scholarly journals Automating the Determination of Prostate Cancer Risk Strata From Electronic Medical Records

2017 ◽  
pp. 1-8 ◽  
Author(s):  
Justin R. Gregg ◽  
Maximilian Lang ◽  
Lucy L. Wang ◽  
Matthew J. Resnick ◽  
Sandeep K. Jain ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Risk ◽  
Risk Stratification ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Gleason Score ◽  
Cancer Care ◽  
Clinical Stage ◽  
Prostate Cancer Risk ◽  
Risk Stratum

Purpose Risk stratification underlies system-wide efforts to promote the delivery of appropriate prostate cancer care. Although the elements of risk stratum are available in the electronic medical record, manual data collection is resource intensive. Therefore, we investigated the feasibility and accuracy of an automated data extraction method using natural language processing (NLP) to determine prostate cancer risk stratum. Methods Manually collected clinical stage, biopsy Gleason score, and preoperative prostate-specific antigen (PSA) values from our prospective prostatectomy database were used to categorize patients as low, intermediate, or high risk by D’Amico risk classification. NLP algorithms were developed to automate the extraction of the same data points from the electronic medical record, and risk strata were recalculated. The ability of NLP to identify elements sufficient to calculate risk (recall) was calculated, and the accuracy of NLP was compared with that of manually collected data using the weighted Cohen’s κ statistic. Results Of the 2,352 patients with available data who underwent prostatectomy from 2010 to 2014, NLP identified sufficient elements to calculate risk for 1,833 (recall, 78%). NLP had a 91% raw agreement with manual risk stratification (κ = 0.92; 95% CI, 0.90 to 0.93). The κ statistics for PSA, Gleason score, and clinical stage extraction by NLP were 0.86, 0.91, and 0.89, respectively; 91.9% of extracted PSA values were within ± 1.0 ng/mL of the manually collected PSA levels. Conclusion NLP can achieve more than 90% accuracy on D’Amico risk stratification of localized prostate cancer, with adequate recall. This figure is comparable to other NLP tasks and illustrates the known tradeoff between recall and accuracy. Automating the collection of risk characteristics could be used to power real-time decision support tools and scale up quality measurement in cancer care.

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.

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

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

Identification of prostate cancer risk categories according to surgical margins status, pathological stage and Gleason score

2013 ◽  
Vol 20 (11) ◽  
pp. 1097-1103 ◽  
Author(s):  
Riccardo Schiavina ◽  
Marco Borghesi ◽  
Michelangelo Fiorentino ◽  
Eugenio Brunocilla ◽  
Fabio Manferrari ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Risk ◽  
Gleason Score ◽  
Prostate Cancer Risk ◽  
Surgical Margins ◽  
Pathological Stage ◽  
Risk Categories

Is clinical stage T2c prostate cancer intermediate- or high-risk disease? Results from the SEARCH database.

2012 ◽  
Vol 30 (5_suppl) ◽  
pp. 123-123
Author(s):  
Abhay A Singh ◽  
Leah Gerber ◽  
Stephen J. Freedland ◽  
William J Aronson ◽  
Martha K. Terris ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
High Risk ◽  
Risk Stratification ◽  
Predictive Accuracy ◽  
Cox Model ◽  
Clinical Stage ◽  
Prostate Cancer Risk ◽  
Clinical Staging ◽  
Intermediate Risk ◽  
Concordance Index

123 Background: Clinical stage T2c is a nebulous factor in the algorithm for prostate cancer risk stratification. According to D’Amico risk stratification cT2c is high-risk category where NCCN guidelines place this stage in intermediate-risk. As diagnostic work up with the use of MRI continues to escalate clinical staging may become more important. As cT2c represents a possible decision fork in treatment decisions we sought to investigate which risk group the clinical behavior of cT2c tumors more closely resembles. Methods: We retrospectively analyzed data from 1089 men who underwent radical prostatectomy (RP) from 1988 to 2009 who did not have low-risk CaP from the SEARCH database. We compared time to BCR between men with cT2c disease, those with intermediate-risk (PSA 10-20 ng/ml or Gleason sum (GS) =7), and those with high-risk (PSA>20 ng/ml, GS 8-10, cT3) using Cox regression models adjusting for age, race, year of RP, center, and percent cores positive. We also compared predictive accuracy of two Cox models wherein cT2c was considered either intermediate- or high-risk by calculating concordance index c. Results: A total of 68 men (3.4%) had cT2c tumors. After a median follow-up of 47.5 months, there was no difference in BCR risk between men with intermediate-risk CaP and those with cT2c tumors (HR=0.90; p=0.60). In contrast, there was a trend for men with high-risk CaP to have nearly 50% increased BCR risk compared to men with cT2c tumors (HR=1.50; 95% CI=0.97-2.30; p=0.07) which did not reach statistical significance. Concordance index c was higher in the Cox model wherein cT2c tumors were considered intermediate-risk (c=0.6147) as opposed to high-risk (c=0.6106). Conclusions: BCR risk for patients with clinical stage T2c was more comparable to men who had intermediate-risk CaP than men with high-risk. In addition, a model which incorporates cT2c disease as intermediate-risk has better predictive accuracy. These findings suggest men with cT2c disease should be offered treatment options for men with intermediate-risk CaP. As clinical staging more routinely incorporates MRI there is the potential to better identify bilateral organ-confined CaP and further establish risk classification.

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
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