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Published in final edited form as: Cancer Epidemiol Biomarkers Prev. 2016 Apr 12;25(7):1059–1063. doi: 10.1158/1055-9965.EPI-16-0011

Parity and Oral Contraceptive Use in Relation to Ovarian Cancer Risk in Older Women

Valerie McGuire 1, Patricia Hartge 2, Linda M Liao 3, Rashmi Sinha 3, Leslie Bernstein 4, Alison J Canchola 5, Garnet L Anderson 6, Marcia L Stefanick 7, Alice S Whittemore 1
PMCID: PMC4930714  NIHMSID: NIHMS777738  PMID: 27197274

Abstract

Background

Several studies have suggested that the ovarian cancer risk reductions associated with parity and oral contraceptive use are weaker in postmenopausal than premenopausal women; yet little is known about the persistence of these reductions as women age. This question gains importance with the increasing numbers of older women in the population.

Methods

We addressed the question using data from three large US cohort studies involving 310,290 white women aged 50+ years at recruitment, of whom 1815 developed subsequent incident invasive epithelial ovarian cancer. We used Cox regression, stratified by cohort, to examine age-related trends in the hazard ratios per full-term pregnancy and per year of oral contraceptive use.

Results

The parity-associated risk reductions waned with age (P < 0.001 for trend in hazard ratio with increasing age), particularly among women aged 75 years or more, for whom we observed no association with parity. However we observed no such attenuation in the oral-contraceptive-associated risk reductions (P = 0.79 for trend in hazard ratio with increasing age).

Conclusion

These findings suggest that prior oral contraceptive use is important for ovarian cancer risk assessment among women of all ages, while the benefits of parity wane as women age.

Impact

This information, if duplicated in other studies, will be useful to preventive counseling and risk prediction, particularly for women at increased ovarian cancer risk due to a personal history of breast cancer or a family history of ovarian cancer.

Keywords: age trends, oral contraceptive use, ovarian cancer, parity

INTRODUCTION

A large and consistent body of evidence indicates that increased parity and duration of oral contraceptive (OC) use are associated with reduced risk of invasive epithelial ovarian cancer (EOC), a malignancy with a 44% five-year survival rate in the US (1). Specifically, the data suggest that each full-term pregnancy (FTP) confers a risk reduction of approximately 19% (2), and risks among women with three or more years of OC use are 30–50% lower than those of women with little or no use (2, 3).

The available data also suggest that these associations are weaker in postmenopausal than premenopausal women (47). However this observation is based largely on women aged less than 65 years, and little is known about the longer-term effects of pregnancy and OC use among women as they age. This question has important clinical and public health significance, as more than 80% of all EOCs now occur after age 50 years (8), and this age group represents an increasing proportion of women in developed countries. Thus the burden of this highly fatal cancer will continue to grow as population distributions of women become more heavily skewed toward older ages, and accurate assessment of women’s risks is critical for development of cost-effective preventive strategies.

Here we assess the existence and extent of age-related trends in the effects of parity and OC use in older women, using data from three large US cohort studies involving 310,290 white women aged 50 years or more at recruitment, of whom 1815 developed subsequent incident invasive EOC. The three studies were the NIH-AARP Diet and Health Study (hereafter called the AARP study), the California Teachers Study (CTS), and the Women’s Health Initiative (WHI).

MATERIALS AND METHODS

Study population

The AARP Study, established in 1995–96, included 339,669 male and 222,732 female AARP members aged 50–71 years and residing in eight regions; California, Florida, Louisiana, New Jersey, North Carolina, Pennsylvania, and the metropolitan areas of Atlanta and Detroit. The CTS, established in 1995–96, included 133,479 female California public school professionals (active or retired) aged 22 years or more at recruitment. The WHI, established in 1993–98 and comprising longitudinal data from a randomized intervention trial and an observational study, includes 161,808 postmenopausal women aged 50–79 years, as identified by 40 US study sites. Details about the studies’ designs and characteristics have been described elsewhere (911).

