Journal Article Seer Cancer Statistics Review 1975-2013 National Cancer Institute

• Journal Listing
• J Natl Cancer Inst
• PMC4580552

J Natl Cancer Inst. 2014 May; 106(5): dju055.

US Incidence of Breast Cancer Subtypes Defined by Joint Hormone Receptor and HER2 Status

Received 2013 Jun 26; Revised 2013 Nov 22; Accepted 2014 February 10.

Supplementary Materials

Supplementary Data

GUID: 63183166-0699-4139-9487-B717A685C3EE

GUID: 3B39C07C-2503-4D73-9B7D-43E7D6C250DD

Abstruse

Background

In 2010, Surveillance, Epidemiology, and Stop Results (SEER) registries began collecting human epidermal growth factor two (HER2) receptor status for chest cancer cases.

Methods

Chest cancer subtypes defined by joint hormone receptor (HR; estrogen receptor [ER] and progesterone receptor [PR]) and HER2 status were assessed across the 28% of the US population that is covered past SEER registries. Age-specific incidence rates by subtype were calculated for non-Hispanic (NH) white, NH black, NH Asian Pacific Islander (API), and Hispanic women. Joint HR/HER2 status distributions past age, race/ethnicity, county-level poverty, registry, phase, Bloom–Richardson grade, tumor size, and nodal status were evaluated using multivariable adapted polytomous logistic regression. All statistical tests were ii-sided.

Results

Among case patients with known Hour/HER2 condition, 36810 (72.7%) were constitute to be HR⁺/HER2⁻, 6193 (12.2%) were triple-negative (HR⁻/HER2⁻), 5240 (10.3%) were HR⁺/HER2⁺, and 2328 (four.6%) were Hour⁻/HER2⁺; 6912 (12%) had unknown HR/HER2 status. NH white women had the highest incidence rate of the Hour⁺/HER2⁻ subtype, and NH black women had the highest rate of the triple-negative subtype. Compared with women with the HR⁺/HER2⁻ subtype, triple-negative patients were more likely to be NH black and Hispanic; Hour⁺/HER2⁺ patients were more likely to be NH API; and Hour⁻/HER2⁺ patients were more than probable to be NH black, NH API, and Hispanic. Patients with triple-negative, HR⁺/HER2⁺, and HR⁻/HER2⁺ breast cancer were ten% to 30% less probable to be diagnosed at older ages compared with Hour⁺/HER2⁻ patients and 6.iv-fold to xx.0-fold more than likely to present with loftier-grade disease.

Conclusions

In the futurity, SEER information can be used to monitor clinical outcomes in women diagnosed with different molecular subtypes of breast cancer for a large portion (approximately 28%) of the US population.

Several distinct molecular subtypes of breast cancer have been defined based on cistron expression patterns (1). Label of this heterogeneity has changed how patients with this complex malignancy are treated. The major subtypes of chest cancer are approximated past the joint expression of three tumor markers: estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor 2–neu (HER2), which are evaluated routinely because of their utility in guiding clinical care. Contempo findings indicate that immunohistochemical protein expression profiles are surrogates for intrinsic gene-derived expression profiles defining molecular breast cancer subtypes (two). The about common subtypes are hormone receptor (ER or PR) positive (i.east., ER⁺ or PR⁺), comprising the luminal A and luminal B subtypes. Luminal B cancers and two other subtypes, triple-negative tumors (ER⁻/PR⁻/HER2⁻ cancers, most of which are of the basal-like phenotype) and HER2− overexpressing tumors (ER⁻/HER2⁺), are known to be more clinically aggressive and have poorer prognoses compared with luminal A tumors (iii–5). A growing torso of evidence suggests that there are notable demographic differences across these subtypes. Triple-negative breast cancer has been shown to exist more than likely to occur among younger women and blackness women (six–11). The literature, however, is based largely on relatively small observational studies or confined to particular geographic regions (viii,9,12–xiv), with the exception of cancer registry data roofing the state of California (6,10,11). Information on HER2 status and its availability was collected on all breast cancer cases diagnosed in 2010 by the unabridged population-based Surveillance, Epidemiology, and End Results (SEER) program. This article presents the first report of nationally representative incidence rates for the major breast cancer subtypes based on joint ER/PR/HER2 status and an assessment of demographic and clinical differences across these subtypes using SEER data roofing an estimated 28% of the The states population (xv)

