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Breast cancer prevention . Graham Colditz, MD, DrPH Niess-Gain Professor, Dept. of Surgery Washington University School of Medicine, ACS Clinical Research Professor, and Associate Director, Prevention and Control. Long history of studying causes. 1850’s family history

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breast cancer prevention

Breast cancer prevention

Graham Colditz, MD, DrPH

Niess-Gain Professor, Dept. of Surgery

Washington University School of Medicine,

ACS Clinical Research Professor, and

Associate Director, Prevention and Control

long history of studying causes
Long history of studying causes
  • 1850’s family history
  • 1920’s reproductive risk factors
    • Lane-Claypon, 1926 case-control study
  • 1950’s menopause
  • 1970 – onwards oral contracpetives, postmenopausal hormones, diet, physical activity, obesity, endogenous hormones, SERMs
do we know causes of breast cancer
Do we know causes of breast cancer?
  • How do we frame this question?
  • Individual cases?
  • At the population level?
  • Does epidemiology guide prevention for individual women or inform population strategies?
prevention
Prevention
  • Prevention today refers mainly to lowering the risk of disease.
  • Risk of most chronic diseases can't be totally eliminated, it can still be significantly reduced.
  • If everyone in the US led a healthy lifestyle, 80% of the cases of heart disease and diabetes could be avoided, as could 70% the cases of stroke and over 50% of cancer.
slide5
Risk
  • Risk is a person's chance of getting a disease over a certain period of time.
  • There are many different ways to present risk.
can we prevent breast ca
Can we prevent breast CA?
  • YES
  • International variation
  • Migration
  • Common claim we do not know causes “ much of breast cancer epidemiology is not explained by known risk factors”
slide8

1930

1990

Seow A, et al Int J Epi 1996

goals
Goals
  • Review risk factors in context of natural history/biology of the breast,

- focus on reproductive factors

- contribution of postmenopausal hormones

  • Potential for prevention

- SERMS (Selective Estrogen Receptor Modulators)

- diet, activity, weight loss (or control), breast feeding

risk factors
Age

Gender

Family history

Benign breast disease

Reproductive factors

Endogenous hormones

Exogenous hormones

Adiposity

Diet

Physical activity

Alcohol

Radiation

Risk factors
models of disease incidence
Models of disease incidence
  • Can summarize risk factors and take account of temporal relations between risk factors and disease
  • Temporal relations often ignored in standard risk estimation and interpretation
  • Offers one approach to summarizing a range of etiologic pathways

- predict population or individual risk

pike model
Pike model
  • Factors associated with reduced risk of breast cancer were considered to lower the rate of breast tissue aging
    • Pike et. al., Nature 1983;303:767-70
  • We translated this to mean the rate of cell division and accumulation of molecular damage on the pathway to breast cancer
one birth model
One Birth Model

Rate of tissue aging

First birth

Menopause

Age

Menarche

Rosner, Colditz, Willett, Am J Epidemiology 1994;139:824

extensions to modeling
Extensions to modeling
  • Includes time from birth to menarche
  • Allows the impact to the first birth to vary with age at first birth
  • Fits log incidence (Poisson regression) model giving terms that are interpretable
  • Contrast contribution of risk factors for receptor positive and negative breast cancer
multiple birth model
Multiple Birth Model

Rate of tissue aging

Rosner, Colditz, Willett, Am J Epidemiology 1994;139:826

application of models to nhs
Application of models to NHS
  • Observed that spacing of births was significantly related to reduced risk of breast cancer – the closer the births the lower the subsequent risk
  • A transient increase in risk was observed with first birth, but not subsequent births
  • Risk prediction and stratification now more accurate than Gail and other models
slide18

16%

27%

Colditz and Rosner, Am J Epidemiology 2000;152:950-64

age at menarche
Age at menarche
  • Later age - lower risk
  • Age 15 vs age 11 gives 30% lower risk to age 70
  • Lack of physical activity associated with earlier menarche
  • Diet may play a role as might fewer childhood infections
slide20