Participants were potentially eligible for the current analysis if at recruitment they reported that they were white, aged 50 years or more, without prior invasive or noninvasive ovarian cancer diagnosis and without prior bilateral oophorectomy. A total of 318,709 participants met these criteria (155,636 from AARP, 50,772 from CTS, and 110,407 from the WHI trial and observational cohorts). Of these, 310,290 (154,045 from AARP, 47,365 from CTS and 108,880 from WHI) provided complete information on parity and duration of OC use, and were included in the analysis. Among the 108,880 eligible WHI subjects, 45,939 (42%) were trial participants. Of these, 16,208 participated in the Hormone Replacement Therapy (HRT) Trial and the remaining 29, 731 participated in one or both of the two diet trials (Diet Modification Trial and Calcium and Vitamin D Trial). Among the 16,208 HRT Trial participants, 10,373 also participated in one or both of the two dietary trials. We focused on parity and OC use because the three cohorts lacked comparable information on other covariates associated with ovarian cancer (e.g., tubal ligation, prior hysterectomy without bilateral oophorectomy, and duration of menopausal hormone therapy).

Ovarian cancer ascertainment

The AARP and CTS investigators identified incident ovarian cancer cases via linkages with cancer registries in the studies’ recruitment areas, while the WHI investigators did so using questionnaires mailed semi-annually during active intervention for clinical trial participants and annually otherwise. All three studies monitored participants’ vital statuses using the U.S. Social Security Administration Death Master File or the National Death Index. The present analysis includes invasive EOC’s diagnosed by December 31, 2006 (AARP), December 31, 2011 (CTS) and August 19, 2009 (WHI). EOC histology was available from the cancer registries for the AARP Study and CTS. In the WHI, all reported ovarian cancers were documented with medical records and pathology reports obtained at each clinic site and centrally reviewed and coded according to SEER standards (12).

Statistical methods

We performed left-truncated, right-censored survival analyses using Cox proportional hazards regression models stratified by cohort, with age as the underlying time variable. Each participant’s time-at-risk was left-truncated at the age she completed her baseline questionnaire, and right-censored at her age at first occurrence of the following events: last contact, death from any cause; diagnosis of any ovarian cancer (in-situ, low malignant potential, invasive epithelial, nonepithelial); bilateral oophorectomy subsequent to baseline questionnaire; and, for AARP and CTS, departure from the cohort catchment area (total US-SEER region for AARP and California for CTS).

All regressions included parity (coded as categorical or as ordinal variable), years of oral contraceptive use, (coded as categorical or as continuous variable) and year of birth (coded as continuous variable). We lacked data on recency of OC use. We used likelihood ratio statistics to evaluate age-related trends in the hazard-ratios (HRs) per full-term pregnancy and per 5-years of OC use. For example, we tested the null hypothesis of no age-related trend in parity-specific HRs by comparing the likelihood of the basic model that includes parity as ordinal variable (adjusted for OC use and birth year as continuous variables) with that of an expanded model that also includes terms for the product of parity and an ordinal variable for the three age-at-risk categories 50–64, 65–74 and 75+ years. We also used likelihood ratio statistics to evaluate age-related heterogeneity in EOC histology and cohort-heterogeneity in age-specific hazard ratios for parity and OC use. Analyses were implemented using SAS statistical software 9.4 (SAS Institute, Cary, NC). All tests of statistical significance are two-sided.

This research was approved by the Institutional Review Boards at the three study sites and at Stanford University School of Medicine.

RESULTS

Table 1 presents selected characteristics of the three cohorts, and the distributions of their eligible participants according to year of birth, age at recruitment, parity and years of OC use. Participants contributed, on average, 10.5 person-years at risk (PYRs) with overall standard deviation (SD) given by 3.3 PYRs. Corresponding cohort-specific values were 9.8 (SD = 2.2) for AARP, 13.0 (SD = 4.7) for CTS and 10.3 (SD = 3.3) for WHI, during which a total of 1815 EOCs were diagnosed. The crude incidence rates (CIRs) are higher than the US SEER rates for white women of similar ages, a difference that reflects the requirement here that time at risk of ovarian cancer be contributed only by participants with at least one intact ovary. (We checked this assertion by applying the SEER rates to the person-years at risk contributed by an expanded AARP cohort supplemented by women who reported a prior bilateral oophorectomy, and found that the expected number of cases was similar to the number observed in the cohort.) As expected, the CIRs decreased with increasing year of birth, increasing number of FTPs, increasing years of OC use, and decreasing age at recruitment.

Table 1.

