scholarly journals An analysis of the association between prostate cancer risk loci, PSA levels, disease aggressiveness and disease-specific mortality

2015 ◽  
Vol 113 (1) ◽  
pp. 166-172 ◽  
Author(s):  
J Sullivan ◽  
R Kopp ◽  
K Stratton ◽  
C Manschreck ◽  
M Corines ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Risk ◽  
Prostate Cancer Risk ◽  
Specific Mortality ◽  
Disease Specific Mortality ◽  
Disease Specific

Development and validation of a mutivariate model combining cell cycle progression score with CAPRA to predict prostate cancer mortality in a conservatively managed cohort.

2013 ◽  
Vol 31 (6_suppl) ◽  
pp. 67-67 ◽  
Author(s):  
Michael K. Brawer ◽  
Matthew R. Cooperberg ◽  
Stephen J. Freedland ◽  
Gregory P. Swanson ◽  
Steven Stone ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cell Cycle Progression ◽  
Multivariate Model ◽  
Prognostic Information ◽  
Cycle Progression ◽  
Model Combining ◽  
Specific Mortality ◽  
Disease Specific Mortality ◽  
The Uk ◽  
Disease Specific

67 Background: Prostate cancer outcomes are variable and difficult to predict. Improved tools are needed to appropriately match treatment to a patient’s risk of progression. We developed and validated a multivariate model to predict disease−specific mortality (DSM) by combining clinical parameters (CAPRA score) with a score based on measuring the expression level of cell cycle progression (CCP) genes. Methods: A multivariate prediction model was trained using patients from 4 retrospective cohorts with median clinical follow up of 7.6 years. We used 200 men from the UK diagnosed after TURP, 353 from Scott & White and 388 from UCSF treated with radical prostatectomy, and 118 men from Durham VA treated with EBRT. CCP score was derived from fixed tumor tissue (biopsy or surgical resection). Outcome was either time from treatment to biochemical recurrence (US cohorts) or time from diagnosis to disease specific mortality (UK cohort). The model was validated for predicting time from diagnosis to DSM in 180 men from the UK diagnosed by needle biopsy with clinically localized prostate cancer and managed conservatively (mean/median CAPRA score = 6). Results: A model combining CAPRA with CCP score was fit in the training set by a Cox Proportional Hazards analysis stratified by cohort. The Combined score was defined as 0.39*CAPRA+0.57*CCP score. There were no significant interactions between cohort and CAPRA or CCP score. This suggests that both CCP score and CAPRA confer similar prognostic information regardless of cohort composition, treatment, or specific outcome. In the validation cohort the Combined score was highly prognostic (HR= 2.27, 95%CI: (1.63, 3.16), p = 1.2 x 10−7). By likelihood ratio testing, the Combined score was a better predictor of DSM than CAPRA alone (p = 0.0028). The c−index of the Combined score was 0.75, which was an improvement over CAPRA (c−index 0.71). Conclusions: This multivariate model predicts DSM in a conservatively treated cohort. The model provides prognostic information beyond clinical variables, and can be used to help differentiate aggressive from indolent cancer at diagnosis.

Ability of cell-cycle progression score to predict risk for progression to metastatic disease and disease-specific mortality in prostate cancer patients after prostatectomy.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 5524-5524
Author(s):  
Gregory P. Swanson ◽  
Steven Stone ◽  
Lauren Lenz ◽  
Todd Cohen
Keyword(s):  
Prostate Cancer ◽  
Cell Cycle ◽  
Metastatic Disease ◽  
Cell Cycle Progression ◽  
Significant Information ◽  
Cycle Progression ◽  
Specific Mortality ◽  
Disease Specific Mortality ◽  
Disease Specific

