November 20th, 2009…
The good, the bad, the ugly
The USPSTF recommends against routine screening
mammography in women aged 40-49.
The decision to start…should be an individualized one and take patient
context into account, including the patients values regarding specific
benefits and harms.”
(C recommendation)
Moderate certainty that the net benefit is small
Annals of Int. Med Nov. 2009: 151 (10) 716-726
Additional USPSTF recommendations…
Women 50 – 74 yrs: change from every 1-2 yrs to every 2 yrs
•
Insufficient evidence for or against screening women after 75 yrs
Insufficient evidence for or against CBE in women > 40 yrs
Recommended against physicians teaching BSE
Annals of Int. Med Nov. 2009: 151 (10) 716-726
What was “good”?
Evidence-based guidelines are critical for medical
decision making
– Outcome data should representative “real world” scenarios
• USPSTF used Breast Cancer Surveillance Consortium (BCSC)
data representing a mix of breast imaging practices
– academic, private, geographically diverse
What was “bad” ?
The presentation…
Steve Breen San Diego Union Tribune 11/30/09
Signe Wilkinson Philadelphia Inquirer 11/20/09
Get a Mammogram. No Don’t. Repeat.
By GINA KOLATA
Published: November 21, 2009
The current dispute over mammograms gives many people who’ve been around since
the 1980s a sense of déjà vu. Like archeologists arguing endlessly over the same set of
bones, cancer specialists, it can seem, have been arguing endlessly over pretty much the
same set of data…..
What was “ugly”?
Data on which analyses were based was old (same RCTs
from 1980’s - 2002 used in prior USPSTF recs)
–
–
–
–
Mortality reductions significantly less than newer trials
False positive rates higher
Radiation risk overestimated
BCSC data from pre-digital mammo era (<2005)
Why wasn’t newer data used?
Outcomes Table
Annals of Int. Med Nov. 2009: 151 (10) 716-726
Diagnostic Performance of Digital versus Film Mammography for
Breast-Cancer Screening
Etta D. Pisano, M.D., Constantine Gatsonis, Ph.D., Edward Hendrick, Ph.D.,
Martin Yaffe, Ph.D., Janet K. Baum, M.D., Suddhasatta Acharyya, Ph.D.,
Emily F. Conant, M.D., Laurie L. Fajardo, M.D., Lawrence Bassett, M.D., Carl
D'Orsi, M.D., Roberta Jong, M.D., Murray Rebner, M.D., for the Digital
Mammographic Imaging Screening Trial (DMIST) Investigators Group
Published at www.nejm.org September 16, 2005
ACRIN Digital Trial 6652 - DMIST
Group
# Cancers
#Women
%DMIST cancers
% DMIST women
age<50
pre or perimenopausal
AND with dense breasts
44
7315
13.1
17.11
age<50
pre or perimenopausal
AND nondense breasts
14
4600
4.2
10.76
age<50
postmenopausal
AND with dense breasts
7
1107
age<50
postmenopausal
AND nondense breasts
7
1108
2.1
2.59
Age 50 or over
postmenopausal
AND nondense breasts
127
14716
37.9
34.42
Age 50 or over
pre or perimenopausal
AND nondense breasts
19
1906
5.7
4.46
Age 50 or over
Postmenopausal
AND dense breasts
87
9142
Age 50 or over, pre or perimenopausal and with dense
breasts
23
1977
6.9
4.62
7
889
2.1
2.08
335
42760
100%
100%
Missing demographic categorization information
Total
21.5%
78.6%
2.1
26.0
33.1%
64.9%
2.59
21.38
72 cancer in 14,130 women = 5.1 cancers/1000 in women < 50 years
Age of new patient visits – Rowan Breast Center
2002
2003
2004
2005
2006
2007
2008
through
6.30.2009
TOTAL
0
1 (0.2%)
2 (0.3%)
1 (0.1%)
0
0
1 (0.1%)
0
7 (0.1%)
20 - 29
8 (1.2%)
9 (1.5%)
4 (0.7%)
8 (1.2%)
2 (0.3%)
6 (1.0%)
25 (3.0%)
6 (1.5%)
90 (1.4%)
30 - 39
64 (9.4%)
68 (11.3%)
47 (8.2%)
76 (11.3%)
49 (8.0%)
50 (8.3%)
95 (11.5%)
39 (9.5%)
612 (9.9%)
40 - 49
211 (30.8%)
185 (30.8%)
172 (30.0%)
190 (28.2%)
187 (30.6%)
173 (28.8%)
218 (26.3%)
116 (28.4%)
1826 (29.3%)
50 - 59
207 (30.2%)
174 (29.0%)
176 (30.7%)
194 (28.8%)
197 (32.2%)
156 (26.0%)
228 (27.5%)
