Hormonal risk factors and invasive epithelial ovarian cancer risk by parity.

A total of 125 437 women were included in the analysis, with 16 589 (13%) nulliparous women and 108 848 (87%) women who reported having had at least one live birth. During the study period, 623 women were diagnosed with invasive epithelial ovarian cancer; 102 (16%) were nulliparous and 521 (84%) reported having had at least one live birth. The median follow-up time for women in this analysis was 10.55 years (interquartile range: 10.52, 10.80 years). Characteristics of study participants according to parity status are shown in Table 1 . Nulliparous women were younger, had higher education, were more likely to never have been married and were less likely to have used OCs, HT or to have undergone hysterectomy or tubal ligation compared with parous women. Parous women were at a reduced risk of ovarian cancer compared with nulliparous women (HR=0.79, 95% CI: 0.63, 0.98) ( Table 2 ), with stronger reduction of the risk with more births ( P trend <0.001). There were no clear differences in the risk estimates for hormonal factors and other characteristics between parous and nulliparous women ( Table 3 ). The use of OC reduced the risk of ovarian cancer similarly in both nulliparous and parous women ( P -heterogeneity=0.98). Similar results were observed when analyses were restricted to nulliparous women who reported ever having been married (married, widowed, divorced, or separated) or living as married. Long duration of use of HT increased the risk in both groups of women ( Table 3 ). Compared with women who had an estimated number of 470 or more LOCs, both nulliparous and parous women with an estimated number of <330 LOCs had lower risk of ovarian cancer. First degree family history of breast and/or ovarian cancer increased the risk of ovarian cancer in both groups of women (HR=1.37, 95% CI: 0.81, 2.34 in nulliparous women; HR=1.21, 95% CI: 0.97, 1.51 in parous women) ( P -heterogeneity=0.60). BMI was associated with a non-statistically significant increased risk of ovarian cancer in nulliparous women (HR=1.36, 95% CI: 0.79, 2.36, comparing 25–29.9 kg m −2 to <25 kg m −2 ; HR=1.48, 95% CI: 0.61, 3.58 comparing 30 kg m −2 or more to <25 kg/m 2 ), but was unrelated to ovarian cancer risk in parous women (HR=0.84, 95% CI: 0.66, 1.07, comparing 25–29.9 kg m −2 with <25 kg/ m −2 ; HR=1.03, 95% CI: 0.69, 1.53 comparing 30 kg m −2 or more with <25 kg m −2 ) ( P -heterogeneity=0.15). BMI was still associated with a non-significant increased ovarian cancer risk among ever married nulliparous women although the association was attenuated (HR=1.33, 95% CI: 0.51, 3.47 comparing 30 kg m −2 or more to <25 kg m −2 ) ( P -heterogeneity=0.19). Compared with never smokers, nulliparous women who were current smokers were at an increased risk of ovarian cancer (HR=1.40, 95% CI: 0.78, 2.49), but the increased was not seen for parous women who were current smokers (HR=0.76, 95% CI: 0.55, 1.05) ( P -heterogeneity=0.10). Similar results were obtained when analyses were further adjusted by education level. We further explored whether the relationship between BMI and parity differed by the number of births among parous women ( Supplementary Table 1 ). Among the 108 370 parous women with information on number of births, there were 11 706 (10.8%) with one birth, 31 451 (29.0%) with two births, 48 397 (44.7%) with three or four births, and 16 816 (15.5%) with five or more births. Five-hundred seventeen invasive ovarian cancer cases among parous women had information on the number of births. Of these, 75 (14.5%) had one birth, 158 (30.6%) had two births, 225 (43.5%) had three to four births and 59 (11.4) had five or more births. Comparing nulliparous women with women with one, two, three to four or five or more births, there was no clear pattern of effect modification ( P -heterogeneity=0.05, 0.63, 0.14, and 0.35, respectively). As HT use has been suggested to modify the association between BMI and ovarian cancer, we additionally stratified the BMI analyses by HT use ( Table 4 ). Among never HT users, the association between BMI and ovarian cancer was stronger in nulliparous women compared with parous women, although the difference was not statistically significant ( P -heterogeneity=0.76). Among ever HT users, nulliparous women with BMI above 30 kg m −2 had a non-statistically significant higher risk of ovarian cancer compared with women with BMI <25 kg m −2 (HR=1.50, 95% CI: 0.57–3.92). This increased risk was not seen for parous women (HR=0.70, 95% CI: 0.44–1.11) ( P -heterogeneity=0.08). Finally, we did not observe a difference between histological subtypes of epithelial ovarian cancer (serous, mucinous, endometroid, clear cell, and other) and parity status (nulliparous vs parous) ( χ 2 -test P -value: 0.13) ( Supplementary Table 2 ).