Methods

Study Population

This report used information from 17 population-based cancer registries that participate in the SEER plan (information from the Alaska Native registry were excluded, north = 57), together comprising approximately 28% of the total population of the U.s. (16). Women diagnosed with invasive breast cancer in 2010 were included in the assay. The year 2010 is the most recent year for which complete SEER data are available and is the commencement year for which information on HER2 status are bachelor (information on ER and PR condition accept been collected since 1990). Case patients diagnosed by autopsy or death certificate (n = 229) or with sarcomas of the breast (based on histology codes 8800, 8801, 8805, 8815, 8830, 8850, 8858, 8890, 8935, 8980, 8982, 8983, 9120, 9180, 9181, 9260) were excluded (north = 84). The terminal analytic set consisted of 57483 case patients.

All study information—including ER, PR, and HER2 status, demographic characteristics, and tumor stage and grade—were ascertained across SEER registries using standardized coding rules based on infirmary medical records and pathology reports. Additionally, area-level poverty data (percentage of persons living below the poverty variable) were derived from the 2000 US Census, based on county at diagnosis, and were used every bit a surrogate for socioeconomic status (SES). Cutpoints based on empirical research and policy relevance (17,xviii) were used to create three levels for this variable (ie, poverty <10.0% for high SES, 10%–19.99% for medium SES, and >xx% for low SES). The data on ER, PR, and HER2 status were recorded by the SEER program in the following categories: i) test non done, two) positive (+), 3) negative (−), four) deadline, v) test done but results missing, and half dozen) unknown. For each biomarker, the original six categories were combined into four categories: positive, negative, borderline, or unknown (Supplementary Table 1, bachelor online). Detailed coding instructions for all iii tumor markers tin can be found nether the collaborative stage data collection organisation (19). The HER2 variable used in the assay was based on a single summary derived variable created past the SEER program using 5 HER2-related site-specific factors from the Collaborative Phase data collection system. Details of the derived HER2 variable tin can be obtained from the SEER website (http://seer.cancer.gov/seerstat/databases/ssf/her2-derived.html).

ER and PR results were combined and analyzed jointly as hormone receptor (Hour) status. HR⁺ was defined as either ER⁺, PR⁺, or borderline (categories ii and 4); 60 minutes⁻ was defined equally both ER⁻ and PR⁻ (category 3); and unknown 60 minutes was defined as test non washed, test done but results missing, or unknown (categories i, five, and 6). Similarly, HER2 condition was defined as HER2⁺ (category two), HER2⁻ (category 3), and unknown HER2 (categories 1, iv, 5, and 6). Notation that case patients with borderline ER or PR status were treated as having ER⁺ or PR⁺ status (borderline ER: n = 62, 0.1%; borderline PR: n = 191, 0.3%), whereas case patients with borderline HER2 condition were treated equally having unknown HER2 status (borderline HER2: n = 1566, 2.7%). ER/PR borderline case patients were grouped with positive case patients considering recent guideline changes indicated that the borderline category most likely was classified every bit positive because lower cutoffs (such every bit 1%) were used for the ER/PR test, whereas cutoffs equally high as 10% had previously been used for determining ER/PR positivity (twenty). Using tumor subtype definitions based on joint ER/PR/HER2 status (vi,14,21), tumors were classified into four mutually exclusive categories: Hour⁺/HER2⁻; ER⁻/PR⁻/HER2⁻ (triple negative); HR⁺/HER2⁺; and 60 minutes⁻/HER2⁺. Details of how tumors with positive or negative expressions for ER/PR/HER2 were coded into the subtypes are presented in Supplementary Table 2 (bachelor online). The SEER*Stat software (22) includes a variable to facilitate the analysis of trends in breast cancer molecular subtypes. The derived HER2 variable or the breast cancer subtype variable can be obtained from the custom database with actress Collaborative Stage site-specific factors upon request from the following URL: http://seer.cancer.gov/seerstat/databases/ssf/.

