Genetics of Breast and Ovarian Cancer Genetics of Breast and Ovarian Cancer
Source: National Cancer Institute

Women with a previous primary breast cancer have a 3-fold to 4-fold increase in risk of a second breast cancer in the contralateral breast.[62] Most studies report an annual risk of development of a second breast cancer of 0.5% to 0.7%.[63] While the risk of contralateral breast cancer persists for up to 30 years after the original diagnosis, the median interval between primary breast cancer and contralateral disease is approximately 4 years.[64]

Although risk is similar following invasive and in situ ductal cancer, it is higher for women with a family history of breast cancer, and for those with a lobular histology in the original cancer.[65] Lobular carcinoma in situ (LCIS), which is often an incidental finding in breast biopsies, is associated with an increased risk of subsequent invasive cancer. Long-term follow-up studies of women diagnosed with LCIS report relative risks of developing breast cancer ranging from 7 to 12. Risks are higher for women diagnosed at a younger age, and for those with a family history of breast cancer. Subsequent breast cancers are most often of ductal histology, and occur equally in either breast, suggesting that LCIS is a marker of risk rather than a precancerous lesion itself.[66]

Other Factors
Other risk factors, including those that are only weakly associated with breast cancer and those that have been inconsistently associated with the disease in epidemiologic studies (e.g., cigarette smoking), may be important in subgroups of women defined according to genotype. For example, some studies have suggested that certain N-acetyl transferase alleles may influence female smokers’ risk of developing breast cancer.[67] This possible gene-environment interaction has varied in some reported studies according to whether the breast cancers occurred premenopausally or postmenopausally. The clinical significance of these emerging findings remains to be defined.

Ethnicity has been inconsistently associated with breast cancer in earlier studies that did not examine associations with genetic mutations or polymorphisms. Even when associations with ethnic factors have been identified, the magnitude of the associations has often been modest. Such inconsistently identified, weak associations with ethnicity may well have been due to uncontrolled confounding by reproductive factors and other established risk factors for breast cancer, rather than to genetic factors such as specific mutations of BRCA1 and BRCA2 breast cancer genes that are now known to occur with increased frequency in certain populations due to founder effects. Nevertheless, the use of genetic markers in epidemiologic studies may help to clarify associations with purported risk factors for breast cancer where the causality of the associations or biologic mechanisms are uncertain.

Other Risk Factors for Ovarian Cancer
Other risk factors for ovarian cancer include age, demographics, and reproductive and surgical history. (Refer to the PDQ summary on Prevention of Ovarian Cancer for more information.) Relatively few studies have addressed the effect of these risk factors in women who are genetically susceptible to ovarian cancer.

Age
Risk for ovarian cancer increases as a woman gets older. Before age 30 years, the risk of developing ovarian cancer is remote; even in hereditary cancer families, epithelial ovarian cancer is virtually nonexistent before age 20 years. Ovarian cancer incidence rises in a linear fashion from age 30 years to age 50 years and continues to increase, although at a slower rate, thereafter. The highest incidence is found in the eighth decade of life, with a rate of 57 cases per 100,000 women aged 75 to 79 years, compared with 16 cases per 100,000 women aged 40 to 44 years.[68]

Demographic
Ovarian cancer incidence varies significantly depending on country of birth, and ranges from a high of 14.9 cases per 100,000 women in Sweden to a low of 2.7 cases per 100,000 women in Japan.[69] Incidence in the United States is 13.3 cases per 100,000 women. Immigration appears to alter the risk to match that of the host country. Offspring of Japanese immigrants to the United States have an increased risk of developing ovarian cancer that approaches the rate among women born in the United States, indicating a possible role for dietary and environmental factors.

Reproductive
Nulliparity is associated with an increased risk of ovarian cancer. Risk may also be increased among women who have used fertility drugs, especially those who remain nulligravid.[70] A small subset from a large retrospective cohort study did not confirm a strong link between infertility drugs and ovarian cancer risk.[71] Evidence is growing that the use of menopausal hormone replacement therapy is associated with an increased risk of ovarian cancer, particularly in long-time users and users of sequential estrogen-progesterone schedules.[72,73] In a prospective study of 329 incident ovarian cancer cases in the Breast Cancer Detection Demonstration Project, use of estrogen only was associated with a significant 60% increased risk of ovarian cancer, and the risk increased with increasing duration of use.[74] In the WHI, 38 incident ovarian cancers were identified, and the hazard ratio for those taking estrogen plus progestin was 1.6 (95% CI 0.8-3.2) compared with the placebo group.[75] No data exist regarding risk either in those with a family history of breast or ovarian cancer or in BRCA1/2 mutation carriers. Data on the role of age at menarche and age at menopause are inconsistent.

