Flora E. van Leeuwen
Cancer Epidemiology
• Descriptive cancer epidemiology
• Risk factors
CBS meldt: Kanker doodsoorzaak no. 1
The ten most frequent invasive tumors in the
Netherlands, 2013, Females
Tumor site n %
1. Breast 14,402 29.6
2. Colon/rectum 5,895 12.1
3. Lung/bronchus/trachea 5,055 10.4
4. Skin, other 4,258 8.7
5. Skin, melanoma 2,879 5.9
6. Corpus uteri 1,997 4.1
7. Non-Hodgkin lymphoma 1,654 3.4
8. Ovary 1,259 2.6
9. Pancreas 1,136 2.3
10 Urinary bladder 734 1.6
Unknown primary 899 1.8
All sites 48,753
Source Netherlands Cancer Registry (www.iknl.nl)
Trends in incidence and mortality of breast cancer 1989 -
2012
ESR: per 100,000
incidence
mortality
Causes of rising breast cancer incidence
• Screening
• Higher prevalence of risk factors
Causes of decreasing mortality
• More effective adjuvant treatment
• Earlier diagnosis (screening)
Changing risk factors for breast
cancer
• Later age at first birth
• More overweight/obesity
• More alcohol use
• Less physical activity
• Fewer women breastfeed for long
durations
• Smoking
Primary driving forces for breast cancer
Hormones
Nurses’ Health Study
postmenopausal women HR 95%CI
E2 3.5 1.6- 8.0
Estron 2.9 1.2- 6.6
EstronSulfate 4.3 1.9-10.1
DHEAS 4.2 1.6-10.0
(In never HRT users, Hankinson et al. JNCI 1998;90:1292-9)
Incidence invasive breast cancer
Netherlands 1989-2003
Source: Netherlands Cancer Registry
Breast cancer
0
50
100
150
200
250
300
350
400
450
1985 1990 1995 2000 2005
year of diagnosis
per 1
00
,00
0 p
erson
-years
<50 yrs
50-69 yrs
70+ yrs
Start screening 50-69 yrs
Start screening 70-74 yrs
Trend in breast cancer mortality in the Netherlands
0
5
10
15
20
25
30
35
40
45
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
year of death
Per 1
00
,00
0p
erso
n y
earsp
er 1
00
00
ESR standardisation CBSSource: CBS
Trends in incidence of lung cancer 1989-2013
Source: Netherlands Cancer Registry (www.iknl.nl)
Percentage rokers Nederlandse
bevolking 1958-2011
www.stivoro.nl
Trends in incidence of melanoma
1989-2013
Source: Netherlands Cancer Registry (www.iknl.nl)
female
male
Trends in incidence of Non-Hodgkin lymphoma
1989-2013
Source: Netherlands Cancer Registry (www.iknl.nl)
male
female
incidence
mortality
Trends in incidence and mortality of
ovarian cancer 1989 - 2011
www.iknl.nl
Trends in incidence of stomach
cancer 1989- 2011
www.iknl.nl
www.iknl.nl
female
male
The ten most frequent invasive tumors in the
Netherlands, 2013, Males
Tumor site n %
1. Prostate 10,897 20.7
2. Colon/rectum 7,475 14.0
3. Lung/bronchus/trachea 7,055 13.2
4. Skin, other 5,263 9.9
5. Skin, Melanoma 2,610 4.9
6. Non-Hodgkin lymphoma 2,441 4.6
7. Urinary bladder 2,198 4.1
8. Oesophagus (with cardia) 1,946 3.7
9. Kidney 1,458 2.9
10 Pancreas 1,192 2.2
Unknown primary 969 1.8
All sites 53,095
Source Netherlands Cancer Registry (www.iknl.nl)
Trends in incidence and mortality of prostate cancer,
1989-2012
ESR: per 100,000
incidence
mortality
Trends in incidence of oesophageal cancer, males
1989-2013
Source: Netherlands Cancer Registry (www.iknl.nl)
Trends in incidence of colon/rectum cancer 1989-2013
Source: Netherlands Cancer Registry (www.iknl.nl)
male
female
Trends in incidence and mortality of testis cancer,
1989-2012
ESR: per 100,000
Incidence
Mortality
The ten most frequent invasive tumors in the
Netherlands, 2012, Females
Tumor site Incidence* Mortality*
1. Breast 169.0 37.8
2. Colon/rectum 71.7 30.2
3. Lung/bronchus/trachea 58.2 47.3
4. Skin, other 48.6 0.6
5. Skin, melanoma 32.3 3.7
6. Corpus uteri 22.3 5.4
7. Non-Hodgkin lymphoma 19.6 5.8
8. Ovary 15.2 12.2
9. Pancreas 13.7 14.9
10 Urinary bladder 8.7 4.7
Unknown primary 10.5 10.6
All sites 573.0 235.9
*
Source:
Crude rates, per 100,000 p/yr
Netherlands Cancer Registry (www.iknl.nl)
