PSA VOLATILITY INDEX (PVI)
& UPDATE ON PSA KINETICS
John Phillips, MD
New York Medical College
19 November, 2010
Hackensack University Medical Center
PSA VOLATILITY INDEX (PVI)
& UPDATE ON PSA KINETICS
John Phillips, MD
New York Medical College
19 November, 2010
Hackensack University Medical Center
PSA VOLATILITY INDEX (PVI)
& UPDATE ON PSA KINETICS
203,415 men developed prostate cancer
28,372 men died from prostate cancer
John Phillips, MD
New York Medical College
19 November, 2010
Hackensack University Medical Center
•34 kD
•Serine protease
•19q13
•Kallikrein-related peptidase III
•Half-life total PSA 2-3 days
•Free PSA <8 hours
J Mol Biol (2008), 376, 1021-33
Serum Proteins
Alpha-2-macroglobulin
Alpha-Chymotrypsin
Free isoforms: B-PSA, I-PSA, and pro-PSA
SCR-270 Radar
Balancing true signal with
interference
Receiver Operating Characteristic
(ROC)
Receiver Operating Characteristic
(ROC)
Area Under Curve*
0.500= worthless
0.650=lukewarm
0.700=very good
0.800=outstanding
*trapezoidal method
PSA cut-offs
•1986 “99% of healthy men < 4.0”
•1992 20-30% men > 4.0
•1994 24,000 screened q 6 months #
cancers 2.6-4 identical to 4-10 ng/ml
•1995 6,691 men PSA 4.1 missed 82% of
cancers in men <50
•2001 PSA 2.5 ng/ml for men <50
PSA cut-offs
•1986 “99% of healthy men < 4.0”
•1992 20-30% men > 4.0
•1994 24,000 screened q 6 months #
cancers 2.6-4 identical to 4-10 ng/ml
•1995 6,691 men PSA 4.1 missed 82% of
cancers in men <50
•2001 PSA 2.5 ng/ml for men <50
•Placebo arm of the 2004 PCPT trial
•<2.1 ng/ml 15 % of men had cancer
•Significant number had high grade disease
•Stacey Loeb 14,000 BLAS
•Median PSA 0.7 age 40-49: 0.7-2.5= 14.6 fold increased risk of prostate ca
•Median PSA 0.9 age 50-59: 0.9-2.5=7.6 fold increased risk of prostate ca
•AUA Guidelines
•PSA testing begin at 40 years of age + DRE if > 10 year life expectancy
•Repeat PSA annually especially if above median for age
•Prostate Cancer exists at all PSA levels
•No absolute cut-off but PSA represents a “continuum of risk”
•PSA presents an odds to a patient, then they can determine comfort zone
Other Scalar Tests
•
•
•
•
•
[-2] pro PSA AUC=.76 Sokoll et al. CEBM 2010
TMPRSS2-ERG
PSAD >0.155
TZ-PSAD
PCA3
Dynamic Tests
•
•
•
•
•
•
PSA doubling time (PSAdt)
Classically described after radiation therapy
Originally identified as a surrogate for failure
PSA dt < 3 months associated with decreased CSS
PSA dt < 6 months associated with increased BCF
n i
Difficult to calculate
log 2 * (tim en 1  tim en )

