Screening for Cancer X

ACOFP:
Screening Wars: The
Science Strikes Back
Andrew W. Swartz, MD
10/7/2014
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The Epidemiology
of
Cancer Screening
Andrew W. Swartz, MD
Board Certified Family Physician
Emergency Medicine Physician
Flight Surgeon, Alaska Air National Guard (Lt Col)
Clinical Instructor, Alaska Family Medicine Residency (U.W.)
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COI + Biases
Am a member of a profession (and specialty) which profits from cancer screening and
treatment
No financial interest in any patents or products
No direct financial relationship to either the cancer screening or treatment industry
Not trying to get any votes
Practice in fear of the legal liability associated with “missing something”
May soon be graded by how many of my patients get screened
Am a member of a society whose health care system is in financial jeopardy
Like most rational humans, I strongly desire prevention and screening to work so that
my loved ones and I may live longer
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Goals
Encourage an appreciation of relevant versus irrelevant screening
evidence
Encourage an appreciation of the harms of screening
Explain the cause of disagreements about screening effectiveness
Encourage physicians and patients to review the actual evidence
for screening
Introduce the concept of “Cancer without Disease”
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Questionnaire
Screening for Cancer X
5-year survival
– Without screening: 68 %
– With screening
99 %
Proportion of Stage-1 cancer cases
– Without screening: 36 %
– With screening:
54 %
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Questionnaire
Screening for Cancer Y
Mortality
– Without screening:
– With screening
2 deaths per 1000 persons
1.6 deaths per 1000 persons
Incidence
– Without screening: 27 cases per 1000 persons
– With screening:
46 cases per 1000 persons
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Bad News
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“Why Smart People Are Stupid”
Here’s a simple arithmetic question:
A bat and ball cost a dollar and ten cents.
The bat costs a dollar more than the ball. How much does the ball cost?
The vast majority of people respond quickly and confidently,
insisting the ball costs ten cents. This answer is both obvious and wrong.
In a lake, there is a patch of lily pads. Every day, the patch doubles
in size. If it takes 48 days for the patch to cover the entire lake,
how long would it take for the patch to cover half of the lake?
Lehrer J. Why Smart People Are Stupid. The New Yorker. June 12, 2012. Online.
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Epidemiology Outline
1. Scientific Method
2. Hierarchy of Evidence
3. Cancer Screening Theory
4. Detection Biases
5. Primary Endpoint [Controversy]
6. Types of Evidence
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Scientific Method
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Hierarchy of Evidence
Systematic Reviews + Meta-analyses of RCT's
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Cancer Screening Theory
Screen
Screen
Screen
Screen
Screen
Screen
Death
Symptomatic
Death
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Cancer Screening Theory
Cancer Begins
Symptomatic Diagnosis
Death
Not Screened
Holy Grail
Screening Diagnosis
Survival Gain
Early
Treatment
Screened
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Cancer Screening Theory
“There is compelling intuitive appeal to
the idea that earlier treatment must be
better than later treatment.1”
1. Monographs in Epidemiology and Biostatistics, Volume 19. Morrison A. Screening in Chronic Disease, 2nd Ed. 1992. Oxford University Press. New York.
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Cancer Screening Theory
Questions to Answer
1. Can we diagnose cancer early ?
Yes
2. Is early treatment beneficial ?
UNCLEAR
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Cancer Screening Theory
“The evaluation of screening must be
based on measures of disease
occurrence that will not be affected by
early diagnosis except to the extent that
early treatment is beneficial.1”
1. Monographs in Epidemiology and Biostatistics, Volume 19. Morrison A. Screening in Chronic Disease, 2nd Ed. 1992. Oxford University Press. New York. p15.
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Relativity Analogy
Diameter
Mortality
Length
Survival
Incidence
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The Father of Cancer Screening
The Father of Cancer Screening
1963: HIP begins 3 year recruitment of 62,000 women aged 40-60
for a randomized controlled trial of screening mammography.
Shapiro S, Strax P, Venet L. Evaluation of Periodic Breast Cancer
Screening With Mammography. JAMA. 1966;195(9): 111.
Hutchinson B, Shapiro S. Lead Time Gained by Diagnostic
Screening for Breast Cancer. J Natl Cancer Inst 1968;41(3): 665-681.
