scholarly journals The ReIMAGINE Multimodal Warehouse: Using Artificial Intelligence for Accurate Risk Stratification of Prostate Cancer

2021 ◽  
Vol 4 ◽  
Author(s):  
Aida Santaolalla ◽  
Tim Hulsen ◽  
Jenson Davis ◽  
Hashim U. Ahmed ◽  
Caroline M. Moore ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
At Risk ◽  
Risk Stratification ◽  
Digital Pathology ◽  
Clinical Information ◽  
Medical Community ◽  
Tissue Samples ◽  
Improve Risk Stratification ◽  
Stratification Method ◽  
Access Rights

Introduction. Prostate cancer (PCa) is the most frequent cancer diagnosis in men worldwide. Our ability to identify those men whose cancer will decrease their lifespan and/or quality of life remains poor. The ReIMAGINE Consortium has been established to improve PCa diagnosis.Materials and methods. MRI will likely become the future cornerstone of the risk-stratification process for men at risk of early prostate cancer. We will, for the first time, be able to combine the underlying molecular changes in PCa with the state-of-the-art imaging. ReIMAGINE Screening invites men for MRI and PSA evaluation. ReIMAGINE Risk includes men at risk of prostate cancer based on MRI, and includes biomarker testing.Results. Baseline clinical information, genomics, blood, urine, fresh prostate tissue samples, digital pathology and radiomics data will be analysed. Data will be de-identified, stored with correlated mpMRI disease endotypes and linked with long term follow-up outcomes in an instance of the Philips Clinical Data Lake, consisting of cloud-based software. The ReIMAGINE platform includes application programming interfaces and a user interface that allows users to browse data, select cohorts, manage users and access rights, query data, and more. Connection to analytics tools such as Python allows statistical and stratification method pipelines to run profiling regression analyses. Discussion. The ReIMAGINE Multimodal Warehouse comprises a unique data source for PCa research, to improve risk stratification for PCa and inform clinical practice. The de-identified dataset characterized by clinical, imaging, genomics and digital pathology PCa patient phenotypes will be a valuable resource for the scientific and medical community.

Improving risk-stratification of localized prostate cancer in a prospective active surveillance cohort.

2018 ◽  
Vol 36 (6_suppl) ◽  
pp. 104-104
Author(s):  
Justin Gregg ◽  
Chad A. Reichard ◽  
Xuemei Wang ◽  
Brian Francis Chapin ◽  
Louis L. Pisters ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Risk Stratification ◽  
Active Surveillance ◽  
Proportional Hazards ◽  
Specific Antigen ◽  
Cox Proportional Hazards ◽  
Tumor Length ◽  
Improve Risk Stratification ◽  
Optimal Monitoring ◽  
Significant Difference

104 Background: Prospective active surveillance (AS) studies in men with low- and intermediate-risk prostate cancer (PCa) have demonstrated feasibility, but no consensus supports an optimal monitoring scheme. To expand our findings on AS disease reclassification, we examined predictors of disease reclassification in a prospective single-institution AS study. Methods: Men with localized PCa diagnosed within 6 months (mos) of AS enrollment were stratified into four groups: group 1 (Gr 1) was defined by a Gleason score (GS) ≤6 (3+3), one positive (pos) core ( < 3 mm), and a prostate-specific antigen (PSA) level < 4 ng/mL (adjusted by prostate size); Gr IIa by GS 6, one pos core, and either tumor length ≥3 mm or PSA ≥4 ng/mL; Gr IIb by GS6, > one pos core, and any PSA level or tumor length; Gr IIc by GS7, > one pos core or any PSA. Monitoring included PSA and digital rectal exam every 6 mo. Biopsy (BX) was repeated at 1 year and then on a predetermined BX scheme. Patients with reclassified disease (upgrading, increase in pos cores and/or tumor length) were offered treatment. Cox proportional hazards modeling was used to determine the association of baseline clinicopathologic parameters with time to reclassification. Results: Between 2006 and 2015, 803 patients met criteria for inclusion: Gr I, 242; Gr IIa, 67; Gr IIb, 376; Gr IIc, 118. Median age was 64 years (range, 36–83), 662 (82.4%) were white, 703 (87.5%) had cT1c disease, 687 (85.6%) had GS 6, and median PSA level was 4.2 ng/mL (range 0.2–34). At a median follow-up of 2.9 years, 249 (31.0%) men had disease reclassification and 258 (32.1%) left AS to pursue curative treatment. Overall, 82% of reclassifications occurred within 3 years of study enrollment. Stratification to group IIb/IIc was significantly associated with time to reclassification compared to Gr I/IIa (HR 2.13, 95 CI 1.63-2.80, p < 0.001) while CAPRA score did not show a significant difference (p = 0.27). Conclusions: Grouping patients on characteristics including tumor length and pos core number may improve risk stratification in localized PCa. Risk-based surveillance protocols merit further evaluation. Clinical trial information: NCT00490763.

Validation of a 17-Gene Genomic Prostate Score (GPS) as a predictor of biochemical recurrence (BCR) in men with prostate cancer treated with radical prostatectomy (RP) in a community setting.

