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Breast Cancer Research : BCR logoLink to Breast Cancer Research : BCR
. 2018 Sep 18;20:114. doi: 10.1186/s13058-018-1033-8

Breast cancer risk factors, survival and recurrence, and tumor molecular subtype: analysis of 3012 women from an indigenous Asian population

Mustapha Abubakar 1, Hyuna Sung 1,2, Devi BCR 3, Jennifer Guida 4, Tieng Swee Tang 3, Ruth M Pfeiffer 1, Xiaohong R Yang 1,✉
PMCID: PMC6145192  PMID: 30227867

Abstract

Background

Limited evidence, mostly from studies in Western populations, suggests that the prognostic effects of lifestyle-related risk factors may be molecular subtype-dependent. Here, we examined whether pre-diagnostic lifestyle-related risk factors for breast cancer are associated with clinical outcomes by molecular subtype among patients from an understudied Asian population.

Methods

In this population-based case series, we evaluated breast cancer risk factors in relation to 10-year all-cause mortality (ACM) and 5-year recurrence by molecular subtype among 3012 women with invasive breast cancer in Sarawak, Malaysia. A total of 579 deaths and 314 recurrence events occurred during a median follow-up period of ~ 24 months. Subtypes (luminal A-like, luminal B-like, HER2-enriched, triple-negative) were defined using immunohistochemical markers for hormone receptors and human epidermal growth factor receptor 2 (HER2) in conjunction with histologic grade. Hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between risk factors and ACM/recurrence were estimated in subtype-specific Cox regression models.

Results

We observed heterogeneity in the relationships between parity/breastfeeding, age at first full-term pregnancy (FFP), family history, body mass index (BMI), and tumor subtype (p value < 0.05). Among luminal A-like patients only, older age at menarche [HR (95% CI) ≥15 vs ≤ 12 years = 2.28 (1.05, 4.95)] and being underweight [HRBMI < 18.5kg/m2 vs. 18.5–24.9kg/m2 = 3.46 (1.21, 9.89)] or overweight [HR25–29.9kg/m2 vs. 18.5–24.9kg/m2 = 3.14 (1.04, 9.50)] were associated with adverse prognosis, while parity/breastfeeding [HRbreastfeeding vs nulliparity = 0.48 (0.27, 0.85)] and older age at FFP [HR > 30 vs < 21 years = 0.20 (0.04, 0.90)] were associated with good prognosis. For these women, the addition of age at menarche, parity/breastfeeding, and BMI, provided significantly better fit to a prognostic model containing standard clinicopathological factors alone [LRχ2 (8df) = 21.78; p value = 0.005]. Overall, the results were similar in relation to recurrence.

Conclusions

Our finding that breastfeeding and BMI were associated with prognosis only among women with luminal A-like breast cancer is consistent with those from previously published data in Western populations. Further prospective studies will be needed to clarify the role of lifestyle modification, especially changes in BMI, in improving clinical outcomes for women with luminal A-like breast cancer.

Keywords: Breast cancer, Risk factors, Survival, Recurrence, Molecular subtype

Background

In addition to impacting incidence, lifestyle and environmental risk factors for breast cancer may influence disease progression. Several studies have previously evaluated this question, with mixed results. While some studies have documented older age at menarche [1–3], early age at first full-term pregnancy (FFP) [4, 5] and nulliparity [6, 7] to be associated with adverse prognosis in breast cancer patients, others have reported better prognosis in relation to these risk factors [8–12]. Discrepancies in reported associations may be explained by differences in study populations, risk factor distributions, and potential confounders, but could also be due to heterogeneity inherent in breast cancer.

Findings from expression profiling studies have been used to classify breast cancers into intrinsic subtypes (i.e. luminal A, luminal B, human epidermal growth factor receptor 2 (HER2)-enriched, basal-like, and normal-like subtypes), which were associated with different prognoses [13] and can be corroborated by immunohistochemical (IHC) markers for hormone receptors (i.e. estrogen receptor (ER), progesterone receptor [PR]) and HER2. Recently, proxies of the extent of tumor proliferation have been endorsed to refine subgroups that recapitulate the intrinsic subtypes more accurately than using hormone receptors and HER2 alone [14, 15]. Epidemiological studies have shown that associations between breast cancer risk factors vary by tumor subtypes. For example, parity and early age at FFP are associated with decreased risk of luminal breast tumors, but they do not protect and may even increase the risk for ER-negative or triple-negative breast cancers [16–19].

Three previous studies have evaluated the relationship between breast cancer risk factors and survival according to molecular subtype, one among women in Seoul, South Korea [20] and the other two involving analyses of US-based prospective breast cancer cohorts [21, 22]. Results from these studies suggest that the associations between late age at menarche [20], breastfeeding [21], high body mass index (BMI) [22] and survival after breast cancer might differ according to molecular subtype. However, findings from these studies are yet to be validated in independent populations and, to our knowledge, no study has specifically examined risk factors in relation to survival according to subtypes defined by the recent IHC classification scheme accounting for proliferation in an Asian population.

Despite racial and geographic variations in the incidence, presentation, and outcome of breast cancer; so far, most investigations on risk factors in relation to tumor subtypes and survival have been conducted in European populations. This analysis, therefore, aims to evaluate the association between breast cancer risk factors and tumor molecular subtypes, defined by hormone receptors and HER2 in conjunction with histologic grade; and to examine the relationship between risk factors and survival by molecular subtype among women in Sarawak, Malaysia.

Methods

Study population

Sarawak is a Malaysian state on Borneo with a multiethnic composition, comprising of native Borneo populations (51%), Chinese (25%) and Malays (24%) [23]. Overall, 3355 women with invasive breast cancer diagnosed and treated between 2003 and 2016 in the Department of Radiotherapy, Oncology, and Palliative Care, Sarawak General Hospital where ~ 93% of all breast cancer cases diagnosed in Sarawak are treated, were recruited for this study. Of these, 106 (~ 3%) did not participate by not filling the questionnaire leading to a participating rate of ~ 97%. Of the 3249 who participated, 168 (~ 5%) were lost to follow-up and 69 did not have complete information on ER, PR, HER2, and grade that is needed to generate breast cancer subtypes hence were excluded from further analysis. Ultimately, 3012 women representing ~ 90% of the original population were included in the current analysis. Information on lifestyle and environmental risk factors were obtained from questionnaires that were administered to participants at enrollment, which was approximately 4 weeks after diagnosis, while information on tumor characteristics was obtained from clinical records. Weight and height measurements were obtained in the clinic as part of the clinical workup for the calculation of chemotherapy doses. Recordings were performed by a trained member of staff using a weighing scale. Patients were given follow-up appointments to the clinic during which recurrence was evaluated and clinically confirmed. For those living in the outskirts of the city, if recurrence was suspected, the patients were referred to our clinic for further evaluation. Furthermore, a research assistant made regular calls to check the patient’s status, whether alive or dead. The current analysis included a follow-up period of 153 months (median follow-up = 24 months). Ethical approval for this project was provided by the Ethics Committee of the National Institutes of Health, Malaysia. This study did not involve the use of personal identifying information; hence, it was exempted from review by the National Institutes of Health (NIH) Office of Human Subject Research Protections [23].

