Heting Mei
Qingya Song
Wenping Lu
Xiyue Wang2
Lei Chang
Zhili Zhuo- 1Department of Oncology, China Academy of Chinese Medical Sciences Guang’anmen Hospital, Beijing, China
- 2Graduate School, Beijing University of Chinese Medicine, Beijing, China
Introduction: Breast cancer is a type of hormone-driven cancer, and pregnancy may increase the risk of recurrence in patients due to hormone surge. Our study was designed to explore the cancer outcomes of premenopausal women who had primary breast cancer and who became pregnant at any time after diagnosis.
Methods: Searches were conducted in ten databases until July 2024, with no language restrictions. We analyzed aggregate data across all study populations and performed subgroup analyses by stage, estrogen receptor status, BRCA mutation status, HER2 status, previous treatment, lymph node status, interval between pregnancy and diagnosis, pregnancy type, reproductive status, and breastfeeding status.
Results: Fifty-two studies were included. The pregnancy group had longer overall survival (n = 18) [RR = 1.09 (1.06, 1.12), P < 0.001]. Nine studies reported the same results [HR = 0.60 (0.48, 0.73), P < 0.001]. The disease-free survival (n = 7) of the pregnancy group was not significantly longer [HR = 0.90 (0.79, 1.02), P = 0.111]. The pregnancy group had longer breast cancer-specific survival (n = 3) [HR = 0.55 (0.40, 0.76), P < 0.001]. The pregnancy group had a lower recurrence rate (n = 17) [RR = 0.61 (0.55, 0.68), P < 0.001]. The pregnancy group had a higher loco-regional recurrence rate, although the difference was not statistically significant (n = 4) [RR = 1.04 (0.74, 1.47), P = 0.814]. The pregnancy group had a lower distant recurrence rate (n = 5) [RR = 0.50 (0.37, 0.68), P < 0.001]. The pregnancy group had a higher contralateral breast cancer rate, although the difference was not statistically significant (n = 3) [RR = 1.06 (0.76, 1.48), P = 0.742].
Discussion: Our findings indicate that pregnancy after breast cancer does not lead to adverse cancer outcomes. Stage, estrogen receptor status, therapy choice (hormone, chemotherapy, or endocrine therapy combined with chemotherapy), and reproductive status are not associated with overall survival. BRCA2 mutation may negatively affect disease-free survival in pregnant patients with breast cancer.
Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42024499971.
Graphical Abstract. Impact of Pregnancy on Survival and Recurrence Outcomes in Breast Cancer Patients. Study flowchart illustrating data sources and analysis results for breast cancer survival. Begins with screening 35,018 records across ten databases, resulting in 52 included studies. Experimental group consists of 9,288 pregnant women; control group has 123,429 non-pregnant women. Graphs show pregnant women have higher survival probabilities and lower recurrence rates in several areas. Statistically significant increases were noted in overall and breast cancer-specific survival, along with significant reductions in certain recurrence rates. No statistically significant association was observed for disease-free survival, loco-regional recurrence, or contralateral breast cancer rates.
1 Introduction
Global statistical data for 2022 revealed that breast cancer (BC) was the most prevalent cancer among women, with 2,308,897 new cases reported worldwide (1). Owing to the improved survival and rejuvenation of patients with BC and the delay of reproductive age in modern people, the convergence of BC diagnosis age and reproductive age distribution is enhanced (2).
However, BC is a hormone-responsive cancer type, and with the increase in female hormones during pregnancy, there is a widespread apprehension that pregnancy may heighten the patient’s risk of recurrence (3). BC patients and their physicians still worry about the safety of babies and mothers after the diagnosis and treatment of BC (4).
There is no consensus on this topic. We aimed to explore the cancer outcomes of premenopausal women who had primary BC and who became pregnant at any time after diagnosis. Compared with previous related meta-analyses, this article included the latest evidence and more databases, such as the POSITIVE clinical trial (5), the study of young BC BRCA carriers (6), and Chinese databases, making it more comprehensive.
2 Materials and methods
2.1 Study subjects and outcome indicators
The experimental group included premenopausal women who had primary BC and who became pregnant at some point after diagnosis. The control group included nonpregnant women with BC.
The outcome indicators included overall survival (OS), disease-free survival(DFS), BC-specific survival, recurrence rate, loco-regional recurrence, distant recurrence, contralateral BC, 5-year relapse-free survival (RFS), 5-year DFS, and 5,10-year survival. OS is defined as the time from the start of a treatment or randomization to the time of death from any cause. DFS is defined as the time from the start of treatment or randomization until the recurrence of disease or death from any cause. BC-specific survival is defined as the time from the diagnosis of BC until death from BC or until the last follow-up visit if the patient is still alive and has not died from BC. RFS is defined as the time interval between complete response after antitumor treatment and the cutoff for recurrence or follow-up.
2.2 Search strategies
We conducted this systematic review and meta-analysis in accordance with the PRISMA 2020 guidelines (7) and MOOSE statement (8). The following databases were searched: PubMed, EMBASE, Cochrane Library, Science Direct, Web of Science, Scopus, CNKI, VIP, Wan Fang, and SinoMed, with no language restrictions until July 2024.
A combination of subject words and free words was used for retrieval. The search terms included “Breast Neoplasms” AND “Pregnancy OR Fertilization OR Parturition OR Fertility OR Obstetrics”. More details are provided in Appendix A. Registration: CRD 42024499971 (PROSPERO). The full protocol is available on the PROSPERO website.
2.3 Inclusion and exclusion criteria
The inclusion criteria were as follows: (1) premenopausal women; (2) studies reporting on pregnancy after primary BC diagnosis; (3) studies with available information on cancer outcomes; (4) prospective and retrospective cohort studies, prospective clinical trials, case–control studies and case series; and (5) outcomes that could be extracted or measured.
The exclusion criteria were as follows: (1) combination with other malignant tumors; (2) pregnancy-related BC (primary BC diagnosed during pregnancy or within one year after pregnancy (lactation); (3) case reports or case series including fewer than 10 patients; and (4) ongoing studies for which results were not presented or published at the time of the literature search.
2.4 Literature screening and data extraction
Two reviewers (Mei and Song) independently evaluated the titles and abstracts. A third author (Lu) resolved any disagreements. Full papers were reviewed, and data extraction was performed independently by five reviewers (Mei, Song, Wang, Liu, and Zhang), who were pilot tested by the other two reviewers (Chang and Zhuo). The extracted data included the first author, country, type of literature, year of publication, recruitment time, follow-up time, interval between diagnosis and pregnancy, tumor characteristics, previous treatment, number of patients in each group, cancer outcomes, and cancer outcomes in the subgroups.
2.5 Quality evaluation
Two authors (Mei and Song) independently conducted the quality evaluation, and the third author (Lu) resolved the differences. The quality assessment of cohort studies and case–control studies was conducted using the Newcastle–Ottawa Scale (NOS) (9), that of nonrandomized clinical trials was conducted using MINORS (10), and that of case series was conducted using the JBI critical appraisal tool (11).
2.6 Statistical analysis
The meta-analysis was carried out using Stata 17.0 software. For dichotomous variables, we selected either the relative risk (RR) or the odds ratio (OR) and their 95% confidence interval (CI) according to the type of study. If only the effect size hazard ratio (HR) was included in the original literature, the HR was directly combined. A table-based form was used to describe the results, and forest plots were used to graphically represent the results of the syntheses. The chi-square test was employed to assess heterogeneity among the studies. P < 0.05 and I2 > 50% suggested statistical heterogeneity, in which case a random effects model was used. Otherwise, a fixed-effects model was used. Sensitivity analysis was performed using the one-by-one elimination method. Publication bias analysis was conducted utilizing both the funnel plot and Egger’s test. The significance level was α =0.05.
