Open Access

Breastfeeding in relation to risk of different breast cancer characteristics

  • Salma Butt1, 2Email author,
  • Signe Borgquist2, 4,
  • Lola Anagnostaki3,
  • Göran Landberg3 and
  • Jonas Manjer1, 2
BMC Research Notes20147:216

https://doi.org/10.1186/1756-0500-7-216

Received: 27 November 2012

Accepted: 21 March 2014

Published: 7 April 2014

Abstract

Background

The aim of this present study was to examine duration of breastfeeding in relation to the risk of different subgroups of breast cancer. A prospective cohort, The Malmö Diet and Cancer study, including 14092 parous women, were followed during a mean of 10.2 years and a total of 424 incident breast cancers were diagnosed.

Methods

Tumours were classified regarding invasiveness, tumour size, axillary lymph node status, Nottingham grade, tumour proliferation (Ki67), HER2, cyclin D1 and p27, WHO histological type and hormone receptor status. Duration of breastfeeding was measured using total time of breastfeeding, categorized in quartiles using the lowest as the reference group (<4.0, ≥4.0- < 8.0, ≥8.0- < 13.0 and ≥13.0 months). Average duration of breastfeeding per child and breastfeeding duration of the first child were also used as exposures in separate analyses. Relative risks, with 95% confidence intervals, were obtained using a Cox’s proportional hazards analysis adjusted for potential confounders.

Results

Overall risk for breast cancer was similar in all quartiles of breastfeeding. No strong results regarding breastfeeding duration and breast cancer subgroups were seen. A few results indicated an association between a relatively long duration of breastfeeding and tumours with high proliferation (Ki67) and grade III histological grade.

Conclusions

Breastfeeding duration was not associated with breast cancer risk and no strong results were seen with regard to breast cancer subgroups.

Keywords

Breast cancer risk Breastfeeding Stage Characteristics

Background

Several early studies and a recently a large meta-analysis including data from thirty countries, have shown a negative association between increasing time of breastfeeding and the risk of breast cancer[1]. However, a number of studies have not been able to shown this association as reviewed by Yang et al.[2]. One reason for these inconclusive findings may be that breastfeeding only influences the risk of certain sub-groups of breast cancer. There has been a limited number of studies investigating breastfeeding in relation to different breast cancer sub-groups, and only characteristics such as histological type and estrogen receptor status have been investigated[35].

In all, 17 035 women participated in a prospective population-based cohort in Malmö, Sweden: The Malmö Diet and Cancer Study (MDCS). The MDCS collected information on breastfeeding, as well as other reproductive and environmental factors. During follow-up, 622 women were diagnosed with breast cancer. Tumour tissue samples were available for about 90% of these women, which allowed tumour reclassification and further tumour biological examinations. Tumours were evaluated with regard to invasiveness, size, axillary lymph node status, Nottingham grade, tumour proliferation (Ki67), Human epidermal growth factor receptor 2 (HER2) status, and expression of cell cycle regulators such as cyclin D1 and p27. Tumours were further examined for WHO histological type (ductal, lobular, and tubular) and hormone receptor status; estrogen receptor alpha (ERα), estrogen receptor beta (ERβ) and progesterone receptor (PgR).

The aim of the present study was to examine breastfeeding in relation to the risk of breast tumours with different biological characteristics.

Methods

The Malmö Diet and Cancer Study (The MDCS)

All women born between 1923 and 1950 in Malmö were invited to a prospective cohort study, the MDCS. Between the years 1991 and 1996, 17 035 women participated[6]. Written informed consent was obtained from all participants.

Information on breastfeeding, education, occupation, marital status, age at menarche, parity, year of each child’s birth, age at menopause, exposure to oral contraceptives (OC) (ever/never), current use of hormonal replacement therapy (HRT), alcohol consumption and smoking habits were collected using a questionnaire at baseline[7].

Menopausal status was assessed using both medical records and the questionnaire. A women was considered postmenopausal: (1) if she had undergone bilateral oophorectomy; or (2) if she had undergone hysterectomy but not bilateral oophorectomy, and if she was ≥55 years of age; or (3) if the above criteria were absent and she affirmed that her menstruations had ceased at least during the calendar year two years prior to baseline examination; or (4) if it was unknown whether or not she had undergone a previous oophorectomy or hysterectomy and information on menstrual status was missing, and she was ≥55 years of age. In all 11388 women were postmenopausal at baseline. A woman was classified as pre-/perimenopausal if she affirmed that she was still menstruating, or if her menstruations had ceased less than two years prior to baseline examinations, or if information on menstrual status was missing and the women was <55 years of age at baseline.

Height and weight was measured at baseline by a trained nurse at the study centre, and Body Mass Index (BMI) was calculated as kg/m2.

The MDCS and the present analyses were approved by the Ethical Committee at Lund University (LU 51–90 and Dnr 652/2005).

Breastfeeding and parity

Time of breastfeeding was assessed with the help of a questionnaire. All participants were asked to fill in the number of children they had given birth to. Information on birth years of the children and duration of breastfeeding was retrieved for the first seven children. No information on twin pregnancies was available. Parity was defined as the total number of children that a women answered she had given birth to.

Mean duration of breastfeeding per child was calculated as the sum of the months of breastfeeding divided by the number of children with information on breastfeeding.

Total time of breastfeeding was calculated as mean time of breastfeeding multiplied with parity. This calculation was made since time of breastfeeding was limited to seven children and a small amount of women had eight or more children (n = 13). Breastfeeding of the first child was investigated in an additional analysis, as it is likely that changes during the first pregnancy and following lactation period may be particularly important with regard to the differentiation of the breast tissue[8]. Women that had never breastfed were included in the lowest quartile in all breastfeeding groups.

Follow-up

All women were followed until 31 December 2004 with tumour end-points retrieved by record linkage with The Swedish Cancer Registry (until 31 December 2003). Due to a delay in central registration, linkage to its regional branch, The Southern Swedish Regional Tumour Registry, provided tumour-endpoints for the year 2004. Vital status was obtained from The Swedish Cause-of-Death Registry until 31 December 2004. A total of 622 incident breast cancer cases (including invasive and cancer in situ) were registered during follow-up.

