Effect of obesity and endocrine therapy on the prognosis of premenopausal women with HR+HER2-breast cancer: a multi-center retrospective study

doi:10.21203/rs.3.rs-4315013/v1

The effects of obesity on breast cancer prognosis may be subtype-dependent. However, research on premenopausal women with HR + HER2- subtype is insufficient. We included premenopausal women with HR + HER2- early breast cancer who received radical surgery in 42 breast centers nationwide from 2016 to 2021. Patients were classified into four groups according to body mass index (BMI): underweight (UW), normal weight (NW), overweight (OW), obesity (OB). Kaplan-Meier curve was used to compare disease-free survival (DFS) between different BMI groups. Multivariate cox regression analysis was used to identify the effect of obesity on prognosis. Total 5094 patients were included in the analysis. DFS in OB patients was significantly worse than that in patients with NW (p = 0.002). After adjusted for age, tumor size, lymph node involvement, Ki67 index, PR, chemotherapy, radiation therapy and OFS, obesity remains an independent prognostic factor for DFS in premenopausal patients with HR + HER2- breast cancer (p = 0.043). In OW/OB patients who only received selective estrogen receptor modulators (SERMs), DFS was significantly worse than that in UW/NW patients (p = 0.0067). However, OW/OB does not affect DFS in patients who received ovarian function suppression (OFS) (p = 0.865). Furthermore, analysis from Restricted Cubic Splines (RCS) showed that the risk of recurrence continues to increase with increasing BMI in overweight and obese patients. Our study confirmed that obesity stands as an independent prognostic factor for DFS in premenopausal patients with HR + HER2- breast cancer. OFS may reverse the prognosis of premenopausal women with HR + HER2- breast cancer who only receiving SERMs.

Biological sciences/Cancer/Breast cancer

Biological sciences/Cancer/Cancer epidemiology

Biological sciences/Cancer/Cancer therapy

obesity

prognosis

breast cancer

premenopausal

Body mass index (BMI), a standard metric for classifying weight and obesity, has been suggested to be associated with incidence of breast cancer. Research has shown that obesity increases the risk for type 2 diabetes mellitus by promoting insulin resistance and increases serum estrogen levels by the upregulation of aromatase. Increased circulating glucose has been shown to activate mammalian target of rapamycin (mTOR), a significant signaling pathway in breast cancer pathogenesis¹. Increasingly, studies have shown the association between BMI and prognosis of patients with early-stage breast cancer. A meta-analysis consisting of 73 cohort studies showed that overweight or obesity was a risk factor for overall survival (OS) in patients with breast cancer compared to normal weight². However, the relationship between obesity and prognosis of breast cancer was varied and controversial in different molecular subtypes and menstrual status. A prospective randomized controlled study shows that obesity is an independent prognostic factor for estrogen receptor positive (ER+) young breast cancer, but not for ER negative subtype³. Sparano et al.'s research analysis based on multiple prospective randomized controlled studies found that increasing BMI within overweight (OW) and obesity (OB) was associated with inferior outcomes in HR + HER2- subtype for disease-free survival (DFS) and OS but not in human epidermal growth factor receptor 2 (HER-2)overexpressing or triple-negative disease⁴. Data from South Korea also indicated that obesity patients have worse OS and breast cancer-specific survival (BCSS) than normal weight in HR + HER2- breast cancer⁵.

Hormone receptor positive early breast cancer patients with different menstrual status receive different drugs as adjuvant endocrine therapy. Retrospective analysis from ATAC trials suggested that obese patients treated with anastrozole had worse prognosis than those without obesity rather than tamoxifen treatment group ⁶. An analysis from the prospective ABCSG-12 trial showed that obesity significantly impacts the efficacy of anastrozole and goserelin in premenopausal patients⁷. High BMI at diagnosis seems associated with a higher risk of recurrence for postmenopausal women who receiving AI. In a similar study, Harborg et al. enrolled 13230 postmenopausal women with breast cancer, revealed increased recurrence hazards associated with obesity compared to patients with healthy weight⁸. However, there are few studies only focusing on premenopausal women, and most of them are single-institute retrospective study. Ozaki et.al reported that high BMI was associated with worse prognosis in premenopausal patients with hormone receptor-positive (HR+) breast cancer who received adjuvant tamoxifen (TAM)⁹. These results indicate that the effect of BMI on the efficacy and prognosis of adjuvant endocrine therapy for premenopausal breast cancer is still controversial. Therefore, more institutional data are needed to explore the relationship between BMI and prognosis in specific subtypes of premenopausal breast cancer.