Aims of cancer registries– Descriptive cancer epidemiology
(cancer burden in the population, planning of health care facilities, time trends, geographic differences)
– Valuable database for analytic epidemiologic studies (etiology)
– case-control
– cohort (linkage studies)
– Clinical studies
– population-based survival
– patterns of care studies
Report
“Signaleringscommissie
Kanker 2011”
Supervised by:
Prof. dr. Bart Kiemeney
UMC St Radboud, Nijmegen
Implications for number of
new cancer diagnoses per
year: +40%
Age specific incidence rates of invasive
tumors according to sex
Male–female ratios of cancer incidence in NL
Age distribution of new cancers in
the Netherlands, 2013, males
Source: Netherlands Cancer Registry
www.iknl.nl60-74 yrs
47.3%
0-29 yrs
1.7% 30-44 yrs
3.3%
45-59 yrs
16.2%
75+ yrs
31%
60-74 yrs
47.7%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
during life time before age 75 years
male
female
Risk of cancer
44%
38%
28%25%
Signaleringsrapport De kans op kanker
KWF Kankerbestrijding 2007 (www.kwfkankerbestrijding.nl)
Causes of cancer
About 90% of all cancers are attributable
to life style and environmental factors
* in combination with weak susceptibility
genes
How do we know that exogenous factors are
responsible for the vast majority of all cancers?
• Large international differences in incidence
rates
• Changes in incidence rates over time
• Migrant studies show that, in 1 to 3
generations, migrants develop cancer
incidence rates that approach those of the
population they have joined
History I
Evolving cancer epidemiology
• After the second World War
• Before then: emphasis on infectious disease epidemiology
• The fame of cancer epidemiology is derivedfrom “discovering” the association betweensmoking and lung cancer (1950s)
Proportion of smokers and non-smokers in
lung-carcinoma patients and in control
patients with diseases other than cancer
Doll and Hill, BMJ 1950; 2(4682): 739
Causes of cancer
About 90% of all cancers are attributable
to life style and environmental factors
* in combination with weak susceptibility
genes
Dole and Peto, J Natl Cancer Inst. 1981
Jun;66(6):1191-308
Proportions of cancer deaths attributed to
various factors in industrial coutries*
Highly penetrant genes 5%
Tobacco 30%
Alcohol 4-6%
Diet 10-30%
Food additives (salt) 1%
Obesity 6-8%
Reproductive factors 5-10%
Occupation 1-3%
Radiation (ionizing, UV) 3-4%
Medicines -5 - +5%
Viruses, Bacteria 5-10%
Physical inactivity 3-5%
Environmental pollution 1-4%
Unknown ?**
* From Doll and Hill, 1981; Peto, 1985; Trichopoulos et al, 1996; Doll 1999
** Grand total may exceed 100% since one cancer may have two or more causes
Lanting, Ned Tijdschr Geneesk 2014; 15B: A8085
Contribution lifestyle factors to cancer risk
Lanting, Ned Tijdschr Geneesk 2014; 15B: A8085
Roken draagt 30% bij aan kankersterfte
Relative risks for cancers of the oral cavity and
pharynx in males, according to smoking and
alcohol drinking. Northern Italy, 1986-89
Alcohol intake
Smoking status
<35
drinks/wk
35-59
drinks/wk
60+
drinks/wk
Non-smokers
Light
Intermediate
Heavy
1
3.1
10.9
17.6
1.6
5.4
26.6
40.2
2.3
10.9
36.4
79.6
Franceschi et al., Cancer Research 1990; 50:6502-07
Proportions of cancer deaths attributed to
various factors in industrial coutries*
Highly penetrant genes 5%
Tobacco 30%
Alcohol 4-6%
Diet 10-30%
Food additives (salt) 1%
Obesity 6-8%
Reproductive factors 5-10%
Occupation 1-3%
Radiation (ionizing, UV) 3-4%
Medicines -5 - +5%
Viruses, Bacteria 5-10%
Physical inactivity 3-5%
Environmental pollution 1-4%
Unknown ?**
* From Doll and Hill, 1981; Peto, 1985; Trichopoulos et al, 1996; Doll 1999
** Grand total may exceed 100% since one cancer may have two or more causes
Which proportion of all cancer
deaths can be explained?
