Postmenopausal Breast Cancer in Women, Clinical and Epidemiological Factors...

[Full title: Postmenopausal Breast Cancer in Women, Clinical and Epidemiological Factors Related to the Molecular Subtype: A Retrospective Cohort Study in a Single Institution for 13 Years. Follow-Up Data]

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International Journal of Environmental Research and Public Health Article Postmenopausal Breast Cancer in Women, Clinical and Epidemiological Factors Related to the Molecular Subtype: A Retrospective Cohort Study in a Single Institution for 13 Years. Follow-Up Data Cristina Marinela Oprean 1,2,3, † , Serban Mircea Negru 2,3,4, † , Dorel Ionel Popovici 2,3,4 , Sorin Saftescu 2,3,4 , Robert-Alexandru Han 3 , Gabriel-Mugurel Dragomir 5 , Teodora Hoinoiu 6, * and Alis Dema 1 1 Discipline of Morpho-pathology, “Victor Babe¸s” University of Medicine and Pharmacy, Eftimie Murgu Sq. No.2, 300041 Timi¸soara, Romania; cristina.oprean@oncohelp.ro (C.M.O.); dema.alis@umft.ro (A.D.) 2 Department of Oncology—ONCOMED Outpatient Unit, Ciprian Porumbescu Street, No. 59, 300239 Timisoara, Romania; serban.negru@oncohelp.ro (S.M.N.); dorel.popovici@oncohelp.ro (D.I.P.); sorin.saftescu@oncohelp.ro (S.S.) 3 Department of Oncology—ONCOHELP Hospital Timisoara, Ciprian Porumbescu Street, No. 59, 300239 Timisoara, Romania; robert.han@oncohelp.ro 4 Discipline of Oncology, “Victor Babe¸s” University of Medicine and Pharmacy, Eftimie Murgu Sq. No.2, 300041 Timi¸soara, Romania 5 Department of Teaching Training—POLYTEHNICAL, University of Timisoara, 300223 Timisoara, Romania; mugur.dragomir@upt.ro 6 Department of Clinical Practical Skills, “Victor Babe¸s” University of Medicine and Pharmacy, Eftimie Murgu Sq. Nr.2, 300041 Timi¸soara, Romania * Correspondence: tstoichitoiu@umft.ro; Tel / Fax: + 40-256-216510 † These authors’ contributions are equally credited to this work Received: 13 October 2020; Accepted: 19 November 2020; Published: 24 November 2020 Abstract: This study focused on the characteristics of postmenopausal breast cancer in the population of southeastern Europe. This retrospective study explored the clinical, epidemiological, and molecular characteristics of women with postmenopausal breast cancer. Material and methods: A retrospective cohort study was performed on 721 postmenopausal breast cancer patients selected from the database of our institution. The data collected consisted of age, living environment, location of the breast tumor, stage of the disease, and molecular sub-type. Patient characteristics were collected based on a systematic chart audit from medical records. The data were analyzed using SPSS 20.0 and Pearson analysis. Results: The most frequent age range for breast cancer diagnosis was 51 to 70 years old. Most of the patients (80.7%) came from an urban environment. The vast majority of patients were initially diagnosed in stage II (40.3%) and III (30.3%). The most frequent molecular sub-types were luminal B (39%) and luminal A (35.4%). Almost half of the breast tumors were located in the upper outer quadrant (48.8%). Conclusions: The results of this study describe the profile of patients in southeastern Europe within our institution diagnosed with postmenopausal breast cancer. In our study, patients were first diagnosed with more advanced stages of breast cancer compared with other European countries Keywords: breast cancer; postmenopausal status; molecular subtype; stage; location; prognostic factor Int. J. Environ. Res. Public Health 2020 , 17 , 8722; doi:10.3390 / ijerph 17238722 www.mdpi.com / journal / ijerph

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Int. J. Environ. Res. Public Health 2020 , 17 , 8722 2 of 10 1. Introduction Breast cancer is the most common type of cancer in the world, becoming the leading cause of cancer-related deaths among women in the world, as well as in southeastern Europe [ 1 ]. The incidence of breast cancer is the highest in economically developed countries. Due to delayed methods of diagnosing breast cancer, we are witnessing an increased incidence of advanced development of this disease in developing and low-income countries [ 2 ]. Globally, the incidence of breast cancer has di ff erent rates of occurrence [ 3 ]. According to GLOBOCAN 2018, 9629 new cases were registered in Romania, ranking second after lung cancer [ 4 ]. Age is an important factor in the heterogeneity