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Detection Biases
1. Lead-time bias
2. Length bias
(1966)
(1968)
3. Overdiagnosis bias
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(1968)
Lead-time Bias
NO TREATMENT
[ True Survival Time ]
Cancer Begins
Symptomatic Diagnosis
Death
Not Screened
Survival Time
Lead Time
Survival Time
Screening Diagnosis
Screened
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Length Bias
NO TREATMENT
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Overdiagnosis Bias
Screen
Death
Screen
Screen
A
Screen
Screen
Screen
B
Symptomatic
C
D
E
Death
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Folkman J, Kalluri R. Cancer without disease. Nature. 2004;427:787.
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Overdiagnosis Bias
“Overdiagnosis occurs with the detection of “pseudodisease” (5), a subclinical
condition that would not have produced signs or symptoms before the individual
died of other causes.1”
“Overdiagnosis plays havoc with our understanding of cancer statistics.
Because overdiagnosis effectively changes a healthy person into a diseased one,
it causes overestimations of the sensitivity, specificity, and positive predictive value of
screening tests and the incidence of disease (13). As the MLP and a recent analysis of
Surveillance, Epidemiology, and End Results (SEER)1 data illustrate (14),
overdiagnosis also markedly increases the length of survival, regardless of whether screening
or associated treatments are actually effective. However, overdiagnosis does not reduce mortality
because treating subjects with pseudodisease does not help those who have real disease.
Consequently, mortality is the most valid end point for the evaluation of screening effectiveness.1”
“pseudodisease is almost impossible to document in a living individual. 1”
1. Black, WC. Overdiagnosis: An Underrecognized Cause of Confusion and Harm in Cancer Screening. J Natl Cancer Inst. 2000;
92 (16):1280-1282.
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Overdiagnosis Bias
Pseudodisease
Overdiagnosis
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Illusion
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Illusion
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Survival Paradox
Because of detection biases,
survival gains from early treatment
cannot be evaluated by measuring
survival.
This has been known and accepted for over 40 years
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Primary Outcome
“The evaluation of screening must be
based on measures of disease
occurrence that will not be affected by
early diagnosis except to the extent that
early treatment is beneficial.1”
1. Monographs in Epidemiology and Biostatistics, Volume 19. Morrison A. Screening in Chronic Disease, 2nd Ed. 1992. Oxford University Press. New York. p15.
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Summary of Detection Biases
Case Mortality
Absolute Mortality
Survival
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Staging
Incidence
Primary Outcome
Mortality
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Primary Outcome
Mortality
Total Deaths
Death Rate (Deaths per 10,000 person-years)
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Primary Outcome
Mortality
All-Cause
- OR -
Disease-specific
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Primary Outcome ?
All-Cause
Mortality
Disease-Specific
Mortality
X
X
X
?
X
1. Olsen O, Gøtzsche PC. Screening for breast cancer with mammography. Cochrane Library. 2000.
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The Father of Cancer Screening
Shapiro S, Strax P, Venet L (1966). Evaluation of Periodic Breast
Cancer Screening With Mammography. Journal of the American
Medical Association (JAMA). 1966;195(9):111.
Hutchinson B, Shapiro S. Lead Time Gained by Diagnostic
Screening for Breast Cancer. JNCI J Natl Cancer Inst (1968) 41(3): 665-681.
Shapiro S, Strax P, Venet L. Periodic breast cancer screening in
reducing mortality from breast cancer. JAMA. 1971;215(11):1784
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Sam Shapiro’s Words
“General Mortality. —If the present picture of lower breast
cancer mortality in the study group, as compared with the
control group, persists over the long run, a question that will
need answering is whether mortality from all other causes
differs between these two groups.”
Shapiro S, Strax P, Venet L. Periodic breast cancer screening in reducing mortality from breast cancer. JAMA.
1971;215(11):1784
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Primary Outcome ?
All-Cause
Mortality
Disease-Specific
Mortality
X
X
X
?
X
X
X
X
1. Olsen O, Gøtzsche PC. Screening for breast cancer with mammography. Cochrane Library. 2000.
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TheNNT.com
Needless to say, at TheNNT.com we do not
accept disease-specific mortality as an outcome
for any kind of study. We consider these outcomes
fraught with problems, misleading, and not
patient-centered. Patients don’t want to avoid a
certain type of death—they just don’t want to die.
1. http://www.thennt.com/blog/2011/08/on-our-lung-cancer-ct-scan-nlst-trial-numbers/
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Primary Outcome ?
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Primary Outcome ?
Black WC, et al. All-Cause Mortality in Randomized Trials of Cancer Screening. JNCI 2002;94:167–73.
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Primary Outcome ?