Study population

Out of 17 035 women, 576 had been diagnosed with breast cancer prior to inclusion in the study, and they were categorized as prevalent breast cancer cases and were subsequently excluded from the analyses. A total of 2089 women were nulliparous and hence excluded from the study population. Yet another 278 had no information on parity and were also excluded. This gave us a study population of 14 092 women with 522 incident breast cancer cases. A total of 57, were cancer in situ (CIS) and only provided person-years until event, but did not provide invasive end-points in the analyses for “all breast cancers”. CIS cases were neither included in the analyses of specific subgroups, e.g. histology and receptor status. Ten women with bilateral breast cancer were excluded as tumour end-points in the analyses due to difficulties in determining the relevant side to be used in the analyses of tumour size, axillary lymph nodes, histopathology and receptor status. A further 31 did not have sufficient tissue for further analyses. Bilateral cases and cases with no tumour material did however provide person-years up until the event. In all 424 tumours were included in the subgroup analyses (Figure 1).
Figure 1

Study population (MDCS).

Histopathological analyses

One senior breast pathologist re-evaluated all invasive tumours (LA). All tumours were re-evaluated concerning invasiveness and tumour type was described according to the WHO classification. The tumours were graded according to Elston and Ellis, including tubular formation, nuclear atypia and mitotic index[9]. Further tumour characteristics were evaluated using the tissue microarray technique (TMA). For the construction of tissue micro array, described elsewhere[10, 11] two cores of 0.6 mm from each tumour were taken and arranged in a recipient block. Immunohistochemical (IHC) analyses were performed using specific antibodies, described previously by Borgquist et al.[10] and tumours were evaluated according to the nucleus expression of ERα, ERβ, PgR, Ki67, cyclin D1 and p27. Tumours were dichotomized as negative and positive using the categories 0–10% and 11-100% of positive nuclei respectively. HER2 was analyzed using IHC as previously described[10]. HER2 was classified according to the Swedish clinical practice[12]. As data on HER2 amplification was not available, HER2 status was based on IHC analyses and in this study dichotomized into negative (0 and 1+) or positive cases (2+ and 3+). All arrays were evaluated independently twice by the same person (SiB) and in case of discrepancy, a third evaluation was performed by the same investigator.

Information on tumour laterality, size and lymph node metastasis were retrieved from medical records and histopathological reports by one registered nurse.

Statistical methods

The main analyses used total duration of breastfeeding as measurements. Additional analyses used mean duration of breastfeeding and breastfeeding duration of the first child. Breastfeeding duration was divided into quartiles. Quartile cut-offs for breastfeeding were based on the distribution of all women in the study cohort. Different quartiles of breastfeeding were compared regarding the distribution of established and potential risk factors for breast cancer. Each subject was followed until the event of breast cancer, death or end of follow- up, 31 December 2004. The incidence of breast cancer was calculated per 100,000 person-years in different breastfeeding quartiles. Corresponding relative risks of breast cancer were analyzed using a Cox’s proportional hazards analysis yielding relative risks (RR) with 95% confidence intervals (CI). These analyses were subsequently adjusted for potential confounders; age at baseline, education, socioeconomic status, marital status, age at menarche, age at first birth, parity, oophorectomy, age at menopause, oral contraceptive use, hormone replacement therapy use, bmi, alcohol consumption, smoking and height (categorized in Table 1).
Table 1

Distribution of risk factors in different quartiles of total duration of breastfeeding

Time in months:

<4.0

≥4.0 - <8.0

≥8.0 - <13.0

≥13.0

Missing

Total: 14092

n = 2908

n = 3688

n = 3484

n = 3451

n = 561

 

Column percent(mean and SD in italics)

Age at baseline (years)

     

    Mean (SD)

55.9 (7.7)

56.7 (7.8)

57.6 (7.7)

58.5 (8.1)

57.7 (6.7)

Education (n)

     

    O-level college

74.0

72.7

69.0

65.6

80.6

    A-level college

7.7

6.7

7.4

6.2

5.0

    University

18.3

20.4

23.2

28.0

13.0

Type of occupation

     

    Manual worker

40.7

39.3

37.9

40.5

45.6

    Non-manual worker

51.0

52.9

53.6

49.7

47.1

    Employer-self-employed

7.3

7.1

7.5

8.3

5.5

Married/cohabiting

     

    No

32.5

30.2

27.5

28.8

35.5

    Yes

67.5

69.8

72.5

71.2

64.2

Age at menarche

     

    ≤12

23.6

21.3

21.6

22.2

22.5

    >12 to <15

53.2

54.8

52.9

51.8

47.1

    ≥15

22.7

23.2

25.1

25.5

27.1

Parity

     

    1

54.9

30.5

14.1

1.2

40.1

    2

35.1

55.7

59.5

41.6

36.5

    ≥3

10.0

13.9

26.4

57.2

23.4

Age at first childbirth

     

    ≤20

17.0

19.7

18.8

22.3

19.4

    >20 to ≤25

38.1

41.6

42.1

43.1

34.9

    >25 to ≤30

29.7

28.2

29.4

26.5

28.3

    >30

15.1

10.4

9.7

8.1

15.9

Bilateral oophorectomy

     

    No

98.7

98.4

98.6

98.7

98.8

    Yes

1.3

1.6

1.4

1.3

1.2

Age at menopause

     

    Pre-/perimenopausal

39.3

36.5

31.4

30.0

26.0

    ≤45

14.5

12.2

11.6

11.3

15.0

    >45 to <53

34.7

36.4

40.0

39.9

43.1

    ≥53

10.2

13.1

15.6

17.4

12.5

Exposure to OC (ever/never)

     

    No

47.3

45.7

49.3

53.5

52.8

    Yes

52.6

54.2

50.7

46.5

46.7

Exposure to HRT*

     