Statistical Analysis

Age-specific incidence rates per 100000 women by breast cancer subtypes were calculated based on 5-year historic period categories using the SEER*Stat software (22). New intercensal population estimates released by the US Census Bureau were used as the denominators in generating rates (23). Standard errors and 95% confidence intervals (CIs) for rates were calculated using the Tiwari method (24). The historic period-specific rates were presented for four mutually exclusive race/ethnicity groups: non-Hispanic white (NH white), non-Hispanic black (NH black), non-Hispanic Asian Pacific Islander (NH API), and Hispanic.

Unordered polytomous logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals to quantify associations between breast cancer subtypes and various demographic and clinical factors. These included age at diagnosis (<fifty, 50–64, 65–74, ≥75 years), race/ethnicity (NH white, NH black, NH API, Hispanic), the American Joint Committee on Cancer'southward Cancer Staging Transmission (7th edition) (25) stage at diagnosis (I, 2, Three, 4), Bloom–Richardson tumor course (low, medium, loftier), and SEER registry. Considering of collinearity with stage, tumor size and lymph node status were non included with stage in the model. SAS version 9.3 statistical software was used to fit the unordered polytomous logistic regression (26). All odds ratios were adapted for race/ethnicity, age, stage, tumor grade, and SEER region and based on patients having consummate information for each of these covariables (ie, women missing data for one or more of these covariables were dropped from the regression assay; northward = 13980). All statistical tests were ii-sided.

Results

Among 2010 case patients with known HR/HER2 status, 36810 (72.seven%) were found to be HR⁺/HER2⁻, 6193 (12.2%) were triple-negative (60 minutes⁻/HER2⁻), 5240 (10.3%) were HR⁺/HER2⁺, and 2328 (iv.6%) were HR⁻/HER2⁺; 6912 (12%) of the example patients had an unknown Hour/HER2 status (Table 1). Subtype distributions varied by historic period, race/ethnicity, county-level poverty, stage, and form. Compared with HR⁺/HER2⁻ example patients (the well-nigh common subtype), those diagnosed with the other three subtypes were somewhat more likely to exist younger, belong to minority racial or indigenous groups, alive in counties with higher poverty levels, and have later phase and college Blossom-Richardson grade disease (Tabular array ane). Subtype distribution likewise varied by SEER registry. Cases with missing HR/HER2 condition tended to be black, Hispanic, older, and diagnosed with more advanced stage disease.

Table i.

Demographic and clinical characteristics of chest cancer subtypes in women with invasive breast cancer, SEER-xviii, excluding Alaska, 2010*

