Literature DB >> 32778072

Prognosis of pregnancy-associated breast cancer: a meta-analysis.

Chunchun Shao1, Zhigang Yu2, Juan Xiao1, Liyuan Liu2, Fanzhen Hong3, Yuan Zhang4,5, Hongying Jia6.   

Abstract

BACKGROUND: Pregnancy-associated breast cancer (PABC) is defined as breast cancer that is diagnosed during pregnancy and/or the postpartum period. Definitions of the duration of the postpartum period have been controversial, and this variability may lead to diverse results regarding prognosis. Moreover, evidence on the dose-response association between the time from the last pregnancy to breast cancer diagnosis and overall mortality has not been synthesized.
METHODS: We systematically searched PubMed, Embase, and the Cochrane Library for observational studies on the prognosis of PABC published up to June 1, 2019. We estimated summary-adjusted hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs). Subgroup analyses based on diagnosis time, PABC definition, geographic region, year of publication and estimation procedure for HR were performed. Additionally, dose-response analysis was conducted by using the variance weighted least-squares regression (VWLS) trend estimation.
RESULTS: A total of 54 articles (76 studies) were included in our study. PABC was associated with poor prognosis for overall survival (OS), disease-free survival (DFS) and cause-specific survival (CSS), and the pooled HRs with 95% CIs were 1.45 (1.30-1.63), 1.39 (1.25-1.54) and 1.40 (1.17-1.68), respectively. The corresponding reference category was non-PABC patients. According to subgroup analyses, the varied definition of PABC led to diverse results. The dose-response analysis indicated a nonlinear association between the time from the last delivery to breast cancer diagnosis and the HR of overall mortality (P < 0.001). Compared to nulliparous women, the mortality was almost 60% higher in women with PABC diagnosed at 12 months after the last delivery (HR = 1.59, 95% CI 1.30-1.82), and the mortality was not significantly different at 70 months after the last delivery (HR = 1.14, 95% CI 0.99-1.25). This finding suggests that the definition of PABC should be extended to include patients diagnosed up to approximately 6 years postpartum (70 months after the last delivery) to capture the increased risk.
CONCLUSION: This meta-analysis suggests that PABC is associated with poor prognosis, and the definition of PABC should be extended to include patients diagnosed up to approximately 6 years postpartum.

Entities:  

Keywords:  Dose-response; Meta-analysis; Pregnancy-associated breast cancer; Prognosis; Survival

Mesh:

Year:  2020        PMID: 32778072      PMCID: PMC7418189          DOI: 10.1186/s12885-020-07248-8

Source DB:  PubMed          Journal:  BMC Cancer        ISSN: 1471-2407            Impact factor:   4.430


Background

Breast cancer is the second most common cancer worldwide and the most commonly occurring malignancy in women [1]. Due to the trend of delayed delivery, the number of women with breast cancer during a pregnancy or in the subsequent few years after a pregnancy is expected to increase [2]. Breast cancer occurring during pregnancy is a challenging clinical situation since the welfare of both the mother and the foetus must be considered in any treatment plan. Conventionally, pregnancy-associated breast cancer (PABC) is defined as breast cancer that is diagnosed during pregnancy or the postpartum period. Definitions of how many years after delivery breast cancer can be diagnosed under this definition have ranged from 0.5 to 5 years, and sometimes even longer [3, 4]. PABC is viewed as a clinically and biologically special type of breast cancer and only comprises 0.2–0.4% of all breast cancers [5, 6]. However, it is the most common cancer in pregnancy and is diagnosed in approximately 15 to 35 per 100,000 births, and the number of breast cancer cases diagnosed during pregnancy is less than after delivery [7-10]. Pregnancy itself may temporarily increase the risk of developing breast cancer, although it has a long-term protective effect on the development of breast cancer [11, 12]. However, whether PABC has a worse prognosis is currently controversial. A meta-analysis published in 2016 showed that the risk of death increased in women with PABC compared with women with non-PABC (pooled hazard ratio (HR), 1.57; 95% confidence interval (CI), 1.35–1.82) [13]. However, other recent studies found no significant difference in the prognosis of PABC and non-PABC [14-17]. Meanwhile, the specific definition of PABC has varied and this variability may lead to diverse results on the relationship among pregnancy, postpartum and breast cancer. Therefore, it is necessary to specify the definition of PABC by summarizing epidemiological evidence. This study was initiated to understand the prognosis of PABC and examine the dose-response relationship to provide quantitative evidence for defining PABC.

Methods

Search strategy

This meta-analysis was performed in accordance with the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. We did our best to include studies published to date regarding the prognosis of PABC. Eligible studies were found by searching PubMed, Embase, and the Cochrane Library for relevant reports published before June 1, 2019. The keywords used for the search were (“pregnan*” OR “gestation*” OR “childbirth” OR “postpartum” OR “parity”) AND “breast” AND (“cancer” OR “neoplasia” OR “carcinoma”). The references lists of all retrieved articles and previous systematic reviews were manually searched.