116 (28.4%)
1809 (29.1%)
60 - 69
112 (16.4%)
102 (17.0%)
109 (19.0%)
120 (17.8%)
107 (17.5%)
124 (20.7%)
165 (19.9%)
76 (18.6%)
1126 (18.1%)
70 - 79
70 (10.2%)
52 (8.7%)
51 (8.9%)
62 (9.2%)
60 (9.8%)
59 (9.8%)
75 (9.0%)
41 (10.0%)
579 (9.3%)
80 - 89
12 (1.8%)
8 (1.3%)
12 (2.1%)
21 (3.1%)
8 (1.3%)
31 (5.2%)
19 (2.3%)
15 (3.7%)
154 (2.5%)
90 - 99
0
1 (0.2%)
1 (0.2%)
1 (0.1%)
1 (0.2%)
1 (0.2%)
3 (0.4%)
0
9 (0.1%)
Total #
684
600
574
673
611
600
829
409
6212
AGE
< 20
Annals of Int. Med Nov. 2009: 151 (10) 716-726
Non- Randomized Controlled Trial
Journal of Cancer
Cancer: Aug. 1, 2002/Vol 95/No. 3
The Impact of Organized Mammography Service Screening on
Breast Carcinoma Mortality in Seven Swedish Counties
A Collaborative Evaluation
Stephen W.Duffy, Msc., Laszlo Tabar, M.D.
Hsui-His Chen, D.D.S.Ph.D., Marit Holmqvist
Ming-Fang Yen, M.Sc.,et al.
Background: The evaluation of organized mammographic service screening programs is a
major challenge in public health. In particular, there is a need to evaluate the effect of the
screening program on the mortality of breast carcinoma, uncontaminated in the screening
epoch by mortality from 1) cases diagnosed in the prescreening period and 2) cases diagnosed
among unscreened women (i.e., nonattenders) after the initiation of organized screening.
Cancer: Aug. 1, 2002/Vol 95/No. 3
Method: Population based screen program begun in 1978-89
• Screening performed every 1.5 - 2 years.
Conclusions: Death rate in Swedish Seven Counties decreased
over past 29 yrs in proportion to % women screened
• For screened women:
• Death rate decreased by 44%
For those refusing screening, no change in death rate
Journal of Cancer
Effectiveness of Population-Based Service
Screening With Mammography for Women
Ages 40 to 49 Years
Barbro Numan Hellquist, MSc1; Stephen W. Duffy, MSc2; Shahin Abdsaleh, MD, PhD3; Lena Bjo¨rneld, RN4;
Pa´l Borda´s, MD5; La´szlo´ Taba´r, MD, PhD6; Bedrich Vita´k, MD, PhD7; Sophia Zackrisson, MD, PhD8;
Lennarth Nystro¨m, PhD9; and Ha˚kan Jonsson, PhD1
RESULTS: There was no significant difference in breast cancer mortality during the prescreening period. During
the study period, there were 803 breast cancer deaths in the study group (7.3 million person-years) and 1238
breast cancer deaths in the control group (8.8 million person-years). The average follow-up was 16 years. The
estimated RR for women who were invited to screening was 0.74 (95% CI, 0.66-0.83), and the RR for women
who attended screening was 0.71 (95% CI, 0.62-0.80).
CONCLUSIONS: In this comprehensive study, mammography screening for women ages 40 to 49 years was
efficient for reducing breast cancer mortality.
Cancer: online publication 9/29/10
Swedish Screening Update 2011
Methods:
• Women aged 40 -49 yrs invited to screen vs those not invited
• Outcome measure breast CA death
• The average follow-up 16 years (1986 to 2005)
Results:
• 803 deaths in study group (7.3 million person-years)
• 1238 deaths in control group (8.8 million person-years)
• RR for those invited to screen was 0.74 (95% CI, 0.66-0.83)
• RR for those attended screening was 0.71 (95% CI, 0.62-0.80)
Those who actually participated in screening had 29% lower BCA
mortality than those who were not invited to screening
Woman screened to prevent 1 death?
Estimate of 1904 women in 40’s needed to be invited
to screening to prevent 1 BCA death is way off...
– Using newer data from women actually screened and
followed for 20 yrs, NNI was 726
This number is even less that what was estimated by
USPSTF for women in 50’s (1339)
Annals of Int. Med Nov. 2009: 151 (10) 716-726
What about Risks?
Yes, mammography is far from perfect and the risk of a
false positive is ~50% with decade of routine screening
• What are false positives?