Characteristic	All case patients	Among case patients with known subtype (n = 50 571)†								Amid total case patients‡
		60 minutes+/HER2−		Triple-negative		HR+/HER2+		HR−/HER2+		Unknown subtype
	n = 57 483	n = 36 810	72.7%	due north = 6193	12.ii%	n = 5240	x.three%	n = 2328	4.half dozen%	n = 6912	12.0%
Demographic characteristics
Age at diagnosis, y
<50	11 949	6902	64.viii%	1616	xv.2%	1528	14.four%	599	five.half dozen%	1304	10.ix%
50–64	21 586	13 610	70.7%	2540	13.2%	2066	x.vii%	1032	5.4%	2338	x.8%
65–74	12 643	8641	77.8%	1151	10.four%	939	8.5%	382	three.four%	1530	12.1%
≥75	eleven 305	7657	80.ane%	886	9.iii%	707	7.4%	315	3.3%	1740	15.4%
Race/ethnicityβ
Non-Hispanic white	xl 744	27 165	75.5%	3850	x.7%	3532	9.eight%	1438	iv.0%	4759	eleven.7%
Non-Hispanic black	6007	3169	60.2%	1183	22.5%	598	11.4%	318	half-dozen.0%	739	12.3%
Non-Hispanic Asian Pacific Islander	4367	2748	71.1%	376	nine.7%	475	12.three%	265	6.ix%	503	xi.5%
Hispanic	5694	3361	68.2%	727	xiv.7%	564	eleven.4%	280	5.7%	762	xiii.iv%
County-level poverty 2000ǁ
High SES, poverty <10%	22 454	14 800	74.0%	2276	11.four%	2073	10.4%	859	four.3%	2446	10.nine%
Medium SES, poverty 10%–19.99%	xxx 611	19 389	72.4%	3359	12.six%	2739	10.2%	1284	4.8%	3840	12.5%
Low SES, poverty >xx%	4398	2608	69.1%	558	14.8%	427	11.3%	184	4.nine%	621	fourteen.one%
SEER registry
Atlanta, metropolitan	2094	1340	73.3%	233	12.8%	179	9.8%	76	4.two%	266	12.7%
Connecticut	3066	2101	76.1%	280	10.i%	282	x.2%	98	3.half dozen%	305	10.0%
Detroit, metropolitan	2899	1801	69.0%	410	15.7%	282	10.8%	118	four.5%	288	ix.9%
Greater California	12 852	8147	73.five%	1306	11.viii%	1110	10.0%	518	iv.7%	1771	xiii.8%
Hawaii	1070	750	75.i%	97	9.7%	101	10.1%	51	5.i%	71	six.6%
Iowa	2331	1584	74.1%	254	11.9%	193	ix.0%	106	5.0%	194	8.three%
Kentucky	3056	1963	72.2%	383	xiv.1%	248	9.i%	125	4.6%	337	11.0%
Los Angeles	5768	3634	71.7%	616	12.two%	575	eleven.four%	241	4.8%	702	12.ii%
Louisiana	3094	1759	67.viii%	407	15.7%	297	xi.5%	131	5.1%	500	16.two%
New Bailiwick of jersey	6627	4065	72.4%	667	eleven.9%	628	xi.ii%	258	iv.6%	1009	fifteen.2%
New Mexico	1266	738	74.9%	106	10.8%	101	10.ii%	41	4.two%	280	22.1%
Rural + greater Georgia	3973	2435	69.0%	503	fourteen.3%	404	11.five%	186	5.iii%	445	xi.2%
San Francisco–Oakland	3124	2114	75.8%	293	10.v%	256	ix.ii%	126	iv.five%	335	x.7%
San Jose–Monterey	1556	1043	74.0%	171	12.1%	142	10.1%	54	3.eight%	146	nine.four%
Seattle, Puget Sound	3439	2536	77.2%	304	9.3%	310	9.4%	136	four.i%	153	4.5%
Utah	1268	800	69.1%	163	14.1%	132	eleven.4%	63	five.4%	110	eight.vii%
Clinical characteristics
AJCC 7th stage¶
I	27 816	19 881	79.5%	2214	nine.0%	2115	8.4%	779	3.1%	2827	10.two%
Two	17 494	10 873	69.3%	2488	14.9%	1783	11.0%	776	4.eight%	1574	9.0%
III	6505	3705	62.six%	958	xvi.1%	803	13.6%	465	seven.8%	574	viii.eight%
4	3203	1532	61.2%	379	xv.ane%	370	14.viii%	223	8.nine%	699	21.8%
Unknown	2390	818	66.2%	152	13.five%	167	13.7%	80	half dozen.6%	1173	49.1%
Bloom–Richardson grade
Low grade	13 158	10 999	91.five%	356	three.0%	547	4.six%	124	1.0%	1132	8.six%
Medium course	twenty 562	15 561	82.iv%	967	5.1%	1847	ix.8%	508	two.7%	1679	8.2%
High grade	fourteen 157	5731	44.one%	3948	30.4%	2032	15.6%	1288	ix.ix%	1158	viii.2%
Unknown	9606	4519	67.8%	922	13.8%	814	12.2%	408	6.1%	2943	30.six%
Tumor size
<2.0 cm	30 763	21 852	79.0%	2463	eight.ix%	2424	8.8%	932	3.4%	3092	10.1%
ii.0–four.9 cm	xviii 614	eleven 231	66.8%	2677	15.9%	2015	12.0%	900	5.4%	1791	9.6%
≥5.0 cm	5036	2730	61.2%	817	xviii.3%	557	12.v%	355	8.0%	577	11.5%
Unknown	3070	997	61.half dozen%	236	14.6%	244	15.1%	141	viii.7%	1452	47.three%
Nodal status
Positive	xvi 085	10 185	69.05%	1875	12.71%	1800	12.20%	890	six.03%	1335	8.30%
Negative	32 891	22 321	74.91%	3592	12.05%	2771	9.30%	1115	3.74%	3092	9.40%
Unknown	8507	4304	71.47%	726	12.06%	669	11.eleven%	323	5.36%	2485	29.21%