Surgical History
Bilateral tubal ligation and hysterectomy have also been reported to be associated with reduced ovarian cancer risk.[70,76,77] A retrospective study and a prospective study have reported a >90% reduction in risk of ovarian cancer in women with documented BRCA1 or BRCA2 mutations who chose prophylactic oophorectomy. In this same population, prophylactic removal of the ovaries also resulted in a nearly 50% reduction in the risk of subsequent breast cancer.[78,79] For further information on these studies refer to the Ovarian Ablation section of this summary.

Models for Prediction of Breast Cancer Risk
Models to predict an individual’s lifetime risk for developing breast cancer are available. In addition, models exist to predict an individual’s likelihood of having a BRCA1 or BRCA2 mutation. Not all models can be appropriately applied for all patients. Each model is appropriate only when the patient’s characteristics and family history are similar to the study population on which the model was based. The table, Characteristics of the Gail and Claus Models, summarizes the salient aspects of the risk assessment models and is designed to aid in choosing the one that best applies to a particular individual.

Two models for predicting breast cancer risk, the Claus model [23] and the Gail model,[51] are widely used in research studies and clinical counseling. Both have limitations, and the risk estimates derived from the 2 models may differ for an individual patient. These models, however, represent the best methods currently available for individual risk assessment.

It is important to note that these models will significantly underestimate breast cancer risk for women in families with hereditary breast cancer susceptibility syndromes. In those cases, Mendelian risks would apply. A 3-generation cancer family history is taken before applying any model. (Refer to the PDQ summary on Elements of Cancer Genetics Risk Assessment and Counseling for more information on Taking a Family History.) Generally, the Claus or Gail models should not be used for families with 1 of the following characteristics:

Three individuals with breast or ovarian cancer (especially when 1 or more breast cancers are diagnosed before age 50 years).
A woman who has both breast and ovarian cancer.
Ashkenazi Jewish ancestry with at least 1 case of breast or ovarian cancer (as these families are more likely to have a hereditary cancer susceptibility syndrome).
Characteristics of the Gail and Claus Models*
Enlarge Table Gail Model Claus Model
*Adapted from Domcheck et al.,[80] Rubenstein et al.,[81] and Rhodes.[82]
Data derived from Breast Cancer Detection Demonstration Project (BCDDP) Study Cancer and Steroid Hormone (CASH) Study
Study population 2,852 cases, age ≥35 years 4,730 cases, age 20-54 years
In situ and invasive cancer Invasive cancer
3,146 controls 4,688 controls
Caucasian Caucasian
Annual screening Not routinely screened
Family history characteristics First-degree relatives with breast cancer First-degree or second-degree relatives with breast cancer
Age of onset in relatives
Other characteristics Current age Current age
Age at menarche
Age at first live birth
Number of breast biopsies
Atypical hyperplasia in breast biopsy
Race (included in the most current version of the Gail model)
Strengths Incorporates: Incorporates:
Risk factors other than family history Paternal as well as maternal history
Age of onset of breast cancer
Family history of ovarian cancer
Limitations Underestimates risk in hereditary families May underestimate risk in hereditary families
Number of breast biopsies without atypical hyperplasia may cause inflated risk estimates May not be applicable to all combinations of affected relatives
Does not include risk factors other than family history
Does not incorporate:
Paternal family history of breast cancer or any family history of ovarian cancer
Age of onset of breast cancer in relatives
All known risk factors for breast cancer [82]
Best application For individuals with no family history of breast cancer or 1 first-degree relative with breast cancer at ≥age 50 years For individuals with 0, 1, or 2 first-degree or second-degree relatives with breast cancer
For determining eligibility for chemoprevention studies