of breast cancer. Breast cancer in older women appears biologically distinct from breast cancer in younger women [ 5 ]. Women have an increased risk of developing cancer as they age [ 6 ]. The luminal A breast cancer subtype is encountered more frequently in postmenopausal women [ 7 ]. A study conducted in Japan that looked at the prognostic value of KI-67 found that patients over 65 years of age develop tumors with a lower proliferation rate; there was no di ff erence in the KI-67 tumor index for patients aged 36–50 and 50–65 years [ 8 ]. In a study focused on the population of breast cancer patients in India, the diagnoses of most (75%) breast cancer patients occurred in stage III. Stage IV disease was diagnosed only in postmenopausal women [ 9 ]. Studies have compared the clinical and pathological characteristics of postmenopausal breast cancer patients with those of premenopausal patients, rather than describing them independently Data regarding the characteristics of postmenopausal breast cancer in the Romanian population are insu ffi cient. The primary aim of this study was to explore the clinical, epidemiological, and molecular characteristics of the women diagnosed with postmenopausal breast cancer registered in our oncological database. Secondly, we aimed to identify whether a relationship exists between these characteristics 2. Materials and Methods This study was a retrospective observational study performed in a single institution—a general oncology specialized center 2.1. Patients We investigated the medical records of 1000 breast cancer patients registered in the database of our clinic that were admitted between May 2004 and December 2017. A total of 271 patients diagnosed with premenopausal breast cancer and 8 male patients were excluded from our study The data of the 721 patients selected, diagnosed with postmenopausal breast cancer and for whom complete clinical records were available, were statistically processed using SPSS 20.0. A trained medical registrar performed data collection between December 2017 and July 2018. To avoid any potential sources of bias, a senior and a junior medical oncologist independently performed a review and a double-check of the accuracy of the collected data. We finalized this process in July 2019. The source documents are the patients’ outpatient paper charts Postmenopausal status was defined as physiological or early menopause at the time of each patient’s diagnosis [ 6 ]. The main causes for premature menopause were: previous medical conditions, surgical procedures, such as total hysterectomy or bilateral oophorectomy, or pelvic radiotherapy [ 10 ]. The Steering Committee of the Outpatient Unit approved this retrospective study in July 2017, the date the study was performed. The retrospective data were collected and reviewed in compliance with the ethical standards set out by the Steering Committee of the institution and with the Declaration of Helsinki. For this retrospective study, the patients’ consent for the review of their medical records was not required by the Steering Committee of the institution 2.2. Data Collection The epidemiological data that we considered for this study were: age, defined as the age at the time of diagnosis, and living environment (rural or urban). Areas forming settlements with populations

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Int. J. Environ. Res. Public Health 2020 , 17 , 8722 3 of 10 of over 10,000 are urban, as defined by the O ffi ce for National Statistics urban area boundaries based on land use. The remainder is defined as a rural town and fringe, village, or hamlet and dispersed using detailed postcode data. The clinical data collected were: location of the breast tumor and stage of the disease at the time of diagnosis. The information about the tumor location inside the quadrant (tumor site) was obtained from mammographies, MRI, and breast ultrasounds undergone by the patients during their initial consultation at the time of diagnosis. The clinical data recorded in the oncology outpatient charts or the surgery medical letters were also used as a source of documentation TNM classifications, both clinically and / or pathologically, were used for establishing the stage of the disease. For the patients who underwent surgical treatment, the pathological TNM was used; for the remaining patients, we used the clinical TNM. Depending on the year of