Figure one shows age-specific female breast cancer incidence rates per 100000 by molecular subtype for four racial and indigenous groups. Incidence rates for HR⁺/HER2⁻ were higher than those for other subtypes across all racial/ethnic groups and all age groups (Figure i). NH white women had the highest charge per unit for this subtype, followed by NH blackness women, and and then NH API and Hispanic women. Racial and ethnic differences in Hour⁺/HER2⁻ rates peaked at 75 to 79 years of age, with higher rates among NH whites (342.7; 95% CI = 329.6 to 356.2), followed by NH blacks (236.8; 95% CI = 206.8 to 270), NH APIs (176.four; 95% CI = 150.8 to 205.1), and Hispanics (190.3; 95% CI = 165.four to 217.nine) (Supplementary Table 3, available online). NH black women had the highest incidence rates of triple-negative breast cancer across all age groups, with the departure in rates reaching its widest bespeak at ages 60 to 64 and 65 to 69 years, when NH black women were much more than likely to be diagnosed with this subtype than were the three other racial/ethnic groups. In particular, the tiptop triple-negative incidence rate among 65 to 69 year-former NH black women aged 65 to 69 years was 69.5 (95% CI = 57.5 to 83.iii), with lower rates among women of the aforementioned historic period in other racial and ethnic groups (eg, NH whites: 36.eight, 95% CI = 33.four to forty.four; NH APIs: 23.half dozen, 95% CI = 16.6 to 32.6; Hispanics: 28.8; 95% CI = 21.7 to 37.4). The HER2-overexpressing tumors (Hour⁺/HER⁺ and Hr⁻/HER2⁺) were less mutual subtypes with fewer observed variations by race/ethnicity compared with both the HR⁺/HER2⁻ and triple-negative subtypes.

Age-specific incidence rates of breast cancer subtypes by race/ethnicity, Surveillance, Epidemiology, and Finish Resulsts 18, excluding Alaska, 2010. The 95% confidence intervals for incidence rates are presented in Supplementary Table three (bachelor online). API = Asian Pacific Islander; HER = human being epidermal growth factor; HR = hormone receptor; NH = non-Hispanic.

Results from the polytomous logistic regression model are summarized in Tabular array 2. Based on the model results and using the HR⁺/HER2⁻ tumors equally the reference outcome and NH white every bit the reference covariable, NH blacks and Hispanics were more likely to be diagnosed with triple-negative (NH blacks: OR = two.0, 95% CI = 1.8 to 2.ii; Hispanics: OR = 1.3, 95% CI = one.2 to i.v) and Hour⁻/HER2⁺ breast cancer (NH blacks: OR = 1.iv, 95% CI = 1.2 to 1.vi; Hispanics: OR = ane.4, 95% CI = 1.2 to ane.vi); and NH APIs were less likely to be diagnosed with triple-negative tumors (OR = 0.8; 95% CI = 0.7 to 0.9) but more likely to exist diagnosed with both HR⁺/HER2⁺ and 60 minutes⁻/HER2⁺ tumors (OR = i.two, 95% CI = 1.one to 1.4; OR = 1.8, 95% CI = 1.5 to 2.ane, respectively) (Tabular array 2). Compared with patients with HR⁺/HER2⁻ chest cancer, those diagnosed with triple-negative, HR⁺/HER2⁺, and Hour⁻/HER2⁺ were 10% to thirty% less probable to be aged 65 to 74 or 75 years or older. This observation is consequent with the earlier historic period of onset seen in Figure 1. Triple-negative cancers had a like stage distribution compared with HR⁺/HER2⁻ cancers, but Hour⁺/HER2⁺ and, in detail, HR⁻/HER2⁺ tumors were more than likely to present at phase Iii or IV. Lastly, marked differences in tumor grade were observed across subtypes, with triple-negative, HR⁺/HER2⁺, and HR⁻/HER2⁺ tumors being 6.4-fold to twenty.0-fold more likely to be loftier class compared with Hr⁺/HER2⁻ tumors.

Table ii.

Adjusted odds ratios for patient and tumor characteristics by chest cancer subtypes, SEER-18, excluding Alaska, 2010*

Characteristics	Hr + /HER2 − †	Triple-negative				HR + /HER2 +				HR − /HER2 +
	n = 31 500	north = 5140				north = 4270				north = 1849
	% Case patients	% Case patients	Odds ratio‡ (95% CI)			% Case patients	Odds ratio‡ (95% CI)			% Case patients	Odds ratio‡ (95% CI)
Race/ethnicity
NH white (referent)	75	62	i.0			68	1.0			62	1.0
NH blackness	viii	xix	2.0 (1.8 to two.2)			eleven	1.2 (1.0 to i.3)			13	1.4 (1.2 to 1.6)
NH API	8	half dozen	0.8 (0.7 to 0.nine)			10	1.2 (1.i to 1.four)			12	1.8 (one.5 to two.i)
Hispanic	9	12	1.3 (i.2 to one.5)			eleven	ane.1 (ane.0 to 1.2)			12	1.4 (1.ii to 1.half-dozen)
Historic period at diagnosis, y
<50	19	26	i.0 (0.9 to1.1)			30	1.3 (1.2 to i.iv)			26	0.9 (0.viii to i.0)
50–64 (referent)	37	41	one.0			39	1.0			44	1.0
65–74	23	xix	0.9 (0.eight to 0.9)			18	0.8 (0.7 to 0.ix)			17	0.7 (0.6 to 0.8)
≥75	20	xiv	0.eight (0.7 to 0.9)			13	0.7 (0.6 to 0.viii)			fourteen	0.7 (0.6 to 0.eight)
AJCC 7th stage at diagnosis
I (referent)	51	38	1.0			43	i.0			36	1.0
II	31	42	1.1 (1.0 to one.2)			36	1.ane (1.0 to 1.1)			36	one.one (1.0 to one.2)
III	10	16	1.0 (0.9 to 1.1)			sixteen	one.ii (1.i to 1.4)			20	ane.6 (1.three to 1.8)
IV	3	5	1.0 (0.8 to 1.ii)			five	ane.4 (i.ii to ane.7)			eight	2.one (i.7 to two.6)
Bloom–Richardson grade
Depression (referent)	34	7	i.0			12	1.0			7	1.0
Medium	48	xviii	1.9 (1.7 to 2.one)			42	2.three (2.1 to two.five)			26	2.6 (2.1 to 3.2)
High	17	75	20.0 (17.eight to 22.5)			46	6.4 (5.8 to seven.1)			67	16.eight (13.nine to 20.5)

Given the large number of instance patients with missing data on Bloom–Richardson grade, we conducted sensitivity analyses that included an additional 6118 case patients with an unknown course. The simply observable differences observed were with respect to stage and the comparison of triple-negative to 60 minutes⁺/HER2⁻ example patients. Analyses adjusted for grade that included unknown form as a separate category showed that, compared with Hr⁺/HER2⁻ case patients, triple-negative tumor patients had an elevated risk of being diagnosed with both stage III (OR = one.2; 95% CI = i.1 to 1.three) and stage IV (OR = 1.two; 95% CI = one.1 to 1.4) disease. Analyses not adjusted for grade merely adjusted for all of the other covariables showed that, compared with 60 minutes⁺/HER2− example patients, triple-negative example patients had an elevated risk of being diagnosed with either stage 3 (OR = two.1; 95% CI = one.9 to 2.3) or stage 4 (OR = 2.0; 95% CI = ane.seven to 2.2) disease.

Discussion

This written report analyzed recently available data on HER2 status for breast cancer patients from SEER registries (based on 28% of the US population) to demonstrate differences in the occurrence of chest cancer subtypes, defined by ER, PR, and HER2 status. Previous studies carried out in observational studies (8,9,11,xiii,14) had limited ability to generalize results to the larger population, although data from California have been available and used for epidemiologic studies (6,10,11). The data presented here ostend the higher proportions of more aggressive breast cancer subtypes amongst younger, NH black, and Hispanic women and notable differences in clinical presentation across subtypes. Additional etiologic studies are recommended to better characterize contributors to historic period, racial, and ethnic differences in the occurrence of chest cancer subtypes.

Unlike the predominant subtype, HR⁺/HER2⁻, the proportion of women with the triple-negative, 60 minutes⁺/HER2⁺, and 60 minutes⁻/HER2⁺ subtypes decreased with advancing age such that, although these three comparison groups comprised 35% of instance patients aged less than 50 years, they represented only twenty% of case patients among women anile 75 years or older. This is consequent with the patterns seen in California (5,6,10,11). These patterns are straight relevant to individualized handling decisions that influence clinical outcomes (27). Biological factors contributing to these differences are non completely understood. Among BRCA1 carriers, who usually develop chest cancer at a young age, the vast majority are diagnosed with the triple-negative subtype (28). These mutations are rare, however, and account for a low attributable fraction of triple-negative case patients. Farther etiologic studies are needed to more than completely characterize contributors to these differences.

NH blackness women were twice as likely to be diagnosed with triple-negative chest cancer compared with NH whites, and Hispanics were 30% more likely to be diagnosed with triple-negative chest cancer than NH whites. This ascertainment is consistent with existing literature indicating a disproportionate brunt of triple-negative disease in these populations, with several studies having documented this amongst black women (29,30) and amid Hispanic women (31). Like to the unique historic period-specific pattern of triple-negative subtypes, the etiologic basis for unlike racial and ethnic patterns remains unclear. NH black, NH API, and Hispanic women also were more likely to be diagnosed with Hr⁻/HER2⁺ breast cancer compared with NH white women, with NH API women having the highest take chances. Footling is known almost the basis for these differences given the lower frequency of these Hr⁻/HER2⁺ cancers, and studies that take explored their etiologies and gamble factors take been hampered by small-scale sample sizes. Looking advisedly at private risk factors such as reproductive history, lactation, weight, physical activity, mammography, postmenopausal hormone use, and longevity could explain the apparent differences in the diagnosis of breast cancer subtypes by race and ethnicity in SEER areas (32).

