Transcript HHS Briefing- Breast Cancer Screening

Agency for Healthcare Research and Quality
Advancing Excellence in Health Care • www.ahrq.gov
US Preventive Services Task
Force
Diana Petitti, MD, MPH
Arizona State University
Advancing
Excellence
in Health
Care
Today’s outline
 Background on the USPSTF
 USPSTF Analysis and Recommendation
on Breast Cancer Screening
Advancing
Excellence
in Health
Care
U.S. Preventive
Services Task Force
 16 member independent, volunteer panel
convened by AHRQ
 Non-Federal experts in clinical prevention
and primary care
 Use evidence to create new and updated
recommendations on screening,
counseling, and medications to prevent
illness
Advancing
Excellence
in Health
Care
USPSTF
 Relevant to practice of primary care for
asymptomatic persons AND average
risk persons
 Uses systematic, unbiased evidence
reviews to gather data on both benefits
and harms
Advancing
Excellence
in Health
Care
USPSTF
 The USPSTF does not use cost or cost
effectiveness data in making
recommendations
 The USPSTF does not make insurance
coverage or policy determinations
Advancing
Excellence
in Health
Care
USPSTF
 New member nominations are sought each
year from the public and from partner
organizations through a Federal Register
notice
– Requirements for nominees
 Expertise in prevention and primary care
 Strong experience in critical appraisal of evidence
 Primary care experience
– New members are named by the AHRQ Director
Advancing
Excellence
in Health
Care
The making of a
recommendation
 Each systematic review starts with an analytic
framework and key questions
 Project at this stage is informed by
– Previous evidence review and recommendation (if
an update)
– Topic Prioritization workgroup of the USPSTF
– 3-4 member topic workgroup of the USPSTF
– Evidence-based practice center (EPC) Principal
Investigator and team
Advancing
Excellence
in Health
Care
Analytic Framework on
Screening for a Disease
Advancing
Excellence
in Health
Care
USPSTF Recommendations
On Breast Cancer Screening
Advancing
Excellence
in Health
Care
Breast Cancer Screening
Recommendation
 Update of 2002 recommendation begun
in 2007
 Two reports commissioned by AHRQ:
– An updated systematic review and metaanalysis of trial data, including new
information from large databases
– A collaborative modeling study from the
Cancer Information and Surveillance
Network (CISNET)
Advancing
Excellence
in Health
Care
Systematic Evidence Review
Advancing
Excellence
in Health
Care
Updated Systematic
Evidence Review- (SER)
 PI: Heidi Nelson, Oregon Evidence-based
Practice Center (EPC)
 Trials of screening with breast cancer mortality
as outcome
– New trial from UK, updates from older trials
 Harms of screening: radiation exposure, pain,
adverse psychosocial responses, overdiagnosis,
false positive mammograms, additional imaging,
biopsies
– Using primary data from the Breast Cancer
Surveillance Consortium (BCSC).
Advancing
Excellence
in Health
Care
SER Results
Film Mammography
 8 screening trials for age 39 – 49 year
olds indicate reduced breast cancer
mortality in screened women
 1 screening trial for ages 70-74 years
indicates no mortality reduction
Advancing
Excellence
in Health
Care
SER Results
New evidence for women 40-49
 Age Trial, in United Kingdom
 Annual mammography to age 48 yrs vs.