The Gail model has been found to be reasonably accurate at predicting breast cancer risk in large groups of white women who undergo annual screening mammography.[83-87] While the model is reliable in predicting the number of breast cancer cases expected in a group of women from the same age-risk strata, it is less reliable in predicting risk for individual patients. Risk can be overestimated in:

Noncompliant women (i.e., not compliant with screening).[83,84]
Women in the highest risk strata.[86]
Risk could be underestimated in the lowest risk strata.[86] Earlier studies [83,84] suggested risk was overpredicted in younger women and underpredicted in older women. More recent studies [85,86] using the modified Gail model (which is currently used) found it performed well in all age groups. Further studies are needed to establish the validity of the Gail model in minority populations.[87]

A study of 491 women aged 18 to 74 years with a family history of breast cancer compared the most recent Gail model and the Claus model in predicting breast cancer risk.[88] The 2 models were positively correlated ®=.55). The Gail model estimates were higher than the Claus model estimates for most participants. Presentation and discussion of both the Gail and Claus models risk estimates may be useful in the counseling setting.

The Gail model is the basis for the Breast Cancer Risk Assessment Tool, a computer program that is available from the NCI by calling the Cancer Information Service at 1-800-4-CANCER (1-800-422-6237, or TTY at 1-800-332-8615). This version of the Gail Model estimates only the risk of invasive breast cancer.

References

American Cancer Society.: Cancer Facts and Figures 2004. Atlanta, Ga: American Cancer Society, 2004. Also available online. Last accessed September 27, 2004.

Yang Q, Khoury MJ, Rodriguez C, et al.: Family history score as a predictor of breast cancer mortality: prospective data from the Cancer Prevention Study II, United States, 1982-1991. Am J Epidemiol 147 (7): 652-9, 1998. [PUBMED Abstract]

Colditz GA, Willett WC, Hunter DJ, et al.: Family history, age, and risk of breast cancer. Prospective data from the Nurses’ Health Study. JAMA 270 (3): 338-43, 1993. [PUBMED Abstract]

Slattery ML, Kerber RA: A comprehensive evaluation of family history and breast cancer risk. The Utah Population Database. JAMA 270 (13): 1563-8, 1993. [PUBMED Abstract]

Johnson N, Lancaster T, Fuller A, et al.: The prevalence of a family history of cancer in general practice. Fam Pract 12 (3): 287-9, 1995. [PUBMED Abstract]

Pharoah PD, Day NE, Duffy S, et al.: Family history and the risk of breast cancer: a systematic review and meta-analysis. Int J Cancer 71 (5): 800-9, 1997. [PUBMED Abstract]

Negri E, Braga C, La Vecchia C, et al.: Family history of cancer and risk of breast cancer. Int J Cancer 72 (5): 735-8, 1997. [PUBMED Abstract]

Hemminki K, Vaittinen P: Familial breast cancer in the family-cancer database. Int J Cancer 77 (3): 386-91, 1998. [PUBMED Abstract]

Kerber RA, Slattery ML: The impact of family history on ovarian cancer risk. The Utah Population Database. Arch Intern Med 155 (9): 905-12, 1995. [PUBMED Abstract]

Auranen A, Pukkala E, Mäkinen J, et al.: Cancer incidence in the first-degree relatives of ovarian cancer patients. Br J Cancer 74 (2): 280-4, 1996. [PUBMED Abstract]

Couch FJ, DeShano ML, Blackwood MA, et al.: BRCA1 mutations in women attending clinics that evaluate the risk of breast cancer. N Engl J Med 336 (20): 1409-15, 1997. [PUBMED Abstract]

Shattuck-Eidens D, Oliphant A, McClure M, et al.: BRCA1 sequence analysis in women at high risk for susceptibility mutations. Risk factor analysis and implications for genetic testing. JAMA 278 (15): 1242-50, 1997. [PUBMED Abstract]

Schildkraut JM, Thompson WD: Familial ovarian cancer: a population-based case-control study. Am J Epidemiol 128 (3): 456-66, 1988. [PUBMED Abstract]

Kerlikowske K, Brown JS, Grady DG: Should women with familial ovarian cancer undergo prophylactic oophorectomy? Obstet Gynecol 80 (4): 700-7, 1992. [PUBMED Abstract]