• <100%
• Interaction
Example of smoking and alcohol
All tumors due to combination of alcohol
and smoking can be prevented by stopping
either smoking or alcohol use
So, if both factors are eliminated, as many
cancers are prevented as when one factor is
eliminated
Proportions of cancer deaths attributed to
various factors in industrial coutries*
Highly penetrant genes 5%
Tobacco 30%
Alcohol 4-6%
Diet 10-30%
Food additives (salt) 1%
Obesity 6-8%
Reproductive factors 5-10%
Occupation 1-3%
Radiation (ionizing, UV) 3-4%
Medicines -5 - +5%
Viruses, Bacteria 5-10%
Physical inactivity 3-5%
Environmental pollution 1-4%
Unknown ?**
* From Doll and Hill, 1981; Peto, 1985; Trichopoulos et al, 1996; Doll 1999
** Grand total may exceed 100% since one cancer may have two or more causes
Diet and Cancera minefield for researchers
• Hard to obtain accurate dietary intake data
• What is the relevant window of exposure(food habits change over life time)
• Many potential (anti)carcinogens in food
• Several (anti)carcinogens in food strongly correlated (e.g., high fat, low fiber, low vegetables)
Cancer epidemiology
Primarily an observational science
Weak associations (risk increases RR <2 and
risk decreases RR >0.5) in 1 or a few studies
are likely to be caused by:
• chance
• selection, misclassification, confounding bias
• publication bias
Oorzakelijk verband waarschijnlijker als:
• Het verband sterk is
• Het verband in meerdere epidemiologische studies is gevonden
belang van meta-analyse!
• Een hogere of langere blootstelling leidt tot grotere kans op ziekte
• Het verband past in biologische inzichten in het ontstaan van de ziekte
Statistisch significant verband
? oorzaak-gevolg relatie
• Pooled analysis of 6
cohort studies
• N=322,647 women
• Follow-up: 11 years
• 4,335 invasive
breast cancers
Bias in case-control studies of diet and cancer
• Selection bias
– Cases: ~90% response
– Controls: ~50-70% response
– Responding controls are more often non-smokers, lean, eating
healthy diets
Association with fat intake, vegetables and fruits etc.
• Misclassification bias
– Cases try to recall past diet better
– Cases may underreport less healthy foods
– Subjects report present diet when asked to recall past diet
Problem when colorectal cancer patients changed diet due to
complaints (less fiber etc.)
• Publication bias
– Data on 50 nutrients, 200 foods Report of positive finding first!