diagnosis, we used the 5 th, 6 th, and 7 th AJCC TNM classification [ 11 – 13 ]. The molecular subtype was classified for invasive tumors according to the 2017 St. Gallen Consensus meeting, depending on the ER, PR, KI-67, and HER 2 status [ 14 ]. According to this classification, patients were divided into five subgroups: luminal A, luminal B, luminal HERpositive, non-luminal HER 2-positive, and triple-negative breast cancer These parameters were obtained from the immunohistochemistry (IHC) examination of the breast cancer tissue sample. The tissue was examined in 2–3 external laboratories located in Timisoara, Romania. All these labs used the manual or automatic platforms for the IHC results. ER and / or PR were considered positive when the value was > 1%. The cut-o ff value for KI-67 to define luminal A to luminal B tumors was considered to be 20%. To distinguish HER 2-positive from HER 2-negative tumors, pathologists performed IHC and in situ hybridization tests and use the ASCO / CAP guidelines valid at the time of the examination 2.3. Statistical Analysis The data were statistically processed using SPSS 20.0. Descriptive statistics were used to group subjects by categories such as age, living environment, tumor location, stage of the disease, and molecular subtype. The method of association tables, related to descriptive statistics, was also used. Pearson correlation analysis was used to assess the correlation between various parameters (age and stage, age and molecular subtype, stage and molecular subtype), where p < 0.05 was considered to define the statistical significance di ff erence 3. Results The mean age was 62.6 years, and the age range was 33–87 years. Distribution by age groups is shown in Table 1 . Out of a total of 721 patients, the majority of patients, i.e., 581 (80.7%), came from an urban environment and only 139 (19.3%) from a rural area. This information was missing for only one patient (0.1%) Table 1. Patient distribution by age group Age at Diagnosis Patients N = 721 Percent % 0–40 years 7 1.0 41–50 years 50 6.9 51–60 years 257 35.6 61–70 years 257 35.6 71–80 years 129 17.9 81–90 years 21 2.9 Total 721 100.0 The analysis of the di ff erent age groups and molecular subtypes showed that in the youngest age group, i.e., 30 to 40 years, the luminal HER 2-positive subtype was prevalent. In the middle age group

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Int. J. Environ. Res. Public Health 2020 , 17 , 8722 4 of 10 (41–50 and 51–60 years), the luminal B subtype prevailed. For the next two patient groups, 61–70 and 71–80, most of the patients had the luminal A subtype. The oldest age group, 81–90 years, showed a predominant luminal B subtype. The data are summarized in Table 2 . Table 2. Age groups and luminal subtypes Molecular Subtype Age at Diagnosis Luminal A Luminal B Luminal HER-Positive Non-Luminal HER-Positive Triple Negative Total 30–40 years N 2 1 3 0 0 6 % 33.3% 16.7% 50.0% 0.0% 0.0% 100.0% 41–50 years N 12 21 9 3 2 47 % 25.5% 44.7% 19.1% 6.4% 4.3% 100.0% 51–60 years N 76 108 28 12 26 250 % 30.4% 43.2% 11.2% 4.8% 10.4% 100.0% 61–70 years N 105 96 29 8 16 254 % 41.3% 37.8% 11.4% 3.1% 6.3% 100.0% 71–80 years N 54 48 5 7 7 121 % 44.6% 39.7% 4.1% 5.8% 5.8% 100.0% 81–90 years N 6 7 3 1 1 18 % 33.3% 38.9% 16.7% 5.6% 5.6% 100.0% Total N 255 281 77 31 52 696 % 36.6% 40.4% 11.1% 4.5% 7.5% 100.0% The correlation between age groups and molecular subtypes showed an inversely proportional relationship between the two variables (r = − 0.114*, p < 0.01, Table 3 ). Table 3. Correlation between age at diagnosis and molecular subtype Correlations Age at Diagnosis Molecular Subtype Age at Diagnosis Pearson Correlation 1 − 0.114 * Sig. (2-tailed) 0.003 N 721 696 Luminal Pearson Correlation − 0.114 ** 1 Sig. (2-tailed) 0.003 N 696 696 * The correlation is significant at the 0.01 level (2-tailed). ** The correlation is significant at the 0.01 level (2-tailed) The majority of patients with stage 0, I breast cancer were in the 61–70 years age group. An initial diagnosis of stage II or III breast cancer prevailed for the 51–60 years age group. Most patients in stage IV were in the 61–70 years age group. The data are summarized in Table 4 . Using Pearson correlation, no statistically significant correlation was established between the stage of the disease and age at diagnosis, the significant threshold being p = 0.322 ( p > 0.05; Table 5 ).

