Prostate Cancer Diagnostic Algorithm as a "Road Map" from the First Stratification of the Patient to the Final Treatment Decision

• Published in: Life (Basel, Switzerland) Vol. 11; no. 4; p. 324
• Main Authors: Sedláčková, Hana, Dolejšová, Olga, Hora, Milan, Ferda, Jiří, Hes, Ondřej, Topolčan, Ondřej, Fuchsová, Radka, Kučera, Radek
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 07.04.2021; MDPI
• Subjects: Algorithms; Antigens; Biomarkers; Biopsy; Clinical medicine; diagnostic algorithm; Gleason score; Health services; Imaging techniques; Ligands; Literature reviews; magnetic resonance; Magnetic resonance imaging; Medical imaging; Mortality; Patients; Prostate cancer; prostate health index; Surveillance; Tumors; Ultrasonic imaging; Gleason score; diagnostic algorithm; magnetic resonance; prostate cancer; biopsy; diagnosis; prostate health index; positron emission tomography; imaging; prostate-specific membrane antigen
• ISSN: 2075-1729; 2075-1729
• DOI: 10.3390/life11040324

The diagnostics of prostate cancer are currently based on three pillars: prostate biomarker panel, imaging techniques, and histological verification. This paper presents a diagnostic algorithm that can serve as a "road map": from initial patient stratification to the final decision regarding treatment. The algorithm is based on a review of the current literature combined with our own experience. Diagnostic algorithms are a feature of an advanced healthcare system in which all steps are consciously coordinated and optimized to ensure the proper individualization of the treatment process. The prostate cancer diagnostic algorithm was created using the prostate specific antigen and in particular the Prostate Health Index in the first line of patient stratification. It then continued on the diagnostic pathway via imaging techniques, biopsy, or active surveillance, and then on to the treatment decision itself. In conclusion, the prostate cancer diagnostic algorithm presented here is a functional tool for initial patient stratification, comprehensive staging, and aggressiveness assessment. Above all, emphasis is placed on the use of the Prostate Health Index (PHI) in the first stratification of the patients as a predictor of aggressiveness and clinical stage of prostrate cancer (PCa). The inclusion of PHI in the algorithm significantly increases the accuracy and speed of the diagnostic procedure and allows to choose the optimal pathway just from the beginning. The use of advanced diagnostic techniques allows us to move towards to a more advanced level of cancer care. This diagnostics algorithm has become a standard of care in our hospital. The algorithm is continuously validated and modified based on our results.