‘usual care’
 Results
– Breast cancer mortality RR 0.83 (0.661.04)
– Number needed to invite 2,512 (1,1,4913,544)
Advancing
Excellence
in Health
Care
SER results
New Evidence for Women 40-49
 Additional follow-up for the Gothenburg
trial
 RCT of mammography among women
aged 39-59 in Gothenburg, Sweden in
1982
 Results
– Breast cancer mortality RR 0.69 (0.451.05)
SER Results
Meta-analysis of Screening Trials of
Women Age 39 to 49 Years
Screened
Cases/N
Control
Cases/N
Gothenburg (2003)
Kopparberg (1995)
Malmo (2002)
HIP (1986)
Age (2006)
CNBSS-1 (2002)
Ostergotland (2002)
Stockholm (2002)
34/11,724
22/9,582
53/13,568
64/13,740
105/53,884
105/25,214
31/10,285
34/14,303
59/14,217
16/5,031
66/12,279
82/13,740
251/106,956
108/25,216
30/10,459
13/8,021
0.69 (0.45, 1.05)
0.72 (0.38, 1.37)
0.73 (0.51, 1.04)
0.78 (0.56, 1.08)
0.83 (0.66, 1.04)
0.97 (0.74, 1.27)
1.05 (0.64, 1.73)
1.47 (0.77, 2.78)
Total
437/152,300
615/195,919
0.85 (0.75, 0.96)
Study (yr)
Relative Risk for Breast
Cancer Death (95% CI)
0.2
0.5
Favors screening
1
2
5
Favors control
16
SER Results
Summary of Meta-analyses of Screening Trials
For All Age Groups
Age Number of
Groups
trials
RR for Breast
Cancer Death
(95% CI)
NNI to Prevent 1
Breast Cancer Death
(95% CI)
39-49
8
0.85 (0.75-0.96)
1,904 (929-6,378)
50-59
6
0.86 (0.75-0.99)
1,339 (322-7,455)
60-69
2
0.68 (0.54-0.87)
377 (230-1,050)
70-74
1
1.12 (0.73-1.72)
Not available
Trials and their acronyms are discussed in the text.
Abbreviations: RR, relative risk; CI, confidence interval; NNI, number needed to invite to screening.
17
Advancing
Excellence
in Health
Care
SER Results
Harms of Screening Mammography
 Radiation – per study very low
 Pain – common, transient
 Adverse psychosocial responses –
anxiety, distress, worry
 Overdiagnosis
– estimates vary - 9 European studies from
1 to 10%
Number per 1000 Women
Screened
Advancing
Excellence
in Health
Care
SER Results
Illustration of Overdiagnosis: Rates of
Invasive Cancer and DCIS
10
8
Invasive Cancer
6
4
DCIS
2
0
40-49
50-59
60-69
70+
Age (yrs)
Invasive
cancer
2.7
4.5
6.3
7.8
DCIS
0.9
1.4
1.6
1.6
19
SER Results: Harms of Screening- Rates of False
Positive and False Negative Mammograms
Rates (%)
12
120
10
100
False Positive
808
606
404
False Negative
202
00
40-49
50-59
60-69
70+
Age (yrs)
False Pos
9.8
8.7
7.9
6.6
False Neg
0.1
0.1
0.1
0.2
20
Advancing
Excellence
in Health
Care
SER results
Breast Self Examination
 Benefits: Two trials conducted in
countries (China, Russia) without mass
mammography screening
– No mortality reduction in either trial
 Harms
– Increased benign biopsy rates in the BSE
group compared to controls
Advancing
Excellence
in Health
Care
SER Results
Clinical Breast Examination
 RCTs in countries without mass mammography
screening (one discontinued, two underway)
 Canadian trial from the 1980’s compared
mammography plus CBE plus BSE versus CBE
plus BSE and found no difference in mortality
between groups.
 Harms- inconclusive data, potential harms
include false positives, anxiety, excess imaging
and benign biopsies
Advancing
Excellence
in Health
Care
SER Results
Digital Mammography and MRI
 No studies of MRI screening in average
risk women
 No trials of digital mammography for
screening average risk women. Studies
of diagnostic accuracy suggest similar to
film mammography and more accurate in
younger women and those with dense
breasts.