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Example
RCT of Heavy smokers, N = 6345 (3171/3174)
Chest x-ray every 6 months for 3 years
Followed for 9 years from randomization
RR = 1.36 [0.94-1.98]
RR = 1.16 [1.004 – 1.35]
NNH = 65
Kubik A, Parkin DM, et al. Lack of Benefit from Semi-Annual Screening for Cancer of the Lung: Follow-up Report of a Randomized Controlled Trial on a Population of High-Risk Males in Czechoslovak
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Secondary Outcome ?
Cancer Incidence
Decrease
Screening which also removes pre-cancerous lesions
Cervical
Colonoscopy
No Change
Screening which only diagnoses cancer early
PSA
Mammograms
Increase
None !
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Overdiagnosis
“Overdiagnosis occurs with the detection of “pseudodisease,”
a subclinical condition that would not have produced signs or
symptoms before the individual died of other causes.1”
Overdiagnosis is NOT False-Positives
“When pseudodisease is treated, as it almost always is, long-term
survival is attributed to the treatment and is labeled a cure.1”
Overdiagnosis exposes the patient to all the potential harms of
treatment with zero potential benefits.
“Overdiagnosis is pure, unadulterated harm2”
Dr. Barnett Kramer, associate director for disease prevention at the National Institutes of Health
1. Black, WC. Overdiagnosis: An Underrecognized Cause of Confusion and Harm in Cancer Screening. J Natl Cancer Inst. 2000. 92(16):1280-1282.
2. "Cancer Society, in Shift, Has Concerns on Screenings." New York Times. 20-Oct-2009. Online.
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Overdiagnosis
The Problem:
Histologically Malignant ≠ Biologically Malignant
Folkman J, Kalluri R. Cancer without disease. Nature. 2004;427:787.
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Overdiagnosis – How Much ???
RCT's
Observ.
Breast
23 %1
50 %2
Lung
51 %2
92 %2,3
Prostate
25 %4
80 %2
Neuroblastoma *
1. Gøtzsche PC. Screening for breast cancer with mammography. The Cochrane Library. 2011.
2. Welch G and Black W. Overdiagnosis in Cancer. J Natl Cancer Inst 2010;102(9):605-13.
3. Sone S, Li F, Yang Z, Honda T, Maruyama Y, Takashima S. Results of three-year mass screening programme for lung cancer using mobile low-dose
spiral computed tomography scanner. Brit J
4. Illic D, et al. Screening for prostate cancer: an updated Cochrane systematic review. The Cochrane Library. 2009.
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Pseudodisease: Reservoir
Autopsy
Breast
7-39 %
Thyroid
36-100 %
Prostate
30-70 %
Welch G and Black W. Overdiagnosis in Cancer. J Natl Cancer Inst. 2010;102(9):605-13.
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Pseudodisease: Reservoir
Theory of Cancer Relativity
We can accurately measure the
amount of clinical cancer.
The amount of preclinical cancer
appears to be relative to how
vigorously we look for it.
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Example
RCT of Heavy smokers, N = 6345 (3171/3174)
Chest x-ray every 6 months for 3 years
Followed for 9 years from randomization
RR = 1.90 [1.09-3.30]
RR = 1.16 [1.00 – RR
1.35]= 1.36 [0.94-1.98]
NNH = 65
Kubik A, Parkin DM, et al. Lack of Benefit from Semi-Annual Screening for Cancer of the Lung: Follow-up Report of a Randomized Controlled Trial on a Population of High-Risk Males in Czechoslovak
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Primary Outcome ?
Black WC, et al. All-Cause Mortality in Randomized Trials of Cancer Screening. JNCI 2002;94:167–73.
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Summary
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Cancer Screening Theory
Cancer Begins
Symptomatic Diagnosis
Death
Not Screened
Screening Diagnosis
Survival Gain
Early
Treatment
Screened
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Overdiagnosis Bias
Pseudodisease
Overdiagnosis
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Survival Paradox
Because of detection biases,
survival gains from early
treatment cannot be assessed
by measuring survival.
This has been known and accepted for over 40 years
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Primary Outcome
Mortality
All-Cause
- AND -
Disease-specific
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Secondary Outcome
Cancer Incidence
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The Major Harm of Screening
Diagnosis of Pseudodisease = Overdiagnosis
Treatment of Pseudodisease = Overtreatment
Overdiagnosis is not false-positives!
Overdiagnosis appears as increased incidence
in the screened group
Overtreatment exposes the patient to all the harms
of treatment with no possible benefit
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Questions
Comments
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