n 1
log(PSAn 1  PSAn )
i
Dynamic Tests
•
•
•
•
•
•
•
•
PSA Velocity
Carter B.L.S.A.
PSA < 4
PSAV was associated with CSS 25 years
later
92 % survival <.35 ng/ml/yr
54% survival >.35 ng/ml/yr
Loeb: 0.75 cut off PSA 4-10
0.35 cut off PSA 2.5-4.0
Dynamic Tests
• Can PSAV be used to help with screening?
• Vickers et al. J U 184: 907-912 2010
• European Randomized Screening Study for Prostate
Cancer ERSPC
•
•
•
•
•
•
N=2,742
Median PSA 4.47 vs 4.69 (No Ca versus Ca)
Median volume 47 vs 36 (No Ca versus Ca)
PSAV 0.26 vs 0.28 ng/ml/yr (No Ca versus Ca)
AUC PSA 0.522 PSAV 0.551 PSA+PSAV 0.621
“Little support for any clinically useful role for PSA velocity to help
determine initial biopsy”
• “May be useful after an initial negative biopsy”
Dynamic Tests
• Can PSAV be used as a trigger in active surveillance?
•
•
•
•
•
•
•
Andrew Loblaw et al. (Laurence Klotz’ group) JU 184: 1942, 2010
N=305 untreated men 6.1 years (range 0.5-13.3)
Zero prostate cancer deaths
Trigger for Treatment (TT)
PSA of 10 ng/ml TT 38% of the time
PSAV associated with TT 42-84% of the time
www.ASURE.com
PSA
•
•
•
•
•
•
•
Incredibly useful
Incredibly misused
Multiple forms
PSA, free PSA, proPSA
PSAV, PSAdt, Ln(PSA)
TMPRSS2ERG
PCA3
Volatility: A measure of
bidirectional variation over time
Volatility: A measure of
bidirectional variation over time.
time, t
Volatility: A measure of
bidirectional variation over time.
time, t
Volatility: A measure of
bidirectional variation over time.
time, t
Volatile (Bidirectional) Variables
Options Pricing
Treasuries
Sunspot Activity
Global Warming
PSA
Source: Stockcharts.com
Volatile (Bidirectional) Variables
Options Pricing
Treasuries
Sunspot Activity
Global Warming
PSA
Source: Stockcharts.com
6-month-ahead Eurodollar rate (Rudebusch et al.)
Volatile (Bidirectional) Variables
Options Pricing
Treasuries
Sunspot Activity
Global Warming
PSA
Daily GOES readings: Nat’l Geophysical Data Canter
Volatile (Bidirectional) Variables
Options Pricing
Treasuries
Sunspot Activity
Global Warming
PSA
Source: Global Temperature Land-Ocean Index:
Goddard Institute, NASA
Volatile (Bidirectional) Variables
Options Pricing
Treasuries
Sunspot Activity
Global Warming
PSA
PSA kinetics
• PSAV: 1 ng/dl/mo
14
12
PSA
10
8
6
4
2
0
1
2
3
4
5
6
7
Year
8
9 10 11 12
PSA velocity
• PSAV: How accurate with volatile PSAs?
14
12
PSA
10
8
6
4
2
0
1
2
3
4
5
6
7
8
9 10 11 12
Year
• Same average PSA, s, t-test
PSA velocity
14
12
PSA
10
8
6
4
2
0
1
2
3
4
5
6
7
Year
8
9 10 11 12
PSA velocity
14
12
PSA
10
8
6
4
2
0
1
2
3
4
5
6
7
Year
8
9 10 11 12
PSA velocity
14
12
PSA
10
8
6
4
2
0
1
2
3
4
5
6
7
Year
8
9 10 11 12
PSA
volatility
(PVI)
PSA
volatility
• Hypothesis : Can a PVI discriminate benign
from malignant states?
14
12
PSA
10
8
6
4
2
0
1
2
3
4
5
6
7
Year
8
9 10 11 12
PVI: Retrospective Study
Population
INCLUSION
At least 3 PSAs
At least 1 (one) prostate biopsy (TRUS or TP)
EXCLUSION
No Urothelial Ca
No h/o pelvic RT
No h/o hormone deprivation
Quantitating PVI
  tQ  
Volatility  s  log t 1  
  Q 
Financial Models

