Paper - Mercaz USA

US008538778B2
(12) Ulllted States Patent
(10) Patent N0.:
Neville
(54)
(45) Date of Patent:
METHODS AND SYSTEMS FOR
6,423,503 B1
INTEGRATED HEALTH SYSTEMS
6,807,531 B1
6,871,171 B1
,
(75) Inventor:
.
.
7,211,397 B2
Thomas Neville, Incl1neV1llage, NV
(Us)
(73)
Assignee: Soar BioDynamics, Ltd., Incline
Village, NV (Us)
(*)
Notice:
Subject to any disclaimer, the term of this
patent is extended or adjusted under 35
U.S.C. 154(b) by 477 days.
(22) Filed,
Mikola'c
7,593,913 B2
9/2009 Wang et al.
k et al.
5/2003 Ban et al.
2003/0133903 A1
7/2003 Dang et a1.
2004/0044546 A1 *
3/2004 Moore ............................ .. 705/2
(Continued)
FOREIGN PATENT DOCUMENTS
EP
1399868
EP
1842139
12/2002
8/2006
(Continued)
OTHER PUBLICATIONS
_
_
Carter, H.B. et al., “Detection of life-threatening prostate cancer with
Pnor Pubhcatlon Data
Us 2010/0049546 A1
Feb 25’ 2010
prostate-speci?c antigen velocity during a Window of curability,”
Journal ofthe National Cancer Institute 98(2l):l52l-l527 (2006).
(Connnued)
Provisional application No. 61/053,600, ?led on May
Primary Examine?’ * Robert Morgan
15, 2008.
Assistant Examiner * Charles P Coleman
Int. Cl-
(74) Attorney, Agent, orFirm * Wilson Sonsini Goodrich &
Rosati
G06Q 50/00
(2012.01)
(52) US. Cl.
(57)
UISPC ......... .... ...... ... ............................. .. 705/3; 705/2
(58)
5/2007
2003/0101075 A1
Related US. Application Data
(60)
7/2002 Mikolajczyk et al.
10/2004 Kanal
3/2005 Agur et al.
12/2008 Saidi eg a?’
May 15, 2009
_
Sep. 17, 2013
7,467,119 B2
(21) Appl. No.: 12/466,684
(65)
US 8,538,778 B2
Fleld of Classl?catlon Search
USPC
for integrated healthcare. As the amount of medical informa
.... ..~ ............................................
705/2, 3
See apphcanon ?le for Complete Search hlstory'
becomes more and more important to extract meaningful
References Cited
conclusions from the information. Statistical and computa
tional methods are described herein that have been created for
U.S. PATENT DOCUMENTS
5,501,983 A
3/1996 Liljaet a1.
5,594,638 A
5,660,176 A
5,937,387 A
5,989,811 A *
6,108,635 A
the methods and systems for integrated healthcare. For
example, a computer system is described extracts signi?
1/1997 Iliff
8/1997 Iliff
8/1999 Summerellet a1.
11/1999
non increases rapidly, including information from multiple
biomarkers, analysis and management of that information
_
(56)
ABSTRACT
Methods’ business methods’ and Systems are provided herein
cance over time of PSA and fPSA biomarker tests for prostate
health.
Veltriet a1. ................ .. 435/614
50 Claims, 54 Drawing Sheets
8/2000 Herren et al.
Treatment Timing System Flow Chart
Probabilities and Early Warning
from Dynamic Snmning
Personal4
Pro?le
Treatment
Options
Trsalmenl
Estimate Cancer Cure Ratlo
Treatment
Side Effects
Summarize Results
Tlmlng Decisions
Blopsy and Treatment
Pathology Report
‘
Treatment
Lead Tlml
New BMW
US 8,538,778 B2
Page 2
(56)
Stephenson, A.J. et al., “Prostate cancer-speci?c mortality after radi
cal prostatectomy for patients treated in the prostate-speci?c antigen
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Stephenson, A.J. et al., “Preoperative nomogram predicting the
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Hara, et al. Application of serum PSA to identify acute bacterial
prostatitis in patients with fever of unknown origin or symptoms of
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Wang, et al. Effects of antibiotic and anti-in?ammatory treatment on
serum PSA and free PSA levels in patients with chronic prostatitis
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Kaplan, S.A. et al., “Combination therapy with doXazosin and
?nasteride for benign prostatic hyperplasia in patients with lower
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Martin, N.E. et al., “The in?uence of serial prostate-speci?c antigen
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antigen levels in men with benign prostate biopsies. BJU Int. Apr.
