SlideShare a Scribd company logo
1 of 7
Download to read offline
ABSTRACT
Using national cancer registration data for female breast cancer
incidence in eight European countries—England & Wales,
Scotland, Northern Ireland, the Irish Republic, Sweden, the Czech
Republic, Finland, and Denmark—for which there is also
comprehensive data on abortion incidence, trends are examined
and future trends predicted. Seven reproductive risk factors are
considered as possible explanatory variables. Induced abortion is
found to be the best predictor, and fertility is also a useful predictor.
Forecasts are made using a linear regression model with these
explanatory variables. Previous forecasts using the same model
and incidence data for years through 1997 for England & Wales are
compared with numbers of cancers observed in years from
1998–2004 in an Appendix. The forecast predicted 100.5% of the
cancers observed in 2003, and 97.5% of those observed in 2004.
TheChallengeofAbortion forEpidemiologists
inFemaleBreastCancerResearch
Trends
It is difficult for epidemiologists to discover women’s abortion
history. In any study the numbers of women who have had abortions
maybeunderreported.
National data on abortions in most countries tends to be
deficient, with abortions underreported. Official abortion statistics
in the United States and France are known to understate the
numbers of legal induced abortions.The countries considered in this
studyarebelieved tohavenearlycompleteofficialabortioncounts.
The long lag time for the development of breast cancer
magnifies the problem. The average age of diagnosis is over 60,
while most abortions and live births occur at ages under 30. The
modern increase in breast cancer incidence is obvious at ages over
45, and Figure 1 for England & Wales shows the increase is small
belowage45.
Abortion did not become legal in most Western countries until
the 1970s, and earlier abortions among older women are not
recorded. Consequently, the older women, whose breast cancer
incidence is known, have abortions not detectable by a longitudinal
study, while the younger women, whose abortion history is
known, tend to be too young to have experienced most of the
modern increase in breast cancer. Where the increased risk is
apparent, even under age 40 in a study free of recall bias, there is
anacknowledgedneedtoextendthestudytowomenolderthan40.
The long time lags, however, can be used to make long-term
forecastsofcancertrends.
Since 1971 the overall increase has been 80%, as shown for
England&WalesinFigure1.
1
2 3
4
1,5,6
1,5,7-11
12
4
In contrast to other cancers, breast cancer is more common in
upper-class women. This reverse gradient is becoming steeper:
see Figure 2. The reported standardized mortality ratio (SMR) in
England for the highest social class I increased to 174 for the years
1997–2000, compared to an SMR of 169 for the years 1993–1996.
As upper-class women have higher survival rates, the incidence
gradient is steeper than the mortality gradient. Fertility differences
do little to explain this gradient. However, the age at first birth
among women who have children does provide a two-fold partial
explanation. The least deprived women studied in a British survey
were found to have a greater preference for abortion when
pregnant. Higher-class women have a later age at first birth and
consequently higher-class women have nulliparous abortions,
whicharemorecarcinogenic.
Local variation within countries can be examined in addition to
international comparisons. The South East of England has more
breast cancer than other parts of the British Isles. It also has the
highest abortion rate. Ireland has the lowest rate of breast cancer
13
14
15
16
17
0
50
100
150
200
250
300
350
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Year
Rateper100,000women
40-44 45-49 50-54 55-59
0
20
40
60
80
100
120
140
160
180
200
I II IIIN IIIM IV V
Social Class
Social Class I is the highest profesional. Social Class IIIN is Skilled Non-Manual and IIIM is Skilled Manual.
ProprotionalMortalityRatio
2001-2004 Forecast
1997-2000
1993-1996
Patrick S. Carroll, M.A.
The Breast Cancer Epidemic:
Modeling and Forecasts Based on Abortion
and Other Risk Factors
Figure 1. Average Yearly Rate of Incidence of Female Breast Cancer in
England & Wales within Age Groups 40-44, 45-49, 50-54 and 55-59 from
1971-2004
Figure 2. Female Breast Cancer Mortality by Social Class: Proportional
mortality ratios show increased reverse gradient across social class of
women in England & Wales.
Journal of American Physicians and Surgeons Volume 12 Number 3 Fall 200772
0.00
0.05
0.10
0.15
0.20
0.25
0.30
1923 1928 1933 1938 1943 1948 1953 1958 1963 1968
Year of Birth
CumulatedCohortAbortionRate
0.000
0.002
0.004
0.006
0.008
0.010
0.012
0.014
0.016
CumulatedCohortBreastCancerRate
Nulliparous Abortion Rate
Parous Abortion Rate
Breast Cancer Rate
0.00
0.05
0.10
0.15
0.20
0.25
0.30
1926
1927
1928
1929
1930
1931
1932
1933
1934
1935
1936
1937
1938
1939
1940
1941
1942
1943
1944
1945
1946
1947
1948
1949
1950
Year of Birth
CohortAbortion
0.000
0.002
0.004
0.006
0.008
0.010
0.012
0.014
0.016
CohortBreastCancer
Abortion Rate per w oman
Breast Cancer Rate per w oman
Correlation Coefficient: 0.98
and the lowest abortion rate. Fertility, higher in Ireland than in
England, is also a factor. But in the South East of England fertility is
not lower than the English average and does not explain the above-
averagebreastcancerrate.
Seven known risk factors were examined as an explanation for
thesetrends:
When a woman is nulliparous, an induced abortion has a greater
carcinogenic effect because it leaves breast cells in a state of
interrupted hormonal development in which they are more
susceptible.
Alowageatfirstbirthisprotective.
Childlessnessincreasestherisk.
A larger number of children (higher fertility) increases
protection.
Breastfeedinggivesadditionalprotection.
Hormonalcontraceptivesareconducivetobreastcancer.
Hormone replacement therapy (HRT) is also conducive to
breastcancer.
For four of these risk factors we are fortunate to have useful
English national data.The total fertility rates (TFRs) and completed
cohort fertility rates are as published by the Office for National
Statistics (ONS), and the total abortion rates (TARs) and cohort
abortionratesarederivedbytheauthorfromofficialdata.
Figure 3 shows cumulated cohort abortion rates for successive
birth cohorts of women born since 1926 in England & Wales,
together with cumulated cohort breast cancer rates for women aged
50–54. The correlation coefficient is high (>0.9), and it is useful to
includethisvariableasanexplanatoryvariableinmodeling.
Figure 4 shows the rates decomposed into parous and
nulliparous cohort rates. The increasing proportion of nulliparous
abortions affecting the women now entering age groups where they
are likely to have breast cancer is apparent. This trend is a driver of
thefurtherincreasesinbreastcancerincidencenow observed.
Figure 5 shows average number of children, representing the
cumulated cohort fertility rate for successive birth cohorts of
English women compared with their breast cancer rate for cancer in
women aged 50–54. The correlation coefficient is -0.57, so this
variableisalsousefultoincludeinmodeling.
Figure 6 shows mean age at first birth in England & Wales for
successive birth cohorts. If the correlation were positive it could
helptoexplainthetrend,butitisnegative.
Figure 7 shows cohort childlessness. The correlation in the
graph is negative, and this variable is not used in the model to
explaintheBritishtrend.
Two explanatory variables are selected for modeling:
(abortion) and (fertility). The trends for abortion and fertility are
shown inFigures8and9forcountriesconsidered.
TheMathematicalModelisthen:
where represents cumulated cohort incidence of breast cancer
within a particular age group; is intercept, and are
coefficients,and israndomerror.
Risk Factors
ModelingforEngland &Wales
18
19
20
15
17
x
x
Y
a b b
e
1
2
1 2
Y = a + b x + b x + ei i i i1 1 2 2
1.80
1.90
2.00
2.10
2.20
2.30
2.40
2.50
1926
1927
1928
1929
1930
1931
1932
1933
1934
1935
1936
1937
1938
1939
1940
1941
1942
1943
1944
1945
1946
1947
1948
1949
1950
Year of Birth
CohortFertility
0.000
0.002
0.004
0.006
0.008
0.010
0.012
0.014
0.016
CohortBrestCancer
Fertility Rate per w oman
Breast Cancer Rate per w oman
Correlation Coefficient: -0.57
Figure 3. Cohort Breast Cancer Incidence within Ages 50-54 vs. Cumulated
Cohort Abortion Rate for Women in England & Wales: Cohorts are defined
by year of birth.
Figure 4. Cumulated Cohort Rates of Abortion (Parous and Nulliparous)
and Cumulated Cohort Rate of Breast Cancer within Ages 50-54 for Women
in England & Wales
Figure 5. Cohort Breast Cancer Incidence within Ages 50-54 vs.
Cumulated Cohort Fertility for Women in England & Wales: Cohorts are
defined by year of birth.
22.5
23.0
23.5
24.0
24.5
25.0
1926 1928 1930 1932 1934 1936 1938 1940 1942 1944 1946 1948 1950 1952 1954
Year of Birth
MeanAgeatFirstBirth
0.000
0.001
0.002
0.003
0.004
0.005
0.006
0.007
0.008
0.009
0.010
CohortBreastCancerRate
Mean Age at First Birth
Breast Cancer Cohort
Correlation Coefficient: -0.56
Figure 6. Cohort Mean Age at First Birth vs Cumulated Breast
Cancer within Age Group 45-49 for
Cohort
Women in England & Wales
Journal of American Physicians and Surgeons Volume 12 Number 3 Fall 2007 73
This model has desirable mathematical properties such as
dimensional homogeneity, linearity, additivity, and parsimonious
parameterization.
The model makes sense in terms of the factors not explicitly
included. Higher fertility is associated with a lower age at first birth
and less childlessness. Breastfeeding is strongly linked to fertility.
Likewise lower fertility is associated with more use of hormonal
contraceptives. Abortion can lead to prescription of hormonal
contraceptives, and the mental health sequelae of abortion may lead
touseofhormonereplacementtherapy.
The model was fitted to English female cohorts born in the years
up to 1950 for cancer in women aged 50–54. The multiple was
0.951. The estimated coefficient of abortion ( ) is 0.0166 (95% CI,
.0065-.0396), and the coefficient of fertility ( ) is −0.0047 (95%
CI, −.0135-.0041). The coefficient of fertility is rather small, with
the 95% confidence interval straddling zero. Some improvement in
breastfeeding may be offsetting fertility decline. These results are
summarized inTable1.
Forecasts are made using the model with the latest TFRs and
TARs to estimate cumulated cohort rates of fertility and abortion
for 25 years in the future. Here the recent rates for England & Wales
in 2006 ofTFR 1.86 andTAR 0.55 are used. Fitting this model gives
an overall increase in the rate of cancer of 50.9%, which
corresponds to a yearly compound increase of 1.7%.Assuming the
breast cancer incidence rates for ages below 45 are constant, for
ages 45–49 follow the trend as modeled for this age group, and for
ages over 50 follow the trend as modeled for ages 50–54, we can
estimate future breast cancer incidence rates for 25 future years
with 2004 as base year for prediction. The numbers of new cancers
to be expected in these years is then estimated using the
Government Actuary’s population projections by applying the
forecast incidence rates to the expected numbers of women in the
relevantagegroups ineachyear.
The numbers of newly diagnosed cancers forecast by this model
are expected to increase to 65,252 in 2025, compared to the
reported number 39,229 in 2004 (a 66.3% increase). These are
shown withforecastsforintermediateyearsinTable2.
The 1997-based forecasts using this model published in 2002
have anticipated quite well the reported increases in female breast
cancerinEngland&Walesin1998to2004[AppendixA].
Cases of ductal carcinoma in situ (DCIS), which also requires
treatment, are registered separately and are also forecast. DCIS is
shown on mammography, and the number of cases has increased in
the age groups targeted by screening. In 2004 there were 39,229
breast cancers and 3,827 cases of DCIS registered in England &
Wales. The number of future cases is forecast by assuming that the
ratio of cancers to DCIS stays constant in the main age groups
affected.Theincreasednumbersforecastareshown inTable2.
These forecast numbers can be used to plan treatment facilities
forwomendiagnosedwithcancer.
In Scotland the incidence gradient (Figure 10) is less than the
gradient in England (Figure 2), and the mortality gradient is almost
R
b
b
1
2
ForecastingforEngland &Wales
ModelingApplied totheSocialGradient
21
4
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
1.80
1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
TotalAbortionRate
England & Wales Scotland Northern Ireland Republic of Ireland Sw eden
Czech Republic Finland Denmark 0.5 Level 0.25 Level
0
2
4
6
8
10
12
14
16
18
1926 1928 1930 1932 1934 1936 1938 1940 1942 1944 1946 1948 1950 1952 1954
Year of Birth
CohortChildlessness%
0.000
0.001
0.002
0.003
0.004
0.005
0.006
0.007
0.008
0.009
0.010
CohortBreastCancerRate
Cohort Childlessness
Cohort Breast Cancer Rate
Correlation Coefficient: -0.01
Country
No of
Years
Used
Goodness of Fit
Multiple R
Intercept (a)
Coefficient of
Abortion (b1)
(95% CI)
Coefficient of
Fertility (b2)
(95% CI)
Increase
Forecast
England & Wales 15 0.951 .0202
.0166
(.0065, .0396)
–.0047
(–.0135, .0041)
50.9%
Scotland * 28 0.603 .0093
.0040
(–.0047, .0127)
–.00053
(–.0029, .0018)
17.2%
Northern Ireland * 8 0.998 .0082
.0107
(.0074, .0140)
–.00020
(–.0006, .0002)
9.3%
Irish Republic * 8 0.997 .0083
.0099
(.0018, .0182)
–.00029
(–.0013, –0007)
8.3%
Sweden 6 0.998 .0097
.0128
(.0059, .0197)
–.00023
(–.0027, .0022)
31.3%
Czech Republic 9 0.859 .021
.0083
(.0014, .0151)
–.0094
(–.0423, .0236)
53%
Finland 16 0.630 .0058
.0298
(–.0092, .0687)
–.0014
(–.0101, .0072)
–6.8%
Denmark 8 0.991 .0065
.0155
(.00046, 0.0305)
–.00024
(–.003, 0.0026)
–4.1%
Table 1. Model Fitting by Country: Regression Intercept and Coefficients,
and Increase in Breast Cancer Incidence Forecast to Occur in 25Years
†
Table 2. Summary: Forecast Cases of Breast Cancer and DCIS
England & Wales
Scotland
Northern Ireland
Republic of Ireland
Sweden
Czech Republic
Finland
Denmark
39229
3917
1117
2336
7293
5449
3794
3952
40018
3963
1137
2336
7777
5596
3824
4043
45529
4482
1256
2560
8519
6200
3931
4175
51849
5058
1382
2883
9288
6804
4005
4325
58567
5639
1508
3222
10096
7561
4024
4452
65252
6177
1626
3601
10895
8412
4045
4533
3827
333
87
163
950
248
-
-
3848
345
87
163
981
258
-
-
4373
392
99
178
1077
278
-
-
5074
450
111
200
1177
300
-
-
5765
502
119
223
1281
334
-
-
6319
537
122
248
1384
372
-
-
Base Year Base Year2005 20052010 20102015 20152020 20202025 2025
In Situ CancersCancers
* 45-49 modeling used
25 years after latest year for which breast cancer incidence is available (2005 for Republic of Ireland;
2004 for England & Wales, Scotland, Northern Ireland, and Sweden; 2003 for Czech Republic and
Finland; 2001 for Denmark).
Linear Regression. Response variable: cumulated cohort breast cancer incidence for women aged 50–54
or 45–49. Explanatory variables: cumulated cohort abortion rates and cumulated cohort fertility rates.
†
Figure 7. Cumulated Cohort Breast Cancer Rates within Ages 45-49 vs.
Cohort Childlessness Percentage for England & Wales
Figure 8. Total Abortion Rates: TARs in England & Wales, Scotland,
Northern Ireland, Republic of Ireland, Sweden, Czech Republic, Finland,
and Denmark; 1968-2006
Journal of American Physicians and Surgeons Volume 12 Number 3 Fall 200774
flat. These differences could result in part from the fact that the
abortion rate has been lower in Scotland than in England since 1968
(Figure 8). Currently, the abortion rate is about 50% higher in
England than in Scotland. However, over the same period, there has
beenagreaterdeclineinfertilityinScotland(Figure9).
Five social classes for Scotland are distinguished according to
deprivation, whereas in England there are six social classes
distinguished by occupation. The Scottish ratios of mortality to
incidence for the social classes were used to derive an approximate
gradient of incidence for England. The modeling for England for
the age groups 45–49 and 50–54 described in the last section was
used to estimate a further increase in incidence of breast cancer in
England of 14.4% in the period 2001–2004, compared to
1997–2000. This was spread across the six social classes in
England in proportion to the existing gradient, and an increased
gradient of incidence across social class for England for the years
2001–2004 was determined. Using the Scottish ratios, this was then
converted into the increased breast cancer mortality gradient for
England&Walesshown inFigure2.
Cancer registrations in Scotland started in 1960. Rates have
been higher than in England, but recently the increase over all ages
in Scottish breast cancer rates has been less than in England
(Figures 11 and 12). Figure 8 shows the lower Scottish abortion
rates. Figure 9 shows the greater decline in Scottish birth rates. The
trend in cohort breast cancer in ages 50–54 up to 2004 proved non-
linear and difficult to fit the model. The model was fitted for
Scotlandforages45–49withresultsshown inTable1.
Forecasts were made using the latest 2006 TAR for Scotland,
0.376, and the latestTFR, 1.67, giving an overall increase in the rate
of cancer of 17.2%, or a yearly increase of 0.64%. Numbers of new
cancers expected in Scotland are 6,177 in 2025 compared to the
3,917 reported for 2004, which is a 57.7% increase, in line with the
agingofthepopulation.
The lower abortion rates in Scotland lead to a forecast of a
lesser further increase in incidence of breast cancer in Scotland
compared to England, partly offset by lower fertility now in
Scotland. Breastfeeding rates have been very low in Scotland,
and this has reduced the protective effects of higher Scottish
fertility in the past. With encouragement in recent years, the
increase in breastfeeding has apparently offset the effects of the
declinein theScottish birth rate.
Data is limited, as cancer registration started in 1993. The
incidence trends for the age groups 45–49 and 50–54 are shown in
Figures 11 and 12. Abortions in England on women resident in
Northern Ireland as reported in English abortion statistics are used
to derive abortion rates for Northern Ireland. The trends in abortion
and fertility in Northern Ireland are shown in Figures 8 and 9.
Abortion rates in Ireland, where abortion is illegal, are much lower
than in Great Britain. By smoothing the graph of cohort cancer
incidence for Northern Ireland it was possible to fit the model and
makeestimates.
With this model fitted on the available years of data to 2004 for
the age range 45–49, and the latest abortion and fertility rates
22
22
23
Modelingand ForecastingforScotland
NorthernIreland
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
TotalFertilityRate
England & Wales Scotland Northern Ireland
Republic of Ireland Sw eden Czech Republic
Denmark Replacement Level 2.07 Finland
0
20
40
60
80
100
1 2 3 4 5
%survival
0
25
50
75
100
125
Least
deprived
Most
deprived
Deprivation quintile
Incidence
Survival
Mortality
0
50
100
150
200
250
300
1943 1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003
Year
Rateper100,000women
England and Wales Scotland Northern Ireland Republic of Ireland
Sw eden Czech Republic Finland Denmark
0
50
100
150
200
250
300
350
1943 1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003
Year
Rateper100,000women
England and Wales Scotland Northern Ireland Republic of Ireland
Sw eden Czech Republic Finland Denmark
Figure 9. Total Fertility Rates: TFR in England & Wales, Scotland, Northern
Ireland, Republic of Ireland, Sweden, , Finland, and
Denmark; 1968-2006
Czech Republic
Figure 10. Cancer of the Female Breast, Scotland: Incidence, mortality and
cause-specific survival at 5 years by deprivation quintile, for patients
diagnosed 1991-95. ISD publicationSource: Trends in Cancer Survival in
Scotland 1971-1995
Figure 11. Breast Cancer in Women within Ages 45-49 in England & Wales,
Scotland, Northern Ireland, Republic of Ireland, Sweden, Czech Republic,
Finland, and Denmark; 1943-2005
Figure 12. Breast Cancer in Women within Ages 50-54 in England & Wales,
Scotland, Northern Ireland, Republic of Ireland, Sweden, Czech Republic,
Finland, and Denmark; 1943-2005