Breast cancer subtype definition

IHC staining for ER, PR, and HER2 was performed on formalin-fixed, paraffin-embedded tissue sections as has been previously described [24]. Molecular subtypes were defined using the St Gallen classification, proposed for the recapitulation of the intrinsic subtypes using IHC and proliferation markers [14, 15]. According to the St Gallen classification scheme, luminal breast cancers can be further distinguished into subgroups based on their level of proliferation (using KI67 or histologic grade) and hormone receptor expression patterns. Accordingly, luminal tumors that homogeneously express hormone receptors (i.e. ER+ and PR+) and low proliferation are classified as luminal A-like while those that heterogeneously express hormone receptors (i.e. ER+/PR− or ER−/PR+) and/or those that homogeneously or heterogeneously express hormone receptors (i.e. ER+ and/or PR+) but are also high proliferating (high KI67 or grade 3) and/or HER2+ are classified as luminal B. In keeping with this definition, we utilized ER, PR, and HER2 in addition to histologic grade [25], to define subtypes as follows: Luminal A-like: ER+ and PR+, HER2− and low grade (histologic grade 1 or 2); Luminal B-like: ER+ and/or PR+, HER2− and high-grade (histologic grade 3) or ER+ and/or PR+, HER2+ (regardless of levels of histologic grade); HER2-enriched: ER− and PR− and HER2+; and triple-negative: ER− and PR− and HER2−.

Statistical analysis

Frequency tables were used to assess the distribution of risk factors and clinicopathological characteristics among the different subtypes. The chi-square test was used to assess differences for categorical variables and the Kruskal-Wallis test was used for continuous variables.

We categorized risk factors based on what is the convention for each variable and in accordance with what has been published in large-scale studies of breast cancer [18, 26]. We categorized age at menarche [≤12 years (early menarche), 13, 14 and ≥ 15 years (late menarche)]; family history of breast cancer in a first-degree relative [yes and no]; age at FFP [< 21, 21–24.9, 25–30, > 30 years] and age at menopause [≤ 50 and > 50 years] similarly as in previously published articles [18, 26]. For BMI, we adopted the World Health Organization classification [< 18.5 kg/m2 (underweight); 18.5–24.9 kg/m2 (normal weight); 25–29.9 kg/m2 (overweight) and ≥ 30 kg/m2 (obese)]. To test for associations between risk factors and molecular subtypes, we constructed a polytomous logistic regression model with tumor subtype as the outcome (luminal A-like subtype as the reference category) and risk factors (age at menarche [≤ 12 years (early menarche, reference category), 13, 14, and ≥ 15 years (late menarche)], parity and breastfeeding [nulliparity (reference category), parity but no breastfeeding, parity and breastfeeding], age at FFP [< 21 (reference category), 21–24.9, 25–30, > 30 years], family history [yes and no (reference category)], and BMI [< 18.5 kg/m2 (underweight); 18.5–24.9 kg/m2 (normal weight, reference category); 25–29.9 kg/m2 (overweight) and ≥ 30 kg/m2 (obese)] as explanatory variables, with adjustment for age at diagnosis (< 35, 35–45, 45–55, 55–65, 65–75, > 75 years) and ethnicity (Chinese, Malay, Native).

The association between breast cancer subtypes and all-cause mortality/recurrence was determined using Kaplan-Meier survival curves and Cox-proportional hazards regression models, which included adjustments for standard prognostic parameters including age at diagnosis, ethnicity, BMI, histologic grade, TNM stage I–IV [i.e. size (T), nodal status (N) and metastasis (M)], systemic therapy (endocrine (tamoxifen or aromatase inhibitor (AI)) and chemotherapy), radiotherapy and surgery. Follow-up started at diagnosis of breast cancer and ended at time of event (recurrence/death) or censoring (end of follow-up or, for the recurrence analysis, also death). For all-cause mortality, we censored at 10 years because this is the threshold at which most breast cancers are, by convention, considered cured in the absence of recurrence or death. We adopted a two-step approach in our survival analyses. In the first step, each of the above risk factors was modeled separately in basic models adjusted for standard prognostic factors separately for each tumor subtype. To test for heterogeneity in risk factor and survival relationships by subtype, we included an interaction term between each risk factor and tumor subtype. Violation of the proportionality assumption of the hazard model was tested by modeling each risk factor as a time-varying covariate. In the second step, it was decided, a priori, that factors that were associated with survival with P <  0.1 in the basic model were to be mutually adjusted for in a multivariable model that included the standard prognostic factors mentioned above. Using likelihood ratio (LR) test, we compared this model with one containing only the clinicopathological factors. For sensitivity analysis, we conducted survival analysis for women stratified into two age groups (< 50 yrs and ≥ 50 yrs). Also, we performed additional sensitivity analysis by excluding women with stage IV disease from our multivariate analyses for both all-cause mortality and recurrence. Results were very similar from these sensitivity analyses as compared to analyses including all women and we therefore presented results from all patients. All analyses were two-sided and performed using Stata statistical software version 14.0 (StataCorp, College Station, TX, USA).

Results

In total, our analysis included 3012 invasive breast cancer cases, with a total of 579 deaths in 10 years and 314 recurrence events in 5 years. The mean age at diagnosis was 52 years and mean BMI was 25 kg/m2. The majority of the patients were Chinese (48%) and had early-stage (I and II, 56%) and HR-positive (66%) tumors (Table 1). Of the 3012 patients, 1016 (34%) were luminal A-like, 989 (33%) were luminal B-like, 387 (13%) were HER2-enriched, and 620 (20%) were triple-negative, respectively.