Stratton JF, Pharoah P, Smith SK, et al.: A systematic review and meta-analysis of family history and risk of ovarian cancer. Br J Obstet Gynaecol 105 (5): 493-9, 1998. [PUBMED Abstract]

Lindor NM, Greene MH: The concise handbook of family cancer syndromes. Mayo Familial Cancer Program. J Natl Cancer Inst 90 (14): 1039-71, 1998. [PUBMED Abstract]

Kerber RA, Slattery ML: Comparison of self-reported and database-linked family history of cancer data in a case-control study. Am J Epidemiol 146 (3): 244-8, 1997. [PUBMED Abstract]

Parent ME, Ghadirian P, Lacroix A, et al.: The reliability of recollections of family history: implications for the medical provider. J Cancer Educ 12 (2): 114-20, 1997 Summer. [PUBMED Abstract]

Feuer EJ, Wun LM, Boring CC, et al.: The lifetime risk of developing breast cancer. J Natl Cancer Inst 85 (11): 892-7, 1993. [PUBMED Abstract]

Malone KE, Daling JR, Thompson JD, et al.: BRCA1 mutations and breast cancer in the general population: analyses in women before age 35 years and in women before age 45 years with first-degree family history. JAMA 279 (12): 922-9, 1998. [PUBMED Abstract]

Newman B, Mu H, Butler LM, et al.: Frequency of breast cancer attributable to BRCA1 in a population-based series of American women. JAMA 279 (12): 915-21, 1998. [PUBMED Abstract]

Ford D, Easton DF, Stratton M, et al.: Genetic heterogeneity and penetrance analysis of the BRCA1 and BRCA2 genes in breast cancer families. The Breast Cancer Linkage Consortium. Am J Hum Genet 62 (3): 676-89, 1998. [PUBMED Abstract]

Claus EB, Risch N, Thompson WD: Autosomal dominant inheritance of early-onset breast cancer. Implications for risk prediction. Cancer 73 (3): 643-51, 1994. [PUBMED Abstract]

Colditz GA, Rosner BA, Speizer FE: Risk factors for breast cancer according to family history of breast cancer. For the Nurses’ Health Study Research Group. J Natl Cancer Inst 88 (6): 365-71, 1996. [PUBMED Abstract]

Narod S, Lynch H, Conway T, et al.: Increasing incidence of breast cancer in family with BRCA1 mutation. Lancet 341 (8852): 1101-2, 1993. [PUBMED Abstract]

Narod SA, Goldgar D, Cannon-Albright L, et al.: Risk modifiers in carriers of BRCA1 mutations. Int J Cancer 64 (6): 394-8, 1995. [PUBMED Abstract]

Collaborative Group on Hormonal Factors in Breast Cancer.: Breast cancer and breastfeeding: collaborative reanalysis of individual data from 47 epidemiological studies in 30 countries, including 50302 women with breast cancer and 96973 women without the disease. Lancet 360 (9328): 187-95, 2002. [PUBMED Abstract]

Jernström H, Lubinski J, Lynch HT, et al.: Breast-feeding and the risk of breast cancer in BRCA1 and BRCA2 mutation carriers. J Natl Cancer Inst 96 (14): 1094-8, 2004. [PUBMED Abstract]

Breast cancer and hormonal contraceptives: collaborative reanalysis of individual data on 53 297 women with breast cancer and 100 239 women without breast cancer from 54 epidemiological studies. Collaborative Group on Hormonal Factors in Breast Cancer. Lancet 347 (9017): 1713-27, 1996. [PUBMED Abstract]

Ursin G, Henderson BE, Haile RW, et al.: Does oral contraceptive use increase the risk of breast cancer in women with BRCA1/BRCA2 mutations more than in other women? Cancer Res 57 (17): 3678-81, 1997. [PUBMED Abstract]

Narod SA, Dubé MP, Klijn J, et al.: Oral contraceptives and the risk of breast cancer in BRCA1 and BRCA2 mutation carriers. J Natl Cancer Inst 94 (23): 1773-9, 2002. [PUBMED Abstract]

Breast cancer and hormone replacement therapy: collaborative reanalysis of data from 51 epidemiological studies of 52,705 women with breast cancer and 108,411 women without breast cancer. Collaborative Group on Hormonal Factors in Breast Cancer. Lancet 350 (9084): 1047-59, 1997. [PUBMED Abstract]

