Risk factors for recurrence in patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative early breast cancer in Japan: a systematic literature review and meta-analysis

Figures & data

Figure 1. PRISMA diagram illustrating the study selection process. PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-analyses.

Table 1. Characteristics of the 42 articles identified in the systematic literature review.

Author, year [reference]	Study design	Sample size	Stage	HR+, %	HER2−, %	Outcome	Evaluated risk factors	RoB
Shibuta et al. (2011)^22	Observational: retrospective	4266	I-III	78.0%	83.0%	DFS	subtype	High
Tokiniwa et al. (2012)^23	Observational: retrospective	71	I-III	87.3%	100.0%	RFS	tumor size, Ki-67, topoisomerase II alpha expression	High
Hisamatsu et al. (2012)^24	Observational: prospective	122	I-III	100.0%	100.0%	RFS	pT, LN metastasis, nuclear grade, Ki-67, FOXA1	High
Ishitobi et al. (2012)^25	Observational: retrospective	375	I-III	50.5%	81.7%	OS, RFS, IBTR	LN status, tumor size, histologic grade, ER, IBTR, age, postoperative chemotherapy, postoperative hormone therapy, tumor morphology, margin width, lymphovascular invasion, HER2, therapeutic effect (neoadjuvant)	Moderate
Masuda et al. (2012)^26	Interventional: RCT Phase III	185	IIA	100.0%	100.0%	Response	regimen (anastrozole + goserelin vs tamoxifen + goserelin)	Low
Tokunaga et al. (2012)^27	Observational: retrospective	246	I-III	68.7%	78.6%	RFS	tumor size, nodal involvement, nuclear grade, ER, PgR, HER2, LOH	Moderate
Kikuchi et al. (2013)^28	Observational: retrospective	1987	I-III	100.0%	100.0%	DFS	p53	High
Satoh et al. (2013)^29	Observational: retrospective	471	I-III	100.0%	100.0%	DFS	menopausal status, lymphatic invasion, nuclear grade, number of LN metastases, comedo-type cancer, family history of breast cancer	High
Kurebayashi et al. (2014)^30	Observational: retrospective	261	I-III	100.0%	100.0%	DDFS, BCSS	lymphovascular invasion, PgR, Ki-67, grade	Moderate
Niikura et al. (2014)^31	Observational: retrospective	1331	I-III	80.0%	84.0%	RFS	T stage, N stage, Ki-67, adjuvant endocrine therapy	Moderate
Nishimiya et al. (2014)^32	Observational: retrospective	253	I-III	71.0%	80.0%	RFS, OS	age, preoperative CEA, preoperative TPA, preoperative CA15-3, pT, pN, histology, HR, HER2, Ki-67, method (total/partial), adjuvant hormone therapy, adjuvant chemotherapy	High
Hisamatsu et al. (2015)^33	Observational: prospective	141	I-III	100.0%	100.0%	DFS	pT, LN metastasis, nuclear grade, Ki-67, GATA-3, FOXA1	Moderate
Honma et al. (2015)^34	Observational: retrospective	1111	I-III	86.5%	96.1%	DFS, OS	menopause, T, LN, grade, ER, PgR, HER2, Bcl-2	High
Kawase et al. (2015)^35	Observational: retrospective	42	II-III	100.0%	100.0%	DDFS	tumor size, LN status, tumor grade, pre ER, post ER, pre PgR, post PgR, pre Ki-67, post Ki-67, pre Bcl-2, post Bcl-2, pre FOXA1, post FOXA1, pre MAPT, post MAPT	Moderate
Nishimukai et al. (2015)^36	Observational: prospective	327	I-III	100.0%	100.0%	DDFS	tumor size, LN metastasis, Ki-67, PgR, menopausal status, nuclear grade, ER, adjuvant chemotherapy	High
Ono et al. (2015)^37	Observational: retrospective	369	I-III	100.0%	100.0%	DFS, BCSS	age, menopause status, tumor size, histology, histological grade, nuclear grade, lymphovascular invasion, Ki-67	High
Higuchi et al. (2016)^38	Observational: retrospective	387	I-III	77.5%	80.6%	RFS	age, menopausal status, T size, LN metastasis, nuclear grade, ER, PgR, HER2, subtype, Ki-67, SUVmax, adjuvant chemotherapy	High
Kawai et al. (2016)^39	Observational: retrospective	9850	I-III	100.0%	100.0%	RFS, BCSS	BMI	Moderate
Miyoshi et al. (2016)^40	Observational: retrospective	639	I-III	100.0%	100.0%	OS	ALDH1, age, bilateral breast cancer, tumor size, nodal status, PgR, Ki-67, tumor grade	High
Okuma et al. (2016)^41	Observational: retrospective	122	II-III	56.6%	61.5%	pCR, DFS	age, stage, subtype, histological grade, response (neoadjuvant), number of axillary LNs, gene expression risk score	Moderate
