Next Article in Journal
Correlation of Optical Coherence Tomography Angiography Characteristics with Visual Function to Define Vision-Threatening Diabetic Macular Ischemia
Previous Article in Journal
Performance Evaluation of a Rapid Antigen Test (RAT) during Omicron Pandemic Wave in Greece, Conducted by Different Personnel, and Comparison with Performance in Previous Wave (Alpha Variant) Period
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Diagnostics
Volume 12
Issue 5
10.3390/diagnostics12051049
diagnostics-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Regional Lymph Node Metastasis and Axillary Surgery of Microinvasive Breast Cancer: A Population-Based Study

by
Jiamei Chen
1,†,
Bo Luo
2,†,
Mengting Gao
3,†,
Gaoke Cai
1,
Xixi Luo
1,
Yutian Zhang-Cai
1,
Shaobo Ke
1,* and
Yongshun Chen
1,*
1
Center of Oncology, Renmin Hospital of Wuhan University, Wuhan 430060, China
2
Department of Pathology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430014, China
3
Center of Information, Renmin Hospital of Wuhan University, Wuhan 430060, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Diagnostics 2022, 12(5), 1049; https://doi.org/10.3390/diagnostics12051049
Submission received: 14 March 2022 / Revised: 15 April 2022 / Accepted: 18 April 2022 / Published: 21 April 2022
(This article belongs to the Section Pathology and Molecular Diagnostics)
Browse Figures
Versions Notes

Abstract

:
Microinvasive breast cancer (MBC for short) is a rare entity with the decision of axillary surgery under debate in clinical practice. We aimed to unravel the lymph node metastasis (LNM) rate, axillary surgery, and prognosis of MBC based on 11,692 patients derived from the Surveillance Epidemiology and End Results (SEER) database between 2003 and 2015. In this retrospective study, 19.5% (2276/11,692) of patients received axillary lymph node dissection (ALND), 80.5% (9416/11,692) received non-ALND. In the total cohort, 10-year breast cancer-specific survival (BCSS) was 96.3%, and the LNM rate was 6.4% (754/11,692). Multivariate analyses showed that LNM had the strongest predictive weight (N3, HR 14.200, 95% CI 7.933–25.417; N2, HR 12.945, 95% CI 7.725–21.694; N1, HR 3.05, 95% CI 2.246–4.140, all p < 0.001). Kaplan–Meier analyses showed that ALND did not confer a survival benefit on 10-year BCS in patients with N0 (94.7% vs. 97.1%, p < 0.001) and in patients with 1–2 positive nodes (92.1% vs. 89.5%, p = 0.355), respectively, when compared to non-ALND. Our study demonstrated that the vast majority of MBC have a low LNM rate and excellent prognosis; patients with LNM showed poor prognosis. Assessment of lymph node status is necessary, and non-ALND surgery is required and sufficient for MBC with 0–2 positive nodes.

1. Introduction

Breast cancer (BC) is a highly heterogeneous disease with various pathological and molecular subtypes [1]. Microinvasive breast cancer (MBC for short) is a rare subtype of BC with clinicopathological characteristics needing further elucidation [2]. It is defined as ductal carcinoma in situ (DCIS) with one or more foci of tumor cells extending beyond the basement membrane, and no focus is larger than 1 mm in max diameter [3]. Though it has been classified as pT1mi that belongs to T1 in the American Joint Committee on Cancer (AJCC) staging system, the decision of axillary surgery and adjuvant therapy for MBC is under debate in clinical practice [2,4,5]. Whether MBC should be managed similarly to pure DCIS or invasive BC remains an open question, particularly for axillary staging. Because regional lymph node status is a stronger predictor of adverse outcomes and critically impacts subsequent treatment decisions.
The latest meta-analysis showed that MBC with the lymph node macrometastases rate of 2% had similar survival to DCIS and suggested that routine axillary staging may be an unnecessary intervention that does not change the management of MBC [6]. Sentinel lymph node biopsy (SLNB), a minimal invasion method that has comparable accuracy with axillary lymph node dissection (ALND), has become the mainstay in axillary staging for early breast cancer [7]. Magnoni et al. [8] reported that MBC had a favorable long-term survival and suggested that even SLNB in MBC may not be applicable. However, some researchers underline the impact of microinvasion on survival and suggest that MBC may have more aggressive pathologic features than DCIS and needs axillary staging [4,9,10], especially for younger patients with SLN metastases [11].
In terms of the inconsistent findings, our retrospective study supplements the existing research on regional lymph node metastasis (LNM) incidence, axillary surgery, and prognosis of MBC based on 11,692 patients pooled from the Surveillance Epidemiology and End Results (SEER) dataset.

2. Patients and Methods

2.1. Database and Patients

This retrospective study was based on the 18 Registries Incidence-SEER Database (November 2020 submission) of the National Cancer Institute, which collects incidence, clinicopathological features, treatment, and outcomes data from 18 cancer registries in the United States. This study was conducted in accordance with the guidelines of the Helsinki Declaration. Patients were included when {Site and Morphology Primary Site-labeled = C50.0-C50.9 breast} AND “{Derived AJCC, 7th ed (2010–2015) T = T1mi} OR {Derived AJCC, 6th ed (2004–2015) T = T1mi}”. Patients were eliminated when they contained the following situation: non-epithelial tumors, diagnosed < 18 years, AJCC IV stage, with the number of resected or positive nodes unknown, without node pathological examination, or with the survival months of zero.

2.2. Data Extraction

Relevant variables of patients were derived via SEER*Stat v8.3.9. Demographic characteristics include patient ID, age, sex, years of diagnosis, race, diagnostic confirmation, tumor history, and sequence number of BC when suffering from multiple tumors. Clinicopathological features were primary tumor site, histological type, grade, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) status, molecular subtype, AJCC Tumor-lymph Node-Metastasis (TNM) stage, number of examined lymph nodes, and number of positive nodes. The grade was classified into 1 (grade I, well-differentiated), 2 (grade II, moderately-differentiated), and 3 (grade III/IV, poorly-differentiated/undifferentiated). Histological types were classified into four groups, favorable type (adenoid cystic, tubular, encapsulated papillary, mucinous, and cribriform carcinoma), non-special type (NST) and others (ductal/lobular NST, intracystic, medullary, and apocrine carcinoma), poor type (micropapillary, clear cell, signet ring cell, and metaplastic carcinoma), and unspecified carcinoma.
As the SEER dataset does not document axillary surgery type, patients were grouped into the ALND subset (six or more nodes examined) and non-ALND subset (1–5 nodes examined) based on the AJCC definition of ALND [12]. Nodes with macrometastases and micrometastases (N1mi) were defined as N+, while negative nodes, nodes with isolated tumor cells (ITCs), N0 (i+), and N0 (mol+) were defined as N0. Breast cancer and non-breast cancer cause of death, vital status, and survival months were derived. Breast cancer-specific survival (BCSS) was determined from the date of diagnosis to the date of BC-associated death.

