Skip Navigation
Skip to contents

JPMPH : Journal of Preventive Medicine and Public Health

OPEN ACCESS
SEARCH
Search

Articles

Page Path
HOME > J Prev Med Public Health > Volume 49(6); 2016 > Article
Review
The Effect of Breastfeeding Duration and Parity on the Risk of Epithelial Ovarian Cancer: A Systematic Review and Meta-analysis
Ho Kyung Sung1orcid, Seung Hyun Ma1,2, Ji-Yeob Choi1,2,3, Yunji Hwang1,2,3, Choonghyun Ahn1,2,3, Byoung-Gie Kim4, Yong-Man Kim5, Jae Weon Kim6, Sokbom Kang7, Jaehoon Kim8, Tae Jin Kim9, Keun-Young Yoo1, Daehee Kang1,2,3, Suekyung Park1,2,3orcid
Journal of Preventive Medicine and Public Health 2016;49(6):349-366.
DOI: https://doi.org/10.3961/jpmph.16.066
Published online: September 8, 2016
  • 15,824 Views
  • 302 Download
  • 52 Crossref
  • 63 Scopus

1Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea

2Cancer Research Institute, Seoul National University, Seoul, Korea

3Department of Biomedical Science, Seoul National University Graduate School, Seoul, Korea

4Department of Obstetrics and Gynecology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea

5Department of Obstetrics and Gynecology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea

6Department of Obstetrics and Gynecology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea

7Department of Gynecologic Oncology, National Cancer Center, Goyang, Korea

8Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea

9Department of Obstetrics and Gynecology, Cheil General Hospital and Women’s Healthcare Center, Kwandong University College of Medicine, Seoul, Korea

Corresponding author: Suekyung Park, MD, PhD  103 Daehak-ro, Jongno-gu, Seoul 03080, Korea  Tel: +82-2-740-8338, Fax: +82-2-747-4830 E-mail: suepark@snu.ac.kr
• Received: June 29, 2016   • Accepted: September 8, 2016