Inclusion and exclusion criteria

All eligible studies met the following criteria: (1) observational prognostic studies with a follow-up period longer than 6 months; (2) participants were diagnosed with breast cancer by clinical diagnosis and/or histologically; (3) the case group was diagnosed with PABC, and the control group was non-PABC or nulliparity; (4) the outcomes were in terms of overall survival (OS), disease-free survival (DFS) or cause-specific survival (CSS); and (5) the risk point estimate was reported as an HR with 95% CI, or the data were presented such that an HR with 95% CI could be calculated. The exclusion criteria were as follows: (1) duplicated or irrelevant articles; (2) reviews, letters, and case reports; (3) non-human studies; and (4) studies with inappropriate data for meta-analysis, such as incomplete or inconsistent data.

Data extraction

Two reviewers extracted the data independently using a predefined data extraction form. Any disagreements were resolved by discussion. The extracted data included the first author, publication year, country, PABC definition, control definition, sample size, cancer type, stage or grade, age, matching criteria, adjusted variables, and adjusted HRs with 95% CIs.

Assessment of study quality

The methodological quality of the studies was assessed by the Newcastle-Ottawa scale (NOS) [18]. A score of 0–9 was allocated to each study, with higher scores indicating higher quality.

Meta-analysis and statistical analysis

We used adjusted HRs and 95% CIs, which are most appropriate for time-to-data events. If HRs were not reported, we estimated HRs from the raw data or Kaplan-Meier curves [19]. The I-square (I2) test was performed to assess the impact of study heterogeneity on the results of the meta-analysis. If severe heterogeneity was present at I2 > 50%, a random effects model was chosen; otherwise, a fixed effects model was used. Visual inspection of the funnel plot and Egger’s and Begg’s tests were performed to assess publication bias. Subgroup analyses were performed according to the diagnosis time, PABC definition, geographic region, year of publication and estimation procedure for HR. Variance-weighted least squares regression (VWLS) model was used to evaluate the dose-response association between the time from the last pregnancy to breast cancer diagnosis and HR of overall mortality [20]. Restricted cubic splines were used to check the time from the last pregnancy as a continuous, nonlinear exposure, and the time was defined by the 5th, 35th, 65th and 95th percentiles of the distribution [21]. The time from the last pregnancy to breast cancer diagnosis reported in each study was converted to months. We used the average value of the lower and upper limits of each category. If the lowest category was open ended, the average value of the upper limit and 0 was used. If the highest category was open ended, the average value was defined as 1.5 times the lower limit. All statistical analyses were performed using STATA Version 13.0. P < 0.05 was considered significant.

Results

Search results and study characteristics

We initially identified 12,414 articles and screened their titles and abstracts (Fig. 1). After duplicated and irrelevant articles were excluded, 54 articles with 76 studies met the inclusion criteria and were thus included in our meta-analysis. The quality of the studies was assessed based on the NOS and ranged from 6 to 9 (mean of 7.2). The characteristics of the studies are summarized in Table 1.
Fig. 1

