3. All learning to improve diagnosis & therapy to
improve survival and functional outcomes
4. Selecting men for primary or salvage
therapy without overtreating is difficult
5. Urgent
Need
for
Precision
Medicine
“linkage of molecular data to
health outcomes in order to
allow a more precise clinical
decision making that is
tailored to individual patients”
Institute of Medicine, 2011
6. Biomarkers: measurable entity whose
presence signifies a disease or condition
• Sources
•Nucleic acid (RNA/DNA)
•Protein
•Metabolite
Associated with meaningful endpoints
Provide additional information above nomograms
Influences physician treatment decisions
Allow more accurate risk assessment
9. Gleason Score 6: same on
histology but different CCP score
Gleason score 6
CCP score -1
Gleason score 6
CCP score 1
Gleason score 6
CCP score 2
Increasing ratio of proliferation gene activity
10. Gleason Score 6: same on
histology but different CCP score
Gleason score 6
CCP score -1
Gleason score 6
CCP score 1
Gleason score 6
CCP score 2
Increasing ratio of proliferation gene activity
11. Levels of Evidence for
Tumour Markers
LOE LOE category Study Design Validation studies required
I A Prospective Preferred, but not required
B
Prospective using
archived samples
≥ 1 with consistent results
II B
Prospective using
archived samples
None or inconsistent results
C
Prospective/
Observational
≥ 2 with consistent results
III C
Prospective/
Observational
None or 1 with consistent results
or inconsistent results
IV-V D
Retrospective/
Observational
n/a
Simon 2009 JNCI
12. Level 1B evidence for CCP
score exists
LOE LOE category Study Design Validation studies required
I A Prospective Preferred, but not required
B
Prospective using
archived samples
≥ 1 with consistent results
II B
Prospective using
archived samples
None or inconsistent results
C
Prospective/
Observational
≥ 2 with consistent results
III C
Prospective/
Observational
None or 1 with consistent results
or inconsistent results
IV-V D
Retrospective/
Observational
n/a
Simon 2009 JNCI
13. UK Watchful waiting study: 1 unit change
in CCP score doubles risk of death
• Age < 76 years,
• 337 men (6 Cancer Registries in
UK)
• Clinically localised cancer
• Diagnosed by TURP (1990 to 1996)
• histology central review (median
Gleason score 6)
• PSA at baseline (median < 10)
• 51% died within 10 years: 20%
prostate cancer; 31% other cause
Cuzick 2011 Lancet Oncology
< 0
0 to 1
1 to 2
CCP Score
> 2
14. Contemporary TRUS biopsy cohort
shows greater prediction by CCP score
Brawer 2014 Focal Therapy
CCP score hazard ratio
2.1 (CI 1.8 to 2.5)
15. CCP score superior to Ki67
Cuzick Lancet Oncol 2011
Cuzick B J Cancer 2012
16% died if ≤ 5% of cells stained V 48% > 5% of cells Ki67
Univariate analysis: hazard ratio = 1.77, P= 1.4 x 10-8
Multivariate analysis: hazard ratio = 0.98, P= 0.86
16. More information on death rate from CCP
alone than CAPRA alone
Cuzick
2014 AUA
Red area (CCR) > Blue area (CAPRA)
CAPRA
CCRCAPRA
CCR
CCR = clinical cell cycle (CCR) score i.e. CCP score & standard clinical variables
17. CCR increases or decreases the predicted
death rates within CAPRA risk categories
Brawer 2014 Focal Therapy
18. CCR increases or decreases the predicted
death rates within CAPRA risk categories
Brawer 2014 Focal Therapy
19. CCR increases or decreases the predicted
death rates within CAPRA risk categories
Brawer 2014 Focal Therapy
Most
useful
range?
