Evaluation of the Predictive Role of Blood-Based Biomarkers in the Context of Suspicious Prostate MRI in Patients Undergoing Prostate Biopsy

Journal of Personalized Medicine

Pascal A. Baltzer¹  Piotr Bryniarski²  Pawel Rajwa²  Andrzej Paradysz²  Nicolai A. Huebner³  Stephan Korn³  Ekaterina Laukhtina³  Nico C. Grossmann³  Dadjar I. Hostermann³  Takafumi Yanagisawa³  Abdulmajeed Aydh³  Reza Sari Motlagh³  Fahad Quhal³  Keiichiro Mori³  Bernhard Grubmüller³  Victor M. Schuettfort³  Shahrokh F. Shariat³  Benjamin Pradere³  Hadi Mostafaei³  Frederik König³ 

[1] Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria;Department of Urology, Medical University of Silesia, 41-800 Zabrze, Poland;Department of Urology, Medical University of Vienna, 1090 Vienna, Austria;

关键词: MRI;    biopsy;    dNLR;    NLR;    PNI;    prostate cancer;   

DOI  :  10.3390/jpm11111231

来源: DOAJ

【 摘 要 】

The aim of this study was to assess the predictive value of pre-biopsy blood-based markers in patients undergoing a fusion biopsy for suspicious prostate magnetic resonance imaging (MRI). We identified 365 consecutive patients who underwent MRI-targeted and systematic prostate biopsy for an MRI scored Prostate Imaging–Reporting and Data System Version (PI-RADS) ≥ 3. We evaluated the neutrophil/lymphocyte ratio (NLR), derived neutrophil/lymphocyte ratio (dNLR), platelet/lymphocyte ratio (PLR), systemic immune inflammation index (SII), lymphocyte/monocyte ratio (LMR,) de Ritis ratio, modified Glasgow Prognostic Score (mGPS), and prognostic nutrition index (PNI). Uni- and multivariable logistic models were used to analyze the association of the biomarkers with biopsy findings. The clinical benefits of biomarkers implemented in clinical decision-making were assessed using decision curve analysis (DCA). In total, 69% and 58% of patients were diagnosed with any prostate cancer and Gleason Grade (GG) ≥ 2, respectively. On multivariable analysis, only high dNLR (odds ratio (OR) 2.61, 95% confidence interval (CI) 1.23–5.56, p = 0.02) and low PNI (OR 0.48, 95% CI 0.26–0.88, p = 0.02) remained independent predictors for GG ≥ 2. The logistic regression models with biomarkers reached AUCs of 0.824–0.849 for GG ≥ 2. The addition of dNLR and PNI did not enhance the net benefit of a standard clinical model. Finally, we created the nomogram that may help guide biopsy avoidance in patients with suspicious MRI. In patients with PI-RADS ≥ 3 lesions undergoing MRI-targeted and systematic biopsy, a high dNLR and low PNI were associated with unfavorable biopsy outcomes. Pre-biopsy blood-based biomarkers did not, however, significantly improve the discriminatory power and failed to add a clinical benefit beyond standard clinical factors.

【 授权许可】

Unknown