Finland

Norway

Sweden

impact of menarche on hormone levels
Impact of Menarche on Hormone levels
  • Singapore data
  • Breast cancer rates doubled
  • 144 post menopausal women
  • Late menarche (after 17) 24% lower estradiol (circulating female hormone) than women with menarche before 17
      • Wu et al CEBP 2002
slide22

44%

Colditz and Rosner, Am J Epidemiology 2000;152:950-64

menopause
Menopause
  • Early menopause reduces risk
  • High circulating hormones levels after menopause increase risk, as does use of postmenopausal hormones
  • Anti-estrogens may have a role
    • who is target population
    • how are they identified, counseled, etc.
    • balance risks vs. benefits
hormonal exposure after menopause
Hormonal exposure after menopause
  • Obesity is related to poor survival
  • Tamoxifen reduces mortality among women with breast cancer
  • Tamoxifen and Raloxifene reduce risk of breast cancer in randomized controlled trials of breast cancer prevention
slide25

P for heterogeneity = < 0.001

Risk of breast cancer by plasma estradiol levels:

By tumor receptor status

Missmer et al, 2004(case n = 152 ER+/PR+, 38 ER-/PR+, 33 ER-/PR-)

body mass index and estrone sulfate
Body Mass Index and estrone sulfate

Hankinson et a, JNCI 1995;87:1297-1302l

weight and weight gain
Weight and weight gain
  • Adult weight gain increases risk of breast cancer
  • Relation seen most clearly among postmenopausal women who never have used hormones
  • 20 kg gain from age 18 associated with doubling in risk of breast cancer vs. stable weight
schairer et al
Schairer et al
  • BCDDP cohort followed 46,355 postmenopausal women
  • 2082 cases of breast cancer
  • Relative risk increased 0.01 (0.0002-0.03) per year of use for estrogen alone
  • RR increased 0.08 (0.02-0.16) for E & P
  • Increase in RR stronger among women with BMI < 24.4 kg/m2

JAMA 2000

ross et al
Ross et al.
  • 1879 postmenopausal cases and 1637 controls in LA county
  • Estrogen alone associated with RR 1.06 (0.97-1.15) for 5 years of use
  • E & P gave RR = 1.24 (1.07-1.45) per 5 years of use
  • Among E & P sequential therapy gave higher risk than continuous therapy

JNCI 2000

women s health initiative design
Women’s Health Initiative Design
  • A randomized controlled primary prevention trial
  • Planned duration 8.5 years
  • 16,608 postmenopausal women 50 – 79 years of age with intact uterus at baseline were recruited by 40 clinical centers in 1993-1998
intervention
Intervention
  • Conjugated equine estrogen 0.625 mg/d, plus medroxyprogesterone acetate, 2.5 mg/d, in 1 tablet (n=8506)
  • Placebo (n=8102)
results at termination of trial
Results at termination of trial
  • Mean duration of follow-up 5.2 years
  • 290 cases of breast cancer
  • Risk increased with duration of use (sig. trend over time)
  • Overall RR vs placebo = 1.26 (1.00-1.59)
  • But, substantial noncompliance will bias results to null:
    • 42% E&P and 38% placebo stopped study medication
    • RR in compliers = 1.49, p<0.001
international agency for research on cancer iarc
International Agency for research on Cancer (IARC)
  • Classify agents as carcinogens after rigorous review of evidence, laboratory, animal, and human studies
  • Vol. 91 classifies combination estrogen plus progestin as carcinogenic to humans
large drop in breast cancer
Large drop in breast cancer
  • US SEER (national tumor registry program)
  • California state
  • New Zealand
  • Germany
  • US drop in prescribing
  • Contribution of a decrease in screening has been debated and ruled out as a cause for drop
dispensed outpatient pmh prescriptions
Dispensed outpatient PMH prescriptions