2017 ◽  
Vol 35 (6_suppl) ◽  
pp. 41-41
Author(s):  
Stephen K. VanDenEeden ◽  
Nan Zhang ◽  
Charles P Quesenberry ◽  
Jeong S Han ◽  
Amethyst D Leimpeter ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Risk Stratification ◽  
Proportional Hazards ◽  
Community Setting ◽  
Cox Proportional Hazards ◽  
Sampling Weights ◽  
Eligibility Criteria ◽  
Full Spectrum ◽  
Clinical Risk ◽  
Improve Risk Stratification

41 Background: Validated biomarkers can improve risk stratification for men with prostate cancer (PCa). A biopsy-based RT-PCR assay that provides a GPS (scale 0-100) has been validated as an independent predictor of adverse surgical pathology and BCR after RP in men with low-risk and low-volume intermediate-risk PCa. We sought to confirm that GPS is a predictor of BCR across the full spectrum of clinical risk (low, intermediate and high) in a large cohort of men with long term follow up within Kaiser Permanente Northern California (KPNC). Methods: From the KPNC clinical database of 6,184 RP treated men diagnosed with NCCN very low, low, intermediate and high-risk PCa between 1995- 2010, we performed a retrospective cohort study using stratified cohort sampling. BCR was defined as either 2 successive post-RP PSAs ≥ 0.2, or initiation of salvage therapy after a rising PSA ≥ 0.1. Archival biopsy tissue was assayed to yield a GPS. Univariable and multivariable Cox proportional hazards models were used to estimate the association, accounting for sampling weights and covariates. Results: Tissue was retrieved for 334 patients. 279 met all eligibility criteria and 259 (93%) generated a valid GPS. The cohort consisted of 117 BCR and 142 non-BCR events. GPS was strongly associated with BCR - HR/20 GPS units = 2.5; p < 0.0001 in univariable analysis, and after adjusting for PSA, clinical T stage and central biopsy Gleason Score (HR/20 units = 2.1; p = 0.002). The association between GPS and BCR was similar within different racial groups. Each of the 4 gene groups in GPS contributed to the prediction of BCR. Conclusions: GPS was associated with BCR independently of other clinical factors in surgically treated men with PCa, and may provide improved risk stratification beyond clinical risk assessment.

ROC optimization may improve risk stratification of prostate cancer patients

Urology ◽  
2001 ◽  
Vol 57 (2) ◽  
pp. 286-290 ◽  
Author(s):  
Rex Cheung ◽  
Martin D Altschuler ◽  
Anthony V D’Amico ◽  
S.Bruce Malkowicz ◽  
Alan J Wein ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Risk Stratification ◽  
Cancer Patients ◽  
Improve Risk Stratification

Assessment of the American Joint Committee on Cancer (6th and 7th editions) for clinically localized prostate cancer and comparison to the National Comprehensive Cancer Network risk stratification method.

2012 ◽  
Vol 30 (5_suppl) ◽  
pp. 23-23
Author(s):  
Mark K Buyyounouski ◽  
Nicholas G. Zaorsky ◽  
Tianyu Li ◽  
Karthik Devarajan ◽  
Eric M. Horwitz
Keyword(s):  
Prostate Cancer ◽  
Risk Stratification ◽  
Stage I ◽  
Stage Ii ◽  
Modest Improvement ◽  
Kaplan Meier ◽  
Stratification Method ◽  
Ajcc Staging ◽  
Network Risk ◽  
Cancer Network

23 Background: The purpose was to compare the prognostic value of the AJCC staging version 6 (v6), version 7 (v7), and the risk-stratification model of the NCCN. Methods: 2,469 men (1989-2006) with clinical T1-4, N0/X-N1, M0 prostate cancer received definitive RT +/- ADT (median follow-up: 70 months). The NCCN grouping was: low-risk included T1-T2a, GS < 7, and PSA < 10 ng/mL; intermediate-risk included T2b-2c, GS = 7, and PSA 10 – 20 ng/mL; high-risk included T3, GS 8, and PSA > 20 ng/mL. The Benjamini and Hochberg adjustment was used to compute the false discovery rates in order to adjust for multiple comparisons. Results: There was a migration of stage II patients to stage I with version 7 (Stage I increased from 1% to 38%, while Stage II decreased from 91% to 55%). Pair-wise comparisons of Kaplan-Meier estimates of BF, DM, PCSS, and OS between stages were not statistically significant for AJCC v6 with one exception (PCSS: II vs III). On the other hand, 16/24 (67%) of comparisons were significant with AJCC v7. For NCCN, 9/12 (75%) of comparisons were significant, including all comparisons for OS. Concordance probability estimate (CPE) and standard error (SE) analysis showed uniform and significant improvement in the predictive power of AJCC v7 versus AJCC v6 for all outcomes. CPE±SE values for AJCC v6 versus AJCC v7 was .51±.009 vs .59±.02 for BF, .54±.02 vs. .70±.05 for DM, .57±.009 vs. .76±.007 for PCSS, and .52±.006 vs. .57±.01 for OS. There was further, albeit modest improvement with the NCCN method. CPE±SE values for AJCC v7 versus NCCN was .59±.02 vs. .59±.02 for BF, 0.70±.05 vs. 0.72±.05 for DM, .76±.007 vs. .80±.01 for PCSS, and .57±.01 vs. .57±.01 for OS. Conclusions: AJCC v7 is a major improvement over AJCC v6 because it better distributes patients among the stages and is more prognostic. Further improvements are needed as the majority of men (55%) are Stage II and the sub-stratification into IIA and IIB was not prognostic. The NCCN model is superior to the AJCC v7 and remains the preferred method for risk-based clinical management of prostate cancer with RT +/- ADT.

scholarly journals Additional SNPs improve risk stratification of a polygenic hazard score for prostate cancer

2021 ◽  
Author(s):  
Roshan A. Karunamuni ◽  
◽  
Minh-Phuong Huynh-Le ◽  
Chun C. Fan ◽  
Wesley Thompson ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Risk Stratification ◽  
Improve Risk Stratification
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