Plasma and urine biomarker algorithm versus systematic biopsy for prostate cancer detection in elderly men: a randomised trial with early termination for futility
DOI:
https://doi.org/10.2340/sju.v61.45464Keywords:
Prostate cancer, biomarkers, prostate biopsyAbstract
Objective: This study aimed to compare test sensitivity for detecting aggressive prostate cancer and test specificity (measured by reduction in prostate biopsies) between algorithm-triage and standard systematic biopsy in elderly men with suspected prostate cancer.
Methods: This randomised controlled trial enrolled men ≥ 70 years old suspected of prostate cancer and randomised them 1:1 to algorithm-triage or standard systematic biopsies. The algorithm arm used a 10-gene mRNA panel from urine and plasma samples, integrated with clinical characteristics and PSA measurements to predict prostate cancer with International Society of Urological Pathology grade group ≥ 2. Patient-reported outcomes measures were collected using the Functional Assessment of Cancer Therapy-Prostate (FACT-P) scores or subdomains throughout a 24-month follow-up. ClinicalTrials.gov: NCT04079699.
Results: A total of 202 men were included between October 2019 and September 2021. The study was terminated early due to algorithm underperformance. The algorithm-triage arm detected fewer indolent cancers (7.9% vs. 19%, absolute difference −10.9 percentage points, 95% confidence interval [CI]: −21.0 to −1.0 pp, P = 0.039) but also fewer clinically significant cancers (26% vs. 40%, absolute difference −13.9 percentage points, 95% CI: −27.6 to −0.1 pp, P = 0.051) compared to systematic biopsy. Patient-reported outcomes showed no significant between-group differences in FACT-P scores or subdomains throughout 24-month follow-up (differences 0.1–2.2 points, all P > 0.05), indicating comparable quality of life.
Conclusion: The biomarker-based algorithm-triage reduced biopsy numbers but also detected fewer clinically significant prostate cancers. Quality of life was comparable between approaches.
Downloads
References
Vickers A, O’Brien F, Montorsi F, et al. Current policies on early detection of prostate cancer create overdiagnosis and inequity with min-imal benefit. BMJ. 2023;381:e071082. https://doi.org/10.1136/bmj-2022-071082 DOI: https://doi.org/10.1136/bmj-2022-071082
Loeb S, Bjurlin MA, Nicholson J, et al. Overdiagnosis and overtreatment of prostate cancer. Eur Urol. 2014;65:1046–1055. https://doi.org/10.1016/j.eururo.2013.12.062 DOI: https://doi.org/10.1016/j.eururo.2013.12.062
David MK, Leslie SW. Prostate-specific antigen. StatPearls [Internet]. Treasure Island, FL: StatPearls Publishing; 2025 [cited 2025 Apr 22]. Available from: http://www.ncbi.nlm.nih.gov/books/NBK557495/
Ploussard G, de la Taille A. The role of prostate cancer antigen 3 (PCA3) in prostate cancer detection. Expert Rev Anticancer Ther. 2018;18: 1013–1020. https://doi.org/10.1080/14737140.2018.1502086 DOI: https://doi.org/10.1080/14737140.2018.1502086
Tosoian JJ, Zhang Y, Xiao L, et al. Development and validation of an 18-gene urine test for high-grade prostate cancer. JAMA Oncol. 2024;10:726–736. https://doi.org/10.1001/jamaoncol.2024.0455 DOI: https://doi.org/10.1001/jamaoncol.2024.0455
Hendriks RJ, van der Leest MMG, Israël B, et al. Clinical use of the SelectMDx urinary-biomarker test with or without mpMRI in prostate cancer diagnosis: a prospective, multicenter study in biopsy-naïve men. Prostate Cancer Prostatic Dis. 2021;24:1110–1119. https://doi.org/10.1038/s41391-021-00367-8 DOI: https://doi.org/10.1038/s41391-021-00367-8
Margolis E, Brown G, Partin A, et al. Predicting high-grade prostate cancer at initial biopsy: clinical performance of the ExoDx (EPI) Prostate Intelliscore test in three independent prospective studies. Prostate Cancer Prostatic Dis. 2022;25:296–301. https://doi.org/10.1038/s41391-021-00456-8 DOI: https://doi.org/10.1038/s41391-021-00456-8
Nordström T, Vickers A, Assel M, et al. Comparison between the four-kallikrein panel and prostate health index for predicting prostate cancer. Eur Urol. 2015;68:139–146. https://doi.org/10.1016/j.eururo.2014.08.010 DOI: https://doi.org/10.1016/j.eururo.2014.08.010
Wagaskar VG, Sobotka S, Ratnani P, et al. A 4K score/MRI-based nomogram for predicting prostate cancer, clinically significant prostate cancer, and unfavorable prostate cancer. Cancer Rep (Hoboken). 2021;4:e1357. https://doi.org/10.1002/cnr2.1357 DOI: https://doi.org/10.1002/cnr2.1357
Albitar M, Ma W, Lund L, et al. A multi-center prospective study to validate an algorithm using urine and plasma biomarkers for predicting Gleason ≥3+4 prostate cancer on biopsy. J Cancer. 2017;8:2554–2560. https://doi.org/10.7150/jca.20031 DOI: https://doi.org/10.7150/jca.20031
Albitar M, Ma W, Lund L, et al. Predicting prostate biopsy results using a panel of plasma and urine biomarkers combined in a scoring system. J Cancer. 2016;7:297–303. https://doi.org/10.7150/jca.12771 DOI: https://doi.org/10.7150/jca.12771
Ma W, Diep K, Fritsche HA, et al. Diagnostic and prognostic scoring system for prostate cancer using urine and plasma biomarkers. Genet Test Mol Biomarkers. 2014;18:156–163. https://doi.org/10.1089/gtmb.2013.0424 DOI: https://doi.org/10.1089/gtmb.2013.0424
Poulsen MH, Feddersen S, Albitar M, et al. A prospective study of a urine and plasma biomarker test for the prediction of gleason ≥ 3 + 4 prostate cancer in a mixed cohort. Scand J Urol. 2020;54:323–327. https://doi.org/10.1080/21681805.2020.1782979 DOI: https://doi.org/10.1080/21681805.2020.1782979
Pedersen TB, Poulsen MH, Lund M, et al. Prospective validation study of a combined urine and plasma test for predicting high-grade pros-tate cancer in biopsy naïve men. Scand J Urol. 2025;60:8–13. https://doi.org/10.2340/sju.v60.42752 DOI: https://doi.org/10.2340/sju.v60.42752
Brewster DH, Fischbacher CM, Nolan J, et al. Risk of hospitalization and death following prostate biopsy in Scotland. Public Health. 2017;142:102–110. https://doi.org/10.1016/j.puhe.2016.10.006 DOI: https://doi.org/10.1016/j.puhe.2016.10.006
Albertsen PC, Hanley JA, Fine J. 20-year outcomes following conservative management of clinically localized prostate cancer. JAMA. 2005;293:2095–2101. https://doi.org/10.1001/jama.293.17.2095 DOI: https://doi.org/10.1001/jama.293.17.2095
Thomsen FF, Garmo H, Egevad L, et al. Temporal trend in risk of prostate cancer death in men with favourable-risk prostate cancer. Scand J Urol. 2024;59:76–83. https://doi.org/10.2340/sju.v59.34015 DOI: https://doi.org/10.2340/sju.v59.34015
Stranne J. 2023/2024 update of the national prostate cancer guidelines in Sweden. Scand J Urol. 2024;59:210–211. https://doi.org/10.2340/sju.v59.42656 DOI: https://doi.org/10.2340/sju.v59.42656
Harris PA, Taylor R, Minor BL, et al. The REDCap consortium: building an international community of software platform partners. J Biomed Inform. 2019;95:103208. https://doi.org/10.1016/j.jbi.2019.103208 DOI: https://doi.org/10.1016/j.jbi.2019.103208
Harris PA, Taylor R, Thielke R, et al. Research electronic data capture (REDCap) – a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377–381. https://doi.org/10.1016/j.jbi.2008.08.010 DOI: https://doi.org/10.1016/j.jbi.2008.08.010
Pocock SJ. Clinical trials with multiple outcomes: a statistical perspective on their design, analysis, and interpretation. Control Clin Trials. 1997;18:530–545; discussion 546–549. https://doi.org/10.1016/S0197-2456(97)00008-1 DOI: https://doi.org/10.1016/S0197-2456(97)00008-1
Machin D, Campbell MJ, Tan S-B. Sample size tables for clinical studies. 3rd ed. Chichester, UK: Wiley; 2009. DOI: https://doi.org/10.1002/9781444300710
Lazarovich A, Vigneswaran H, Palsdottir T, et al. A comparison of Stockholm3, serum biomarkers, and risk calculators to predict prostate cancer in a racially and ethnically diverse cohort: evaluation of the Stockholm3 multiethnic SEPTA Trial. J Urol. 2025;213:590–599. https://doi.org/10.1097/JU.0000000000004437 DOI: https://doi.org/10.1097/JU.0000000000004437
Nordström T, Discacciati A, Bergman M, et al. Prostate cancer screening using a combination of risk-prediction, MRI, and targeted prostate biopsies (STHLM3-MRI): a prospective, population-based, randomised, open-label, non-inferiority trial. Lancet Oncol [Internet]. 2021;22:1240–1249. https://doi.org/10.1016/S1470-2045(21)00348-X DOI: https://doi.org/10.1016/S1470-2045(21)00348-X
Vigneswaran HT, Eklund M, Discacciati A, et al. Stockholm3 in a multiethnic cohort for Prostate Cancer Detection (SEPTA): a prospective multicentered trial. J Clin Oncol. 2024;42:3806–3816. https://doi.org/10.1200/JCO.24.00152 DOI: https://doi.org/10.1200/JCO.24.00152
Ahmed HU, El-Shater Bosaily A, Brown LC, et al. Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PRO-MIS): a paired validating confirmatory study. Lancet. 2017;389:815–822. https://doi.org/10.1016/S0140-6736(16)32401-1 DOI: https://doi.org/10.1016/S0140-6736(16)32401-1
Ng ABCD, Asif A, Agarwal R, et al. Biparametric vs multiparametric MRI for prostate cancer diagnosis: the PRIME diagnostic clinical trial. JAMA [Internet]. 2025;334:1170–1179. https://doi.org/10.1001/jama.2025.13722 DOI: https://doi.org/10.1001/jama.2025.13722
Shao L, Liang C, Yan Y, et al. An MRI-pathology foundation model for noninvasive diagnosis and grading of prostate cancer. Nat Cancer. 2025;6:1621–1637. https://doi.org/10.1038/s43018-025-01041-x DOI: https://doi.org/10.1038/s43018-025-01041-x
Shankar PR, Ellimoottil C, George AK, et al. Testing-related health impact of transrectal and transperineal prostate biopsy as assessed by health utilities. J Urol. 2021;206:1403–1410. https://doi.org/10.1097/JU.0000000000002118 DOI: https://doi.org/10.1097/JU.0000000000002118
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Torben Brøchner Pedersen, Charlotte Aaberg Poulsen, Martin Lund, Maher Albitar, Louise Dorner Østergaard, Søren Feddersen, Lars Lund, Mads Hvid Poulsen
This work is licensed under a Creative Commons Attribution 4.0 International License.
As from Volume 59 (2024) all published articles, unless otherwise specified, are published under CC-BY license, allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material, with the condition of proper attribution to the original work.