Chen CL, Weiss NS, Newcomb P, et al.: Hormone replacement therapy in relation to breast cancer. JAMA 287 (6): 734-41, 2002. [PUBMED Abstract]

Writing Group for the Women’s Health Initiative Investigators.: Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results From the Women’s Health Initiative randomized controlled trial. JAMA 288 (3): 321-33, 2002. [PUBMED Abstract]

Chlebowski RT, Hendrix SL, Langer RD, et al.: Influence of estrogen plus progestin on breast cancer and mammography in healthy postmenopausal women: the Women’s Health Initiative Randomized Trial. JAMA 289 (24): 3243-53, 2003. [PUBMED Abstract]

Schuurman AG, van den Brandt PA, Goldbohm RA: Exogenous hormone use and the risk of postmenopausal breast cancer: results from The Netherlands Cohort Study. Cancer Causes Control 6 (5): 416-24, 1995. [PUBMED Abstract]

Steinberg KK, Thacker SB, Smith SJ, et al.: A meta-analysis of the effect of estrogen replacement therapy on the risk of breast cancer. JAMA 265 (15): 1985-90, 1991. [PUBMED Abstract]

Sellers TA, Mink PJ, Cerhan JR, et al.: The role of hormone replacement therapy in the risk for breast cancer and total mortality in women with a family history of breast cancer. Ann Intern Med 127 (11): 973-80, 1997. [PUBMED Abstract]

Stanford JL, Weiss NS, Voigt LF, et al.: Combined estrogen and progestin hormone replacement therapy in relation to risk of breast cancer in middle-aged women. JAMA 274 (2): 137-42, 1995. [PUBMED Abstract]

Colditz GA, Egan KM, Stampfer MJ: Hormone replacement therapy and risk of breast cancer: results from epidemiologic studies. Am J Obstet Gynecol 168 (5): 1473-80, 1993. [PUBMED Abstract]

Gorsky RD, Koplan JP, Peterson HB, et al.: Relative risks and benefits of long-term estrogen replacement therapy: a decision analysis. Obstet Gynecol 83 (2): 161-6, 1994. [PUBMED Abstract]

Helzlsouer KJ, Harris EL, Parshad R, et al.: Familial clustering of breast cancer: possible interaction between DNA repair proficiency and radiation exposure in the development of breast cancer. Int J Cancer 64 (1): 14-7, 1995. [PUBMED Abstract]

Helzlsouer KJ, Harris EL, Parshad R, et al.: DNA repair proficiency: potential susceptiblity factor for breast cancer. J Natl Cancer Inst 88 (11): 754-5, 1996. [PUBMED Abstract]

Gowen LC, Avrutskaya AV, Latour AM, et al.: BRCA1 required for transcription-coupled repair of oxidative DNA damage. Science 281 (5379): 1009-12, 1998. [PUBMED Abstract]

Abbott DW, Freeman ML, Holt JT: Double-strand break repair deficiency and radiation sensitivity in BRCA2 mutant cancer cells. J Natl Cancer Inst 90 (13): 978-85, 1998. [PUBMED Abstract]

Easton DF: Cancer risks in A-T heterozygotes. Int J Radiat Biol 66 (6 Suppl): S177-82, 1994. [PUBMED Abstract]

Kastan M: Ataxia-telangiectasia–broad implications for a rare disorder. N Engl J Med 333 (10): 662-3, 1995. [PUBMED Abstract]

Hisada M, Garber JE, Fung CY, et al.: Multiple primary cancers in families with Li-Fraumeni syndrome. J Natl Cancer Inst 90 (8): 606-11, 1998. [PUBMED Abstract]

Kleihues P, Schäuble B, zur Hausen A, et al.: Tumors associated with p53 germline mutations: a synopsis of 91 families. Am J Pathol 150 (1): 1-13, 1997. [PUBMED Abstract]

Pierce LJ, Strawderman M, Narod SA, et al.: Effect of radiotherapy after breast-conserving treatment in women with breast cancer and germline BRCA1/2 mutations. J Clin Oncol 18 (19): 3360-9, 2000. [PUBMED Abstract]