We assessed whether the relationship between hormone-related factors and ovarian cancer risk differed between nulliparous and parous women using data from two large prospective cohorts. Overall, we did not observe significant differences in risk factor associations between nulliparous and parous women. We only found a suggestive difference of the associations between BMI and ovarian cancer risk in ever users of HT, whereby the estimated ovarian cancer risk associated with BMI was greater among nulliparous women than parous women. However, because of the number of tests performed, this finding could be due to chance. These data suggest that the impact of most factors on ovarian cancer risk is the same for nulliparous women as for parous women, even though ovarian cancer incidence is higher among nulliparous women. We found a suggestive difference between never vs current smokers and risk of ovarian cancer by parity. However, in a recent meta-analysis of 51 epidemiological studies, including the NIH-AARP study and the PLCO trial, there was no difference in ovarian cancer risk between never and current smokers when stratified by parity ( Collaborative Group on Epidemiological Studies of Ovarian Cancer et al , 2012 ). Given the small numbers of ovarian cancer cases who were current smokers in our study, this suggestive difference could just be chance. Previously, it had been found that BMI significantly increased the risk of ovarian cancer by a 2.5-fold in nulliparous women, but not in parous women ( Greer et al , 2006 ). We also observed that BMI increased the risk of ovarian cancer by nearly 1.5-fold in nulliparous women, albeit non-significant, but not in parous women. However, in both studies the test of heterogeneity did not reach statically significance ( P -interaction=0.06 in ( Greer et al , 2006 ) and P -interaction=0.15 in our study). A limitation of the study by Greer et al (2006) was the inclusion of pre- and postmenopausal women and the lack of information on HT use among postmenopausal women. It has been reported that BMI and HT may interact on the risk of ovarian cancer ( Leitzmann et al , 2009 ; Collaborative Group on Epidemiological Studies of Ovarian Cancer, 2012 ). We were able to look at this interaction separately among nulliparous and parous women, and found some differences in the magnitude of the associations, although the number of cases in these subgroups was too small to reach firm conclusions. However, it may be worthwhile to assess this association in larger studies. In a case–control study the use of OC did not reduce the risk of ovarian cancer in nulliparous women, but it was associated with a lower risk in parous women ( Ness et al , 2001 ). We did not observe any qualitative difference in the risk estimates for OC use between nulliparous and parous women. A previous prospective study based on 181 ovarian cancer cases found that the association between nulliparity and ovarian cancer was stronger among those with a first degree family history of breast or ovarian ( Vachon et al , 2002 ). While first degree family history of breast or ovarian cancer was more strongly associated with ovarian cancer in nulliparous than in parous women in our study, neither association reached statistical significance and our estimates were lower than those found earlier ( Vachon et al , 2002 ). The study by Vachon et al (2002) was also a prospective study of postmenopausal women with similar follow-up time, but our combined data set was larger (37 377 vs 125 437) and there were more incident epithelial ovarian cases (181 vs 623). However, there were a higher proportion of nulliparous women with missing information on family history than parous women in our study. Our study has several limitations. Despite combining two large studies, the number of cases was small and may have precluded us from observing statistically significant associations. However, our sample size was larger than any other previous study. Given the low incidence of ovarian cancer, a small number of cases is a common problem of prospective studies of this disease. Another limitation was that we did not have fertility information in the NIH-AARP study, and, therefore, we could not adjust for this variable, which may be particularly important in the nulliparous group. About 60% of the nulliparous women were ever married (married, widowed, divorced, or separated) or living as married. As these women might have reproductive and hormonal characteristics different from nulliparous women who were never married or did not live as married, we conducted sensitivity analyses restricted to women who were ever married or living as married. However, the results were similar to those presented in our tables. For some factors that have been associated with ovarian cancer, such as tubal ligation, endometriosis or infertility, information was only available in the PLCO data set, and the number of ovarian cancer cases among nulliparous women was too small ( N =8) to determine the ovarian cancer risk associated with them. Finally, we did not have follow-up information regarding oophorectomy after enrolment and, therefore, we could not censor women who removed their ovaries after the beginning of the study. Our study has several notable strengths such as the prospective design with long follow-up, a larger number of nulliparous women compared with previous studies, and the comprehensive assessment of hormonal risk factors. In summary, we did not observe significant differences in strengths of associations of known risk factors between among nulliparous and parous women. There was a suggestive interaction between BMI and parity in ever users of HT. Pooled analyses or larger studies are needed to provide more definitive and reliable evidence of this potential interaction.

Data from two prospective cohorts, the National Institutes of Health-AARP Diet and Health Study (NIH-AARP) ( Schatzkin et al , 2001 ) and the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) ( Prorok et al , 2000 ) were combined for this analysis ( Figure 1 ). Both studies have been previously described ( Prorok et al , 2000 ; Schatzkin et al , 2001 ). Briefly, the NIH-AARP study was established in 1995–1996 when over 500 000 AARP members, aged 50–71 in six states (California, Florida, Louisiana, New Jersey, North Carolina and Pennsylvania) and two metropolitan areas (Atlanta, GA, and Detroit, MI) satisfactorily completed a baseline questionnaire ( Schatzkin et al , 2001 ). A second questionnaire was sent in 1996–1997 to obtain additional risk factor information, including family history of breast and/or ovarian cancer. Information from both questionnaires was used in this analysis (baseline questionnaire collected in 1995–1996 and second questionnaire collected in 1996–1997). The last follow-up date for this study was 31 December 2006. The NIH-AARP study was approved by the Special Studies Institutional Review Board of the National Cancer Institute. The PLCO study is a multi-centre, randomised trial designed to evaluate screening modalities for prostate, lung, colon, and ovarian cancers ( Prorok et al , 2000 ). Participants were recruited between 1992 and 2001 and they were followed for up to 13 years. For this analysis, the last follow-up time for the PLCO was 31 December, 2006. At enrolment, women aged 55–74 years old, without a history of ovarian cancer completed a baseline questionnaire. Exposure data from this questionnaire, collected from 1992 to 2001, was used in the analysis. Only information from women in the screening arm of the PLCO study was available when these analyses were conducted. Informed consent for the PLCO was obtained from all women and each screening centre obtained approval by the local institutional review boards. In both studies, participants completed self-administered questionnaires or telephone-based interviews with information regarding demographic and lifestyle characteristics, as well as reproductive and medical history. Data from the both studies were harmonised into a single data set ( Supplementary Note ). Analyses were restricted to women who reported at age at menopause at the beginning of either study. National Institutes of Health-AARP participants were followed through the US Postal Service national database for address changes and cancers were ascertained by linkage to state cancer registries in the original recruitment areas plus three catchment areas that were common states of relocation (Arizona, Nevada, and Texas) ( Schatzkin et al , 2001 ). Vital status was updated from the US Social Security Administration Death Master File and the National Death Index Plus ( Schatzkin et al , 2001 ). The completeness of case ascertainment has been previously reported to have a minimum sensitivity of ∼90% and specificity of 99.5% compared with identification of cases by cancer registries ( Michaud et al , 2005 ). Follow-up in the PLCO was conducted from annual study update forms completed by participants or a proxy and subsequently confirmed from medical records, death certificates, and cancer registries ( Prorok et al , 2000 ). Subjects who did not return the questionnaire were contacted by repeat mailing or telephone to improve completeness of end point ascertainment. The outcome of interest for this analysis was primary invasive epithelial ovarian cancer. Using the International Classification of Diseases for Oncology, 3rd edition, (ICD-O-3) coding system ( Fritz et al , 2000 ), these were cases with C56.9 site codes and epithelial morphology (serous: 8441, 8460, 8461; endometrioid: 8380, 8381, 8560, 8570; mucinous: 8470, 8471, 8480, 8481; clear cell: 8310, 8313; and other epithelial: 8010, 8020, 8021, 8050, 8070, 8120, 8140, 8240, 8246, 8255, 8260,8323, 8440, 8450, 8490, 8562). Cox regression models were used to compute hazard ratios (HRs) and 95% CIs as measures of association between risk factors and incidence of ovarian cancer. Follow-up started at the age at the time of the second questionnaire for women in the NIH-AARP study or the age at the baseline questionnaire for women in the PLCO and ended at the age of diagnosis of invasive epithelial ovarian cancer or censoring at the age of death, loss of follow-up, or 31 December 2006, whichever occurred first. The baseline hazard function was stratified by study (PLCO vs AARP) in all models. Women who reported at least one live birth or provided an age at first birth were classified as parous and those who reported no age at first birth and no live births were considered nulliparous, similar to Schonfeld et al (2011) . Subjects were excluded from the analysis if they did not report age at menopause at the beginning of the study, had a bilateral oophorectomy or unknown ovarian surgery status, had a personal history of ovarian cancer, prevalent ovarian cancer at study enrolment, had missing information on parity, or if questionnaire information was obtained via proxy respondents (see Figure 1 ). Analyses were done separately for nulliparous and parous women from both cohorts combined. Analyses for nulliparous women were adjusted for BMI at study entry (continuous), duration of use of OC (never or <1/1–9/⩾10 years), duration of use of HT (never/<10/⩾10 years), first degree family history of breast and/or ovarian cancer (no/yes/missing). Analyses for parous women were adjusted for the same variables as nulliparous women and in addition for the number of live births in categories (1/2/3–4/⩾5). When models were additionally adjusted for education, marriage, age at menopause, age at menarche or hysterectomy status results did not significantly changed. To assess differences in effects by parity status, we compared a Cox model that combined the data of the nulliparous and parous women and was adjusted for all the above factors and parity (no/yes) to a similar model with an additional interaction term between parity and the risk factor of interest modelled as a continuous variable. Significance of the interaction term was determined by a likelihood-ratio test. The number of lifetime ovulatory cycles (LOCs) was computed using the model by Cramer et al (1995) that estimates LOC based on the age at menopause, age at menarche, time being pregnant, duration of OC, and the average cycle length. We assumed that the average cycle length of all participants was 28 days. Estimated LOCs from this model result in similar estimates as to those from other published models ( George, 2011 ). Quartiles of LOCs were defined based on their distribution in the entire study population. The proportional hazard assumption was tested based on the slope of the Schoenfeld's residuals ( Grambsch and Therneau, 1994 ). All statistical tests were two-sided and P -values <0.05 were considered statistical significant. Analyses were performed by using STATA, version 10.1, software (StataCorp LP, College Station, TX, USA).