WCRF report
2007
Diet and Cancerpresent state of knowledge
• Fat and - breast cancer- colon cancer : no association- prostate cancer
• Fiber and - colon cancer : possibly/probably protective
• Red meat - colon cancer : probable association and processed - stomach cancer : no association
meat
• Vegetables - colon cancer : possibly protective
• and fruits - stomach cancer : probably protective- lung, head and : protective effect
neck, oesophagus
• Salt/salted foods - stomach cancer : probably risk increase
CARET Results
Omenn. NEJM 1996:334(18):1150-55
Proportions of cancer deaths attributed to
various factors in industrial coutries*
Highly penetrant genes 5%
Tobacco 30%
Alcohol 4-6%
Diet 10-30%
Food additives (salt) 1%
Obesity 6-8%
Reproductive factors 5-10%
Occupation 1-3%
Radiation (ionizing, UV) 3-4%
Medicines -5 - +5%
Viruses, Bacteria 5-10%
Physical inactivity 3-5%
Environmental pollution 1-4%
Unknown ?**
* From Doll and Hill, 1981; Peto, 1985; Trichopoulos et al, 1996; Doll 1999
** Grand total may exceed 100% since one cancer may have two or more causes
Overweight, obesity and cancer mortality in
females
BMI
(kg/ m2) All sites
RRs
Breast Colorectal Kidney
Uterine
corpus
18.5-25
25-30
30-35
35-40
40
1.0
1.08*
1.23*
1.32*
1.62*
1.0
1.34*
1.63*
1.70*
2.12*
1.0
1.10*
1.33*
1.36*
1.46*
1.0
1.33*
1.66*
1.70*
4.75*
1.0
1.50*
2.53*
2.77*
6.25*
† Calle et al., NEJM 2003; 348(17):1625-38
* P <0.05
US Cancer Prevention Study II†
• Prospective cohort study started in 1982
• 404,576 men: 495,477 women
• 16 yrs of follow-up, 57,145 cancer deaths
Overweight, obesity and cancer mortality in
males
BMI
(kg/ m2) All sites
RRs
Colorectal Esophagus Kidney
18.5-25
25-30
30-35
35-40
40
1.0
0.97*
1.09*
1.20*
1.52*
1.0
1.20*
1.47*
1.84*
-
1.0
1.15*
1.28*
1.63*
-
1.0
1.18*
1.36*
1.70*
-
† Calle et al., NEJM 2003; 348(17):1625-38
* P <0.05
US Cancer Prevention Study II†
• Prospective cohort study started in 1982
• 404,576 men: 495,477 women
• 16 yrs of follow-up, 57,145 cancer deaths
Obesity and breast cancer risk
• Increased postmenopausal breast cancer risk:
– Convincing; overweight 30%; obesity 50%
– Population attributable risk: 17% (US 23%)
• Timing in life: adult weight gain!
– per 5 kg/m2 increase in BMI: 12% risk increase
• Decreased premenopausal breast cancer risk:
– Probable; but heterogeneity across populations
– 8% decrease in risk per 5 kg/m2 increase in BMI
Calle & Kaaks Nature Reviews Cancer 2004, Renehan Lancet 2008
BMI: effect modification by
menopausal status
Postmenopausal
• Adipose tissue is the main site of estrogen synthesis
• Adipose cells increase levels of insuline and IGF1, which reduces SHBG and increases ovarian androgen synthesis
Obesity results in increased bioavailibility of hormones
Calle & Kaaks Nature Reviews Cancer 2004, Renehan Lancet 2008
Proportions of cancer deaths attributed to
various factors in industrial coutries*
Highly penetrant genes 5%
Tobacco 30%
Alcohol 4-6%
Diet 10-30%
Food additives (salt) 1%
Obesity 6-8%
Reproductive factors 5-10%
Occupation 1-3%
Radiation (ionizing, UV) 3-4%
Medicines -5 - +5%
Viruses, Bacteria 5-10%
Physical inactivity 3-5%
Environmental pollution 1-4%
Unknown ?**
* From Doll and Hill, 1981; Peto, 1985; Trichopoulos et al, 1996; Doll 1999
** Grand total may exceed 100% since one cancer may have two or more causes
Established risk factors for breast cancer
Reproductive factors Typical RR
Nulliparity (vs any parity)
Age at first birth (35 vs <16)
Parity (4 vs 1)
Age at menarche (<12 vs >14)
Age at menopause (>55 vs <45)
Oophorectomy before age 35 (vs nat. menopause)
2
3
0.5-0.7
1.3-1.5
2
0.3
Breast-feeding (1-2 years vs more)
Induced or spontaneous abortion
Menstrual cycle length?