Table 1.

Distribution of risk factors and clinicopathological characteristics by tumor subtype

Characteristic Overall (%) A-like (N = 1016/34%) % B-like (N = 989/33%) % HER2-enriched (N = 387/13%) % Triple-neg. (N = 620/20%) % P valuea
Age, yrs
 Mean (range) 51.6 (19, 91) 52.6 (24–90) 51.1 (19, 90) 51.6 (23, 91) 51.5 (21, 87)
  < 35 180 (5) 47 4.6 49 5.0 26 6.7 40 6.5 0.01
 35–45 711 (21) 192 18.9 219 22.1 76 19.7 144 23.2
 45–55 1204 (36) 368 36.2 366 37.0 136 35.1 203 32.7
 55–65 806 (24) 241 23.7 246 24.9 105 27.1 143 23.1
 65–75 364 (11) 135 13.3 90 9.1 35 9.1 65 10.5
  > 75 90 (3) 33 3.3 19 1.9 9 2.3 25 4.0
Ethnicity
 Chinese 1626 (48) 567 55.8 435 44 180 46.5 275 44.4 < 0.0001
 Malay 801 (24) 204 20.1 263 26.6 104 26.9 155 25
 Native 928 (28) 245 24.1 291 29.4 103 26.6 190 30.6
Menarche
  ≤ 12 yrs 1105 (33) 344 34.1 326 33.2 118 30.8 190 30.9 0.20
 13 yrs 1117 (34) 318 31.5 340 34.7 148 38.6 201 32.7
 14 yrs 548 (16) 163 16.2 167 17 60 15.7 111 18
  ≥ 15 yrs 559 (17) 184 18.2 148 15.1 57 14.9 113 18.4
Menopause
  ≤ 50 yrs 428 (29) 146 32.7 128 29.7 38 23.2 87 31.6 0.14
  > 50 yrs 1031 (71) 301 67.3 303 70.3 126 76.8 188 68.4
Parity
 Nulliparous 745 (22) 242 23.8 224 22.6 77 19.9 128 20.6 0.29
 Parous 2601 (78) 774 76.2 765 77.4 310 80.1 492 79.4
Age at FFPb, yrs
  < 21 466 (18) 116 15 158 20.7 54 17.4 95 19.3 0.02
 21–24.9 1011 (39) 284 36.7 287 37.5 129 41.6 199 40.5
 25–30 864 (33) 275 35.5 248 32.4 103 33.2 154 31.4
  > 30 259 (10) 99 12.8 72 9.4 24 7.7 43 8.7
Breastfeeding
 No 377 (14) 133 17.2 103 13.5 31 10 64 13 0.01
 Yes 2224 (86) 641 82.9 662 86.5 279 90 428 87
Breastfeeding duration
  < 6 months 927 (52) 285 54.2 280 51.8 111 49.6 175 51.3 0.40
 6–10 months 374 (21) 112 21.3 122 22.6 48 21.4 62 18.2
  > 10 months 489 (27) 129 24.5 138 25.6 65 29.0 104 30.5
BMI, kg/m2
  < 18.5 1253 (39) 373 37.8 336 35.1 163 43.7 240 40.2 0.03
 18.5–24.9 565 (17) 160 16.2 172 18 68 18.2 114 19.1
 25–29.9 998 (31) 317 32.2 301 31.4 104 27.9 177 29.6
  ≥ 30 433 (13) 136 13.8 148 15.5 38 10.2 66 11.1
Family history
 No 2835 (86) 840 84 854 87.8 338 88 516 84.9 0.05
 Yes 468 (14) 160 16 119 12.2 46 12 92 15.1
Histological grade
 Well diff. 365 (11) 212 20.9 67 6.8 10 2.6 27 4.4 < 0.0001
 Moderately diff. 1790 (55) 781 76.9 442 44.7 180 46.5 238 38.4
 Poorly diff. 1123 (34) – – 473 47.8 192 49.6 344 55.5
Stage
 I 454 (14) 222 22.1 100 10.3 34 8.9 61 10 < 0.0001
 II 1353 (42) 444 44.2 395 40.6 136 35.6 249 40.9
 III 1005 (31) 241 24 330 33.9 150 39.3 203 33.3
 IV 421 (13) 78 7.8 139 14.3 57 14.9 91 14.9
Tumor size
  < 2 cm 2137 (64) 761 75.6 620 63.3 210 54.7 353 57.8 < 0.0001
 2–5 cm 522 (16) 121 12 150 15.3 83 21.6 104 17
  > 5 cm 660 (20) 125 12.4 209 21.4 91 23.7 154 25.2
Node status
 0 1517 (46) 566 55.7 368 37.2 146 37.7 272 43.9 < 0.0001
 1 922 (28) 249 24.5 310 31.3 95 24.5 163 26.3
 2 480 (15) 120 11.8 156 15.8 70 18.1 94 15.2
  ≥ 3 375 (11) 72 7.1 139 14.1 68 17.6 75 12.1
Endocrine
 None 1248 (40) 48 5.1 126 14.2 357 97.5 584 97.2 < 0.0001
 Tamoxifen 1456 (47) 687 72.9 591 66.7 7 1.9 15 2.5
 Aromatase Inhibitor 395 (13) 207 22.0 169 19.1 2 0.6 2 0.3
Chemotherapy
 No 799 (24) 371 37.3 177 18.3 62 16.4 95 15.5 < 0.0001
 Yes 2483 (76) 625 62.7 789 81.7 317 83.6 519 84.5
Surgery
 No 389 (12) 80 10.2 106 15.8 53 19.4 87 16.3 < 0.0001
 Yes 2841 (88) 913 89.8 833 84.2 312 80.6 519 83.7
Radiotherapy
 No 800 (26) 261 27.7 218 24.6 79 23.9 149 26.4 0.01
 Yes 2235 (74) 683 72.3 669 75.4 252 76.1 416 73.6
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Breast cancer subtypes were defined based on 2013 St Gallen criteria by using hormone receptor (ER and PR) and HER2 in conjunction with histologic grade. In bold are statistically significant P values (< 0.05)

aP values are for chi-square tests

bFFP first full-term pregnancy

Distribution of risk factors and clinicopathological characteristics by tumor subtype

As shown in Table 1, women with the luminal A-like subtype were slightly older than those with other subtypes. The distributions of ethnicity (P value < 0.001), age at FFP (P value = 0.019), breastfeeding practices (P value = 0.01), family history (P value = 0.05) and BMI (P value = 0.03) differed by subtype. No differences were observed in the distributions of age at menarche, age at menopause and parity according to subtype. The frequencies of all clinicopathological parameters differed by subtype, with low-grade, small, early-stage and node-negative tumors being more frequent for the luminal A-like subtype (Table 1).