Subgroup analysis was used to investigate possible sources of heterogeneity, including BC stage, estrogen receptor(ER) status, BRCA mutation status, HER2 status, previous treatment, lymph node status, interval between pregnancy and diagnosis, pregnancy type, reproductive status, and breastfeeding status. Owing to the limitation of the available extracted data for subgroups, the majority of the outcome indicators were derived from only two articles. The sensitivity analysis chart composed solely of two articles had limited significance; consequently, this chart was excluded during the subgroup analysis.
3 Results
3.1 Literature retrieval results
Among the 35,018 identified records, 52 studies were included. The PRISMA flow diagram is shown in Figure 1. The pregnancy group included 9,288 patients, and nonpregnancy group included 123,429 patients. Basic information is presented in Table 1 and Table 2.
Figure 1. PRISMA 2020 flow diagram of study selection process.
Table 1. Basic information of included articles.
Table 2. Cancer outcomes of included articles.
3.2 Quality evaluation
The results are presented in Appendix B. Among the cohort studies, 21 were categorized as high-quality and 17 as medium-quality. Among the case–control studies, two were deemed medium-quality, and one was deemed high-quality.
3.3 Cancer outcomes
3.3.1 Overall survival
A meta-analysis of OS was performed on the basis of the dichotomous data (number of events) reported by 18 studies (6, 12–28), which included 3,390 pregnant BC patients and 52,166 nonpregnant BC patients. The pregnancy group had longer OS [RR = 1.09, 95% CI (1.06, 1.12), P < 0.001] (Figure 2). A funnel plot (Figure C.33) and Egger’s test (P = 0.099) revealed no significant publication bias. The sensitivity analysis is shown in Figure C.34.
Figure 2. Forest plot of survival outcomes in pregnant BC patients compared with nonpregnant BC patients.
A separate meta-analysis of OS was conducted using HRs directly extracted from Cox proportional hazards models in 9 studies (29–37), involving 4,037 pregnant BC patients and 67,391 nonpregnant BC patients. The pregnancy group had longer OS [HR = 0.60, 95% CI (0.48, 0.73), P < 0.001] (Figure 2). A funnel plot (Figure C.35) and Egger’s test (P = 0.770) revealed no significant publication bias. The sensitivity analysis results are shown in Figure C.36.
3.3.2 Disease-free survival
Seven studies (12, 19, 22, 35–38) compared the DFS of 1,666 pregnant BC patients and 10,247 nonpregnant BC patients. The pregnancy group had numerically longer DFS compared to the nonpregnancy group, although this difference did not reach statistical significance [HR = 0.90, 95% CI (0.79, 1.02), P = 0.111] (Figure 2). A funnel plot (Figure C.37) and Egger’s test (P = 0.197) revealed no significant publication bias. The results of the sensitivity analysis are shown in Figure C.38.
3.3.3 Breast cancer-specific survival
Three studies (34, 38, 39) compared the BC-specific survival of 1,232 pregnant BC patients with that of 4,862 nonpregnant BC patients. The BC-specific survival of the pregnancy group was longer [HR = 0.55, 95% CI (0.40, 0.76), P < 0.001] (Figure 2). A funnel plot (Figure C.39) and Egger’s test (P = 0.972) revealed no significant publication bias. The results of the sensitivity analysis are shown in Figure C.40.
3.3.4 Recurrence rate
Seventeen studies (12, 13, 18, 21, 23, 24, 26, 27, 35, 40–47) compared the recurrence rates of the 2,273 pregnant BC patients with those of 39,019 nonpregnant BC patients. The pregnancy group had a lower recurrence rate [RR = 0.61, 95% CI (0.55, 0.68), P < 0.001] (Figure 3). A funnel plot (Figure C.41) and Egger’s test (P = 0.763) revealed no significant publication bias. The results of the sensitivity analysis are shown in Figure C.42.
Figure 3. Forest plot of recurrence outcomes in pregnant BC patients compared with nonpregnant BC patients.
3.3.5 Loco-regional recurrence rate
Four studies (12, 18, 35, 47) reported the loco-regional recurrence rate of 835 pregnant BC patients compared with 4,826 nonpregnant BC patients. The loco-regional recurrence rate was slightly higher in the pregnancy group, but the difference was not statistically significant [RR = 1.04, 95% CI (0.74, 1.47), P = 0.814] (Figure 3). A funnel plot (Figure C.43) and Egger’s test results (P = 0.012) revealed significant publication bias. The results of the sensitivity analysis are shown in Figure C.44.
3.3.6 Distant recurrence rate
Five studies (12, 18, 35, 40, 47) reported the distant recurrence rate of 885 pregnant BC patients and 6,895 nonpregnant BC patients. The distant recurrence rate of the pregnancy group was lower [RR = 0.50, 95% CI (0.37, 0.68), P < 0.001] (Figure 3). A funnel plot (Figure C.45) and Egger’s test (P = 0.520) revealed no significant publication bias. The sensitivity analysis is shown in Figure C.46.
3.3.7 Contralateral breast cancer rate
Three studies (12, 35, 47) reported the contralateral BC rate of 815 pregnant BC patients and 4,806 nonpregnant BC patients. The pregnancy group had a higher contralateral BC rate, but the difference was not statistically significant [RR = 1.06, 95% CI (0.76, 1.48), P = 0.742] (Figure 3). A funnel plot (Figure C.47) and Egger’s test (P = 0.456) revealed no significant publication bias. However, sensitivity analysis indicated that the results were unstable and were influenced predominantly by one study (35) (Figure C.48).
3.3.8 Relapse-free survival rate
Three studies (26, 42, 48) reported the 5-year RFS rate, including 1,175 pregnant BC patients. The result was 78% [95% CI (0.58, 0.97), P < 0.001] (Figure C.1). A funnel plot (Figure C.49) and Egger’s test (P = 0.411) revealed no significant publication bias. The results of the sensitivity analysis are shown in Figure C.50.
Two studies (26, 42) reported the 5-year RFS rate, including 31,092 nonpregnant BC patients. The result was 65% [95% CI (0.34, 0.95), P < 0.001] (Figure C.2). A funnel plot (Figure C.51) indicated that there might be publication bias. Sensitivity analysis indicated that the pooled estimate was unstable (Figure C.52).
3.3.9 5-year disease-free survival rate
Four studies (13, 18, 43, 49) reported the 5-year DFS rate, including 138 pregnant BC patients. The result was 80% [95% CI (0.64, 0.95), P < 0.001] (Figure C.3). A funnel plot (Figure C.53) and Egger’s test (P = 0.934) revealed no significant publication bias. The sensitivity analysis results are shown in Figure C.54.
Four studies (13, 18, 43, 49) reported the 5-year DFS rate, including 319 nonpregnant BC patients. The result was 60% [95% CI (0.33, 0.88), P < 0.001] (Figure C.4). A funnel plot (Figure C.55) and Egger’s test (P = 0.682) revealed no significant publication bias. The sensitivity analysis is shown in Figure C.56.
3.3.10 5-year survival rate
Nine studies (13, 14, 16, 18, 26, 31, 48, 50, 51) reported on the 5-year survival rate of 1,564 BC patients in the pregnancy group. The result was 88% [95% CI (0.83,0.93), P < 0.001] (Figure C.5). A funnel plot (Figure C.57) and Egger’s test (P = 0.012) revealed significant publication bias. The sensitivity analysis is shown in Figure C.58.
Seven cohort studies (13, 14, 16, 18, 26, 31, 49) reported on the 5-year survival rate of 35,348 BC patients in the nonpregnancy group. The result was 82% [95% CI (0.78,0.86), P < 0.001] (Figure C.6). A funnel plot (Figure C.59) and Egger’s test (P = 0.198) revealed no significant publication bias. The results of the sensitivity analysis are shown in Figure C.60.
3.3.11 10-year survival rate
Six studies (14, 16, 36, 48, 50, 51) reported the 10-year survival rate of 676 pregnant patients with BC. The result was 82% [95% CI (0.71,0.92), P < 0.001] (Figure C.7). A funnel plot (Figure C.61) and Egger’s test (P = 0.027) revealed significant publication bias. The sensitivity analysis is shown in Figure C.62.
Three studies (14, 16, 36) reported the 10-year survival rate of 931 nonpregnant BC patients. The result was 75% [95% CI (0.54,0.97), P < 0.001] (Figure C.8). A funnel plot (Figure C.63) and Egger’s test (P = 0.562) revealed no significant publication bias. The sensitivity analysis is shown in Figure C.64.
3.4 Subgroup analysis
3.4.1 BC stage
Pregnancy was a protective factor for OS in stage I BC patients (15, 17, 25, 32, 34) [HR = 0.59, 95% CI (0.43, 0.80), P = 0.001] (Figure C.9). A funnel plot (Figure C.65) and Egger’s test (P = 0.106) revealed no significant publication bias. The results of the sensitivity analysis are shown in Figure C.66.
Stage II and III BC patients in the pregnant group had longer OS (15, 17, 25, 32) [HR = 0.57, 95% CI (0.43, 0.77), P < 0.001] (Figure C.10). A funnel plot (Figure C.67) and Egger’s test (P = 0.554) revealed no significant publication bias. Sensitivity analysis indicated that the results were unstable and were predominantly influenced by one study (17) (Figure C.68).
3.4.2 ER status
3.4.2.1 Overall survival
ER-positive BC patients in the pregnant group had longer OS (25, 32, 37, 38) [HR = 0.75, 95% CI (0.58, 0.96), P = 0.024] (Figure C.11). A funnel plot (Figure C.69) and Egger’s test (P = 0.072) revealed no significant publication bias. Sensitivity analysis indicated that the pooled estimate was unstable and was influenced by the articles published in 2022 (32) and 2020 (25) (Figure C.70).
ER-negative BC patients in the pregnant group had longer OS (25, 32, 37, 38) [HR = 0.52, 95% CI (0.40, 0.69), P < 0.001] (Figure C.12). A funnel plot (Figure C.71) and Egger’s test (P = 0.968) revealed no significant publication bias. The sensitivity analysis results are shown in Figure C.72.
3.4.2.2 Disease free survival
ER-positive BC patients in the pregnancy group had shorter DFS, but the difference was not statistically significant (35, 37, 38) [HR = 1.14, 95% CI (0.93, 1.39), P = 0.203] (Figure C.13). A funnel plot (Figure C.73) and Egger’s test (P = 0.591) revealed no significant publication bias. The sensitivity analysis results are shown in Figure C.74.
ER-negative BC patients in the pregnant group had longer DFS (35, 37, 38) [HR = 0.74, 95% CI (0.62, 0.89), P = 0.001] (Figure C.14). A funnel plot (Figure C.75) and Egger’s test (P = 0.322) revealed no significant publication bias. The sensitivity analysis is shown in Figure C.76.
3.4.3 BRCA mutation
The pregnancy group had longer DFS in BRCA mutation BC patients, although this difference was not statistically significant (35, 38) [HR = 0.96, 95% CI (0.81, 1.14), P = 0.640] (Figure C.15). A funnel plot is shown in Figure C.77. Among BRCA1 mutation BC patients, those in the pregnancy group had longer DFS (35, 38) [HR = 0.76, 95% CI (0.62, 0.94), P = 0.010]. Among BRCA2 mutation BC patients, those in the pregnancy group had shorter DFS (35, 38) [HR = 1.64, 95% CI (1.23, 2.18), P = 0.001].
3.4.4 HER2 status
The pregnancy group had longer DFS in HER2 positive BC patients, although this difference was not statistically significant (22, 38) [HR = 0.90, 95% CI (0.49, 1.66), P = 0.737] (Figure C.16). A funnel plot (Figure C.78) indicated that there was no publication bias.
3.4.5 Hormone therapy
The pregnancy group had better OS among BC patients who had received hormone therapy (17, 25, 33, 36, 38) [HR = 0.36, 95% CI (0.25, 0.50), P < 0.001] (Figure C.17). A funnel plot (Figure C.79) and Egger’s test (P = 0.872) revealed no significant publication bias. The sensitivity analysis results are shown in Figure C.80.
The pregnancy group had better OS among BC patients who did not receive hormone therapy (17, 25, 33, 36, 38) [HR = 0.41, 95% CI (0.26, 0.64), P < 0.001] (Figure C.18). A funnel plot (Figure C.81) and Egger’s test (P = 0.714) revealed no significant publication bias. The sensitivity analysis results are shown in Figure C.82.
3.4.6 Chemotherapy
The pregnancy group had longer OS in BC patients who had received chemotherapy (17, 25, 32, 33, 36, 38) [HR = 0.48, 95% CI (0.31, 0.74), P = 0.001] (Figure C.19). A funnel plot (Figure C.83) and Egger’s test (P = 0.364) revealed no significant publication bias. The sensitivity analysis results are shown in Figure C.84.
The pregnancy group had longer OS among BC patients who did not receive chemotherapy (17, 25, 38) [HR = 0.57, 95% CI (0.39, 0.84), P = 0.004] (Figure C.20). A funnel plot (Figure C.85) and Egger’s test (P = 0.721) revealed no significant publication bias. Sensitivity analysis indicated that the pooled estimate was unstable and was influenced by the article (17). (Figure C.86).
3.4.7 Endocrine therapy plus chemotherapy
The pregnancy group had longer OS in BC patients who had received endocrine therapy plus chemotherapy (33, 36) [HR = 0.31, 95% CI (0.18, 0.54), P < 0.001] (Figure C.21). A funnel plot (Figure C.87) indicated that there was no publication bias.
3.4.8 Chemotherapy plus trastuzumab
The pregnancy group had longer OS in BC patients who had received chemotherapy plus trastuzumab, although this difference was not statistically significant (33, 36) [HR = 0.35, 95% CI (0.09, 1.39), P = 0.135] (Figure C.22). A funnel plot (Figure C.88) indicated that there might be publication bias.
3.4.9 ER positivity and interruption of adjuvant endocrine therapy
The recurrence rate was not significantly lower in the pregnant group of ER-positive BC patients who had interruption of adjuvant endocrine therapy (46, 47) [RR = 0.77, 95% CI (0.57, 1.05), P = 0.098] (Figure C.23). A funnel plot (Figure C.89) indicated that there was no publication bias.
3.4.10 Lymph node status
The pregnancy group had longer OS in patients with lymph node-positive BC, although this difference was not statistically significant (17, 25, 28) [RR = 1.10, 95% CI (0.99, 1.22), P = 0.074] (Figure C.24). A funnel plot (Figure C.90) and Egger’s test (P = 0.695) revealed no significant publication bias. The sensitivity analysis is shown in Figure C.91.
The pregnancy group had longer OS in patients with lymph node-negative BC (17, 25, 28) [RR = 1.04, 95% CI (1.00, 1.08), P = 0.033] (Figure C.25). A funnel plot (Figure C.92) and Egger’s test (P = 0.267) revealed no significant publication bias. Sensitivity analysis indicated that the results were unstable (Figure C.93).
3.4.11 Interval between diagnosis and pregnancy
The pregnancy group had longer DFS in BC patients with an interval between diagnosis and pregnancy ≤2 years (37, 38)[HR = 0.58, 95% CI (0.46, 0.74), P < 0.001] (Figure C.26). A funnel plot (Figure C.94) indicated that there was no publication bias.
The pregnancy group had longer DFS in BC patients, with an interval between diagnosis and pregnancy >2 years, although this difference was not statistically significant (37, 38) [HR = 0.85, 95% CI (0.50, 1.42), P = 0.529] (Figure C.27). A funnel plot (Figure C.95) indicated that there might be publication bias.
3.4.12 Pregnancy type
BC patients who had received assisted reproductive technology(ART) had a lower recurrence rate than those who had achieved spontaneous conception (12, 45, 52, 53) [RR = 0.18, 95% CI (0.06, 0.57), P = 0.003] (Figure C.28). A funnel plot (Figure C.96) and Egger’s test (P = 0.457) revealed no significant publication bias. Sensitivity analysis indicated that the pooled estimate was unstable and was influenced by the article (52) (Figure C.97).
3.4.13 Reproductive status
BC patients with full-term pregnancies had longer OS than nonpregnant BC patients did (12, 15, 17, 25, 26, 29, 30, 32, 33, 36, 38) [HR = 0.47, 95% CI (0.36, 0.60), P < 0.001] (Figure C.29). A funnel plot (Figure C.98) and Egger’s test (P = 0.449) revealed no significant publication bias. The sensitivity analysis is shown in Figure C.99.
BC patients with spontaneous or induced abortions had longer OS than nonpregnant BC patients (25, 26, 36, 38) [HR = 0.67, 95% CI (0.48, 0.94), P = 0.020] (Figure C.30). A funnel plot (Figure C.100) and Egger’s test (P = 0.848) revealed no significant publication bias. Sensitivity analysis indicated that the pooled estimate was unstable and was influenced by the article (6) (Figure C.101).
3.4.14 Breastfeeding
Pregnant BC patients who had breastfed their newborns had longer DFS than nonpregnant BC patients, although this difference was not statistically significant (37, 38) [HR = 0.75, 95% CI (0.55, 1.03), P = 0.072] (Figure C.31). A funnel plot revealed no significant publication bias (Figure C.102).
Pregnant BC patients who had not breastfed their newborns had longer DFS than nonpregnant BC patients, although this difference was not statistically significant (37, 38) [HR = 0.82, 95% CI (0.29, 2.30), P = 0.702] (Figure C.32). A funnel plot indicated that there might be publication bias (Figure C.103).
4 Discussion
Recently, a growing number of studies have indicated that pregnant patients with BC do not face an elevated risk of relapse (6, 54). However, owing to the complexity of cancer and its treatment, oncologists remain concerned about the outcomes of pregnancy following a BC diagnosis. This systematic review provides updated evidence on pregnancy after breast cancer.
Our study revealed that pregnant BC patients had better cancer outcomes, such as OS, BC-specific survival, recurrence rate, and distant recurrence rate, than nonpregnant BC patients did. Subgroup analysis revealed that pregnant BC patients had longer OS than nonpregnant BC patients did, and the results were not related to BC stage, ER status, hormone therapy, chemotherapy, or endocrine therapy combined with chemotherapy or reproductive status.
The pregnancy group had significantly longer DFS among ER-negative BC patients. However, ER-positive BC patients of the pregnancy group had shorter DFS, although the difference was not statistically significant. ER-positive pregnant patients might interrupt adjuvant endocrine therapy because of pregnancy, which might result in a shorter DFS. However, the POSITIVE trial (5) indicated that temporarily discontinuing endocrine therapy did not result in an increased short-term risk of BC events. We suspected that the small sample size of the included articles or the disparity in outcome indicators compared with those of the POSITIVE trial might explain the observed results. We look forward to longer follow-up of the POSITIVE trial to support this line of inquiry.
Among BRCA1 mutation BC patients, pregnant BC patients had significantly longer DFS. However, among patients with BRCA2 mutation BC patients, pregnant patients with BC had significantly shorter DFS. Pregnancy has potential protective effects on patients with BRCA1 mutations and may have negative effects on BRCA2 mutation carriers (35). Late age at first birth, breastfeeding, and delayed menarche protect only BC patients with BRCA1 mutations (55). The BRCA2 mutation population deserves further attention, and pregnancy requires careful consideration.
Notably, the results revealed that compared with BC patients who had achieved spontaneous conception, BC patients who had received ART had a lower recurrence rate. One study revealed that ART treatment could reduce the incidence of BC (56), but the literature does not support that ART treatment is associated with better survival results. This may reflect selection bias. BC patients with earlier stages and better physical condition are more likely to consider ART for pregnancy, which could contribute to a lower recurrence rate.
This study has several limitations. First, most of the included studies were retrospective in design. Second, the limited number of studies available for certain subgroups reduced the robustness of the findings. Most importantly, direct comparisons between clinically relevant subgroups were precluded by the lack of available data; consequently, the analyses had to rely on indirect comparisons, which are susceptible to unmeasured confounding. Furthermore, the results may be influenced by a “healthy mother effect”, wherein women who conceive after a cancer diagnosis tend to have earlier-stage disease and a lower intrinsic risk of relapse, potentially biasing the outcomes. To address these limitations, we emphasize the need for future large-scale, prospective studies. Such studies should be specifically designed to enable direct comparisons between carefully defined subgroups, incorporating key clinicopathological variables such as breastfeeding status, nodal status, reproductive history, and the timing of pregnancy relative to diagnosis, among others.
5 Conclusions
Our results indicate that pregnancy after a BC diagnosis does not lead to adverse cancer outcomes. BRCA2 mutation may be a harmful factor for DFS in pregnant BC patients and deserves attention.
Data availability statement
The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author.
Author contributions
HM: Methodology, Conceptualization, Writing – original draft, Data curation, Visualization, Formal Analysis. QS: Data curation, Methodology, Conceptualization, Visualization, Writing – original draft, Formal Analysis. WL: Conceptualization, Project administration, Funding acquisition, Writing – original draft, Methodology. XW: Data curation, Writing – review & editing. JL: Writing – review & editing, Data curation, Validation. WZ: Writing – review & editing, Data curation. LC: Supervision, Data curation, Writing – review & editing. ZZ: Writing – review & editing, Data curation, Supervision.
Funding
The author(s) declare financial support was received for the research and/or publication of this article. The work was supported by High Level Chinese Medical Hospital Promotion Project -Special Project on Formulation R&D and New Drug Translation for Medical Institutions (HLCMHPP2023037).
Acknowledgments
We would like to express sincere gratitude to the investigators who participated in this study. We also thank American Journal Experts (AJE) for their assistance with English language editing.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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The author(s) declare that no Generative AI was used in the creation of this manuscript.
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Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fonc.2025.1644566/full#supplementary-material
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Keywords: breast cancer, pregnancy, cancer outcomes, meta-analysis, review
Citation: Mei H, Song Q, Lu W, Wang X, Liu J, Zhang W, Chang L and Zhuo Z (2025) Cancer outcomes of pregnancy after diagnosis of breast cancer in premenopausal women: an updated systematic review and meta-analysis. Front. Oncol. 15:1644566. doi: 10.3389/fonc.2025.1644566
Received: 10 June 2025; Accepted: 23 September 2025;
Published: 14 October 2025.
Edited by:
Rohit Kumar, Homi Bhabha Cancer Hospital and Mahamana Pandit Madan Mohan Malaviya Cancer Centre, IndiaReviewed by:
Prashanth Giridhar, Tata Memorial Centre, IndiaHiral Uday Mistry, Memorial Sloan Kettering Cancer Center, NY, United States
Copyright © 2025 Mei, Song, Lu, Wang, Liu, Zhang, Chang and Zhuo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Wenping Lu, bHVfd2VucGluZ0BzaW5hLmNvbQ==
†These authors share first authorship