Schematic representation of the study selection process

Table 1

Characteristics of the studies included in the meta-analysis

Study IDCountryNo. of PABC casesNo. of controlsPABC definitionCancer stage or gradeMean/median age of PABCFollow-up yearsOutcomes measuredHR estimateHR95% CINOS scoreMatching criteriaAdjusting variable
Mausner, 1969 [22]USA73647Pregnancy & < 6 months postpartumStage I II III, Grade I II III355OSindirect1.361.07–1.737
Wallgren, 1977 [23]Sweden1558Pregnancy & < 12 months postpartumGrade I II III< 3010OSindirect1.350.71–2.587
Nugent, 1985 [24]USA19155PregnancyStage I II III325OSindirect0.960.55–1.676
Tretli, 1988-Pregnancy [25]Norway2040PregnancyStage I II III334OSindirect2.411.32–4.376Diagnosed year, diagnosed age
Tretli, 1988-Postpartum [25]Norway1540UnspecifiedStage I II III364OSindirect1.470.66–3.276
Greene, 1988 [26]USA836PregnancyNA<3514OSindirect1.500.18–12.626
Petrek, 1991 [27]USA56166Pregnancy & < 12 months postpartumNA5OSpaper0.740.37–1.456Node status
Zemlickis, 1992 [28]Canada102269Pregnancy & postpartum (unspecified)Stage 0 I II III IV3325CSSindirect1.250.93–1.698Stage, age at diagnosis
Ishida, 1992 [29]Japan192191Pregnancy & < 24 months postpartumStage 0 Tis I II III IV3210OSindirect2.001.27–3.166
Guinee, 1994-Pregnancy [30]USA26139PregnancyNA28(20–29)10OSpaper2.831.24–6.458Tumour size, number of positive axillary nodes
Guinee, 1994-Postpartum [30]USA40139< 12 Months postpartumNA28(20–29)10OSpaper1.880.88–3.988
Von Schoultz, 1995 [31]Sweden1731740Pregnancy & < 60 months postpartumNA< 507DFSpaper1.020.72–1.439Age, nodal status, tumour size, ER status
Ezzat, 1996-OS [32]Saudi Arabia2884PregnancyStage I II III20–457OSpaper0.900.6–1.36Year of diagnosis, date of beginning
Ezzat, 1996-DFS [32]Saudi Arabia2884PregnancyStage I II III20–457DFSpaper1.100.8–1.56
Anderson, 1996-OS [33]USA22205Pregnancy & < 12 months postpartumStage 0 I II IIIa< 3010OSpaper2.401.28–4.508Stage, axillary LN involvement, adjuvant CT, tumour size
Anderson, 1996-DFS [33]USA22205Stage 0 I II IIIa< 3010DFSindirect3.191.20–8.498
Bonnier, 1997-OS [34]France154308Pregnancy & < 6 months postpartumGrade I II III33.9(23.2–46.4)5OSpaper1.460.72–2.966Clinical tumour size, microscopic lymph-node involvement, inflammatory cancer, age
Bonnier, 1997-DFS [34]France154308Grade I II III5DFSpaper1.481.00–2.196
Olson, 1998 [35]USA146NA< 4515OSpaper7Age, tumour size, lymph nodes, ER status, histology
Reeves, 2000 [36]UKStage I II III IV< 60> 10OSpaper9Age at diagnosis, year of diagnosis, hospital, weight in kg
Ibrahim, 2000 [37]Saudi Arabia72216PregnancyStage I II III IV, Grade I II III3410OSindirect0.940.62–1.446Age, stage, year of diagnosis
Daling, 2002 [38]USA83309< 24 Months postpartumStage I II III IV< 455OSindirect2.301.4–3.99Age, diagnosis year
Aziz, 2003 [39]Pakistan2448Pregnancy & < 12 months postpartumNA32(20–45)7OSindirect1.670.82–3.416Age, tumour grade, tumour size, axillary lymph node status
Siegelmann-Danieli, 2003-OS [40]Israel22192Pregnancy & < 12 months postpartumNA33(25–27)5OSindirect3.390.58–19.816
Siegelmann-Danieli, 2003-DFS [40]Israel20181NA33(25–28)5DFSindirect4.811.46–15.96
Bladstrom, 2003 [41]Sweden9414,599PregnancyNA≤455OSpaper2.402.0–2.99Age, time of diagnosis, time period interaction, number of children, age at first child’s birth
Bladstrom, 2003(2) [41]Sweden9414,599PregnancyNA≤4510OSpaper1.200.9–1.79
Whiteman, 2004 [42]USA59355< 12 Months postpartumNA20–4515OSpaper1.511.02–2.239Surgery, radiation therapy, race, oral contraceptive use, education, BMI, stage history of breast disease
Rodriguez, 2008 [43]USA7974177Pregnancy & < 12 months postpartumStage I II III IV< 5513OSpaper1.141.00–1.299Race, tumour size, AJCC stage, surgery, hormone receptor
Stensheim, 2009-Pregnancy [44]Norway5913,106PregnancyNA< 505CSSpaper1.230.82–1.817Age, diagnostic period, initial extent of disease
Stensheim, 2009-Postpartum [44]Norway4613,106< 6 Months postpartumNA< 505CSSpaper1.951.36–2.787
Beadle, 2009-OS [45]USA104564Pregnancy & < 12 months postpartumStage I II III≤3510OSindirect1.240.87–1.796
Beadle, 2009-DFS (distant metastasis) [45]USA104564Pregnancy & < 12 months postpartumStage I II III≤3510DFSindirect1.350.98–1.856
Beadle, 2009-DFS (locoregional recurrence) [45]USA104564Stage I II III≤3510DFSindirect1.440.78–2.666
Halaska, 2009-OS [46]Greece3232Pregnancy & < 12 months postpartumGrade I II III< 4510OSindirect1.420.58–3.486Age at diagnosis, tumour size, axillary lymph node status, presence or absence of metastatic deposits
Halaska, 2009-DFS [46]Greece3232Grade I II III< 4510DFSindirect1.820.82–4.056
Largillier, 2009-OS [47]France105788Pregnancy & < 12 months postpartumGrade I II III<3510OSpaper1.511.05–2.207
Largillier, 2009-DFS [47]France105788Grade I II III<3510DFSpaper1.250.90–1.747
Phillips, 2009 [48]Multicentre676NA10OSpaper8Study centre, education, BMI, time since last full-term pregnancy, age at diagnosis
Moreira, 2010 [49]Brazil87252Pregnancy & < 12 months postpartumNA≤ 4510OSpaper1.521.10–2.107Registration institution, age, registration year
Johansson, 2011 [50]Sweden111014,611Pregnancy & < 24 months postpartumNA15–4415OSpaper1.511.36–1.687Age, calendar time, education
Murphy, 2012 [51]USA99186Pregnancy & < 12 months postpartumGrade 0 I II III35(24–48)18OSpaper0.590.29–1.177Age, year of diagnosisTumour grade, ER status, LN involvement
Azim, 2012-OS [52]Italy65130PregnancyNA< 506OSpaper1.700.80–3.907Age, year of surgery, pathological tumour size, pathological nodal statuspN, neoadjuvant chemotherapy, ER
Azim, 2012-DFS [52]Italy65130PregnancyNA< 506DFSpaper2.301.30–4.207Age, pT, pN, neoadjuvant chemotherapy, Ki-67, HER2, perivascular invasion
Ali, 2012-OS [53]USA4040Pregnancy & < 12 months postpartumStage I II III IV33(24–42)16OSindirect2.151.13–4.097Age and stage-matched
Ali, 2012-DFS [53]USA4040Stage I II III IV33(24–42)16DFSindirect2.001.12–3.597
Amant, 2013-OS [54]Belgium311865PregnancyStage I II III, Grade I II III33(31–36)5OSpaper1.190.73–1.938Age at diagnosis, stage, grading, histologic tumour type, ER/PR status, HER2, chemotherapy
Amant, 2013-DFS [54]Belgium311865PregnancyStage I II III, Grade I II III33(31–36)5DFSpaper1.340.93–1.918
Litton, 2013-OS [55]USA75150PregnancyStage I II III24–455OSpaper1.871.04–3.367Age at diagnosis, stage at diagnosis, year of diagnosisAge at diagnosis, year of diagnosis, clinical cancer stage, tumour nuclear grade
Litton, 2013-DFS [55]USA75150PregnancyStage I II III24–455DFSpaper2.091.19–3.677
Valentini, 2013 [56]USA75269Pregnancy & < 12 months postpartumNA32.5(20–45)15OSpaper0.790.25–2.447Age at diagnosis, tumour size, lymph node status, ER status, use of chemotherapy, oophorectomy
Dimitrakakis, 2013 [57]Greece3939Pregnancy & < 12 months postpartumStage I II III IV, Grade I II III34.3 ± 5.05OSpaper9.282.94–29.276Stage, age, year of diagnosisStage, ER status, grade, age at diagnosis
Calliha, 2013-OS [58]USA7686Pregnancy & < 60 months postpartumStage 0 I II III IV, Grade I II III≤455OSpaper2.651.09–6.426Tumour biological subtype, clinical stage, year of diagnosis
Calliha, 2013-DFS [58]USA7484Pregnancy & < 60 months postpartumStage 0 I II III IV, Grade I II III≤455DFSpaper2.801.12–6.576Tumour biological subtype, clinical stage, year of diagnosis, local recurrence
Bell, 2013-OS [59]Australia13377Pregnancy & < 12 months postpartumNA< 485OSpaper2.500.5–11.76
Bell, 2013-DFS [59]Australia13377Pregnancy & < 12 months postpartumNA< 485DFSpaper0.900.2–4.46
Moller, 2013 [60]UKStage I II III IV10–5410OSpaper7Age, stage
Framarino-dei-Malatesta, 2014 [61]Italy2245PregnancyNA37.2 ± 3.210OSindirect0.960.29–3.216Age
Madaras, 2014 [62]Hungary3131Pregnancy & < 12 months postpartum3410OSindirect5.762.09–15.987Age, year of first breast cancer diagnosis
Nagatsuma, 2014 [63]JapanStage 0 I II III IV, Grade I II III26–4410OSpaper7Age at diagnosis, AJCC clinical stage, histological tumour grade, oestrogen and progesterone receptor status, HER2 status
Strasser-Weippl, 2014 [64]China1091274Pregnancy & < 60 months postpartumGrade I II III< 455DFSpaper1.621.04–2.548Age, oestrogen receptor, progesterone receptor, HER2 status, disease stage
Genin, 2015-OS [65]France87174Pregnancy & < 12 months postpartumGrade I II III35(27–40)10OSindirect1.090.79–1.527Age, year of diagnosis
Genin, 2015-DFS [65]France87174Pregnancy & < 12 months postpartumGrade I II III35(27–40)10DFSpaper1.871.05–3.337Age, year of diagnosisAge, ER, HR status, tumour stage, HER2 status, Ki-67 rate
Iqbal, 2017 [14]Canada5015832Pregnancy & < 21 months postpartumStage I II III IV20–455OSpaper1.110.86–1.459Year of diagnosis, age, tumour size, nodal status, oestrogen receptor status, progesterone receptor status, chemotherapy, radiotherapy, et al
Kim, 2017 [66]Korea344668Pregnancy & < 12 months postpartumStage 0 I II III IV, Grade I II III20–4510OSindirect1.851.28–2.678Operation period, age, initial stage
Bae, 2018(1) [67]Korea402770Pregnancy & < 12 months postpartumStage 0 I II III33.5 (27–40)5CSSpaper4.001.20–12.908Age, stage, chemotherapy
Bae, 2018(2) [68]Korea41183,381Pregnancy & < 12 months postpartumStage 0 I II III IV20–4915OSpaper1.030.74–1.429Age at diagnosis, stage, high versus low/intermediate, luminal subtype, HER2 subtype, et al
Boudy, 2018-DFS [16]France4951PregnancyGrade I II III< 465DFSindirect1.190.75–1.918Propensity score
Boudy, 2018-CSS [16]France4951PregnancyGrade I II III< 465CSSindirect1.060.65–1.728
Johansson, 2018 [2]Sweden7781661Pregnancy & < 24 months postpartumStage 0 I II III IV15–4410OSindirect0.900.55–1.409Age, period, education, region, tumour characteristics, pathologic T stage, N stage, ER/PR
Chuang, 2018 [69]China (Taiwan)Stage I II III20–50> 10OSpaper9Age and year of diagnosis, stage, tumour size, positive lymph nodes, histological grading, treatments
Ploquin, 2018-OS [15]France111253PregnancyStage 0 I II III IV22–465OSpaper1.100.67–1.798Age, clinical T stage, hormone receptorClinical nodal status, age
Ploquin, 2018-DFS [15]France111253PregnancyStage 0 I II III IV22–465DFSpaper1.150.78–1.688
Suleman, 2019-OS [70]Saudi Arabia110114PregnancyStage I II III IV20–48> 10OSindirect2.581.26–5.267Diagnosed year
Suleman, 2019-DFS [70]Saudi Arabia110114PregnancyStage I II III IV20–48> 10DFSindirect1.180.70–1.977
Choi, 2019 [17]Korea633804Pregnancy & < 12 months postpartumNA< 5010OSpaper1.520.82–2.838Histologic type, stage, ER, PR, age at diagnosis, Charlson comorbidity index

BMI Body mass index, ER Oestrogen receptor, PR Progesterone receptor, HER-2 Human epidermal growth factor receptor-2

Schematic representation of the study selection process Characteristics of the studies included in the meta-analysis BMI Body mass index, ER Oestrogen receptor, PR Progesterone receptor, HER-2 Human epidermal growth factor receptor-2

Overall survival (OS)

Forty-five studies comprising 6602 PABC patients and a total of 157,657 individuals were identified for the meta-analysis of OS. There was an overall increased risk of death for PABC patients compared to controls, with a pooled hazard ratio of 1.45 (95% CI 1.30–1.63). There was significant heterogeneity (I = 64.9, P<0.001). The subgroup analysis according to different follow-up durations (4 years, 5 years, 6 years, 7 years, 10 years and > 10 years) had similar results to the overall analysis (Fig. 2). However, the 6-year and 7-year OS, with few studies, showed nonsignificant results.
Fig. 2

Hazard ratios and 95% CIs of studies included in the meta-analysis of OS

Hazard ratios and 95% CIs of studies included in the meta-analysis of OS

Disease-free survival (DFS)

Twenty studies comprising 1786 PABC patients and a total of 9762 individuals were identified for the meta-analysis of DFS. The overall HR was 1.39 (95% CI, 1.25–1.54). There was no significant heterogeneity (I = 24.5, P = 0.146). The subgroup analysis according to different follow-up durations (5 years, 6 years, 10 years and > 10 years) had similar results as the overall analysis (Fig. 3). However, the 7-year DFS, with only 2 studies, showed nonsignificant results.
Fig. 3

Hazard ratios and 95% CIs of studies included in the meta-analysis of DFS

Hazard ratios and 95% CIs of studies included in the meta-analysis of DFS

Cause-specific survival (CSS)

Only 6 studies provided information on CSS with 296 PABC patients and a total of 29,598 individuals. The overall HR was 1.40 (95% CI, 1.17–1.68). There was no significant heterogeneity (I = 53.1, P = 0.074). The subgroup analysis (5-year CSS) had similar results as the overall analysis (Fig. 4).
Fig. 4

Hazard ratios and 95% CIs of studies included in the meta-analysis of CSS

Hazard ratios and 95% CIs of studies included in the meta-analysis of CSS

Subgroup analyses

Several factors that may have induced differences in outcomes were investigated with subgroup analyses, including diagnosis time, PABC definition, geographic region, year of publication and estimation procedure for HR. The results consistently showed worse prognoses in women with PABC than in those with non-PABC, except for the subgroup based on PABC definition and year of publication (Table 2). It is worth noticing that the specific definition has varied and this variability led to diverse results. Studies published during the years 2000–2010 and 2011–2019 had a clear trend of poor prognoses, which was less apparent in those published before 2000. The pooled HR of DFS based on studies published before 2000 was 1.27 (95% CI, 0.97–1.72).
Table 2

Subgroup analyses

SubgroupsNo. of Articles(No. of Studies)HR (95% CI)Heterogeneity Test
I2 (%)P-value
All studies included54 (76)
Diagnosed timeDuring pregnancyOS13 (14)1.46(1.12–1.90)73.6< 0.001
DFS7 (7)1.30(1.11–1.53)26.30.228
During postpartum periodOS13(13)1.97(1.67–2.33)49.00.023
DFS2(2)1.86(1.17–2.93)0.00.740
PABC definitionPregnancy & < 6 months postpartumOS2(2)1.37(1.09–1.72)0.00.852
Pregnancy & < 12 months postpartumOS20(20)1.44(1.20–1.72)60.7< 0.001
DFS8(9)1.52(1.27–1.81)17.40.288
Pregnancy & < 24 months postpartumOS3(3)1.42(1.01–2.01)67.40.047
Pregnancy & < 60 months postpartumOS3(3)1.48(0.90–2.44)65.20.057
Geographic regionEuropeOS15(17)1.53(1.26–1.86)71.1< 0.001
DFS9(9)1.32(1.15–1.52)8.70.363
North AmericaOS16(17)1.38 (1.17–1.63)53.20.005
DFS5(6)1.68(1.35–2.08)15.50.315
AsiaOS9(9)1.42(1.09–1.85)60.00.010
OthersOS2(2)1.55(1.13–2.13)0.00.544
Year of publicationBefore 2000OS11(13)1.46(1.18–1.82)45.40.038
DFS3(3)1.27(0.97–1.72)50.70.107
2000–2010OS11(12)1.48(1.19–1.85)79.0< 0.001
DFS4(5)1.40(1.14–1.71)20.50.284
2011–2019OS20(20)1.43(1.20–1.72)62.7< 0.001
DFS11(11)1.50(1.29–1.76)11.50.334
HR estimatePaper reportOS24(25)1.42(1.22–1.65)73.1< 0.001
DFS12(12)1.35(1.19–1.53)29.10.160
IndirectOS19(20)1.43(1.28–1.60)47.40.010
DFS7(8)1.48(1.22–1.79)24.70.232
Subgroup analyses

Dose-response association between the time from the last pregnancy to breast cancer diagnosis and HR of overall mortality

As the meta-analysis included studies reporting the HRs with their 95% CIs of overall mortality relating to three or more categories of time since the last pregnancy, all the studies were eligible to be included in the dose-response analysis. A total of ten studies were included in the dose-response meta-analysis, and nulliparous women were taken as the corresponding reference category (Table 3). The analysis of departure from linearity indeed indicated a nonlinear association between the time from the last delivery to breast cancer diagnosis and the hazard ratio of PABC overall mortality (P < 0.001). The nonlinear spline showed a decreasing trend. Compared to nulliparous women, the mortality was almost 60% higher in women with PABC diagnosed at 12 months after the last delivery (HR = 1.59, 95% CI 1.30–1.82), and the mortality was not significantly different at 70 months after the last delivery (HR = 1.14, 95% CI 0.99–1.25) (Fig. 5). These results showed a higher risk of death than that in nulliparous patients, suggesting that the definition of PABC should be extended to include patients diagnosed up to approximately 6 years postpartum (70 months since the last delivery) to capture the increased risk.
Table 3