20. CCP Score stratifies risk in
transrectal biopsy cohort
• 442 men in 6 UK cancer registries
• Transrectal prostate
biopsies 1990-1996
• Age < 76 years
• Central pathology
review
• Median follow up 11.8 years
CCP >3
CCP 2-3
CCP <2
Cuzick 2012 B J Cancer
HR 2.56 (CI 1.9 to 3.5)
21. Combined Risk Score (PSA, GS &
CCP) predicts 10 year death rate
CCP HR 1.65 for 1 unit change at 10 years, 2.56 for 5 years
Cuzick 2012 BJC
22. CAncer of the Prostate Risk Assessment
(CAPRA) score can predict outcomes
23. 10 year predicted mortality rate on TRUS biopsy
in contemporary cohort = earlier TURP cohort
Red line
contemporary cohort
Green line
earlier cohort
Cuzick 2014 AUA; Cuzick 2012 BJC
24. Index & secondary lesions show
similar CCP score - Field Effect
Carvalho 2014 AUA
25. Combined Clinical Risk (CCR) <0.8 in
“typical” AS cohort - no deaths at 10 years
Stone 2014 SUO
GS ≤ 3+4
< 25% core +ve
PSA < 10
Clin stage ≤ T2a
26. Radical Prostatectomy & CCP
• Radical prostatectomy (n=366)
• 1985 to 1995
• Scott & White Clinic in Texas
• Median age 68 years
• Clinical T2 67%
• Median preop 6.9 ng/ml
• BCR criteria > 0.3
• Median Gleason score 6
• SM+ 23%
• T3 34%
• Median follow up 9.8 years
• 36% recurrence rate at 10 years
Normal distribution of
CCP score
Cuzick 2011 Lancet Oncology
27. CCP & Log PSA only significant
variables on multivariate analysis
Cuzick 2011 Lancet Oncology
28. TRUS Biopsy CCP score
predicts risk after prostatectomy
• Bishoff 2014
• 582 men in 3 Cohorts
• Martini Clinic (simulated biopsy; n= 283, 2005-2006,
median f/u 61 month)
• Durham Veteran Affairs Center (TRUS bx, n=176,
1994-2005, median f/u 88 months)
• Intermountain Healthcare (TRUS bx n=123,
1997-2004, 132 months)
Bishoff 2014 J Urol
29. Risk of progression after RP
proportional to TRUS biopsy CCP score
Bishoff 2014 J Urol
30. Risk of metastasis after RP significant
if TRUS biopsy CCP score ≥ 2
Bishoff 2014 J Urol
31. Progression free survival proportional to
CCP score in contemporary cohort of RP
Cooperberg
2013
J Clin Oncol
32. Meta-analysis of 16 studies: each unit
increase in CCP doubles risk of death
Sommariva 2014 Eur Urol (online Dec 14)
33. Prolaris needs to be better
than multivariable prediction
• Sloane Kettering Nomogam
• CAPRA-s score
34. CAncer of the Prostate Risk
Assessment Post-Surgical CAPRA-S
Variable Level Points
Pre-op PSA 0.00 to 6.00 0
6.01 to 10.00 1
10.01 to 20.00 2
> 20.00 3
Path. Gleason < 3 + 3 = 6 0
3 + 4 = 7 1
4 + 3 = 7 2
> 4 + 4 = 8 3
Margins Negative 0
Positive 2
ECE No 0
Yes 2
SVI No 0
Yes 2
LNI No 0
Yes 1
• CAPRA-S 0-2
low risk
• CAPRA-S 3-5
Intermediate risk
• CAPRA-S >5
High risk
Cooperberg 2011 Cancer
35. 72 years, PSA 8, pT2, Gleason pattern 4
cancer at the apex - adjuvant radiotherapy?
36. CAncer of the Prostate Risk
Assessment Post-Surgical CAPRA-S
Variable Level Points
Pre-op PSA 0.00 to 6.00 0
6.01 to 10.00 1
10.01 to 20.00 2
> 20.00 3
Path. Gleason < 3 + 3 = 6 0
3 + 4 = 7 1
4 + 3 = 7 2
> 4 + 4 = 8 3
Margins Negative 0
Positive 2
ECE No 0
Yes 2
SVI No 0
Yes 2
LNI No 0
Yes 1
• CAPRA-S 0-2
low risk
• CAPRA-S 3-5
Intermediate risk
• CAPRA-S >5
High risk
40. Combina5on
of
CCP-‐score
&
CAPRA-‐S
has
greater
net
benefit
than
CAPRA-‐S
alone
to
predict
PFS
37
Cooperberg J Clin Oncol 2013
Decision Curve Analysis
41. CCP score changed treatment decisions
by patients & urologist ➔ to less treatment
Gonzalgo 2014 SUO
Crawford 2014 CMRO
42. Biomarkers: measurable entity whose
presence signifies a disease or condition
•Associated with meaningful endpoint✔️
•Provide additional information above
nomograms ✔️
•Influences physician treatment decisions ✔️
•Allow more accurate risk assessment ✔️
•Individualised treatment decisions ✔️
43. CCP Score Advantages
• CCP score is a strong independent predictor of
death
• CCP is best used in combination with other
predictors e.g. CAPRA, CAPRA-s
• Low CCP scores and BCR after treatment possibly
indicate local recurrence
• High CCP scores indicate higher chance of
metastatic disease & need for adjuvant Rx