 ln(s / K )  (r  s 2 / 2)t 
  Ke  rt N   s t
C  SN 
s t



(Black & Sholes, 1973)
K i RT
2
1
s   2 e Q( K i ) 
T i Ki
T
2
F

 1

 K0 
2
(Rattray & Shah, 2003)
PSA Volatility Index (PVI)
e
SE
slope
HYPOTHESIS
An e-based normalization for PSA scatter
and a PVI may predict Ca from BPH
Retrospective Study Population
N1=932
N2=279
107 Cancer
172 BPH (e.g. BPH, atrophy, prostatitis, PIN)
Independent variables
Age, race, IPSS, ASA, Meds, TRUS data, Grade,
volume/core, # cores, surgical pathology
aPSA, aPSAV, aPSAdt, PSAD, Ln(PSA), PVI
Descriptives
30
30
25
20
20
15
10
10
5
0
Jun-94 Oct-95 Mar-97 Jul-98 Dec-99 Apr-01 Sep-02 Jan-04 May-05 Oct-06 Feb-08 Jul-09
Prostate Ca (n=107)
0
Jan-93
Oct-95
Jul-98
Apr-01
Jan-04
BPH (n=179)
Total PSA ng/dl 1993-2010
Oct-06
Jul-09
Demographics
BENIGN n=172
Age
CANCER n=107
P-Value
64.75 ± 8.67
65.14 ± 9.22
0.89
Caucasian (%)
82.94
80.95
0.85
ASA Class I-II (%)
66.48
64.58
0.88
ASA Class III-IV (%)
33.52
35.42
AUA-SS (0-40)
8.15 ± 5.67
6.42 ± 5.58
<.01
Nocturia (voids/night)
1.40 ± 1.16
1.38 ± 0.89
0.49
Study Interval (yrs)
5.10 ± 3.33
4.04 ± 2.96
<.01
58.82
48.82
0.07
6.90 ± 3.82
5.05 ± 2.78
<.01
13.69
20.41
0.15
44.08 ± 25.01
40.24 ± 20.59
0.21
1.75 ± 1.03
1.50 ± 0.88
0.06
Treated for LUTS (%)
Number of PSAs
Abnormal DRE (%)
TRUS vol (cc)
Number of Biopsies
Descriptives
30
30
25
20
20
15
10
10
5
0
Jun-94 Oct-95 Mar-97 Jul-98 Dec-99 Apr-01 Sep-02 Jan-04 May-05 Oct-06 Feb-08 Jul-09
0
Jan-93
BENIGN n=172
Oct-95
Jul-98
Apr-01
Jan-04
CANCER n=107
Oct-06
Jul-09
p-value
PSA ng/ml
5.60 ± 3.05
6.36 ± 5.53
0.7
free PSA (%)
19.78 ± 9.33
16.17 ± 8.51
0.04
PSAV ng/ml/yr
-0.39 ± 6.28
0.71 ± 2.86
0.09
241.28 ± 240.18
0.06
PSA dt (mo)
slope ln(PSA)*1000
12.81 ± 336.95
-0.06 ± .00
PVI
1.56 ± 1.29
PSAD (ng/ml/cc)
0.15 ± 0.09
0.38 ± 1.1
<.0001
0.83 ± 0.83
<.0001
0.19 ± 0.20
.04
PVI Correlations
30
30
25
20
20
15
10
10
5
0
Jan-93
0
Jun-94 Oct-95 Mar-97 Jul-98 Dec-99 Apr-01 Sep-02 Jan-04 May-05 Oct-06 Feb-08 Jul-09
X
Y
Oct-95
Jul-98
P value
Apr-01
Jan-04
R2
PVI
PSAV
0.11
PVI
# biopsies 0.20
PVI
IPSS
0.29
PVI
BPH
<0.00
.06
PVI
PSAD
<0.00
0.05
PVI
Proscar
<0.00
0.06
Oct-06
Jul-09
PVI Correlations
30
30
25
20
20
15
10
10
5
0
Jan-93
0
Jun-94 Oct-95 Mar-97 Jul-98 Dec-99 Apr-01 Sep-02 Jan-04 May-05 Oct-06 Feb-08 Jul-09
X
Y
Oct-95
Jul-98
P value
Apr-01
Jan-04
R2
PVI
PSAV
0.11
PVI
# biopsies 0.20
PVI
IPSS
0.29
PVI
BPH
<0.00
.06
PVI
PSAD
<0.00
0.05
PVI
Proscar
<0.00
0.06
Oct-06
Jul-09
Linear Regression y=mx+b
Linear Regression y=mx+b
For each increase of 1 unit of x, y increases by 4.88 %
PSA volatility and % cancer
Or, as cancer volume decreases, PSA volatility increases
Logistic Regression = yes or no
1
f ( z) 
z
1 e
For each change in x, the probability of the outcome
goes up by y
Logistic Regression = yes or no
UNIVARIATE
Coeff
free PSA
PSAD
AUA SS
Ln(PSA)*1000†
PVI
p-value
-0.05
0.05
2.07
0.06
-0.06
0.02
1.43
<.001
-0.77
<.001
MULTIVARIATE
Coeff
Ln(PSA) + AUA SS
p-value
1.23
<.001
-0.05
PVI + AUA SS
-0.78
-0.06
0.05
<.001
0.03
ROCs
AUC=.800
Nomograms=Prediction Tools
Nomograms=Prediction Tools
Formula for the oxygen consumption of rainbow trout as a function of weight
and water temperature. Ron Doerfler Dead Reckonings
Nomograms=Prediction Tools
•Too Many Variables can Compromise
the Model
•Increasing Complexity may Reduce
Clinical Usefulness
•“Precision versus Parsimony”-Sengupta
and Blute 2006
PVI Nomogram
PVI
•PVI > 2 benign, esp. in total PSA range 4-20
•PVI < 1 malignant
•PVI quantifies the PSA instability over time
•www.psastatistics.com
•Multivariable analysis
e
SE
slope
WWW.PSASTATISTICS.COM/PVI
PVI
•PVI > 2 benign, esp. in total PSA range 4-20
•PVI < 1 malignant
•PVI quantifies the PSA instability over time
•www.psastatistics.com
•Multivariable analysis
e
SE
slope
Thanks
Muhammad Choudhury, MD (NYMC)
Andrew Fishman, MD (NYMC)
Basir Tareen, MD (BIMC)
Harris Nagler, MD (BIMC)
Devesh Shah, PhD (Goldman Sachs)