Gail MH, Brinton LA, Byar DP, et al.: Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. J Natl Cancer Inst 81 (24): 1879-86, 1989. [PUBMED Abstract]

Dupont WD, Page DL: Risk factors for breast cancer in women with proliferative breast disease. N Engl J Med 312 (3): 146-51, 1985. [PUBMED Abstract]

Carter CL, Corle DK, Micozzi MS, et al.: A prospective study of the development of breast cancer in 16,692 women with benign breast disease. Am J Epidemiol 128 (3): 467-77, 1988. [PUBMED Abstract]

London SJ, Connolly JL, Schnitt SJ, et al.: A prospective study of benign breast disease and the risk of breast cancer. JAMA 267 (7): 941-4, 1992. [PUBMED Abstract]

Dupont WD, Page DL, Parl FF, et al.: Long-term risk of breast cancer in women with fibroadenoma. N Engl J Med 331 (1): 10-5, 1994. [PUBMED Abstract]

Unic I, Stalmeier PF, Peer PG, et al.: A review on family history of breast cancer: screening and counseling proposals for women with familial (non-hereditary) breast cancer. Patient Educ Couns 32 (1-2): 117-27, 1997 Sep-Oct. [PUBMED Abstract]

Boyd NF, Byng JW, Jong RA, et al.: Quantitative classification of mammographic densities and breast cancer risk: results from the Canadian National Breast Screening Study. J Natl Cancer Inst 87 (9): 670-5, 1995. [PUBMED Abstract]

Byrne C, Schairer C, Wolfe J, et al.: Mammographic features and breast cancer risk: effects with time, age, and menopause status. J Natl Cancer Inst 87 (21): 1622-9, 1995. [PUBMED Abstract]

Pankow JS, Vachon CM, Kuni CC, et al.: Genetic analysis of mammographic breast density in adult women: evidence of a gene effect. J Natl Cancer Inst 89 (8): 549-56, 1997. [PUBMED Abstract]

Boyd NF, Lockwood GA, Martin LJ, et al.: Mammographic densities and risk of breast cancer among subjects with a family history of this disease. J Natl Cancer Inst 91 (16): 1404-8, 1999. [PUBMED Abstract]

Vachon CM, King RA, Atwood LD, et al.: Preliminary sibpair linkage analysis of percent mammographic density. J Natl Cancer Inst 91 (20): 1778-9, 1999. [PUBMED Abstract]

Kelsey JL, Gammon MD: The epidemiology of breast cancer. CA Cancer J Clin 41 (3): 146-65, 1991 May-Jun. [PUBMED Abstract]

Singletary SE, Taylor SH, Guinee VF, et al.: Occurrence and prognosis of contralateral carcinoma of the breast. J Am Coll Surg 178 (4): 390-6, 1994. [PUBMED Abstract]

Cook LS, White E, Schwartz SM, et al.: A population-based study of contralateral breast cancer following a first primary breast cancer (Washington, United States) Cancer Causes Control 7 (3): 382-90, 1996. [PUBMED Abstract]

Habel LA, Moe RE, Daling JR, et al.: Risk of contralateral breast cancer among women with carcinoma in situ of the breast. Ann Surg 225 (1): 69-75, 1997. [PUBMED Abstract]

Bodian CA, Perzin KH, Lattes R: Lobular neoplasia. Long term risk of breast cancer and relation to other factors. Cancer 78 (5): 1024-34, 1996. [PUBMED Abstract]

Ambrosone CB, Freudenheim JL, Graham S, et al.: Cigarette smoking, N-acetyltransferase 2 genetic polymorphisms, and breast cancer risk. JAMA 276 (18): 1494-501, 1996. [PUBMED Abstract]

Amos CI, Struewing JP: Genetic epidemiology of epithelial ovarian cancer. Cancer 71 (2 Suppl): 566-72, 1993. [PUBMED Abstract]

Heintz AP, Hacker NF, Lagasse LD: Epidemiology and etiology of ovarian cancer: a review. Obstet Gynecol 66 (1): 127-35, 1985. [PUBMED Abstract]

Whittemore AS, Harris R, Itnyre J: Characteristics relating to ovarian cancer risk: collaborative analysis of 12 US case-control studies. II. Invasive epithelial ovarian cancers in white women. Collaborative Ovarian Cancer Group. Am J Epidemiol 136 (10): 1184-203, 1992. [PUBMED Abstract]