    No

79.2

79.7

79.9

82.8

81.7

    ERT

8.0

7.5

8.4

7.8

6.0

    PRT

0.5

0.3

0.2

0.3

0.0

    CHRT

12.0

12.0

11.1

8.8

12.1

Height

     

    Mean (SD)

163.5 (6.0)

163.8 (6.0)

163.6 (5.9)

163.4 (6.1)

162.8 (6.2)

Body mass index

     

    Mean (SD)

25.5 (4.4)

25.3 (4.5)

25.3 (4.2)

25.7 (4.4)

26.0 (4.8)

Alcohol consumption

     

    Nothing last year (teetotaler)

10.9

9.2

10.3

13.8

17.5

    Something last year (not last month)

12.1

11.4

12.0

12.2

13.7

    Something last month

76.8

79.3

77.6

73.8

67.6

Smoking

     

    Never

38.2

40.6

45.4

49.9

44.4

    Current

33.2

30.6

26.5

23.0

33.9

    Ex

28.5

28.8

28.1

27.1

21.7

Percentages do not always add up to 100% due to missing. *Current in peri- and postmenopausal women n = 10288.

Trend over breastfeeding categories was examined from the lowest to the highest quartile, excluding the missing category.

To examine heterogeneity, to test whether effect estimates were similar between for example grade I and grade III tumours in a certain breastfeeding quartile, adjusted case-case models using unconditional logistic regression analysis were used and p-values <0.05 were considered statistically significant.

Results

Total duration of breastfeeding in relation to risk factors for breast cancer

Women in the highest quartile of breastfeeding duration were more often multiparous and younger at first childbirth, as compared to all other groups. Moreover, women in the highest quartile were older at menopause, were less exposed to oral contraceptives and had to a higher extent never smoked (Table 1). All other factors were evenly distributed between breastfeeding categories.

Total duration of breastfeeding in relation to risk of different breast cancer subgroups

The overall risk of breast cancer (i.e. the risk of unilateral invasive tumours with biological material) was similar in all breastfeeding groups as compared to the lower quartile (Table 2). There was a trend towards grade III tumours in women with higher duration of breastfeeding, however this association did not reach statistical significance (Table 2). The risk of high Ki67 expressing tumours was statistically significantly associated with increased duration of breastfeeding (Table 3). Women in the lowest breastfeeding quartile had a higher risk of expressing ductal type of breast tumour, however this results was not statistically significant (Table 4).
Table 2

Risk of breast cancer subgroups defined by clinico-pathological markers in relation to total duration of breastfeeding

Tumour subgroup

Breastfeeding total in months

Number of cases

Incidence/100000

RR

RR*

Invasive

     

breast cancer**

<4.0

80

270

1.00

1.00

 

≥4.0 - <8.0

108

288

1.07 (0.80 - 1.42)

1.04 (0.77 - 1.40)

 

≥8.0 - <13.0

109

304

1.12 (0.84 - 1.49)

1.09 (0.80 - 1.48)

 

≥13.0

103

293

1.08 (0.81 - 1.45)

1.10 (0.78 - 1.54)

 

Missing

24

399

---

---

 

Total

424

294

p-trend: 0.56

p-trend:0.45

CIS

     
 

<4.0

9

30

1.00

1.00

 

≥4.0 - <8.0

19

51

1.67 (0.76 - 3.70)

1.90 (0.84 - 4.30)

 

≥8.0 - <13.0

13

36

1.20 (0.51 - 2.81)

1.40 (0.57 - 3.46)

 

≥13.0

13

37

1.22 (0.52 - 2.86)

1.59 (0.60 - 4.21)

 

Missing

3

50

---

---

 

Total

57

40

p-trend:0.98

p-trend:0.48

Size ≤20 mm#

     
 

<4.0

55

186

1. 00

1.00

 

≥4.0 - <8.0

80

214

1.15 (0.82 - 1.62)

1.12 (0.79 - 1.60)

 

≥8.0 - <13.0

69

192

1.03 (0.72 - 1.47)

0.99 (0.68 - 1.45)

 

≥13.0

85

241

1.30 (0.93 - 1.82)

1.29 (0.87 - 1.92)

 

Missing

15

249

---

---

 

Total

304

211

p-trend:0.21

p-trend:0.24

Size >20 mm

     
 

<4.0

25

84

1.00

1.00

 

≥4.0 - <8.0

27

72

0.85 (0.50 - 1.47)

0.84 (0.48 - 1.47)

 

≥8.0 - <13.0

39

109

1.28 (0.78 - 2.12)

1.28 (0.75 - 2.20)

 

≥13.0

18

51

0.61 (0.33 - 1.11)

0.65 (0.33 - 1.27)

 

Missing

9

150

---

---

 

Total

118

82

p-trend:0.36

p-trend:0.63

Axillary lymph

     

node neg#

<4.0

27

91

1.00

1.00

 

≥4.0 - <8.0

32

85

0.94 (0.56 - 1.56)

0.91 (0.54 - 1.54)

 

≥8.0 - <13.0

34

95

1.04 (0.63 - 1.72)

0.99 (0.56 - 1.70)

 

≥13.0

31

88

0.97 (0.58 - 1.62)

0.90 (0.50 - 1.64)

 

Missing

5

83

---

---

 

Total

129

89

p-trend:0.99

p-trend:0.82

Axillary lymph

     

node pos

<4.0

53

179

1.00

1.00

 

≥4.0 - <8.0

72

192

1.07 (0.75 - 1.53)

1.05 (0.73 - 1.51)

 

≥8.0 - <13.0

71

198

1.10 (0.77 - 1.57)

1.08 (0.73 - 1.57)

 

≥13.0

71

202

1.13 (0.79 - 1.61)

1.18 (0.78 - 1.79)

 

Missing

19

316

---

---

 

Total

286

198

p-trend: 0.52

p-trend:0.30

Grade I#

     
 

<4.0

27

91

1.00

1.00

 

≥4.0 - <8.0

37

99

1.08 (0.66 - 1.78)

1.01 (0.61 - 1.69)

 

