Prostate Cancer Risk Stratification Using Artificial Intelligence-Based Multimodality Integration: A Retrospective Two-Center Study in 1,442 Patients

2020 ◽  
Author(s):  
Jie Bao ◽  
Ying Hou ◽  
Rui Zhi ◽  
Ximing Wang ◽  
Chunhong Hu ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Artificial Intelligence ◽  
Cancer Risk ◽  
Risk Stratification ◽  
Prostate Cancer Risk ◽  
Center Study

scholarly journals Entering an era of radiogenomics in prostate cancer risk stratification

2018 ◽  
Vol 7 (S4) ◽  
pp. S443-S452 ◽  
Author(s):  
Nachiketh Soodana-Prakash ◽  
Radka Stoyanova ◽  
Abhishek Bhat ◽  
Maria C. Velasquez ◽  
Omer E. Kineish ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Risk ◽  
Risk Stratification ◽  
Prostate Cancer Risk

scholarly journals Pre-treatment risk stratification of prostate cancer patients:A critical review

2012 ◽  
Vol 6 (2) ◽  
Author(s):  
George Rodrigues ◽  
Padraig Warde ◽  
Tom Pickles ◽  
Juanita Crook ◽  
Michael Brundage ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Prognostic Factors ◽  
Cancer Risk ◽  
Risk Stratification ◽  
Gleason Score ◽  
Critical Review ◽  
Specific Antigen ◽  
Prostate Cancer Risk ◽  
Original Research ◽  
Pre Treatment

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.

108 TEMPLATE TRANSPERINEAL PROSTATE MAPPING BIOPSIES FOR PROSTATE CANCER RISK STRATIFICATION AND CANCER LOCALIZATION

2010 ◽  
Vol 9 (2) ◽  
pp. 67
Author(s):  
P.B. Singh ◽  
H.U. Ahmed ◽  
D. Stevens ◽  
P. Gurung ◽  
A. Freeman ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Risk ◽  
Risk Stratification ◽  
Prostate Cancer Risk

scholarly journals Understanding PSA and its derivatives in prediction of tumor volume: addressing health disparities in prostate cancer risk stratification

Oncotarget ◽  
2017 ◽  
Vol 8 (13) ◽  
pp. 20802-20812 ◽  
Author(s):  
Felix M. Chinea ◽  
Kirill Lyapichev ◽  
Jonathan I. Epstein ◽  
Deukwoo Kwon ◽  
Paul Taylor Smith ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Health Disparities ◽  
Cancer Risk ◽  
Risk Stratification ◽  
Tumor Volume ◽  
Prostate Cancer Risk

Prostate cancer risk stratification by genotype and PSA

2009 ◽  
Vol 6 (12) ◽  
pp. 641-642 ◽  
Author(s):  
Jonathan L. Wright ◽  
Daniel W. Lin
Keyword(s):  
Prostate Cancer ◽  
Cancer Risk ◽  
Risk Stratification ◽  
Prostate Cancer Risk

scholarly journals Prostate cancer risk stratification improved across multiple ancestries with new polygenic hazard score

2021 ◽  
Author(s):  
Minh-Phuong Huynh-Le ◽  
Roshan Karunamuni ◽  
Chun Chieh Fan ◽  
Asona Lui ◽  
Wesley K Thompson ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Risk ◽  
Risk Stratification ◽  
Genetic Risk ◽  
African Ancestry ◽  
Prostate Cancer Risk ◽  
Psa Testing ◽  
Hazard Ratios ◽  
Clinically Significant ◽  
Fatal Prostate Cancer

Introduction: Prostate cancer risk stratification using single-nucleotide polymorphisms (SNPs) demonstrates considerable promise in men of European, Asian, and African genetic ancestries, but there is still need for increased accuracy. We evaluated whether including additional SNPs in a prostate cancer polygenic hazard score (PHS) would improve associations with clinically significant prostate cancer in multi-ancestry datasets. Methods: In total, 299 SNPs previously associated with prostate cancer were evaluated for inclusion in a new PHS, using a LASSO-regularized Cox proportional hazards model in a training dataset of 72,181 men from the PRACTICAL Consortium. The PHS model was evaluated in four testing datasets: African ancestry, Asian ancestry, and two of European Ancestry — the Cohort of Swedish Men (COSM) and the ProtecT study. Hazard ratios (HRs) were estimated to compare men with high versus low PHS for association with clinically significant, with any, and with fatal prostate cancer. The impact of genetic risk stratification on the positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was also measured. Results: The final model (PHS290) had 290 SNPs with non-zero coefficients. Comparing, for example, the highest and lowest quintiles of PHS290, the hazard ratios (HRs) for clinically significant prostate cancer were 13.73 [95% CI: 12.43-15.16] in ProtecT, 7.07 [6.58-7.60] in African ancestry, 10.31 [9.58-11.11] in Asian ancestry, and 11.18 [10.34-12.09] in COSM. Similar results were seen for association with any and fatal prostate cancer. Without PHS stratification, the PPV of PSA testing for clinically significant prostate cancer in ProtecT was 0.12 (0.11-0.14). For the top 20% and top 5% of PHS290, the PPV was 0.19 (0.15-0.22) and 0.26 (0.19-0.33), respectively. Conclusion: We demonstrate better genetic risk stratification for clinically significant prostate cancer than prior versions of PHS in multi-ancestry datasets. This is promising for implementing precision-medicine approaches to prostate cancer screening decisions in diverse populations.

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