2.3. Statistical Analysis

Data were first characterized by descriptive statistics, then presented as a percentage for categorical variables and median (range) for continuous variables. Differences between groups were compared using the Chi-square test with Bonferroni correction. Survival outcomes were compared by Kaplan–Meier with the log-rank test. Multivariate Cox proportional hazard regression analysis was performed to identify prognostic predictors for 10-year BCSS. Propensity score matching (PSM) was used to create matched pairs by year of diagnosis to avoid potential inference from imbalanced data. All statistical analyses were processed using the SPSS 26.0 (SPSS Inc., Chicago, IL, USA) and the packages in R version 4.1.0 (R Foundation for Statistical Computing, Vienna, Austria). Two sides p < 0.05 was considered statistically significant.

3. Results

Finally, 11,692 patients with primary MBC diagnosed between 2003 and 2015 were included (Figure 1). Patients diagnosed before 2003 were excluded because the diagnostic criterion for MBC is an evolving process that is constantly being refined until 2003 (Figure 2(a1,a2)).

3.1. Demographic and Clinicopathological Characteristics

The clinicopathological characteristics of the eligible population are detailed in Table 1. About 56.7% (6627/11,692) of patients were in the age category of 50–69 years (Figure 2(b1)), and the vast majority of histological type was NST and others (95.3%). Except for borderline/unknown status, there were 25.2% negative ER (ER−), 64.9% positive ER (ER+), 42.5% negative (HER2−), and 21.5% positive HER2 (HER2+) (Figure 2(b2)). For patients diagnosed in 2010 or later, 48.3% were luminal subtype (HR+/HER2− or HR+/HER2+), 10.1% were HER2 enriched-type (HR-/HER2+), and 5.2% were triple-negative (TNBC, HR-/HER2−) (Figure 2(b3)).
As a discrepancy exists between before and after 2012 on the definition of microinvasion location (Figure 2(a2)), a comparison of the baseline characteristics was conducted. Compared to patients diagnosed in 2012–2015, patients in 2003–2011 had a higher proportion of LNM, grade 3, AJCC III stage, ALND, and chemotherapy. However, there were no significant differences in histological type, molecular subtype, primary site surgery, and radiotherapy (Table 1).
Table
Table 1. Baseline demographic and clinicopathological characteristics of 11,692 microinvasive breast cancer.
Table 1. Baseline demographic and clinicopathological characteristics of 11,692 microinvasive breast cancer.
CharacteristicsTotal n (%)2003–2011 n (%) (n = 7827)2012–2015 n (%) (n = 3865)p-Value
Age, years <0.001
 20–492906 (24.8)2013 (25.7) a893 (23.1) b
 50–696627 (56.7)4309 (55.1) a2318 (60.0) b
 ≥702159 (18.5)1505 (19.2) a654 (16.9) b
Race <0.001
 White8948 (76.5)6095 (77.9) a2853 (73.8) b
 Black1308 (11.2)862 (11.0) a446 (11.5) a
 Other ①/Unknown1436 (12.3)870 (11.1) a566 (14.7) b
Histological type 0.523
 Favorable type ②314 (2.7)221 (2.8)93 (2.4)
 NST and others ③11,142 (95.3)7446 (95.1)3696 (95.6)
 Poor type ④33 (0.3)24 (0.3)9 (0.2)
 Unspecified carcinoma203 (1.7)136 (1.7)67 (1.7)
Grade <0.001
 11923 (16.4)1247 (15.9) a676 (17.5) b
 23100 (26.5)2019 (25.8) a1081 (28.0) b
 32796 (23.9)2063 (26.4) a733 (19.0) b
 Unknown3873 (33.1)2498 (31.9) a1375 (35.6) b
ER <0.001
 Negative2946 (25.2)2044 (26.1) a902 (23.3) b
 Positive7591 (64.9)4788 (61.2) a2803 (72.5) b
 Borderline/Unknown1155 (9.9)995 (12.7) a160 (4.1) b
PR <0.001
 Negative4259 (36.4)2862 (36.6) a1397 (36.1) a
 Positive6007 (51.4)3753 (47.9) a2254 (58.3) b
 Borderline/Unknown1426 (12.2)1212 (15.5) a214 (5.5) b
HER2 (from 2010) 0.018
 Negative2430 (42.5)766 (41.4) a1664 (43.0) a
 Positive1229 (21.5)372 (20.1) a857 (22.2) a
 Borderline/Unknown2056 (36.0)712 (38.5) a1344 (34.8) b
Molecular subtype (from 2010) 0.044
 Luminal2761 (48.3)853 (46.2)1908 (49.4)
 Triple-negative298 (5.2)97 (5.2)201 (5.2)
 HER2 enriched578 (10.1)180 (9.7)398 (10.3)
 Unknown2078 (36.4)720 (38.9)1358 (35.1)
N stage <0.001
 N010,938 (93.6)7265 (92.8) a3673 (95.0) b
 N1656 (5.6)478 (6.1) a178 (4.6) b
 N264 (0.5)55 (0.7) a9 (0.2) b
 N334 (0.3)29 (0.4) a5 (0.1) b
AJCC stage <0.001
 I11,182 (95.7)7445 (95.1) a3737 (96.7) b
 II413 (3.5)299 (3.8) a114 (2.9) b
 III97 (0.8)83 (1.1) a14 (0.4) b
Primary site <0.001
 Inner1874 (16.0)1189 (15.2) a685 (17.7) b
 Outer/Axillary tail4928 (42.1)3267 (41.7) a1661 (43.0) a
 Other4890 (41.8)3371 (43.1) a1519 (39.3) b
Sequence No. of breast cancer <0.001
 One primary only8059 (68.9)5231 (66.8) a2828 (73.2) b
 1st of multi-tumors1483 (12.9)1160 (14.8) a323 (8.4) b
 ≥ 2nd of multi-tumors2150 (18.4)1436 (18.3) a714 (18.5) a
Primary site surgery 0.599
 No/unknown15 (0.1)11 (0.1)4 (0.1)
 Yes11,677 (99.9)7816 (99.9)3861 (99.9)
Axillary surgery <0.001
 non-ALND (1–5 nodes)9416 (80.5)6007 (76.7)3409 (88.2)
 ALND (≥6 nodes)2276 (19.5)1820 (23.3)456 (11.8)
Chemotherapy <0.001
 No/unknown10,687 (91.4)7099 (90.7)3588 (92.8)
 Yes1005 (8.6)728 (9.3)277 (7.2)
Radiotherapy 0.020
 Yes5098 (43.6)3401 (43.5) a1697 (43.9) a
 No/unknown6511 (55.7)4382 (56.0) a2129 (55.1) a
 Refused83 (0.7)44 (0.6) a39 (1.0) b
Notes: ① Other races are Asian or Pacific Islander and American Indian/Alaska Native. ② Favorable types included adenoid cystic, tubular, encapsulated papillary, mucinous, and cribriform carcinoma. ③ NST and others include ductal and lobular carcinoma non-special type (NST), intracystic, medullary, and apocrine carcinoma. ④ Poor type includes micropapillary, clear cell, signet ring cell, and metaplastic carcinoma. a, b: Different marks a and b indicate that pairwise comparisons are statistically significant between subgroups. The same marks indicate not statistically significant, such as a and a.