Table 2 shows the associations between examined risk factors and molecular subtype in the multivariable polytomous regression model. Compared with women with the luminal A-like subtype, women with the luminal B-like, HER2-enriched and triple-negative tumors were significantly more likely to be Malay and Native than Chinese. Furthermore, women with other tumor subtypes were more likely to be parous and have breastfed [odds ratio (OR) (95% CI) parity and breastfeeding vs nulliparity = 1.44 (1.05, 1.98); 1.64 (1.06, 2.25); and 1.54 (1.07, 2.22) for luminal B, HER2-enriched and triple-negative subtypes, respectively] and less likely to experience their FFP after the age of 30 years [OR (95% CI) > 30 years vs < 21 years = 0.63 (0.42, 0.94); 0.57 (0.32, 1.02); and 0.58 (0.36, 0.93) for luminal B, HER2-enriched and triple-negative subtypes, respectively] than those with the luminal A-like subtype. Women with HER2-enriched [OR (95% CI) BMI > 30 kg/m2 vs 18.5–24.9 kg/m2 = 0.55 (0.34, 0.89); P value = 0.02] and triple-negative [OR (95% CI) BMI > 30 kg/m2 vs 18.5–24.9 kg/m2 = 0.59 (0.40, 0.88); P value = 0.01] tumors were significantly less likely to be obese than those with the luminal A-like subtype.

Table 2.

OR and 95% CI from a polytomous logistic regression model testing the associations between breast cancer risk factors and tumor molecular subtype

Risk factor Subtype
A-like (comparison group) B-like HER2-enriched Triple-negative
N N ORa (95% CI) N OR (95% CI) N OR (95% CI)
Ethnicity
 Chinese 567 435 1.00 (reference) 180 1.00 (reference) 275 1.00 (reference)
 Malay 204 263 1.50 (1.18, 1.90) 104 1.54 (1.13, 2.11) 155 1.51 (1.14, 1.98)
 Native 245 291 1.39 (1.10, 1.76) 103 1.21 (0.88, 1.66) 190 1.50 (1.15, 1.95)
 P value 0.001 0.10 < 0.001
Menarche
  ≤ 12 yrs 344 326 1.00 (reference) 118 1.00 (reference) 190 1.00 (reference)
 13 yrs 318 340 1.14 (0.91, 1.43) 148 1.31 (0.98, 1.77) 201 1.15 (0.88, 1.49)
 14 yrs 163 167 1.04 (0.79, 1.38) 60 1.02 (0.70, 1.48) 111 1.18 (0.86, 1.61)
  ≥ 15 yrs 184 148 0.83 (0.63, 1.10) 57 0.87 (0.59, 1.28) 113 1.10 (0.80, 1.50)
 P value 0.43 0.51 0.31
Parity and BFb
 Nulliparous 242 224 1.00 (reference) 77 1.00 (reference) 128 1.00 (reference)
 Parous and No BF 133 103 1.26 (0.84, 1.90) 31 1.07 (0.76, 1.52) 64 1.25 (0.77, 2.00)
 Parous and BF 641 662 1.44 (1.05, 1.98) 279 1.64 (1.06, 2.55) 428 1.54 (1.07, 2.22)
 P value 0.17 0.005 0.12
Age at FFPc
  < 21 yrs 116 158 1.00 (reference) 54 1.00 (reference) 95 1.00 (reference)
 21–24.9 yrs 284 287 0.78 (0.57, 1.05) 129 1.01 (0.67, 1.51) 199 0.90 (0.64, 1.26)
 25–30 yrs 275 248 0.77 (0.57, 1.06) 103 0.91 (0.60, 1.38) 154 0.77 (0.54, 1.09)
  > 30 yrs 99 72 0.63 (0.42, 0.94) 24 0.57 (0.32, 1.02) 43 0.58 (0.36, 0.93)
 P value 0.35 0.06 0.38
Family history
 No 840 854 1.00 (reference) 338 1.00 (reference) 516 1.00 (reference)
 Yes 160 119 0.72 (0.55, 0.94) 46 0.71 (0.49, 1.02) 92 0.92 (0.69, 1.23)
 P value 0.02 0.05 0.62
BMI, kg/m2
 18.5–24.9 160 172 1.00 (reference) 68 1.00 (reference) 114 1.00 (reference)
  < 18.5 373 336 0.89 (0.69, 1.17) 163 1.07 (0.76, 1.51) 240 0.96 (0.72, 1.29)
 P value 0.38 0.65 0.76
 25–29.9 317 301 0.86 (0.65, 1.12) 104 0.74 (0.51, 1.06) 177 0.75 (0.55, 1.02)
 P value 0.27 0.13 0.08
  ≥ 30 136 148 0.90 (0.65, 1.24) 38 0.55 (0.34, 0.89) 66 0.59 (0.40, 0.88)
 P value 0.62 0.02 0.01
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Statistically significant (P value < 0.05) estimates are indicated in bold

aOR and corresponding estimates are from a single polytomous logistic regression model that was mutually adjusted for ethnicity, menarche, parity and breastfeeding, age at FFP, family history, BMI and age

bBF breastfeeding

cFFP first full-term pregnancy

Breast cancer risk factors in relation to all-cause mortality and recurrence by subtype

Overall, all-cause mortality and recurrence differed significantly by tumor subtype. In general, women with luminal A-like tumors had better survival outcomes than those with the other subtypes (Fig. 1). As shown in Table 3, in basic models for each risk factor (with adjustment for standard prognostic factors in addition to age, ethnicity and BMI), later age at menarche, parity/breastfeeding, and being underweight were significantly associated with 10-year all-cause mortality in the luminal A-like but not any of the other subtypes. Also, later age at FFP showed a suggestive association with mortality in luminal A-like patients (P trend = 0.08) but not the other subtypes. Results were similar in basic models for recurrence (Table 4).

Fig. 1.