Data from multiple institutions was used to explore the effect of BMI on the prognosis of premenopausal patients with HR + HER- early breast cancer. We try to explore whether obesity is an independent risk factor for the prognosis of premenopausal breast cancer. Furthermore, understanding the effect of BMI on the prognosis of premenopausal breast cancer in various endocrine therapy regimens is also a significant aspect of our research.

Patients' characteristics

As Fig. 1 showed, total 5094 premenopausal women with HR + HER2- early breast cancer was finally included in our study. Patients' characteristics are shown in Table 1. 198 (3.9%) patients are UW, 3690 (72.5%) patients are NW, 1061 (20.8%) patients were OW, and 145 (3.8%) patients were OB at diagnosis. Patients with older (>40) are more OW and OB at diagnosis than UW and NW. Obese patients have a higher stage (III) and a higher proportion of lower ER expression (≤ 50%). More patients with OW and OB received chemotherapy and radiotherapy. Patients with OW and OB are more likely to have larger tumors (≥ 2cm), higher histological grade (Grade III) and more lymph node involvement (N2&N3) at diagnosis compared with patients with UW and NW (Table 2).

BMI and Prognosis

The primary analysis of DFS in HR + HER2- premenopausal patients by different BMI subgroup is shown in Fig. 2. OB has significantly worse DFS than that in patients with NW (HR 3.725; 95% CI, 1.618–8.573; p = 0.002) (Fig. 2A). Compared with NW, UW and OW did not show significantly different DFS (Fig. 2A-2B). When stratified by OFS, we found that the DFS of OW/OB in patients who only received selective estrogen receptor modulators (SERMs) without OFS was significantly worse than that of UW/NW (HR 1.711; 95% CI, 1.16–2.523; p = 0.0067) (Fig. 3A). However, the DFS of OW/OB in patients who received SERMs/AI and OFS were not significantly different from that of UW/NW (HR 1.045, 95% CI: 0.631–1.728, p = 0.865) (Fig. 3B).

Multivariate cox regression analysis was performed to evaluate the effect of OB for prognosis adjusted for other prognostic factors. After adjusted for age, tumor size, lymph node involvement, Ki67 and PR, patients with OB has significantly worse DFS than that in patients with NW (HR 1.814, 95% CI: 1.022–3.219, p = 0.042). After further adjustment of chemotherapy, radiation therapy, and OFS, obesity remains an independent risk factor for DFS (HR 1.810, 95% CI: 1.019–3.212, p = 0.043) (Table 3). As shown in Fig. 4, the recurrence hazard in patients with a BMI greater than 25 monotonically heightens with increasing BMI.

HR + HER2- is the most common molecular subtype of breast cancer. To be best of our knowledge, there is no relevant research to independently explore the relationship between BMI and the prognosis of premenopausal breast cancer in HR + HER2- subtype. We conducted the study based on multi-center data and found that obesity could increase risk of breast cancer recurrence in premenopausal patients with HR + HER2- subtype. More interestingly, obesity seems to be more likely to increase the risk of recurrence in premenopausal patients with HR + HER2- breast cancer treated with SERMs while not in patients who receiving OFS in the adjuvant endocrine therapy. In addition, the recurrence hazard of breast cancer continues to increase when BMI exceeds normal.