Int. J. Environ. Res. Public Health 2020 , 17 , 8722 5 of 10 Table 4. Stage related to age Stage Age at Diagnosis (years) Total 30–40 41–50 51–60 61–70 71–80 81–90 0 N 0 0 1 2 1 0 4 % 0.0% 0.0% 25.0% 50.0% 25.0% 0.0% 100.0% I N 0 2 28 38 13 2 83 % 0.0% 2.4% 33.7% 45.8% 15.7% 2.4% 100.0% II N 2 23 105 103 53 5 291 % 0.7% 7.9% 36.1% 35.4% 18.2% 1.7% 100.0% III N 3 14 81 69 41 10 218 % 1.4% 6.4% 37.2% 31.7% 18.8% 4.6% 100.0% III N 3 14 81 69 41 10 218 % 1.4% 6.4% 37.2% 31.7% 18.8% 4.6% 100.0% IV N 1 10 37 42 17 3 110 % 0.9% 9.1% 33.6% 38.2% 15.5% 2.7% 100.0% Total N 6 49 252 254 125 20 706 % 0.8% 6.9% 35.7% 36.0% 17.7% 2.8% 100.0% Table 5. Correlation between the stage of the disease and age at diagnosis Correlations Patients N Age at Diagnosis Stage Pearson Correlation 1 − 0.037 Sig. (2-tailed) - 0.322 N 706 706 Age at Diagnosis Pearson Correlation − 0.037 1 Sig. (2-tailed) 0.322 N 706 721 Among the 721 patients selected, 509 (70.6%) were diagnosed in stages II and III. The distribution of patients by stage is summarized in Table 6 . Table 6. Stage of the disease at diagnosis Correlations Stage of the Disease Patients, N Percent, % Stage 0 4 0.6 I 83 11.5 II A 171 23.7 II B 120 16.6 III A 87 12.1 III B 111 15.4 III C 20 2.8 IV 110 15.3 Total 706 98 Not evaluable 15 2.0 Total 721 100.0 The analysis of the molecular subtype revealed that the most predominant molecular subtype in this postmenopausal population was luminal B, 281 patients (39%), closely followed by luminal A with 255 patients (35.4%). The result of the molecular subtype distribution is shown in Table 7 .