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Bruun, et al. Assessment of intra-individual variation in prostate
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screening program in Sweden. Prostate. Nov. 1, 2005;65(3):216-21.
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Kobayashi, et al . Intraindividual variation in total and percent free
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Prostate Volume in the Management of Patients with Symptomatic
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Benign Prostatic Hyperplasia,” European Urology44:695-700
Komatsu, et al. Physiologic (intraindividual) variation of serum pros
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(2003).
Mochtar, CA et al., “Prognostic role of prostate-speci?c antigen and
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benign prostatic hyperplasia initially managed with alpha1 -blockers
and watchful waiting,” Urology. Feb. 2005; 65(2): 300-5.
Mochtar, CA et al., “PSA velocity in conservatively managed BPH:
can it predict the need for BPH-related invasive therapy?” Prostate.
Sep. 15, 2006;66(13):1407-12.
Ng, M.K. et al., “Prostate-speci?c antigen (PSA) kinetics in
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Lujan, et al. Prostate speci?c antigen variation in patients without
clinically evident prostate cancer. J Urol. Oct. 1999;162(4):1311-3.
Morote, et al. Intraindividual variations of total and percent free
serum pro static-speci?c antigen levels in patients with normal digital
rectal examination. Eur Urol. Aug. 1999;36(2):111-5.
Nixon, et al. Day to day changes in free and total PSA: signi?cance of
biological variation. Prostate Cancer Prostatic Dis. Dec.
untreated, localized prostate cancer: PSA velocity vs PSA doubling
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time,” BJU Int (Oct. 16, 2008).
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Yan. Intraindividual variation of prostate speci?c antigen measure
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improves prediction of outcome beyond pretreatment PSA alone in
patients treated with radical prostatectomy,” J Clin Oncol
Bartsch, et al. Tyrol Prostate Cancer Demonstration Project: early
detection, treatment, outcome, incidence and mortality. BJU Int. Apr.
27(22):3591-7 (2009).
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US 8,538,778 B2
Page 3
Carter, et al. Longitudinal evaluation of prostate-speci?c antigen
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Carter, et al. PSA velocity for the diagnosis of early prostate cancer.
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Pearson, et al. Mixed-effects regression models for studying the
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radical prostatectomy and risk of prostate cancer speci?c mortality. J
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* cited by examiner
US. Patent
Sep. 17, 2013
US 8,538,778 B2
Sheet 1 0f 54
Treatment Timing System Flow Chart
Probabilities and Early Warning
from Dynamic Screening
Personal
Pro?le
lnput Relevant Information
+
Treatment
Select Treatment
Options
+
Select Years of Early Warning
Project Treatment Timing
Treatment
Effectiveness
,
Estimate Cancer Cure Ratio
Project Probability of Death
Project Probability of Progressing Cancer
Treatment
Side Effects
Estimate Side Effect Risks
Calculate Life Score Impacts
Calculate Life Score
Summarize Results
Timing Decisions
+
Biopsy and Treatment
Pathology Report
Treatment
41'
Lead Time
New Biopsy
FIG. 1
US. Patent
Sep. 17, 2013
Sheet 2 0f 54
US 8,538,778 B2
Probability of
Progressing Cancer
and Cure Ratio
i
Treatment
Life
Timing —>
Scenarios
Personal
Outcome
Simulator
4- Pro?le
i
Life Score Graphs
for Timing Scenarios
2
Maximum Life Score
SLciofre
-- Life Score
0
Treatment
Biopsy
-7
-6
4
-3
-2
-5
Confined Progression
-1
O
1
2
3
4
5
6
Penetrating Progression
Years Before (-) and After Transition Point (+)
3
US. Patent
Sep. 17, 2013
US 8,538,778 B2
Sheet 3 0f 54
Minimum Life Score impact
SLIcmiopfraect
WWmSide Effects LS Impact
—Cancer Death LS impact
—-—Totai Life Score Impact
0
Treatment
Biopsy
-6
-5
-4
-3
—2
Confined Progression
—1
O
1
2
3
4
5
Penetrating Progression
Years Before (-) and After Transition Point (+)
FIG. 4
US. Patent
Sep. 17, 2013
Sheet 4 0f 54
US 8,538,778 B2
Dynamic Screening System
Experience a
of Other Men‘
lndividual Results:
1
Individual Diagnosis of:
.
Biomarkers —>
lmages—>
E
‘5,’
I
Dynam'c
—> Progressing Cancer —>
01
Screening
System
—> Long-Term Conditions —>
m
g
(I)
1
E
Individual Diagnosis of
Temporary Conditions
FIG. 5
US. Patent
Sep. 17, 2013
Sheet 5 0f 54
US 8,538,778 B2
Dynamic Screening Analysis System
Control System and Decisions
individual Risk Ratios —>
Prior
Probabilities
Probabilities of;
Related Changes
Progressing _>
Individual
Cancer
Results:
"
Biomarkers—>
Trends
|ma9e$—>
l
1‘
Long-Term
—> Progressing Cancer
Probabilities —> Long-Term Conditions
Residual
Early
Values
Warning
—> Years of Warning
‘l
Temporary
Long-Term
Long-Term
Conditions
Conditions
Severity
Test
Severity of Long-Term
Conditions
‘ Severity of Temporary
Timing
' Conditions
Decisions
'
A
Temporary
Probabilities of:
> Temporary Conditions
Probabilities
Test Timing
Recommendations
Information Value
of Test Timing
FIG. 6
US. Patent
Sep. 17, 2013
Sheet 6 0f 54
US 8,538,778 B2
Trend
Residual
Velocities
l
Cancer (Years of Early Warning) _>
0
Mean Residual Velocity
0
Variation in Distribution
0 Trend
o Biologic
Long'Term
Probabilities
No-Cancer Prediction —>
0 Mean Residual Velocity
0
Probability of
—> Progressing
Cancer
Variation in Distribution
0 Trend
o
Biologic
T
Prior
Probabilities
7
US. Patent
Sep. 17, 2013
Sheet 7 0f 54
US 8,538,778 B2
Trend Models
Values,
Velocities
& Variation
P(Trends: l CX)
Biologic Models'
'
Cancer (Years of Early Warning)
Personalized
.
..
Probablllty
I
PSA
'
PSAV’
:
0
- nBnfealm Vases: 8;_velocities_’ Distributions
Noéancéo oglc aria lOl’l
-
Mean Values & Velocities
-
Biologic Variation
&
Probabilities
Bayes
l Long-Term
Probability of
: Probabilities —> ggogzssmg
P(Trend5: I NC)
T
Personal Information
Personal Profile Data
0
'
PSA
PSAV,
0
fPSA%
0 fPSAV%
T
Prior
Probabilities
8
US. Patent
Sep. 17, 2013
Sheet 8 0f 54
US 8,538,778 B2
Four Dimensional Frequency Generator
Monte Carlo iteration Controller
<—
Healthy
Prostate
Monte Carlo
Generator
from
Distributions
v
Volume
v
PSA
v
v
v
Summation:
Growth
PSA
No Cancer
‘
No Cancer
'
4D
Monte Carlo
PSAV ‘ Monte Carlo
?> Frequency
Generator
fPSA
fPSA
from
fPSAV
Generator
fPSAV _
Distributions
'
V
V
V
!
YearX
425A
‘
Summation:
Cancel’
,
'
YrXCancer
—> Monte Carlo
Generator
From
Distributions
_>
; Collector
425A
‘
YrXCancer
'
+No Cancer
P‘m!_> +No Cancer
PSWL> 4D
fFSA
‘
fPSAV
>
fFSA
‘
fPSAV V
>
Monte Carlo
Generator
i_______ E
Frequency
Collector
1
v v
Monte Carlo iteration Completion
598
FIG. 9
US. Patent
Sep. 17, 2013
Sheet 9 0f 54
US 8,538,778 B2
No Cancer Four Dimensional Frequency Generator
Monte Carlo iteration Controller
i
Healthy
Prostate
Monte Carlo
Generator
from
Distributions
V
Volume
Growth
Monte Carlo
Generator
from
Distributions
PSA
PSAV
fPSA
fPSAV
>
V
V
V
Summation:
No Cancer
Monte Carlo
Generator
PSA
No Cancer
4D
PSAV
fPSA
V
fPSAV
V
Frequency
Collector
Monte Carlo Iteration Completion
FIG. 10
US. Patent
Sep. 17, 2013
US 8,538,778 B2
Sheet 10 0f 54
Cancer Plus No Cancer Four Dimensional Frequency Generator
Monte Carlo Iteration Controller
l
Healthy
Prostate
Monte Carlo
Generator
from
Distributions
V
Volume
Growth
Monte Carlo
Generator
from
Distributions
V
PSA
PSAV
fPSA
fPSAV
V
YearX
423A
Cancer
‘
—> Monte Carlo
V
‘
V
V
Summation:
'
fPSA
From
fP SAV
-ll5A
Yr X Cancer
P‘mL > + No Cancer
Generator
Distributions
V
Summation:
No Cancer
Monte Carlo
Generator
a Monte Carlo
Generator
‘ YrXCancer
'
+ No Cancer
PSKL > 4D
fF 3A
> Frequency
fp SAV
Collector
>
v
Monte Carlo Iteration Completion
FIG. 11
US. Patent
Sep. 17, 2013
Sheet 11 0154
US 8,538,778 B2
2D Rectangle of Possible Results
PSA
FIG. 12
FB 1 3
US. Patent
Sep. 17, 2013
Sheet 12 0f 54
Range of Target Results in Bucket
PSA
PVeSlocAity
FIG. 14
US 8,538,778 B2
US. Patent
Sep. 17, 2013
Sheet 13 0f 54
US 8,538,778 B2
No Cancer Four Dimensional Frequency Generator
Monte Carlo iteration Controller
V
No
‘ Stop Iteration
PSA Monte Carlo
Yes
V
No
‘ Stop iteration
PSAV Monte Carlo
Yes
V
No
‘ Stop iteration
fPSA% Monte Carlo
i Yes
‘
No
‘ Stop Iteration
fPSAV% Monte Carlo
Yes
V
4D Frequency Collector
i
Monte Carlo iteration Completion
FIG. 16
US. Patent
Sep. 17, 2013
Sheet 14 0f 54
US 8,538,778 B2
Cancer Plus No Cancer Four Dimensional Frequency Generator
Monte Carlo Iteration Controller
V
No
‘ Stop Iteration I
CX PSA Monte Carlo
v Yes
No
‘ Stop Iteration I
CX PSAV Monte Carlo
v Yes
No
‘ Stop Iteration I
CX fPSA% Monte Carlo
V Yes
No
0
< Stop Iteration‘ CX fPSAV /0 Monte Carlo
A
V
Yes
CX 4D Frequency Collector n
V
Monte Carlo Iteration Completion
FIG. 17
US. Patent
Sep. 17, 2013
Sheet 15 0154
US 8,538,778 B2
Accelerating PSA
14
13
__
12
+
11 1
+
____ W
g
1T5.“
J
8 -
+
51 7
0-
~1
,+
6
++
J;
5
++
4 -
3
+ +++
2 '
++
+++
++
1 -—++++++++++++++
0
50
51
52
53
54
55
56
57
58
59
60
Accelerating PSA with
Age 10yr Window
14
13
+
12 11 -
Trend
__
10yr Window
+
' ' ' Linear (10yr Window)
4,
10
+1"
9
<
+
8
' ¢ .
++' '
2 7
‘ 5f
2.
¢ — ’ ‘ |++
'
2
’ ‘ a ;+ ++++|
1 +++++++,++4++++
0
' '
50
51
52
53
54
55
Age
56
57
58
59
60
FIG. 19
US. Patent
Sep. 17, 2013
Sheet 16 0f 54
US 8,538,778 B2
Accelerating PSA for 2, 6 and 10yr Windows
APSA
+
Trend
7
2yr Window
6yr Window
10yr Window
/
//
IV
' ' ' Linear (10yr Window)
1%
— - Linear (6yr Window)
Linear (2yr Window)
4>bNo.)01o:\10o(0oc»->A
50
51
52
53
54
, e
g7 ¢ ’
2
55
56
57
58
59
60
Age
FIG. 20
Estimated PSA at Age 60 vs Window Size
O
1
2
3
4
5
6
Window Size (years)
7
8
9
10
FIG. 21
US. Patent
Sep. 17, 2013
Sheet 17 0f 54
US 8,538,778 B2
Standard Deviation Estimated PSA at Age 60
0.15
\
0.10 ~
\
0.05
0.00
0
1
3
_ 4
5
6
Wmdow S|ze (years)
7
8
9
10
SD vs PSA for Various Window Sizes
0.45
<
w
040
D.
/
.5 0.35
/
.5 0'30
17291021,
5 0.25 -
5
a 0.20
O
‘I
2
3
4
5
6PSA7
8
9
1O
11
12
FIG 22
`