Fig. 1

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Kaplan-Meier curves for the associations between breast cancer molecular subtypes and (a) 10-year all-cause mortality (b) 5-year recurrence-free survival among 3012 women diagnosed and treated in Sarawak General Hospital, Sarawak Malaysia

Table 3.

HR and 95% CI for the associations between risk factors and 10-year all-cause mortality by tumor molecular subtype

Risk factor1a 10-year all-cause mortality P hetd
A-like B-like HER2-enriched Triple-negative
N/events HR (95% CI) N/events HR (95% CI) N/events HR (95% CI) N/events HR (95% CI)
Ethnicity
 Chinese 567/39 1.00 (reference) 435/41 1.00 (reference) 180/38 1.00 (reference) 275/57 1.00 (reference) 0.81
 Malay 204/17 1.23 (0.65, 2.34) 263/70 2.32 (1.49, 3.60) 104/29 1.11 (0.63, 1.96) 155/54 1.22 (0.79, 1.89)
 Native 245/19 1.04 (0.52, 2.05) 291/39 1.68 (1.02, 2.77) 103/20 0.93 (0.48, 1.79) 190/41 1.06 (0.67, 1.67)
 P value 0.80 0.03 0.87 0.77
Menarche
  ≤ 12 yrs 344/14 1.00 (reference) 326/52 1.00 (reference) 118/23 1.00 (reference) 190/46 1.00 (reference) 0.06
 13 yrs 318/26 1.53 (0.76, 3.11) 340/44 0.88 (0.55, 1.40) 148/29 0.84 (0.45, 1.57) 201/46 1.21 (0.76, 1.92)
 14 yrs 163/11 1.25 (0.54, 2.91) 167/27 0.86 (0.50, 1.48) 60/22 0.92 (0.47, 1.80) 111/26 1.05 (0.61, 1.80)
  ≥ 15 yrs 184/23 2.25 (1.06, 4.78) 148/27 0.84 (0.49, 1.42) 57/11 0.49 (0.21, 1.11) 113/31 0.89 (0.52, 1.55)
 P value 0.06 0.49 0.15 0.66
Parity and BFb
 Nulliparous 242/24 1.00 (reference) 224/36 1.00 (reference) 77/18 1.00 (reference) 128/40 1.00 (reference) 0.28
 Parous and No BF 133/10 0.59 (0.27, 1.32) 103/12 0.81 (0.37, 1.75) 31/8 0.87 (0.34, 2.25) 64/20 1.02 (0.52, 1.96)
 Parous and BF 641/41 0.46 (0.26, 0.81) 662/102 0.99 (0.64, 1.56) 279/61 0.61 (0.33, 1.14) 428/92 0.86 (0.55, 1.34)
 P value 0.009 0.91 0.11 0.48
Age at FFPc
  < 21 yrs 116/10 1.00 (reference) 158/32 1.00 (reference) 54/13 1.00 (reference) 95/19 1.00 (reference) 0.22
 21–24.9 yrs 284/14 0.99 (0.38, 2.55) 287/33 1.30 (0.75, 2.25) 129/28 0.83 (0.37, 1.84) 199/42 0.71 (0.39, 1.29)
 25–30 yrs 275/23 0.85 (0.41, 1.73) 248/39 1.14 (0.69, 1.90) 103/22 0.77 (0.40, 1.49) 154/41 0.98 (0.60, 1.60)
  > 30 yrs 99/4 0.36 (0.10, 1.29) 72/10 1.34 (0.64, 2.81) 24/6 0.78 (0.25, 2.46) 43/9 0.53 (0.23, 1.24)
 P value 0.08 0.92 0.15 0.58
Family history
 No 840/56 1.00 (reference) 854/131 1.00 (reference) 338/73 1.00 (reference) 516/122 1.00 (reference) 0.25
 Yes 160/17 1.70 (0.93, 3.08) 119/17 1.05 (0.59, 1.88) 46/13 1.47 (0.76, 2.82) 92/22 0.77 (0.46, 1.27)
 P value 0.08 0.86
BMI, kg/m2
 18.5–24.9 160/6 1.00 (reference) 172/25 1.00 (reference) 68/15 1.00 (reference) 114/25 1.00 (reference) 0.80
  < 18.5 373/38 3.42 (1.20, 9.71) 336/43 1.06 (0.62, 1.82) 163/37 0.83 (0.44, 1.57) 240/63 1.15 (0.70, 1.91)
 P value 0.02 0.83 0.58 0.56
 25–30 317/21 2.88 (0.97, 8.59) 301/49 1.30 (0.77, 2.20) 104/19 0.80 (0.39, 1.64) 177/40 0.92 (0.54, 1.57)
 P value 0.06 0.32 0.54 0.77
  > 30 136/7 1.30 (0.37, 4.52) 148/23 1.12 (0.61, 2.05) 38/10 1.23 (0.52, 2.90) 66/18 1.21 (0.63, 2.32)
 P value 0.68 0.71 0.63 0.57
Open in a new tab

In bold are variables which met our criteria (P value < 0.1) for inclusion in multivariate models

aEach risk factor was adjusted for age, ethnicity, BMI, tumor stage, histologic grade, surgery, systemic therapy (endocrine (tamoxifen or AI versus none), chemotherapy (any regimen versus none)) and radiotherapy (received versus none)

bBF breastfeeding

cFFP first full-term pregnancy

dP value for heterogeneity (P-het) of HR estimates according to molecular subtypes

Table 4.

HR and 95% CI for the associations between risk factors and 5-year recurrence by tumor molecular subtype