Characteristics of the studies included in the dose-analysis meta-analysis

Study IDTime point of breast cancer diagnosisTime after last delivery(months)No. of participantsAdjusted HRa95% CI
Guinee, 1994 [30]Postpartum 1–12 m1–12401.880.88–3.98
Postpartum 13–48 m13–48511.090.54–2.19
Postpartum ≥49 m≥49350.540.19–1.55
Olson, 1998 [35]Postpartum < 24 m0–24423.11.8–5.4
Postpartum ≥24 m≥243521.30.9–2.0
Reeves, 2000 [36]Postpartum < 60 m0–60671.561.01–2.42
Postpartum 60–108 m60–108800.880.58–1.32
Postpartum > 120 m> 1205250.990.77–1.27
Daling, 2002 [38]Postpartum < 24 m0–24832.31.5–3.4
Postpartum 24–60 m24–701201.51.0–2.1
Postpartum > 60 m> 706611.20.9–1.6
Whiteman, 2004 [42]Postpartum ≤12 m0–12591.511.02–2.23
Postpartum 13–48 m13–482131.250.95–1.64
Postpartum > 48 m> 4814701.060.86–1.31
Phillips, 2009 [48]Postpartum < 24 m0–241332.751.98–3.83
Postpartum 24–60 m24–602312.21.65–2.94
Postpartum ≥72 m≥7220670.980.79–1.22
Calliha, 2013 [58]Postpartum < 60 m0–60862.651.09–6.42
Postpartum ≥60 m≥601721.520.71–3.28
Nagatsuma, 2014 [63]Postpartum ≤24 m0–24372.191.05–4.56
Postpartum 36–60 m36–60591.490.79–2.83
Postpartum > 60 m> 601810.810.46–1.43
Johansson, 2018 [2]Postpartum 0–6 m0–6411.160.64–2.14
Postpartum 6–12 m6–12841.30.83–2.03
Postpartum 12–24 m12–241941.010.70–1.46
Postpartum 24–60 m24–606291.220.96–1.55
Postpartum 60–120 m60–12011061.080.87–1.53
Postpartum > 120 m> 12016230.980.78–1.22
Chuang, 2018 [69]Postpartum 0–12 m0–123471.290.96–1.74
Postpartum 13–24 m13–244101.270.95–1.70
Postpartum 25–60 m25–6015831.060.88–1.27

aCorresponding reference category: nulliparous

Fig. 5

Dose-response relation between the time from the last delivery to breast cancer diagnosis and the HR of overall mortality

Characteristics of the studies included in the dose-analysis meta-analysis aCorresponding reference category: nulliparous Dose-response relation between the time from the last delivery to breast cancer diagnosis and the HR of overall mortality

Publication Bias

As shown in Fig. 6, each point represents an independent study of the indicated association, and a visual inspection of the funnel plot did not suggest evidence of publication bias among the articles (Egger’s test, P = 0.451; Begg’s test, P = 0.077).
Fig. 6

Funnel plot to explore the presence of publication bias

Funnel plot to explore the presence of publication bias

Discussion

We reviewed and meta-analyzed the existing scientific literature on the prognosis of PABC to draw a powerful conclusion that PABC is associated with a poor prognosis. Our results are consistent with those of the previous meta-analysis conducted in 2016 [13]. However, the negative effect on OS and DFS appears to be less pronounced in our study overall than in the previous meta-analysis. This is the largest and latest meta-analysis in this field. It included a larger number of participants, thus reducing the small-study effect to a great degree. The studies included in our meta-analysis were of relatively high quality. The mean Newcastle-Ottawa score of the studies was 7.2. There are two explanations that may account for the results. On the one hand, mammary gland involution following pregnancy has been suggested to explain the poor prognosis [71]. Breast degeneration is the process of tissue remodelling, until wound healing, inflammatory bowel disease and immune infiltration reach a state indistinguishable from the non-productive breast [72, 73], which supposedly promotes tumour progression. On the other hand, pregnancy and breastfeeding lead to less timely detection and clinical examination. The delayed diagnosis allows more time for tumour growth, increasing the metastatic potential of the disease [52, 74]. Pregnancy also makes the treatment strategy more conservative to ensure the safety of the foetus [10, 75]. However, the exact reasons for the poor prognosis of PABC need to be explored in the future. To the best of our knowledge, this is the first dose-response meta-analysis providing comprehensive insights into the association between the time from the last pregnancy to breast cancer diagnosis and the overall mortality of PABC. The scientific value of dose-response meta-analyses is higher than meta-analyses with exposure classified as two categories [20, 76]. Through the variance weighted least-squares regression with a random effects model, we found a nonlinear direct association between the time from the last pregnancy to breast cancer diagnosis and overall mortality. Compared with nulliparous women, the mortality was almost 60% higher in women with PABC diagnosed at 12 months after the last delivery, and the mortality had no significant difference at 70 months after the last delivery. We propose that the definition of PABC should include patients diagnosed up to at least 6 years postpartum to better delineate the increased risk imparted by a postpartum diagnosis. These findings also provide valuable insights into further research. Callihan’s cohort demonstrated that breast cancer patients diagnosed within 5 years postpartum have a significantly higher risk of metastasis and mortality than nulliparous patients [58]. Compared to that cohort, our dose-response meta-analysis provides a higher quality of evidence to expand the definition of PABC. Understanding the differences between breast cancers diagnosed during different times postpartum would better permit the translation of informative data from basic science and epidemiologic studies into the clinical care and treatment of breast cancer in young women. The present meta-analysis has the following limitations that must be taken into account. First, if HRs and 95% CIs were not directly reported in the included studies, we estimated HRs from the crude data or Kaplan-Meier curves. This may cause bias without adjustment. However, we performed subgroup analysis based on the estimation procedure for HR. This analysis consistently showed a worse prognosis for women with PABC than for those with non-PABC. Second, the meta-analysis was based on data from observational studies; although most of the included studies adjusted for several relevant confounders (including age, year of diagnosis, tumour stage, axillary lymph node status, oestrogen receptor, hormonal receptor status, HER2 status, family history, etc.), residual confounding by other potential factors cannot be ruled out. Third, high between-study heterogeneity is another limitation of the current meta-analysis. This was likely due to significant differences in the sample sizes, definitions of PABC and/or treatment interventions. Last, the language of the studies was limited to English, which may result in potential language bias.