34.5M ’92 to high of 87.5M 2000

Wysowski et al 2005

clarke et al california
Clarke et al, California
  • Kaiser data on prescribing
    • 68% drop in E&P prescribing following release of WHI results
  • 10% drop in breast cancer incidence
  • For US women 50 to 69 (26 million women), this is 8,200 fewer cases of breast cancer, each year
      • J Clin Oncology Nov 2006
further seer analysis
Further SEER analysis
  • Jemal et al used state of art analysis (joint point analysis) to evaluate trends in breast cancer over time
  • 1975 to 2003 – 394,891 invasive cancers
  • Decrease in breast cancer largely confined to ER+ tumors in the 2003 downturn
  • Trend down strongest in women 55 to 64
  • In situ rates stable from 2000 to 2003
  • Rules out substantial screening impact

Jemal Breast Cancer Res May 2007

further analysis of california data
Further analysis of California data
  • California health interview survey
  • California tumor registry breast cancer
  • Classified CA counties into 3 levels based on 2001 E&P use
  • Breast cancer incidence declined
    • 8.8% in counties with smallest decline
    • 13.9% intermediate
    • 22.6% largest E&P decline
    • No change in proportion of women having mammograms

Robbins and Clarke JCO 2007 (August)

risk accumulation
Risk accumulation
  • Overall evidence points to accumulation of risk through the life course
  • SERMs may offer some potential to inhibit final stages of progression to cancer - prevention greatest among those with high estrogen levels
  • Lifestyle contributes to cumulative risk
  • No one intervention for prevention
physical activity
Physical activity
  • Evidence from more than 30 studies
  • Typical reduction in risk with 4 hours per week = 20% decrease in risk
  • Evidence present for pre and post- menopausal women
    • Barriers to physical activity include neighborhood safety, time and family responsibilities, social pressures
slide42

Cumulative rates of invasive and noninvasive breast cancers occurring in participants receiving placebo or tamoxifen. The P value are two-sided

Fisher et al, 1998; 90:1371-88

preventability
Preventability
  • International variation in rates
  • Variation in reproductive characteristics
  • Growth and obesity
  • Primary prevention randomized trials
social strategy to prevent breast cancer
Social strategy to prevent breast cancer
  • Provider
    • counseling on diet, activity, weight gain/loss
    • identify “higher risk” for preventive interventions
      • Balance risks and benefits
  • Regulation
    • facilitate lactation, physical activity, ?diet
  • Community
    • lactation, physical activity, access to care
goals for prevention
Goals for Prevention
  • Reduce exposure to hormones after menopause
    • Avoid postmenopausal hormones
    • Weight loss
    • Anti estrogens for those at high enough risk
  • Promote increase in physical activity
  • Manage alcohol intake
risk vs benefit who should get a serm
Risk vs. benefit: who should get a SERM
  • 35.6M women 50 to 79
  • 134,000 incident cases/yr
  • Raloxifene would prevent 80,872 cases/yr
  • Raloxifene would cause 67,649 thromboembolic events
    • Based on 19/10,000 per year treated
  • For benefit (reduced breast cancer) to exceed harm (thromboembolic events) incidence must be greater than 380/100,000
age and risk decile for benefits to exceed risks
Age and risk decile for benefits to exceed risks

Incidence based on Rosner/Colditz model

Incidence per 100,000 women per year

50 to 64 year old population 5.1M eligible, 25%<65

incidence number needed to treat for 5 years to prevent 1 cases top decile
Incidence, Number Needed to Treat (for 5 years) to prevent 1 cases (top decile)

Assumes 50% reduction in Breast CA risk

Incidence per 100,000/yr.

Chen W, Rosner B, Colditz G. Cancer 2007

next steps to prevention of breast cancer
Next steps to prevention of breast cancer
  • Refine assessment of risk
    • Stratify and provide appropriate counseling
  • Balance risk and benefits
    • Provide tools to aid weighing risks and benefits for women
  • Implement population strategies to change behavior of providers, community, and even regulations to reinforce behavior changes (e.g., physical activity, weight control)