Sato et al. (2016)^42	Observational: retrospective	118	I-III	100.0%	100.0%	BCSS	PgR, histological grade, Ki-67, tumor size, adjuvant hormonal therapy	Moderate
Kurozumi et al. (2017)^43	Observational: retrospective	177	I-III	100.0%	100.0%	RFS, BCSS	Ki-67, PgR, menopausal status, pT, pN, histological grade, adjuvant chemotherapy, adjuvant endocrine therapy	Moderate
Ono et al. (2017)^44	Observational: retrospective	368	I-III	100.0%	100.0%	DFS, BCSS	age, menopause, pT, grade, nuclear grade, histology, PgR	Moderate
Hayashi et al. (2018)^45	Observational: retrospective	719	0-III	68.5%	76.9%	DFS, OS	pCR status (neoadjuvant)	Moderate
Imamura et al. (2018)^46	Observational: retrospective	1076	I-III	79.3%	83.4%	DFS	tumor size, LN metastasis, tumor grade, ER, PgR, chemotherapy, CEA, CA15-3	Moderate
Kurozumi et al. (2018)^47	Observational: prospective	107	I-III	100.0%	100.0%	RFS, BCSS	residual tumor size, residual node status, residual Ki-67 level, PgR, preoperative endocrine prognostic index	High
Yamada et al. (2018)^48	Observational: retrospective	1806	I-III	100.0%	100.0%	RFS	ER/PgR, tumor size, number of involved LNs, histological grade, postoperative radiation therapy, neoadjuvant/adjuvant chemotherapy, adjuvant hormonal therapy	Moderate
Arima et al. (2019)^49	Observational: retrospective	1866	I-III	100.0%	100.0%	DFS	regimen (endocrine vs endocrine + chemo), PgR/Ki-67	Moderate
Fujimoto et al. (2019)^50	Observational: retrospective	717	I-III	81.3%	85.2%	DFS, OS	menopausal status, tumor size, LN metastasis, nuclear grade, ER, HER2, adjuvant chemotherapy, TILs	High
Naoi et al. (2019)^51	Observational: retrospective	257	II-III	100.0%	80.1%	distant recurrence rate, pCR	menopause, tumor size, histological grade, PgR, Ki-67, 95GC score	Moderate
Ohara et al. (2019)^52	Observational: retrospective	124	I-III	100.0%	75.0%	DDFS, pCR	RCB, menstrual status, T, N, histological grade, PgR, HER2, Ki-67, TILs, PAM50	High
Takuwa et al. (2019)^53	Observational: retrospective	418	0-III	100.0%	100.0%	DFS, OS, BCSS	radiotherapy	Moderate
Horimoto et al. (2020)^54	Observational: prospective	117	I-III	100.0%	100.0%	DFS	age, tumor size, LN metastasis, tumor grade, FOXA1	High
Ishiguro et al. (2020)^55	Interventional: RCT Phase II	193	I-III	100.0%	100.0%	pCR	NAC	Moderate
Sugano et al. (2020)^56	Observational: retrospective	336	I-II	100.0%	100.0%	DFS, BCSS	histological grade, nuclear grade, ACTN4, age, menopausal status, area of invasive tumor, histology, lymphovascular invasion, Ki-67	Moderate
Fujihara et al. (2021)^57	Observational: retrospective	120	0-III	85.3%	81.6%	local RFS	lymphatic vessel invasion, surgical margin lateral, surgical margin vertical, age, MRI findings, histology, tumor size, nodal status, stage, ER, PgR, HER2, subtype, EIC, nuclear grade, operation, adjuvant hormonal therapy, chemotherapy	High
Takahashi et al. (2021)^58	Observational: prospective	189	I-II	73.0%	90.5%	RFS	pathological stage, pathological LN, TP53 status, tumor size, histological grade, ER, PgR, HER2, Ki-67, adjuvant chemotherapy, adjuvant endocrine therapy	Moderate
Tanaka et al. (2021)^59	Observational: retrospective	169	I-III	100.0%	100.0%	DDFS, DFS	Ki-67, podoplanin, age, tumor size, lymphatic invasion, histological grade, Ki-67, PgR, TILs, adjuvant chemotherapy	Moderate
Toi et al. (2021)^60	Interventional: RCT Phase III	1930	I-III	100.0%	100.0%	invasive DFS, OS	regimen (endocrine vs endocrine + S-1)	Low
Kurozumi et al. (2022)^61	Observational: retrospective	142	I-III	100.0%	100.0%	BCSS	LAT1 expression, Ki-67, PgR, tumor size, nodal status, histological grade	High
Sueta et al. (2022)^62	Observational: retrospective	95	I-III	66.3%	100.0%	pCR, RFS, BCSS	tumor size, LN metastasis, histological grade, Ki-67, tumor subtype, response (NAC), BRCAness	High
Yamamoto et al. 2022^63	Observational: retrospective	57	I-III	100.0%	100.0%	RFS, OS	clinical stage, pathological stage, biological feature prior to NAC, biological feature following NAC	High