Journal of American Physicians and Surgeons Volume 12 Number 3 Fall 2007 75
entered, the 2006TAR for Northern Ireland is 0.16, the latestTFR is
1.87, and the forecast increase in the rate of cancer is 9.3% (yearly
increase0.36%).
This forecasts an increase in new cancers in Northern Ireland to
1,626 in 2025 compared to the 1,117 reported for 2004, which is a
46% increase, largely due to aging of the population. This small
increase follows from the very low abortion rate and comparatively
highfertilityinNorthernIreland.
Data is limited, as cancer registration started in 1994. The
incidence trends for the age groups 45–49 and 50–54 are shown in
Figures 11 and 12. Data on women resident in the Republic in
English abortion statistics are used to derive Irish abortion rates.
The trends in abortion and fertility in the Republic of Ireland are
shown in Figures 8 and 9. Abortion rates in the Republic are low,
andIrishfertilityratesarehighcomparedwithEngland.
Modeling used the latest available cancer data up to 2005 fitted
for cohort incidence within ages 45–49. Forecasting used the TAR
of 0.18 for 2006 and TFR of 1.86, giving a forecast increase in the
rate of cancer of 8.3%, which corresponds to a yearly compound
increase of 0.32%. This predicts an increase in numbers of new
cancers in the Republic of Ireland to around 3,601 in 2025,
compared to the 2,336 reported for 2005. The 54% increase is
largely a consequence of the expected growth and aging of the Irish
population.
In Sweden cancer registration started in 1958. The incidence
trends for the age groups 45–49 and 50–54 are shown in Figures
11and 12. The trends in abortion and fertility in Sweden are shown
in Figures 8 and 9. The nonlinear trend in fertility makes modeling
difficult.The abortion rates in Sweden are higher than in England at
the adult ages, but in Sweden most abortions are parous.
Breastfeeding is also successfully promoted in Sweden, offsetting
thecarcinogeniceffectofahighabortionrate.
Modeling is possible using recent years data. Forecasting with
the latest TAR for Sweden of 0.65 and the latest TFR of 1.75
produces an overall increase in the rate of cancer of 31.3%, which
corresponds to a yearly compound increase of 1.12%. From this
model, new cancers in Sweden are expected to be 10,895 in 2025,
comparedtothe7,293reportedfor2005,a49%increase.
In the Czech Republic cancer registration started in 1977. The
incidence trends are shown in Figures 11 and 12. Czech rates of
breast cancer are low by comparison with other countries
considered. Perhaps there is less genetic susceptibility.The trends in
abortion and fertility in the Czech Republic are shown in Figures 8
and 9. Abortion rates in the Czech Republic were high, and most
abortions areparous. Dataforrecentyears was usedtofitthemodel.
Forecasts using the latest TAR for the Czech Republic of 0.35
and the latest TFR of 1.23 gave an overall increase in the rate of
cancer of 39.2%, or a yearly increase of 1.33%. The Czech abortion
rate has declined markedly, but the Czech birth rate has declined
even more remarkably in recent years. These are offsetting factors
Republic ofIreland
Sweden
CzechRepublic
24
for breast cancer.The model predicts 8,412 new malignancies in the
Czech Republic in 2025 compared to the 5,449 reported for 2003, a
54%increase.
In Finland cancer registration started in 1953 and data is
available for years since 1977. The incidence trends are shown in
Figures 11 and 12. The trends in abortion and fertility in Finland are
shown in Figures 8 and 9. By using data for recent years it was
possibletofitthemodel.
The latest available TAR for Finland is 0.34 and the latest TFR
is 1.7. In the modeling these gave an expected decrease in the rate of
cancer of 6.8%, i.e. a yearly compound decrease of 0.28%,
reflecting the decline in the Finnish abortion rate and some
recovery in the birth rate in Finland. The forecast increase to 4,045
breast cancers in 2025, compared to the 3,794 reported for 2003,
resultsfromtheagingofthepopulation.
Anegative social gradient in Finland is reported in a large study.
“Cancers of the breast were most common in high social classes
throughout the whole observation period 1971–1995. The relative
difference between the SIRs (Standardised Incidence Ratios) of
social classes I and IV diminished from 2-fold in the period
1971–1975 to 1.5-fold in 1991–1995. SIRs were 1.67 in social class
I and 0.81 in social class IV in 1971–1975 and 1.4 and 0.81
respectivelyin1991–1995.”
The social gradient was not explicable in terms of fertility. “In
Finland there is relatively little difference between social classes in
the age at first birth and average number of children.” Abortion
was not considered as an explanatory variable in this study. If it had
been considered, the gradient might have been better understood.
The lessening of the social gradient may be linked to a decline in the
Finnishabortionrate.
In Denmark cancer registration goes back to the 1940s but data
after 2001 is not available. The trend is similar to other countries
discussed above (Figures 11 and 12). Abortion rates declined after
1989 (Figure 8) and are less than in Sweden and England. Fertility
shows adeclinesimilartothatinSweden(Figure9).
Cohort fertility for years of birth before 1945 and abortion rates
before 1973 were estimated. Age-specific fertility rates were not
available for earlier years, and approximate estimates were made.
Trend lines proved nonlinear, and model fitting was difficult.
Modeling used a fixed intercept and recent data with results
summarized in Table 1. The latest TAR (0.45) and TFR (1.8) gave
an expected decrease in the rate of cancer of 4.1%, i.e. a yearly
compound decrease of 0.16%. This decline reflects the decline in
theDanishabortionrate.
A social gradient has also been found in Denmark. A large
Danish national study found a higher incidence of breast cancer in
the higher social classes. Academics (persons with higher
education) had the highest risk of breast cancer, which was 74%
above that of women in agriculture, who had the lowest risk. The
records were adequate to control for various risk factors, and the
study concluded that “the large social differences in fertility history
among Danish women could not explain the social differences in
breast cancer risk.” In particular, “[a]ge at first birth and parity
Finland
Denmark
25
25
26,27
27
26
Journal of American Physicians and Surgeons Volume 12 Number 3 Fall 200776
could not explain the effect of socioeconomic group on breast
cancer incidence and mortality.” Abortion was not considered as a
relevant factor. If it had been considered the gradient might have
beenexplained.
In most countries considered, women now over age 45 have had
more abortions and fewer children than previous generations of
women, and a further increase in breast cancer incidence is to be
expected. Variations in breast cancer incidence across social class
andacrossgeographicregionscanalsobeexpectedtoincrease.
In England, a high rate of abortion leads to the large forecast
increase. In Scotland, the lower abortion rate, offset by lower
fertility than in England, leads to a slightly lower rate of increase
expected. In both Irish jurisdictions, a continuation of low abortion
rates and comparatively high fertility rates lead to low forecast
increases in incidence of breast cancer. In Sweden a high abortion
rate is offset partly by fewer nulliparous abortions and a high level
offertilityandbreastfeeding.
In the Czech Republic, the forecast of an increase in breast
cancer incidence is largely the result of the fallen birth rate. In
Finland and Denmark, lower abortion rates imply less breast cancer
inthefuture.
The negative or reverse social gradient whereby upper class
women have more breast cancer is apparent in four countries where
it is measured: England & Wales, Scotland, , and Denmark.
In all of these countries the known reproductive factors other than
abortion fail to explain the gradient. But the known likelihood for
upper class and upwardly mobile women to prefer abortions when
pregnant could provide some explanation of this gradient. If
abortions had been examined in the studies of this social gradient,
theroleofthisfactorcouldhavebeenmadeclear.
The increase in breast cancer incidence appears to be best
explained by an increase in abortion rates, especially nulliparous
abortions, and lower fertility. And the social gradient, which is not
explained by fertility, seems also attributable circumstantially to
abortion. A linear regression model of successive birth cohorts of
women with abortion and fertility as explanatory variables fitted to the
cancer incidence up to 1977 has produced forecasts that have
performed well in the years 1998–2004 in Great Britain (AppendixA).
Thenew forecasts foreightcountries canbetestedinthecoming years.
27
Summary
Conclusion
Finland
Patrick S. Carroll, M.A.,
Acknowledgements:
Potential conflicts of interest:
is Director of Research, Pension and Population
Research Institute (PAPRI), 35 Canonbury Road, London N1 2DG, UK.
Contact: papriresearch@btconnect.com.
Particular thanks are due to the charities LIFE and The
Medical Education Trust, which funded the research, to the national statistical
offices and cancer registries, which provided the data, and to the statisticians
who kindly gave advice. Figure 10 is reproduced from the publication
with permission of the Cancer
Surveillance Team, Information Services Division (ISD), NHS National
Services, Scotland. Computing was done by Andrew Chan and Lee Young.
none disclosed.
Trends
in Cancer Survival in Scotland 1971-1995
REFERENCES
1
Goldacre MJ, Kurina LM, Seagroat V, et al. A case control record
linkage study. 2001:55:336-337.J Epidemiol Community Health
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
18
19
20
21
22
23
26
27
28
29
Finer LB, Henshaw SK. Estimates of U.S. abortion incidence in 2001
and 2002. Alan Guttmacher Institute (AGI); 2005.
Blayo C. L’evolution du recourse a l’avortement en France depuis
1976. Institut National des Etudes Demographiques
(INED); 1995:779-810.
Cancer Incidence Data, Office for National Statistics and Welsh
Cancer Incidence and Surveillance Unit (WCISU). Available at:
www.statistics.gov.uk and www.wcisu.wales.nhs.uk. Accessed Jul
31, 2007.
Melbye M, Wohlfahrt J, Olsen JH, et al. Induced abortion and the risk
of breast cancer. 1997:336.81-85.
Brewster DH, Stockton DL, Dobbie R, et al. Risk of breast cancer after
miscarriage or induced abortion: a Scottish record linkage case
control study. 2005;59:283-287.
Lindefors Harris BM, Eklund G, et al. Risk of cancer of the breast after
legal abortion during first trimester: a Swedish register study.
1989:299:1430-1322.
Brind J. Induced abortion as an independent risk factor for breast
cancer. 2005;10:105-110.
Beral V, Bull D, Doll R, Peto R, Reeves G. Breast cancer and abortion:
collaborative reanalysis of data from 53 epidemiological studies.
2004;363:1007-1016.
Erlandsson G, Montgomery SM, Cnattingius S, Ekborn A. Abortions
and breast cancer: record based control study.
2003;103:676-679.
Schwerdlow A, dos Santos Silva I, Doll R.
. Oxford
University Press; 2001.
Howe H, Senie R T, Bzduch H, Herzfeld P. Early abortion and breast
cancer risk among women under age 40.
1989;18:300-304.
White C, van Galen F, Chow YH. Trends in social class differences in
mortality by cause, 1986-2000.
2003(winter):25-37. Available at: http://www.statistics.gov.uk/
statbase/Product.asp?vlnk=6725&More=N. Accessed Jul 31, 2007.
Lee E, Clements S, Ingham R, et al. York, UK:
Joseph Rowntree Foundation; 2004. Available at: http://www.
jrf.org.uk/. Accessed Jul 31, 2007.
Birth Statistics. Office for National Statistics (ONS) (UK).
London, UK: ONS; 2005.
Abortion Statistics . ONS 1968–2001. Department of
Health 2002–2006.
Russo J, Rivera R, Russo IH. Influence of age and parity on the
development of the human breast.
1992:23:211-218.
Leon D. A prospective study of the independent effects of parity and
age at first birth on breast cancer incidence in England & Wales.
1989:43:986-991.
Ramazzini B. London, UK; 1751:152.
Carroll P. Pregnancy related risk factors in female breast cancer
incidence. 2002;4:331-375.
Information and Statistics Division of the National Health Service in
Scotland. Edinburgh, Scotland; 1960–2004.
White A, Freeth S, O’Brian M. London, UK: Office
for Population Censuses and Surveys (OPCS); 1992.
Stockholm, Sweden: Socialstyrelsen; 2000.
Pukkala E. Time trends in socio-economic differences in incidence
rates of cancers of the breast and female genital organs.
1999;81:56-61.
Dano H, Andersen O, Ewertz M, et al. Socio-economic status and
breast cancer in Denmark. 2003: 32: 216-226.
Dano H, Hansen KD, Jensen P, et. al. Fertility pattern does not explain
social gradient in breast cancer in Denmark.
2004:111:451-456.
Carroll P. Trends and reproductive risk factors in female breast cancer
incidence in Great Britain. 2004;91(Suppl 1):S24, Poster 2.
Carroll P. Trends and risk factors in British female breast cancer.
Joint Statistical Meetings (JSM), American
Statistical Association, Minneapolis, Minn.; 2005:2511-2519.
Population No. 3.
N Engl J Med
J Epidemiol Community Health
BMJ
J Am Phys Surg
Lancet
Int J Cancer
Cancer Incidence and
Mortality in England & Wales. Trends and Risk Factors
Int J Epidemiol
Health Statistics Quarterly No. 20;
A Matter of Choice.
Cancer Atlas of the United Kingdom and Ireland.
Breast Cancer Res Treat
Int J
Cancer
Of the Diseases of Artificers.
Int Congress of Actuaries, Transactions
Infant Feeding 1990.
Anning av barn foedda. [Breastfeeding of Infants Born in 1998].
Int J Cancer
Int J Epidemiol
Int J Cancer
Br J Cancer
Statistics in Epidemiology.
17
24
25
England & Wales
Statistical Bulletin;
Journal of American Physicians and Surgeons Volume 12 Number 3 Fall 2007 77
AppendixA. Female Breast Cancers and Ductal Carcinoma in Situ (DCIS) in
England &Wales: Comparison of Forecast Numbers Published in 2002 with
ReportedIncidenceintheYears 1998–2004
Modelling based on breast cancer incidence data up to 1997 was used
to forecast incidence over future years through 2027. Forecast rates were
applied to the projected female population in the 1998-based forecast made
bytheUK GovernmentActuarytocalculateforecastnumbersofcancers.
In these 1997-based forecasts, the same rate of increase in incidence
wasassumedtoapplytoallagegroups.
Two forecasts were made: (1) Using model fitting without weighting to
allow for additionally carcinogenic effect of nulliparous abortions gave a
lower increase in rates of 44.4% over 30 years, or 1.25% per annum. (2)
With weighting to allow for the additionally carcinogenic effects of
nulliparous abortions, the model gave a higher increase of 2.2% per annum
or92% over30years.
21
Tables 1A-3A show the observed cases from official counts of new
cases and the expected numbers calculated with the unweighted model, for
cancers, ductal carcinoma in situ (DCIS), and cancers combined with
DCIS, respectively. The forecast tended to underestimate slightly the
number of cancers; the ratio of observed to expected was 1.013 (101.3%) in
2004. For DCIS, the underestimate, O/E = 1.54 (154.3%) for 2004, was
much more notable, probably owing to extension of screening programs.
The combined rate of cancers and DCIS was somewhat underestimated,
O/E=1.04 (104.4%) in2004.
Weighting for the increased carcinogenicity of nulliparous abortions
gave the results shown in Tables 4A-6A for cancers, DCIS, and cancers
combined with DCIS, respectively. Cancers were slightly overestimated,
O/E = 0.946 (94.6%) for 2004. DCIS was underestimated, but less so than
with the first model: O/E = 1.44 (144%) in 2004. The combined forecast
proved quite good, with 100.5% of the total new malignancies anticipated
in2003, and97.5% in2004.
Year 15-44 45-49 50-54 55-59 60+ All ages
% Observed/
Expected
1998
1999
2000
2001
2002
2003
2004
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Age Groups
3880
4005
4022
4153
4183
4151
4375
4161
4527
4101
4666
4214
4802
4312
3220
3099
3241
3088
3275
3042
3365
2950
3487
2993
3619
3066
3771
3268
4725
4633
4909
5031
5051
4951
5172
4957
5039
4514
5021
4554
5081
4439
3621
3880
3805
4198
4005
4138
4284
4477
4761
4819
5079
5396
5292
5136
19042
19029
19450
19791
19872
19544
20374
19846
20836
20293
21402
21575
21981
21557
34488
34646
35427
36261
36386
35826
37570
36391
38650
36720
39787
38805
40927
38712
100.5
102.4
98.5
96.9
95.0
97.5
94.6
Year 15-44 45-49 50-54 55-59 60+ All ages
% Observed/
Expected
1998
1999
2000
2001
2002
2003
2004
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Age Groups
193
136
200
255
208
279
218
264
225
290
232
278
239
315
321
231
323
272
327
243
336
272
348
261
361
249
376
275
471
674
490
765
504
804
516
832
503
813
501
817
507
827
375
454
394
488
414
544
443
622
493
675
526
789
547
612
746
917
765
1006
784
1163
800
1163
819
1230
847
1530
881
1644
2106
2412
2172
2786
2237
3033
2313
3153
2388
3269
2467
3663
2550
3673
114.5
128.3
135.6
136.3
136.9
148.5
144.0
Year 15-44 45-49 50-54 55-59 60+ All ages
% Observed/
Expected
1998
1999
2000
2001
2002
2003
2004
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Age Groups
4073
4141
4222
4408
4391
4430
4593
4425
4752
4391
4898
4492
5041
4627
3541
3330
3564
3360
3602
3285
3701
3222
3835
3254
3980
3315
4147
3543
5196
5307
5399
5796
5555
5755
5688
5789
5542
5327
5522
5371
5588
5266
3996
4334
4199
4686
4419
4682
4727
5099
5254
5494
5605
6185
5839
5748
19788
19946
20215
20797
20656
20707
21174
21009
21655
21523
22249
23105
22862
23201
36594
37058
37599
39047
38623
38859
39883
39544
41038
39989
42254
42468
43477
42385
101.3
103.9
100.6
99.2
97.4
100.5
97.5
Year 15-44 45-49 50-54 55-59 60+ All ages
% Observed/
Expected
1998
1999
2000
2001
2002
2003
2004
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Age Groups
4033
4141
4140
4408
4264
4430
4415
4425
4524
4391
4558
4492
4705
4627
3507
3330
3494
3360
3497
3285
3559
3222
3650
3254
3752
3315
3871
3543
5145
5307
5294
5796
5393
5755
5468
5789
5275
5327
5205
5371
5216
5266
3956
4334
4117
4686
4290
4682
4545
5099
5002
5494
5284
6185
5451
5748
19595
19946
20453
20797
20055
20707
20357
21009
20616
21523
20975
23105
21365
23201
36236
37058
37498
39047
37499
38859
38344
39544
39067
39989
39774
42468
40608
42385
102.3
104.1
103.6
103.1
102.4
106.8
104.4
Year 15-44 45-49 50-54 55-59 60+ All ages
% Observed/
Expected
1998
1999
2000
2001
2002
2003
2004
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Age Groups
191
136
196
255
202
279
209
264
214
290
219
278
223
315
318
231
317
272
317
243
323
272
331
261
340
249
351
275
467
674
480
765
489
804
496
832
478
813
472
817
473
827
371
454
386
488
402
544
426
622
469
675
496
789
511
612
739
917
751
1006
761
1163
769
1163
780
1230
799
1530
822
1644
2086
2412
2130
2786
2171
3033
2223
3153
2272
3269
2326
3663
2380
3673
115.6
130.8
139.7
141.8
143.9
157.5
154.3
Year 15-44 45-49 50-54 55-59 60+ All ages
% Observed/
Expected
1998
1999
2000
2001
2002
2003
2004
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
Expected
Observed
3842
4005
3944
4153
4062
4151
4206
4161
4310
4101
4339
4214
4482
4312
3189
3099
3177
3088
3180
3042
3236
2950
3319
2993
3412
3066
3520
3268
4678
4633
4814
5031
4904
4951
4972
4957
4797
4514
4733
4554
4743
4439
3585
3880
3731
4198
3888
4138
4119
4477
4533
4819
4788
5396
4940
5136
18856
19029
19702
19791
19294
19544
19588
19846
19836
20293
20176
21575
20543
21557
34150
34646
35368
36261
35328
35826
36121
36391
36795
36720
37448
38805
38228
38712
101.5
102.5
101.4
100.7
99.8
103.6
101.3
Age Groups
Table 6A. Combined Cases of Female Breast Cancer and DCIS in England &
Wales, Observed v. Predicted from Model Weighted for NulliparousAbortion
Table 5A. Number of Cases of Female DCIS in England & Wales, Observed
v. Predicted from Model Weighted for NulliparousAbortion
Table 4A. Number of Female Breast Cancers in England & Wales, Observed
v. Predicted from Model Weighted for NulliparousAbortions
Table 3A. Combined Cases of Female Breast Cancer and DCIS in England
& Wales, Observed v. Predicted from Unweighted Model
Table 2A. Number of Cases of Female DCIS in England & Wales, Observed
v. Predicted from Unweighted Model
Table 1A. Number of Female Breast Cancers in England & Wales, Observed
v. Predicted from Unweighted Model
Forecast based on incidence of breast cancer up to 1997
Journal of American Physicians and Surgeons Volume 12 Number 3 Fall 200778