Distribution of Participants, Person-years at Risk (PYR) and Invasive Epithelial Ovarian Cancers (EOCs), by Study Site

AARP CTS WHI Total

N PYRs EOCs CIRb N PYRs EOCs CIR N PYRs EOCs CIR N PYRs EOCs CIR
All participants 154,045 1,508,720 836 55.4 47,365 617,526 380 61.5 108,880 1,120,878 599 53.4 310,290 3,247,124 1815 55.9
Year of birth <1930 44,444 427,330 305 71.4 17,614 204,446 171 83.6 40,341 394,481 227 57.5 102,399 1,026,261 703 68.5
1930–39 80,326 789,177 406 51.5 15,102 207,323 125 60.3 47,158 494,275 285 57.7 142,586 1,490,773 816 54.7
1940+ 29,275 292,213 125 42.8 14,649 205,757 84 40.8 21,381 232,122 87 37.5 65,305 730,090 296 40.5
Age (yrs) at
recruitment
50–64 100,651 995,395 473 47.5 28,384 394,815 192 48.6 61,277 651,837 323 49.6 190,312 2,042,047 988 48.4
65–74 53,394 513,325 363 70.7 11,448 149,893 131 87.4 40,456 404,786 232 57.3 105,298 1,068,004 726 68.0
75+ -- -- -- 7,533 72,818 57 78.3 7,147 64,255 44 68.5 14,680 137,073 101 73.7
Number of
FTPsa
0 23,838 233,185 162 69.5 9,775 125,271 92 73.4 12,369 127,660 77 60.3 45,982 486,116 331 68.1
1–2 56,154 552,485 318 57.6 21,675 282,897 172 60.8 35,900 370,582 215 58.0 113,729 1,205,964 717 59.5
3–4 57,500 562,992 292 51.9 13,895 182,942 108 59.0 44,318 457,568 230 50.3 115,713 1,203,502 630 52.4
5+ 16,553 160,058 64 40.0 2,020 26,416 8 30.3 16,293 165,068 77 46.7 34,866 351,542 149 42.4
Yrs OC use <1 91,827 896,198 566 63.2 26,193 324,358 252 77.7 72,027 729,214 426 58.4 190,047 1,949,770 1244 63.8
1–4 27,529 270,681 131 48.4 8,170 113,004 56 49.6 15,821 168,234 73 43.4 51,520 551,920 260 47.1
5–9 19,536 192,573 89 46.2 7,085 98,058 39 39.8 10,752 114,780 58 50.5 37,373 405,410 186 45.9
10+ 15,153 149,268 50 33.5 5,917 82,106 33 40.2 10,280 108,650 42 38.7 31,350 340,024 125 36.8
a

FTP = full-term pregnancy

b

CIR = crude incidence rate (# EOCs per 100,000 PYRs)

Table 2 shows that most EOCs were classified as serous cancers (49.7% serous, versus 22.1% non-serous and 28.2% other/unspecified EOCs cancers). The proportion of serous EOCs among those of known histology did not vary significantly with age at risk (χ22=3.19, P = 0.20) for test of heterogeneity among the three age groups (data not shown).

Table 2.

Distribution of epithelial ovarian cancer (EOC) cases according to histological subtype, by cohort

AARP
N=836
CTS
n-380
WHI
N=599
Total
N=1815

N % N % N % N %
All cases 836 46.0 380 21.3 599 33.0 1815 100.0
  Serous 436 52.2 169 44.5 297 49.6 902 49.7
  Endometrioid 67 8.0 44 11.6 59 9.9 170 9.4
  Mucinous 36 4.3 13 3.4 21 3.5 70 3.9
  Clear Cell 26 3.1 20 5.3 30 5.0 76 4.2
  Undifferentiated/Unclassified 271 32.4 134 35.2 192 32.0 597 32.8

Table 3 shows EOC hazard ratios corresponding to parity and OC duration, for three age-at-risk categories: 50–64, 65–74 and 75+ years. The table shows clear patterns of decreasing EOC risk with increasing parity for women aged less than 75 years, with statistically significant risk reductions of 12% per full-term pregnancy (FTP) among women aged < 65 years, and 8% per FTP among women aged 65–74 years. However these patterns are not evident among women aged 75+ years. Indeed there is no decrease in the EOC hazard ratio with increasing FTPs (P < 0.001 for interaction between parity and age at risk).

Table 3.

Parity and Oral Contraceptive (OC) Use in Relation to Invasive Epithelial Ovarian Cancer (EOCs) Incidence, by Age at Risk

Age (years) at Risk

50 – 64 65 – 74 75 +
PYRsa EOCs CIRa HRb 95% CI PYRs EOCs CIR HR 95% CI PYRs EOCs CIR HR 95% CI
FTPc -- -- -- -- -- -- -- -- --
  0 209428.3 116 55.39 1.00 REF 194582.2 154 79.14 1.00 REF   82104.3 61 74.30 1.00 REF
  1–2 523337.8 206 39.36 0.93 0.75–1.16 485899.1 234 48.16 0.84 0.69–1.02 196728.6 100 50.83 1.01 0.75–1.37
  3–4 391339.8 173 44.21 0.69 0.54–0.89 587899.6 367 62.43 0.74 0.61–0.89 224262.1 166 74.02 0.98 0.72–1.32
  5+   82103.5 34 41.41 0.38 0.22–0.63 194164.4 135 69.53 0.56 0.43–0.73   75274.3 69 91.66 0.92 0.62–1.36
  Trend per
FTP
0.88 0.83–0.93 0.91 0.88–0.95 1.00 0.95–1.06
Pinteraction = <0.001 d
Yrs OC Use
  <1 508337.6 248 48.79 1.00 REF 963115.4 650 67.49 1.00 REF 478316.4 346 72.34 1.00 REF
  1–4 302470.8 125 41.33 0.85 0.68–1.06 208348.1 116 55.68 0.87 0.71–1.06    41101.4 19 46.23 0.65 0.41–1.03
  5–9 225398.2 94 41.70 0.86 0.67–1.09 151149.4 76 50.28 0.80 0.63–1.02    28862.5 16 55.44 0.77 0.46–1.27
  10+ 170002.8 62 55.39 0.73 0.55–0.97 139932.4 48 79.14 0.53 0.39–0.71    30089.0 15 74.30 0.70 0.42–1.18
  Trend per
5 yrs use
0.88 0.80–0.98 0.82 0.74–0.91 0.85 0.71–1.02
Pinteraction = 0.79e
a

PYRs = person-years at risk; CIR = crude incidence rate (# EOCs per 100,000 PRYs)

b

HR = hazard ratio from Cox regression with baseline hazard stratified by cohort. Parity HRs are adjusted for birth year and OC use, and OC HRs are adjusted for birth year and parity

c

FTP = full-term pregnancy

d

likelihood ratio χ22 test of hypothesis that risk per FTP does not vary with age at risk

e

likelihood ratio χ22 test of hypothesis that risk per 5 years of OC use does not vary with age at risk

In contrast, the lower EOC risk associated with duration of OC use did not vary with attained age (P = 0.79 for interaction). The risk reductions per five years of OC use ranged from 12% to 18% in the three age groups, with no evidence for differences among the attained age groups, and with an overall reduction of 14% (95% confidence interval: 8–20%) among all ages combined. Indeed, even in the highest age group, despite the relatively few person-years contributed by women with a history of OC use, we nevertheless observed a statistically significant risk reduction among OC users relative to nonusers, with only 50 ovarian cancer cases observed among users compared to 72.4 cases expected (P < 0.004). Overall, increasing duration of OC use was associated with decreasing risk: a model involving four duration categories provided better fit (P = 0.01) than one involving just two categories (use for less than or more than one year). These findings were similar when we restricted analysis to serous and to nonserous EOCs (data not shown). Restriction of analysis to EOC cases with specific nonserous histologies was precluded by the sparsity of these cases, as seen in Table 2. Finally, we found no evidence for inter-cohort heterogeneity in the hazard ratios associated with parity (nulliparous vs. parous; P = 0.39) or duration of OC use (less than one year vs. one or more years; P = 0.71).

DISCUSSION

We used data from Caucasian participants of three large prospective cohort studies to examine how the risk reductions associated with parity and OC use change as women age. We found age-related differences in the protective effects of parity, with significantly reduced parity-associated hazard ratios among women less than 75 years, but no effect at later ages. In contrast, we did not find evidence that the risk reductions associated with OC use wane with age among older women.

Interpreting these findings and their implications for the etiology and pathogenesis of EOC is challenging. Since the lag between last exposure and age at risk is likely to be greater for pregnancy than for OC use (which may end only at menopause), the observed lack of age-related trend in the effects of OC use could reflect its recency relative to that of pregnancy. Another issue is that the HR associated with OC use may be attenuated among women aged 50–60 years by their use of menopausal hormone therapy, which is positively correlated with OC use (13).