Conclusions

In summary, this meta-analysis suggests that PABC is associated with a poor prognosis for OS, DFS and CSS compared to non-PABC cases. The definition of PABC should be extended to include patients diagnosed up to approximately 6 years postpartum to capture the increased risk of death. Further long-term prospective cohort studies with larger sample sizes should be conducted to validate this article’s findings.
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1.  Influence of pregnancy on the outcome of breast cancer: a case-control study. Societe Francaise de Senologie et de Pathologie Mammaire Study Group.

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Journal:  Int J Cancer       Date:  1997-09-04       Impact factor: 7.396

2.  Clinicopathological features and prognosis of pregnancy associated breast cancer - a matched case control study.

Authors:  Lilla Madaras; Kristóf Attila Kovács; Attila Marcell Szász; István Kenessey; Anna-Mária Tőkés; Borbála Székely; Zsuzsanna Baranyák; Orsolya Kiss; Magdolna Dank; Janina Kulka
Journal:  Pathol Oncol Res       Date:  2013-12-20       Impact factor: 3.201

3.  Cancer of the breast in Philadelphia hospitals 1951-1964.

Authors:  J S Mausner; M B Shimkin; N H Moss; G P Rosemond
Journal:  Cancer       Date:  1969-02       Impact factor: 6.860

4.  Alternatively activated macrophages and collagen remodeling characterize the postpartum involuting mammary gland across species.

Authors:  Jenean O'Brien; Traci Lyons; Jenifer Monks; M Scott Lucia; R Storey Wilson; Lisa Hines; Yan-gao Man; Virginia Borges; Pepper Schedin
Journal:  Am J Pathol       Date:  2010-01-28       Impact factor: 4.307

5.  Aligned collagen is a prognostic signature for survival in human breast carcinoma.

Authors:  Matthew W Conklin; Jens C Eickhoff; Kristin M Riching; Carolyn A Pehlke; Kevin W Eliceiri; Paolo P Provenzano; Andreas Friedl; Patricia J Keely
Journal:  Am J Pathol       Date:  2011-03       Impact factor: 4.307

6.  Prognosis for patients diagnosed with pregnancy-associated breast cancer: a paired case-control study.

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Journal:  Sao Paulo Med J       Date:  2010-05       Impact factor: 1.044

7.  Survival outcomes in pregnancy associated breast cancer: a retrospective case control study.

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8.  The prognosis of women diagnosed with breast cancer before, during and after pregnancy: a meta-analysis.

Authors:  Emily K Hartman; Guy D Eslick
Journal:  Breast Cancer Res Treat       Date:  2016-09-28       Impact factor: 4.872

9.  Effect of pregnancy on prognosis for young women with breast cancer.

Authors:  V F Guinee; H Olsson; T Möller; K R Hess; S H Taylor; T Fahey; J V Gladikov; J W van den Blink; F Bonichon; S Dische
Journal:  Lancet       Date:  1994-06-25       Impact factor: 79.321

10.  Clinicopathologic characteristics and prognosis of breast cancer patients associated with pregnancy and lactation: analysis of case-control study in Japan.

Authors:  T Ishida; T Yokoe; F Kasumi; G Sakamoto; M Makita; T Tominaga; K Simozuma; K Enomoto; K Fujiwara; T Nanasawa
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2.  The definition of pregnancy-associated breast cancer is outdated and should no longer be used.

Authors:  Frédéric Amant; Hanne Lefrère; Virginia F Borges; Elyce Cardonick; Matteo Lambertini; Sibylle Loibl; Fedro Peccatori; Ann Partridge; Pepper Schedin
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6.  The Risk Factors, Incidence and Prognosis of Postpartum Breast Cancer: A Nationwide Study by the SMARTSHIP Group.

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7.  Genomic copy number alterations as biomarkers for triple negative pregnancy-associated breast cancer.

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