Advancing
Excellence
in Health
Care
CISNET Modeling Data
Advantages of (Collaborative) Modeling
• Models can “test” strategies not feasible in the
population
• Models can “test” strategies in large samples
• Models can ask “what if” questions
• Multiple models can use common data
(“experimental conditions”) and:
– “Replicate” experiments
– Control the experimental conditions
– Provide sense of qualitative ranking
– Provide range of plausible quantitative effects
• Results can inform practice and policy debates
Overview of
CISNET Breast Cancer Models
Original Objective: Assess Impact of Screening
and/or Adjuvant Therapy on Breast Cancer Mortality
Population Inputs
(Common to all models)
•
•
•
•
Dissemination of Adjuvant Therapy
Dissemination of Mammography
Change in Background Risk
Mortality from Other Causes
Model Specific Inputs and
Assumptions
• Efficacy of Treatment
• Tumor Growth Rates & Metastatic
Spread
• Operating Characteristics of Screening
(e.g., sensitivity, lead time)
• Consequences of Screening (e.g., stage
shift, over diagnosis)
• Post Diagnosis Survival by Tumor Characteristics
Predicted Mortality
For:
• Treatment Alone
• Screening Alone
• Treatment and
Screening
Outcome Measures -Benefits
• Two primary measures of benefit of
screening (vs. no screening):
– % reduction in breast cancer mortality
– Life years gained (per 1000 women)
• Secondary metrics:
– Additional change in effect for
screening at ages younger or older
than 50 to 69.
Outcome MeasuresResources and Harms
• Resources required:
– Number of screening mammograms
• Exposure to harms:
– False positive screens
– Number of un-necessary biopsies
– Detection of tumors never destined to
cause breast cancer death (“over
diagnosis”)
– (NO measure of morbidity or decrement in
QOL)
% Benefit Maintained Moving from Annual to
Biennial Screening by Strategy and Model
Screening
Strategy
Models
W
M
G
D
S
E
50-69
68%
93%
85%
75%
74%
75%
40-69
67%
97%
86%
75%
73%
73%
45-69
70%
96%
91%
78%
78%
74%
40-79
70%
98%
87%
78%
76%
75%
40-84
71%
97%
88%
81%
77%
75%
55-69
71%
92%
91%
80%
80%
75%
60-69
70%
93%
86%
74%
74%
73%
50-74
72%
94%
89%
80%
79%
76%
50-79
70%
94%
88%
78%
85%
75%
50-84
73%
95%
89%
81%
79%
76%
~70 to 98% of benefit maintained screening biennial
Percent mortality decline
Efficiency Frontier Non-dominated Strategies
(% Mortality Decline)– Exemplar Model
Model S
40%
35%
30%
25%
20%
15%
10%
5%
0%
A 40-84
A 50-84
B 50-84
A 40-79
B 50-79
A 50-79
B 40-79
B 50-74
B 60-69
B 50-69
0
10
20
30
Average number of screens
40
Harms: Screen Detection of Invasive Tumors
Never Destined to Cause Cancer Death by Age
Annual Screening Ages 40-84
25%
Percent over diagnosis
• Model assumes that all
invasive cancers
progress with different
age-specific lead times
• Percent dying in lead
time increases steeply in
older age due to:
– High rate of death
from other illnesses
– Longer lead time in
older age
20%
15%
10%
5%
0%
40- 45- 50- 55- 60- 65- 70- 75- 8044 49 54 59 64 69 74 79 84
Age
Model D
Harms: Screen Diagnosis of Tumors Never
Destined to Cause Cancer Death
• Two models (E, W) include:
– Some DCIS/small local tumors that never progress
(“low malignant potential”)
– Screen detection of progressive invasive cancers
where death occurs in the lead time from other
illness
• These models project “over-diagnosis” rates
several orders of magnitude higher than models
without “low malignant potential” tumors
• Overall, there is uncertainty for this potential
harm due to limited primary data upon which to
base models
Potential Harms:
False Positive Results, Unnecessary Biopsies
Based on published age-specific specificity in BCSC:
• False positives increase in linear fashion with
number of mammograms performed (~8.3% rate;
varies by age)
– If 9 screens ~0.8 false + per woman
– If 18 screens ~1.5 false +
– If 36 screens ~3.0 false +
• Adding 10 years screening in younger women adds
> 2x as many false positives as adding 10 years at
older ages.