The observed temporal waning of the effects of pregnancy is consistent with the hypothesis that anovulation reduces a woman’s ovarian cancer risk by reducing her burden of mutated epithelial cells at risk of conversion to malignancy. These mutations may reflect some ovulatory consequence (such as rupture of the ovarian epithelium or cellular exposure to follicular fluid or to hormonal fluctuations). The long-term benefits of anovulation (i.e, reducing the burden of premalignant cells) may be attenuated by the occurrence of additional somatic mutations occurring as part of normal ovarian tissue aging (14, 15). The attenuation may be greater for pregnancy than OC use because pregnancies occurred in the more distant past. Alternatively, the attenuation may be more obvious for pregnancy than OC use because a year of pregnancy-induced anovulation confers a greater risk reduction at all ages than one due to OC use, possibly due to transient hormonal changes during pregnancy that induce apoptosis of existing premalignant cells (16).

The present combined analysis of large prospective cohorts has several advantages. Unlike retrospective case-control studies comparing prior oral contraceptive use as recalled by EOC cases with those of disease-free controls, the cohort design ascertains reproductive history at cohort entry relatively soon after menopause and before the onset of disease, and thus avoids potential long-term recall bias. However the combined analysis of large cohorts has weaknesses. In the present study, for example, the questionnaire data was too limited to allow evaluation of such factors as recency of anovulatory exposures to age at risk. Another limitation is the sparsity of OC-users who subsequently developed EOC at ages 75+ years (n = 50). These limitations emphasize the need for replication of the current observations in other large cohorts of older women.

In summary, the current data suggest that the protective effects of OC use persist for decades after the menopause, while the protection afforded by increased parity wanes in older women, particularly those aged 75 years of more. This information, if duplicated in other studies, will be useful to preventive counseling and risk prediction, particularly for women at elevated ovarian cancer risk due to a personal history of breast cancer or a family history of ovarian cancer.

Acknowledgments

We are indebted to the participants in the NIH-AARP Diet and Health Study for their outstanding cooperation. We also thank Sigurd Hermansen and Kerry Grace Morrissey from Westat for study outcomes ascertainment and management and Leslie Carroll at Information Management Services for data support and analysis. The authors also thank the WHI investigators and staff for their dedication, and the study participants for making the program possible. A full listing of WHI investigators can be found at: http://www.whi.org/researchers/Documents%20%20Write%20a%20Paper/WHI%20Investigator%20Short%20List.pdf. The authors wish to thank Pamela Horn-Ross and David Nelson from the California Teachers’ Study for helpful discussion.

FINANCIAL SUPPORT

This research was supported by National Institutes of Health grants R01CA094069 (A.S. Whittemore) and the Stanford Cancer Institute Developmental Cancer Research Award (A.S. Whittemore). The California Teachers Study was supported by RO1 CA77398 (L. Bernstein). The AARP program was supported [in part] by the Intramural Research Program of the National Institutes of Health, National Cancer Institute (http://dietandhealth.cancer.gov/acknowledgement.html) (P. Hartge, L.M. Liao, R. Sinha). The Women’s Health Initiative program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C (G.L. Anderson, M.L. Stefanick).

ABBREVIATIONS

AARP

American Association of Retired Persons

CI

confidence interval

CIR

crude incidence rate

CTS

California Teachers Study

EOC

epithelial ovarian cancer

FTP

full-term pregnancy

HR

hazard ratio

NIH

National Institutes of Health

OC

oral contraceptive

PYRs

person-years

WHI

Women’s Health Initiative

Footnotes

DISCLOSURE OF POTENTIAL CONFLICTS OF INTEREST

No potential conflicts of interest were disclosed.