≥8.0 - <13.0

28

78

0.85 (0.50 - 1.45)

0.78 (0.44 - 1.38)

 

≥13.0

28

80

0.87 (0.51 - 1.48)

0.87 (0.47 - 1.61)

 

Missing

7

116

---

---

 

Total

127

88

p-trend:0.42

p-trend:0.71

Grade II

     
 

<4.0

33

111

1.00

1.00

 

≥4.0 - <8.0

47

125

1.12 (0.72 - 1.75)

1.05 (0.67 - 1.66)

 

≥8.0 - <13.0

53

148

1.32 (0.85 - 2.03)

1.15 (0.73 - 1.83)

 

≥13.0

46

131

1.17 (0.75 - 1.83)

0.99 (0.60 - 1.64)

 

Missing

12

199

---

---

 

Total

191

132

p-trend:0.40

p-trend:0.97

Grade III##

     
 

<4.0

20

67

1.00

1.00

 

≥4.0 - <8.0

23

61

0.91 (0.45 - 1.66)

1.00 (0.54 - 1.85)

 

≥8.0 - <13.0

28

78

1.15 (0.65 - 2.05)

1.43 (0.77 - 2.66)

 

≥13.0

29

82

1.22 (0.69 - 2.16)

1.74 (0.89 - 3.41)

 

Missing

5

83

---

---

 

Total

105

73

p-trend:0.34

p-trend:0.051

*Adjusted for age at baseline (continuous), education, socioeconomic status, marital status, age at menarche, age at first birth, parity, oophorectomy, age at menopause, oral contraceptive use, hormone replacement therapy use, bmi, alcohol consumption, smoking and height.

**All cases with unilateral invasive breast cancer with tissue samples available for examination.

#Reference group in heterogeneity analyses. ##Heterogeneity: p = 0.031.

Table 3

Risk of breast cancer subgroups defined by immunohistochemical markers in relation to total duration of breastfeeding

Tumour subgroup

Breastfeeding total in months

Number of cases

Incidence/100000

RR

RR*

Ki67 low

     

(≤10%)#

<4.0

54

182

1.00

1.00

 

≥4.0 - <8.0

76

203

1.11 (0.78 - 1.57)

1.06 (0.74 - 1.51)

 

≥8.0 - <13.0

72

201

1.09 (0.77 - 1.56)

1.01 (0.69 - 1.47)

 

≥13.0

58

165

0.90 (0.62 - 1.31)

0.82 (0.53 - 1.25)

 

Missing

11

183

---

---

 

Total

271

188

p-trend:0.54

p-trend:0.44

Ki67 high

     

(>10%)

<4.0

17

57

1.00

1.00

 

≥4.0 - <8.0

21

56

0.98 (0.51 - 1.85)

1.02 (0.53 - 1.96)

 

≥8.0 - <13.0

26

72

1.25 (0.68 - 2.31)

1.39 (0.72 - 2.67)

 

≥13.0

30

85

1.48 (0.82 - 2.69)

1.88 (0.94 - 3.76)

 

Missing

7

116

---

---

 

Total

101

70

p-trend:0.11

p-trend:0.03

HER2 (0-1+)#

     
 

<4.0

57

192

1.00

1.00

 

≥4.0 - <8.0

78

208

1.08 (0.77 - 1.52)

1.02 (0.72 - 1.45)

 

≥8.0 - <13.0

84

234

1.21 (0.86 - 1.69)

1.12 (0.78 - 1.61)

 

≥13.0

73

207

1.07 (0.76 - 1.52)

1.07 (0.72 - 1.59)

 

Missing

19

499

---

---

 

Total

311

216

p-trend:0.58

p-trend:0.44

HER2 (2 + -3+)

     
 

<4.0

9

30

1.00

1.00

 

≥4.0 - <8.0

9

24

0.80 (0.32 - 2.01)

1.02 (0.39 - 2.65)

 

≥8.0 - <13.0

11

31

1.02 (0.42 - 2.46)

1.40 (0.53 - 3.69)

 

≥13.0

11

31

1.03 (0.43 - 2.49)

1.35 (0.46 - 3.97)

 

Missing

1

17

---

---

 

Total

41

28

p-trend:0.79

p-trend:0.59

Cyclin D1 low

     

(≤10%) #

<4.0

54

182

1.00

1.00

 

≥4.0 - <8.0

82

219

1.20 (0.85 - 1.69)

1.15 (0.81 - 1.64)

 

≥8.0 - <13.0

73

203

1.11 (0.78 - 1.58)

1.05 (0.72 - 1.53)

 

≥13.0

73

122

1.14 (0.80 - 1.62)

1.06 (0.71 - 1.60)

 

Missing

13

216

---

---

 

Total

295

205

p-trend:0.65

p-trend:0.77

Cyclin D1 high

     

(>10%)

<4.0

14

47

1.00

1.00

 

≥4.0 - <8.0

14

37

0.79 (0.37 - 1.65)

0.84 (0.39 - 1.78)

 

≥8.0 - <13.0

24

67

1.38 (0.72 - 2.68)

1.56 (0.77 - 3.19)

 

≥13.0

20

57

1.19 (0.60 - 2.36)

1.61 (0.73 - 3.56)

 

Missing

6

100

---

---

 

Total

78

54

p-trend:0.29

p-trend:0.10

P27 low

     

(≤10%) #

<4.0

21

71

1.00

1.00

 

≥4.0 - <8.0

41

109

1.55 (0.91 - 2.62)

1.56 (0.91 - 2.67)

 

≥8.0 - <13.0

31

86

1.22 (0.70 - 2.12)

1.21 (0.68 - 2.18)

 

≥13.0

35

99

1.40 (0.82 - 2.41)

1.35 (0.73 - 2.50)

 

Missing

7

116

---

---

 

Total

135

94

p-trend:0.47

p-trend:0.61

P27 high

     

(>10%)

<4.0

48

162

1.00

1.00

 

≥4.0 - <8.0

53

141

0.87 (0.59 - 1.29)

0.83 (0.55 - 1.24)

 

≥8.0 - <13.0

65

181

1.11 (0.76 - 1.61)

1.04 (0.70 - 1.56)

 

≥13.0

53

151

0.93 (0.63 - 1.37)

0.93 (0.59 - 1.46)

 

Missing

11

183

---

---

 

Total

230

159

p-trend:0.95

p-trend:0.73

*Adjusted for age at baseline (continuous), education, socioeconomic status, marital status, age at menarche, age at first birth, parity, oophorectomy, age at menopause, oral contraceptive use, hormone replacement therapy use, bmi, alcohol consumption, smoking and height.