An increasing body of research have indicated high BMI is a risk factor for postmenopausal breast cancer⁸; ¹⁰; ¹¹. However, few studies focused on the relationship between BMI and the prognosis of premenopausal with breast cancer. Ozaki et al. analyzed 3380 cases of premenopausal women with HR + breast cancer and found that high BMI was associated with worse breast cancer-specific survival (BCSS) in patients who received adjuvant TAM⁹. Another single center retrospective analysis from Taiwan showed that BMI was an independent prognostic factor for OS and DFS in breast cancer patients younger than 50 years¹². Previous studies have shown that BMI is not an independent prognostic factor for HER2 positive and triple negative breast cancer. The effects of obesity on breast cancer prognosis may be subtype-dependent. In order to avoid interference from other subtypes, our study separately included premenopausal patients with HR + HER2- breast cancer for analysis. Analysis base on 5094 cases of HR + HER2- premenopausal breast cancer from multiple-centers showed that obesity is an independent risk factor for DFS after adjusted clinical pathological and treatment factors. The mechanism of high BMI leading to poor prognosis of premenopausal HR + HER2- breast cancer is still unclear, and there may be several reasons. Firstly, high BMI is usually accompanied by changes in hormone levels, especially an increase in estrogen levels. High levels of estrogen may promote the growth and proliferation of HR + breast cancer cells. Premenopausal patients with HR + HER2- breast cancer usually receives TAM treatment. Sahar et al. demonstrated that circulating exosomes derived from obese women could more likely lead to tumorigenesis and tamoxifen resistance in MCF7 cells than derived from normal women¹³. Secondly, obesity can lead to upregulation of pro-inflammatory cytokines, adipokines, and angiogenic factors, which are closely related to the proliferation and invasive characteristics of breast cancer¹⁴. Furthermore, high BMI increases the circulating levels of insulin and insulin-like growth factor-1, promoting tumor cell proliferation and invasion¹⁵. In vivo experiments demonstrated that in an obese microenvironment, there were elevated local levels of leptin, which triggered the activation of PI3K, ERK1/2, and STAT3 pathways through leptin receptors. This cascade of events ultimately facilitated an accelerated progression of tumors¹⁶. Another study from Linares et al. showed that leptin both increases proliferation of breast cancer cells in vitro and diminished the efficacy of tamoxifen¹⁷. Recently, a preplanned analysis of the PALLAS trial demonstrates a significant impact of BMI on side effects, dose reductions, early treatment discontinuation, and relative dose intensity¹⁸. This result suggests that BMI may ultimately affect prognosis by affecting drug efficacy and side effects.

Furthermore, our study suggested that BMI did not affect the prognosis of premenopausal women with HR + HER2- breast cancer who receiving OFS plus as endocrine therapy. Exploratory analysis from the ABCSG12 trial shows that, overweight premenopausal patients who received OFS and aromatase inhibitor

(AI) had a significantly increased risk of disease recurrence compared with normal weight patients. however, BMI did not influence premenopausal patients who received OFS and TAM⁷. Ozaki et al. reported similar results. They also found that BMI ≥ 25 premenopausal patients with HR + breast cancer who received TAM, BCSS was significantly worse than that in BMI<25 patients. These results suggested that the addition of OFS may reverse the effect of BMI on the prognosis of premenopausal breast cancer treated with TAM. Regrettably, our study is unable to further analyze the impact of BMI on the prognosis of premenopausal breast cancer when combining OFS with TAM. Longer follow-up time is required to determine the benefits of adding OFS as an adjuvant endocrine therapy in premenopausal breast cancer patients with high BMI to receive TAM treatment.

Obesity is an independent prognostic factors for DFS in premenopausal patients with HR + HER2- breast cancer. OFS may reverse the prognosis of premenopausal women with HR + HER2- breast cancer who only receiving SERMs.

Patients

In this study, all data were acquired from Shanghai Jiaotong University-Breast cancer Database (SJTU-BCDB) (http://47.100.125.104:8080/). This database contains breast cancer data from 42 breast centers in China. Premenopausal female patients who underwent radical breast surgery for stage I–III HR+/HER2- primary breast cancer from January 2016 to December 2021 were included in our study. The study protocol received approval from the independent ethical committee of Quanzhou First Hospital, affiliated with Fujian Medical University, and adhered to the principles of the Helsinki Declaration. Due to the retrospective nature of the study, the requirement for informed consent was waived. All patients must receive selective estrogen receptor modulators (SERMs) or SERMs/AI combined OFS as adjuvant endocrine therapy. Patients with a history of breast cancer or other invasive cancers were excluded. Male and bilateral breast cancer were also excluded. Patients who did not receive or missing information on endocrine therapy were excluded in this study. Lack of BMI records or follow-up information were also not included. BMI was classified as follows: underweight (UW), BMI < 18.5 kg/m2; normal weight (NW), 18.5–24.9 kg/m2; overweight (OW), 25.0–29.9 kg/m2; obese (OB), ≥ 35 kg/m2.

Outcome

The end point was DFS, defined as the time interval from the date of radical breast surgery to the date of recurrence, metastasis or death from breast cancer. Kaplan-Meier curve was used to compare DFS between BMI categories. Then, we utilized a multivariable cox regression model to compute hazard ratios for DFS according to BMI categories. Multivariable models included the following covariates: age at diagnosis, tumor size, node status, Ki67 index, PR, chemotherapy, radiotherapy and OFS. Furthermore, multivariable cox regression model with BMI as a continuous exposure was used to demonstrate the relationship between BMI and the prognosis of premenopausal women with HR+HER2- breast cancer.

Statistical Analysis

Chi-square tests or Fisher’s exact tests were employed to assess disparities in clinicopathological characteristics and treatment information across BMI categorical. Restricted cubic splines were used to visualize continuous BMI and hazard ratios for breast cancer recurrence. A two-tailed P value of less than 0.05 was considered statistically significant. Analyses were conducted using R version 4.2.3, and GraphPad Prism 9 software was utilized for graphical representation.

Acknowledgments

We appreciate the data support provided by the Shanghai Jiaotong University-Breast cancer Database (SJTU-BCDB) (http://47.100.125.104:8080/).

Author contributions

WL, DC and CW designed the overall study，analysis of data was contributed by WL and CH, WL prepared all the figures and tables, WL drafted the manuscript, WL, DC and CW discussed and edited the paper. All authors read and approved the manuscript.

Funding

This work was supported by the Quanzhou City Science & Technology Program of China (Grant No.2021N076S).

Data availability

All data supporting our article will be made available by Weibin Lian.

All methods conducted in this study adhered strictly to the pertinent guidelines and regulations or Declaration of Helsinki.

Ethics approval and consent to participate

The studies involving human participants received approval from the Ethics Committee of Quanzhou First Hospital, affiliated with Fujian Medical University. Written informed consent was obtained from all patients/participants prior to their involvement in this study.

Consent for publication

Not applicable.

Competing interests

The authors have declared no competing interests.

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Table 1. Patients' characteristics
Characteristics	N=5094(%)
Age(years)
≤40	1441 (28.3)
>40	3653 (71.7)
BMI
UW (<18.5 kg/m2)	198 (3.9%)
NW (18.5–24.9 kg/m2)	3690 (72.5%)
OW (25.0–29.9 kg/m2)	1061 (20.8%)
OB（30kg/m2）	145 (3.8%)
Tumor size
≤2cm	3219 (63.2)
>2cm	1875 (36.8)
N stage
N0	3198 (62.8)
N1	1257 (24.6)
N2	451 (8.9)
N3	188 (3.7)
TNM Stage
I	2379 (46.7)
II	2035 (39.9)
III	680 (13.4)
ER
≤50%	485 (9.5)
＞50%	4609 (90.5)
PR
≤20	917 (18)
>20	4177 (82)
Ki67
＜14%	2076 (40.8)
≥14	3018 (59.2)
Grade
I	515 (10.1)
II	2973 (58.4)
III	766 (15)
unknow	840 (16.5)
Chemotherapy
Yes	3643 (71.5)
No	1451 (28.5)
Radiotherapy
Yes	3115 (61.2)
No	1979 (38.8)
OFS
Yes	1812 (35.6)
No	3282 (64.4)
Abbreviations: BMI, Body mass index; UW, underweight; NW, normal weight; OW, overweight; OB, obese; ER, estrogen receptor; PR, progesterone receptor; OFS, ovarian function suppression

Table 2 Characteristics of patients according to BMI
Characteristics	Patients, No. (%)				p value
Characteristics	UW <18.5kg/m2	NW18.5–24.9kg/m2	OW 25.0–29.9kg/m2	OB 30kg/m2	p value
All	198 (3.9)	3690 (72.4)	1061 (20.8)	145 (2.9)
Age					＜0.001
≤40	105 (53)	1059 (28.7)	242 (22.8)	35 (24.1)
>40	93 (47)	2631 (71.3)	819 (77.2)	110(75.9)
ER					0.016
≤50%	13 (6.6)	359 (9.7)	90 (8.5)	23 (15.9)
＞50%	185 (93.4)	3331 (90.3)	971(91.5)	122(84.1)
PR					0.687
≤20	36 (18.2)	654 (17.7)	196 (18.5)	31 (21.4)
>20	162 (81.8)	3039 (82.3)	865 (81.5)	114(78.6)
TNM Stage					＜0.001
I	103 (52)	1817 (49.2)	412 (38.8)	47 (32.4)
II	68 (34.3)	1428 (38.7)	475 (44.8)	64 (44.1)
III	27 (13.7)	445 (12.1)	174 (16.4)	34 (23.5)
Tumor size					＜0.001
≤2cm	133 (67.2)	2432 (65.9)	586 (55.2)	68 (46.9)
>2cm	65 (32.8)	1258 (34.1)	475 (44.8)	77 (53.1)
N stage					＜0.001
N0	130 (65.7)	2379 (64.5)	612 (57.7)	77 (53.1)
N1	41 (20.7)	893 (24.2)	285 (26.9)	38 (26.2)
N2	18 (9)	295 (8)	117 (11)	21 (14.5)
N3	9 (4.6)	123 (3.3)	47 (4.4)	9 (6.2)
Ki67					0.581
＜14%	82 (41.4)	1522 (41.2)	418 (39.4)	54 (37.2)
≥14	116 (58.6)	2168 (58.8)	643 (60.6)	91 (62.8)
Grade					0.004
I	21 (10.6)	404 (11)	85 (8)	5 (3.4)
II	120 (60.6)	2151 (58.3)	618 (58.2)	84 (57.9)
III	23 (11.6)	544 (14.7)	169 (16)	30 (20.7)
Not grade	34 (17.2)	591 (16)	189 (17.8)	26 (17.9)
Chemotherapy					＜0.001
No	60 (30.3)	1100 (29.8)	265 (25)	26 (17.9)
Yes	138 (69.7)	2590 (70.2)	796 (75)	119(82.1)
OFS					0.013
No	106 (53.5)	2394 (64.9)	689 (64.9)	93 (64.1)
Yes	92 (46.5)	1296 (35.1)	372 (35.1)	52 (35.9)
Radiotherapy					0.043
No	80 (40.4)	1469 (39.8)	372 (35.1)	58 (40)
Yes	118 (59.6)	2221 (60.2)	689 (64.9)	87 (60)
Abbreviations: BMI, Body mass index; UW, underweight; NW, normal weight; OW, overweight; OB, obese; ER, estrogen receptor; PR, progesterone receptor; OFS, ovarian function suppression

Table 3 Multivariate cox proportional hazards analyses of prognostic factors for DFS
Prognostic factor	Adjusted HR (95% CI)	p value	Adjusted# HR (95% CI)	p value
Prognostic factor	Adjusted HR (95% CI)	p value	Adjusted# HR (95% CI)	p value
OB versus NW	1.814(1.022-3.219)	0.042	1.810 (1.019-3.212)	0.043
Age ＞40y versus 40y	0.688（0.503-0.940）	0.019	0.705 (0.509-0.978)	0.036
Tumor size ＞2cm versus ≥2cm	1.444(1.048-1.991)	0.025	1.424(1.03-1.97)	0.033
N2 & N3 versus N0 & N1	2.298(1.613-3.274)	＜0.001	2.275(1.548-3.345)	＜0.001
Ki67 ≥14% versus ＜14%	1.526(1.083-2.151)	0.016	1.497(1.049-2.135)	0.026
PR ＞20% versus ≤20%	0.644(0.459-0.903)	0.011	0.645(0.459-0.907)	0.012
Chemotherapy yes versus no			1.091(0.699-1.702)	0.703
Radiotherapy yes versus no			0.912(0.643-1.294)	0.607
OFS yes versus no			1.101(0.784-1.546)	0.578
Abbreviations: DFS, disease-free survival; HR, hazard ratio; CI, confidential interval; NW, normal weight; OB, obese; PR, progesterone receptor; OFS, ovarian function suppression.

No competing interests reported.

Effect of obesity and endocrine therapy on the prognosis of premenopausal women with HR+HER2-breast cancer: a multi-center retrospective study

Status:

Version 1

Abstract

Figures

Introduction

Results

Patients' characteristics

BMI and Prognosis

Discussion

Conclusion

Methods

Patients

Outcome

Declarations

References

Tables

Additional Declarations

Status:

Version 1