REFERENCES

  • 1.Siegel RL, Miller KD, Jemal A. Cancer statistics 2015. CA: A Cancer Journal for Clinicians. 2015;65(1):5–29. doi: 10.3322/caac.21254. [DOI] [PubMed] [Google Scholar]
  • 2.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. 1992;136(10):1184–1203. doi: 10.1093/oxfordjournals.aje.a116427. [DOI] [PubMed] [Google Scholar]
  • 3.Collaborative Group on Epidemiological Studies of Ovarian Cancer. Beral V, Doll R, Hermon C, Peto R, Reeves G. Ovarian cancer and oral contraceptives: collaborative reanalysis of data from 45 epidemiological studies including 23,257 women with ovarian cancer and 87,303 controls. Lancet. 2008;371(9609):303–314. doi: 10.1016/S0140-6736(08)60167-1. [DOI] [PubMed] [Google Scholar]
  • 4.Moorman PG, Calingaert B, Palmieri RT, Iversen ES, Bentley RC, Halabi S, et al. Hormonal risk factors for ovarian cancer in premenopausal and postmenopausal women. Am J Epidemiol. 2008;167(9):1059–1069. doi: 10.1093/aje/kwn006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Tung KH, Wilkens LR, Wu AH, McDuffie K, Wilkens LR, Kolonel LN, et al. Effect of anovulation factors on pre- and postmenopausal ovarian cancer risk: revisiting the incessant ovulation hypothesis. Am J Epidemiol. 2005;161(4):321–329. doi: 10.1093/aje/kwi046. [DOI] [PubMed] [Google Scholar]
  • 6.Whittemore AS, Harris R, Itnyre J. Characteristics relating to ovarian cancer risk: collaborative analysis of 12 US case-control studies. IV. The pathogenesis of epithelial ovarian cancer. Collaborative Ovarian Cancer Group. Am J Epidemiol. 1992;136(10):1212–1220. doi: 10.1093/oxfordjournals.aje.a116429. [DOI] [PubMed] [Google Scholar]
  • 7.Whittemore AS. Personal characteristics relating to risk of invasive epithelial ovarian cancer in older women in the United States. Cancer. 1993;71(2 Suppl):558–565. doi: 10.1002/cncr.2820710211. [DOI] [PubMed] [Google Scholar]
  • 8.Howlader N, Noone AM, Krapcho M, Garshell J, Miller D, Altekruse SF, et al. SEER Cancer Statistics Review, 1975–2012. Bethesda, MD: National Cancer Institute; http://seer.cancer.gov/csr/1975_2012/, based on November 2014 SEER data submission, posted to the SEER web site, April 2015. [Google Scholar]
  • 9.Schatzkin A, Subar AF, Thompson FE, Harlan LC, Tangrea J, Hollenbeck AR, et al. Design and serendipity in establishing a large cohort with wide dietary intake distributions: the National Institutes of Health-American Association of Retired Persons Diet and Health Study. Am J Epidemiol. 2001;154(12):1119–1125. doi: 10.1093/aje/154.12.1119. [DOI] [PubMed] [Google Scholar]
  • 10.Hays J, Hunt JR, Hubbell FA, Anderson GL, Limacher M, Allen C, et al. The Women's Health Initiative recruitment methods and results. Ann Epidemiol. 2003;13(9 Suppl):S18–S77. doi: 10.1016/s1047-2797(03)00042-5. [DOI] [PubMed] [Google Scholar]
  • 11.Bernstein L, Allen M, Anton-Culver H, Deapen D, Horn-Ross PL, Peel D, et al. High breast cancer incidence rates among California teachers: results from the California Teachers Study (United States) Cancer Causes Control. 2002;13(7):625–635. doi: 10.1023/a:1019552126105. [DOI] [PubMed] [Google Scholar]
  • 12.Curb JD, McTiernan A, Heckbert SR, Kooperberg C, Stanford J, Nevitt M, et al. Outcomes ascertainment and adjudication methods in the Women's Health Initiative. Ann Epidemiol. 2003;13(9 Suppl):S122–S128. doi: 10.1016/s1047-2797(03)00048-6. [DOI] [PubMed] [Google Scholar]
  • 13.Norman SA, Berlin JA, Weber AL, Strom BL, Daling JR, Weiss LK, et al. Combined effect of oral contraceptive use and hormone replacement therapy on breast cancer risk in postmenopausal women. Cancer Causes Control. 2003;14:933–943. doi: 10.1023/b:caco.0000007967.25865.29. [DOI] [PubMed] [Google Scholar]
  • 14.Casagrande JT, Louie EW, Pike MC, Roy S, Ross RK, Henderson BE. "Incessant ovulation" and ovarian cancer. Lancet. 1979;2(8135):170–173. doi: 10.1016/s0140-6736(79)91435-1. [DOI] [PubMed] [Google Scholar]
  • 15.Pike MC. Age-related factors in cancers of the breast, ovary, and endometrium. J Chronic Dis. 1987;40(Suppl 2):59s–69s. doi: 10.1016/s0021-9681(87)80009-7. [DOI] [PubMed] [Google Scholar]
  • 16.Risch HA. Hormonal etiology of epithelial ovarian cancer, with a hypothesis concerning the role of androgens and progesterone. J Natl Cancer Inst. 1998;90(23):1774–1786. doi: 10.1093/jnci/90.23.1774. [DOI] [PubMed] [Google Scholar]

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