Risk factora Recurrence after 5 years P-hetd
A-like B-like HER2-enriched Triple-negative
N/events HR (95% CI) N/events HR (95% CI) N/events HR (95% CI) N/events HR (95% CI)
Ethnicity
 Chinese 567/34 1.00 (reference) 435/49 1.00 (reference) 180/30 1.00 (reference) 275/38 1.00 (reference) 0.96
 Malay 204/8 1.01 (0.39, 2.60) 263/30 0.81 (0.45, 1.45) 104/17 0.69 (0.31, 1.51) 155/24 1.11 (0.61, 2.02)
 Native 245/16 1.17 (0.49, 2.79) 291/22 0.84 (0.46, 1.55) 103/10 0.47 (0.18, 1.23) 190/22 0.67 (0.34, 1.34)
 P value 0.75 0.55 0.11 0.32
Menarche
  ≤ 12 yrs 344/13 1.00 (reference) 326/38 1.00 (reference) 118/14 1.00 (reference) 190/34 1.00 (reference) 0.07
 13 yrs 318/17 1.55 (0.57, 4.23) 340/31 1.03 (0.58, 1.82) 148/21 1.52 (0.69, 3.33) 201/24 0.72 (0.38, 1.37)
 14 yrs 163/14 2.51 (0.86, 7.33) 167/21 0.81 (0.40, 1.64) 60/9 0.56 (0.16, 1.92) 111/13 0.65 (0.30, 1.43)
  ≥ 15 yrs 184/13 3.26 (1.08, 9.92) 148/11 0.77 (0.35, 1.68) 57/12 1.11 (0.38, 3.28) 113/12 0.61 (0.27, 1.36)
 P value 0.02 0.41 0.81 0.18
Parity and BFc
 Nulliparous 242/19 1.00 (reference) 224/16 1.00 (reference) 77/12 1.00 (reference) 128/19 1.00 (reference) 0.56
 Parous and No BF 133/7 0.55 (0.20, 1.50) 103/14 1.86 (0.76, 4.56) 31/7 1.35 (0.39, 4.64) 64/17 1.57 (0.67, 3.66)
 Parous and BF 641/32 0.27 (0.12, 0.58) 662/71 1.63 (0.81, 3.28) 279/38 0.58 (0.25, 1.34) 428/48 0.77 (0.39, 1.52)
 P value 0.001 0.23 0.15 0.28
Age at FFPd
  < 25 400/13 1.00 (reference) 445/44 1.00 (reference) 183/30 1.00 (reference) 294/41 1.00 (reference) 0.52
  ≥ 25 374/26 1.69 (0.66, 4.34) 320/41 1.32 (0.78, 2.22) 127/15 0.50 (0.21, 1.16) 197/23 0.75 (0.41, 1.39)
 P value 0.27 0.28 0.10 0.36
Family history
 No 840/42 1.00 (reference) 854/85 1.00 (reference) 338/49 1.00 (reference) 516/66 1.00 (reference) 0.94
 Yes 160/13 0.77 (0.29, 2.03) 119/14 1.17 (0.60, 2.28) 46/7 1.24 (0.45, 3.35) 92/12 0.85 (0.43, 1.70)
 P value 0.60 0.64 0.67
BMI, kg/m2
 18.5–24.9 160/6 1.00 (referent) 172/14 1.00 (referent) 68/11 1.00 (referent) 114/16 1.00 (referent) 0.98
  < 18.5 373/30 3.97 (0.91, 17.34) 336/29 1.37 (0.62, 3.03) 163/21 0.50 (0.20, 1.27) 240/30 1.01 (0.51, 2.01)
 P value 0.06 0.43 0.15 0.97
 25–30 317/16 3.40 (0.75, 15.42) 301/37 2.02 (0.95, 4.29) 104/15 0.70 (0.27, 1.81) 177/24 0.83 (0.39, 1.73)
 P value 0.11 0.06 0.46 0.62
  > 30 136/5 1.65 (0.27, 10.15) 148/15 1.28 (0.53, 3.12) 38/7 1.41 (0.46, 4.27) 66/13 0.89 (0.35, 2.25)
 P value 0.59 0.58 0.55 0.81
Open in a new tab

In bold are variables which met our criteria (P-value < 0.1) for inclusion in multivariate models

aEach risk factor was adjusted for age, ethnicity, BMI, tumor stage, histologic grade, surgery, systemic therapy (endocrine (tamoxifen or AI versus none), chemotherapy (any regimen versus none)) and radiotherapy (received versus none)

bBF breastfeeding

cFFP first full-term pregnancy. Due to sample size considerations age at FFP was dichotomized

dP value for heterogeneity (P-het) of HR estimates according to molecular subtypes

In the multivariable model with the mutual adjustment for ethnicity, menarche, parity/breastfeeding, age at FFP, family history, and BMI in addition to standard clinicopathological factors and treatment variables, increasing age at menarche [hazard ratio (HR) (95% confidence interval (CI) ≥15 years vs ≤ 12 years = 2.28 (1.05, 4.95); P value for trend (P trend) = 0.06]; parity/breastfeeding [HR (95% CI) vs nulliparity = 0.48 (0.27, 0.85); P trend = 0.01]; older age at FFP [HR (95% CI) > 30 vs < 21 years = 0.20 (0.04, 0.90); P trend = 0.06]; and being underweight [HR (95% CI) vs normal weight = 3.46 (1.21, 9.89); P value = 0.02] or overweight [HR (95% CI) vs normal weight = 3.14 (1.04, 9.50); P value = 0.04] remained significantly associated with 10-year all-cause mortality in women with the luminal A-like subtype (Table 5 and Fig. 2). For these women, the addition of age at menarche, parity/breastfeeding, and BMI, provided significantly better fit to a model containing clinicopathological factors alone [LRχ2 (8df) = 21.78; P value = 0.005]. In general, the results were consistent in relation to recurrence (Table 5).

Table 5.

Multivariate HR and 95% CI for the association between breast cancer risk factors and 10-year all-cause mortality and 5-year recurrence among women with luminal A-like subtype breast cancer