Brinton LA, Lamb EJ, Moghissi KS, et al.: Ovarian cancer risk after the use of ovulation-stimulating drugs. Obstet Gynecol 103 (6): 1194-203, 2004. [PUBMED Abstract]

Rodriguez C, Patel AV, Calle EE, et al.: Estrogen replacement therapy and ovarian cancer mortality in a large prospective study of US women. JAMA 285 (11): 1460-5, 2001. [PUBMED Abstract]

Riman T, Dickman PW, Nilsson S, et al.: Hormone replacement therapy and the risk of invasive epithelial ovarian cancer in Swedish women. J Natl Cancer Inst 94 (7): 497-504, 2002. [PUBMED Abstract]

Lacey JV Jr, Mink PJ, Lubin JH, et al.: Menopausal hormone replacement therapy and risk of ovarian cancer. JAMA 288 (3): 334-41, 2002. [PUBMED Abstract]

Anderson GL, Judd HL, Kaunitz AM, et al.: Effects of estrogen plus progestin on gynecologic cancers and associated diagnostic procedures: the Women’s Health Initiative randomized trial. JAMA 290 (13): 1739-48, 2003. [PUBMED Abstract]

Tortolero-Luna G, Mitchell MF: The epidemiology of ovarian cancer. J Cell Biochem Suppl 23: 200-7, 1995. [PUBMED Abstract]

Hankinson SE, Hunter DJ, Colditz GA, et al.: Tubal ligation, hysterectomy, and risk of ovarian cancer. A prospective study. JAMA 270 (23): 2813-8, 1993. [PUBMED Abstract]

Kauff ND, Satagopan JM, Robson ME, et al.: Risk-reducing salpingo-oophorectomy in women with a BRCA1 or BRCA2 mutation. N Engl J Med 346 (21): 1609-15, 2002. [PUBMED Abstract]

Rebbeck TR, Lynch HT, Neuhausen SL, et al.: Prophylactic oophorectomy in carriers of BRCA1 or BRCA2 mutations. N Engl J Med 346 (21): 1616-22, 2002. [PUBMED Abstract]

Domchek SM, Eisen A, Calzone K, et al.: Application of breast cancer risk prediction models in clinical practice. J Clin Oncol 21 (4): 593-601, 2003. [PUBMED Abstract]

Rubinstein WS, O’Neill SM, Peters JA, et al.: Mathematical modeling for breast cancer risk assessment. State of the art and role in medicine. Oncology (Huntingt) 16 (8): 1082-94; discussion 1094, 1097-9, 2002. [PUBMED Abstract]

Rhodes DJ: Identifying and counseling women at increased risk for breast cancer. Mayo Clin Proc 77 (4): 355-60; quiz 360-1, 2002. [PUBMED Abstract]

Bondy ML, Lustbader ED, Halabi S, et al.: Validation of a breast cancer risk assessment model in women with a positive family history. J Natl Cancer Inst 86 (8): 620-5, 1994. [PUBMED Abstract]

Spiegelman D, Colditz GA, Hunter D, et al.: Validation of the Gail et al. model for predicting individual breast cancer risk. J Natl Cancer Inst 86 (8): 600-7, 1994. [PUBMED Abstract]

Rockhill B, Spiegelman D, Byrne C, et al.: Validation of the Gail et al. model of breast cancer risk prediction and implications for chemoprevention. J Natl Cancer Inst 93 (5): 358-66, 2001. [PUBMED Abstract]

Costantino JP, Gail MH, Pee D, et al.: Validation studies for models projecting the risk of invasive and total breast cancer incidence. J Natl Cancer Inst 91 (18): 1541-8, 1999. [PUBMED Abstract]

Bondy ML, Newman LA: Breast cancer risk assessment models: applicability to African-American women. Cancer 97 (1 Suppl): 230-5, 2003. [PUBMED Abstract]

McTiernan A, Kuniyuki A, Yasui Y, et al.: Comparisons of two breast cancer risk estimates in women with a family history of breast cancer. Cancer Epidemiol Biomarkers Prev 10 (4): 333-8, 2001. [PUBMED Abstract]


Share: