N=2391
Breast cancer screening: evidence of benefit depends on the method used
Philippe Autier, MD, and Mathieu Boniol, PhD
International Prevention Research Institute, Lyon (France)
Correspondence
Ph Autier, International Prevention Research Institute, 95 Cours Lafayette, F-69006 Lyon
(France). Philippe.autier@i-pri.org; www.i-pri.org.
Conflict of interest
None to declare
1
Abstract
The ability of mammography screening to decrease breast cancer risk in general
populations (effectiveness) is often assessed by case-control studies that compare
the screening history of women dying from breast cancer to that of women still
alive. Some authors propose to institute the case-control design as the method of
reference for the evaluation of breast screening effectiveness. However, when
breast cancer mortality decreases for reasons unrelated to screening, this design
leads to results suggesting that screening is the cause of the decrease. Available
statistical methods cannot correct the confounding by indication that distorts
results of case-control studies. Studies based on the incidence-based mortality are
often flawed because they had no control area or ignored the role of treatments
in mortality reductions. Evaluation of effectiveness should rest on the monitoring
of the incidence of advanced cancer (that should decrease if screening is
effective), or on mortality trends in areas with contrasting screening policies and
where good information is available on non-screening factors involved in
mortality.
2
Background
Four randomised trials conducted in Sweden from 1977 to 1993 obtained results
suggesting 20 to 30% reductions in breast cancer mortality associated with
regular participation of women 40 to 74 years of age to mammography screening
[1-4]. These trials encouraged the implementation of mammography screening
services, and in 2012, screening programs have been in place for 20 years or more
in several high income countries or regions.
Breast screening mobilizes considerable resources and generates harm because
of false positive exams, overdiagnosis and overtreatment, the amount of which
depends on factors like screening intensity, screening ages, radiologist
experience and the legal environment (e.g., defensive medicine in the USA). An
essential question is thus the effectiveness of screening activities, that is, are
mortality reductions observed in the ideal conditions of randomised trial
(efficacy) also found in the real world conditions of general population mass
screening (effectiveness) ? If screening proved to be weakly effective while
causing harm, then resources could be re-allocated to more cost-effective, less
detrimental health activities.
In their paper, D Puliti and M Zappa [5] posit that case-control studies and
studies based on incidence-based mortality (IBM) constitute valid, unbiased
3
evaluations of screening effectiveness. In contrast, studies based on mortality
statistics have limitations that explain why their findings are different than those
of case-control and IBM studies. As a result of these considerations, the paper
proposes to institute the case-control design as the standard method for
evaluating breast screening effectiveness.
In this opinion article, we briefly review the main methods used for evaluation of
the effectiveness of breast screening and show that case-control and IBM studies
cannot provide reliable figures on screening effectiveness and may lead to errors.
In contrast, methods based on the incidence of advanced cancer and of cancerspecific mortality rates should remain the reference methods for assessing
screening effectiveness.
The case-control design
The case-control design compares the exposure to screening of women who died
from breast cancer (the cases) to that of women who did not die from breast
cancer (the controls). This comparison is deemed to inform on the ability of
regular participation to screening to reduce the risk to die from breast cancer.
This design is appealing because of its low cost and swift execution.
4
The many problems associated with case-control designs for the evaluation of
screening effectiveness have been described in length [6], but the more serious
limitation is the confounding by indication for which no method exists that can
adjust for it [7]. Compared with women participating in screening
mammography, non participating women have characteristics associated with a
higher risk to die from breast cancer and from other cause like higher rate of
obesity and of chronic disease, and lower compliance to treatments [8,9]. So,
although a number of non-participants die from breast cancer for reasons
unrelated to screening, the case-control design makes believe that these deaths
are due to not having been screened. This type of confounding by indication has
been termed “self-selection”. As the IARC Hanbook on Breast Cancer Screening
concluded:”Observational studies of screening, such as cohort and case-control
studies, may give biased measures of effect because of self-selection of women
for screening. There are no certain ways of eliminating the bias” [10].