Abbreviations. HR: hormone receptor; RoB: risk of bias; RCT: randomized controlled trial; DFS: disease-free survival; RFS: relapse-free survival; OS: overall survival; IBTR: ipsilateral breast tumor recurrence; DDFS: distant disease-free survival; BCSS: breast cancer-specific survival; pCR: pathological complete response; pT: pathological tumor; LN: lymph node; FOXA1: Forkhead box protein A1; ER: estrogen receptor; HER2: human epidermal growth factor receptor 2; PgR: progesterone receptor; LOH: loss of heterozygosity; CEA: carcinoembryonic antigen; TPA: tissue polypeptide antigen; CA15-3: carbohydrate antigen 15-3; pN: pathological node; GATA-3: GATA-binding protein 3; bcl-2: B cell lymphoma 2; MAPT: microtubule-associated protein tau; SUVmax: maximum standardized uptake value; BMI: body mass index; ALDH1: aldehyde dehydrogenase 1; TILs: tumor-infiltrating lymphocytes; 95GC: 95‑gene classifier; RCB: residual cancer burden; PAM50: prediction analysis of microarray 50; NAC: neoadjuvant chemotherapy; ACTN4: actinin-4; MRI: magnetic resonance imaging; EIC: extensive intraductal component; LAT1: L-type amino acid transporter 1; BRCA: breast cancer susceptibility.

Figure 2. Forest plots for relationships between various factors and RFS/DFS in multivariable analyses. HRs represented by gray boxes; size of boxes correlated with weight; length of lines represents 95% CIs; diamonds indicate pooled HRs. (A) Lymph node metastasis; yes vs no (reference). (B) Tumor size; large vs small (reference). (C) Ki-67; high vs low (reference). (D) Adjuvant chemotherapy; yes vs no (reference). (E) PgR status; high vs low (reference). (F) Histological grade; high vs low (reference). (G) Nuclear grade; high vs low (reference). PgR: progesterone receptor; RFS/DFS; relapse-free survival or disease-free survival; HR: hazard ratio; CI: confidence interval; HK: Hartung-Knapp.

Table 2. Results of meta-analysis by outcomes and factors.

