in Prostate Cancer Management: Current Status and Future Perspectives. Invest Radiol. 2015;50:594-600. DOI:10.1097/rli.0000000000000163.
  5. 5. Barentsz JO, Richenberg J, Clements R, et al. ESUR prostate MR guidelines 2012. Eur Radiol. 2012;22:746-57. DOI:10.1007/s00330-011-2377-y.
  6. 6. Weinreb JC, Barentsz JO, Choyke PL, et al. PI-RADS Prostate Imaging - Reporting and Data System: 2015, Version 2. Eur Urol. 2016;69:16-40. DOI:10.1016/j.eururo.2015.08.052.
  7. 7. Carroll PR, Parsons JK, Andriole G, et al. NCCN Guidelines Insights: Prostate Cancer Early Detection, Version 2.2016. J Natl Compr Canc Netw. 2016;14:509-19. DOI:10.6004/jnccn.2016.0060.
  8. 8. Dickinson L, Ahmed HU, Allen C, et al. Magnetic resonance imaging for the detection, localisation, and characterisation of prostate cancer: recommendations from a European consensus meeting. Eur Urol. 2011;59:477-94. DOI:10.1016/j.eururo.2010.12.009.

Details

Primary Language

English

Subjects

Urology

Journal Section

Research Article

Publication Date

June 29, 2021

Submission Date

December 30, 2020

Acceptance Date

May 28, 2021

Published in Issue

Year 2021 Volume: 16 Number: 2

APA
Yilmaz, S., Yılmaz, M., Yalçın, S., Kaya, E., Gazel, E., Aybal, H. Ç., Özdemir, H., Yorubulut, M., Oner, A., & Tunç, L. (2021). Basic factors predicting prostate cancer in Prostate Imaging Reporting and Data System-3 lesions. Yeni Üroloji Dergisi, 16(2), 184-189. https://doi.org/10.33719/yud.2021;16-2-850090
AMA
1.Yilmaz S, Yılmaz M, Yalçın S, et al. Basic factors predicting prostate cancer in Prostate Imaging Reporting and Data System-3 lesions. New J Urol. 2021;16(2):184-189. doi:10.33719/yud.2021;16-2-850090
Chicago
Yilmaz, Sercan, Mehmet Yılmaz, Serdar Yalçın, et al. 2021. “Basic Factors Predicting Prostate Cancer in Prostate Imaging Reporting and Data System-3 Lesions”. Yeni Üroloji Dergisi 16 (2): 184-89. https://doi.org/10.33719/yud.2021;16-2-850090.
EndNote
Yilmaz S, Yılmaz M, Yalçın S, Kaya E, Gazel E, Aybal HÇ, Özdemir H, Yorubulut M, Oner A, Tunç L (June 1, 2021) Basic factors predicting prostate cancer in Prostate Imaging Reporting and Data System-3 lesions. Yeni Üroloji Dergisi 16 2 184–189.
IEEE
[1]S. Yilmaz et al., “Basic factors predicting prostate cancer in Prostate Imaging Reporting and Data System-3 lesions”, New J Urol., vol. 16, no. 2, pp. 184–189, June 2021, doi: 10.33719/yud.2021;16-2-850090.
ISNAD
Yilmaz, Sercan - Yılmaz, Mehmet - Yalçın, Serdar - Kaya, Engin - Gazel, Eymen - Aybal, Halil Çağrı - Özdemir, Hakan - Yorubulut, Mehmet - Oner, Ali - Tunç, Lütfi. “Basic Factors Predicting Prostate Cancer in Prostate Imaging Reporting and Data System-3 Lesions”. Yeni Üroloji Dergisi 16/2 (June 1, 2021): 184-189. https://doi.org/10.33719/yud.2021;16-2-850090.
JAMA
1.Yilmaz S, Yılmaz M, Yalçın S, Kaya E, Gazel E, Aybal HÇ, Özdemir H, Yorubulut M, Oner A, Tunç L. Basic factors predicting prostate cancer in Prostate Imaging Reporting and Data System-3 lesions. New J Urol. 2021;16:184–189.
MLA
Yilmaz, Sercan, et al. “Basic Factors Predicting Prostate Cancer in Prostate Imaging Reporting and Data System-3 Lesions”. Yeni Üroloji Dergisi, vol. 16, no. 2, June 2021, pp. 184-9, doi:10.33719/yud.2021;16-2-850090.
Vancouver
1.Sercan Yilmaz, Mehmet Yılmaz, Serdar Yalçın, Engin Kaya, Eymen Gazel, Halil Çağrı Aybal, Hakan Özdemir, Mehmet Yorubulut, Ali Oner, Lütfi Tunç. Basic factors predicting prostate cancer in Prostate Imaging Reporting and Data System-3 lesions. New J Urol. 2021 Jun. 1;16(2):184-9. doi:10.33719/yud.2021;16-2-850090