Risk factor 10-year all-cause mortality 5-year recurrence
N/events HR1 (95% CI) N/events HRa (95% CI)
Ethnicity
 Chinese 539/38 1.00 (reference) 399/21 1.00 (reference)
 Malay 194/16 1.14 (0.59, 2.20) 154/7 0.81 (0.29, 2.27)
 Native 235/17 0.87 (0.41, 1.85) 190/11 0.90 (0.35, 2.29)
 P value 0.95 0.74
Menarche
  ≤ 12 yrs 338/13 1.00 (reference) 260/8 1.00 (reference)
 13 yrs 302/25 1.45 (0.70, 3.01) 235/13 1.69 (0.59, 4.81)
 14 yrs 156/10 1.23 (0.52, 2.92) 119/8 2.64 (0.87, 7.99)
  ≥ 15 yrs 172/23 2.28 (1.05, 4.95) 129/10 3.52 (1.10, 11.23)
 P value 0.06 0.02
Parity and BFb
 Nulliparous 229/23 1.00 (reference) 180/15 1.00 (reference)
 Parous and No BF 127/9 0.61 (0.26, 1.42) 87/5 0.53 (0.17. 1.59)
 Parous and BF 612/39 0.48 (0.27, 0.85) 476/19 0.28 (0.13, 0.64)
 P value 0.01 0.002
Age at FFPc
  < 21 yrs 111/9 1.00 (reference) 85/4 1.00 (reference)
 21–24.9 yrs 276/14 0.85 (0.31, 2.31) 220/4 0.40 (0.06, 2.28)
 25–30 yrs 262/22 0.71 (0.27, 1.82) 201/17 1.26 (0.30, 5.22)
  > 30 yrs 95/4 0.20 (0.04, 0.90) 73/1 0.26 (0.02, 3.09)
 P value 0.06 0.95
Family history
 No 804/53 1.00 (reference) 629/31 1.00 (referent)
 Yes 155/17 1.68 (0.91, 3.10) 122/7 0.75 (0.28, 2.02)
 P value 0.10 0.57
BMI
 18.5–24.9 kg/m2 160/6 1.00 (reference) 117/2 1.00 (reference)
  < 18.5 kg/m2 365/37 3.46 (1.21, 9.89) 285/22 4.31 (0.94, 19.83)
 P value 0.02 0.06
 25–29.9 kg/m2 310/21 3.14 (1.04, 9.50) 235/12 4.74 (1.00, 22.64)
 P value 0.04 0.05
  ≥ 30 kg/m2 133/7 1.38 (0.39, 4.86) 106/3 2.16 (0.34, 13.78)
 P value 0.61 0.41
Open in a new tab

In bold are statistically significant estimates (P value < 0.05)

aHR was mutually adjusted for ethnicity, menarche, parity and breastfeeding, age at FFP, family history, BMI, age, TNM stage, histologic grade, surgery, systemic therapy (endocrine (tamoxifen or AI versus none), chemotherapy (any regimen vs and radiotherapy (received versus none)

bBF breastfeeding

cFFP first full-term pregnancy

Fig. 2.

Fig. 2

Open in a new tab

Survival curves for the multivariate association between (a) age at menarche, (b) parity and breastfeeding and (c) BMI and 10-year all-cause mortality among 1016 women with the luminal A-like subtype of breast cancer

When we examined the association between duration of breastfeeding and all-cause-mortality/recurrence for luminal A-like cases with complete information on breastfeeding duration (N = 719), we observed an inverse association between each breastfeeding duration category and all-cause mortality [HR (95% CI) vs nulliparity = 0.37 (0.18, 0.85), 0.86 (0.35, 2.11), 0.53 (0.24, 1.17) for < 6, 6–10, and > 10 months, respectively (P trend = 0.38)] and recurrence [HR (95% CI) vs nulliparity = 0.47 (0.19, 1.16), 0.73 (0.23, 2.37), 0.05 (0.01, 0.42) for < 6, 6–10, and > 10 months, respectively (P trend = 0.002)]. Among women who breastfed, all-cause mortality did not significantly vary by breastfeeding durations (comparing > 10 months to < 6 months, P value = 0.38) but women who breastfed for > 10 months tended to have better recurrence outcomes [HR (95% CI) vs < 6 months = 0.11 (0.01, 0.93); P value = 0.04].

Discussion

In this study involving over 3000 invasive breast cancer cases from a population-based case series in Sarawak, Malaysia, with detailed demographic, risk factor, pathology, and follow-up data, we investigated several established breast cancer risk factors in relation to tumor subtypes and patient outcomes. We found differences in the prevalence of parity and breastfeeding, age at FFP, family history of breast cancer and obesity across different breast tumor subtypes. In general, traditional breast cancer risk factors (older age at FFP, higher BMI, lower parity, lack of breastfeeding) seem to show higher frequencies among women with the luminal A-like subtype compared with women with other subtypes. Further, we found that age at menarche, breastfeeding, and BMI were independent prognostic factors for both overall mortality and breast cancer recurrence but only for women with the luminal A-like subtype, which had better survival and recurrence outcomes than the other subtypes.

Our findings that nulliparity and older age at FFP were more prevalent in luminal A-like patients are consistent with those reported in studies in Western countries [16, 27]. However, unlike the observation of higher BMI and shorter breastfeeding duration in triple-negative patients among Western, especially African American, women [18, 19, 28, 29], we found lower frequencies of obesity and breastfeeding among HR− (HER2-enriched and triple-negative) than luminal A-like tumors, which may be reflective of population/ethnic differences. In line with this hypothesis, a previous study conducted in South Korea [30] also showed a higher frequency of breastfeeding among women with luminal B or HER2-enriched than those with luminal A disease. In another study involving 730 Mexican women with breast cancer, Martinez and colleagues [31] reported the prevalence of breastfeeding to be higher among women with triple-negative than luminal A tumors. Similarly, results from a multiethnic study showed an inverse association between triple-negative tumors and breastfeeding in White, Hispanic and African American but, notably, not in Asian women, for whom breastfeeding for > 2 months was associated with an 86% increased likelihood of triple-negative tumors [32].

The prevalence of obesity is still much lower in most Asian populations compared with other race/ethnicity groups. In contrast to the reduced breast cancer risk associated with higher BMI among premenopausal Western women, obesity is associated with increased risk for both premenopausal and postmenopausal Asian women [33–35]. The heterogeneity of obesity by tumor subtype among Asian cases remains unclear. Results from both our study and the South Korean study [30] suggest that obesity was less frequent among patients with HER2-enriched tumors. In combination with our finding that women with the HER2-enriched subtype were more likely to be parous and to have breastfed than women with the luminal A-like subtype, our data suggest that these factors (parity, breastfeeding, and low BMI) may not protect against HER2-enriched breast cancers. The decreasing prevalence of these factors associated with the adoption of westernized lifestyles may, therefore, not affect the incidence of this subtype, which is known to be more prevalent among Asian women [36, 37]. More research to understand the risk factors associated with the HER2-enriched subtype is warranted.

Most epidemiological studies considering the prognostic significance of age at menarche in breast cancer have treated the disease as a homogeneous entity, and results from these studies are largely conflicting [1–3, 8, 38]. We found that older age at menarche was associated with worse prognosis but only among women with the luminal A-like subtype. This finding is consistent with results from a previous study of women in East Asia [20] that also evaluated relationships between risk factors and survival according to subtypes. It is unclear why late menarche and younger age at FFP lead to worse survival outcomes in women with the luminal A-like subtype since they are well known protective factors in terms of breast cancer risk. One possibility is that because early menarche and late age at FFP increase breast cancer risk through prolonged and sustained exposure of the mammary epithelium to the mitogenic effects of reproductive hormones [39, 40], these factors predispose more strongly to HR+ tumors which have better prognosis than HR− tumors [18, 41]. Although this association was confined to the luminal A-like subtype, which, by definition, is HR+, expression of hormone receptors in tumors occurs in a spectrum. Whereas some tumors have very high expression levels, others have lower levels despite crossing the threshold for consideration as HR+. Due to differences in cumulative lifetime exposure to endogenous estrogens, luminal A-like tumors occurring among women with late menarche may have lower levels of hormone receptor expression, hence worse survival/recurrence outcomes, than those occurring among women with early menarche. Indeed, this is consistent with the finding by Song et al. that longer duration of endogenous estrogen exposure was associated with better survival [30]. On the other hand, late menarche and early age at FFP may be indicative of lower socioeconomic status (SES) which, in turn, may be reflective of less exposure to “westernized” environments/lifestyles. Nonetheless, adjustment of known surrogates for SES did not change the associations between these factors and survival. That late age at menarche and early age at FFP were not associated with survival/recurrence in the other subtypes may be due to the masking effect of other more aggressive tumor features, which are inherent in these subtypes.

Our findings of breastfeeding being associated with better outcomes are generally consistent with previous reports [2, 12, 42]. A distinctive feature of luminal A-like tumors defined in our analysis is the low levels of proliferation, indicated by low histologic grade. Findings from one previous study showed that the protective effect of breastfeeding on breast cancer mortality was stronger for tumors with low expression of proliferation genes [21]. In our study, breastfeeding was associated with a preponderance of lobular carcinoma and small size tumors, both of which are highly correlated with low levels of proliferation [43–45].

Results from several studies, summarized in two comprehensive reviews and meta-analyses [46, 47], are supportive of the prognostic value of BMI in breast cancer. The association between BMI and survival after breast cancer is thought to be U-shaped [47–49], with underweight and overweight/obese women more likely to suffer worse survival outcomes than their normal weight counterparts. In our study, being underweight and overweight, but not obese, were suggestively associated with worse prognosis, but this might be due to the low frequency of obesity in this population (13%). Compared with overweight/obesity, the effect of underweight in breast cancer survival is less well-studied. Overall, our finding of an association between underweight and worse survival outcomes in breast cancer is in line with those of several other studies involving Asian populations [49–52]. Whilst insulin resistance, chronic inflammation, and altered adipokine and cytokine production have been proposed to underlie the obesity-cancer link [53], the precise mechanisms underpinning the relationship between underweight BMI and disease progression are not well understood. Chronic, pre-diagnostic, malnutrition may contribute to weight loss in cancer patients and may independently influence outcomes in the disease. However, when we examined the impact of indicators of socioeconomic deprivation, as surrogates for chronic malnutrition, our estimates remained unchanged.

Strengths of this study include: a population-based breast cancer case series in an understudied Asian population and the collection of detailed questionnaire information, which allowed us to account for various confounding variables including sociodemographic factors. Several limitations of this study should be noted. First, we did not include controls in our study and therefore our case-case comparisons could not be translated into relative risk estimates. Second, relatively small sample sizes for some of the subtypes may have affected our power to detect significant associations. Third, data on the specific cause of death were not available and, therefore, we only evaluated risk factors in relation to all-cause, but not breast cancer-specific, mortality even though some of the risk factors, such as BMI, are important predictors of death from other causes [54]. Nonetheless, the consistency of our results for all-cause mortality and for breast cancer recurrence indicate that these factors may contribute to breast cancer-specific mortality in a similar manner.

Conclusions

In conclusion, our data indicate that risk factors for breast cancer are differentially associated with tumor subtypes and exert subtype-specific influence on survival/recurrence from the disease. Specifically, we observed that menarche after the age of 15 years, FFP after 30 years, underweight or overweight BMI, and breastfeeding practices were associated with survival/recurrence only among women with luminal A-like tumors. These findings are supportive of the prognostic value of reproductive and lifestyle-related factors in tumors with biologically favorable profiles, and could have implications for clinical counseling and for the development of subtype-specific prognostic tools. Future prospective studies are needed to delineate the role of lifestyle modification, especially changes in BMI, in improving clinical outcomes for women with luminal A-like breast cancer.

Acknowledgements

The authors acknowledge Julie Buckland and Jane Demuth at Information Management Systems for data management support.

Funding

This research was supported by the Intramural Research Program of the National Institutes of Health, National Cancer Institute, Division of Cancer Epidemiology and Genetics.

Availability of data and materials

The datasets used and analyzed for the current study will be available from the corresponding author upon reasonable request.

Abbreviations

ACM

All-cause mortality

BMI

Body mass index

CI

Confidence interval

ER

Estrogen receptor

FFP

First full-term pregnancy

HER2

Human epidermal growth factor receptor 2

HR

Hazard ratio

IHC

Immunohistochemical

KM

Kaplan-Meier

LR

Likelihood ratio

OR

Odds ratio

PR

Progesterone receptor

Authors’ contributions

MA, HS, and XRY conceived the study design and analytical concept. MA performed statistical analyses and drafted the manuscript. HS, RMP, and XRY contributed to the interpretation of results and the critical revision of the manuscript. DBCR and TST contributed to the acquisition of patient information and pathology data. JG helped with data management. All authors participated in the revision of the manuscript and approved the final manuscript.

Ethics approval and consent to participate

All study participants provided written informed consent and the project was approved by the Ethics Committee of the National Institutes of Health, Malaysia. The study was also exempted from review by the Office of Human Subject Research Protections at the National Institutes of Health since NIH investigators do not have the access to the personal identifying information.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Mustapha Abubakar, Email: mustapha.abubakar2@nih.gov.

Hyuna Sung, Email: hyuna.sung@cancer.org.

Devi BCR, Email: beenadevicr@gmail.com.

Jennifer Guida, Email: jennifer.guida@nih.gov.

Tieng Swee Tang, Email: tangtiengswee@gmail.com.

Ruth M. Pfeiffer, Email: pfeiffer@mail.nih.gov

Xiaohong R. Yang, Phone: 240-276-7226, Email: royang@mail.nih.gov

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The datasets used and analyzed for the current study will be available from the corresponding author upon reasonable request.

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