These information besides suggest some hitting differences in stage and course by chest cancer subtype. Using HR⁺/HER2⁻ as the comparing group in these analyses, niggling deviation was found in the stage distribution of triple-negative example patients, unlike prior studies (29,33); however, triple-negative instance patients were essentially more probable to accept high-grade cancer (17% vs 75%) (Table 2). Although the divergence in class is well described (8,12,xiii) after decision-making for phase, prior studies likewise found that triple-negative tumors were more probable to present at an advanced stage (2,6,11). The higher proportion of advanced stage and loftier-grade tumors among Hour⁺/HER2⁺ and HR⁻/HER2⁺ case patients too has been reported previously and is consistent with the known aggressiveness of these tumor subtypes compared with HR⁺/HER2⁻ affliction (4,eight,13,fourteen).

It is important to admit the limitations of this study. The starting time limitation relates to missing data for ER, PR, and HER2 condition. Although the proportion of example patients missing ER and PR status was low (5.4% and six.one%, respectively), 8.eight% of case patients had missing HER2 data (which led to an overall 12% of case patients missing molecular subtypes). The missing HER2 data were not entirely random but varied past age, stage, race/ethnicity, county-level SES, and registry. The magnitude and direction of potential biases introduced past the missing data are unknown. However, it is likely to differentially underestimate incidence rates by subtypes presented in this article and may also contribute to the observed lack of association between advanced-stage and triple-negative chest cancer. Multiple imputation methods have been used in previous studies (34,35) of SEER data to correct for missing ER status. Still, we did non impute missing HER2 status for this analysis because nosotros felt survival time would exist an important predictor for missing HER2 observations, which is consequently not available to account for in the imputation model. The second limitation involves possible variations in laboratory techniques for testing biomarkers beyond multiple hospitals that might exist expected in a population-based sample. Third, the information presented here are express to a single diagnosis year, which may lend some inherent instability to the incidence rates observed, particularly for rarer subtypes. Thus, continued monitoring of subtypes is needed, both within population subgroups and over fourth dimension. Finally, we acknowledge that there are different approaches to categorizing breast cancer case patients based on Hour and HER2 status in the literature; nosotros used the existing HR and HER2 information to best categorize chest cancers that approximate the subtypes of luminal A, luminal B, triple-negative, and HER2-overexpressing tumors (1).

In summary, this written report provides large-scale, population-based estimates of incidence rates of chest cancer subtypes divers by ER, PR, and HER2 status in the United States. There were marked differences in the incidence of these subtypes by age and race/ethnicity. These findings have both clinical and public health implications given differences in available treatments and risks of recurrence and mortality by subtype. For example, ER⁻ breast cancers are twice every bit likely to be missed past mammographic screening compared with ER⁺ chest cancers (36). Furthermore, no targeted therapeutic agents currently are bachelor for triple-negative breast cancer. Finally, triple-negative, ER⁺/HER2⁺, and ER⁻/HER2⁺ breast cancers carry a higher risk of mortality compared with ER⁺/HER2⁻ tumors. Understanding of the biological basis for differences in breast cancer subtype incidence and mortality rates across population groups is limited and warrants continued intensive study. SEER information can serve in the futurity to monitor clinical outcomes in women with different molecular subtypes of breast cancer.

Funding

Surveillance Enquiry Program, Segmentation of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Wellness contracts with SEER registries.

Supplementary Material

Acknowledgments

The authors give thanks SEER registries at the following locations: Atlanta, Connecticut, Detroit, Hawaii, Iowa, New United mexican states, San Francisco‐Oakland, Seattle‐Puget Audio, Utah, Los Angeles, San Jose‐Monterey, Rural Georgia, Alaska, Greater California, Kentucky, Louisiana, New Jersey, and Greater Georgia. The authors would besides like to thank Drs. William F. Anderson of the Sectionalisation of Cancer Epidemiology and Genetics (DCEG) and Linda C. Harlan of the the Division of Cancer Control and Population Sciences (DCCPS) for providing a very helpful review of the manuscript.

Notes

Findings and conclusions are the authors' and do non necessarily represent the official positions of their affiliations, or those of the National Cancer Institute, the National Institutes of Wellness, or the US Section of Wellness and Homo Services.

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