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Br J Cancer. 2019 Jun;120(12):1120-1128. doi: 10.1038/s41416-019-0472-z. Epub 2019 May 16.

CE-MS-based urinary biomarkers to distinguish non-significant from significant prostate cancer.

Author information

1
Mosaiques diagnostics GmbH, Hannover, Germany.
2
Urology Department, Reina Sofía University Hospital, Cordoba, Spain.
3
Maimonides Institute of Biomedical Research of Cordoba (IMIBIC), Cordoba, Spain.
4
Department of Cell Biology, Physiology and Immunology, University of Cordoba (UCO), Cordoba, Spain.
5
Division of Experimental Urology, Department of Urology, Medical University of Innsbruck, Innsbruck, Austria.
6
Department of Urology, University Clinic of Schleswig-Holstein, Campus Lübeck, Lübeck, Germany.
7
CIBER Physiopathology of Obesity and Nutrition (CIBERobn), Madrid, Spain.
8
Agrifood Campus of International Excellence (CeiA3), Cordoba, Spain.
9
Urology Department, Reina Sofía University Hospital, Cordoba, Spain. julia.carrasco.sspa@juntadeandalucia.es.
10
Maimonides Institute of Biomedical Research of Cordoba (IMIBIC), Cordoba, Spain. julia.carrasco.sspa@juntadeandalucia.es.

Abstract

BACKGROUND:

Prostate cancer progresses slowly when present in low risk forms but can be lethal when it progresses to metastatic disease. A non-invasive test that can detect significant prostate cancer is needed to guide patient management.

METHODS:

Capillary electrophoresis/mass spectrometry has been employed to identify urinary peptides that may accurately detect significant prostate cancer. Urine samples from 823 patients with PSA (<15 ng/ml) were collected prior to biopsy. A case-control comparison was performed in a training set of 543 patients (nSig = 98; nnon-Sig = 445) and a validation set of 280 patients (nSig = 48, nnon-Sig = 232). Totally, 19 significant peptides were subsequently combined by a support vector machine algorithm.

RESULTS:

Independent validation of the 19-biomarker model in 280 patients resulted in a 90% sensitivity and 59% specificity, with an AUC of 0.81, outperforming PSA (AUC = 0.58) and the ERSPC-3/4 risk calculator (AUC = 0.69) in the validation set.

CONCLUSIONS:

This multi-parametric model holds promise to improve the current diagnosis of significant prostate cancer. This test as a guide to biopsy could help to decrease the number of biopsies and guide intervention. Nevertheless, further prospective validation in an external clinical cohort is required to assess the exact performance characteristics.

PMID:
31092909
DOI:
10.1038/s41416-019-0472-z

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