#Reference group in heterogeneity analyses.

Table 4

Risk of breast cancer subgroups defined by type and receptor status in relation to total duration of breastfeeding

Tumour subgroup

Breastfeeding total in months

Number of cases

Incidence/100000

RR

RR*

Ductal#

     
 

<4.0

59

199

1.00

1.00

 

≥4.0 - <8.0

74

197

0.99 (0.70 - 1.39)

0.99 (0.70 - 1.41)

 

≥8.0 - <13.0

74

206

1.03 (0.73 - 1.45)

1.04 (0.72 - 1.51)

 

≥13.0

79

224

1.12 (0.80 - 1.58)

1.20 (0.81 - 1.78)

 

Missing

12

199

---

---

 

Total

298

207

p-trend:0.45

p-trend:0.26

Lobular

     
 

<4.0

15

51

1.00

1.00

 

≥4.0 - <8.0

21

56

1.11 (0.57 - 2.15)

0.95 (0.48 - 1.88)

 

≥8.0 - <13.0

23

64

1.27 (0.66 - 2.43)

1.02 (0.51 - 2.04)

 

≥13.0

14

40

0.79 (0.38 - 1.63)

0.65 (0.29 - 1.45)

 

Missing

9

150

---

---

 

Total

82

57

p-trend:0.63

p-trend:0.44

Tubular

     
 

<4.0

4

13

1.00

1.00

 

≥4.0 - <8.0

10

27

1.97 (0.62 - 6.29)

2.09 (0.64 - 6.89)

 

≥8.0 - <13.0

7

20

1.43 (0.42 - 4.89)

1.59 (0.43 - 5.91)

 

≥13.0

6

17

1.26 (0.36 - 4.47)

1.56 (0.37 - 6.70)

 

Missing

2

33

---

---

 

Total

29

20

p-trend:.1.00

p-trend:0.75

ERα neg ≤10%#

     
 

<4.0

9

30

1.00

1.00

 

≥4.0 - <8.0

12

32

1.05 (0.44 - 2.50)

1.16 (0.48 - 2.83)

 

≥8.0 - <13.0

13

36

1.18 (0.50 - 2.75)

1.38 (0.55 - 3.47)

 

≥13.0

15

43

1.40 (0.61 - 3.19)

1.61 (0.60 - 4.35)

 

Missing

1

17

---

---

 

Total

50

35

p-trend:0.38

p-trend:0.30

ERα pos >10%

     
 

<4.0

61

206

1.00

1.00

 

≥4.0 - <8.0

85

227

1.10 (0.79 - 1.53)

1.06 (0.75 - 1.48)

 

≥8.0 - <13.0

88

245

1.19 (0.86 - 1.64)

1.13 (0.79 - 1.60)

 

≥13.0

80

227

1.10 (0.79 - 1.54)

1.09 (0.75 - 1.61)

 

Missing

20

332

---

---

 

Total

334

232

p-trend:0.52

p-trend:0.47

ERβ neg ≤10%#

     
 

<4.0

29

98

1.00

1.00

 

≥4.0 - <8.0

38

101

1.04 (0.64 - 1.68)

1.04 (0.63 - 1.70)

 

≥8.0 - <13.0

44

123

1.26 (0.79 - 2.01)

1.26 (0.76 - 2.09)

 

≥13.0

40

114

1.16 (0.72 - 1.87)

1.20 (0.69 - 2.09)

 

Missing

9

150

---

---

 

Total

160

111

p-trend:0.40

p-trend:0.32

ERβ pos >10%

     
 

<4.0

33

111

1.00

1.00

 

≥4.0 - <8.0

41

109

0.98 (0.62 - 1.54)

0.95 (0.59 - 1.53)

 

≥8.0 - <13.0

40

111

0.98 (0.62 - 1.55)

0.93 (0.57 - 1.53)

 

≥13.0

33

94

0.84 (0.52 - 1.35)

0.80 (0.46 - 1.40)

 

Missing

9

150

---

---

 

Total

156

108

p-trend:0.48

p-trend:0.62

PgR neg ≤10%#

     
 

<4.0

42

142

1.00

1.00

 

≥4.0 - <8.0

49

131

0.92 (0.61 - 1.39)

0.91 (0.59 - 1.38)

 

≥8.0 - <13.0

50

139

0.98 (0.65 - 1.48)

0.96 (0.62 - 1.49)

 

≥13.0

49

139

0.98 (0.65 - 1.48)

1.01 (0.63 - 1.63)

 

Missing

9

150

---

---

 

Total

199

138

p-trend:0.98

p-trend:0.90

PgR pos >10%

     
 

<4.0

28

94

1.00

1.00

 

≥4.0 - <8.0

40

107

1.12 (0.69 - 1.82)

1.13 (0.69 - 1.86)

 

≥8.0 - <13.0

43

120

1.25 (0.78 - 2.02)

1.30 (0.78 - 2.16)

 

≥13.0

38

108

1.14 (0.70 - 1.85)

1.24 (0.70 - 2.17)

 

Missing

10

166

---

---

 

Total

159

110

p-trend:0.55

p-trend:0.29

*Adjusted for age at baseline (continuous), education, socioeconomic status, marital status, age at menarche, age at first birth, parity, oophorectomy, age at menopause, oral contraceptive use, hormone replacement therapy use, bmi, alcohol consumption, smoking and height.

#Reference group in heterogeneity analyses.