More Related Content

What's hot

Maternal Mortality
Maternal MortalityMaternal Mortality
Maternal Mortalitylimgengyan
 
Aging and infertility in women
Aging and infertility in womenAging and infertility in women
Aging and infertility in womenTüp Bebek Danış
 
Maternal mortality in India
Maternal mortality in IndiaMaternal mortality in India
Maternal mortality in IndiaAayupta Mohanty
 
Indicators_demographic & fertility_practical class
Indicators_demographic & fertility_practical classIndicators_demographic & fertility_practical class
Indicators_demographic & fertility_practical classTanveerRehman4
 
Measures of fertility
Measures of fertility Measures of fertility
Measures of fertility Tauseef Jawaid
 
Maternal Mortality
Maternal MortalityMaternal Mortality
Maternal Mortalityrdlj
 
Infant Mortality Rate in India -Millennium Development Goal
Infant Mortality Rate in India -Millennium Development GoalInfant Mortality Rate in India -Millennium Development Goal
Infant Mortality Rate in India -Millennium Development GoalVijay Kumar Modi
 
Applications for Measuring Maternal Mortality: Three Case Studies Using Verba...
Applications for Measuring Maternal Mortality: Three Case Studies Using Verba...Applications for Measuring Maternal Mortality: Three Case Studies Using Verba...
Applications for Measuring Maternal Mortality: Three Case Studies Using Verba...MEASURE Evaluation
 
Women’s sexual and reproductive health – increasing the evidence base
Women’s sexual and reproductive health – increasing the evidence baseWomen’s sexual and reproductive health – increasing the evidence base
Women’s sexual and reproductive health – increasing the evidence baseIDS
 
Trends in Maternal Mortality: 1990 - 2013
Trends in Maternal Mortality: 1990 - 2013Trends in Maternal Mortality: 1990 - 2013
Trends in Maternal Mortality: 1990 - 2013UNICEF Publications
 
Saving Mothers and Babies: Introduction to maternal and perinatal mortality
Saving Mothers and Babies: Introduction to maternal and perinatal mortalitySaving Mothers and Babies: Introduction to maternal and perinatal mortality
Saving Mothers and Babies: Introduction to maternal and perinatal mortalitySaide OER Africa
 
Early Detection of Breast Cancer: Awareness and Practice of Self Breast Exami...
Early Detection of Breast Cancer: Awareness and Practice of Self Breast Exami...Early Detection of Breast Cancer: Awareness and Practice of Self Breast Exami...
Early Detection of Breast Cancer: Awareness and Practice of Self Breast Exami...iosrjce
 
Increasing rates of prenatal testing among Jewish and Arab women in Israel ov...
Increasing rates of prenatal testing among Jewish and Arab women in Israel ov...Increasing rates of prenatal testing among Jewish and Arab women in Israel ov...
Increasing rates of prenatal testing among Jewish and Arab women in Israel ov...Jenny Ostrovsky
 
Infant mortality rate
Infant mortality rateInfant mortality rate
Infant mortality rateshivujagga
 
HIV/AIDS Epidemic
HIV/AIDS EpidemicHIV/AIDS Epidemic
HIV/AIDS Epidemicrdlj
 
Femaleinfertility 130404172604-phpapp01-converted
Femaleinfertility 130404172604-phpapp01-convertedFemaleinfertility 130404172604-phpapp01-converted
Femaleinfertility 130404172604-phpapp01-convertedZoibaRiaz
 
Indications and Outcomes of Emergency Caesarean Section at St Paul’s Hospital...
Indications and Outcomes of Emergency Caesarean Section at St Paul’s Hospital...Indications and Outcomes of Emergency Caesarean Section at St Paul’s Hospital...
Indications and Outcomes of Emergency Caesarean Section at St Paul’s Hospital...Crimsonpublishers-IGRWH
 

What's hot (20)

Maternal Mortality
Maternal MortalityMaternal Mortality
Maternal Mortality
 
Aging and infertility in women
Aging and infertility in womenAging and infertility in women
Aging and infertility in women
 
Maternal mortality in India
Maternal mortality in IndiaMaternal mortality in India
Maternal mortality in India
 
Indicators_demographic & fertility_practical class
Indicators_demographic & fertility_practical classIndicators_demographic & fertility_practical class
Indicators_demographic & fertility_practical class
 
Measures of fertility
Measures of fertility Measures of fertility
Measures of fertility
 
Maternal Mortality
Maternal MortalityMaternal Mortality
Maternal Mortality
 
Infant Mortality Rate in India -Millennium Development Goal
Infant Mortality Rate in India -Millennium Development GoalInfant Mortality Rate in India -Millennium Development Goal
Infant Mortality Rate in India -Millennium Development Goal
 
Infant mortality rate
Infant mortality rateInfant mortality rate
Infant mortality rate
 
Applications for Measuring Maternal Mortality: Three Case Studies Using Verba...
Applications for Measuring Maternal Mortality: Three Case Studies Using Verba...Applications for Measuring Maternal Mortality: Three Case Studies Using Verba...
Applications for Measuring Maternal Mortality: Three Case Studies Using Verba...
 
Women’s sexual and reproductive health – increasing the evidence base
Women’s sexual and reproductive health – increasing the evidence baseWomen’s sexual and reproductive health – increasing the evidence base
Women’s sexual and reproductive health – increasing the evidence base
 
Trends in Maternal Mortality: 1990 - 2013
Trends in Maternal Mortality: 1990 - 2013Trends in Maternal Mortality: 1990 - 2013
Trends in Maternal Mortality: 1990 - 2013
 
Saving Mothers and Babies: Introduction to maternal and perinatal mortality
Saving Mothers and Babies: Introduction to maternal and perinatal mortalitySaving Mothers and Babies: Introduction to maternal and perinatal mortality
Saving Mothers and Babies: Introduction to maternal and perinatal mortality
 
Early Detection of Breast Cancer: Awareness and Practice of Self Breast Exami...
Early Detection of Breast Cancer: Awareness and Practice of Self Breast Exami...Early Detection of Breast Cancer: Awareness and Practice of Self Breast Exami...
Early Detection of Breast Cancer: Awareness and Practice of Self Breast Exami...
 
Increasing rates of prenatal testing among Jewish and Arab women in Israel ov...
Increasing rates of prenatal testing among Jewish and Arab women in Israel ov...Increasing rates of prenatal testing among Jewish and Arab women in Israel ov...
Increasing rates of prenatal testing among Jewish and Arab women in Israel ov...
 
Infant mortality rate
Infant mortality rateInfant mortality rate
Infant mortality rate
 
HIV/AIDS Epidemic
HIV/AIDS EpidemicHIV/AIDS Epidemic
HIV/AIDS Epidemic
 
Maternal Mortality 2018
Maternal Mortality 2018Maternal Mortality 2018
Maternal Mortality 2018
 
Near miss
Near missNear miss
Near miss
 
Femaleinfertility 130404172604-phpapp01-converted
Femaleinfertility 130404172604-phpapp01-convertedFemaleinfertility 130404172604-phpapp01-converted
Femaleinfertility 130404172604-phpapp01-converted
 
Indications and Outcomes of Emergency Caesarean Section at St Paul’s Hospital...
Indications and Outcomes of Emergency Caesarean Section at St Paul’s Hospital...Indications and Outcomes of Emergency Caesarean Section at St Paul’s Hospital...
Indications and Outcomes of Emergency Caesarean Section at St Paul’s Hospital...
 

Similar to The Breast Cancer Epidemic: Modeling and Forecasts Based on Abortion and Other Risk Factors

Breast cancer epidemiology
Breast cancer epidemiology Breast cancer epidemiology
Breast cancer epidemiology D.A.B.M
 
Epidemiology of breast cancer 2014 ap
Epidemiology of breast cancer 2014 apEpidemiology of breast cancer 2014 ap
Epidemiology of breast cancer 2014 apletymbou
 
Dr Ayman Ewies - Cervical screening 2009
Dr Ayman Ewies - Cervical screening 2009Dr Ayman Ewies - Cervical screening 2009
Dr Ayman Ewies - Cervical screening 2009AymanEwies
 
Epidemiology of cancer
Epidemiology of cancer Epidemiology of cancer
Epidemiology of cancer suhas k r
 
Risk Factors of Breast Cancer
Risk Factors of Breast CancerRisk Factors of Breast Cancer
Risk Factors of Breast CancerSaeed Al-Shomimi
 
The incidence of significant lesions on cervical poster
The incidence of significant lesions on cervical   posterThe incidence of significant lesions on cervical   poster
The incidence of significant lesions on cervical posterGenevieve Warner Learmonth
 
The incidence of significant lesions on cervical smears in women under thirty...
The incidence of significant lesions on cervical smears in women under thirty...The incidence of significant lesions on cervical smears in women under thirty...
The incidence of significant lesions on cervical smears in women under thirty...Genevieve Warner Learmonth
 
The incidence of significant lesions on cervical poster
The incidence of significant lesions on cervical   posterThe incidence of significant lesions on cervical   poster
The incidence of significant lesions on cervical posterGenevieve Warner Learmonth
 
Marc Espié : Variations in breast cancer incidence and mortality
Marc Espié :  Variations in breast cancer incidence and mortalityMarc Espié :  Variations in breast cancer incidence and mortality
Marc Espié : Variations in breast cancer incidence and mortalitybreastcancerupdatecongress
 
[TMMC Healthcare] Breast cancer screening
[TMMC Healthcare] Breast cancer screening[TMMC Healthcare] Breast cancer screening
[TMMC Healthcare] Breast cancer screeningTmmc Healthcare
 
Knowledge, Attitude and Practice toward Cervical Cancer and Cervical Cancer S...
Knowledge, Attitude and Practice toward Cervical Cancer and Cervical Cancer S...Knowledge, Attitude and Practice toward Cervical Cancer and Cervical Cancer S...
Knowledge, Attitude and Practice toward Cervical Cancer and Cervical Cancer S...ijtsrd
 
Linking Breast Cancer & our Environment
Linking Breast Cancer & our Environment Linking Breast Cancer & our Environment
Linking Breast Cancer & our Environment v2zq
 
Breast ca riskk & prognostic factors the lect
Breast ca riskk & prognostic factors the lectBreast ca riskk & prognostic factors the lect
Breast ca riskk & prognostic factors the lectHamedRashad1
 

Similar to The Breast Cancer Epidemic: Modeling and Forecasts Based on Abortion and Other Risk Factors (20)

Breast cancer epidemiology
Breast cancer epidemiology Breast cancer epidemiology
Breast cancer epidemiology
 
Epidemiology of breast cancer 2014 ap
Epidemiology of breast cancer 2014 apEpidemiology of breast cancer 2014 ap
Epidemiology of breast cancer 2014 ap
 
No Title
No TitleNo Title
No Title
 
Ectopic pregnancy 2
Ectopic pregnancy 2Ectopic pregnancy 2
Ectopic pregnancy 2
 
Dr Ayman Ewies - Cervical screening 2009
Dr Ayman Ewies - Cervical screening 2009Dr Ayman Ewies - Cervical screening 2009
Dr Ayman Ewies - Cervical screening 2009
 
Epidemiology of cancer
Epidemiology of cancer Epidemiology of cancer
Epidemiology of cancer
 
Risk Factors of Breast Cancer
Risk Factors of Breast CancerRisk Factors of Breast Cancer
Risk Factors of Breast Cancer
 
Cancers
CancersCancers
Cancers
 
The incidence of significant lesions on cervical poster
The incidence of significant lesions on cervical   posterThe incidence of significant lesions on cervical   poster
The incidence of significant lesions on cervical poster
 
Cancer Epidemiology part II
Cancer Epidemiology part IICancer Epidemiology part II
Cancer Epidemiology part II
 
The incidence of significant lesions on cervical smears in women under thirty...
The incidence of significant lesions on cervical smears in women under thirty...The incidence of significant lesions on cervical smears in women under thirty...
The incidence of significant lesions on cervical smears in women under thirty...
 
The incidence of significant lesions on cervical poster
The incidence of significant lesions on cervical   posterThe incidence of significant lesions on cervical   poster
The incidence of significant lesions on cervical poster
 
POST-PN-0527
POST-PN-0527POST-PN-0527
POST-PN-0527
 
Marc Espié : Variations in breast cancer incidence and mortality
Marc Espié :  Variations in breast cancer incidence and mortalityMarc Espié :  Variations in breast cancer incidence and mortality
Marc Espié : Variations in breast cancer incidence and mortality
 
[TMMC Healthcare] Breast cancer screening
[TMMC Healthcare] Breast cancer screening[TMMC Healthcare] Breast cancer screening
[TMMC Healthcare] Breast cancer screening
 
Breast Cancer Screening Presentation - PiPP
Breast Cancer Screening Presentation - PiPPBreast Cancer Screening Presentation - PiPP
Breast Cancer Screening Presentation - PiPP
 
Prof Richard Peto on Breast Cancer Screening
Prof Richard Peto on Breast Cancer ScreeningProf Richard Peto on Breast Cancer Screening
Prof Richard Peto on Breast Cancer Screening
 
Knowledge, Attitude and Practice toward Cervical Cancer and Cervical Cancer S...
Knowledge, Attitude and Practice toward Cervical Cancer and Cervical Cancer S...Knowledge, Attitude and Practice toward Cervical Cancer and Cervical Cancer S...
Knowledge, Attitude and Practice toward Cervical Cancer and Cervical Cancer S...
 
Linking Breast Cancer & our Environment
Linking Breast Cancer & our Environment Linking Breast Cancer & our Environment
Linking Breast Cancer & our Environment
 
Breast ca riskk & prognostic factors the lect
Breast ca riskk & prognostic factors the lectBreast ca riskk & prognostic factors the lect
Breast ca riskk & prognostic factors the lect
 

More from Mario Guillermo Simonovich

Precios de automóviles 0 km y usados en Argentina
Precios de automóviles 0 km y usados en ArgentinaPrecios de automóviles 0 km y usados en Argentina
Precios de automóviles 0 km y usados en ArgentinaMario Guillermo Simonovich
 
Legisladores mendocinos piden que no se legalice el aborto en Argentina
Legisladores mendocinos piden que no se legalice el aborto en ArgentinaLegisladores mendocinos piden que no se legalice el aborto en Argentina
Legisladores mendocinos piden que no se legalice el aborto en ArgentinaMario Guillermo Simonovich
 
Obras sociales beneficiadas - Resolución 1345
Obras sociales beneficiadas - Resolución 1345Obras sociales beneficiadas - Resolución 1345
Obras sociales beneficiadas - Resolución 1345Mario Guillermo Simonovich
 
Resolución 344/2020 del Ministerio de Seguridad
 Resolución 344/2020 del Ministerio de Seguridad  Resolución 344/2020 del Ministerio de Seguridad
Resolución 344/2020 del Ministerio de Seguridad Mario Guillermo Simonovich
 
Gobierno otorga $1.300 millones a 202 obras sociales para cancelar pagos a pr...
Gobierno otorga $1.300 millones a 202 obras sociales para cancelar pagos a pr...Gobierno otorga $1.300 millones a 202 obras sociales para cancelar pagos a pr...
Gobierno otorga $1.300 millones a 202 obras sociales para cancelar pagos a pr...Mario Guillermo Simonovich
 
Procedimiento para la revisión de concursos de personal y de nombramientos en...
Procedimiento para la revisión de concursos de personal y de nombramientos en...Procedimiento para la revisión de concursos de personal y de nombramientos en...
Procedimiento para la revisión de concursos de personal y de nombramientos en...Mario Guillermo Simonovich
 
El manejo del cianuro en la extraccion del oro
El manejo del cianuro en la extraccion del oroEl manejo del cianuro en la extraccion del oro
El manejo del cianuro en la extraccion del oroMario Guillermo Simonovich
 

More from Mario Guillermo Simonovich (20)

Precandidatos Elecciones P.A.S.O. Mendoza
Precandidatos Elecciones P.A.S.O. MendozaPrecandidatos Elecciones P.A.S.O. Mendoza
Precandidatos Elecciones P.A.S.O. Mendoza
 
PASO 2021 - Escrutinio definitivo en Mendoza
PASO 2021  - Escrutinio definitivo en MendozaPASO 2021  - Escrutinio definitivo en Mendoza
PASO 2021 - Escrutinio definitivo en Mendoza
 
Lista de precios de automóviles - Marzo 2021
Lista de precios de automóviles - Marzo 2021Lista de precios de automóviles - Marzo 2021
Lista de precios de automóviles - Marzo 2021
 