• ~ 7% of false positives lead to “unnecessary” biopsy
Balance Sheet of Potential Benefits & Harms
Starting Ages
Model S
Potential Benefits (vs. no screening)
Potential Harms
Average
Screens
per 1000
%
Mortality
Reduction
Breast
Cancer
Deaths
Averted
per 1000
Life
Years
Gained
per 1000
# False
positives
per 1000
# of
unnecessary
biopsies per
1000
Over
diagnosis of
invasive
cancer*
B 40-69
13700
16%
6.1
120
1250
88
0.8%
B 45-69
11800
17%
6.2
116
1050
74
0.8%
B 50-69
8900
15%
5.4
99
780
55
0.7%
B 55-69
6900
13%
4.9
80
590
41
0.8%
B 60-69
4200
9%
3.4
52
340
24
0.6%
Strategy
Biennial
Annual
Shaded =dominated by other strategies
A 40-69
27600
22%
8.3
164
2250
158
1.0%
A 45-69
22600
22%
8.0
152
1800
126
0.9%
A 50-69
17800
20%
7.3
132
1350
95
0.9%
A 55-69
13000
16%
6.1
102
950
67
0.9%
A 60-69
8400
12%
4.6
69
600
42
0.8%
*% over-diagnosed invasive cancers within the strategy divided by all cancer cases occurring over life time from age 40.
Probability of over-diagnosis is ~10 times higher in models E and W with explicit LMP
Balance Sheet of Potential Benefits & Harms
Stopping Ages
Model S
Potential Benefits (vs. no
screening)
Potential Harms
Strategy Average
Screens
per
1000
%
Mortality
Reduction
Breast
Cancer
Deaths
Averted
per 1000
Life
Years
Gained
per
1000
# False
positives
per 1000
# of
unnecessary
biopsies per
1000
Over
diagnosisinvasive*
15%
5.4
99
780
55
0.7%
Biennial
B 50-69
8900
B 50-74
11100
20%
7.5
121
940
66
1.5%
B 50-79
12300
25%
9.4
130
1020
71
2.1%
B 50-84
13800
26%
9.6
138
1130
79
3.3%
A 50-69
17800
20%
7.3
132
1350
95
0.9%
A 50-74
21400
26%
9.5
156
1570
110
1.7%
A 50-79
24400
30%
11.1
170
1740
122
2.6%
A 50-84
26900
33%
12.2
178
1880
132
3.7%
Annual
*% over-diagnosed invasive cancers within the strategy divided by all cancer cases occurring over life time
from age 40. Probability of over-diagnosis is ~10 times higher in models E and W with explicit LMP.
Shaded=dominated by other strategies
USPSTF Assessment- Grades
Net Benefit (Benefit – Harms)
Certainty
Substantial Moderate
Small
Zero or
negative
High
A
B
C
D
Moderate
B
B
C
D
Low
Insufficient
Advancing
Excellence
in Health
Care
Summary of New USPSTF
recommendations
 Biennial screening mammography between
50 and 74 years (B grade)
 The decision to start regular screening
before the age of 50 should be an individual
one and take into account patient context,
including values regarding specific benefits
and harms (C grade)
 Previous recommendation was to screen
women 40 and older every 1 to 2 years
Advancing
Excellence
in Health
Care
Summary of New USPSTF
recommendations
 The USPSTF concludes evidence is
insufficient to assess the additional benefits
and harms of screening mammography in
women 75 years or older (I statement)
 Previous recommendation had no ending
date (applied to women 40 and older)
 Insufficient evidence on the additional
benefits and harms of clinical breast
examination beyond mammography in
women 40 or older (I statement)
 This is unchanged from previous
Advancing
Excellence
in Health
Care
Summary of New USPSTF
recommendations
 USPSTF recommends against clinicians
teaching women how to perform breast selfexamination (D grade)
 Previous recommendation: teaching BSE was
given an Insufficient Evidence rating
 Insufficient evidence to assess additional
benefits and harms for
– digital mammography or
– magnetic resonance imaging
(I statement)
 These new modalities were not mentioned in
the 2002 recommendation
Advancing
Excellence
in Health
Care
 Questions and Discussion