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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. 1850’s family history

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Breast cancer prevention

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  1. 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

  2. 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

  3. 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?

  4. 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.

  5. 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.

  6. 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”

  7. Breast Cancer Average Annual Incidence per 100,000 by age, 1982 Age (years/female)

  8. 1930 1990 Seow A, et al Int J Epi 1996

  9. Singapore breast cancer incidence by age and birth cohort 1908 1948 Seow 1996

  10. 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

  11. Age Gender Family history Benign breast disease Reproductive factors Endogenous hormones Exogenous hormones Adiposity Diet Physical activity Alcohol Radiation Risk factors

  12. 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

  13. 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

  14. One Birth Model Rate of tissue aging First birth Menopause Age Menarche Rosner, Colditz, Willett, Am J Epidemiology 1994;139:824

  15. 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

  16. Multiple Birth Model Rate of tissue aging Rosner, Colditz, Willett, Am J Epidemiology 1994;139:826

  17. 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

  18. 16% 27% Colditz and Rosner, Am J Epidemiology 2000;152:950-64

  19. 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

  20. Finland Norway Sweden

  21. 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

  22. 44% Colditz and Rosner, Am J Epidemiology 2000;152:950-64

  23. 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

  24. 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

  25. 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-)

  26. Body Mass Index and estrone sulfate Hankinson et a, JNCI 1995;87:1297-1302l

  27. 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

  28. Eliassen JAMA 2006

  29. 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

  30. 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

  31. 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

  32. Intervention • Conjugated equine estrogen 0.625 mg/d, plus medroxyprogesterone acetate, 2.5 mg/d, in 1 tablet (n=8506) • Placebo (n=8102)

  33. 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

  34. 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

  35. 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

  36. Dispensed outpatient PMH prescriptions 34.5M ’92 to high of 87.5M 2000 Wysowski et al 2005

  37. 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

  38. 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

  39. 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)

  40. 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

  41. 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

  42. 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

  43. JAMA 1999, JNCI 2004

  44. Preventability • International variation in rates • Variation in reproductive characteristics • Growth and obesity • Primary prevention randomized trials

  45. 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

  46. 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

  47. No significant difference in adverse events

  48. 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

  49. 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

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