5524 Background: Prostate cancer treatment aims to prevent metastatic disease (METS) and disease-specific mortality (DSM). A major challenge is to identify those at highest risk so additional intervention can be initiated earlier when it has a better chance of success. Pathologic parameters alone have limited ability to predict METS and DSM, but data suggests biomarkers can improve risk discrimination. Methods: Eligible patients had: (1) prostate cancer treated with radical prostatectomy (RP; 1988-1995); (2) available tissue for cell-cycle progression (CCP) testing that resulted in a valid score; (3) preoperative prostate-specific antigen (PSA); (4) no neoadjuvant therapy; and (5) clinical follow-up (N = 360). Cancer of the prostate risk assessment post-surgical (CAPRA-S) was combined with CCP into a combined cell-cycle risk score (CCR = 0.38 × CAPRA-S + 0.57 × CCP). Results: Median follow-up was 23.5 years for patients alive at last follow-up. Overall, 11% (41/360) developed METS and 9% (33/360) had DSM. CCP score added significant information to CAPRA-S when predicting METS (p = 0.001) and DSM (p = 0.001). CCR score was also a significant predictor of METS and DSM (p-values < 1×10−8). CCP and CCR scores were prognostic of METS in patients with rising post-RP PSA. Of patients with biochemical recurrence (BCR), 25% (41/163) developed METS. CAPRA-S alone was predictive of these events (p = 0.01) but was significantly improved with the addition of CCP (Hazard Ratio [HR] = 1.69 [95% Confidence Interval (CI) 1.13, 2.52], p = 0.014). CCR was also highly prognostic (HR = 1.56 [95% CI 1.20, 2.03], p = 0.001). CCR score discriminated risk of METS both post-RP and after post-RP BCR (Table). Conclusions: Overall, the CCR score significantly predicted METS and DSM in prostate cancer post-RP and was also highly prognostic in those with a post-RP rising PSA. It is therefore a useful tool for determining who is at greatest risk of treatment failure and may benefit from earlier intervention. [Table: see text]

Prostate cancer incidence and disease-specific survival in men participating in the ERSPC with an initial PSA less than 3.0 ng/mL.

2011 ◽  
Vol 29 (7_suppl) ◽  
pp. 7-7
Author(s):  
M. Bul ◽  
P. J. van Leeuwen ◽  
X. Zhu ◽  
F. H. Schröder ◽  
M. J. Roobol
Keyword(s):  
Prostate Cancer ◽  
Clinical Stage ◽  
Randomized Study ◽  
Specific Antigen ◽  
Specific Mortality ◽  
Screening Population ◽  
Disease Specific Mortality ◽  
Increasing Risk ◽  
Disease Specific

7 Background: The European Randomized Study of Screening for Prostate Cancer (ERSPC) applies a prostate- specific antigen (PSA) cut-off >3.0 ng/mL as an indication for biopsy. We analyzed the incidence and disease-specific mortality for prostate cancer (PC) within ERSPC Rotterdam for men with an initial PSA <3.0 ng/ml in a 15-year follow-up period. Methods: From 1993-1999, a total of 42,376 men identified from population registries in the Rotterdam region (55-74 yrs) were randomized to a screening or control arm. During the first screening round 19,950 men were screened, with biopsies being initially recommended in case of abnormal DRE or PSA >4.0 ng/mL. From 1997 on, solely PSA >3.0 ng/mL was used. The screening interval was 4 yrs. A total of 15,758 men (79%) had an initial PSA <3.0 ng/mL. Follow-up was complete until January 2009. Results: From 1993-2008, 915 PC cases were diagnosed in 15,758 men (5.8%, median age 62.3 yrs) with an initial PSA <3.0 ng/mL (733 screen detected and 182 interval detected). Median follow-up was 11 yrs. PC incidence increased significantly with higher initial PSA levels (Table). Aggressive PC (clinical stage >T2c, Gleason score >8, PSA >20 ng/mL, positive lymph nodes or metastases at diagnosis) was detected in 65/733 screen detected PC (8.9%) and 102/182 interval detected PC (56.0%). PC death occurred in 23 cases (5 screen detected and 18 interval detected) in the total population (0.15%), with increasing risk in men with higher initial PSA values. Conclusions: The risk of (aggressive) PC and PC mortality in a screening population with initial PSA <3.0 ng/mL increases significantly with higher PSA levels. The risk of dying of PC is minor in men with initial PSA <1.0 ng/mL. Interval detected PC is more aggressive and has a substantial influence on PC specific mortality. [Table: see text] [Table: see text]

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