Copyright © 2016 The Korean Society for Preventive Medicine

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

prev next
  • Objectives
    We conducted a systematic review and meta-analysis to summarize current evidence regarding the association of parity and duration of breastfeeding with the risk of epithelial ovarian cancer (EOC).
  • Methods
    A systematic search of relevant studies published by December 31, 2015 was performed in PubMed and EMBASE. A random-effect model was used to obtain the summary relative risks (RRs) and 95% confidence intervals (CIs).
  • Results
    Thirty-two studies had parity categories of 1, 2, and ≥3. The summary RRs for EOC were 0.72 (95% CI, 0.65 to 0.79), 0.57 (95% CI, 0.49 to 0.65), and 0.46 (95% CI, 0.41 to 0.52), respectively. Small to moderate heterogeneity was observed for one birth (p<0.01; Q=59.46; I2=47.9%). Fifteen studies had breastfeeding categories of <6 months, 6-12 months, and >13 months. The summary RRs were 0.79 (95% CI, 0.72 to 0.87), 0.72 (95% CI, 0.64 to 0.81), and 0.67 (95% CI, 0.56 to 0.79), respectively. Only small heterogeneity was observed for <6 months of breastfeeding (p=0.17; Q=18.79, I2=25.5%). Compared to nulliparous women with no history of breastfeeding, the joint effects of two births and <6 months of breastfeeding resulted in a 0.5-fold reduced risk for EOC.
  • Conclusions
    The first birth and breastfeeding for <6 months were associated with significant reductions in EOC risk.
Worldwide, ovarian cancer is the seventh most common cancer in women. Furthermore, it is the sixth leading cause of cancer deaths in women and the second most common cause of death among those with gynecologic cancers [1]. Approximately 90% of ovarian cancers are of epithelial origin [2], with the remaining 10% composed of sex cord-stromal tumors (5% to 8%), germ cell tumors (3% to 5%), and other rare types of ovarian cancer [3].
Most ovarian cancers are life-threatening and are notorious for having a poor prognosis, as they are usually diagnosed at an advanced stage. Moreover, screening results based on pelvic imaging or tumor markers for early detection remain unsatisfactory [4]. Therefore, to reduce the risk of ovarian cancer, primary prevention, such as avoiding risk factors or strengthening exposure to preventive factors, is important.
Reproductive risk factors for epithelial ovarian cancer (EOC) have been extensively explored in epidemiologic studies. For instance, a pooled analysis of 12 US case-control studies in 1992 showed that parous women and those who had breastfed had a lower risk of EOC [5,6]. The protective effect of parity and breastfeeding against EOC is biologically plausible and can be explained by two hypotheses: (1) the incessant ovulation hypothesis, in which monthly ovulation might increase the odds of genetic mutations, potentially leading to subsequent malignant changes [7], and (2) the gonadotropin hypothesis, in which ovarian overstimulation by elevated gonadotropins might trigger hyperproliferation, including subsequent malignant transformation [8]. A pooled analysis in 1992 showed that the greatest protection was associated with the first birth and the first few months of breastfeeding [5]. However, this was only observed in a pooled analysis of six population-based case-control studies, not in hospital-based case-control studies.
Since 1992, many studies from around the world have reported associations of parity and breastfeeding with ovarian cancer. However, findings concerning the protective role of increasing parity and duration of breastfeeding remain inconsistent. For parity, some studies have indicated that the first birth reduces ovarian cancer risk more than subsequent births [9-13]. In contrast, other studies have reported that the second birth was associated with a greater protective effect [14-16]. Likewise, for breastfeeding, some studies have indicated that the first six months of breastfeeding reduce risk more than a month of subsequent breastfeeding [17,18], whereas other studies have reported that each additional six months of breastfeeding confer approximately the same level of additional risk reduction [12,19].
Therefore, we conducted a systematic review and meta-analysis to summarize the current evidence regarding the association of parity and duration of breastfeeding with EOC risk. The aim of this study was to clarify the threshold for risk reduction among the studies without heterogeneity across the results. An additional aim was to perform a meta-analysis to estimate the joint risk reductions associated with parity and breastfeeding.
Search Strategy
We performed a literature search including studies published through December 2015 using the following search terms in the PubMed and EMBASE databases (1) (parity or “number of live births”) and (ovary or ovarian) and (cancer or tumor or neoplasm or malignancy) or (2) (breastfeeding or lactation) and (ovary or ovarian) and (cancer or tumor or neoplasm or malignancy). Furthermore, to find any additional published studies, a manual search was performed by checking all references of prior meta-analyses [5,6.8,20-23] and of all the original studies. This systematic review was planned, conducted, and reported in adherence to the standards of quality for reporting meta-analyses [24,25].
Study Selection
To be included, studies had to meet the following criteria: (1) the studies were observational (case-control or cohort studies), (2) the exposures of interest were the number of live births and the total duration of breastfeeding, (3) the outcome of interest was EOC, (4) odds ratios (ORs) or relative risk (RR) estimates with 95% confidence intervals (CIs) were reported or sufficient data were present to allow the calculation of these effect measures, and (5) articles were published in the English language. In the case of overlapping data, the study with the largest number of cases was included. As fertility treatments and BRCA mutation effects on EOC may alter the association between parity/breastfeeding and EOC [26], we excluded studies conducted on specific populations, such as BRCA-1 or BRCA-2 mutation carriers or infertile women treated with fertility drugs. The detailed steps of our literature search are shown in Figure 1.
Data Extraction
Data extraction was conducted independently by two authors. Disagreements were discussed and resolved by consensus. The following data were collected from each study: the first author’s last name, publication year, study region and design, study period, participant age, sample size (cases and controls or cohort size), exposure variables (parity or total breastfeeding duration), study-specific adjusted RR or OR with 95% CIs for each exposure category, and factors matched or adjusted for in the design or data analysis. If no adjusted RR or OR was presented, we included crude estimates. If no RRs or ORs were presented in a given study, we calculated them and the 95% CIs according to the raw frequencies presented in the article. The quality of the study was assessed independently by two authors using the 9-star Newcastle-Ottawa Scale (range, 0 to 9 stars) [27]. This measure assesses aspects of methodology in observational studies related to study quality, including the selection of cases, comparability of populations, and ascertainment of exposure to risks.
Statistical Analysis
The study-specific RRs or ORs with 95% CIs were used to determine the principal outcome. Because the OR closely approximates the RR for rare diseases, the RR can be estimated from a case-control study using the OR as an approximation [28]. Ovarian cancer is relatively rare and its absolute risk is low, with an incidence of 6.1 per 100 000 women [1]. Therefore, in the meta-analysis, ORs from case-control studies were used as an equivalent of RRs from cohort studies; we reported all results as RRs [22.29]. Mantel-Haenszel crude estimates of the RRs and corresponding 95% CIs were calculated when the RRs were not present but enough data were available. Logit RR estimates were calculated when the data were sparse. A random-effect model was used to obtain the summary RR and 95% CI. To assess whether the risk of EOC decreased with increasing parity or duration of breastfeeding, we categorized parity (1, 2, or ≥3; 1, 2, 3, or ≥4; and 1, 2, 3, 4, or ≥5) relative to nulliparity and total breastfeeding duration (<6 months, 6-12 months, or ≥13 months; and <6 months, 6-12 months, 13-24 months, or ≥25 months) relative to never having breastfed, as reported by most of the studies.
One study did not provide the required risk estimates for analysis or separate the risk estimates for different categories of parity or breastfeeding duration. For this study, we used the method proposed by Fleiss and Gross [30]. This method allows adjusted effect estimates and CIs to be calculated for any alternative comparison of levels and can help in a dose-response meta-analysis. Briefly, we combined risk estimates obtained through a simple fixed-effects meta-analysis wherein the subjects were divided into unexposed groups (i=0) and exposed groups (i=1, …, n), and estimates (Ri) with lower and upper 95% CIs were available. To obtain the R1+, we meta-analyzed R1, R2, R3, …, Rn using a fixed-effect model. The categories of parity or breastfeeding duration varied across studies; accordingly, the number of studies included in each meta-analysis and the summary RRs in each meta-analysis were different depending upon the number of categories.
Statistical heterogeneity among studies was evaluated with the Cochran Q and I-squared statistics [31]. The significance level for the Q statistic was defined as p-value<0.1. The I-squared value represents the proportion of total variation composed of between-study variation [31]. I-squared values ≤25%, 25.1-50%, 50.1-75%, and >75% were interpreted as indicating no, small, moderate, and significant heterogeneity, respectively [32]. Subgroup analyses were conducted to explore the potential sources of heterogeneity, according to the following characteristics: (1) study design (cohort, case-control studies); (2) the quality of study methodology across studies, with studies with ≥8 stars considered high-quality and those with ≤7 stars considered low-quality as per the 9-star Newcastle-Ottawa Scale; and (3) year of publication (<2000, ≥2000), respectively.
Publication bias was evaluated using the Begg rank correlation and the Egger linear regression test, in which p-vlaue <0.05 were considered representative of statistically significant publication bias [33].
From the meta-analyzed result, to calculate the RR for the joint effect of parity and breastfeeding, we applied the log-linear dose-response model proposed by Berlin et al. [34].
We configured the following formula for the multivariate linear logit regression of two factors:
Logit P=α+β1χ1+β2χ2;