Precios de automóviles 0 km y usados en Argentina
Precios de automóviles 0 km y usados en ArgentinaPrecios de automóviles 0 km y usados en Argentina
Precios de automóviles 0 km y usados en Argentina
 
Precios Cuidados 2021
Precios Cuidados 2021 Precios Cuidados 2021
Precios Cuidados 2021
 
Precios Cuidados 2021
Precios Cuidados 2021Precios Cuidados 2021
Precios Cuidados 2021
 
Lista de precios de automóviles - Enero 2021
Lista de precios de automóviles - Enero 2021Lista de precios de automóviles - Enero 2021
Lista de precios de automóviles - Enero 2021
 
Legisladores mendocinos piden que no se legalice el aborto en Argentina
Legisladores mendocinos piden que no se legalice el aborto en ArgentinaLegisladores mendocinos piden que no se legalice el aborto en Argentina
Legisladores mendocinos piden que no se legalice el aborto en Argentina
 
Anexo Resolución 1360 - Boletín Oficial
Anexo Resolución 1360 - Boletín OficialAnexo Resolución 1360 - Boletín Oficial
Anexo Resolución 1360 - Boletín Oficial
 
Obras sociales beneficiadas - Resolución 1345
Obras sociales beneficiadas - Resolución 1345Obras sociales beneficiadas - Resolución 1345
Obras sociales beneficiadas - Resolución 1345
 
Inflacion interanual desde 2017
Inflacion interanual desde 2017Inflacion interanual desde 2017
Inflacion interanual desde 2017
 
Anexo 6121047 2
Anexo 6121047 2 Anexo 6121047 2
Anexo 6121047 2
 
Resolución 344/2020 del Ministerio de Seguridad
 Resolución 344/2020 del Ministerio de Seguridad  Resolución 344/2020 del Ministerio de Seguridad
Resolución 344/2020 del Ministerio de Seguridad
 
Salarios de militares en Argentina
Salarios de militares en ArgentinaSalarios de militares en Argentina
Salarios de militares en Argentina
 
Gobierno otorga $1.300 millones a 202 obras sociales para cancelar pagos a pr...
Gobierno otorga $1.300 millones a 202 obras sociales para cancelar pagos a pr...Gobierno otorga $1.300 millones a 202 obras sociales para cancelar pagos a pr...
Gobierno otorga $1.300 millones a 202 obras sociales para cancelar pagos a pr...
 
Poder, ganancias y pandemia
Poder, ganancias y pandemiaPoder, ganancias y pandemia
Poder, ganancias y pandemia
 
Inhabilidad del 17 al 31 de marzo.pdf
Inhabilidad del 17 al 31 de marzo.pdfInhabilidad del 17 al 31 de marzo.pdf
Inhabilidad del 17 al 31 de marzo.pdf
 
Los chicos del campamento
Los chicos del campamento Los chicos del campamento
Los chicos del campamento
 
Procedimiento para la revisión de concursos de personal y de nombramientos en...
Procedimiento para la revisión de concursos de personal y de nombramientos en...Procedimiento para la revisión de concursos de personal y de nombramientos en...
Procedimiento para la revisión de concursos de personal y de nombramientos en...
 
El manejo del cianuro en la extraccion del oro
El manejo del cianuro en la extraccion del oroEl manejo del cianuro en la extraccion del oro
El manejo del cianuro en la extraccion del oro
 

Recently uploaded

The Most Attractive Hyderabad Call Girls Kothapet 𖠋 6297143586 𖠋 Will You Mis...
The Most Attractive Hyderabad Call Girls Kothapet 𖠋 6297143586 𖠋 Will You Mis...The Most Attractive Hyderabad Call Girls Kothapet 𖠋 6297143586 𖠋 Will You Mis...
The Most Attractive Hyderabad Call Girls Kothapet 𖠋 6297143586 𖠋 Will You Mis...chandars293
 
Lucknow Call girls - 8800925952 - 24x7 service with hotel room
Lucknow Call girls - 8800925952 - 24x7 service with hotel roomLucknow Call girls - 8800925952 - 24x7 service with hotel room
Lucknow Call girls - 8800925952 - 24x7 service with hotel roomdiscovermytutordmt
 
Russian Call Girls in Jaipur Riya WhatsApp ❤8445551418 VIP Call Girls Jaipur
Russian Call Girls in Jaipur Riya WhatsApp ❤8445551418 VIP Call Girls JaipurRussian Call Girls in Jaipur Riya WhatsApp ❤8445551418 VIP Call Girls Jaipur
Russian Call Girls in Jaipur Riya WhatsApp ❤8445551418 VIP Call Girls Jaipurparulsinha
 
Call Girls Kochi Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Kochi Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Kochi Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Kochi Just Call 9907093804 Top Class Call Girl Service AvailableDipal Arora
 
Call Girls Dehradun Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Dehradun Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Dehradun Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Dehradun Just Call 9907093804 Top Class Call Girl Service AvailableDipal Arora
 
Top Rated Hyderabad Call Girls Erragadda ⟟ 6297143586 ⟟ Call Me For Genuine ...
Top Rated  Hyderabad Call Girls Erragadda ⟟ 6297143586 ⟟ Call Me For Genuine ...Top Rated  Hyderabad Call Girls Erragadda ⟟ 6297143586 ⟟ Call Me For Genuine ...
Top Rated Hyderabad Call Girls Erragadda ⟟ 6297143586 ⟟ Call Me For Genuine ...chandars293
 
Call Girls Service Surat Samaira ❤️🍑 8250192130 👄 Independent Escort Service ...
Call Girls Service Surat Samaira ❤️🍑 8250192130 👄 Independent Escort Service ...Call Girls Service Surat Samaira ❤️🍑 8250192130 👄 Independent Escort Service ...
Call Girls Service Surat Samaira ❤️🍑 8250192130 👄 Independent Escort Service ...CALL GIRLS
 
Call Girls Ooty Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Ooty Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Ooty Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Ooty Just Call 9907093804 Top Class Call Girl Service AvailableDipal Arora
 
All Time Service Available Call Girls Marine Drive 📳 9820252231 For 18+ VIP C...
All Time Service Available Call Girls Marine Drive 📳 9820252231 For 18+ VIP C...All Time Service Available Call Girls Marine Drive 📳 9820252231 For 18+ VIP C...
All Time Service Available Call Girls Marine Drive 📳 9820252231 For 18+ VIP C...Arohi Goyal
 
Call Girls Gwalior Just Call 8617370543 Top Class Call Girl Service Available
Call Girls Gwalior Just Call 8617370543 Top Class Call Girl Service AvailableCall Girls Gwalior Just Call 8617370543 Top Class Call Girl Service Available
Call Girls Gwalior Just Call 8617370543 Top Class Call Girl Service AvailableDipal Arora
 
Book Paid Powai Call Girls Mumbai 𖠋 9930245274 𖠋Low Budget Full Independent H...
Book Paid Powai Call Girls Mumbai 𖠋 9930245274 𖠋Low Budget Full Independent H...Book Paid Powai Call Girls Mumbai 𖠋 9930245274 𖠋Low Budget Full Independent H...
Book Paid Powai Call Girls Mumbai 𖠋 9930245274 𖠋Low Budget Full Independent H...Call Girls in Nagpur High Profile
 
Bangalore Call Girl Whatsapp Number 100% Complete Your Sexual Needs
Bangalore Call Girl Whatsapp Number 100% Complete Your Sexual NeedsBangalore Call Girl Whatsapp Number 100% Complete Your Sexual Needs
Bangalore Call Girl Whatsapp Number 100% Complete Your Sexual NeedsGfnyt
 
VIP Call Girls Indore Kirti 💚😋 9256729539 🚀 Indore Escorts
VIP Call Girls Indore Kirti 💚😋  9256729539 🚀 Indore EscortsVIP Call Girls Indore Kirti 💚😋  9256729539 🚀 Indore Escorts
VIP Call Girls Indore Kirti 💚😋 9256729539 🚀 Indore Escortsaditipandeya
 
Top Rated Bangalore Call Girls Mg Road ⟟ 8250192130 ⟟ Call Me For Genuine Sex...
Top Rated Bangalore Call Girls Mg Road ⟟ 8250192130 ⟟ Call Me For Genuine Sex...Top Rated Bangalore Call Girls Mg Road ⟟ 8250192130 ⟟ Call Me For Genuine Sex...
Top Rated Bangalore Call Girls Mg Road ⟟ 8250192130 ⟟ Call Me For Genuine Sex...narwatsonia7
 
Premium Call Girls Cottonpet Whatsapp 7001035870 Independent Escort Service
Premium Call Girls Cottonpet Whatsapp 7001035870 Independent Escort ServicePremium Call Girls Cottonpet Whatsapp 7001035870 Independent Escort Service
Premium Call Girls Cottonpet Whatsapp 7001035870 Independent Escort Servicevidya singh
 
Best Rate (Hyderabad) Call Girls Jahanuma ⟟ 8250192130 ⟟ High Class Call Girl...
Best Rate (Hyderabad) Call Girls Jahanuma ⟟ 8250192130 ⟟ High Class Call Girl...Best Rate (Hyderabad) Call Girls Jahanuma ⟟ 8250192130 ⟟ High Class Call Girl...
Best Rate (Hyderabad) Call Girls Jahanuma ⟟ 8250192130 ⟟ High Class Call Girl...astropune
 
Call Girls Cuttack Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Cuttack Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Cuttack Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Cuttack Just Call 9907093804 Top Class Call Girl Service AvailableDipal Arora
 
Chandrapur Call girls 8617370543 Provides all area service COD available
Chandrapur Call girls 8617370543 Provides all area service COD availableChandrapur Call girls 8617370543 Provides all area service COD available
Chandrapur Call girls 8617370543 Provides all area service COD availableDipal Arora
 
VIP Hyderabad Call Girls Bahadurpally 7877925207 ₹5000 To 25K With AC Room 💚😋
VIP Hyderabad Call Girls Bahadurpally 7877925207 ₹5000 To 25K With AC Room 💚😋VIP Hyderabad Call Girls Bahadurpally 7877925207 ₹5000 To 25K With AC Room 💚😋
VIP Hyderabad Call Girls Bahadurpally 7877925207 ₹5000 To 25K With AC Room 💚😋TANUJA PANDEY
 
VIP Service Call Girls Sindhi Colony 📳 7877925207 For 18+ VIP Call Girl At Th...
VIP Service Call Girls Sindhi Colony 📳 7877925207 For 18+ VIP Call Girl At Th...VIP Service Call Girls Sindhi Colony 📳 7877925207 For 18+ VIP Call Girl At Th...
VIP Service Call Girls Sindhi Colony 📳 7877925207 For 18+ VIP Call Girl At Th...jageshsingh5554
 

Recently uploaded (20)

The Most Attractive Hyderabad Call Girls Kothapet 𖠋 6297143586 𖠋 Will You Mis...
The Most Attractive Hyderabad Call Girls Kothapet 𖠋 6297143586 𖠋 Will You Mis...The Most Attractive Hyderabad Call Girls Kothapet 𖠋 6297143586 𖠋 Will You Mis...
The Most Attractive Hyderabad Call Girls Kothapet 𖠋 6297143586 𖠋 Will You Mis...
 
Lucknow Call girls - 8800925952 - 24x7 service with hotel room
Lucknow Call girls - 8800925952 - 24x7 service with hotel roomLucknow Call girls - 8800925952 - 24x7 service with hotel room
Lucknow Call girls - 8800925952 - 24x7 service with hotel room
 
Russian Call Girls in Jaipur Riya WhatsApp ❤8445551418 VIP Call Girls Jaipur
Russian Call Girls in Jaipur Riya WhatsApp ❤8445551418 VIP Call Girls JaipurRussian Call Girls in Jaipur Riya WhatsApp ❤8445551418 VIP Call Girls Jaipur
Russian Call Girls in Jaipur Riya WhatsApp ❤8445551418 VIP Call Girls Jaipur
 
Call Girls Kochi Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Kochi Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Kochi Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Kochi Just Call 9907093804 Top Class Call Girl Service Available
 
Call Girls Dehradun Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Dehradun Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Dehradun Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Dehradun Just Call 9907093804 Top Class Call Girl Service Available
 
Top Rated Hyderabad Call Girls Erragadda ⟟ 6297143586 ⟟ Call Me For Genuine ...
Top Rated  Hyderabad Call Girls Erragadda ⟟ 6297143586 ⟟ Call Me For Genuine ...Top Rated  Hyderabad Call Girls Erragadda ⟟ 6297143586 ⟟ Call Me For Genuine ...
Top Rated Hyderabad Call Girls Erragadda ⟟ 6297143586 ⟟ Call Me For Genuine ...
 
Call Girls Service Surat Samaira ❤️🍑 8250192130 👄 Independent Escort Service ...
Call Girls Service Surat Samaira ❤️🍑 8250192130 👄 Independent Escort Service ...Call Girls Service Surat Samaira ❤️🍑 8250192130 👄 Independent Escort Service ...
Call Girls Service Surat Samaira ❤️🍑 8250192130 👄 Independent Escort Service ...
 
Call Girls Ooty Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Ooty Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Ooty Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Ooty Just Call 9907093804 Top Class Call Girl Service Available
 
All Time Service Available Call Girls Marine Drive 📳 9820252231 For 18+ VIP C...
All Time Service Available Call Girls Marine Drive 📳 9820252231 For 18+ VIP C...All Time Service Available Call Girls Marine Drive 📳 9820252231 For 18+ VIP C...
All Time Service Available Call Girls Marine Drive 📳 9820252231 For 18+ VIP C...
 
Call Girls Gwalior Just Call 8617370543 Top Class Call Girl Service Available
Call Girls Gwalior Just Call 8617370543 Top Class Call Girl Service AvailableCall Girls Gwalior Just Call 8617370543 Top Class Call Girl Service Available
Call Girls Gwalior Just Call 8617370543 Top Class Call Girl Service Available
 
Book Paid Powai Call Girls Mumbai 𖠋 9930245274 𖠋Low Budget Full Independent H...
Book Paid Powai Call Girls Mumbai 𖠋 9930245274 𖠋Low Budget Full Independent H...Book Paid Powai Call Girls Mumbai 𖠋 9930245274 𖠋Low Budget Full Independent H...
Book Paid Powai Call Girls Mumbai 𖠋 9930245274 𖠋Low Budget Full Independent H...
 
Bangalore Call Girl Whatsapp Number 100% Complete Your Sexual Needs
Bangalore Call Girl Whatsapp Number 100% Complete Your Sexual NeedsBangalore Call Girl Whatsapp Number 100% Complete Your Sexual Needs
Bangalore Call Girl Whatsapp Number 100% Complete Your Sexual Needs
 
VIP Call Girls Indore Kirti 💚😋 9256729539 🚀 Indore Escorts
VIP Call Girls Indore Kirti 💚😋  9256729539 🚀 Indore EscortsVIP Call Girls Indore Kirti 💚😋  9256729539 🚀 Indore Escorts
VIP Call Girls Indore Kirti 💚😋 9256729539 🚀 Indore Escorts
 
Top Rated Bangalore Call Girls Mg Road ⟟ 8250192130 ⟟ Call Me For Genuine Sex...
Top Rated Bangalore Call Girls Mg Road ⟟ 8250192130 ⟟ Call Me For Genuine Sex...Top Rated Bangalore Call Girls Mg Road ⟟ 8250192130 ⟟ Call Me For Genuine Sex...
Top Rated Bangalore Call Girls Mg Road ⟟ 8250192130 ⟟ Call Me For Genuine Sex...
 
Premium Call Girls Cottonpet Whatsapp 7001035870 Independent Escort Service
Premium Call Girls Cottonpet Whatsapp 7001035870 Independent Escort ServicePremium Call Girls Cottonpet Whatsapp 7001035870 Independent Escort Service
Premium Call Girls Cottonpet Whatsapp 7001035870 Independent Escort Service
 
Best Rate (Hyderabad) Call Girls Jahanuma ⟟ 8250192130 ⟟ High Class Call Girl...
Best Rate (Hyderabad) Call Girls Jahanuma ⟟ 8250192130 ⟟ High Class Call Girl...Best Rate (Hyderabad) Call Girls Jahanuma ⟟ 8250192130 ⟟ High Class Call Girl...
Best Rate (Hyderabad) Call Girls Jahanuma ⟟ 8250192130 ⟟ High Class Call Girl...
 
Call Girls Cuttack Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Cuttack Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Cuttack Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Cuttack Just Call 9907093804 Top Class Call Girl Service Available
 
Chandrapur Call girls 8617370543 Provides all area service COD available
Chandrapur Call girls 8617370543 Provides all area service COD availableChandrapur Call girls 8617370543 Provides all area service COD available
Chandrapur Call girls 8617370543 Provides all area service COD available
 
VIP Hyderabad Call Girls Bahadurpally 7877925207 ₹5000 To 25K With AC Room 💚😋
VIP Hyderabad Call Girls Bahadurpally 7877925207 ₹5000 To 25K With AC Room 💚😋VIP Hyderabad Call Girls Bahadurpally 7877925207 ₹5000 To 25K With AC Room 💚😋
VIP Hyderabad Call Girls Bahadurpally 7877925207 ₹5000 To 25K With AC Room 💚😋
 
VIP Service Call Girls Sindhi Colony 📳 7877925207 For 18+ VIP Call Girl At Th...
VIP Service Call Girls Sindhi Colony 📳 7877925207 For 18+ VIP Call Girl At Th...VIP Service Call Girls Sindhi Colony 📳 7877925207 For 18+ VIP Call Girl At Th...
VIP Service Call Girls Sindhi Colony 📳 7877925207 For 18+ VIP Call Girl At Th...
 

The Breast Cancer Epidemic: Modeling and Forecasts Based on Abortion and Other Risk Factors

  • 1. ABSTRACT Using national cancer registration data for female breast cancer incidence in eight European countries—England & Wales, Scotland, Northern Ireland, the Irish Republic, Sweden, the Czech Republic, Finland, and Denmark—for which there is also comprehensive data on abortion incidence, trends are examined and future trends predicted. Seven reproductive risk factors are considered as possible explanatory variables. Induced abortion is found to be the best predictor, and fertility is also a useful predictor. Forecasts are made using a linear regression model with these explanatory variables. Previous forecasts using the same model and incidence data for years through 1997 for England & Wales are compared with numbers of cancers observed in years from 1998–2004 in an Appendix. The forecast predicted 100.5% of the cancers observed in 2003, and 97.5% of those observed in 2004. TheChallengeofAbortion forEpidemiologists inFemaleBreastCancerResearch Trends It is difficult for epidemiologists to discover women’s abortion history. In any study the numbers of women who have had abortions maybeunderreported. National data on abortions in most countries tends to be deficient, with abortions underreported. Official abortion statistics in the United States and France are known to understate the numbers of legal induced abortions.The countries considered in this studyarebelieved tohavenearlycompleteofficialabortioncounts. The long lag time for the development of breast cancer magnifies the problem. The average age of diagnosis is over 60, while most abortions and live births occur at ages under 30. The modern increase in breast cancer incidence is obvious at ages over 45, and Figure 1 for England & Wales shows the increase is small belowage45. Abortion did not become legal in most Western countries until the 1970s, and earlier abortions among older women are not recorded. Consequently, the older women, whose breast cancer incidence is known, have abortions not detectable by a longitudinal study, while the younger women, whose abortion history is known, tend to be too young to have experienced most of the modern increase in breast cancer. Where the increased risk is apparent, even under age 40 in a study free of recall bias, there is anacknowledgedneedtoextendthestudytowomenolderthan40. The long time lags, however, can be used to make long-term forecastsofcancertrends. Since 1971 the overall increase has been 80%, as shown for England&WalesinFigure1. 1 2 3 4 1,5,6 1,5,7-11 12 4 In contrast to other cancers, breast cancer is more common in upper-class women. This reverse gradient is becoming steeper: see Figure 2. The reported standardized mortality ratio (SMR) in England for the highest social class I increased to 174 for the years 1997–2000, compared to an SMR of 169 for the years 1993–1996. As upper-class women have higher survival rates, the incidence gradient is steeper than the mortality gradient. Fertility differences do little to explain this gradient. However, the age at first birth among women who have children does provide a two-fold partial explanation. The least deprived women studied in a British survey were found to have a greater preference for abortion when pregnant. Higher-class women have a later age at first birth and consequently higher-class women have nulliparous abortions, whicharemorecarcinogenic. Local variation within countries can be examined in addition to international comparisons. The South East of England has more breast cancer than other parts of the British Isles. It also has the highest abortion rate. Ireland has the lowest rate of breast cancer 13 14 15 16 17 0 50 100 150 200 250 300 350 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 Year Rateper100,000women 40-44 45-49 50-54 55-59 0 20 40 60 80 100 120 140 160 180 200 I II IIIN IIIM IV V Social Class Social Class I is the highest profesional. Social Class IIIN is Skilled Non-Manual and IIIM is Skilled Manual. ProprotionalMortalityRatio 2001-2004 Forecast 1997-2000 1993-1996 Patrick S. Carroll, M.A. The Breast Cancer Epidemic: Modeling and Forecasts Based on Abortion and Other Risk Factors Figure 1. Average Yearly Rate of Incidence of Female Breast Cancer in England & Wales within Age Groups 40-44, 45-49, 50-54 and 55-59 from 1971-2004 Figure 2. Female Breast Cancer Mortality by Social Class: Proportional mortality ratios show increased reverse gradient across social class of women in England & Wales. Journal of American Physicians and Surgeons Volume 12 Number 3 Fall 200772
  • 2. 0.00 0.05 0.10 0.15 0.20 0.25 0.30 1923 1928 1933 1938 1943 1948 1953 1958 1963 1968 Year of Birth CumulatedCohortAbortionRate 0.000 0.002 0.004 0.006 0.008 0.010 0.012 0.014 0.016 CumulatedCohortBreastCancerRate Nulliparous Abortion Rate Parous Abortion Rate Breast Cancer Rate 0.00 0.05 0.10 0.15 0.20 0.25 0.30 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 Year of Birth CohortAbortion 0.000 0.002 0.004 0.006 0.008 0.010 0.012 0.014 0.016 CohortBreastCancer Abortion Rate per w oman Breast Cancer Rate per w oman Correlation Coefficient: 0.98 and the lowest abortion rate. Fertility, higher in Ireland than in England, is also a factor. But in the South East of England fertility is not lower than the English average and does not explain the above- averagebreastcancerrate. Seven known risk factors were examined as an explanation for thesetrends: When a woman is nulliparous, an induced abortion has a greater carcinogenic effect because it leaves breast cells in a state of interrupted hormonal development in which they are more susceptible. Alowageatfirstbirthisprotective. Childlessnessincreasestherisk. A larger number of children (higher fertility) increases protection. Breastfeedinggivesadditionalprotection. Hormonalcontraceptivesareconducivetobreastcancer. Hormone replacement therapy (HRT) is also conducive to breastcancer. For four of these risk factors we are fortunate to have useful English national data.The total fertility rates (TFRs) and completed cohort fertility rates are as published by the Office for National Statistics (ONS), and the total abortion rates (TARs) and cohort abortionratesarederivedbytheauthorfromofficialdata. Figure 3 shows cumulated cohort abortion rates for successive birth cohorts of women born since 1926 in England & Wales, together with cumulated cohort breast cancer rates for women aged 50–54. The correlation coefficient is high (>0.9), and it is useful to includethisvariableasanexplanatoryvariableinmodeling. Figure 4 shows the rates decomposed into parous and nulliparous cohort rates. The increasing proportion of nulliparous abortions affecting the women now entering age groups where they are likely to have breast cancer is apparent. This trend is a driver of thefurtherincreasesinbreastcancerincidencenow observed. Figure 5 shows average number of children, representing the cumulated cohort fertility rate for successive birth cohorts of English women compared with their breast cancer rate for cancer in women aged 50–54. The correlation coefficient is -0.57, so this variableisalsousefultoincludeinmodeling. Figure 6 shows mean age at first birth in England & Wales for successive birth cohorts. If the correlation were positive it could helptoexplainthetrend,butitisnegative. Figure 7 shows cohort childlessness. The correlation in the graph is negative, and this variable is not used in the model to explaintheBritishtrend. Two explanatory variables are selected for modeling: (abortion) and (fertility). The trends for abortion and fertility are shown inFigures8and9forcountriesconsidered. TheMathematicalModelisthen: where represents cumulated cohort incidence of breast cancer within a particular age group; is intercept, and are coefficients,and israndomerror. Risk Factors ModelingforEngland &Wales 18 19 20 15 17 x x Y a b b e 1 2 1 2 Y = a + b x + b x + ei i i i1 1 2 2 1.80 1.90 2.00 2.10 2.20 2.30 2.40 2.50 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 Year of Birth CohortFertility 0.000 0.002 0.004 0.006 0.008 0.010 0.012 0.014 0.016 CohortBrestCancer Fertility Rate per w oman Breast Cancer Rate per w oman Correlation Coefficient: -0.57 Figure 3. Cohort Breast Cancer Incidence within Ages 50-54 vs. Cumulated Cohort Abortion Rate for Women in England & Wales: Cohorts are defined by year of birth. Figure 4. Cumulated Cohort Rates of Abortion (Parous and Nulliparous) and Cumulated Cohort Rate of Breast Cancer within Ages 50-54 for Women in England & Wales Figure 5. Cohort Breast Cancer Incidence within Ages 50-54 vs. Cumulated Cohort Fertility for Women in England & Wales: Cohorts are defined by year of birth. 22.5 23.0 23.5 24.0 24.5 25.0 1926 1928 1930 1932 1934 1936 1938 1940 1942 1944 1946 1948 1950 1952 1954 Year of Birth MeanAgeatFirstBirth 0.000 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008 0.009 0.010 CohortBreastCancerRate Mean Age at First Birth Breast Cancer Cohort Correlation Coefficient: -0.56 Figure 6. Cohort Mean Age at First Birth vs Cumulated Breast Cancer within Age Group 45-49 for Cohort Women in England & Wales Journal of American Physicians and Surgeons Volume 12 Number 3 Fall 2007 73
  • 3. This model has desirable mathematical properties such as dimensional homogeneity, linearity, additivity, and parsimonious parameterization. The model makes sense in terms of the factors not explicitly included. Higher fertility is associated with a lower age at first birth and less childlessness. Breastfeeding is strongly linked to fertility. Likewise lower fertility is associated with more use of hormonal contraceptives. Abortion can lead to prescription of hormonal contraceptives, and the mental health sequelae of abortion may lead touseofhormonereplacementtherapy. The model was fitted to English female cohorts born in the years up to 1950 for cancer in women aged 50–54. The multiple was 0.951. The estimated coefficient of abortion ( ) is 0.0166 (95% CI, .0065-.0396), and the coefficient of fertility ( ) is −0.0047 (95% CI, −.0135-.0041). The coefficient of fertility is rather small, with the 95% confidence interval straddling zero. Some improvement in breastfeeding may be offsetting fertility decline. These results are summarized inTable1. Forecasts are made using the model with the latest TFRs and TARs to estimate cumulated cohort rates of fertility and abortion for 25 years in the future. Here the recent rates for England & Wales in 2006 ofTFR 1.86 andTAR 0.55 are used. Fitting this model gives an overall increase in the rate of cancer of 50.9%, which corresponds to a yearly compound increase of 1.7%.Assuming the breast cancer incidence rates for ages below 45 are constant, for ages 45–49 follow the trend as modeled for this age group, and for ages over 50 follow the trend as modeled for ages 50–54, we can estimate future breast cancer incidence rates for 25 future years with 2004 as base year for prediction. The numbers of new cancers to be expected in these years is then estimated using the Government Actuary’s population projections by applying the forecast incidence rates to the expected numbers of women in the relevantagegroups ineachyear. The numbers of newly diagnosed cancers forecast by this model are expected to increase to 65,252 in 2025, compared to the reported number 39,229 in 2004 (a 66.3% increase). These are shown withforecastsforintermediateyearsinTable2. The 1997-based forecasts using this model published in 2002 have anticipated quite well the reported increases in female breast cancerinEngland&Walesin1998to2004[AppendixA]. Cases of ductal carcinoma in situ (DCIS), which also requires treatment, are registered separately and are also forecast. DCIS is shown on mammography, and the number of cases has increased in the age groups targeted by screening. In 2004 there were 39,229 breast cancers and 3,827 cases of DCIS registered in England & Wales. The number of future cases is forecast by assuming that the ratio of cancers to DCIS stays constant in the main age groups affected.Theincreasednumbersforecastareshown inTable2. These forecast numbers can be used to plan treatment facilities forwomendiagnosedwithcancer. In Scotland the incidence gradient (Figure 10) is less than the gradient in England (Figure 2), and the mortality gradient is almost R b b 1 2 ForecastingforEngland &Wales ModelingApplied totheSocialGradient 21 4 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 Year TotalAbortionRate England & Wales Scotland Northern Ireland Republic of Ireland Sw eden Czech Republic Finland Denmark 0.5 Level 0.25 Level 0 2 4 6 8 10 12 14 16 18 1926 1928 1930 1932 1934 1936 1938 1940 1942 1944 1946 1948 1950 1952 1954 Year of Birth CohortChildlessness% 0.000 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008 0.009 0.010 CohortBreastCancerRate Cohort Childlessness Cohort Breast Cancer Rate Correlation Coefficient: -0.01 Country No of Years Used Goodness of Fit Multiple R Intercept (a) Coefficient of Abortion (b1) (95% CI) Coefficient of Fertility (b2) (95% CI) Increase Forecast England & Wales 15 0.951 .0202 .0166 (.0065, .0396) –.0047 (–.0135, .0041) 50.9% Scotland * 28 0.603 .0093 .0040 (–.0047, .0127) –.00053 (–.0029, .0018) 17.2% Northern Ireland * 8 0.998 .0082 .0107 (.0074, .0140) –.00020 (–.0006, .0002) 9.3% Irish Republic * 8 0.997 .0083 .0099 (.0018, .0182) –.00029 (–.0013, –0007) 8.3% Sweden 6 0.998 .0097 .0128 (.0059, .0197) –.00023 (–.0027, .0022) 31.3% Czech Republic 9 0.859 .021 .0083 (.0014, .0151) –.0094 (–.0423, .0236) 53% Finland 16 0.630 .0058 .0298 (–.0092, .0687) –.0014 (–.0101, .0072) –6.8% Denmark 8 0.991 .0065 .0155 (.00046, 0.0305) –.00024 (–.003, 0.0026) –4.1% Table 1. Model Fitting by Country: Regression Intercept and Coefficients, and Increase in Breast Cancer Incidence Forecast to Occur in 25Years † Table 2. Summary: Forecast Cases of Breast Cancer and DCIS England & Wales Scotland Northern Ireland Republic of Ireland Sweden Czech Republic Finland Denmark 39229 3917 1117 2336 7293 5449 3794 3952 40018 3963 1137 2336 7777 5596 3824 4043 45529 4482 1256 2560 8519 6200 3931 4175 51849 5058 1382 2883 9288 6804 4005 4325 58567 5639 1508 3222 10096 7561 4024 4452 65252 6177 1626 3601 10895 8412 4045 4533 3827 333 87 163 950 248 - - 3848 345 87 163 981 258 - - 4373 392 99 178 1077 278 - - 5074 450 111 200 1177 300 - - 5765 502 119 223 1281 334 - - 6319 537 122 248 1384 372 - - Base Year Base Year2005 20052010 20102015 20152020 20202025 2025 In Situ CancersCancers * 45-49 modeling used 25 years after latest year for which breast cancer incidence is available (2005 for Republic of Ireland; 2004 for England & Wales, Scotland, Northern Ireland, and Sweden; 2003 for Czech Republic and Finland; 2001 for Denmark). Linear Regression. Response variable: cumulated cohort breast cancer incidence for women aged 50–54 or 45–49. Explanatory variables: cumulated cohort abortion rates and cumulated cohort fertility rates. † Figure 7. Cumulated Cohort Breast Cancer Rates within Ages 45-49 vs. Cohort Childlessness Percentage for England & Wales Figure 8. Total Abortion Rates: TARs in England & Wales, Scotland, Northern Ireland, Republic of Ireland, Sweden, Czech Republic, Finland, and Denmark; 1968-2006 Journal of American Physicians and Surgeons Volume 12 Number 3 Fall 200774
  • 4. flat. These differences could result in part from the fact that the abortion rate has been lower in Scotland than in England since 1968 (Figure 8). Currently, the abortion rate is about 50% higher in England than in Scotland. However, over the same period, there has beenagreaterdeclineinfertilityinScotland(Figure9). Five social classes for Scotland are distinguished according to deprivation, whereas in England there are six social classes distinguished by occupation. The Scottish ratios of mortality to incidence for the social classes were used to derive an approximate gradient of incidence for England. The modeling for England for the age groups 45–49 and 50–54 described in the last section was used to estimate a further increase in incidence of breast cancer in England of 14.4% in the period 2001–2004, compared to 1997–2000. This was spread across the six social classes in England in proportion to the existing gradient, and an increased gradient of incidence across social class for England for the years 2001–2004 was determined. Using the Scottish ratios, this was then converted into the increased breast cancer mortality gradient for England&Walesshown inFigure2. Cancer registrations in Scotland started in 1960. Rates have been higher than in England, but recently the increase over all ages in Scottish breast cancer rates has been less than in England (Figures 11 and 12). Figure 8 shows the lower Scottish abortion rates. Figure 9 shows the greater decline in Scottish birth rates. The trend in cohort breast cancer in ages 50–54 up to 2004 proved non- linear and difficult to fit the model. The model was fitted for Scotlandforages45–49withresultsshown inTable1. Forecasts were made using the latest 2006 TAR for Scotland, 0.376, and the latestTFR, 1.67, giving an overall increase in the rate of cancer of 17.2%, or a yearly increase of 0.64%. Numbers of new cancers expected in Scotland are 6,177 in 2025 compared to the 3,917 reported for 2004, which is a 57.7% increase, in line with the agingofthepopulation. The lower abortion rates in Scotland lead to a forecast of a lesser further increase in incidence of breast cancer in Scotland compared to England, partly offset by lower fertility now in Scotland. Breastfeeding rates have been very low in Scotland, and this has reduced the protective effects of higher Scottish fertility in the past. With encouragement in recent years, the increase in breastfeeding has apparently offset the effects of the declinein theScottish birth rate. Data is limited, as cancer registration started in 1993. The incidence trends for the age groups 45–49 and 50–54 are shown in Figures 11 and 12. Abortions in England on women resident in Northern Ireland as reported in English abortion statistics are used to derive abortion rates for Northern Ireland. The trends in abortion and fertility in Northern Ireland are shown in Figures 8 and 9. Abortion rates in Ireland, where abortion is illegal, are much lower than in Great Britain. By smoothing the graph of cohort cancer incidence for Northern Ireland it was possible to fit the model and makeestimates. With this model fitted on the available years of data to 2004 for the age range 45–49, and the latest abortion and fertility rates 22 22 23 Modelingand ForecastingforScotland NorthernIreland 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 Year TotalFertilityRate England & Wales Scotland Northern Ireland Republic of Ireland Sw eden Czech Republic Denmark Replacement Level 2.07 Finland 0 20 40 60 80 100 1 2 3 4 5 %survival 0 25 50 75 100 125 Least deprived Most deprived Deprivation quintile Incidence Survival Mortality 0 50 100 150 200 250 300 1943 1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003 Year Rateper100,000women England and Wales Scotland Northern Ireland Republic of Ireland Sw eden Czech Republic Finland Denmark 0 50 100 150 200 250 300 350 1943 1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003 Year Rateper100,000women England and Wales Scotland Northern Ireland Republic of Ireland Sw eden Czech Republic Finland Denmark Figure 9. Total Fertility Rates: TFR in England & Wales, Scotland, Northern Ireland, Republic of Ireland, Sweden, , Finland, and Denmark; 1968-2006 Czech Republic Figure 10. Cancer of the Female Breast, Scotland: Incidence, mortality and cause-specific survival at 5 years by deprivation quintile, for patients diagnosed 1991-95. ISD publicationSource: Trends in Cancer Survival in Scotland 1971-1995 Figure 11. Breast Cancer in Women within Ages 45-49 in England & Wales, Scotland, Northern Ireland, Republic of Ireland, Sweden, Czech Republic, Finland, and Denmark; 1943-2005 Figure 12. Breast Cancer in Women within Ages 50-54 in England & Wales, Scotland, Northern Ireland, Republic of Ireland, Sweden, Czech Republic, Finland, and Denmark; 1943-2005 Journal of American Physicians and Surgeons Volume 12 Number 3 Fall 2007 75
  • 5. entered, the 2006TAR for Northern Ireland is 0.16, the latestTFR is 1.87, and the forecast increase in the rate of cancer is 9.3% (yearly increase0.36%). This forecasts an increase in new cancers in Northern Ireland to 1,626 in 2025 compared to the 1,117 reported for 2004, which is a 46% increase, largely due to aging of the population. This small increase follows from the very low abortion rate and comparatively highfertilityinNorthernIreland. Data is limited, as cancer registration started in 1994. The incidence trends for the age groups 45–49 and 50–54 are shown in Figures 11 and 12. Data on women resident in the Republic in English abortion statistics are used to derive Irish abortion rates. The trends in abortion and fertility in the Republic of Ireland are shown in Figures 8 and 9. Abortion rates in the Republic are low, andIrishfertilityratesarehighcomparedwithEngland. Modeling used the latest available cancer data up to 2005 fitted for cohort incidence within ages 45–49. Forecasting used the TAR of 0.18 for 2006 and TFR of 1.86, giving a forecast increase in the rate of cancer of 8.3%, which corresponds to a yearly compound increase of 0.32%. This predicts an increase in numbers of new cancers in the Republic of Ireland to around 3,601 in 2025, compared to the 2,336 reported for 2005. The 54% increase is largely a consequence of the expected growth and aging of the Irish population. In Sweden cancer registration started in 1958. The incidence trends for the age groups 45–49 and 50–54 are shown in Figures 11and 12. The trends in abortion and fertility in Sweden are shown in Figures 8 and 9. The nonlinear trend in fertility makes modeling difficult.The abortion rates in Sweden are higher than in England at the adult ages, but in Sweden most abortions are parous. Breastfeeding is also successfully promoted in Sweden, offsetting thecarcinogeniceffectofahighabortionrate. Modeling is possible using recent years data. Forecasting with the latest TAR for Sweden of 0.65 and the latest TFR of 1.75 produces an overall increase in the rate of cancer of 31.3%, which corresponds to a yearly compound increase of 1.12%. From this model, new cancers in Sweden are expected to be 10,895 in 2025, comparedtothe7,293reportedfor2005,a49%increase. In the Czech Republic cancer registration started in 1977. The incidence trends are shown in Figures 11 and 12. Czech rates of breast cancer are low by comparison with other countries considered. Perhaps there is less genetic susceptibility.The trends in abortion and fertility in the Czech Republic are shown in Figures 8 and 9. Abortion rates in the Czech Republic were high, and most abortions areparous. Dataforrecentyears was usedtofitthemodel. Forecasts using the latest TAR for the Czech Republic of 0.35 and the latest TFR of 1.23 gave an overall increase in the rate of cancer of 39.2%, or a yearly increase of 1.33%. The Czech abortion rate has declined markedly, but the Czech birth rate has declined even more remarkably in recent years. These are offsetting factors Republic ofIreland Sweden CzechRepublic 24 for breast cancer.The model predicts 8,412 new malignancies in the Czech Republic in 2025 compared to the 5,449 reported for 2003, a 54%increase. In Finland cancer registration started in 1953 and data is available for years since 1977. The incidence trends are shown in Figures 11 and 12. The trends in abortion and fertility in Finland are shown in Figures 8 and 9. By using data for recent years it was possibletofitthemodel. The latest available TAR for Finland is 0.34 and the latest TFR is 1.7. In the modeling these gave an expected decrease in the rate of cancer of 6.8%, i.e. a yearly compound decrease of 0.28%, reflecting the decline in the Finnish abortion rate and some recovery in the birth rate in Finland. The forecast increase to 4,045 breast cancers in 2025, compared to the 3,794 reported for 2003, resultsfromtheagingofthepopulation. Anegative social gradient in Finland is reported in a large study. “Cancers of the breast were most common in high social classes throughout the whole observation period 1971–1995. The relative difference between the SIRs (Standardised Incidence Ratios) of social classes I and IV diminished from 2-fold in the period 1971–1975 to 1.5-fold in 1991–1995. SIRs were 1.67 in social class I and 0.81 in social class IV in 1971–1975 and 1.4 and 0.81 respectivelyin1991–1995.” The social gradient was not explicable in terms of fertility. “In Finland there is relatively little difference between social classes in the age at first birth and average number of children.” Abortion was not considered as an explanatory variable in this study. If it had been considered, the gradient might have been better understood. The lessening of the social gradient may be linked to a decline in the Finnishabortionrate. In Denmark cancer registration goes back to the 1940s but data after 2001 is not available. The trend is similar to other countries discussed above (Figures 11 and 12). Abortion rates declined after 1989 (Figure 8) and are less than in Sweden and England. Fertility shows adeclinesimilartothatinSweden(Figure9). Cohort fertility for years of birth before 1945 and abortion rates before 1973 were estimated. Age-specific fertility rates were not available for earlier years, and approximate estimates were made. Trend lines proved nonlinear, and model fitting was difficult. Modeling used a fixed intercept and recent data with results summarized in Table 1. The latest TAR (0.45) and TFR (1.8) gave an expected decrease in the rate of cancer of 4.1%, i.e. a yearly compound decrease of 0.16%. This decline reflects the decline in theDanishabortionrate. A social gradient has also been found in Denmark. A large Danish national study found a higher incidence of breast cancer in the higher social classes. Academics (persons with higher education) had the highest risk of breast cancer, which was 74% above that of women in agriculture, who had the lowest risk. The records were adequate to control for various risk factors, and the study concluded that “the large social differences in fertility history among Danish women could not explain the social differences in breast cancer risk.” In particular, “[a]ge at first birth and parity Finland Denmark 25 25 26,27 27 26 Journal of American Physicians and Surgeons Volume 12 Number 3 Fall 200776
  • 6. could not explain the effect of socioeconomic group on breast cancer incidence and mortality.” Abortion was not considered as a relevant factor. If it had been considered the gradient might have beenexplained. In most countries considered, women now over age 45 have had more abortions and fewer children than previous generations of women, and a further increase in breast cancer incidence is to be expected. Variations in breast cancer incidence across social class andacrossgeographicregionscanalsobeexpectedtoincrease. In England, a high rate of abortion leads to the large forecast increase. In Scotland, the lower abortion rate, offset by lower fertility than in England, leads to a slightly lower rate of increase expected. In both Irish jurisdictions, a continuation of low abortion rates and comparatively high fertility rates lead to low forecast increases in incidence of breast cancer. In Sweden a high abortion rate is offset partly by fewer nulliparous abortions and a high level offertilityandbreastfeeding. In the Czech Republic, the forecast of an increase in breast cancer incidence is largely the result of the fallen birth rate. In Finland and Denmark, lower abortion rates imply less breast cancer inthefuture. The negative or reverse social gradient whereby upper class women have more breast cancer is apparent in four countries where it is measured: England & Wales, Scotland, , and Denmark. In all of these countries the known reproductive factors other than abortion fail to explain the gradient. But the known likelihood for upper class and upwardly mobile women to prefer abortions when pregnant could provide some explanation of this gradient. If abortions had been examined in the studies of this social gradient, theroleofthisfactorcouldhavebeenmadeclear. The increase in breast cancer incidence appears to be best explained by an increase in abortion rates, especially nulliparous abortions, and lower fertility. And the social gradient, which is not explained by fertility, seems also attributable circumstantially to abortion. A linear regression model of successive birth cohorts of women with abortion and fertility as explanatory variables fitted to the cancer incidence up to 1977 has produced forecasts that have performed well in the years 1998–2004 in Great Britain (AppendixA). Thenew forecasts foreightcountries canbetestedinthecoming years. 27 Summary Conclusion Finland Patrick S. Carroll, M.A., Acknowledgements: Potential conflicts of interest: is Director of Research, Pension and Population Research Institute (PAPRI), 35 Canonbury Road, London N1 2DG, UK. Contact: papriresearch@btconnect.com. Particular thanks are due to the charities LIFE and The Medical Education Trust, which funded the research, to the national statistical offices and cancer registries, which provided the data, and to the statisticians who kindly gave advice. Figure 10 is reproduced from the publication with permission of the Cancer Surveillance Team, Information Services Division (ISD), NHS National Services, Scotland. Computing was done by Andrew Chan and Lee Young. none disclosed. Trends in Cancer Survival in Scotland 1971-1995 REFERENCES 1 Goldacre MJ, Kurina LM, Seagroat V, et al. A case control record linkage study. 2001:55:336-337.J Epidemiol Community Health 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 18 19 20 21 22 23 26 27 28 29 Finer LB, Henshaw SK. Estimates of U.S. abortion incidence in 2001 and 2002. Alan Guttmacher Institute (AGI); 2005. Blayo C. L’evolution du recourse a l’avortement en France depuis 1976. Institut National des Etudes Demographiques (INED); 1995:779-810. Cancer Incidence Data, Office for National Statistics and Welsh Cancer Incidence and Surveillance Unit (WCISU). Available at: www.statistics.gov.uk and www.wcisu.wales.nhs.uk. Accessed Jul 31, 2007. Melbye M, Wohlfahrt J, Olsen JH, et al. Induced abortion and the risk of breast cancer. 1997:336.81-85. Brewster DH, Stockton DL, Dobbie R, et al. Risk of breast cancer after miscarriage or induced abortion: a Scottish record linkage case control study. 2005;59:283-287. Lindefors Harris BM, Eklund G, et al. Risk of cancer of the breast after legal abortion during first trimester: a Swedish register study. 1989:299:1430-1322. Brind J. Induced abortion as an independent risk factor for breast cancer. 2005;10:105-110. Beral V, Bull D, Doll R, Peto R, Reeves G. Breast cancer and abortion: collaborative reanalysis of data from 53 epidemiological studies. 2004;363:1007-1016. Erlandsson G, Montgomery SM, Cnattingius S, Ekborn A. Abortions and breast cancer: record based control study. 2003;103:676-679. Schwerdlow A, dos Santos Silva I, Doll R. . Oxford University Press; 2001. Howe H, Senie R T, Bzduch H, Herzfeld P. Early abortion and breast cancer risk among women under age 40. 1989;18:300-304. White C, van Galen F, Chow YH. Trends in social class differences in mortality by cause, 1986-2000. 2003(winter):25-37. Available at: http://www.statistics.gov.uk/ statbase/Product.asp?vlnk=6725&More=N. Accessed Jul 31, 2007. Lee E, Clements S, Ingham R, et al. York, UK: Joseph Rowntree Foundation; 2004. Available at: http://www. jrf.org.uk/. Accessed Jul 31, 2007. Birth Statistics. Office for National Statistics (ONS) (UK). London, UK: ONS; 2005. Abortion Statistics . ONS 1968–2001. Department of Health 2002–2006. Russo J, Rivera R, Russo IH. Influence of age and parity on the development of the human breast. 1992:23:211-218. Leon D. A prospective study of the independent effects of parity and age at first birth on breast cancer incidence in England & Wales. 1989:43:986-991. Ramazzini B. London, UK; 1751:152. Carroll P. Pregnancy related risk factors in female breast cancer incidence. 2002;4:331-375. Information and Statistics Division of the National Health Service in Scotland. Edinburgh, Scotland; 1960–2004. White A, Freeth S, O’Brian M. London, UK: Office for Population Censuses and Surveys (OPCS); 1992. Stockholm, Sweden: Socialstyrelsen; 2000. Pukkala E. Time trends in socio-economic differences in incidence rates of cancers of the breast and female genital organs. 1999;81:56-61. Dano H, Andersen O, Ewertz M, et al. Socio-economic status and breast cancer in Denmark. 2003: 32: 216-226. Dano H, Hansen KD, Jensen P, et. al. Fertility pattern does not explain social gradient in breast cancer in Denmark. 2004:111:451-456. Carroll P. Trends and reproductive risk factors in female breast cancer incidence in Great Britain. 2004;91(Suppl 1):S24, Poster 2. Carroll P. Trends and risk factors in British female breast cancer. Joint Statistical Meetings (JSM), American Statistical Association, Minneapolis, Minn.; 2005:2511-2519. Population No. 3. N Engl J Med J Epidemiol Community Health BMJ J Am Phys Surg Lancet Int J Cancer Cancer Incidence and Mortality in England & Wales. Trends and Risk Factors Int J Epidemiol Health Statistics Quarterly No. 20; A Matter of Choice. Cancer Atlas of the United Kingdom and Ireland. Breast Cancer Res Treat Int J Cancer Of the Diseases of Artificers. Int Congress of Actuaries, Transactions Infant Feeding 1990. Anning av barn foedda. [Breastfeeding of Infants Born in 1998]. Int J Cancer Int J Epidemiol Int J Cancer Br J Cancer Statistics in Epidemiology. 17 24 25 England & Wales Statistical Bulletin; Journal of American Physicians and Surgeons Volume 12 Number 3 Fall 2007 77
  • 7. AppendixA. Female Breast Cancers and Ductal Carcinoma in Situ (DCIS) in England &Wales: Comparison of Forecast Numbers Published in 2002 with ReportedIncidenceintheYears 1998–2004 Modelling based on breast cancer incidence data up to 1997 was used to forecast incidence over future years through 2027. Forecast rates were applied to the projected female population in the 1998-based forecast made bytheUK GovernmentActuarytocalculateforecastnumbersofcancers. In these 1997-based forecasts, the same rate of increase in incidence wasassumedtoapplytoallagegroups. Two forecasts were made: (1) Using model fitting without weighting to allow for additionally carcinogenic effect of nulliparous abortions gave a lower increase in rates of 44.4% over 30 years, or 1.25% per annum. (2) With weighting to allow for the additionally carcinogenic effects of nulliparous abortions, the model gave a higher increase of 2.2% per annum or92% over30years. 21 Tables 1A-3A show the observed cases from official counts of new cases and the expected numbers calculated with the unweighted model, for cancers, ductal carcinoma in situ (DCIS), and cancers combined with DCIS, respectively. The forecast tended to underestimate slightly the number of cancers; the ratio of observed to expected was 1.013 (101.3%) in 2004. For DCIS, the underestimate, O/E = 1.54 (154.3%) for 2004, was much more notable, probably owing to extension of screening programs. The combined rate of cancers and DCIS was somewhat underestimated, O/E=1.04 (104.4%) in2004. Weighting for the increased carcinogenicity of nulliparous abortions gave the results shown in Tables 4A-6A for cancers, DCIS, and cancers combined with DCIS, respectively. Cancers were slightly overestimated, O/E = 0.946 (94.6%) for 2004. DCIS was underestimated, but less so than with the first model: O/E = 1.44 (144%) in 2004. The combined forecast proved quite good, with 100.5% of the total new malignancies anticipated in2003, and97.5% in2004. Year 15-44 45-49 50-54 55-59 60+ All ages % Observed/ Expected 1998 1999 2000 2001 2002 2003 2004 Expected Observed Expected Observed Expected Observed Expected Observed Expected Observed Expected Observed Expected Observed Age Groups 3880 4005 4022 4153 4183 4151 4375 4161 4527 4101 4666 4214 4802 4312 3220 3099 3241 3088 3275 3042 3365 2950 3487 2993 3619 3066 3771 3268 4725 4633 4909 5031 5051 4951 5172 4957 5039 4514 5021 4554 5081 4439 3621 3880 3805 4198 4005 4138 4284 4477 4761 4819 5079 5396 5292 5136 19042 19029 19450 19791 19872 19544 20374 19846 20836 20293 21402 21575 21981 21557 34488 34646 35427 36261 36386 35826 37570 36391 38650 36720 39787 38805 40927 38712 100.5 102.4 98.5 96.9 95.0 97.5 94.6 Year 15-44 45-49 50-54 55-59 60+ All ages % Observed/ Expected 1998 1999 2000 2001 2002 2003 2004 Expected Observed Expected Observed Expected Observed Expected Observed Expected Observed Expected Observed Expected Observed Age Groups 193 136 200 255 208 279 218 264 225 290 232 278 239 315 321 231 323 272 327 243 336 272 348 261 361 249 376 275 471 674 490 765 504 804 516 832 503 813 501 817 507 827 375 454 394 488 414 544 443 622 493 675 526 789 547 612 746 917 765 1006 784 1163 800 1163 819 1230 847 1530 881 1644 2106 2412 2172 2786 2237 3033 2313 3153 2388 3269 2467 3663 2550 3673 114.5 128.3 135.6 136.3 136.9 148.5 144.0 Year 15-44 45-49 50-54 55-59 60+ All ages % Observed/ Expected 1998 1999 2000 2001 2002 2003 2004 Expected Observed Expected Observed Expected Observed Expected Observed Expected Observed Expected Observed Expected Observed Age Groups 4073 4141 4222 4408 4391 4430 4593 4425 4752 4391 4898 4492 5041 4627 3541 3330 3564 3360 3602 3285 3701 3222 3835 3254 3980 3315 4147 3543 5196 5307 5399 5796 5555 5755 5688 5789 5542 5327 5522 5371 5588 5266 3996 4334 4199 4686 4419 4682 4727 5099 5254 5494 5605 6185 5839 5748 19788 19946 20215 20797 20656 20707 21174 21009 21655 21523 22249 23105 22862 23201 36594 37058 37599 39047 38623 38859 39883 39544 41038 39989 42254 42468 43477 42385 101.3 103.9 100.6 99.2 97.4 100.5 97.5 Year 15-44 45-49 50-54 55-59 60+ All ages % Observed/ Expected 1998 1999 2000 2001 2002 2003 2004 Expected Observed Expected Observed Expected Observed Expected Observed Expected Observed Expected Observed Expected Observed Age Groups 4033 4141 4140 4408 4264 4430 4415 4425 4524 4391 4558 4492 4705 4627 3507 3330 3494 3360 3497 3285 3559 3222 3650 3254 3752 3315 3871 3543 5145 5307 5294 5796 5393 5755 5468 5789 5275 5327 5205 5371 5216 5266 3956 4334 4117 4686 4290 4682 4545 5099 5002 5494 5284 6185 5451 5748 19595 19946 20453 20797 20055 20707 20357 21009 20616 21523 20975 23105 21365 23201 36236 37058 37498 39047 37499 38859 38344 39544 39067 39989 39774 42468 40608 42385 102.3 104.1 103.6 103.1 102.4 106.8 104.4 Year 15-44 45-49 50-54 55-59 60+ All ages % Observed/ Expected 1998 1999 2000 2001 2002 2003 2004 Expected Observed Expected Observed Expected Observed Expected Observed Expected Observed Expected Observed Expected Observed Age Groups 191 136 196 255 202 279 209 264 214 290 219 278 223 315 318 231 317 272 317 243 323 272 331 261 340 249 351 275 467 674 480 765 489 804 496 832 478 813 472 817 473 827 371 454 386 488 402 544 426 622 469 675 496 789 511 612 739 917 751 1006 761 1163 769 1163 780 1230 799 1530 822 1644 2086 2412 2130 2786 2171 3033 2223 3153 2272 3269 2326 3663 2380 3673 115.6 130.8 139.7 141.8 143.9 157.5 154.3 Year 15-44 45-49 50-54 55-59 60+ All ages % Observed/ Expected 1998 1999 2000 2001 2002 2003 2004 Expected Observed Expected Observed Expected Observed Expected Observed Expected Observed Expected Observed Expected Observed 3842 4005 3944 4153 4062 4151 4206 4161 4310 4101 4339 4214 4482 4312 3189 3099 3177 3088 3180 3042 3236 2950 3319 2993 3412 3066 3520 3268 4678 4633 4814 5031 4904 4951 4972 4957 4797 4514 4733 4554 4743 4439 3585 3880 3731 4198 3888 4138 4119 4477 4533 4819 4788 5396 4940 5136 18856 19029 19702 19791 19294 19544 19588 19846 19836 20293 20176 21575 20543 21557 34150 34646 35368 36261 35328 35826 36121 36391 36795 36720 37448 38805 38228 38712 101.5 102.5 101.4 100.7 99.8 103.6 101.3 Age Groups Table 6A. Combined Cases of Female Breast Cancer and DCIS in England & Wales, Observed v. Predicted from Model Weighted for NulliparousAbortion Table 5A. Number of Cases of Female DCIS in England & Wales, Observed v. Predicted from Model Weighted for NulliparousAbortion Table 4A. Number of Female Breast Cancers in England & Wales, Observed v. Predicted from Model Weighted for NulliparousAbortions Table 3A. Combined Cases of Female Breast Cancer and DCIS in England & Wales, Observed v. Predicted from Unweighted Model Table 2A. Number of Cases of Female DCIS in England & Wales, Observed v. Predicted from Unweighted Model Table 1A. Number of Female Breast Cancers in England & Wales, Observed v. Predicted from Unweighted Model Forecast based on incidence of breast cancer up to 1997 Journal of American Physicians and Surgeons Volume 12 Number 3 Fall 200778