Prognostic factors in prostate Cancer: A Review Article

Introduction: The use of accepted prostate cancer risk stratification groups based on prostate-specific antigen, T stage and Gleason score assists in therapeutic treatment decision-making, clinical trial design and outcome reporting. The utility of integrating novel prognostic factors into an updated risk stratification schema is an area of current debate. The purpose of this work is to critically review the available literature on novel pre-treatment prognostic factors and alternative prostate cancer risk stratification schema to assess the feasibility and need for changes to existing risk stratification systems. Methods: A systematic literature search was conducted to identify original research publications and review articles on prognostic factors and risk stratification in prostate cancer. Search terms included risk stratification, risk assessment, prostate cancer or neoplasms, and prognostic factors. Abstracted information was assessed to draw conclusions regarding the potential utility of changes to existing risk stratification schema. Results: The critical review identified three specific clinically relevant potential changes to the most commonly used three-group risk stratification system: (1) the creation of a very-low risk category; (2) the splitting of intermediate-risk into a low- and highintermediate risk groups; and (3) the clarification of the interface between intermediate- and high-risk disease. Novel pathological factors regarding high-grade cancer, subtypes of Gleason score 7 and percentage biopsy cores positive were also identified as potentially important risk-stratification factors. Conclusions: Multiple studies of prognostic factors have been performed to create currently utilized prostate cancer risk stratification systems. We propose potential changes to existing systems.

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Dynamic Contrast-Enhanced Imaging as a Prognostic Tool in Early Diagnosis of Prostate Cancer: Correlation with PSA and Clinical Stage

Contrast Media & Molecular Imaging ◽

10.1155/2018/3181258 ◽

2018 ◽

Vol 2018 ◽

pp. 1-7 ◽

Cited By ~ 2

Author(s):

Xingchen Wu ◽

Petri Reinikainen ◽

Mika Kapanen ◽

Tuula Vierikko ◽

Pertti Ryymin ◽

...

Keyword(s):

Prostate Cancer ◽

Prognostic Factors ◽

Early Diagnosis ◽

Early Stage ◽

Clinical Stage ◽

Specific Antigen ◽

Transfer Constant ◽

Dce Mri ◽

Dynamic Contrast Enhanced ◽

Contrast Enhanced

Background and Purpose. Although several methods have been developed to predict the outcome of patients with prostate cancer, early diagnosis of individual patient remains challenging. The aim of the present study was to correlate tumor perfusion parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and clinical prognostic factors and further to explore the diagnostic value of DCE-MRI parameters in early stage prostate cancer. Patients and Methods. Sixty-two newly diagnosed patients with histologically proven prostate adenocarcinoma were enrolled in our prospective study. Transrectal ultrasound-guided biopsy (12 cores, 6 on each lobe) was performed in each patient. Pathology was reviewed and graded according to the Gleason system. DCE-MRI was performed and analyzed using a two-compartmental model; quantitative parameters including volume transfer constant (Ktrans), reflux constant (Kep), and initial area under curve (iAUC) were calculated from the tumors and correlated with prostate-specific antigen (PSA), Gleason score, and clinical stage. Results. Ktrans (0.11 ± 0.02 min−1 versus 0.16 ± 0.06 min−1; p<0.05), Kep (0.38 ± 0.08 min−1 versus 0.60 ± 0.23 min−1; p<0.01), and iAUC (14.33 ± 2.66 mmoL/L/min versus 17.40 ± 5.97 mmoL/L/min; p<0.05) were all lower in the clinical stage T1c tumors (tumor number, n=11) than that of tumors in clinical stage T2 (n=58). Serum PSA correlated with both tumor Ktrans (r=0.304, p<0.05) and iAUC (r=0.258, p<0.05). Conclusions. Our study has confirmed that DCE-MRI is a promising biomarker that reflects the microcirculation of prostate cancer. DCE-MRI in combination with clinical prognostic factors may provide an effective new tool for the basis of early diagnosis and treatment decisions.

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