3.2. Incidence of LNM

Approximately 99.9% patients received primary tumor excision, followed with ALND (19.5%, 2276/11,692), or non-ALND (80.5%, 9416/11,692), respectively (Table 1). LNM occurred in 6.4% (754/11,692) patients including 4.3% (508/11,692) macrometastases and 2.1% (246/11,692) N1mi. In non-ALND subgroup, there were 1.3% (127/9416) macrometastases, 1.6% (148/9416) N1mi, and 2.8% (261/9416) ITCs.

3.3. Survival Outcomes and Prognostic Predictors for BCSS

With a median follow-up of 96 months (range, 1–191 months), 2.9% (334/11,692) breast cancer-associated deaths were reported, including 253 (2.3%) in N0 subgroup and 81 (10.7%) in N+ subgroup, 10-year BCSS was 96.3% in total cohort.
In univariate analysis, LNM, older age (≥70), black race, poor histological type, grade 3, TNBC, and suffered multiple tumors were significantly associated with poor BCSS. These variables and ER, PR, HER2, and primary tumor site were entered into multivariate Cox regression. Results showed that LNM (N3, HR 14.200, 95%CI 7.933–25.417; N2, HR 12.945, 95%CI 7.725–21.694; N1, HR 3.05, 95%CI 2.246–4.140, all p < 0.001), TNBC (HR 2.825, p = 0.007), suffered multiple tumors (HR 2.707, p < 0.001), older age (≥70) (HR 2.397, p < 0.001), black race (HR 1.719, p < 0.001) and grade 3 (HR 1.375, p = 0.021) were poor predictors of BCSS (Table 2). Among these six predictors, LNM had the strongest prognostic weight, the N+ subgroup had a lower 10-year BCSS than the N0 subgroup (87.4% vs. 97.0%, p < 0.001), and the N3 subgroup had the worst 10-year BCSS with merely 49.3% (Figure 3a,b).
Table
Table 2. Independent prognostic factors of breast cancer-specific survival for microinvasive breast cancer.
Table 2. Independent prognostic factors of breast cancer-specific survival for microinvasive breast cancer.
CharacteristicsUnivariate AnalysesMultivariate Analyses
HR (95%CI)p-ValueHR (95%CI)p-Value
Age (≥70 vs. 50–69)2.561 (1.975–3.320)<0.0012.397 (1.840–3.123)<0.001
Age (≤49 vs. 50–69)1.183 (0.911–1.537)0.2071.159 (0.889–1.512)0.276
Race (Black vs. White)1.869 (1.413–2.470)<0.0011.719 (1.293–2.285)<0.001
Primary site (outer/axillary tail vs. inner)1.072 (0.761–1.511)0.6911.059 (0.750–1.494)0.745
Histological type (NST vs. favorable)1.120 (0.555–2.259)0.7521.020 (0.503–2.07)0.955
Histological type (Poor vs. favorable)3.81(1.011–14.362)0.0482.167 (0.557–8.431)0.265
Grade (3 vs. 1/2)1.461 (1.133–1.885)0.0031.375 (1.049–1.803)0.021
N (1 vs. 0)3.311 (2.457–4.463)<0.0013.050 (2.246–4.140)<0.001
N (2 vs. 0)10.879 (6.563–18.034)<0.00112.945 (7.725–21.694)<0.001
N (3 vs. 0)18.646 (10.676–32.565)<0.00114.200 (7.933–25.417)<0.001
ER (positive vs. negative)0.907 (0.708–1.163)0.4421.235 (0.858–1.780)0.256
PR (positive vs. negative)0.843 (0.668–1.065)0.1530.841 (0.607–1.166)0.299
HER2 (positive vs. negative)0.812 (0.454–1.453)0.4830.782 (0.338–1.808)0.565
Sequence No. of BC (1st vs. one only)2.376 (1.796–3.142)<0.0012.483 (1.870–3.298)<0.001
Sequence No. of BC (2nd vs. one only)2.838 (2.218–3.632)<0.0012.707 (2.094–3.499)<0.001
Subtype (TNBC vs. Luminal)2.949 (1.498–5.806)0.0022.825 (1.328–6.008)0.007
Subtype (HER2 enriched vs. Luminal)1.268 (0.609–2.638)0.5251.780 (0.637–4.980)0.272
Notes: CI, confidence interval; HR, hazard ratio; No., number; NST, ductal and lobular carcinoma non-special type; TNBC, triple-negative breast cancer.
Diagnostics 12 01049 g003 550
Figure 3. Prognostic value of lymph node metastases of breast cancer-specific survival (BCSS), and survival benefit of axillary lymph node dissection (ALND) for microinvasive breast cancer. (a) N+ subgroup had lower 10-year BCSS than N0 subgroup (87.4% vs. 97.0%, p < 0.001). (b) Lymph node metastases had the strongest prognostic weight (N3, HR 14.200; N2, HR 12.945; N1, HR 3.05, all p < 0.001). (c) ALND did not confer a survival benefit on 10-year BCSS (92.1% vs. 89.5%, p = 0.355) in patients with 1–2 positive nodes when compared to non-ALND surgery. (d) Patients received ALND even had a lower 10-year BCSS than patients with non-ALND (94.7% vs. 97.1%, p < 0.001) in the N0 cohort.
Figure 3. Prognostic value of lymph node metastases of breast cancer-specific survival (BCSS), and survival benefit of axillary lymph node dissection (ALND) for microinvasive breast cancer. (a) N+ subgroup had lower 10-year BCSS than N0 subgroup (87.4% vs. 97.0%, p < 0.001). (b) Lymph node metastases had the strongest prognostic weight (N3, HR 14.200; N2, HR 12.945; N1, HR 3.05, all p < 0.001). (c) ALND did not confer a survival benefit on 10-year BCSS (92.1% vs. 89.5%, p = 0.355) in patients with 1–2 positive nodes when compared to non-ALND surgery. (d) Patients received ALND even had a lower 10-year BCSS than patients with non-ALND (94.7% vs. 97.1%, p < 0.001) in the N0 cohort.
Diagnostics 12 01049 g003