0.7
1.0
Collaborative Group on Hormonal Factors in
Breast Cancer
Meta-analysis on original data of 47
epidemiologic studies in 30 countries
50,302 women with breast cancer
96,973 women without breast cancer
Lancet 2002;360(9328):187-95
Relative risk of breast cancer in parous women
according to breastfeeding history and number of
births
Lancet 2002;360(9328):187-95
Relative risk of breast cancer in
relation to breast feeding (parae)
Lancet 2002;360(9328):187-95
Relative risk on breast cancer
risk decreases by:
• 7% for each birth
• 4% for every 12 months of breastfeeding
• 3% for each year a women has her first birth
earlier
Lancet 2002;360(9328):187-95
The impact of parity and breastfeeding
on breast cancer incidence
(CGHFBC. Breast cancer and breastfeeding. Lancet 2002;360:187-95.)
Lancet 2002;360(9328):187-95
Reproductive factors and risk of breast cancer
Model of cumulative incidence of breast cancer in Dutch
population according to reproductive factors
Based on:
• RR from Oxford meta-analysis, Lancet 2002;360:187-95
7.0% per child
4.3% per year of duration of breast feeding
3.0% per later year of age at first birth
• Dutch data in the general population:
- prevalence of reproductive factors (2001)
- cumulative risk at age 75 of breast cancer (1999-2003)
Risk of breast cancer in the Netherlands
Reproductive factors:
Cu
mu
lati
ve
Ris
k (
%)
Age at first birth
Duration of breastfeeding (0; 1-6; 6-12; 12-24; 24-36; >36 months)
1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4
nulliparae
parae
Total number of children
40-4415-19 20-24 25-29 30-34 35-39
18.00
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
16.00
II I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I II I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I II I I I I
(Rookus, Handboek Mammacarcinoom, 2007;
Rookus, Neth. J Med, in preparation)
Risk of breast cancer in the Netherlands
Reproductive factors:
Cu
mu
lati
ve
Ris
k (
%)
Age at first birth
Duration of breastfeeding (0; 1-6; 6-12; 12-24; 24-36; >36 months)
40-4415-19 20-24 25-29 30-34 35-39
18.00
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
16.00
1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4
II I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I II I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I II I I I I
nulliparae
parae
Total number of children
7.9 9.2
(Rookus, Handboek Mammacarcinoom, in press,
Rookus, Neth. J Med, in preparation, on request)
HRT and breast cancer
• Current users who had used HRT for 5 yrs:
RR = 1.35, 95% CI: 1.21-1.149
• Duration-response relationship
• 5 or more years after cessation of HRT use:
no excess risk
• Stronger association in lean women
• Much stronger association for estrogen-
progestagen pills than for estrogen alone
Implications of small increases of risk
• Hormonal replacement therapy and breast cancer
Meta-analyses show 30% risk increase (RR=1.3)
with 5 years of use.
Implications in the Netherlands (12% use):
225 extra cases of breast cancer yearly
(3.5% of all cases in women > 50 years)
• Passive smoking
EPA meta-analyses (1992) show 19% risk increase
(RR=1.19) for exposed female nonsmokers.
Implications in the Netherlands:
about 200 extra cases of lung cancer yearly
(2.4% of all lung cancer cases)
Een heel hoog RR heeft heel weinig
implicaties voor de volksgezondheid
ALS DE ZIEKTE ZELDZAAM IS
borstkanker leverkanker
100
140
5
0102030405060708090
100110120130140150160
RR = 1.4
RR = 5
geen HST geen HSTHST HST
1
Jaarlijks aantal
diagnoses per
100.000 inw.
JAMA 2002; 288: 321-33
Women’s Health Initiative
Design: RCT
Population: 16,608 US postmenopausal women aged
50-79 yrs (mean age at entry 63 yrs!)