Factor	RFS/DFS		OS		BCSS
	Multivariable	Univariable	Multivariable	Univariable	Multivariable	Univariable
Lymph node metastasis yes vs no (reference)	K = 15, 2.76 [1.97; 3.88]	K = 10, 3.15 [1.99; 4.99]	K = 6, 2.43 [1.28; 4.63]	K = 4, 3.89 [2.76; 5.47]	K = 2	K = 3
Tumor size large vs small (reference)	K = 12, 1.67 [1.24; 2.23]	K = 14, 2.27 [1.60; 3.21]	K = 6, 1.80 [1.24; 2.62]	K = 4, 2.48 [1.34; 4.57]	K = 3	K = 6, 2.39 [1.17; 4.87]
Ki-67 high vs low (reference)	K = 7, 1.50 [0.94; 2.41]	K = 10, 2.65 [1.76; 4.00]			K = 5, 2.12 [0.53; 8.49]	K = 6, 3.76 [1.79; 7.93]
Adjuvant chemotherapy yes vs no (reference)	K = 6, 0.81 [0.47; 1.38]	K = 6, 1.19 [0.54; 2.61]
Adjuvant endocrine therapy yes vs no (reference)	K = 3	K = 3
PgR status high vs low (reference)	K = 4, 0.60 [0.29; 1.22]	K = 9, 0.51 [0.27; 0.96]			K = 4, 0.20 [0.10; 0.42]	K = 4, 0.14 [0.03; 0.73]
Histological grade high vs low (reference)	K = 9, 1.50 [1.04; 2.16]	K = 9, 1.90 [1.49; 2.41]	K = 5, 2.02 [1.44; 2.84]	K = 3	K = 5, 2.28 [0.60; 8.69]	K = 5, 5.63 [2.24; 14.13]
Nuclear grade high vs low (reference)	K = 5, 2.02 [1.61; 2.54]	K = 6, 2.06 [1.31; 3.24]			K = 2	K = 3
Menopausal status post vs pre (reference)	K = 3	K = 7, 1.06 [0.84; 1.35]	K = 3	K = 2	K = 1	K = 3
Age high vs low (reference)	K = 2	K = 5, 0.95 [0.78; 1.14]				K = 3
Histology IDC vs other (reference)		K = 3				K = 3
Lymphovascular invasion yes vs no (reference)		K = 3			K = 1	K = 2

Quantitative synthesis results expressed as hazard ratio [95% confidence interval]. RFS/DFS: relapse-free survival or disease-free survival; OS: overall survival; BCSS: breast cancer-specific survival; K: number of studies; PgR: progesterone receptor; IDC: invasive ductal carcinoma.

Figure 3. Forest plots for relationships between various factors and OS in multivariable analyses. HRs represented by gray boxes; size of boxes correlated with weight; length of lines represents 95% CIs; diamonds indicate pooled HRs. (A) Lymph node metastasis; yes vs no (reference). (B) Tumor size; large vs small (reference). (C) Histological grade; high vs low (reference). OS: overall survival; HR: hazard ratio; CI: confidence interval; HK: Hartung-Knapp.

Figure 4. Forest plots for relationships between various factors and BCSS in multivariable analyses. HRs represented by gray boxes; sizes of boxes correlated with weight; lengths of lines represent 95% CIs; diamonds indicate pooled HRs. (A) Ki-67; high vs low (reference). (B) PgR status; high vs low (reference). (C) Histological grade; high vs low (reference). PgR: progesterone receptor; BCSS: breast cancer-specific survival; HR: hazard ratio; CI: confidence interval; HK: Hartung-Knapp.

Shibuta K, Ueo H, Furusawa H, et al. The relevance of intrinsic subtype to clinicopathological features and prognosis in 4,266 Japanese women with breast cancer. Breast Cancer. 2011;18(4):292–298. doi: 10.1007/s12282-010-0209-6.

 PubMed Web of Science ®Google Scholar

Tokiniwa H, Horiguchi J, Takata D, et al. Topoisomerase II alpha expression and the Ki-67 labeling index correlate with prognostic factors in estrogen receptor-positive and human epidermal growth factor type-2-negative breast cancer. Breast Cancer. 2012;19(4):309–314. doi: 10.1007/s12282-011-0291-4.

 PubMed Web of Science ®Google Scholar

Hisamatsu Y, Tokunaga E, Yamashita N, et al. Impact of FOXA1 expression on the prognosis of patients with hormone receptor-positive breast cancer. Ann Surg Oncol. 2012;19(4):1145–1152. doi: 10.1245/s10434-011-2094-4.

 PubMed Web of Science ®Google Scholar

Ishitobi M, Ohsumi S, Inaji H, et al. Ipsilateral breast tumor recurrence (IBTR) in patients with operable breast cancer who undergo breast-conserving treatment after receiving neoadjuvant chemotherapy: risk factors of IBTR and validation of the MD Anderson prognostic index. Cancer. 2012;118(18):4385–4393. doi: 10.1002/cncr.27377.

 PubMed Web of Science ®Google Scholar

Masuda N, Sagara Y, Kinoshita T, et al. Neoadjuvant anastrozole versus tamoxifen in patients receiving goserelin for premenopausal breast cancer (STAGE): a double-blind, randomised phase 3 trial. Lancet Oncol. 2012;13(4):345–352. doi: 10.1016/S1470-2045(11)70373-4.

 PubMed Web of Science ®Google Scholar

Tokunaga E, Okada S, Yamashita N, et al. High incidence and frequency of LOH are associated with aggressive features of high-grade HER2 and triple-negative breast cancers. Breast Cancer. 2012;19(2):161–169. doi: 10.1007/s12282-010-0232-7.

 PubMed Web of Science ®Google Scholar

Kikuchi S, Nishimura R, Osako T, et al. Definition of p53 overexpression and its association with the clinicopathological features in luminal/HER2-negative breast cancer. Anticancer Res. 2013;33:3891–3897.

 PubMed Web of Science ®Google Scholar

Satoh K, Tanaka M, Yano A, et al. Treatment when prognostic factors do not match St. Gallen recommendations: profiling of prognostic factors among HR(+) and HER2(–) breast cancer patients. World J Surg. 2013;37(3):516–524. doi: 10.1007/s00268-012-1881-9.

 PubMed Web of Science ®Google Scholar

Kurebayashi J, Kanomata N, Shimo T, et al. Marked lymphovascular invasion, progesterone receptor negativity, and high Ki67 labeling index predict poor outcome in breast cancer patients treated with endocrine therapy alone. Breast Cancer. 2014;21(2):214–222. doi: 10.1007/s12282-012-0380-z.

 PubMed Web of Science ®Google Scholar

Niikura N, Masuda S, Kumaki N, et al. Prognostic significance of the Ki67 scoring categories in breast cancer subgroups. Clin Breast Cancer. 2014;14(5):323–329.e3. doi: 10.1016/j.clbc.2013.12.013.

 PubMed Web of Science ®Google Scholar

Nishimiya H, Kosaka Y, Yamashita K, et al. Prognostic significance of Ki-67 in chemotherapy-naïve breast cancer patients with 10-year follow-up. Anticancer Res. 2014;34:259–268.

 PubMed Web of Science ®Google Scholar

Hisamatsu Y, Tokunaga E, Yamashita N, et al. Impact of GATA-3 and FOXA1 expression in patients with hormone receptor-positive/HER2-negative breast cancer. Breast Cancer. 2015;22(5):520–528. doi: 10.1007/s12282-013-0515-x.

 PubMed Web of Science ®Google Scholar

Honma N, Horii R, Ito Y, et al. Differences in clinical importance of bcl-2 in breast cancer according to hormone receptors status or adjuvant endocrine therapy. BMC Cancer. 2015;15(1):698. doi: 10.1186/s12885-015-1686-y.

 PubMedGoogle Scholar

Kawase M, Toyama T, Takahashi S, et al. FOXA1 expression after neoadjuvant chemotherapy is a prognostic marker in estrogen receptor-positive breast cancer. Breast Cancer. 2015;22(3):308–316. doi: 10.1007/s12282-013-0482-2.

 PubMed Web of Science ®Google Scholar

Nishimukai A, Yagi T, Yanai A, et al. High Ki-67 expression and low progesterone receptor expression could independently lead to a worse prognosis for postmenopausal patients with estrogen receptor-positive and HER2-negative breast cancer. Clin Breast Cancer. 2015;15(3):204–211. doi: 10.1016/j.clbc.2014.12.007.

 PubMed Web of Science ®Google Scholar

Ono M, Tsuda H, Yunokawa M, et al. Prognostic impact of Ki-67 labeling indices with 3 different cutoff values, histological grade, and nuclear grade in hormone-receptor-positive, HER2-negative, node-negative invasive breast cancers. Breast Cancer. 2015;22(2):141–152. doi: 10.1007/s12282-013-0464-4.

 PubMed Web of Science ®Google Scholar

Higuchi T, Nishimukai A, Ozawa H, et al. Prognostic significance of preoperative 18F-FDG PET/CT for breast cancer subtypes. Breast. 2016;30:5–12. doi: 10.1016/j.breast.2016.08.003.

 PubMed Web of Science ®Google Scholar

Kawai M, Tomotaki A, Miyata H, et al. Body mass index and survival after diagnosis of invasive breast cancer: a study based on the Japanese national clinical database–breast cancer registry. Cancer Med. 2016;5(6):1328–1340. doi: 10.1002/cam4.678.

 PubMed Web of Science ®Google Scholar

Miyoshi Y, Shien T, Ogiya A, et al. Differences in expression of the cancer stem cell marker aldehyde dehydrogenase 1 among estrogen receptor-positive/human epidermal growth factor receptor type 2-negative breast cancer cases with early, late, and no recurrence. Breast Cancer Res. 2016;18(1):73. doi: 10.1186/s13058-016-0731-3.

 PubMedGoogle Scholar

Okuma HS, Koizumi F, Hirakawa A, et al. Clinical and microarray analysis of breast cancers of all subtypes from two prospective preoperative chemotherapy studies. Br J Cancer. 2016;115(4):411–419. doi: 10.1038/bjc.2016.184.

 PubMed Web of Science ®Google Scholar

Sato K, Miyashita M, Ishida T, et al. Prognostic significance of the progesterone receptor status in Ki67-high and low luminal B-like HER2-negative breast cancers. Breast Cancer. 2016;23(2):310–317. doi: 10.1007/s12282-014-0575-6.

 PubMed Web of Science ®Google Scholar

Kurozumi S, Matsumoto H, Hayashi Y, et al. Power of PgR expression as a prognostic factor for ER-positive/HER2-negative breast cancer patients at intermediate risk classified by the Ki67 labeling index. BMC Cancer. 2017;17(1):354. doi: 10.1186/s12885-017-3331-4.

 PubMedGoogle Scholar

Ono M, Tsuda H, Yoshida M, et al. Prognostic significance of progesterone receptor expression in estrogen-receptor positive, HER2-negative, node-negative invasive breast cancer with a low Ki-67 labeling index. Clin Breast Cancer. 2017;17(1):41–47. doi: 10.1016/j.clbc.2016.06.012.

 PubMed Web of Science ®Google Scholar

Hayashi N, Takahashi Y, Matsuda N, et al. The prognostic effect of changes in tumor stage and nodal status after neoadjuvant chemotherapy in each primary breast cancer subtype. Clin Breast Cancer. 2018;18(2):e219–29–e229. doi: 10.1016/j.clbc.2017.09.013.

 Web of Science ®Google Scholar

Imamura M, Morimoto T, Nomura T, et al. Independent prognostic impact of preoperative serum carcinoembryonic antigen and cancer antigen 15-3 levels for early breast cancer subtypes. World J Surg Oncol. 2018;16(1):26. doi: 10.1186/s12957-018-1325-6.

 PubMedGoogle Scholar

Kurozumi S, Matsumoto H, Inoue K, et al. Impact of combining the progesterone receptor and preoperative endocrine prognostic index (PEPI) as a prognostic factor after neoadjuvant endocrine therapy using aromatase inhibitors in postmenopausal ER positive and HER2 negative breast cancer. PLoS One. 2018;13(8):e0201846. doi: 10.1371/journal.pone.0201846.

 PubMed Web of Science ®Google Scholar

Yamada Y, Mukai H, Tokudome Y, et al. Improved overall survival over recent decades in patients with hormone-receptor-positive, HER2-negative breast cancer: a single-center retrospective analysis of prognostic factors. Jpn J Clin Oncol. 2018;48(3):248–254. doi: 10.1093/jjco/hyy001.

 PubMed Web of Science ®Google Scholar

Arima N, Nishimura R, Osako T, et al. Ki-67 index value and progesterone receptor status can predict prognosis and suitable treatment in node-negative breast cancer patients with estrogen receptor-positive and HER2-negative tumors. Oncol Lett. 2019;17:616–622.

 PubMed Web of Science ®Google Scholar

Fujimoto Y, Watanabe T, Hida AI, et al. Prognostic significance of tumor-infiltrating lymphocytes may differ depending on Ki67 expression levels in estrogen receptor-positive/HER2-negative operated breast cancers. Breast Cancer. 2019;26(6):738–747. doi: 10.1007/s12282-019-00977-0.

 PubMed Web of Science ®Google Scholar

Naoi Y, Saito Y, Kishi K, et al. Development of recurrence risk score using 95‑gene classifier and its application to formalin‑fixed paraffin‑embedded tissues in ER‑positive, HER2‑negative and node‑negative breast cancer. Oncol Rep. 2019;42(6):2680–2685. doi: 10.3892/or.2019.7358.

 PubMed Web of Science ®Google Scholar

Ohara AM, Naoi Y, Shimazu K, et al. PAM50 for prediction of response to neoadjuvant chemotherapy for ER-positive breast cancer. Breast Cancer Res Treat. 2019;173(3):533–543. doi: 10.1007/s10549-018-5020-7.

 PubMed Web of Science ®Google Scholar

Takuwa H, Tsuji W, Yotsumoto F, et al. Prevention of locoregional recurrence and distant metastasis in japanese breast cancer patients using Japanese standard postoperative radiation fields: experience at a single institution. Cancer Rep. 2019;2:e1191.

 Google Scholar

Horimoto Y, Sasahara N, Sasaki R, et al. High FOXA1 protein expression might predict late recurrence in patients with estrogen-positive and HER2-negative breast cancer. Breast Cancer Res Treat. 2020;183(1):41–48. doi: 10.1007/s10549-020-05751-x.

 PubMed Web of Science ®Google Scholar

Ishiguro H, Masuda N, Sato N, et al. A randomized study comparing docetaxel/cyclophosphamide (TC), 5-fluorouracil/epirubicin/cyclophosphamide (FEC) followed by TC, and TC followed by FEC for patients with hormone receptor-positive HER2-negative primary breast cancer. Breast Cancer Res Treat. 2020;180(3):715–724. doi: 10.1007/s10549-020-05590-w.

 PubMed Web of Science ®Google Scholar

Sugano T, Yoshida M, Masuda M, et al. Prognostic impact of ACTN4 gene copy number alteration in hormone receptor-positive, HER2-negative, node-negative invasive breast carcinoma. Br J Cancer. 2020;122(12):1811–1817. doi: 10.1038/s41416-020-0821-y.

 PubMed Web of Science ®Google Scholar

Fujihara M, Yamasaki R, Ito M, et al. Risk factors of local recurrence following implant-based breast reconstruction in breast cancer patients. BMC Womens Health. 2021;21:147.

 PubMed Web of Science ®Google Scholar

Takahashi S, Fukui T, Nomizu T, et al. TP53 signature diagnostic system using multiplex reverse transcription–polymerase chain reaction system enables prediction of prognosis of breast cancer patients. Breast Cancer. 2021;28(6):1225–1234. doi: 10.1007/s12282-021-01250-z.

 PubMed Web of Science ®Google Scholar

Tanaka Y, Ohno T, Kadonaga T, et al. Podoplanin expression in cancer-associated fibroblasts predicts unfavorable prognosis in node-negative breast cancer patients with hormone receptor-positive/HER2 − negative subtype. Breast Cancer. 2021;28(4):822–828. doi: 10.1007/s12282-021-01217-0.

 PubMed Web of Science ®Google Scholar

Toi M, Imoto S, Ishida T, et al. Adjuvant S-1 plus endocrine therapy for oestrogen receptor-positive, HER2-negative, primary breast cancer: a multicentre, open-label, randomised, controlled, phase 3 trial. Lancet Oncol. 2021;22(1):74–84. doi: 10.1016/S1470-2045(20)30534-9.

 PubMed Web of Science ®Google Scholar

Kurozumi S, Kaira K, Matsumoto H, et al. Association of L-type amino acid transporter 1 (LAT1) with the immune system and prognosis in invasive breast cancer. Sci Rep. 2022;12(1):2742. doi: 10.1038/s41598-022-06615-8.

 PubMed Web of Science ®Google Scholar

Sueta A, Yamamoto-Ibusuki M, Tomiguchi M, et al. Predictive and prognostic significance of BRCAness in HER2-negative breast cancer. Breast Cancer. 2022;29(2):368–376. doi: 10.1007/s12282-021-01319-9.

 PubMed Web of Science ®Google Scholar

Yamamoto S, Chishima T, Shibata Y, et al. Stratification of prognosis by biological features following neoadjuvant chemotherapy in luminal breast cancer. In Vivo. 2022;36(2):859–864. doi: 10.21873/invivo.12774.

 PubMed Web of Science ®Google Scholar

Data availability statement

The datasets used and/or analyzed during this study are available from the corresponding author upon reasonable request.