where P is the probability of a particular outcome (EOC risk), α is the intercept from the linear regression equation, β is the regression coefficient multiplied by some value of the predictor, and χ is the risk factor (parity and breastfeeding).
Using this equation yields the value of the RR for the joint effects of parity and breastfeeding duration. For example, in the case of a subject who has no risk factors, logit(P) is α. In this case, the probability of EOC is exp(α)=1.0. In the case of a subject with only χ1, logit(P) is α+β1. In the case of a subject with both χ1 and χ2, logit(P) is α+β1+β2. Accordingly, the probability of EOC is exp(β1+β2)=OR1×OR2.
Since the category of parity and breastfeeding duration varied across studies, to calculate the RR for the joint effect of parity and breastfeeding, we used the summary RR for parity and breastfeeding duration that contained the largest number of studies.
All statistical analyses were performed with Stata version 12.0 (StataCorp., College Station, TX, USA).
Study Characteristics
The characteristics of the 32 studies included with data regarding parity and the 15 studies included with data regarding breastfeeding are shown in Supplemental Tables 1 and 2. For parity, six cohort studies and 26 case-control studies were included. The included studies were conducted between 1973 and 2008. Of the 32 studies, 14 were performed in North America, 12 in Europe, four in Asia, one in Australia, and one in Africa. For breastfeeding, two cohort studies and 13 case-control studies were included. The included studies were conducted between 1978 and 2008. Of the 15 studies, seven were performed in North America, six in Europe, one in Asia, and one in Australia.
Parity and Epithelial Ovarian Cancer Risk
Thirty-two studies had parity categories of 1, 2, and ≥3. The summary RRs for the first, second, and third births were 0.72 (95% CI, 0.65 to 0.79), 0.57 (95% CI, 0.49 to 0.65), and 0.46 (95% CI, 0.41 to 0.52), respectively (Table 1). Small to moderate heterogeneity was observed for the first birth (p<0.01; Q=59.46, I2=47.9%), whereas significant heterogeneity was observed for the second (p<0.01; Q=175.09; I2=82.3%) and third (p<0.01; Q=186.20; I2=81.7%) births. Analyses gave no indication of publication bias. Similar results were also observed for parity categories of 1, 2, 3, and ≥4 and 1, 2, 3, 4, and ≥5.
Duration of Breastfeeding and Epithelial Ovarian Cancer Risk
Fifteen studies had breastfeeding categories of <6 months, 6-12 months, and ≥13 months. The summary RRs for these categories were 0.79 (95% CI, 0.72 to 0.87), 0.72 (95% CI, 0.64 to 0.81) and 0.67 (95% CI, 0.56 to 0.79), respectively (Table 1). Small or no heterogeneity was observed for <6 months (p=0.17; Q=18.79; I2=25.5%) and 6-12 months (p=0.24; Q=17.41; I2=19.6%), whereas moderate heterogeneity was observed for ≥13 months (p<0.01; Q=39.30; I2=64.4%). Analyses gave no indication of publication bias. Similar results were also observed for the breastfeeding categories of <6 months, 6-12 months, 13-24 months, and ≥25 months.
Subgroup Analysis According to Study Design, Study Quality, and Publication Year
The results from the subgroup analysis according to study design, study quality, and publication year are shown in Table 2. In high-quality studies, the summary RRs for the first, second, and third births were 0.73 (95% CI, 0.64 to 0.84), 0.60 (95% CI, 0.49 to 0.74), and 0.46 (95% CI, 0.41 to 0.52), respectively. The summary RRs for <6 months, 6-12 months, and ≥13 months of breastfeeding were 0.79 (95% CI, 0.68 to 0.91), 0.82 (95% CI, 0.69 to 0.97), and 0.79 (95% CI, 0.66 to 0.95), respectively. The summary RRs of the first birth and <6 months of breastfeeding from the analysis of high-quality studies were almost identical to the values from the analysis of all 32 and 15 studies, without heterogeneity (I2=0%).
The summary RR for the first birth in cohort studies was weaker, and only had a borderline significant effect on EOC risk (RR, 0.86; 95% CI, 0.75 to 1.00) relative to case-control studies (RR, 0.69; 95% CI, 0.61 to 0.77). In contrast, with regards to breastfeeding, the summary RRs for <6 months were similar between cohort studies and case-control studies (Table 2), with small heterogeneity.
Relative Risk for the Joint Effect of Parity and Breastfeeding
The RR for the joint effect of parity and breastfeeding, obtained using the summary RR from the analysis of 32 studies with parity categories of 1, 2, and ≥3 and 15 studies with breastfeeding categories of <6 months, 6-12 months, and ≥13 months, is shown in Table 3. Compared to nulliparous women who never breastfed, uniparous women with no history of breastfeeding had a nearly 30% reduced risk for EOC (Table 3). Without breastfeeding, two births and three or more births elicited 40% and 50% reduced risks for EOC, respectively. When breastfeeding <6 months was added to each parity category, an additional 10% reduction in EOC risk was found.
The findings of this meta-analysis indicate that parity and breastfeeding experiences in women can help prevent EOC, which is typically life-threatening and has a poor prognosis. In particular, the first birth and the first six months of breastfeeding had a greater protective effect than did subsequent births and/or additional breastfeeding, although multiparity and additional breastfeeding did provide some additional protection. The risk reduction effect of the first birth on EOC risk was almost 30%, and the combined effect of the first birth and <6 months of breastfeeding was 40%; thus, breastfeeding provided a nearly 10% greater risk reduction. In regards to parity, the EOC risk reduction was highest for the first birth, with some additional protection from the second birth. However, slightly less risk reduction was observed for the third birth (Figure 2). Although a prior meta-analysis suggested a continuous risk reduction of approximately 14% for each additional pregnancy after the first [5], the current findings show different results, with a gradually decreasing risk from additional parity and/or breastfeeding duration that eventually plateaus (Table 1).
Pregnancy and breastfeeding are thought to reduce EOC risk by decreasing pituitary gonadotropin levels and inducing anovulation [7,35]. Pregnancy and breastfeeding are expected to decrease the likelihood of spontaneous genetic mutation under the incessant ovulation hypothesis and of the hyperproliferation of inclusion cysts under the gonadotropin hypothesis. However, the observation that multiparity and additional breastfeeding did not provide an equal amount of protection does not provide evidence for either of these hypotheses. Nevertheless, the results of two experimental studies provide biological evidence for the relatively weaker protective effect of additional parity and breastfeeding [36,37]. For instance, high progesterone levels during pregnancy can increase apoptosis, which may clear transformed cells from the ovarian epithelium, meaning that all the accumulated transformed cells are washed fully out by the first pregnancy. Therefore, the first pregnancy provides a stronger protective effect than subsequent pregnancies [36]. In regards to breastfeeding, breastfeeding in the first few months completely inhibits the pulsatile secretion of gonadotropin-releasing hormone and luteinizing hormone, leading to suppression of ovulation [37]. After a couple of months, ovulatory activity may return, even though breastfeeding continues [37]; thus, a longer duration of breastfeeding does not provide an additional protective effect.
Our finding of decreased EOC risk with longer breastfeeding is similar to that reported by prior meta-analyses in 2013 and 2014 [22,23], but differs from that of a meta-analysis of nine case-control studies conducted in developed countries in 2001, in which breastfeeding for ≥12 months was associated with a significant 0.72-fold reduced risk of EOC compared to never having breastfed, while breastfeeding <12 months did not show such an association (OR, 0.95; 95% CI, 0.80 to 1.12) [21].
Based on the RR for the joint effect of parity and breastfeeding, women who had two births and breastfed for <6 months had a 0.5-fold reduced risk of EOC. Our findings may provide evidence for developing guidelines for EOC prevention.
The strength of this meta-analysis is that it included all available studies, and the large number of EOC cases allowed for the investigation of the risk associated with different categories of parity and breastfeeding duration. However, the current study also has several limitations. First, our meta-analysis was restricted to studies published in indexed journals and might not have included unpublished studies. Second, some residual confounders may not have been excluded and may have influenced the protective effect of parity and breastfeeding, although a large number of potential confounding factors, such as age, race, and use of oral contraceptives, were adjusted for in most of the included studies. Third, significant heterogeneity must be considered. Significant heterogeneity was present in the analysis assessing whether the risk of EOC decreased with increasing parity or duration of breastfeeding, especially for higher parity and longer duration of breastfeeding. Despite the subgroup analyses, heterogeneity still existed in the results of the highest category of parity and longest duration of breastfeeding. Categories of parity and duration of breastfeeding, especially the highest parity and longest duration of breastfeeding, differed among studies and may have contributed to the heterogeneity in the results. However, the first birth and <6 months of breastfeeding showed little heterogeneity, and similar results were found in the subgroup analysis to those of the high-quality studies. Fourth, as a meta-analysis of observational studies, the data were prone to biases such as recall and selection bias inherent in the original studies. Cohort studies are less susceptible to bias than case-control studies because information is collected before the diagnosis of the disease. However, only a small number of cohort studies have been published; therefore, it was not possible to analyze the various categories of parity and breastfeeding duration using cohort studies alone. Fifth, the included studies were primarily from North America and Europe. Therefore, the findings may not apply to Asian populations with a low incidence of ovarian cancer.
In conclusion, our findings indicated that the first birth and breastfeeding for <6 months were associated with significant reductions in EOC risk. As a modifiable reproductive risk factor, two childbirths and additional breastfeeding, regardless of breastfeeding duration, can reduce EOC risk by 50%. These findings may help to generate recommendations for the prevention of EOC.
This work was supported by a grant from the National R&D Program for Cancer Control, Ministry for Health, Welfare and Family Affairs, Republic of Korea (0920010).

