using biomarkers for early detection of prostate...
TRANSCRIPT
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Using Biomarkers for Early Detection of Prostate Cancer Brian Denton Department of Industrial and Operations Engineering University of Michigan
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Prostate cancer is the most common cancer among men
• 60-80% of men will eventually develop
prostate cancer
• 1 in 7 men will be diagnosed during his lifetime
• 1 in 36 men will die of prostate cancer
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Prostate cancer in the news
“A major European study has shown that blood test screening for prostate cancer saves lives, but doubts remain about whether the benefit is large enough to offset the harms caused by unnecessary biopsies and treatments that can render men incontinent and impotent.”
– Tara Parker-Pope. (2014) Prostate Cancer Screening Still Not Recommended for All, New York Times. August 6, 2014
“Sophisticated new prostate cancer tests are coming to market that might supplement the unreliable PSA test, potentially saving tens of thousands of men each year from unnecessary biopsies, operations and radiation treatments.”
– Pollack A (2013) New Prostate Cancer Tests Could Reduce False Alarms. New York Times. March 26, 2013.
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Prostate cancer screening is controversial
• Longer life expectancy with early detection and treatment
• Unnecessary biopsies and overtreatment
• High cost of screening, biopsy and treatment
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Conflicting guidelines for PSA screening
• American Urological Association (AUA, 2013)
• American Cancer Society (ACS, 2014)
• National Comprehensive Cancer Network (NCCN, 2014)
• U.S. Preventive Services Task Force (USPSTF, 2008, revised 2011, revised 2012,...)
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Can new biomarkers improve prostate cancer screening?
• PCA3 – urine test that received FDA approval in 2012 for repeat biopsy decisions
• T2:ERG – urine test in late stage clinical validation
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Research Questions
• Can using a patient’s screening history improve his prostate cancer screening and treatment decisions?
• Can new biomarkers improve prostate cancer screening?
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Predicting prostate cancer diagnosis
Tomlins SA, Day JR, Lonigro RJ, Hovelson DH, Siddiqui J, Kunju LP, Dunn RL, Meyer S, Hodge P, Groskopf J, Wei JT, Chinnaiyan AM. Urine TMPRSS2:ERG + PCA3 for individualized prostate cancer risk assessment. European Urol. In Press.
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PSA model example
0
1
2
3
4
5
6
7
8
40 45 50 55 60 65 70 75
PSA
(n
g/m
L)
Age
Cancer Free
Cancer at Age 52
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Prostate cancer screening model
Age 50 Age 51
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Treatment options
• Radical Prostatectomy:
– For patients with localized cancer, medium or high grade (Gleason score ≥ 7)
• Active Surveillance:
– For patients with Gleason score ≤ 6, delays and possibly avoids curative treatment until evidence of disease progression
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Natural history model
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Model validation
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Bayesian Updating
𝑃𝑟𝑡+1 𝑠𝑡+1 = 𝑞𝑡+1 𝑜𝑡+1 𝑠𝑡+1) 𝑝𝑡(𝑠𝑡+1|𝑠𝑡, 𝑎𝑡) 𝑃𝑟𝑡( 𝑠𝑡) 𝑠𝑡∈𝑆
𝑞𝑡+1(𝑜𝑡+1 𝑠𝑡+1∈𝑆 𝑠𝑡+1 𝑝𝑡(𝑠𝑡+1𝑠𝑡∈𝑆
𝑠𝑡 , 𝑎𝑡 𝑃𝑟𝑡(𝑠𝑡)
The probability a patient is in state 𝑠𝑡 is estimated using the entire history of observations up to time t
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Optimal Screening Policies
Decisions are based on risk of prostate cancer by selecting among the three possibilities:
{𝑑𝑒𝑓𝑒𝑟 𝑃𝑆𝐴 𝑡𝑒𝑠𝑡 (𝐷𝑃), 𝑃𝑆𝐴 𝑡𝑒𝑠𝑡 (𝐷𝐵), 𝑏𝑖𝑜𝑝𝑠𝑦 (𝐵}} Optimality equations:
𝑣𝑡(𝑃𝑟𝑡 𝐶 ) = 𝑚𝑎𝑥
𝑣𝑡 𝑃𝑟𝑡 𝐶 , 𝐷𝑃
𝑣𝑡(𝑃𝑟𝑡 𝐶 , 𝐷𝐵)
𝑣𝑡 𝑃𝑟𝑡 𝐶 , 𝐵
Boundary Condition:
𝑣𝑇 𝑃𝑟𝑇 𝑠𝑇 = 𝑅 𝑠𝑇 , ∀𝑠𝑇
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Properties of Screening Policies
Proposition: The incremental benefit of an additional PSA test in expected QALYs is nonnegative. Theorem: The optimal biopsy referral policy is of control-limit type such that
𝑎𝑡∗(𝑃𝑟𝑡 𝐶 ) =
𝑊, 𝑃𝑟𝑡 𝐶 ≤ 𝑝𝑡∗
𝐵, 𝑃𝑟𝑡 𝐶 > 𝑝𝑡∗
Theorem: There exists an age, N, at which it is optimal to discontinue biopsy referral if and only if: 𝑅 𝑁 𝑇 − 𝑅 𝑁 𝐶 ≤
𝜇
𝑓
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Risk based screening policies
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Related Work
Zhang, J., Denton, B.T., Balasubramanian, H., Inman, B., Shah, N., “Optimization of Prostate Biopsy Decisions,” M&SOM, 14(4), 529-547, 2012 Zhang, J., Denton, B.T., Balasubramanian, H., Inman, B., Shah, N., “Estimating the True Value of PSA Tests for Prostate Cancer Detection,” Medical Decision Making, 32(2), 337-349, 2012. Inman, B., Zhang, J., Shah, N., Denton, B.T., An Evaluation of the Dynamic Changes in PSA Occurring in a Population-Based Cohort of Men Over Time,” British Journal of Urology International, 110(3), 375-381, 2012 Underwood, D., Zhang, J., Denton, B.T., Shah, N., Inman, B., “Simulation Optimization of PSA Threshold Based Prostate Cancer Screening Policies,” Health Care Management Science, 15(4), 293-309, 2012.
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Screening with multiple biomarkers
Option 1:
Option 2:
MiPS
PSA
PCA3
T2ERG
All Cancer Risk Score
High Grade Risk Score
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Screening strategy types
• No Screening
• PSA
• PSA + PCA3
• PSA + T2:ERG
• MiPS
• HG MiPS
• Perfect
• HG Perfect
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Screening schedules
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Biopsy thresholds
• PSA: {1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 6.5}
• PCA3: {19, 25, 35, 55, 75}
• T2:ERG: {7, 10, 30, 50, 100}
• MiPS: {0.05, 0.10, 0.15, 0.20, 0.25, 0.30, 0.35, 0.40, 0.45, 0.50}
# of screening strategies = (# of screening types)×(# of screening schedules)×(# of biopsy thresholds) = 1,439
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Detection of high-grade cancers is most important
0
10
20
30
40
50
0 100 200 300 400 500 600 700 800
Number of metastatic
cases per 1,000 men
Number of screening biopsies per 1,000 men
No screening
PSA only
PSA + PCA3
PSA + T2:ERG
MiPS - cancer
MiPS - HG cancer
Perfect - cancer
Perfect - HG cancer
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35
36
37
38
39
40
0 50 100 150 200
Number of metastatic cases per
1,000 men
Number of screening biopsies per 1,000 men
High-grade MiPS simultaneously reduces biopsies and metastatic cases
AUA
HG MiPS
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35
36
37
38
39
40
0 50 100 150 200
Number of metastatic cases per
1,000 men
Number of screening biopsies per 1,000 men
High-grade MiPS simultaneously reduces biopsies and metastatic cases
Annual screening ages 55-69, risk threshold of 0.50
Screening once every two years ages 55-69, risk threshold of 0.50
Screening once every two years ages 55-69, PSA threshold of 4 ng/mL
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35
36
37
38
39
40
0 50 100 150 200
Number of metastatic cases per
1,000 men
Number of screening biopsies per 1,000 men
↓ biopsies by 14% ↓ metastatic cases by 7%
↓ biopsies by 32% ↓ metastatic cases by 2%
High-grade MiPS simultaneously reduces biopsies and metastatic cases
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Recent Work
Merdan, S., Tomlins, S.A., , Barnett, C.L., Underwood, D.J., Morgan, T.M., Montie, J.E., Wei, J.T., Denton, B.T., “Assessment of Long Term Outcomes Associated with Urinary Prostate Cancer Antigen 3 and TMPRSS2:ERG Gene Fusion at Repeat Biopsy,” Cancer (in press), 2015.
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Conclusions
• New biomarkers used in conjunction with PSA could reduce unnecessary biopsies and development of metastatic cancer
• High grade cancer biomarkers are much more valuable than “any cancer” biomarkers
• Optimization of screening based on belief thresholds may improve screening
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Acknowledgements
• Christine Barnett, MSc
• Daniel Underwood, PhD
• James Montie, MD
• Todd Morgan, MD
• Scott Tomlins, MD, PhD
• John Wei, MD
• Jim Wilson, PhD
This material is based upon work supported by the University of Michigan MCubed Initiative and funding from the National Science Foundation Grant No. CMMI 1536444
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Brian Denton
Industrial and Operations Engineering
University of Michigan
Thank You
Slides posted on my website:
http://umich.edu/~btdenton
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