– 10% call back rate from screening
– Approx. 2.4% biopsy rate (24/1000)
Nevertheless, women report they would accept
trade-off of FP in favor of finding cancer early1
Schwartz LM et al. BMJ 2000;1635-40.
Cancer diagnosed in 40’s?
Cancers that occur in pre-menopausal women have a
more rapid growth rate
•One in 6 breast cancer deaths are attributable to
women diagnosed in their 40’s
•One third of all years lost to breast cancer deaths are
due to women diagnosed in their 40’s
Wu LC et al. Ann Inten Med 2012;157;597.
Shapiro S et al. HIPP and Sequelae, JHU Press 1988
Perspective:
United States Preventive Services Task Force
Screening Mammography Recommendations:
Science Ignored
R. Edward Hendrick1 and Mark A. Helvie21
Objective: To examine the scientific evidence used by USPSTF to
recommend against screening mammography:
•Women 40–49 years old
•Against annual screening mammography in women 50 and older.
AJR 2011; 196:W112-W116
Conclusions
Averaged over six USPSTF models of benefit for
annual screening:
• For 40–74 yrs: up to 39.6% mortality reduction
– 71% more lives saved than USPSTF biennial screening
for 50–74 yrs olds, which had 23.2% mortality reduction
For 40–84 years: 99,829 more lives saved than USPSTF recs if
all women comply, and 64,889 more lives with the current 65%
compliance rate
AJR 2011; 196:W112-W116
Potential Harms?
For screening women 40–49 yrs screened yearly?
•
•
•
•
a recall for diagnostic workup every 12 years
a negative biopsy every 149 years
a missed breast cancer every 1,000 years
and a fatal radiation-induced breast cancer every 76,000–
97,000 years
“Evidence made available to USPSTF strongly supports
the mortality benefit of annual screening mammo
beginning at age 40 yrs, whereas potential harms of
screening with this regimen are minor”
AJR 2011; 196:W112-W116
The Screening Process
General Population
Population with Disease
How Should Women Be Screened?
Risk Stratification
•
•
•
•
•
•
•
Gender
Personal/Family History
Exposure history
Genetics
Serum Biomarkers
Tissue Markers from Prior Biopsy
Risk Models (Claus/Gail)
Imaging --- what quantitative measures can we use?
Density as a Risk Factor
Mammographic dense tissue, percent dense area (PD) is one
of strongest risk factors for breast cancer
Boyd et al., NEJM 2007
Women with >50% dense breasts are at 3- to 5X greater
risk for breast cancer than women with density <25% 2
– Partly due to the lower sensitivity of mammo but remains even when
accounting for “masking”
– Mammo dense breast tissue is rich in epithelium and stroma and
association could represent activation of these cells
Mammographically dense breast tissue results in up to 3X
higher false positive call-backs at screening3
Boyd 1995, 2Tice Ann Intern Med. 2008, 3Yankaskas AJR 2001
Breast Density
Estimation
Cumulus (Univ. Toronto)
PD = 42.5%
Annals of Internal Medicine
Established in 1927 by the American College of Physicians
Using Clinical Factors and Mammographic Breast Density to
Estimate Breast Cancer Risk: Development and Validation of
a New Predictive Model
Jeffrey A. Tice, MD; Steven R. Cummings, MD; Rebecca Smith-Bindman, MD;
Laura Ichikawa, MS; William E. Barlow, PhD; and Karla Kerlikowske, MD
Conclusion: A breast cancer prediction model that incorporates
routinely reported measures of breast density can estimate 5-year
risk for invasive breast cancer. Its accuracy needs to be further
evaluated in independent populations before it can be recommended
for clinical use.
Ann Intern Med. 2008;148:337-347
Computer-Assisted Risk Estimation
General Population
Risk stratification
Image assessment
Image Screening
Imaging diagnosis/guided biopsy
Population with Disease
Identify women at high risk of breast cancer, so customized screening protocols and
individualized risk reduction strategies may be implemented
Patient questionnaire
Calculated glandularity
Tailored screening
recommendations
What about DCIS?
In U.S. in 1983 (prescreening era) 4,900 women were
diagnosed with DCIS
In 2010, approximately 54,000 women who will be
diagnosed with DCIS (20-30% of cancers diagnosed)
How do we tell the bad actors from the less bad ones???
http://www.seer.cancer.gov/csr/1975_2007/browse_csr.php?section=4&page=sect_04_zfig.01.html
Graph shows age-adjusted incidence rates of DCIS in the United States from 1975 to 2007.
Jørgensen K J et al. Radiology 2011;260:621-627