In 2002, SW Duffy et al proposed a method to correct for self-selection [11]. This
method is based on computation of a quantity “Dr” that is the ratio of the breast
cancer mortality rate in non-participating women at the end of a screening
period to the rate in all women before screening introduction. Table 1
summarizes the effects of correcting for self-selection in a situation where
screening has no impact on breast cancer mortality. Panel 1 reflects the fact that
5
the risk of breast cancer death of participants to screening is 30 to 60% lower than
that of non participants and this difference in risk exists in the absence of
screening [12-13]. A case-control study after a period of screening will find a
crude risk of death of 0.61 in participants vs. non participants, but the correction
for self-selection will yield an adjusted relative risk of 1.0, in line with the
absence of effectiveness of screening. In Panel 2, a 25% reduction in breast cancer
mortality occurs that is unrelated to screening (e.g., because of improved
treatment). The crude risk of breast cancer death is still 0.61, but the quantity Dr
is smaller than in panel 1 because treatments have improved breast cancer
prognosis in non participants. As a consequence, the study will make believe that
participation to screening is associated with a 44% reduction in breast cancer
mortality.
Hence, when breast cancer mortality decreases over time for reasons unrelated to
screening, the case-control design will attribute the decrease to screening.
Correction for self-selection cannot adjust for confounding by indication when
mortality trends are changing for reasons other than screening.
Other biases specific to case-control designs will further distort the true
relationship between exposure to screening and breast cancer death. For instance,
the life-expectancy of women participating to screening is longer than that of non
6
participating women [13], with the consequence that participating women have a
greater chance to be selected as control, what will bias the risk of death in favour
of screening.
Incidence based mortality (IBM) studies
IBM studies compare breast cancer mortality in breast cancer patients diagnosed
during similar periods before (control period) and after screening introduction
(screening period). The advantage of this method is that it uses the refined
mortality that is obtained by excluding breast cancer deaths due to cancers
diagnosed before screening introduction. Some IBM studies are summarized in
Table 2.
According to the IARC Handbook on Breast Cancer screening [10] “Refined
mortality should be estimated for screened and unscreened population to ensure
comparability. Furthermore, cancer registration with data on treatment is likely
to be the only means for differentiating the confounding effect of changes in
treatment from the effect of screening.”
7
In Sweden, breast cancer mortality steadily decreases by 0.9% per year since 1972
that is well before screening started [14]. The two main IBM studies done in
Sweden [15,16] could not realize how these secular trends influenced their results
because they had no comparison areas where no screening existed during the
entire study period. Furthermore, these studies did not consider that changes in
mortality over time could also be due to improved treatments [19]. Mortality
trends in control areas may reflect the influence of non-screening factors [17,18],
but it cannot replace information on patient management that is known to vary
substantially across regions [20].
Swedish IBM studies corrected their results in various ways (Table 2). The most
contentious correction is that of mortality data for the sharp increases in breast
cancer incidence taking place after screening introduction. This correction is
based on the assumption that if screening had not existed, breast cancer
mortality would have increased in parallel to the incidence. This correction is not
justified because first, in the absence of screening, mortality and incidence trends
are not correlated, and second, mammography screening itself is the main cause
of increasing breast cancer incidence.
8
Finally, counting breast cancer deaths due to breast cancer diagnosed during a
specific period is prone to inaccuracies. In the study of Hellquist et al [17], the
ratio of deaths in participants and non-participants was 0.94. Bearing in mind
that women not participating to screening may have a risk of breast cancer death
1.7 to 3 times greater than participating women, a number of breast cancer deaths
may have been missing in the screened groups.
Changes in the incidence of advanced breast cancer mortality
Mammographic screening aims to detect cancer at an earlier stage, when the
cancer is less life threatening and easier to cure than if detected clinically. In a
previous work that followed this logic, we found that in randomized trials of
mammographic screening, breast cancer mortality reductions were directly
proportional to the fall in the incidence of advanced breast cancer [21].
The incidence of advanced breast cancer incidence is not influenced by
subsequent treatments. Therefore, in populations were breast screening is
widespread since long (≥7 years), a reduction of advanced cancer incidence
should reflect the impact of screening activities alone. Longstanding broad
9
consensus exists for considering a decrease in advanced breast cancer incidence
as the best early indicator of the impact of screening [1,10,22,23]. This consensus
fitted well with cancer registry data showing marked decreases in the incidence
of advanced cervical and colorectal cancers over the last decades [24,25] which
illustrated the contribution of screening to the reductions in mortality due to
these two cancers.
The IARC meeting of 2002 devoted a section on trends in advanced breast cancer
incidence [10]. However, at that time, few cancer registries had collected
adequate data on too short period of time after screening introduction.
From 2006 onwards, with accumulating years of screening activities in
populations where good quality cancer registries existed, larger amounts of data
on advanced breast cancer incidence were available. A systematic review showed
that in areas in Europe, North America and Australia where screening was
widespread since long, no or small decreases in the incidence of advanced and of
very advanced breast cancer was observed [26]. An analysis of breast cancer
incidence in the USA reached the same conclusion [27].
A team of radiologists performed an in depth analysis of screen-detected,
interval and all breast cancers diagnosed from 1989 to 2007 in the South-East
10
region of the Netherlands and found no decline in the incidence of advanced
breast cancer [28].
In the United Kingdom, cancer registry data of Scotland, Northern Ireland and
the West Midlands showed no decline of the incidence of advanced breast cancer
after screening introduction in 1989 [26,29].
Changes in breast cancer mortality rates in countries with large difference in
the timing of screening introduction
It is the observation of a lack of downward trends in the incidence of advanced
breast cancer in areas where such decrease was expected thanks to screening that
prompted us to compare breast cancer mortality trends in pairs of similar
European countries, since nonexistence of reduction in the incidence of advanced
breast cancer means no impact on breast cancer mortality. In any logic, if breast
screening was capable to reduce breast cancer mortality by 20 to 30% after 7 to 10
years, such reduction should become apparent in countries where screening is
widespread since long, whereas no or smaller reductions should be observed in
countries where screening was not implemented.
11
The ecological design may be useful for comparative effectiveness research, i.e.,
comparison of disease-specific trends in countries with similar quality of health
systems and access to treatment, but with different prevention policies. This
design has been used when randomized trials were impracticable, like for
instance, the banning of smoking in public places in 2006 in Scotland was
followed by a one-year 17% reduction in hospital admissions for acute
myocardial events [30]. In contrast, in England where such ban did not yet exists,
the hospital admission during that one-year period decreased by 4%. In this
respect, the IARC Handbook on Breast Cancer Screening stated that “Routine
screening programmes can be evaluated most readily by time trends and
differential mortality from the disease for which screening is being performed.
Probably the best known is screening for cervical cancer. The substantial
differences among the Nordic countries in the extent of organized screening were
closely matched by the mortality rates from cervical cancer (Läärä et al., 1987)”
[10].
We mimicked the Nordic study on cervical cancer screening by selecting three
pairs of European countries (The Netherlands and Belgium; Northern Ireland
and Ireland; Sweden and Norway) having similar prevalence of risk factors for
breast cancer death, access to treatment and expenditures for health, but where
by year 1993, nationwide screening was in place in the first country of each pair,
12
while screening was implemented 10 to 12 years later in the second country [31].
Of note, in 2005, participation to screening in Belgium was still below 60%. The
data showed equivalent reductions in breast cancer mortality from 1989 to 2007
in each country pair. These results agreed with the observation that breast cancer
mortality reductions in high income countries are unrelated to the temporal
introduction of screening mammography [14, 32].
A limitation of studies on mortality trends is the contamination of mortality data
during the screening era with deaths due to breast cancer diagnosed before
screening start. Also, probably not enough time had passed for being able to
observe the benefits of screening. The epidemiologists evaluating the Dutch
breast screening programme considered that decreases in breast cancer mortality
due to screening started quite soon after screening implementation [33], and thus,
the argument about insufficient observation time is not tenable. In 1993, the 8year survival of deadly (stage III) breast cancer is about 30% [34] and survival
has continuously improved since then. Our study extended over 15 to 19 years of
screening in Sweden, Northern Ireland and the Netherlands. Hence most fatal
breast cancers diagnosed in these three countries before the screening era
weighted little in the breast cancer mortality burden after 2000.
13
Conclusion
Evaluation of effectiveness of screening for cervical and colorectal cancer is
mainly based on time-trends of advanced disease incidence and cancer-specific
mortality, with use of designs enabling comparisons between periods and
geographical areas [24,25,35]. Until recently, the method based on incidence
trends of advanced breast cancer has been supported by many breast screening
enthusiasts [1,22,23]. Why this method is no longer cheered and why is there a
motivation to institute the case-control design as the reference method for
effectiveness evaluation?
We recommend abandoning the case-control design for the evaluation of
screening effectiveness because when cancer mortality is decreasing for any
reason, this design will attribute the decrease to screening, even though
screening had no effect on mortality. IBM studies are likely to obtain biased
results when secular trends in mortality and increasing treatment effectiveness
are not considered. Furthermore, the gathering of data for IBM analysis may be
subject to bias. We conclude that evaluation of effectiveness should be based on
the monitoring of the incidence of advanced cancer and on mortality trends in
areas with contrasting screening policies and where good information is
available on non-screening factors involved in mortality. Indeed, it remains to
14
explain why results of studies on effectiveness of breast screening do not match
with results of Swedish randomized trials.
References
1. Tabar L, Gad A, Holmberg LH, Ljungquist U, Fagerberg CJG, Baldetrop L,
et al. Reduction in mortality from breast cancer after mass screening
with mammography. Lancet 1985; i: 829-832.
2. Andersson I, Aspegren K, Janzon L, Landberg T, Lindholm K, Linell
F, et al. Mammographic screening and mortality from breast cancer:
the Malmo mammographic screening trial. BMJ 1988; 297:
943–948.
3. Frisell J, Lidbrink E, Hellstrom L, Rutqvist LE. Follow-up after 11 years update of mortality results in the Stockholm mammographic screening
trial. Breast Cancer Research and Treatment 1997; 45: 263–270.
4. Bjurstam N, Björneld L, Warwick J, Sala E, Duffy SW, Nystrom L, et al.
The Gothenburg breast screening trial. Cancer 2003; 97: 2387-2396.
5. Puliti D, Zappa M. Breast cancer screening: are we seeing the benefit?
BMC Medicine 2012 (in press).
6. Cronin KA, Weed DL, Connor RJ, Prorok PC. Case-control studies of
cancer screening: theory and practice. J Natl Cancer Inst 1998; 90:
498–504.
7. Bosco JLF, Silliman RA, Thwin SS, Geiger AM, Buist DSM, Prout MN, et al.
A most stubborn bias: no adjustment method fully resolves
confounding by indication in observational studies. J Clin Epidemiol.
2010;63:64-74.
8. Flamant C, Gauthier E, Clavel-Chapelon F. Determinants of noncompliance to recommendations on breast cancer screening among
women participating in theFrench E3N cohort study. Eur J Cancer Prev
2006; 15:27–33.
15
9. Ferrante JM, Chen PH, Crabtree BF, Wartenberg D. Cancer Screening in
Women: BMI and Adherence to Physician Recommendations. Am J Prev
Med 2007; 32: 525–531.
10. International Agency for Research on Cancer. IARC/WHO handbooks of
cancer prevention vol. 7: Breast Cancer Screening. IARC Press, Lyon, 2002.
11. Duffy SW, Cuzick J, Tabar L, Vitak B, Hsiu-His Chen T, Yen MF, Smith
RA. Correcting for non-compliance bias in case-control studies to
evaluate cancer screening programmes. Appl Statist 2002; 51(Part 2): 235–
243.
12. Duffy SW, Tabar L, Fagerberg G,Gad A, Grontoft O, South MC, Day NE.
Breast screening, prognostic factors and survival - results from the
Swedish two county study. Br J Cancer 1991; 64: 1133-1138.
13. Mook S, Van ’t Veer LJ, Rutgers EJ, Ravdin PM, van de Velde AO, van
Leeuwen FE, Visser O, Schmidt MK. Independent Prognostic Value of
Screen Detection in Invasive Breast Cancer. J Natl Cancer Inst 2011; 103:1–
13.
14. Autier P, Boniol M, LaVecchia C, Vatten L, Gavin A, Héry C, Heanue M.
Disparities in breast cancer mortality trends between thirty European
countries: retrospective trend analysis of WHO mortality database. BMJ
2010; 341:c3620.
15. Tabar L, Yen MF, Vitak B, Tony Chen HH, Smith RA, Duffy SW.
Mammography service screening and mortality in breast cancer
patients: 20-year follow-up before and after introduction of screening.
Lancet 2003; 361: 1405–10
16. SOSSEG. The Swedish Organised Service Screening Evaluation Group.
Reduction in Breast Cancer Mortality from Organized Service Screening
with Mammography: 1. Further Confirmation with Extended Data.
Cancer Epidemiol Biomarkers Prev 2006;15; 45–51.
17. Hellquist BN, Duffy SW, Abdsaleh S, Bjorneld L, Bordas P, Tabar L, Vitak
B, et al. Effectiveness of population-based service screening with
mammography for women ages 40 to 49 years. Cancer 2011; 117:714-722.
16
18. Kalager M, Zelen M, Langmark F, Adami HO. Effect of screening
mammography on breast-cancer mortality in Norway. New Eng J Med
2010; 363: 1203-1210.
19. Wilking U , Jonsson B, Wilking N, Bergh J. Trastuzumab use in breast
cancer patients in the six Health Care Regions in Sweden. Acta
Oncologica, 2010; 49: 844–850.
20. Johansson P, Fohlin H, Arnesson LG, Dufmats M, Nordenskjöld K,
Nordenskjöld B, Stål O. Improved survival for women with stage I breast
cancer in south-east Sweden: a comparison between two time periods
before and after increased use of adjuvant systemic therapy. Acta Oncol
2009; 48:504-513.
21. Autier P, Héry C, Haukka J, Boniol M, Byrnes G. Advanced breast cancer
and breast cancer mortality in randomized controlled trials on
mammography screening. J Clin Oncol 2009; 27:5919-5923.
22. Duffy SW, Tabar L, Vitak B, Day NE, Smith RA, Chen HH, Yen MF. The
Relative contributions of screen-detected in situ and invasive breast
carcinomas in reducing mortality from the disease. Eur J Cancer 2003; 39:
1755-1760.
23. Fracheboud J, Otto SJ, van Dijck JA, Broeders MJ, Verbeek AL, de Koning
HJ. Decreased rates of advanced breast cancer due to mammography
screening in The Netherlands. Br J Cancer 2004; 91: 861-867.
24. Sigurdson K, Sigvaldason H. Effectiveness of cervical cancer screening in
Iceland, 1964-2002: a study on trends in incidence and mortality and the
effect of risk factors. Acta Obstetricia et Gynecologica 2006; 85: 343-349.
25. Edwards BK, Ward E, Kohler BA, et al. Annual report to the nation on
the status of cancer, 1975-2006, featuring colorectal cancer trends and
impact of interventions (risk factors, screening, and treatment) to reduce
future rates. Cancer 2010; 116:544-573.
26. Autier P, Boniol M, Middleton R, Doré JF, Héry C, Zheng T, Gavin A.
Advanced breast cancer incidence following population‐based
mammographic screening. Ann Oncol 2011; 22:1726-1735.
17
27. Esserman L, Shieh Y, Thompson I. Rethinking screening for breast cancer
and prostate cancer. JAMA 2009; 302: 1685-1692.
28. Nederend J, Duijm LEM, Voogd AC, Groenewoud JH, Jansen FH,
Louwman MWJ. Trends in incidence and detection of advanced breast
cancer at biennial screening mammography in The Netherlands: a
population based study. Breast Cancer Research 2012; 14:R10
doi:10.1186/bcr3091
29. Autier P, Boniol M. The incidence of advanced breast cancer in the West
Midlands, United Kingdom. Eur J Cancer Prev 2012 [Epub ahead of print]
30. Pell JP, Haw S, Cobbe S, Newby DE, Pell ACH, Fischbacher C, et al.
Smoke-free legislation and hospitalizations for acute coronary
syndrome. New Eng J Med 2008;359:482-491.
31. Autier P, Boniol M, Gavin A, Vatten L. Breast cancer mortality in
neighbouring European countries with different levels of screening but
similar access to treatment: trend analysis of WHO mortality database.
BMJ 2011; 343: d4411.
32. Bleyer A. US breast cancer mortality is consistent with European
Data. BMJ 2011; 343: d5630.
33. Otten JDM, Broeders MJM, Fracheboud J, Otto SJ, de Koning HJ, Verbeek
ALM. Impressive time-related influence of the Dutch screening
programme on breast cancer incidence and mortality, 1975-2006. Int J
Cancer 2008; 123: 1929–1934.
34. Thomson CS, Brewster DH, Dewar JA, Twelves CJ. Improvements in
survival for women with breast cancer in Scotland between 1987 and
1993: impact of earlier diagnosis and changes in treatment. Eur J Cancer
2004; 40: 743–753
35. Quinn M, Babb P, Jones J, Allen E. Effect of screening on incidence of
and mortality from cancer of cervix in England: evaluation based on
routinely collected statistics. BMJ 1999; 318: 904-908.
18
Table 1 - Relative risk of breast cancer death associated with screening in an area with 75% participation to screening.
Panel A
Panel B
RR breast cancer
RR breast cancer
Non
All women
Non
All women
Participants
Participants
Period
death, participants vs.
death, participants
participants
†
participants
†
non-participants
vs. non-participants
Before screening
86
142
100
0.61
86
142
100
0.61
BC death rate*
After years of
Change in mortality due
0%
0%
0%
0%
0%
0%
screening
to screening:
Change in mortality
unrelated to screening:
BC death rate*
Dr
p*phi*Dr
1-[(1-p)*Dr]
Corrected RR ‡
0%
0%
0%
86
142
100
0.61
1.42
0.65
1.00
-25%
-25%
-25%
65
107
75
0.61
1.07
0.48
0.73
0.66
RR: relative risk.
* Per 100,000 women-year
† (rate in participants*0.75)+(rate in non-participants * 0.25)
‡ After Duffy et al, 2002.
Table 2 - Summary of main incidence-based mortality studies on breast cancer screening.
Study
Country
Areas in study
Comparison area where no
Age of screened
Effect of changes in
screening existed during the
women
treatments considered
entire study period
Effect of
Data on cancer
screening on risk Adjustment of results done for
management
of BC death
SelfIncidence Lead time
selection
Tabar et al,
2003[15]
SOSSEG, 2006
[16]
Helquist et al,
2010 [17]
Kalager et al,
2010 [18]
Sweden
Dalarna and
Kopparberg counties
40-69
No
No
No
-45%
Yes
Yes
No
Sweden
About half of Swedish
counties
40(50)-69(74)
No
Yes, but only in non
participants
No
-27%
Yes
Yes
No
Sweden
All Swedish counties
40-49
Yes
Yes (control areas)
No
-26%
Yes
No
Yes
Norway
4 counties with pilot
programme
50-69
Yes
Yes (control areas)
No
-10% (NS)
No
No
No
19
20
21