Skip to main content
Log in

Efficacy of plasma atherogenic index in predicting malignancy in the presence of Prostate Imaging–Reporting and Data System 3 (PI-RADS 3) prostate lesions

  • Urology - Original Paper
  • Published:
International Urology and Nephrology Aims and scope Submit manuscript

Abstract

Purpose

Plasma atherogenic index (PAI) was shown to be positively correlated with the presence of malignity in patients with suspicious findings for renal cell cancer and colon cancer in reported studies. In this study, we aimed to evaluate whether there is an association with the presence of malignity in patients PI-RADS 3 prostate lesions and PAI.

Methods

This retrospective study reviewed the data of 139 patients who underwent transrectal ultrasonography-guided systematic and cognitive fusion prostate biopsy for PI-RADS 3 lesions in multiparametric magnetic resonance imaging. The patients were divided to two groups as malign (n = 33) and benign (n = 106). The association between age, body mass index, comorbidities, smoking status, prostate-specific antigen (PSA), PSA density, free/total PSA, prostate weight, lesion diameter, triglyceride value, high-density lipoprotein-cholesterol value, PAI value data and presence of malignity were investigated by descriptive, multivariate and receiver-operating characteristic (ROC) analysis.

Results

PSA, PSAD, lesion diameter and PAI value were statistically significantly higher in the malignant group compared to the benign group, and the free/total PSA ratio was lower. In multivariate logistic regression analysis, PSA > 9.9 ng/ml, free/total PSA < 12.1%, lesion diameter > 13.5 mm and PAI > 0.13 were identified as independent risk factors for presence of prostate malignancy.

Conclusion

PAI was found to be a predictive parameter for prostate cancer in PI-RADS 3 prostate lesions. Our study can open new thoughts about PAI as metric to assess the prostate cancer risk.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

Data availability

The data that support the findings of this study are openly available in Figshare Repository at https://figshare.com/s/1b5021c69e26f68be453.

Code availability

Not applicable.

References

  1. Ferlay J, Ervik M, Lam F et al (2020) Global cancer observatory: cancer today. Available online at: https://www.gco.iarc.fr/today/ Accessed 29 Aug 2022.

  2. Culp MB, Soerjomataram I, Efstathiou JA, Bray F, Jemal A (2020) Recent global patterns in prostate cancer incidence and mortality rates. Eur Urol 77:38–52

    Article  Google Scholar 

  3. EAU Guidelines Office (2022) Arnhem, the Netherlands. EAU guidelines. Edn. presented at the EAU Annual Congress Amsterdam

  4. Barkovich EJ, Shankar PR, Westphalen AC (2019) A systematic review of the existing prostate imaging reporting and data system version 2 (PI-RADSv2) literature and subset meta-analysis of PI-RADSv2 categories stratified by Gleason scores. AJR Am J Roentgenol 212:847–854

    Article  Google Scholar 

  5. Eklund M, Jäderling F, Discacciati A et al (2021) MRI-targeted or standard biopsy in prostate cancer screening. N Engl J Med 385:908–920

    Article  Google Scholar 

  6. Houlahan KE, Salmasi A, Sadun TY et al (2019) Molecular hallmarks of multiparametric magnetic resonance imaging visibility in prostate cancer. Eur Urol 76:18–23

    Article  CAS  Google Scholar 

  7. Eldred-Evans D, Burak P, Connor MJ et al (2021) Population-based prostate cancer screening with magnetic resonance imaging or ultrasonography: the IP1-PROSTAGRAM study. JAMA Oncol 7:395–402

    Article  Google Scholar 

  8. Kim L, Boxall N, George A et al (2020) Clinical utility and cost modelling of the phi test to triage referrals into image-based diagnostic services for suspected prostate cancer: the PRIM (Phi to RefIne Mri) study. BMC Med 18:1–9

    Article  CAS  Google Scholar 

  9. Giambelluca D, Cannella R, Vernuccio F et al (2021) PI-RADS 3 lesions: role of prostate MRI texture analysis in the identification of prostate cancer. Curr Probl Diagn Radiol 50:175–185

    Article  Google Scholar 

  10. Esposito K, Chiodini P, Capuano A et al (2013) Effect of metabolic syndrome and its components on prostate cancer risk: meta-analysis. J Endocrinol Invest 36:132–139

    Article  CAS  Google Scholar 

  11. Blanc-Lapierre A, Spence A, Karakiewicz PI, Aprikian A, Saad F, Parent M-É (2015) Metabolic syndrome and prostate cancer risk in a population-based case–control study in Montreal, Canada. BMC Public Health 15:1–11

    Article  Google Scholar 

  12. Vidal AC, Howard LE, Moreira DM, Castro-Santamaria R, Andriole GL, Freedland SJ (2014) obesity increases the risk for high-grade prostate cancer: results from the REDUCE study. Cancer Epidemiol Biomark Prev Cancer Epidemiol 23:2936–2942

    Article  CAS  Google Scholar 

  13. Freedland S, Hamilton R, Gerber L et al (2013) Statin use and risk of prostate cancer and high-grade prostate cancer: results from the REDUCE study. Prostate Cancer Prostatic Dis 16:254–259

    Article  CAS  Google Scholar 

  14. Munir R, Usman H, Hasnain S, Smans K, Kalbacher H, Zaidi N (2014) Atypical plasma lipid profile in cancer patients: cause or consequence? Biochimie 102:9–18

    Article  CAS  Google Scholar 

  15. Pirro M, Ricciuti B, Rader DJ, Catapano AL, Sahebkar A, Banach M (2018) High density lipoprotein cholesterol and cancer: marker or causative? Prog Lipid Res 71:54–69

    Article  CAS  Google Scholar 

  16. Fernández-Macías JC, Ochoa-Martínez AC, Varela-Silva JA, Pérez-Maldonado IN (2019) Atherogenic index of plasma: novel predictive biomarker for cardiovascular illnesses. Arch Med Res 50:285–294

    Article  Google Scholar 

  17. Karabay E, Karsiyakali N, Duvar S, Tosun C, Aslan AR, Yucebas OE (2019) Relationship between plasma atherogenic index and final pathology of Bosniak III-IV renal masses: a retrospective, single-center study. BMC Urol 19:1–7

    Article  CAS  Google Scholar 

  18. Gundogdu UD, Coban FK (2021) A study of atherogenic plasma and triglyceride-glucose indices and monocyte/HDL-C ratios in colon cancer patients. J Pharm Res Int 33(46):213–217

    Article  Google Scholar 

  19. Weinreb JC, Barentsz JO, Choyke PL et al (2016) PI-RADS prostate imaging–reporting and data system: 2015, version 2. Eur Urol 69:16–40

    Article  Google Scholar 

  20. Wang F-M, Zhang Y (2019) High lipoprotein (a) level is independently associated with adverse clinicopathological features in patients with prostate cancer. Dis Markers 2019:9483935

  21. Kotani K, Sekine Y, Ishikawa S, Ikpot IZ, Suzuki K, Remaley AT (2013) High-density lipoprotein and prostate cancer: an overview. J Epidemiol 23:313–319

    Article  Google Scholar 

  22. Jamnagerwalla J, Howard LE, Allott EH et al (2018) Serum cholesterol and risk of high-grade prostate cancer: results from the REDUCE study. Prostate Cancer Prostatic Dis 21:252–259

    Article  CAS  Google Scholar 

  23. Wolny-Rokicka EI, Tukiendorf A, Wydmański J, Zembroń-Łacny A (2017) The comparison and estimation of the prognostic value of lipid profiles in patients with prostate cancer depends on cancer stage advancement. Am J Mens Health 11:1745–1751

    Article  Google Scholar 

  24. Wan F, Qin X, Zhang G et al (2015) Oxidized low-density lipoprotein is associated with advanced-stage prostate cancer. Tumour Biol 36:3573–3582

    Article  CAS  Google Scholar 

Download references

Funding

The author(s) received no financial support for the research or authorship.

Author information

Authors and Affiliations

Authors

Contributions

Conception and design: SS, AK, and ST; data acquisition: KC, EU, and MEP; data analysis and interpretation: YK, KC, and FS; drafting the manuscript: SS and AK; critical revision of the manuscript for scientific and factual content: MEP; statistical analysis: SS; supervision: EO.

Corresponding author

Correspondence to Samet Senel.

Ethics declarations

Conflict of interest

The authors report no conflicts of interest.

Ethical approval

The present study protocol was reviewed and approved by the Institutional Review Board of Ankara City Hospital (approval number: E2-22-2396).

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Senel, S., Ceviz, K., Kasap, Y. et al. Efficacy of plasma atherogenic index in predicting malignancy in the presence of Prostate Imaging–Reporting and Data System 3 (PI-RADS 3) prostate lesions. Int Urol Nephrol 55, 255–261 (2023). https://doi.org/10.1007/s11255-022-03409-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11255-022-03409-9

Keywords

Navigation