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Int. J. Environ. Res. Public Health 2020 , 17 , 8722 6 of 10 Table 7. Molecular subtypes of breast cancer Molecular Subtype Patients, N Percent, % Stage Luminal A 255 35.4 Luminal B 281 39.0 Luminal HER-positive 77 10.7 Non-Luminal HER-positive 31 4.3 Triple negative 52 7.2 Total 696 96.5 Not Evaluable 25 3.5 Total 721 100.0 The most frequent breast tumor location in this postmenopausal breast cancer population was the Upper-Outer quadrant (UOQ) with 352 patients (48.8%), and the least frequent was the Lower-Inner quadrant (LIQ) with 56 patients (7.8%). The results are summarized in Table 8 . Table 8. Tumor location in the breast Tumor Location, Breast Quadrant ** Patients, N Percent, % LOQ 74 10.3 UOQ 352 48.8 CQ- 94 13.0 LIQ 56 7.8 UIQ 119 16.5 BB 7 1.0 WB 11 1.5 Total 713 98.9 Not evaluable 8 1.1 Total 721 100.0 ** Breast Quadrant: LOQ—Lower-Outer Quadrant, UOQ—Upper-Outer Quadrant, CQ—Central Quadrant, LIQ—Lower-Inner Quadrant, UIQ—Upper-Inner Quadrant, BB—bilateral breast, WB—whole breast This analysis of subtypes showed that the luminal A subtype was prevalent in stages 0, I, and II The luminal B subtype was prevalent in stages III and IV. The last ones represented in all stages were the HER 2-positive and triple negative subtypes. The data are illustrated in Figure 1 . The Pearson correlation showed a small and positive correlation coe ffi cient (r = 0.089, p < 0.05). The correlation is weak, but it is statistically significant, with the significance threshold of p < 0.05 (Table 9 ). Table 9. Correlation between stage and molecular subtype Correlations Molecular Subtype Stage of the Disease Luminal Pearson Correlation 1 0.089 Sig. (2-tailed) 0.019 N 696 689 Stage of the disease Pearson Correlation 0.089 1

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Int. J. Environ. Res. Public Health 2020 , 17 , 8722 7 of 10 1 Figure 1. Stage of the disease related to molecular subtype 4. Conclusions This was a retrospective, single-institution study of postmenopausal Romanian women with breast cancer. In this study, most postmenopausal patients diagnosed with breast cancer were between 51 and 60 years of age (35.6%) and 61 and 70 years of age (35.6%). The data are similar to national Romanian statistics [ 4 , 15 ]. The highest incidence rates of breast cancer in Romania occurs in the age group > 65 years [ 16 ]. Similar data were reported in the U.K. statistics [ 17 ]. We found major di ff erences between the urban and rural population, with 80.7% of the patients coming from urban areas and only 19.3% from rural areas. An Australian study showed similar results [ 18 ]. These di ff erences can be explained by low access to mammography screening in rural areas, which accounts for determining an advanced stage of disease at diagnosis [ 19 ]. Breast cancer was often diagnosed in our study group in stages II (40.3%) and III (30.3%) The diagnosis in stage IV of the disease was found in 15.3% of the cases. Compared with other European statistics, we found a higher incidence in the advanced stages of breast cancer disease and a low percentage of patients diagnosed in stage I (11.5%) [ 17 , 20 , 21 ]. Regarding the molecular subtype distribution in our study population, the results showed a predominance of the luminal B (39%) and luminal A (35.4%) subtypes. The HER 2-positive subtype was found in 15% of the patients, with more luminal HER 2-positive (10.7%) than non-luminal HER 2-positive (4.3%) cases. The statistical data are similar to those reported in other