3.4. Survival Benefit of ALND

We further investigated the survival benefit of ALND in patients with N0 and 1–2 positive nodes, respectively. Baseline characteristics of patients between ALND and non-ALND subgroups in cohort with 1–2 positive nodes were roughly the same (Table 3). Kaplan–Meier analyses showed that ALND did not confer a survival benefit on 10-year BCSS (92.1% vs. 89.5%, p = 0.355) in patients with 1–2 positive nodes compared to non-ALND surgery (Figure 3c). Because significant biases existed in the N0 cohort, 1:3 PSM was used to minimize biases (Table 3). After matching, Kaplan–Meier analyses showed that patients who received ALND even had a lower 10-year BCSS than patients with non-ALND (94.7% vs. 97.1%, p < 0.001) in the N0 cohort (Figure 3d).

4. Discussion

In this study, 19.5% of patients received ALND, 80.5% were non-ALND; the LNM rate was 6.4%, including 4.3% macrometastases and 2.1% N1mi. Of note, the LNM rate reduced to 1.3% macrometastases and 1.6% N1mi in the non-ALND subgroup, slightly lower than 2% and 3% in the latest meta-analysis by Choi [6]. With a median follow-up of 96 months, MBC showed an excellent survival with a 10-year BCSS of 96.3% in the total cohort. However, 10-year BCSS declined to 87.4% in the N+ subgroup and 49.3% in the N3 subgroup. Among clinicopathological risk factors, LNM was the strongest poor prognostic predictor.
As for varied LNM rates (1.5–20%) reported in the literature [6,8,13,14,15,16], this may be partly attributable to different diagnostic criteria of MBC, inconsistent definitions of LNM, and varied SLN tracer and SLN evaluating methods. Firstly, though the concept “microinvasion” was proposed in 1982 [17], the definition of microinvasion was not internationally standardized until the 3rd edition of the WHO classification of tumors [18]. The location of tumor cells was confined to non-specialized interlobular stroma before 2012, which are likely to have deeper invasion than in the specialized interlobular stroma [19]. We did find that patients from 2003 to 2011 had a higher LNM rate in this study. Secondly, there was inconsistency in the classification of ITCs; some studies included ITCs into N+, leading to a high LNM rate [8,9,15]. Considering that some ITCs may be an iatrogenic transit of tumor cells to lymph nodes, not actual metastases, we classified ITCs into N0 based on AJCC staging [12]. Furthermore, research demonstrated that fluorescence imaging with indocyanine green is superior to a single technique with blue dye or radioisotope for SLN identification [20]. Additionally, immunohistochemistry staining can detect more N1mi and ITCs [13,21]. Beyond that, patients with ALND were not included in those studies.
As for the axillary staging of MBC, some studies suggested that MBC had very similar survival rates to DCIS, and it should be treated and followed up as pure DCIS [2,13]. Others suggested that axillary staging may be an unnecessary intervention that does not change MBC management for the majority of MBC diagnosed postoperatively [6], and even routine SLNB is perhaps not useful for MBC [8]. However, 10-year BCSS declined from 97.0% in the N0 subgroup to 87.4% in the N+ subgroup in this study, which was in line with the results of three other research based on the SEER dataset [4,5,10]. These large-scale studies compared clinicopathological features, treatments, and outcomes of pure DCIS, MBC, and T1a invasive BC. They all demonstrated that MBC seemed to resemble T1a invasive BC with more aggressive characteristics such as ER− (22.9–33.1%), HER2+ (10.5–36.5%), higher LNM rate (7.6–9.6%), and worse outcomes than that of pure DCIS. Patients with MBC may have an approximately two-fold increased risk of BC-specific death compared to patients with pure DCIS [5]. However, it should be noted that Wang et al. [10] included patients diagnosed between 1990 and 2012 and restricted to the age of 20–69 years, Cosette et al. [4] included patients with Nx or node aspiration, and Sopik et al. [5] excluded patients with LNM. Thus, there were patient biases as the target population differed across the studies due to distinct research purposes.
In addition, early breast cancer has been suggested to be a systemic disease, and sometimes breast tumors metastasize with unknown primary [22,23]. For instance, 28 excluded patients in this series presented with bone, lung, or brain metastases at initial diagnosis. Usually, actual risks are not from early invasive cancer but microinvasion because invasive cancer is treated with adjuvant therapies after surgery according to guidelines. Additionally, some MBC diagnosed intra-operatively may upgrade to invasive BC postoperatively. In multivariate analyses, LNM showed the strongest prognostic weight for BCSS; 10-year BCSS for the N3 subgroup was merely 49.3%. Furthermore, Brown et al. [24] and Pereira et al. [25] showed that the blood vessels in lymph nodes could serve as an exit route for tumor cells entering the systemic circulation. Therefore, assessment of lymph node status is necessary for MBC.
Currently, the treatment concept for BC is shifted from maximal tolerate therapy to minimum effective treatment. Thus, de-escalation of axillary surgery is required to avoid postoperative complications such as lymphedema, dysfunction of the shoulder joint, nerve injury, etc., without harming the accuracy of lymph node staging and local contrast [26]. The American College of Surgeons Oncology Group Z0011 [27] and International Breast Cancer Study Group 23-01 trials [28] indicated that omission of ALND for patients with 1–2 positive SLNs had not increased local recurrence or decreased survival compared with ALND. Based on these researches, guidelines recommended that ALND is not a must for patients who met the Z0011 trial criteria [7]. In this study, we found that patients with 1–2 positive nodes did not benefit more from ALND than from non-ALND, and patients who received ALND even showed a lower 10-BCSS than those who received non-ALND in the N0 subgroup. Therefore, we suggest that non-ALND such as SLNB is required and sufficient for patients with high-risk MBC undergoing mastectomy. However, the feasibility and predictive ability of SLNB have yet to be standardized as the medical resource is unevenly distributed in the real world. A multicenter, retrospective study in China showed that about 43.5% of early breast cancer underwent SLNB, and 83.0% of patients out of one or two positive SLNs received ALND [29].
In contrast to previous single-center studies, our study is based on a national dataset with large sample size and relatively long follow-up. However, our study has several limitations due to its retrospective nature. Firstly, it may hold a risk of misclassification and missing data. A large proportion of the patients have a missing grade (33.1%), ER (9.9%), PR (12.2%), and HER2 (36.0%) status. Apart from the abovementioned features, other features such as Ki67, several foci, lymphovascular invasion, extensive in situ components, and surgical margin status are not available. Secondly, the diagnostic criteria of MBC and all the other pathological features were continually revised during a quite large timespan of the data. These, plus varied categorization of variables in studies, have significant implications in identifying prognostic factors for MBC. Thirdly, limited information is available on surgery, chemotherapy, and radiotherapy. The treatment status of patients recorded as no/unknown for chemotherapy is 91.4%, and unknown for radiotherapy is 55.7%. Though more patients were recorded as radiotherapy-received in the non-ALND subgroup than in the ALND subgroup (33.8% vs. 29.7%) during PSM analysis, more than 60% of patients remain unclear whether they received radiotherapy or not. Consequently, we cannot conclude whether radiotherapy affects prognosis in the N0 subgroup. Moreover, specific regimens of medical therapies were inaccessible.