Intervention: Estrogen-Progestin-HRT (equine estrogens
0.625 mg/d plus MPA 2,5 mg/d), or placebo
Planned follow-up: 8.5 yrs
Trial stopped early at 5.2 yrs
HRT n=8,506 breast cancer (n=166)
no breast cancer
16,608 5.2 yrs of follow-up
women
breast cancer (n=124)
Placebo n=8,102 no breast cancer
HRT and Breast Cancer risk, WHI results JAMA 2002; 288: 321-33
Placebo
HRT
Time, y 0 1 2 3 4 5 6 7
0.03
0.02
0.01
0
Placebo
HRT
Time, y 0 1 2 3 4 5 6 7
0.03
0.02
0.01
0
Proportions of cancer deaths attributed to
various factors in industrial coutries*
Highly penetrant genes 5%
Tobacco 30%
Alcohol 4-6%
Diet 10-30%
Food additives (salt) 1%
Obesity 6-8%
Reproductive factors 5-10%
Occupation 1-3%
Radiation (ionizing, UV) 3-4%
Medicines -5 - +5%
Viruses, Bacteria 5-10%
Physical inactivity 3-5%
Environmental pollution 1-4%
Unknown ?**
* From Doll and Hill, 1981; Peto, 1985; Trichopoulos et al, 1996; Doll 1999
** Grand total may exceed 100% since one cancer may have two or more causes
Risk factors for breast cancer
Radiation
• Established risk factor
Evidence from:
• Atomic bomb survivors
• Patients with tuberculosis given chest fluoroscopes
• Women given radiotherapy for benign or malignant disorders– Hodgkin's disease patients
– patients with acute postpartum mastitis
– breast cancer patients
– children with tinea capitis
– infants with thymic enlargement
• Women occupationally exposed to radiation
Risk of breast cancer after HL by
follow-up time
(120 breast cancers in 1122 Dutch HL Patients)
0
2
4
6
8
10
12
14
16
18
5-9yrs 10-14yrs 15-19yrs 20-24yrs 25-29yrs >=30yrs
SIR
0
50
100
150
200
250
5-9yrs 10-14yrs 15-19yrs 20-24yrs 25-29yrs >=30yrs
AER
30 yr survivors: 25 excess cases/100 pts followed for 10 yrs
SIR = observed/expected
(general population)
AER = absolute excess
risk/10,000 pts/yr
De Bruin M, J. Clin Oncol 2009; 27(26): 4239-4246
Cumulative incidence of breast cancer by age at
HL
De Bruin et al. JCO 2009; 27(26): 4239-4246
Proportions of cancer deaths attributed to
various factors in industrial coutries*
Highly penetrant genes 5%
Tobacco 30%
Alcohol 4-6%
Diet 10-30%
Food additives (salt) 1%
Obesity 6-8%
Reproductive factors 5-10%
Occupation 1-3%
Radiation (ionizing, UV) 3-4%
Medicines -5 - +5%
Viruses, Bacteria 5-10%
Physical inactivity 3-5%
Environmental pollution 1-4%
Unknown ?**
* From Doll and Hill, 1981; Peto, 1985; Trichopoulos et al, 1996; Doll 1999
** Grand total may exceed 100% since one cancer may have two or more causes
Proportions of cancer deaths attributed to
various factors in industrial coutries*
Highly penetrant genes 5%
Tobacco 30%
Alcohol 4-6%
Diet 10-30%
Food additives (salt) 1%
Obesity 6-8%
Reproductive factors 5-10%
Occupation 1-3%
Radiation (ionizing, UV) 3-4%
Medicines -5 - +5%
Viruses, Bacteria 5-10%
Physical inactivity 3-5%
Environmental pollution 1-4%
Unknown ?**
* From Doll and Hill, 1981; Peto, 1985; Trichopoulos et al, 1996; Doll 1999
** Grand total may exceed 100% since one cancer may have two or more causes
Physical activity
• Physical activity reduces the risks of
breast, colon and endometrial cancer by
almost 20-30%
• Effects of duration, frequency, intensity
and age at activity not yet clear
Physical activity, body weight and
breast cancer risk
• Physical activity (PA)
– Associated with modest (15-20%) decreased risk
– Evidence: postmenopausal convincing; premenopausal weaker
– 6% decrease in breast cancer risk for each additional hour of physical activity per week, lifetime
• Overweight and obesity (BMI)– 30% and 50% increased postmenopausal bc risk; probable decreased
premenopausal breast cancer risk
– Timing in life of adiposity: adult weight gain!
– per 5 kg/m2 increase in BMI: 12% risk increase and 8% decrease post- and premenopausal bc risk
• Effects are independentMonninkhof et al Epidemiology 2007, Calle & Kaaks Nature Reviews Cancer 2004, Renehan et al Lancet 2008
McTiernan Nature Reviews Cancer 2008
Increased
physical activity
Reduced
Adiposity
Improved
immune function
Decreased
insulin & glucose
Altered
adipocytokines
Decreased
risk of cancer
Decreased
oestrogens & androgens
Suggested biological mechanism
PA/BMI
• MEER lichamelijke activiteit LAGERE kans
op borstkanker
• Hoe werkt het?
– Niet alleen via afvallen
– Lichamelijke activiteit stofwisseling oestrogenen
– Sporten menarcheleeftijd
– Sporten - meer menstruele cycli zonder eisprong
- lagere hormoonspiegels in 2e deel van
menstruele cyclus
Borstkanker en bewegen/sporten
Limited knowledge of breast cancer
etiology
• Nearly all risk factors are weak
• Only 30-55% of all new breast
cancers can be attributed to presently
known risk factors
• Most identified risk factors are not
readily preventable
Conclusion breast cancer risk factors
• Known risk factors explain only 50% of all breast
cancers
• Strong risk factors (radiation, BRCA1/2) have a low
prevalence
• Weak association with most risk factors (genes, life-
style factors):
many women with risk factors do not develop
breast cancer
many women without known risk factors do
develop breast cancer
Perspectives for future research in
cancer epidemiology
• To further clarify the role of controversial
risk factors, most of which are only weakly
associated with cancer risk (e.g., dietary
factors, physical exercise, EMF)
• To develop novel ideas about possible risk
factors that still await discovery (e.g., intra
uterine, perinatal factors)
Perspectives for future research in
cancer epidemiology
Collaboration with basic research disciplines
• Molecular epidemiology; e.g., to incorporate
biological parameters in epidemiologic studies
• Genetic epidemiologic, e.g., to examine
interactions between epidemiologic risk factors
and cancer predisposing genes
Screening for breast cancer
• Start Netherlands 1990
• 50-75 years, once every 2 years
• Participation 78%
• Annually:4.400 with breast cancer 50-70 yr
50% by screening
20% interval cancers
30% non screening group
• More favorable stage distribution, more DCIS
Crucial question:
Does breast cancer mortality decrease by screening?
Screening for breast cancer
Advantages:
• High participation rate
• Non-invasive screening method
• Screening more favorable stage distribution
• Screening nearly always increases duration of survival / survival rates, but:
- Lead time bias
- Length time bias
- Longer time of knowing about cancer diagnosis
• Does lower stage distribution lower mortality??
Varying estimates: 8 – 20% reduction
Patz et al. NEJM 2000; 343:1627-33
Patz et al. NEJM 2000; 343:1627-33
Screening for breast cancer
Potential harms:
• False positives
• Overdiagnosis and overtreatment
• Late effects of overtreatment
Patz et al. NEJM 2000; 343:1627-33
Welch NEJM 2010 363;13: 1276
Benefits and harms of breast cancer screening
Bonneux, L. NTvG 2009;152:A887
Bonneux, L. NTvG 2009;152:A887
Screening mammacarcinoom
• 100 borstkanker, ontdekt bij de screening
• ? eerdere diagnose door screening, anders, bij diagnose na symptomen ook overleefd
• ? eerdere diagnose door screening, anders was borstkanker nooit bij hen vastgesteld
• ? eerdere diagnose door screening, maar overlijden tóch aan borstkanker
• 40 andere : intervalcarcinoom
• ? eerdere diagnose door screening, late effecten van bestraling
• 5-10(?) eerdere diagnose door screening, daardoor effectieve behandeling, nog geen micrometa’s