studies [ 22 ]. Looking at the location of the primary tumor, our results showed that the most frequent location was the upper quadrants (65.3%), more in the UOQ (48.8%) than in the UIQ (16.5%). These data are in agreement with the data of the study conducted on 13,984 tumors. The results of this study, carried out using the tumor registry in Tacoma, WA, USA, showed that more than half (58%) of the breast tumors were located in the UOQ. The location of the tumor could be correlated with the survival, prognosis, stage of the disease, and positive axillary lymph nodes. Patients with a localization of the primary tumor in the UOQ have a significantly higher survival rate than women with a tumor in other

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Int. J. Environ. Res. Public Health 2020 , 17 , 8722 8 of 10 quadrants [ 23 ]. The di ff erences in survival rates depending on the location of the tumor are major, and other prognostic factors must be considered [ 24 ]. We found no statistically significant correlation between the stage of breast cancer and age group ( p > 0.05). In our study, the correlation between the age group and molecular subtype was statistically significant ( p < 0.01), meaning that the aggressiveness of breast tumors lowered with age. This result is similar to the results of studies conducted in other populations. The American study that investigated age-specific changes in intrinsic breast cancer subtypes in older women showed that age at the time of the diagnosis is not an independent prognostic factor for the outcome [ 25 ]. The stage–molecular subtype correlation was weakly positive and statistically significant ( p < 0.05). The luminal A subtype is mostly associated with early stages (0, I, and II), and luminal B with advanced stages (III and IV). More than half (53.66%) of our stage I patients had a the luminal A subtype. This result is similar to a Chinese retrospective study that concluded that there were significant di ff erences in the distribution of TNM staging among the five subtypes of breast cancer [ 26 ]. The results of this study describe the profile of Romanian patients in our institution with postmenopausal breast cancer. This population is rarely described separately from the population of other European countries. Although Romania is representative of middle-income countries, the statistical results of our study are similar to other high-income European countries. The only di ff erence is related to the stage of the disease. The patient population in our study presented with more advanced stages of the disease at diagnosis. Further prospective studies should be conducted to validate these results Author Contributions: C.M.O., R.-A.H., S.S., and T.H. double-checked the data collected, performed the literature search, and selected the references; C.M.O., R.-A.H., G.-M.D., and A.D. designed the study; C.M.O., R.-A.H., D.I.P., S.M.N., and T.H. wrote the manuscript; G.-M.D. and S.S. performed the statistical analyses and created the graphics; C.M.O., R.-A.H., S.M.N., D.I.P., and A.D. analyzed and interpreted the dataset and contributed to discussions, T.H. performed the review and editing. All authors have read and agreed to the published version of the manuscript Funding: No funding was received for this work Acknowledgments: The authors thank all the members of ONCOHELP Medical Hospital and ONCOMED SRL OUTPATIENT ONCOLOGY UNIT for supporting this study Conflicts of Interest: The authors declare no conflict of interest. The authors deny any financial interest in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript or in the decision to publish the results Abbreviations ER—Estrogen receptor; PR—Progesterone receptor; KI-67—a cell proliferation-associated antigen; MRI—magnetic resonance imaging; TNM—tumor (T), nodes (N), metastases (M); AJCC—American Joint Committee on Cancer; IHC—Immunohistochemistry; SPSS—Statistical Package for the Social Sciences; LOQ—Lower-Outer Quadrant; UOQ—Upper-Outer Quadrant; CQ—Central Quadrant; LIQ—Lower-Inner Quadrant; UIQ—Upper-Inner Quadrant; BB—bilateral breast; WB—Whole Breast References 1 Fitzmaurice, C.; Allen, C.; Barber, R.M.; Barregard, L.; Bhutta, Z.A.; Brenner, H.; Dicker, D.J.; Chimed-Orchir, O.; Dandona, R.; Fleming, T.; et al. Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-Years for 32 Cancer Groups, 1990 to 2015: A Systematic Analysis for the Global Burden of Disease Study JAMA Oncol 2017 , 3 , 524–548. [ CrossRef ] [ PubMed ] 2 Torre, L.A.; Islami, F.; Siegel, R.L.; Ward, E.M.; Jemal, A. Global Cancer in Women: Burden and Trends Cancer Epidemiol. Biomarkers Prev 2017 , 26 , 444–457. [ CrossRef ] [ PubMed ] 3 Ferlay, J.; Shin, H.-R.; Bray, F.; Forman, D.; Mathers, C.; Parkin, D.M. Estimates of Worldwide Burden of Cancer in 2008: GLOBOCAN 2008 Int. J. Cancer 2010 , 127 , 2893–2917. [ CrossRef ] [ PubMed ]

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Int. J. Environ. Res. Public Health 2020 , 17 , 8722 9 of 10 4 Bray, F.; Ferlay, J.; Soerjomataram, I.; Siegel, R.L.; Torre, L.A.; Jemal, A. Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries CA Cancer J. Clin 2018 , 68 , 394–424. [ CrossRef ] [ PubMed ] 5 Chollet-Hinton, L.; Anders, C.K.; Tse, C.-K.; Bell, M.B.; Yang, Y.C.; Carey, L.A.; Olshan, A.F.; Troester, M.A. Breast Cancer Biologic and Etiologic Heterogeneity by Young Age and Menopausal Status in the Carolina Breast Cancer Study: A Case-Control Study Breast Cancer Res 2016 , 18 , 79. [ CrossRef ] [ PubMed ] 6 Cooper, K Pathophysiology Made Incredibly Easy ; Springhouse-Lippincott Williams & Wilkins: Philadelphia, PA, USA, 1998 7 Murase, K.; Yanai, A.; Saito, M.; Imamura, M.; Miyagawa, Y.; Takatsuka, Y.; Inoue, N.; Ito, T.; Hirota, S.; Sasa, M.; et al. Biological Characteristics of Luminal Subtypes in Preand Postmenopausal Estrogen Receptor-Positive and HER 2-Negative Breast Cancers Breast Cancer 2012 , 21 , 52–57. [ CrossRef ] [ PubMed ] 8 Nishimura, R.; Osako, T.; Okumura, Y.; Hayashi, M.; Toyozumi, Y.; Arima, N. Ki-67 as a Prognostic Marker According to Breast Cancer Subtype and a Predictor of Recurrence Time in Primary Breast Cancer Exp. Ther Med 2010 , 1 , 747–754. [ CrossRef ] [ PubMed ] 9 Surakasula, A.; Nagarjunapu, G.C.; Raghavaiah, K.V. A Comparative Study of Preand Post-Menopausal Breast Cancer: Risk Factors, Presentation, Characteristics and Management J. Res. Pharm. Pract 2014 , 3 , 12–18. [ CrossRef ] [ PubMed ] 10 Okeke, T.C.; Anyaehie, U.B.; Ezenyeaku, C.C. Premature Menopause Ann. Med. Health Sci. Res 2013 , 3 , 90–95. [ CrossRef ] [ PubMed ] 11 Edge, S.B.; Byrd, D.R.; Compton, C.C.; Fritz, A.G.; Greene, F.L.; Trotti, A. (Eds.) AJCC Cancer Staging Manual , 7 th ed.; Springer: New York, NY, USA, 2010 12 Greene, F.L.; American Joint Committee on Cancer AJCC Cancer Staging Manual ; Springer: New York, NY, USA, 2020 13 Fleming, I.D.; Okeke, J.S.; Henson, D.E.; Hutter, R.V.P.; Kennedy, B.J.; Murphy, G.P.; American Joint Committee on Cancer (AJCC) (Eds.) AJCC Cancer Staging Manual , 5 th ed.; J. B. Lippincott: Philadelphia, PA, USA, 1997 14 Curigliano, G.; Burstein, H.; Winer, E.; Gnant, M.; Dubsky, P.; Loibl, S.; Colleoni, M.; Regan, M.; Piccart-Gebhart, M.; Senn, H.-J.; et al. De-Escalating and Escalating Treatments for Early-Stage Breast Cancer: The St. Gallen International Expert Consensus Conference on the Primary Therapy of Early Breast Cancer 2017 Ann. Oncol 2017 , 28 , 1700–1712. [ CrossRef ] [ PubMed ] 15 Buzas, R.; Rogobete, A.F.; Popovici, S.E.; Mateescu, T.; Hoinoiu, T.; Sorop, V.B.; Bratu, T.; Ticelea, M.; Popoiu, C.M.; Sandesc, D. Nuclear Transcription Factor Kappa B (NF- к B) and Molecular Damage Mechanisms in Acute Cardiovascular Diseases. A Review J. Cardiovasc. Emergencies 2018 , 4 , 65–72. [ CrossRef ] 16 SSPR-2017. Available online: http: // insp.gov.ro / sites / cnepss / wp-content / uploads / 2018 / 11 / SSPR-2017.pdf (accessed on 26 April 2020) 17 Breast Cancer Incidence (Invasive) Statistics. Cancer Research UK. Available online: https: // www.cancerrese archuk.org / health-professional / cancer-statistics / statistics-by-cancer-type / breast-cancer / incidence-invasive (accessed on 14 May 2015) 18 Mitchell, K.; Fritschi, L.; Reid, A.; McEvoy, S.; Ingram, D.S.; Jamrozik, K.; Clayforth, C.; Byrne, M. Rural–Urban Di ff erences in the Presentation, Management and Survival of Breast Cancer in Western Australia Breast 2006 , 15 , 769–776. [ CrossRef ] [ PubMed ] 19 Stameni´c, V.; Strnad, M. Urban-Rural Di ff erences in a Population-Based Breast Cancer Screening Program in Croatia Croat. Med. J 2011 , 52 , 76–86. [ CrossRef ] [ PubMed ] 20 Walters, S.; Maringe, C.; Butler, J.M.; Rachet, B.; Barrett-Lee, P.; Bergh, J.P.W.V.D.; Boyages, J.; Christiansen, P.; Lee, M.; Warnberg, F.; et al. Breast Cancer Survival and Stage at Diagnosis in Australia, Canada, Denmark, Norway, Sweden and the UK, 2000–2007: A Population-Based Study Br. J. Cancer 2013 , 108 , 1195–12081 [ CrossRef ] [ PubMed ] 21 Hoinoiu, T.; Grujic, D.; Prilipceanu, G.; Folescu, R.; Hoinoiu, B.; Bratu, T.; Poroch, V.; Grujic, L. The Use of Collagen-Glycosaminoglycan Biodegradable Matrix (Integra ® ) in the Management of Neck Postburn Hypertrophic Scars and Contractures Appl. Sci 2020 , 10 , 3731. [ CrossRef ] 22 Collins, L.C.; Marotti, J.D.; Gelber, S.; Cole, K.; Ruddy, K.; Kereakoglow, S.; Brachtel, E.F.; Schapira, L.; Come, S.E.; Winer, E.P.; et al. Pathologic Features and Molecular Phenotype by Patient Age in a Large Cohort of Young Women with Breast Cancer Breast Cancer Res. Treat 2011 , 131 , 1061–1066. [ CrossRef ] [ PubMed ]

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Int. J. Environ. Res. Public Health 2020 , 17 , 8722 10 of 10 23 Sohn, V.Y.; Arthurs, Z.M.; Sebesta, J.A.; Brown, T.A. Primary Tumor Location Impacts Breast Cancer Survival Am. J. Surg 2008 , 195 , 641–644. [ CrossRef ] [ PubMed ] 24 Kroman, N.; Wohlfahrt, J.; Mouridsen, H.T.; Melbye, M. Influence of Tumor Location on Breast Cancer Prognosis Int. J. Cancer 2003 , 105 , 542–545. [ CrossRef ] [ PubMed ] 25 Jenkins, E.O.; Deal, A.M.; Anders, C.K.; Prat, A.; Perou, C.M.; Carey, L.A.; Muss, H.B. Age-Specific Changes in Intrinsic Breast Cancer Subtypes: A Focus on Older Women Oncologist 2014 , 19 , 1076–1083. [ CrossRef ] [ PubMed ] 26 Li, J.; Chen, Z.; Su, K.; Zeng, J. Clinicopathological Classification and Traditional Prognostic Indicators of Breast Cancer Int. J. Clin. Exp. Pathol 2015 , 8 , 8500–8505. [ PubMed ] Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional a ffi liations © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http: // creativecommons.org / licenses / by / 4.0 / ).

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