5. Conclusions

Our study confirmed that though MBC has a low LNM rate (6.4%) and relatively excellent prognosis for most patients, patients with LNM showed poor prognosis, and SLNB is required and sufficient for MBC. In addition, internationally standardized diagnostic criteria and categorization are the premises for a more comprehensive and in-depth understanding. Further prospectively and retrospectively research is warranted to distinguish patients with high-risk characteristics and help tailor axillary management to guide adjuvant treatment while minimizing unnecessary interventions of MBC.

Author Contributions

Conceptualization, S.K. and Y.C.; methodology, software, and formal analysis, J.C. and M.G.; data curation, G.C., X.L. and Y.Z.-C.; writing and funding acquisition, J.C. and B.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Health Commission of Hubei Province Scientific Research Project (WJ2019H365), the Wuhan Municipal Health Commission Scientific Research Foundation (WX19Q18), and the National Natural Science Foundation of China (81901820/H18).

Institutional Review Board Statement

Ethical review and approval were waived for this study because it is a publicly archived database-based retrospective analysis.

Informed Consent Statement

Not applicable.

Data Availability Statement

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Aleskandarany, M.A.; Vandenberghe, M.E.; Marchio, C.; Ellis, I.O.; Sapino, A.; Rakha, E.A. Tumour heterogeneity of breast cancer: From morphology to personalised medicine. Pathobiology 2018, 85, 23–34. [Google Scholar] [CrossRef] [PubMed]
  2. Kim, M.; Kim, H.J.; Chung, Y.R.; Kang, E.; Kim, E.K.; Kim, S.H.; Kim, Y.J.; Kim, J.H.; Kim, I.A.; Park, S.Y. Microinvasive Carcinoma versus ductal carcinoma in situ: A comparison of clinicopathological features and clinical outcomes. J. Breast Cancer 2018, 21, 197–205. [Google Scholar] [CrossRef] [PubMed]
  3. Edge, S.; Byrd, D.; Compton, C.; Fritz, G.; Greene, F.; Trotti, A. AJCC Cancer Staging Manual, 7th ed.; Springer: New York, NY, USA, 2009. [Google Scholar]
  4. Champion, C.D.; Ren, Y.; Thomas, S.M.; Fayanju, O.M.; Rosenberger, L.H.; Greenup, R.A.; Menendez, C.S.; Hwang, E.S.; Plichta, J.K. DCIS with microinvasion: Is it in situ or invasive disease? Ann. Surg. Oncol. 2019, 26, 3124–3132. [Google Scholar] [CrossRef] [PubMed]
  5. Sopik, V.; Sun, P.; Narod, S.A. Impact of microinvasion on breast cancer mortality in women with ductal carcinoma in situ. Breast Cancer Res. Treat. 2018, 167, 787–795. [Google Scholar] [CrossRef]
  6. Choi, B.; Jegatheeswaran, L.; Nakhoul, M.; Haria, P.; Srivastava, R.; Karki, S.; Lupi, M.; Patel, V.; Chakravorty, A.; Babu, E. Axillary staging in ductal carcinoma in situ with microinvasion: A meta-analysis. Surg. Oncol. 2021, 37, 101557. [Google Scholar] [CrossRef]
  7. Lyman, G.H.; Somerfield, M.R.; Bosserman, L.D.; Perkins, C.L.; Weaver, D.L.; Giuliano, A.E. Sentinel lymph node biopsy for patients with early-stage breast cancer: American Society of Clinical Oncology Clinical Practice Guideline Update. J. Clin. Oncol. 2017, 35, 561–564. [Google Scholar] [CrossRef] [Green Version]
  8. Magnoni, F.; Massari, G.; Santomauro, G.; Bagnardi, V.; Pagan, E.; Peruzzotti, G.; Galimberti, V.; Veronesi, P.; Sacchini, V.S. Sentinel lymph node biopsy in microinvasive ductal carcinoma in situ. Br. J. Surg. 2019, 106, 375–383. [Google Scholar] [CrossRef] [Green Version]
  9. Strang, L.R.; Sun, J.; Sun, W.; Boulware, D.; Kiluk, J.V.; Lee, M.C.; Khazai, L.; Laronga, C. Characteristics of microinvasive ductal carcinoma in situ versus noninvasive and invasive breast cancer. J. Surg. Res. 2020, 254, 378–383. [Google Scholar] [CrossRef]
  10. Wang, W.; Zhu, W.; Du, F.; Luo, Y.; Xu, B. The Demographic Features, Clinicopathological characteristics and cancer-specific outcomes for patients with microinvasive breast cancer: A SEER Database Analysis. Sci. Rep. 2017, 7, 42045. [Google Scholar] [CrossRef] [Green Version]
  11. Holm-Rasmussen, E.V.; Jensen, M.B.; Balslev, E.; Kroman, N.; Tvedskov, T.F. Sentinel and non-sentinel lymph node metastases in patients with microinvasive breast cancer: A nationwide study. Breast Cancer Res. Treat. 2019, 175, 713–719. [Google Scholar] [CrossRef]
  12. Giuliano, A.E.; Connolly, J.L.; Edge, S.B.; Mittendorf, E.A.; Rugo, H.S.; Solin, L.J.; Weaver, D.L.; Winchester, D.J.; Hortobagyi, G.N. Breast cancer-major changes in the American Joint Committee on Cancer eighth edition cancer staging manual. CA Cancer J. Clin. 2017, 67, 290–303. [Google Scholar] [CrossRef] [Green Version]
  13. Lillemoe, T.J.; Tsai, M.L.; Swenson, K.K.; Susnik, B.; Krueger, J.; Harris, K.; Rueth, N.; Grimm, E.; Leach, J.W. Clinicopathologic analysis of a large series of microinvasive breast cancers. Breast J. 2018, 24, 574–579. [Google Scholar] [CrossRef]
  14. Kapoor, N.S.; Shamonki, J.; Sim, M.S.; Chung, C.T.; Giuliano, A.E. Impact of multifocality and lymph node metastasis on the prognosis and management of microinvasive breast cancer. Ann. Surg. Oncol. 2013, 20, 2576–2581. [Google Scholar] [CrossRef]
  15. Orzalesi, L.; Casella, D.; Criscenti, V.; Gjondedaj, U.; Bianchi, S.; Vezzosi, V.; Nori, J.; Cecconi, L.; Meattini, I.; Livi, L.; et al. Microinvasive breast cancer: Pathological parameters, cancer subtypes distribution, and correlation with axillary lymph nodes invasion. Results of a large single-institution series. Breast Cancer 2016, 23, 640–648. [Google Scholar] [CrossRef]
  16. Si, J.; Guo, R.; Pan, H.; Lu, X.; Guo, Z.; Han, C.; Xue, L.; Xing, D.; Wu, W.; Chen, C. Multiple microinvasion foci in ductal carcinoma in situ is associated with an increased risk of recurrence and worse survival outcome. Front. Oncol. 2020, 10, 607502. [Google Scholar] [CrossRef]
  17. Lagios, M.D.; Westdahl, P.R.; Margolin, F.R.; Rose, M.R. Duct carcinoma in situ. Relationship of extent of noninvasive disease to the frequency of occult invasion, multicentricity, lymph node metastases, and short-term treatment failures. Cancer 1982, 50, 1309–1314. [Google Scholar] [CrossRef]
  18. Tavassoli, F.A.; Devilee, P. Pathology & genetics. In Tumours of the Breast and Female Genital Organs; IARC Press: Lyon, France, 2003. [Google Scholar]
  19. Lakhani, S.R.; Ellis, I.O.; Schnitt, S.J.; Tan, P.H.; van de Vijver, M.J. WHO Classification of Tumours of the Breast; IARC Press: Lyon, France, 2012. [Google Scholar]
  20. Kedrzycki, M.S.; Leiloglou, M.; Ashrafian, H.; Jiwa, N.; Thiruchelvam, P.T.R.; Elson, D.S.; Leff, D.R. Meta-analysis comparing fluorescence imaging with radioisotope and blue dye-guided sentinel node identification for breast cancer surgery. Ann. Surg. Oncol. 2021, 28, 3738–3748. [Google Scholar] [CrossRef]
  21. Fan, B.; Pardo, J.A.; Serres, S.; Alapati, A.C.; Szewczyk, J.; Mele, A.; James, T.A. Role of sentinel lymph node biopsy in microinvasive breast cancer. Ann. Surg. Oncol. 2020, 27, 4468–4473. [Google Scholar] [CrossRef]
  22. Linde, N.; Casanova-Acebes, M.; Sosa, M.S.; Mortha, A.; Rahman, A.; Farias, E.; Harper, K.; Tardio, E.; Reyes Torres, I.; Jones, J.; et al. Macrophages orchestrate breast cancer early dissemination and metastasis. Nat. Commun. 2018, 9, 21. [Google Scholar] [CrossRef] [Green Version]
  23. Barbieri, E.; Anghelone, C.A.P.; Gentile, D.; La Raja, C.; Bottini, A.; Tinterri, C. Metastases from occult breast cancer: A case report of carcinoma of unknown primary syndrome. Case Rep. Oncol. 2020, 13, 1158–1163. [Google Scholar] [CrossRef]
  24. Brown, M.; Assen, F.P.; Leithner, A.; Abe, J.; Schachner, H.; Asfour, G.; Bago-Horvath, Z.; Stein, J.V.; Uhrin, P.; Sixt, M.; et al. Lymph node blood vessels provide exit routes for metastatic tumor cell dissemination in mice. Science 2018, 359, 1408–1411. [Google Scholar] [CrossRef] [Green Version]
  25. Pereira, E.R.; Kedrin, D.; Seano, G.; Gautier, O.; Meijer, E.F.J.; Jones, D.; Chin, S.M.; Kitahara, S.; Bouta, E.M.; Chang, J.; et al. Lymph node metastases can invade local blood vessels, exit the node, and colonize distant organs in mice. Science 2018, 359, 1403–1407. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Gnant, M.; Harbeck, N.; Thomssen, C. St. Gallen/Vienna 2017: A Brief Summary of the Consensus Discussion about Escalation and De-Escalation of Primary Breast Cancer Treatment. Breast Care 2017, 12, 102–107. [Google Scholar] [CrossRef] [Green Version]
  27. Giuliano, A.E.; Ballman, K.V.; McCall, L.; Beitsch, P.D.; Brennan, M.B.; Kelemen, P.R.; Ollila, D.W.; Hansen, N.M.; Whitworth, P.W.; Blumencranz, P.W.; et al. Effect of Axillary Dissection vs No Axillary Dissection on 10-Year Overall Survival Among Women With Invasive Breast Cancer and Sentinel Node Metastasis: The ACOSOG Z0011 (Alliance) Randomized Clinical Trial. JAMA 2017, 318, 918–926. [Google Scholar] [CrossRef]
  28. Galimberti, V.; Cole, B.F.; Viale, G.; Veronesi, P.; Vicini, E.; Intra, M.; Mazzarol, G.; Massarut, S.; Zgajnar, J.; Taffurelli, M.; et al. Axillary dissection versus no axillary dissection in patients with breast cancer and sentinel-node micrometastases (IBCSG 23-01): 10-year follow-up of a randomised, controlled phase 3 trial. Lancet Oncol. 2018, 19, 1385–1393. [Google Scholar] [CrossRef]
  29. Zhang, J.; Wang, T.; Yan, C.; Huang, M.; Fan, Z.; Ling, R. Clinical Practice Status of Sentinel Lymph Node Biopsy for Early-Stage Breast Cancer Patients in China: A Multicenter Study. Clin. Epidemiol. 2020, 12, 917–924. [Google Scholar] [CrossRef]
Diagnostics 12 01049 g001 550
Figure 1. The flow chart of patient inclusion and exclusion. AJCC: American Joint Committee on Cancer, ITCs: isolated tumor cells, MBC: microinvasive breast cancer, N1: 1–3 positive nodes, N2: 4–9 positive nodes, N3: ≥10 positive nodes, N1mi: micrometastases nodes.
Figure 1. The flow chart of patient inclusion and exclusion. AJCC: American Joint Committee on Cancer, ITCs: isolated tumor cells, MBC: microinvasive breast cancer, N1: 1–3 positive nodes, N2: 4–9 positive nodes, N3: ≥10 positive nodes, N1mi: micrometastases nodes.
Diagnostics 12 01049 g001
Diagnostics 12 01049 g002 550
Figure 2. The diagnostic criterion of microinvasive breast cancer (MBC) and major clinicopathological characteristics of the eligible population. (a1) MBC is defined as ductal carcinoma in situ (yellow dash line) with one or more foci of tumor cells (red dash line) extending beyond the basement membrane. No focus is larger than 1 mm in max diameter. (a2) Evolution of the diagnostic criterion for microinvasion. A unified measurement standard for microinvasion was first established in the AJCC 6th edition manual. Subsequently, the 2003 WHO classification of breast tumors recommended that the tumor cells in non-specialized interlobular, not cells in interlobular stromal tissue, were regarded as microinvasions. The constraint for the location of tumor cells did not change until the 2012 WHO classification of tumors. (b1) Age distribution of the eligible population. (b2) ER, PR, HER2 distribution of the eligible population, and the HER2 status was not included in the SEER data until 2010. (b3) Molecular subtypes distribution, and the subtype was not available until 2010 accordingly.
Figure 2. The diagnostic criterion of microinvasive breast cancer (MBC) and major clinicopathological characteristics of the eligible population. (a1) MBC is defined as ductal carcinoma in situ (yellow dash line) with one or more foci of tumor cells (red dash line) extending beyond the basement membrane. No focus is larger than 1 mm in max diameter. (a2) Evolution of the diagnostic criterion for microinvasion. A unified measurement standard for microinvasion was first established in the AJCC 6th edition manual. Subsequently, the 2003 WHO classification of breast tumors recommended that the tumor cells in non-specialized interlobular, not cells in interlobular stromal tissue, were regarded as microinvasions. The constraint for the location of tumor cells did not change until the 2012 WHO classification of tumors. (b1) Age distribution of the eligible population. (b2) ER, PR, HER2 distribution of the eligible population, and the HER2 status was not included in the SEER data until 2010. (b3) Molecular subtypes distribution, and the subtype was not available until 2010 accordingly.
Diagnostics 12 01049 g002
Table
Table 3. Baseline characteristics between non-ALND and ALND subgroups in cohort with N0 and 1–2 positive nodes.
Table 3. Baseline characteristics between non-ALND and ALND subgroups in cohort with N0 and 1–2 positive nodes.
CharacteristicsN0 Original CohortN0 Propensity-Matched Cohort1–2 Positive Nodes Cohort
Non-ALND n (%) (n = 9141)ALND n (%) (n = 1797)p-ValueNon-ALND n (%) (n = 5391)ALND n (%) (n = 1797)p-ValueNon-ALND n (%) (n = 267)ALND n (%) (n = 337)p-Value
Age, years <0.001 0.361 0.05
 20–492207 (24.1) a440 (24.5) b 1356 (25.2)440 (24.5) 86 (32.2)117 (35.7)
 50–695294 (57.9) a945 (52.6) b 2885 (53.5)945 (52.6) 135 (50.6)185 (54.9)
 ≥701640 (17.9) a412 (22.9) a 1150 (21.3)412 (22.9) 46 (17.2)35 (10.4)
Race <0.001 0.758 0.406
 White7053 (77.2) a1352 (75.2) a 4076 (75.6)1352 (75.2) 190 (71.2)248 (73.6)
 Black924 (10.1) a241 (13.4) b 688 (12.8)241 (13.4) 55 (20.6)56 (16.6)
 Other ①/unknown1164 (12.7) a204 (11.4) a 627 (11.6)204 (11.4) 22 (8.2)33 (9.8)
Histological type 0.151 0.387 0.428
 Favorable type ②257 (2.8)47 (2.6) 144 (2.7)47 (2.6) 3 (1.1)6 (1.8)
 NST and others ③8698 (95.2)1716 (95.5) 5138 (95.3)1716 (95.5) 258 (96.6)323 (95.8)