CONFLICT OF INTEREST

The authors have no conflicts of interest associated with the material presented in this paper.

Supplemental Table 1.
Details of studies on parity and ovarian cancer risk
jpmph-49-6-349-supple1.pdf
Supplemental Table 2.
Details of studies on breastfeeding and ovarian cancer risk
jpmph-49-6-349-supple2.pdf
Figure. 1.
Literature search algorithm.
jpmph-49-6-349f1.gif
Figure. 2.
Decreasing epithelial ovarian cancer (EOC) risk with increasing parity and breastfeeding duration. (A) Decreasing EOC risk with increasing parity1,2. (B) Decreasing EOC risk with increasing breastfeeding duration1,2. 1The relative risks (RRs) in each category were estimated using a random effect model. 2We used summary RRs from 32 studies for parity and 15 studies for breastfeeding (shown in Table 1).
jpmph-49-6-349f2.gif
Table 1.
Summary risk estimates for the association of epithelial ovarian cancer with parity and breastfeeding duration
No. of studies1 Summary RR (95% CI)2 p-heterogeneity Q-statistic I-squared (%)
Parity (n) 1 32 0.72 (0.65, 0.79) <0.01 59.46 47.9
2 0.57 (0.49, 0.65) <0.01 175.09 82.3
≥3 0.46 (0.41, 0.52) <0.01 186.20 81.7
1 21 0.70 (0.62, 0.80) <0.01 52.97 56.6
2 0.53 (0.45, 0.62) <0.01 146.32 84.3
3 0.48 (0.42, 0.54) <0.01 69.26 66.8
≥4 0.39 (0.36, 0.42) <0.01 80.00 71.3
1 12 0.68 (0.58, 0.81) <0.01 35.60 66.3
2 0.50 (0.41, 0.61) <0.01 94.17 87.3
3 0.43 (0.40, 0.46) <0.01 47.20 74.6
4 0.34 (0.29, 0.41) 0.01 27.19 55.9
≥5 0.33 (0.29, 0.37) 0.01 26.72 55.1
Breastfeeding duration (mo) < 6 15 0.79 (0.72, 0.87) 0.17 18.79 25.5
6-12 0.72 (0.64, 0.81) 0.24 17.41 19.6
≥13 0.67 (0.56, 0.79) <0.01 39.30 64.4
< 6 6 0.87 (0.72, 1.04) 0.16 7.91 36.8
6-12 0.71 (0.58, 0.87) 0.30 6.05 17.3
13-24 0.75 (0.60, 0.93) 0.28 6.34 21.1
≥25 0.53 (0.36, 0.77) <0.01 21.16 73.4

RR, relative risk; CI, confidence interval.

1 No publication bias in each category (p>0.05 in both the Begg and Egger tests).

2 The summary RRs (95% CIs) in each meta-analysis were estimated using a random effect model.

Table 2.
Subgroup analysis according to study design, study quality, and publication year
No. of studies1 Summary RR (95% CI)2 p-heterogeneity Q-statistic I-squared (%)
Parity (n) Quality High3 1 8 0.73 (0.64, 0.84) 0.71 4.61 0.0
2 0.60 (0.49, 0.74) 0.03 15.86 62.2
>3 0.46 (0.41, 0.52) <0.01 28.06 75.1
Low4 1 24 0.71 (0.63, 0.81) <0.01 54.69 57.9
2 0.56 (0.47, 0.66) <0.01 155.48 85.2
>3 0.46 (0.40, 0.53) <0.01 145.47 84.2
Study design Cohort 1 6 0.86 (0.75, 1.00) 0.77 2.54 0.0
2 0.75 (0.66, 0.84) 0.88 1.79 0.0
>3 0.60 (0.54, 0.68) 0.34 5.63 11.1
Case-control 1 26 0.69 (0.61, 0.77) <0.01 52.56 52.4
2 0.75 (0.66, 0.84) <0.01 147.39 83.0
>3 0.43 (0.38, 0.49) <0.01 132.57 81.1
Year of publication < 2000 1 24 0.68 (0.60, 0.76) 0.01 40.29 42.9
2 0.54 (0.45, 0.64) <0.01 144.90 84.1
>3 0.45 (0.39, 0.52) <0.01 136.78 83.2
>2000 1 8 0.84 (0.72, 0.98) 0.17 10.35 32.4
2 0.64 (0.54, 0.76) 0.03 15.45 54.7
>3 0.49 (0.40, 0.61) <0.01 34.34 79.6
Breastfeeding duration (mo) Quality High3 < 6 4 0.79 (0.68, 0.91) 0.43 2.76 0.0
6-12 0.82 (0.69, 0.97) 0.39 2.99 0.0
>13 0.79 (0.66, 0.95) 0.33 39.30 13.0
Low4 < 6 11 0.78 (0.68, 0.90) 0.06 17.65 43.3
6-12 0.69 (0.60, 0.79) 0.31 11.69 14.5
>13 0.63 (0.52, 0.78) <0.01 28.38 64.8
Study design Cohort < 6 2 0.77 (0.63, 0.93) 0.22 1.53 34.6
6-12 0.87 (0.71, 1.06) 0.43 0.63 0.0
>13 0.81 (0.67, 0.98) 0.33 0.97 0.0
Case-control < 6 13 0.79 (0.70, 0.90) 0.09 18.97 36.8
6-12 0.69 (0.61, 0.77) 0.39 12.69 8.8
>13 0.64 (0.53, 0.77) <0.01 31.53 61.9
Year of publication < 2000 < 6 11 0.78 (0.70, 0.86) 0.28 12.11 17.4
6-12 0.70 (0.61, 0.82) 0.12 15.26 34.5
>13 0.63 (0.53, 0.76) <0.01 25.58 60.9
> 2000 < 6 4 0.80 (0.57, 1.12) 0.04 8.39 64.2
6-12 0.75 (0.60, 0.94) 0.56 2.04 0.0
>13 0.81 (0.51, 1.27) 0.01 11.77 74.5

RR, relative risk; CI, confidence interval.

1 No publication bias in each category (p>0.05 in both the Begg and Egger test).

2 The summary RRs (95% CIs) in each meta-analysis were estimated using a random effect model.

3 Studies with ≥8 stars were considered high-quality as per the 9-star Newcastle-Ottawa Scale.

4 Studies with ≤7 stars were considered low-quality as per the 9-star Newcastle-Ottawa Scale.

Table 3.
Relative risks (RRs) for the joint effect of parity and breastfeeding
Parity (n)
Breastfeeding (mo)
Category RR1,2 0 <6 6-12 ≥13
RR1,2 1.00 0.79 0.72 0.67
0 1.00 Joint RR 1.0
1 0.72 0.7 0.6 0.5 0.5
2 0.57 0.6 0.5 0.4 0.4
≥3 0.46 0.5 0.4 0.3 0.3

1 The RRs in each category were estimated using a random effect model.

2 We used the summary RR from the analysis of 32 studies with parity categories of 1, 2, and ≥3 and 15 studies with breastfeeding categories of <6, 6-12, and ≥13 months (as shown in Table 1).

  • 1. International Agency for Research on Cancer. GLOBOCAN 2012: estimated cancer incidence, mortality and prevalence worldwide in 2012; [cited 2016 Nov 20]. Available from: http://globocan.iarc.fr/Default.aspx
  • 2. Prat J; FIGO Committee on Gynecologic Oncology. FIGO’s staging classification for cancer of the ovary, fallopian tube, and peritoneum: abridged republication. J Gynecol Oncol 2015;26(2):87-89ArticlePubMedPMC
  • 3. Colombo N, Peiretti M, Castiglione M; ESMO Guidelines Working Group. Non-epithelial ovarian cancer: ESMO clinical recommendations for diagnosis, treatment and follow-up. Ann Oncol 2009;20 Suppl 4: 24-26ArticlePubMed
  • 4. Clarke-Pearson DL. Clinical practice. Screening for ovarian cancer. N Engl J Med 2009;361(2):170-177ArticlePubMed
  • 5. 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):1184-1203ArticlePubMed
  • 6. Harris R, Whittemore AS, Itnyre J. Characteristics relating to ovarian cancer risk: collaborative analysis of 12 US case-control studies. III. Epithelial tumors of low malignant potential in white women. Collaborative Ovarian Cancer Group. Am J Epidemiol 1992;136(10):1204-1211PubMed
  • 7. Fathalla MF. Incessant ovulation--a factor in ovarian neoplasia? Lancet 1971;2(7716):163ArticlePubMed
  • 8. 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):1212-1220ArticlePubMed
  • 9. Risch HA, Marrett LD, Howe GR. Parity, contraception, infertility, and the risk of epithelial ovarian cancer. Am J Epidemiol 1994;140(7):585-597ArticlePubMed
  • 10. Ness RB, Grisso JA, Klapper J, Schlesselman JJ, Silberzweig S, Vergona R, et al. Risk of ovarian cancer in relation to estrogen and progestin dose and use characteristics of oral contraceptives. Am J Epidemiol 2000;152(3):233-241ArticlePubMed
  • 11. Titus-Ernstoff L, Perez K, Cramer DW, Harlow BL, Baron JA, Greenberg ER. Menstrual and reproductive factors in relation to ovarian cancer risk. Br J Cancer 2001;84(5):714-721ArticlePubMedPMC
  • 12. Riman T, Dickman PW, Nilsson S, Correia N, Nordlinder H, Magnusson CM, et al. Risk factors for epithelial borderline ovarian tumors: results of a Swedish case-control study. Gynecol Oncol 2001;83(3):575-585ArticlePubMed
  • 13. Riman T, Dickman PW, Nilsson S, Correia N, Nordlinder H, Magnusson CM, et al. Risk factors for invasive epithelial ovarian cancer: results from a Swedish case-control study. Am J Epidemiol 2002;156(4):363-373ArticlePubMed
  • 14. Hankinson SE, Colditz GA, Hunter DJ, Willett WC, Stampfer MJ, Rosner B, et al. A prospective study of reproductive factors and risk of epithelial ovarian cancer. Cancer 1995;76(2):284-290ArticlePubMed
  • 15. Weiderpass E, Sandin S, Inoue M, Shimazu T, Iwasaki M, Sasazuki S, et al. Risk factors for epithelial ovarian cancer in Japan - results from the Japan Public Health Center-based Prospective Study cohort. Int J Oncol 2012;40(1):21-30PubMed
  • 16. Yang HP, Trabert B, Murphy MA, Sherman ME, Sampson JN, Brinton LA, et al. Ovarian cancer risk factors by histologic subtypes in the NIH-AARP Diet and Health Study. Int J Cancer 2012;131(4):938-948ArticlePubMed
  • 17. Gwinn ML, Lee NC, Rhodes PH, Layde PM, Rubin GL. Pregnancy, breast feeding, and oral contraceptives and the risk of epithelial ovarian cancer. J Clin Epidemiol 1990;43(6):559-568ArticlePubMed
  • 18. Danforth KN, Tworoger SS, Hecht JL, Rosner BA, Colditz GA, Hankinson SE. Breastfeeding and risk of ovarian cancer in two prospective cohorts. Cancer Causes Control 2007;18(5):517-523ArticlePubMed
  • 19. Siskind V, Green A, Bain C, Purdie D. Breastfeeding, menopause, and epithelial ovarian cancer. Epidemiology 1997;8(2):188-191ArticlePubMed
  • 20. Whittemore AS, Harris R, Itnyre J, Halpern J. Characteristics relating to ovarian cancer risk: collaborative analysis of 12 US case-control studies. I. Methods. Collaborative Ovarian Cancer Group. Am J Epidemiol 1992;136(10):1175-1183ArticlePubMed
  • 21. Ip S, Chung M, Raman G, Trikalinos TA, Lau J. A summary of the Agency for Healthcare Research and Quality’s evidence report on breastfeeding in developed countries. Breastfeed Med 2009;4 Suppl 1: S17-S30ArticlePubMed
  • 22. Luan NN, Wu QJ, Gong TT, Vogtmann E, Wang YL, Lin B. Breastfeeding and ovarian cancer risk: a meta-analysis of epidemiologic studies. Am J Clin Nutr 2013;98(4):1020-1031ArticlePubMedPMC
  • 23. Li DP, Du C, Zhang ZM, Li GX, Yu ZF, Wang X, et al. Breastfeeding and ovarian cancer risk: a systematic review and meta-analysis of 40 epidemiological studies. Asian Pac J Cancer Prev 2014;15(12):4829-4837ArticlePubMed
  • 24. Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. JAMA 2000;283(15):2008-2012ArticlePubMed
  • 25. Moher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ 2009;339: b2535ArticlePubMedPMC
  • 26. Fishman A. The effects of parity, breastfeeding, and infertility treatment on the risk of hereditary breast and ovarian cancer: a review. Int J Gynecol Cancer 2010;20(11 Suppl 2):S31-S33ArticlePubMed
  • 27. Wells GA, Shea B, O’Connell D, Peterson J, Welch V, Losos M, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. Available from: http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp
  • 28. Schlesselman JJ, Stolley PD. Case-control studies: design, conduct, analysis. New York: Oxford University Press; 1982. p. 33-34
  • 29. Greenland S. Quantitative methods in the review of epidemiologic literature. Epidemiol Rev 1987;9: 1-30PubMed
  • 30. Fleiss JL, Gross AJ. Meta-analysis in epidemiology, with special reference to studies of the association between exposure to environmental tobacco smoke and lung cancer: a critique. J Clin Epidemiol 1991;44(2):127-139ArticlePubMed
  • 31. Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med 2002;21(11):1539-1558ArticlePubMed
  • 32. Godos J, Bella F, Torrisi A, Sciacca S, Galvano F, Grosso G. Dietary patterns and risk of colorectal adenoma: a systematic review and meta-analysis of observational studies. J Hum Nutr Diet 2016. doi: https://doi.org/10.1111/jhn.12395Article
  • 33. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ 1997;315(7109):629-634ArticlePubMedPMC
  • 34. Berlin JA, Longnecker MP, Greenland S. Meta-analysis of epidemiologic dose-response data. Epidemiology 1993;4(3):218-228ArticlePubMed
  • 35. Konishi I. Gonadotropins and ovarian carcinogenesis: a new era of basic research and its clinical implications. Int J Gynecol Cancer 2006;16(1):16-22ArticlePubMed
  • 36. Bu SZ, Yin DL, Ren XH, Jiang LZ, Wu ZJ, Gao QR, et al. Progesterone induces apoptosis and up-regulation of p53 expression in human ovarian carcinoma cell lines. Cancer 1997;79(10):1944-1950ArticlePubMed
  • 37. McNeilly AS. Lactational control of reproduction. Reprod Fertil Dev 2001;13(7-8):583-590ArticlePubMed

Figure & Data

References

    Citations

    Citations to this article as recorded by  
    • Pelvic inflammatory disease and risk of epithelial ovarian cancer: a national population-based case-control study in Sweden
      Sarah Jonsson, Håkan Jonsson, Eva Lundin, Christel Häggström, Annika Idahl
      American Journal of Obstetrics and Gynecology.2024; 230(1): 75.e1.     CrossRef
    • Agricultural exposure and risk of ovarian cancer in the AGRIculture and CANcer (AGRICAN) cohort
      Marine Renier, Juliette Hippert, Louis-Bastien Weiswald, Séverine Tual, Matthieu Meryet-Figuiere, Nicolas Vigneron, Elisabeth Marcotullio, Isabelle Baldi, Pierre Lebailly
      Occupational and Environmental Medicine.2024; 81(2): 75.     CrossRef
    • Prenatal Counseling on the Maternal Health Benefits of Lactation: A Randomized Trial
      Eleanor B. Schwarz, Adrienne Hoyt-Austin, Margaret Fix, Laura R. Kair, Caidon Iwuagwu, Melissa J. Chen
      Breastfeeding Medicine.2024; 19(1): 52.     CrossRef
    • Awareness of the Maternal Health Benefits of Lactation Among U.S. Pregnant Individuals
      Caidon Iwuagwu, Melissa J. Chen, Adrienne E. Hoyt-Austin, Laura Kair, Margaret Fix, Eleanor Bimla Schwarz
      Women's Health Issues.2024; 34(3): 283.     CrossRef
    • Breastfeeding’s protective role in alleviating breast cancer burden: A comprehensive review
      Emmanuel Ifeanyi Obeagu, Getrude Uzoma Obeagu
      Annals of Medicine & Surgery.2024;[Epub]     CrossRef
    • Fraction of cancers attributable to and prevented by reproductive factors and exogenous hormones use in Italy
      Federica Turati, Giulia Collatuzzo, Matteo Di Maso, Eva Negri, Giovanna Esposito, Gianfranco Alicandro, Matteo Malvezzi, Claudio Pelucchi, Paolo Boffetta, Carlo La Vecchia, Fabio Parazzini
      European Journal of Obstetrics & Gynecology and Reproductive Biology.2024; 301: 49.     CrossRef
    • A dose–response meta-analysis of the relationship between number of pregnancies and risk of gynecological cancers
      Jalal Poorolajal, Amin Doosti-Irani, Ali Mohammad Karami, Marzieh Fattahi-Darghlou
      Archives of Gynecology and Obstetrics.2024;[Epub]     CrossRef
    • Ovulation induction drug and ovarian cancer: an updated systematic review and meta-analysis
      Liang Yu, Jiafan Sun, Qiqin Wang, Wennian Yu, Anqi Wang, Shu Zhu, Wei Xu, Xiuli Wang
      Journal of Ovarian Research.2023;[Epub]     CrossRef
    • La Salpingo-oforectomía o Salpingectomía como estrategia para prevenir el cáncer de ovario
      Scarlet Hochstatter Irarrázabal, Erwin Hochstatter Arduz
      Revista Medica.2023; 27(1): 26.     CrossRef
    • Stratifying the risk of ovarian cancer incidence by histologic subtypes in the Korean Epithelial Ovarian Cancer Study (Ko‐EVE)
      Soseul Sung, Youjin Hong, Byoung‐Gie Kim, Ji‐Yeob Choi, Jae Weon Kim, Sang‐Yoon Park, Jae‐Hoon Kim, Yong‐man Kim, Jong‐Min Lee, Tae Jin Kim, Sue K. Park
      Cancer Medicine.2023; 12(7): 8742.     CrossRef
    • Abortion and Female Cancer Risks among Women Aged 20 to 45 Years: A 10-Year Longitudinal Population-Based Cohort Study in Taiwan
      Cheng-Ting Shen, Shu-Yu Tai, Yu-Hsiang Tsao, Fang-Ming Chen, Hui-Min Hsieh
      International Journal of Environmental Research and Public Health.2023; 20(4): 3682.     CrossRef
    • Lifetime ovulatory years and risk of epithelial ovarian cancer: a multinational pooled analysis
      Zhuxuan Fu, Maria Mori Brooks, Sarah Irvin, Susan Jordan, Katja K H Aben, Hoda Anton-Culver, Elisa V Bandera, Matthias W Beckmann, Andrew Berchuck, Angela Brooks-Wilson, Jenny Chang-Claude, Linda S Cook, Daniel W Cramer, Kara L Cushing-Haugen, Jennifer A
      JNCI: Journal of the National Cancer Institute.2023; 115(5): 539.     CrossRef
    • Role of breastfeeding on maternal and childhood cancers: An umbrella review of meta-analyses
      Dazhi Fan, Qing Xia, Dongxin Lin, Yubo Ma, Jiaming Rao, Li Liu, Hai Tang, Tingting Xu, Pengsheng Li, Gengdong Chen, Zixing Zhou, Xiaoling Guo, Zhifang Zhang, Zhengping Liu
      Journal of Global Health.2023;[Epub]     CrossRef
    • What does a doctor need to know about breastfeeding and adolescent health and pregnancy?
      Leandro Meirelles Nunes, Rossiclei de Souza Pinheiro, Izailza Matos Dantas Lopes, Darci Vieira da Silva Bonetto, Alda Elizabeth Boehler Iglesias Azevedo
      Revista da Associação Médica Brasileira.2023;[Epub]     CrossRef
    • Deficiencies in the Intentions, Attitudes, and Knowledge of Future Healthcare Professionals Regarding Breastfeeding
      Marija Čatipović, Štefica Mikšić, Rajko Fureš, Zrinka Puharić, Dragica Pavlović
      Children.2023; 10(7): 1256.     CrossRef
    • Examining psychometric properties of the Iranian version of exclusive breastfeeding social support scale (EBFSS)
      Sepideh Mashayekh-Amiri, Mina Hosseinzadeh, Mohammad Asghari Jafarabadi, Sepideh Soltani, Mojgan Mirghafourvand
      BMC Psychology.2023;[Epub]     CrossRef
    • Are pregnancy and parity associated with telomere length? A systematic review
      Nourit Houminer-Klepar, Shiran Bord, Elissa Epel, Orna Baron-Epel
      BMC Pregnancy and Childbirth.2023;[Epub]     CrossRef
    • Global patterns and temporal trends in ovarian cancer morbidity, mortality, and burden from 1990 to 2019
      Afrooz Mazidimoradi, Zohre Momenimovahed, Yousef Khani, Armin Rezaei Shahrabi, Leila Allahqoli, Hamid Salehiniya
      Oncologie.2023; 25(6): 641.     CrossRef
    • Pregnancy, preeclampsia and maternal aging: From epidemiology to functional genomics
      Eliza C. Miller, Ashley Wilczek, Natalie A. Bello, Sarah Tom, Ronald Wapner, Yousin Suh
      Ageing Research Reviews.2022; 73: 101535.     CrossRef
    • Lifetime ovulations and epithelial ovarian cancer risk and survival: A systematic review and meta-analysis
      Zhuxuan Fu, Sarah Taylor, Francesmary Modugno
      Gynecologic Oncology.2022; 165(3): 650.     CrossRef
    • The Effects of Breastfeeding on Maternal Mental Health: A Systematic Review
      Megan Yuen, Olivia J. Hall, Grace A. Masters, Benjamin C. Nephew, Catherine Carr, Katherine Leung, Adrienne Griffen, Lynne McIntyre, Nancy Byatt, Tiffany A. Moore Simas
      Journal of Women's Health.2022; 31(6): 787.     CrossRef
    • Breastfeeding Among Pediatric Emergency Physicians
      Marissa Hendrickson, Cynthia S. Davey, Brian A. Harvey, Kari Schneider
      Pediatric Emergency Care.2022; 38(7): e1372.     CrossRef
    • A Follow-Up Study of Ovarian Cancer (OOPS): A Study Protocol
      Ting-Ting Gong, Fang-Hua Liu, Ya-Shu Liu, Shi Yan, He-Li Xu, Xin-Hui He, Yi-Fan Wei, Xue Qin, Song Gao, Yu-Hong Zhao, Qi-Jun Wu
      Frontiers in Nutrition.2022;[Epub]     CrossRef
    • Extraterrestrial Gynecology: Could Spaceflight Increase the Risk of Developing Cancer in Female Astronauts? An Updated Review
      Rosa Drago-Ferrante, Riccardo Di Fiore, Fathi Karouia, Yashwanth Subbannayya, Saswati Das, Begum Aydogan Mathyk, Shehbeel Arif, Ana Paula Guevara-Cerdán, Allen Seylani, Aman Singh Galsinh, Weronika Kukulska, Joseph Borg, Sherif Suleiman, David Marshall Po
      International Journal of Molecular Sciences.2022; 23(13): 7465.     CrossRef
    • Behaviour, Attitudes and Knowledge of Healthcare Workers on Breastfeeding
      Marija Čatipović, Zrinka Puharić, Drita Puharić, Paula Čatipović, Josip Grgurić
      Children.2022; 9(8): 1173.     CrossRef
    • Lactancia materna
      E. Raimond, N. Leloux, R. Gabriel
      EMC - Ginecología-Obstetricia.2022; 58(4): 1.     CrossRef
    • Human Milk Microbiota and Oligosaccharides: A Glimpse into Benefits, Diversity, and Correlations
      Carole Ayoub Moubareck
      Nutrients.2021; 13(4): 1123.     CrossRef
    • Couples talk about breastfeeding: Interviews with parents about decision-making, challenges, and the role of fathers and professional support
      Erin J Henshaw, Maria Mayer, Sarina Balraj, Elsie Parmar, Kristine Durkin, Rita Snell
      Health Psychology Open.2021;[Epub]     CrossRef
    • Influence of lactation and nutrition on health of nursing woman
      S. V. Orlova, E. A. Nikitina, A. N. Vodolazkaya, L. Yu. Volkova, E. V. Prokopenko
      Medical alphabet.2021; (21): 75.     CrossRef
    • Supporting Exclusive Breastfeeding Among Factory Workers and Their Unemployed Neighbors: Peer Counseling in Bangladesh
      Rukhsana Haider, Virginia Thorley
      Journal of Human Lactation.2020; 36(3): 414.     CrossRef
    • The Ketogenic Diet Including Breast Milk for Treatment of Infants with Severe Childhood Epilepsy: Feasibility, Safety, and Effectiveness
      Anastasia Dressler, Chiara Häfele, Vito Giordano, Franz Benninger, Petra Trimmel-Schwahofer, Gudrun Gröppel, Sharon Samueli, Martha Feucht, Christoph Male, Andreas Repa
      Breastfeeding Medicine.2020; 15(2): 72.     CrossRef
    • Gender of offspring and risk of ovarian cancer: The HOPE study
      Zhuxuan Fu, Kirsten Moysich, Roberta B. Ness, Francesmary Modugno
      Cancer Epidemiology.2020; 64: 101646.     CrossRef
    • Ovarian cancer screening: Current status and future directions
      Zachary Nash, Usha Menon
      Best Practice & Research Clinical Obstetrics & Gynaecology.2020; 65: 32.     CrossRef
    • “I was determined to breastfeed, and I always found a solution”: successful experiences of exclusive breastfeeding among Chinese mothers in Ireland
      Qianling Zhou, Haoyue Chen, Katherine M. Younger, Tanya M. Cassidy, John M. Kearney
      International Breastfeeding Journal.2020;[Epub]     CrossRef
    • An Update on Screening and Prevention for Breast and Gynecological Cancers in Average and High Risk Individuals
      Anahid M Pahlawanian, Vanessa A Norris, Amelia M Jernigan, Brooke Morrell, Mignonne Morrell, Navya Nair, Amber M Karamanis, Erin M Dauchy, Michelle M Loch, Agustin A Garcia
      The American Journal of the Medical Sciences.2020; 360(5): 489.     CrossRef
    • Association of Social and Community Factors with U.S. Breastfeeding Outcomes
      Leslie Kummer, Naomi Duke, Laurel Davis, Iris Borowsky
      Breastfeeding Medicine.2020; 15(10): 646.     CrossRef
    • Breastfeeding Among Mothers Who Have Experienced Childhood Maltreatment: A Review
      Amara Channell Doig, Michelle Jasczynski, Jamie L. Fleishman, Elizabeth M. Aparicio
      Journal of Human Lactation.2020; 36(4): 710.     CrossRef
    • Offspring sex and risk of epithelial ovarian cancer: a multinational pooled analysis of 12 case–control studies
      Francesmary Modugno, Zhuxuan Fu, Susan J. Jordan, AOCS Group, Jenny Chang-Claude, Renée T. Fortner, Marc T. Goodman, Kirsten B. Moysich, Joellen M. Schildkraut, Andrew Berchuck, Elisa V. Bandera, Bo Qin, Rebecca Sutphen, John R. McLaughlin, Usha Menon, Su
      European Journal of Epidemiology.2020; 35(11): 1025.     CrossRef
    • Translational Theragnosis of Ovarian Cancer: where do we stand?
      Maria Grazia Perrone, Oreste Luisi, Anna De Grassi, Savina Ferorelli, Gennaro Cormio, Antonio Scilimati
      Current Medicinal Chemistry.2020; 27(34): 5675.     CrossRef
    • Breastfeeding factors and risk of epithelial ovarian cancer
      Francesmary Modugno, Sharon L. Goughnour, Danielle Wallack, Robert P. Edwards, Kunle Odunsi, Joseph L. Kelley, Kirsten Moysich, Roberta B. Ness, Maria Mori Brooks
      Gynecologic Oncology.2019; 153(1): 116.     CrossRef
    • Flexible piecewise linear model for investigating dose‐response relationship in meta‐analysis: Methodology, examples, and comparison
      Chang Xu, Lehana Thabane, Tongzu Liu, ASM Borhan, Xin Sun
      Journal of Evidence-Based Medicine.2019; 12(1): 63.     CrossRef
    • Critical questions in ovarian cancer research and treatment: Report of an American Association for Cancer Research Special Conference
      Robert C. Bast, Ursula A. Matulonis, Anil K. Sood, Ahmed A. Ahmed, Adaobi E. Amobi, Frances R. Balkwill, Monicka Wielgos‐Bonvallet, David D. L. Bowtell, James D. Brenton, Joan S. Brugge, Robert L. Coleman, Giulio F. Draetta, Kai Doberstein, Ronny I. Drapk
      Cancer.2019; 125(12): 1963.     CrossRef
    • Novel Approaches to Ovarian Cancer Screening
      Denise R. Nebgen, Karen H. Lu, Robert C. Bast
      Current Oncology Reports.2019;[Epub]     CrossRef
    • Age at last birth and risk of developing epithelial ovarian cancer: a meta-analysis
      Yanjun Wu, Wenjun Sun, Xueling Xin, Weijing Wang, Dongfeng Zhang
      Bioscience Reports.2019;[Epub]     CrossRef
    • The impact of historical breastfeeding practices on the incidence of cancer in France in 2015
      Kevin D. Shield, Laure Dossus, Agnès Fournier, Claire Marant Micallef, Sabina Rinaldi, Agnès Rogel, Isabelle Heard, Sophie Pilleron, Freddie Bray, Isabelle Soerjomataram
      Cancer Causes & Control.2018; 29(3): 325.     CrossRef
    • The role of pregnancy, perinatal factors and hormones in maternal cancer risk: a review of the evidence
      R. Troisi, T. Bjørge, M. Gissler, T. Grotmol, C. M. Kitahara, S. M. Myrtveit Sæther, A. G. Ording, C. Sköld, H. T. Sørensen, B. Trabert, I. Glimelius
      Journal of Internal Medicine.2018; 283(5): 430.     CrossRef
    • Ovarian Cancer Prevention and Screening
      Usha Menon, Chloe Karpinskyj, Aleksandra Gentry-Maharaj
      Obstetrics & Gynecology.2018; 131(5): 909.     CrossRef
    • Breastfeeding experience, challenges and service demands among Chinese mothers: A qualitative study in two cities
      Yan Zhang, Yi Jin, Carel Vereijken, Bernd Stahl, Hong Jiang
      Appetite.2018; 128: 263.     CrossRef
    • Postpartum Cardiomyopathy and Considerations for Breastfeeding
      Laura Kearney, Paul Wright, Sadeer Fhadil, Martin Thomas
      Cardiac Failure Review.2018; 4(2): 112.     CrossRef
    • Breastfeeding and the Benefits of Lactation for Women's Health
      Luiz Antonio Del Ciampo, Ieda Regina Lopes Del Ciampo
      Revista Brasileira de Ginecologia e Obstetrícia / RBGO Gynecology and Obstetrics.2018; 40(06): 354.     CrossRef
    • Ovarian Cancer Prevention in High-risk Women
      SARAH M. TEMKIN, JENNIFER BERGSTROM, GOLI SAMIMI, LORI MINASIAN
      Clinical Obstetrics & Gynecology.2017; 60(4): 738.     CrossRef
    • Risk Reduction of Breast Cancer by Childbirth, Breastfeeding, and Their Interaction in Korean Women: Heterogeneous Effects Across Menopausal Status, Hormone Receptor Status, and Pathological Subtypes
      Seok Hun Jeong, Yoon Suk An, Ji-Yeob Choi, Boyoung Park, Daehee Kang, Min Hyuk Lee, Wonshik Han, Dong Young Noh, Keun-Young Yoo, Sue K. Park
      Journal of Preventive Medicine and Public Health.2017; 50(6): 401.     CrossRef

    Figure
    • 0
    • 1
    Related articles
    The Effect of Breastfeeding Duration and Parity on the Risk of Epithelial Ovarian Cancer: A Systematic Review and Meta-analysis
    Image Image
    Figure. 1. Literature search algorithm.
    Figure. 2. Decreasing epithelial ovarian cancer (EOC) risk with increasing parity and breastfeeding duration. (A) Decreasing EOC risk with increasing parity1,2. (B) Decreasing EOC risk with increasing breastfeeding duration1,2. 1The relative risks (RRs) in each category were estimated using a random effect model. 2We used summary RRs from 32 studies for parity and 15 studies for breastfeeding (shown in Table 1).
    The Effect of Breastfeeding Duration and Parity on the Risk of Epithelial Ovarian Cancer: A Systematic Review and Meta-analysis
    No. of studies1 Summary RR (95% CI)2 p-heterogeneity Q-statistic I-squared (%)
    Parity (n) 1 32 0.72 (0.65, 0.79) <0.01 59.46 47.9
    2 0.57 (0.49, 0.65) <0.01 175.09 82.3
    ≥3 0.46 (0.41, 0.52) <0.01 186.20 81.7
    1 21 0.70 (0.62, 0.80) <0.01 52.97 56.6
    2 0.53 (0.45, 0.62) <0.01 146.32 84.3
    3 0.48 (0.42, 0.54) <0.01 69.26 66.8
    ≥4 0.39 (0.36, 0.42) <0.01 80.00 71.3
    1 12 0.68 (0.58, 0.81) <0.01 35.60 66.3
    2 0.50 (0.41, 0.61) <0.01 94.17 87.3
    3 0.43 (0.40, 0.46) <0.01 47.20 74.6
    4 0.34 (0.29, 0.41) 0.01 27.19 55.9
    ≥5 0.33 (0.29, 0.37) 0.01 26.72 55.1
    Breastfeeding duration (mo) < 6 15 0.79 (0.72, 0.87) 0.17 18.79 25.5
    6-12 0.72 (0.64, 0.81) 0.24 17.41 19.6
    ≥13 0.67 (0.56, 0.79) <0.01 39.30 64.4
    < 6 6 0.87 (0.72, 1.04) 0.16 7.91 36.8
    6-12 0.71 (0.58, 0.87) 0.30 6.05 17.3
    13-24 0.75 (0.60, 0.93) 0.28 6.34 21.1
    ≥25 0.53 (0.36, 0.77) <0.01 21.16 73.4
    No. of studies1 Summary RR (95% CI)2 p-heterogeneity Q-statistic I-squared (%)
    Parity (n) Quality High3 1 8 0.73 (0.64, 0.84) 0.71 4.61 0.0
    2 0.60 (0.49, 0.74) 0.03 15.86 62.2
    >3 0.46 (0.41, 0.52) <0.01 28.06 75.1
    Low4 1 24 0.71 (0.63, 0.81) <0.01 54.69 57.9
    2 0.56 (0.47, 0.66) <0.01 155.48 85.2
    >3 0.46 (0.40, 0.53) <0.01 145.47 84.2
    Study design Cohort 1 6 0.86 (0.75, 1.00) 0.77 2.54 0.0
    2 0.75 (0.66, 0.84) 0.88 1.79 0.0
    >3 0.60 (0.54, 0.68) 0.34 5.63 11.1
    Case-control 1 26 0.69 (0.61, 0.77) <0.01 52.56 52.4
    2 0.75 (0.66, 0.84) <0.01 147.39 83.0
    >3 0.43 (0.38, 0.49) <0.01 132.57 81.1
    Year of publication < 2000 1 24 0.68 (0.60, 0.76) 0.01 40.29 42.9
    2 0.54 (0.45, 0.64) <0.01 144.90 84.1
    >3 0.45 (0.39, 0.52) <0.01 136.78 83.2
    >2000 1 8 0.84 (0.72, 0.98) 0.17 10.35 32.4
    2 0.64 (0.54, 0.76) 0.03 15.45 54.7
    >3 0.49 (0.40, 0.61) <0.01 34.34 79.6
    Breastfeeding duration (mo) Quality High3 < 6 4 0.79 (0.68, 0.91) 0.43 2.76 0.0
    6-12 0.82 (0.69, 0.97) 0.39 2.99 0.0
    >13 0.79 (0.66, 0.95) 0.33 39.30 13.0
    Low4 < 6 11 0.78 (0.68, 0.90) 0.06 17.65 43.3
    6-12 0.69 (0.60, 0.79) 0.31 11.69 14.5
    >13 0.63 (0.52, 0.78) <0.01 28.38 64.8
    Study design Cohort < 6 2 0.77 (0.63, 0.93) 0.22 1.53 34.6
    6-12 0.87 (0.71, 1.06) 0.43 0.63 0.0
    >13 0.81 (0.67, 0.98) 0.33 0.97 0.0
    Case-control < 6 13 0.79 (0.70, 0.90) 0.09 18.97 36.8
    6-12 0.69 (0.61, 0.77) 0.39 12.69 8.8
    >13 0.64 (0.53, 0.77) <0.01 31.53 61.9
    Year of publication < 2000 < 6 11 0.78 (0.70, 0.86) 0.28 12.11 17.4
    6-12 0.70 (0.61, 0.82) 0.12 15.26 34.5
    >13 0.63 (0.53, 0.76) <0.01 25.58 60.9
    > 2000 < 6 4 0.80 (0.57, 1.12) 0.04 8.39 64.2
    6-12 0.75 (0.60, 0.94) 0.56 2.04 0.0
    >13 0.81 (0.51, 1.27) 0.01 11.77 74.5
    Parity (n)
    Breastfeeding (mo)
    Category RR1,2 0 <6 6-12 ≥13
    RR1,2 1.00 0.79 0.72 0.67
    0 1.00 Joint RR 1.0
    1 0.72 0.7 0.6 0.5 0.5
    2 0.57 0.6 0.5 0.4 0.4
    ≥3 0.46 0.5 0.4 0.3 0.3
    Table 1. Summary risk estimates for the association of epithelial ovarian cancer with parity and breastfeeding duration

    RR, relative risk; CI, confidence interval.

    No publication bias in each category (p>0.05 in both the Begg and Egger tests).

    The summary RRs (95% CIs) in each meta-analysis were estimated using a random effect model.

    Table 2. Subgroup analysis according to study design, study quality, and publication year

    RR, relative risk; CI, confidence interval.

    No publication bias in each category (p>0.05 in both the Begg and Egger test).

    The summary RRs (95% CIs) in each meta-analysis were estimated using a random effect model.

    Studies with ≥8 stars were considered high-quality as per the 9-star Newcastle-Ottawa Scale.

    Studies with ≤7 stars were considered low-quality as per the 9-star Newcastle-Ottawa Scale.

    Table 3. Relative risks (RRs) for the joint effect of parity and breastfeeding

    The RRs in each category were estimated using a random effect model.

    We used the summary RR from the analysis of 32 studies with parity categories of 1, 2, and ≥3 and 15 studies with breastfeeding categories of <6, 6-12, and ≥13 months (as shown in Table 1).


    JPMPH : Journal of Preventive Medicine and Public Health
    TOP