Average duration of breastfeeding

Women in the lowest quartile of average duration of breastfeeding were younger at baseline and were more often pre-/perimenopausal at breast cancer diagnosis as compared to all other groups (Additional file1: Table S1). The relative risks for average duration of breastfeeding were similar to relative risks of total duration of breastfeeding. The risk of having grade III tumours were statistically significant for women in the highest quartile and the trend for having grade III tumours with increasing time of breastfeeding duration reached statistical significance (Additional file1: Table S2). Moreover, no higher risk for tubular type was seen in any breastfeeding category (Additional file1: Table S4).

Breastfeeding duration of first child

The analyses of breastfeeding of first child in relation to risk factors for breast cancer showed that women in the highest quartile were more likely to have had at later first childbirth as compared to the other breastfeeding groups. All other risk factors were distributed as for total duration of breastfeeding (Additional file1: Table S5). All relative risks for breastfeeding of the first childbirth in relation to risk of different breast cancer subgroups were similar to those related to total duration of breastfeeding and average duration of breastfeeding (Additional file1: Table S6-S8). There was a statistically significant increased risk of having high expression of cyclin D1 with increasing duration of breastfeeding (Additional file1: Table S7).

Discussion

The aim of this study was to investigate breastfeeding in relation to the risk of different breast cancer subtypes and could not find any strong results. There was a trend towards more grade III tumours and high Ki67 expression with increasing duration of breastfeeding. However a lot of markers were tested and the quartile risks were not statistically significant for grade and Ki67 when studying total duration of breastfeeding.

Methodological considerations

Information on breastfeeding was retrieved from a questionnaire provided at baseline examinations where all women were 44 years or older, thus unlikely to have additional children following baseline. A previous study has confirmed self-reported breastfeeding to be highly accurate[13], hence we consider this information to be valid. A limitation of this study is that the questionnaire did not allow for a distinction between different breastfeeding patterns. That is, some women may have reported the time they were exclusively breastfeeding, whilst others may have filled in total duration of breastfeeding. There may also be secular trend in breastfeeding patterns, as the recommendations for exclusive/partial breastfeeding have changed over time in Sweden[14]. Today, Sweden is a country with high rate of women breastfeeding for at least six months[14], yielding a study population that is most likely affected by these patterns. There is still no established “best way” of defining the amount of breastfeeding. Most previous studies have used ever/never breastfeeding as exposure. In the present study, there were 680 women (4.8%) who reported that they had never breastfed. When the present data was re-analyzed using this categorization, there was no statistically significant association between overall breast cancer risk and ever breastfeeding (adjusted relative risk =1.14: 0.70-1.88) as compared to never. Indeed, we consider it more valuable to investigate total time of breastfeeding in relation to different breast cancer characteristics in order to see if there was a threshold.

All tumour endpoints were retrieved by record linkage to The Swedish Cancer Registry. This is a nation-wide registry and all cancer cases in Sweden are to be reported to this registry. This registry has previously been validated in Malmö and the completeness was 99% regarding breast cancer[15].

Women with prevalent breast cancer were not included in the analyses since these women most likely are cause to bias. Women with a prevalent breast cancer at baseline are more likely to decline participation in a prospective study making them subject to selection bias. Moreover, a recent study has shown reduced lactation in these women[16].

The mammography screening program was fully initiated in Malmö 1990 and during 1991 – 1996 the average participation rate was 65%[17, 18]. This could have led to over diagnosis of breast cancer, but in our study only incident invasive breast cancers were included in the subgroup analyses. Further tumour classification with regard to the biomarkers, were analyzed using the TMA technique which is a well-documented method for tumour tissue screening and two cores are considered to be sufficient in order to get a representative sample[19, 20]. The IHC data was not retrieved in medical records since laboratory analyses were subject to changes over this period of time and hence analyzing all tumours again within TMAs by one pathologist was considered more accurate.

Women in the MDCS were probably selected towards higher socioeconomic groups and the participants in the MDCS had a higher incidence of breast cancer as compared to the rest of the female population in Malmö[6]. However, absolute risks may not be applicable to the background population, but, as we had a large variation in exposure within our sample, we consider that it is still possible to make internal comparisons, thus calculating valid relative risks.

In this study it is important to consider chance findings. There is a risk of a type I error due to the many analyses in this study and our previous study on parity and risk for different breast cancer subgroups was carried out in the same cohort MDCS[21]. No correction for multiple testing was made. As for type II errors, due to few individuals in some analyses, the confidence intervals were wide and the statistical power was relatively low which may have lead to a type II error in some comparisons. And it is important to consider confounding especially in the subgroup analyses, and socioeconomic status might have an impact on breastfeeding pattern. Thulier et al. have reviewed variables associated with breastfeeding and concluded that higher educated and married women, tend to breastfeed their children for longer periods[22]. The relationship between increased risk of unfavourable breast cancer characteristics and time of breastfeeding could be measure of the association between socioeconomic status and breast cancer subgroups. In the MDCS, there was information available on education, type of occupation and marital status/cohabiting and all multivariate analyses were adjusted for these possible confounders. Hence, socioeconomic status should not have affected the results of these analyses. It has previously been shown that women in lower socioeconomic classes have a lower attendance in mammography screening as compared to women in higher socioeconomic classes[17]. This could possibly lead to detection bias, as women in higher socioeconomic classes would more likely have their breast cancer detected earlier; hence more likely have breast cancer with less aggressive characteristics and this would lead to a spurious association between breastfeeding and less aggressive breast cancer tumours. As the results in the present study were in the opposite direction, it makes such an association/detection bias unlikely.

Previous studies

The breast cancer characteristics Ki67 and grade have to our knowledge not been investigated with regard to breastfeeding previously. Most previous studies on breastfeeding and breast cancer markers, have investigated histological type and hormone receptor status. One previous study found increasing total time of breastfeeding protective against ductal type of breast cancer[5] opposite the non-significant findings in our study. Ursin et al. found total duration of breastfeeding to be protective against ER + PR + and ER-PR- tumours[5], and yet another found breastfeeding for more than six months to be protective against triple-negative breast tumours[4]. These findings were not confirmed in this study.

Potential explanations

Breastfeeding reduces lifetime ovulatory menstrual cycles[23] i.e. reducing the impact of hormone levels present during normal menstrual cycles[24] and by specifically reducing the progesterone exposure[25]. This may explain the finding in previous studies of a reduced risk of breast cancer in women who had breastfed. It is possible to hypothesize that an environment with relatively low levels of estrogen/progesterone may develop certain kind of tumour sub-groups, i.e. hormone independent tumours which in most cases are prognostically unfavourable tumours. We could in this study there not find any statistically significant association between breastfeeding and ER- tumours. Moreover breastfeeding stimulate the production of prolactin, a hormone that has been reported to have tumour promoting effects[26]. The potential relation between breastfeeding, prolactin and breast cancer is, however complex. Even if prolactin levels are high during lactation, it has been reported that among non-lactating women, prolactin levels in blood are relatively low in women with a previous long duration of breastfeeding[27]. Moreover, breast tissue itself may be able to produce prolactin and this would probably lead to locally increased levels which are not detectable in ordinary blood samples[28]. The potential relationship between breast cancer subgroups and prolactin will however need to be studied in experimental studies, in order to investigate this further.

Generally, factors associated with an increased risk of breast cancer, e.g. HRT[10] and obesity[29] have been associated with prognostically relatively favorable breast tumours. Even if this study did not find any association of breastfeeding and reduced risk of breast cancer, it may be possible to hypothesize that the few associations between breastfeeding duration and aggressive breast cancer characteristics may reflect the same mechanism. It is possible to hypothesize that reproductive factors that are protective against breast cancer may also promote tumours that are non-hormone dependent and hence tumours that grow more autonomous. This should give rise to more aggressive characteristics when studying breast cancer subgroups with regard to reproductive factors as exposures. However, the biological mechanism behind this hypothesis has still to be identified.

Conclusions

Breastfeeding duration was not associated with breast cancer risk and no strong results were seen with regard to breast cancer subgroups.

Availability of data

This study was carried out in the Malmö Diet and Cancer Study (MDCS). In order to get access to the data, an application to the committee is needed. Please contact Prof. Jonas Manjer: jonas.manjer@med.lu.se.

Declarations

Acknowledgements

Financial support was received from The Ernhold Lundström Foundation, The Einar and Inga Nilsson Foundation, The Malmö University Hospital Cancer Research Fund, The Malmö University Hospital Funds and Donations, The Crafoord Foundation, The Anna Lisa and Sven-Eric Lundgren Foundation, The Mossfelt Foundation, The Fröken Anna Jönssons Foundation and The Maja and Hjalmar Leanders Foundation. The authors would also like to thank Ms Else Nilsson for excellent technological work.

Authors’ Affiliations

(1)
Department of Surgery, Skåne University Hospital, Malmö, Lund University
(2)
Malmö Diet and Cancer Study, Skåne University Hospital
(3)
Centre for Molecular Pathology, Department of Laboratory Medicine, Skåne University Hospital
(4)
Division of Oncology, Department of Clinical Sciences, Skåne University Hospital

References

  1. Collaborative Group on Hormonal Factors in Breast Cancer: Breast cancer and breastfeeding: collaborative reanalysis of individual data from 47 epidemiological studies in 30 countries, including 50302 women with breast cancer and 96973 women without the disease. Lancet. 2002, 360 (9328): 187-195.View ArticleGoogle Scholar
  2. Yang L, Jacobsen KH: A systematic review of the association between breastfeeding and breast cancer. J Womens Health (Larchmt). 2008, 17 (10): 1635-1645. 10.1089/jwh.2008.0917.View ArticleGoogle Scholar
  3. Ma H, Bernstein L, Pike MC, Ursin G: Reproductive factors and breast cancer risk according to joint estrogen and progesterone receptor status: a meta-analysis of epidemiological studies. Breast Cancer Res. 2006, 8 (4): R43-10.1186/bcr1525.PubMedPubMed CentralView ArticleGoogle Scholar
  4. Phipps AI, Malone KE, Porter PL, Daling JR, Li CI: Reproductive and hormonal risk factors for postmenopausal luminal, HER-2-overexpressing, and triple-negative breast cancer. Cancer. 2008, 113 (7): 1521-1526. 10.1002/cncr.23786.PubMedPubMed CentralView ArticleGoogle Scholar
  5. Ursin G, Bernstein L, Lord SJ, Karim R, Deapen D, Press MF, Daling JR, Norman SA, Liff JM, Marchbanks PA, Folger SG, Simon MS, Strom BL, Burkman RT, Weiss LK, Spirtas R: Reproductive factors and subtypes of breast cancer defined by hormone receptor and histology. Br J Cancer. 2005, 93 (3): 364-371. 10.1038/sj.bjc.6602712.PubMedPubMed CentralView ArticleGoogle Scholar
  6. Manjer J, Carlsson S, Elmståhl S, Gullberg B, Janzon L, Lindström M, Mattisson I, Berglund G: The Malmo Diet and Cancer Study: representativity, cancer incidence and mortality in participants and non-participants. Eur J Cancer Prev. 2001, 10 (6): 489-499. 10.1097/00008469-200112000-00003.PubMedView ArticleGoogle Scholar
  7. Manjer J, Elmstahl S, Janzon L, Berglund G: Invitation to a population-based cohort study: differences between subjects recruited using various strategies. Scand J Public Health. 2002, 30 (2): 103-112. 10.1177/14034948020300020401.PubMedView ArticleGoogle Scholar
  8. Russo J, Moral R, Balogh GA, Mailo D, Russo IH: The protective role of pregnancy in breast cancer. Breast Cancer Res. 2005, 7 (3): 131-142. 10.1186/bcr1029.PubMedPubMed CentralView ArticleGoogle Scholar
  9. Elston CW, Ellis IO: Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. Histopathology. 1991, 19 (5): 403-410. 10.1111/j.1365-2559.1991.tb00229.x.PubMedView ArticleGoogle Scholar
  10. Borgquist S, Anagnostaki L, Jirstrom K, Landberg G, Manjer J: Breast tumours following combined hormone replacement therapy express favourable prognostic factors. Int J Cancer. 2007, 120 (10): 2202-2207. 10.1002/ijc.22542.PubMedView ArticleGoogle Scholar
  11. Borgquist S1, Wirfält E, Jirström K, Anagnostaki L, Gullberg B, Berglund G, Manjer J, Landberg G: Diet and body constitution in relation to subgroups of breast cancer defined by tumour grade, proliferation and key cell cycle regulators. Breast Cancer Res. 2007, 9 (1): R11-10.1186/bcr1644.PubMedPubMed CentralView ArticleGoogle Scholar
  12. Dowsett M, Bartlett J, Ellis IO, Salter J, Hills M, Mallon E, Watters AD, Cooke T, Paish C, Wencyk PM, Pinder SE: Correlation between immunohistochemistry (HercepTest) and fluorescence in situ hybridization (FISH) for HER-2 in 426 breast carcinomas from 37 centres. J Pathol. 2003, 199 (4): 418-423. 10.1002/path.1313.PubMedView ArticleGoogle Scholar
  13. Troy LM, Michels KB, Hunter DJ, Spiegelman D, Manson JE, Colditz GA, Stampfer MJ, Willett WC: Self-reported birthweight and history of having been breastfed among younger women: an assessment of validity. Int J Epidemiol. 1996, 25 (1): 122-127. 10.1093/ije/25.1.122.PubMedView ArticleGoogle Scholar
  14. SoS (The National Board of Health and Welfare in Sweden): Breast-feeding, children born 2006. 2006, [http://www.socialstyrelsen.se/publikationer2008/2008-125-12]Google Scholar
  15. Garne JP: Invasive breast cancer in Malmö 1961–1992 - an epidemiological study. Dissertation. 1996, Malmö: Lund UniversityGoogle Scholar
  16. Leal SC, Stuart SR, Carvalho Hde A: Breast irradiation and lactation: a review. Expert Rev Anticancer Ther. 2013, 13 (2): 159-164. 10.1586/era.12.178.PubMedView ArticleGoogle Scholar
  17. Matson S, Andersson I, Berglund G, Janzon L, Manjer J: Nonattendance in mammographic screening: a study of intraurban differences in Malmo, Sweden, 1990–1994. Cancer Detect Prev. 2001, 25 (2): 132-137.PubMedGoogle Scholar
  18. Zackrisson S, Andersson I, Manjer J, Janzon L: Non-attendance in breast cancer screening is associated with unfavourable socio-economic circumstances and advanced carcinoma. Int J Cancer. 2004, 108 (5): 754-760. 10.1002/ijc.11622.PubMedView ArticleGoogle Scholar
  19. Camp RL, Charette LA, Rimm DL: Validation of tissue microarray technology in breast carcinoma. Lab Invest. 2000, 80 (12): 1943-1949. 10.1038/labinvest.3780204.PubMedView ArticleGoogle Scholar
  20. Hoos A, Cordon-Cardo C: Tissue microarray profiling of cancer specimens and cell lines: opportunities and limitations. Lab Invest. 2001, 81 (10): 1331-1338. 10.1038/labinvest.3780347.PubMedView ArticleGoogle Scholar
  21. Butt S, Borgquist S, Anagnostaki L, Landberg G, Manjer J: Parity and age at first childbirth in relation to the risk of different breast cancer subgroups. Int J Cancer. 2009, 125 (8): 1926-1934. 10.1002/ijc.24494.PubMedView ArticleGoogle Scholar
  22. Thulier D, Mercer J: Variables associated with breastfeeding duration. J Obstet Gynecol Neonatal Nurs. 2009, 38 (3): 259-268. 10.1111/j.1552-6909.2009.01021.x.PubMedView ArticleGoogle Scholar
  23. Russo J, Russo IH: Toward a physiological approach to breast cancer prevention. Cancer Epidemiol Biomarkers Prev. 1994, 3 (4): 353-364.PubMedGoogle Scholar
  24. Bernstein L: Epidemiology of endocrine-related risk factors for breast cancer. J Mammary Gland Biol Neoplasia. 2002, 7 (1): 3-15. 10.1023/A:1015714305420.PubMedView ArticleGoogle Scholar
  25. Henderson BE, Ross RK, Judd HL, Krailo MD, Pike MC: Do regular ovulatory cycles increase breast cancer risk?. Cancer. 1985, 56 (5): 1206-1208. 10.1002/1097-0142(19850901)56:5<1206::AID-CNCR2820560541>3.0.CO;2-9.PubMedView ArticleGoogle Scholar
  26. Tworoger SS, Hankinson SE: Prolactin and breast cancer risk. Cancer Lett. 2006, 243 (2): 160-169. 10.1016/j.canlet.2006.01.032.PubMedView ArticleGoogle Scholar
  27. Hietala M, Olsson H, Jernstrom H: Prolactin levels, breast-feeding and milk production in a cohort of young healthy women from high-risk breast cancer families: implications for breast cancer risk. Fam Cancer. 2008, 7 (3): 221-228. 10.1007/s10689-007-9178-0.PubMedView ArticleGoogle Scholar
  28. Clevenger CV, Chang WP, Ngo W, Pasha TL, Montone KT, Tomaszewski JE: Expression of prolactin and prolactin receptor in human breast carcinoma. Evidence for an autocrine/paracrine loop. Am J Pathol. 1995, 146 (3): 695-705.PubMedPubMed CentralGoogle Scholar
  29. Borgquist S, Jirstrom K, Anagnostaki L, Manjer J, Landberg G: Anthropometric factors in relation to different tumor biological subgroups of postmenopausal breast cancer. Int J Cancer. 2009, 124 (2): 402-411. 10.1002/ijc.23850.PubMedView ArticleGoogle Scholar

Copyright

© Butt et al.; licensee BioMed Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.

Advertisement