 Poor type ④22 (0.2)9 (0.50) 15 (0.3)9 (0.5) 1 (0.4)0 (0.0)
 Unspecified164 (1.8)25 (1.4) 94 (1.7)25 (1.4) 5 (1.9)8 (2.4)
Grade 0.004 0.403 0.059
 11549 (16.9) a285 (15.9) a 862 (16.0)285 (15.9) 38 (14.2)44 (13.0)
 22462 (26.9) a436 (24.3) b 1405 (26.0)436 (24.3) 59 (22.1)105 (31.2)
 32088 (22.8) a475 (26.4) b 1347 (25.0)475 (26.4) 76 (28.5)95 (28.2)
 Unknown3042 (33.3) a601 (33.4) a 1777 (33.0)601 (33.4) 94 (35.2)93 (27.6)
ER <0.001 0.002 0.156
 Negative2264 (24.8) a494 (27.5) b 1394 (25.9) a494 (27.5) a 174 (65.2)241 (71.5)
 Positive6055 (66.2) a1027 (57.2) b 3313 (61.4) a1027 (57.2) b 27 (10.1)22 (6.5)
 Borderline/unknown822 (9.0) a276 (15.3) a 684 (12.7) a276 (15.3) b 66 (24.7)74 (22.0)
PR <0.001 0.005 0.085
 Negative3310 (36.2) a668 (37.2) a 1953 (36.2) a668 (37.2) a 92 (34.5)118 (35.0)
 Positive4791 (52.4) a810 (45.1) b 2629 (48.8) a810 (45.1) b 141 (52.8)194 (57.6)
 Borderline/unknown1040 (11.4) a319 (17.7) b 809 (15.0) a319 (17.7) b 34 (12.7)25 (7.4)
HER2 (from 2010) <0.001 0.192 0.002
 Negative2044 (42.3) a232 (41.2) b 783 (42.7)232 (41.1) 52 (41.0) a77 (56.6) a
 Positive1003 (20.7) a126 (22.3) b 387 (21.1)126 (22.4) 39 (30.7) a42 (30.9) a
 Borderline/unknown1788 (37.0) a206 (36.5) b 663 (36.2)206 (36.5) 36 (28.3) a17 (12.5) b
Molecular subtype (from 2010) <0.001 0.373 <0.001
 Luminal2315 (47.9) a261 (46.2) b 878 (47.9)261 (46.2) 65 (51.2) a88 (64.7) a
 Triple-negative246 (5.1) a27 (4.8) b 76 (4.1)27 (4.8) 9 (7.1) a12 (8.8) a
 HER2 enriched-type468 (9.7) a67 (11.9) b 208 (11.4)67 (11.9) 16 (12.6) a19 (14.0) a
 Unknown1806 (37.3) a209 (37.1) b 671 (36.6)209 (37.1) 37 (29.1) a17 (12.5) b
Primary site <0.001 0.322 0.544
 Inner1558 (17.0) a226 (12.6) b 752 (14.0)226 (12.6) 36 (13.5)38 (11.3)
 Outer/Axillary tail3880 (42.5) a769 (42.8) a 2293 (42.5)769 (42.8) 90 (33.7)126 (37.4)
 Other3703 (40.5) a802 (44.6) b 2346 (43.5)802 (44.6) 141 (52.8)173 (51.3)
Sequence No. of breast cancer 0.576 0.894 0.204
 One primary only6320 (69.1)1220 (67.9) 3661 (67.9)1220 (67.9) 172 (64.4)240 (71.2)
 1st of multi-tumors1151 (12.6)234 (13.0) 721 (13.4)234 (13.0) 42 (15.7)43 (12.9)
 ≥2nd of multi-tumors1670 (18.3)343 (19.1) 1009 (18.7)343 (19.1) 53 (19.9)54 (15.9)
Primary site surgery 0.513 1 0.052
 No/unknown6 (0.07)2 (0.11) 5 (0.1)2 (0.1) 5 (1.9)1 (0.3)
 Yes9135 (99.9)1795 (99.9) 5386 (99.9)1795 (99.9) 262 (98.1)336 (99.7)
Chemotherapy <0.001 0.152 <0.001
 No/unknown403 (4.4)131 (7.3) 339 (6.3)131 (7.3) 117 (43.8)234 (69.4)
 Yes8738 (95.6)16,686 (92.7) 5052 (93.7)1666 (92.7) 150 (56.2)103 (30.6)
Radiotherapy <0.001 0.004 0.236
 Yes4307 (47.1) a533 (29.7) b 1824 (33.8)533 (29.7) 83 (31.1)95 (28.2)
 No/unknown4764 (52.1) a1256 (69.9) b 3550 (65.9)1256 (69.9) 184 (68.9)239 (70.9)
 Refused70 (0.8) a8 (0.4) a 17 (0.3)8 (0.4) 0 (0.00)3 (0.90)
Notes: ① Other races are Asian or Pacific Islander and American Indian/Alaska Native. ② Favorable type include adenoid cystic, tubular, encapsulated papillary, mucinous, and cribriform carcinoma. ③ NST and others include ductal and lobular carcinoma non-special type (NST), intracystic, medullary, and apocrine carcinoma. ④ Poor type includes micropapillary, clear cell, signet ring cell, and metaplastic carcinoma. a, b Different marks a and b indicate that pairwise comparisons are statistically significant between subgroups. The same marks indicate not statistically significant, such as a and a. ALND, axillary lymph node dissection; CI, confidence interval; No., number; OR, odds ratio; SLNB, sentinel lymph node biopsy.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Chen, J.; Luo, B.; Gao, M.; Cai, G.; Luo, X.; Zhang-Cai, Y.; Ke, S.; Chen, Y. Regional Lymph Node Metastasis and Axillary Surgery of Microinvasive Breast Cancer: A Population-Based Study. Diagnostics 2022, 12, 1049. https://doi.org/10.3390/diagnostics12051049

AMA Style

Chen J, Luo B, Gao M, Cai G, Luo X, Zhang-Cai Y, Ke S, Chen Y. Regional Lymph Node Metastasis and Axillary Surgery of Microinvasive Breast Cancer: A Population-Based Study. Diagnostics. 2022; 12(5):1049. https://doi.org/10.3390/diagnostics12051049

Chicago/Turabian Style

Chen, Jiamei, Bo Luo, Mengting Gao, Gaoke Cai, Xixi Luo, Yutian Zhang-Cai, Shaobo Ke, and Yongshun Chen. 2022. "Regional Lymph Node Metastasis and Axillary Surgery of Microinvasive Breast Cancer: A Population-Based Study" Diagnostics 12, no. 5: 1049. https://doi.org/10.3390/diagnostics12051049

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop