Assessment of the predictive role of oestrogen and progesterone receptor status in breast cancer patients treated with neoadjuvant chemotherapy: A retrospective analysis for 689 patients

Assessment of the predictive role of oestrogen and progesterone receptor status in breast cancer patients treated with neoadjuvant chemotherapy: A retrospective analysis for 689 patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Assessment of the predictive role of oestrogen and progesterone receptor status in breast cancer patients treated with neoadjuvant chemotherapy: A retrospective analysis for 689 patients Ying Ye, Rui Chen, Yong Fu, Yang Peng, Fanli Qu, Zhenrong Tang, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-16004/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : To explore the predictive indicators in hormone receptor (HR)-positive breast cancer (BC) patients receiving neoadjuvant chemotherapy (NACT) and to evaluate the value of quantitative oestrogen receptor (ER) and progesterone receptor (PR) in predicting tumour response. Methods : Six hundred eighty-nine BC patients with HR-positive status who were treated with anthracycline, epirubicin and taxane NACT treatment were retrospectively analysed. Clinical and pathological features of the patients were used to evaluate the response to NACT. Results : Patients with larger tumour sizes ( OR 1.657 CI 1.186-2.313 p=0.003 ), those who were in a premenopausal status ( OR 1.458 CI 1.039-2.045 p=0.029 ) and those with higher Ki67 levels ( OR 1.735 CI 1.231-2.444 p=0.002 ) exhibited a better therapy response. Among the patients in the postmenopausal subgroup, a lower pretreatment ER or PR expression were associated with a reduction in tumour size, and the cut-off values for ER and PR were 87.5% and 65%, respectively ( p=0.006 and p=0.05 ). Decreased expression of ER and PR was also observed after NACT treatment ( p=0.028 and p<0.001, respectively ) but played only a predictive role in the Her-2-negative subgroup; the cut-off values for decreased ER and PR were 17.5% and 26.5%, respectively ( p=0.044 and p<0.001 ). Conclusions : Semiquantified pretreatment HR expression can be used to predict the response of NACT in postmenopausal BC patients. Decreased ER and PR expression is also associated with a reduction in tumour size in Her-2-negative subtypes treated with NACT. Oncology Breast Cancer Menstruation Neoadjuvant Chemotherapy Oestrogen Receptor Progesterone Receptor. Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Breast cancer (BC) is the leading cause of cancer-related death among women worldwide, and approximately 75% of all BCs are hormone receptor (HR) positive [ 1 ]. Neoadjuvant chemotherapy (NACT) has become a well-established approach to treat large or locally advanced BCs [ 2 , 3 , 4 ], which shrinks the tumour to improve the chances of surgical resection and to evaluate the tumour response to chemotherapeutic agents [ 5 , 6 , 7 ]. Although HR-positive BC patients are sensitive to endocrine therapy, they have an undesirable response to NACT treatment compared to the HR-negative subtypes. However, NACT is necessary for a large number of HR + BC patients. Unfortunately, studies investigating the prediction of tumour response after NACT treatment among HR-positive BC patients are scarce [ 7 , 8 ]. Oestrogen receptor (ER)/progesterone receptor (PR) status has been reported to be a predictive marker of tumour response in endocrine therapy [ 8 ], but few studies have assessed the quantitative status of ER and PR as predictive indicators in NACT. In our study, a semiquantitative method was used to evaluate the predictive effect of pretreatment ER and PR expression. In addition, the change in the semiquantitative expression of ER and PR was also evaluated as a possible predictor for NACT treatment. Methods Patients and treatments A total of 689 BC patients characterized as ER and/or PR positive who had undergone NACT and surgery at the Department of Endocrine Breast Surgery in the First Affiliated Hospital of Chongqing Medical University between January 2012 and November 2017 were recruited. All patients received at least 3 cycles of treatment with the TEC regimen: cyclophosphamide (500 mg/m 2 ), epirubicin (75 mg/m 2 ), and docetaxel (75 mg/m 2 ) every 21 days. Patients with bilateral breast cancer, male breast cancer, and a history of contralateral breast cancer were excluded. In our study, Herceptin was not used in patients with Her-2-positive status before the operation. Pathology assessment ER and PR expression were evaluated by the Pathology Department of Chongqing Medical University, and the results were evaluated as the percentage of breast cancer cells with ER/PR staining confirmed via immunohistochemistry (IHC). Samples were defined as ER (+) or PR (+) when at least 1% of nuclei were stained [ 9 ]. Her-2 status was considered to be positive when more than 10% of the tumour cells showed a staining intensity of 3 + via IHC or showed a > 2.2-fold increase via fluorescence in situ hybridization (FISH) [ 10 ]. Regarding Ki67, a range of 500 to 1000 cells were counted to calculate the percentage of positive tumour cell nuclei, including hot spot areas, and 14% was defined as the best cut-off value [ 11 ]. Evaluation of treatment efficacy Ultrasonography and magnetic resonance imaging (MRI) were used to evaluate the response to NACT. We compared the primary imaging materials to the latest materials before the operation to evaluate tumour shrinkage. The Response Evaluation Criteria in Solid Tumours (RECIST) guidelines version 1.1 were used to evaluate the treatment response as follows: CR (complete remission) was considered if all the target lesions had disappeared, and the short axis of any pathological lymph nodes was less than 10 mm; PR (partial remission) was considered if the longest diameter of the tumour lesion was decreased by ≥ 30%; PD (progressive disease) was considered if the longest tumour diameter was increased by ≥ 20%; and SD (stable disease) was considered if the longest tumour diameter was decreased by less than 30% or increased by less than 20%. pCR (pathologic complete remission) was defined as no residual tumour lesion in any breast tissues or lymph nodes. Among them, patients with pCR, CR and PR were regarded as responders, while those with PD or SD were regarded as nonresponders. Statistical methods The differences in clinicopathological characteristics between the responders and nonresponders were calculated with the chi-squared test and multivariate logistic regression models, while the Kruskal–Wallis test was used to compare quantitative characteristics. A receiver operating characteristic (ROC) curve was used to assess the cut-off value. Differences were considered to be statistically significant at P < 0.05. SPSS version 22.0 software (SPSS Inc, Chicago, USA) was used for all statistical analyses. Results Baseline characteristics The average age of the enrolled patients was 48.5 ± 8.92 years (range, 22 to 72 years), and 435 patients (63.2%) were menopausal. The tumour size was 3.94 ± 2.15 cm at diagnosis and 2.13 ± 1.55 cm after NACT. Two hundred ninety-six patients (42.9%) featured clinically positive lymph nodes. According to IHC and FISH, 669 (97.1%) and 514 (74.6%) patients were ER positive and PR positive, respectively, while 198 (29.0%) patients were Her-2-positive. In this study, 479 (69.6%) patients showed a response to NACT treatment, including 45 with pCR (6.50%), 67 with CR (9.70%) and 367 with PR (53.3%), based on the clinical pathological response. Additional details regarding the patient characteristics are shown in Table 1 . Table 1 Clinicopathological features of the study cohort (n = 689) Parameters Number(%) Parameters Number(%) Age(year) ER Status ༜40 94(13.8) Positive 669(97.1) ≥ 40 595(86.2) Negative 20(2.90) Menopause PR Status Yes 254(36.8) Positive 534(77.5) No 435(63.2) Negative 155(22.5) Chemotherapy cycles Her-2 3 18(2.6) Positive 198(29.0) 4 621(90.1) 5–6 50(7.3) Negative 385(55.7) Unknown 2 106(15.3) Subtypes of Cancer Ki67(%) Ductal 673(97.7) ༜14 238(34.5) Lobular 10(1.40) ≥ 14 451(65.5) Others 6(0.90) Subgroup Tumor Size ER + PR+ 514(74.6) ༜2 cm 58(8.40) ER + PR- 155(22.5) 2-4cm 391(56.8) ER-PR+ 20(2.90) ༞4 cm 240(34.8) Responders 3 Clinical nodal status pCR 45(6.50) Positive 296(42.9) CR 67(9.70) Negative 393(57.1) PR 367(53.3) Histological Grade SD 189(27.4) I 24(3.50) PD 21(3.50) II 451(65.5) III 66(9.60) Unknown 1 148(21.4) Abbreviations: pCR pathologic complete remission, CR complete remission, PR partial remission, SD stable disease, PD progressive disease. 1: The pathology test was given but the results were unknown. 2: IHC test was given and showed Her-2(2+), but not be verified by FISH. 3: pCR, CR and PR were regarded as responders to NACT, while SD or PD was regarded as non-responders to NACT. Table.2 Univariate analysis of baseline characteristics according to response to NAC Characteristic clinical response P value Res 1 Non-Res 2 Age(Y) 47.9 ± 8.81 50.0 ± 9.02 0.019 Tumor size (cm) 4.1 ± 2.11 3.7 ± 1.93 0.003 Histological Grade I II III 16 302 41 8 150 25 0.752 Menopause Yes No 162 317 92 118 0.012 Clinical nodal status Positive negative 217 262 79 131 0.061 Molecular subtype ER + PR+ ER + PR- 351 112 163 43 0.408 PR status Positive negative 367 112 167 43 0.427 Her2 status positive negative 149 261 49 124 0.062 Ki67 expression (%) ༜14 ≥ 14 144 333 94 118 ༜0.001 1: including pCR, CR and PR; 2: including PD and SD. Univariate and multivariable analysis of clinicopathological characteristics based on the response to NACT Univariate analysis and multivariate logistic regression models were used to analyse the relationship between treatment response and baseline characteristics (Tables 2 and 3 ). Histological grade, molecular subtype and PR status did not show a statistically significant association with the response to NACT treatment ( all p > 0.05 ). In contrast, a larger tumour size ( OR 1.657 CI 1.186–2.313 p = 0.003 ), postmenopausal status ( OR 1.458 CI 1.039–2.045 p = 0.029 ) and higher Ki67 index ( OR 1.735 CI 1.231–2.444 p = 0.002 ) predicted a better therapy response. In addition, clinical nodal status showed a marginal P value ( p = 0.061 ) in the univariate analysis but no statistical significance in the multivariate logistic regression analysis ( OR 1.212 CI 0.860–1.707 p = 0.272 ). Characteristic clinical response P value Res 1 Non-Res 2 Age(Y) 47.9 ± 8.81 50.0 ± 9.02 0.019 Tumor size (cm) 4.1 ± 2.11 3.7 ± 1.93 0.003 Histological Grade I II III 16 302 41 8 150 25 0.752 Menopause Yes No 162 317 92 118 0.012 Clinical nodal status Positive negative 217 262 79 131 0.061 Molecular subtype ER+PR+ ER+PR- 351 112 163 43 0.408 PR status Positive negative 367 112 167 43 0.427 Her2 status positive negative 149 261 49 124 0.062 Ki67 expression (%) ＜ 14 ≥ 14 144 333 94 118 ＜ 0.001 1: including pCR, CR and PR; 2: including PD and SD. Table.2 Univariate analysis of baseline characteristics according to response to NAC Table 3 Multivariate logistic regression models of baseline characteristics according to response to NAC Characteristic clinical response P value HR 95%CI Reference 0.907 Tumor size 1.657 1.186–2.313 0.003 Menopause 1.458 1.039–2.045 0.029 Clinical nodal status 1.212 0.860–1.707 0.272 Ki67 expression 1.735 1.231–2.444 0.002 Predictive value of pretreatment and decreased ER and PR expression The interaction between pretreatment HR expression and clinical response was further evaluated. As shown in Fig. 1 , in the postmenopausal subgroup, the patients who exhibited a clinical response showed lower ER expression before NACT ( n = 244, p = 0.006 ) (Fig. 1 A and 1 B), but this phenomenon was not observed in the premenopausal subgroup ( n = 425, p = 0.157 ). Similarly, Figs. 1 C and 1 D show that in the postmenopausal subgroup patients had higher PR expression prior to NACT, reducing their chances of achieving a response ( n = 182, p = 0.05 ). Moreover, ROC curve analysis was used to define the optimal cut-off value for primary HR expression in the postmenopausal subgroup (Fig. 2 ). The area under the curve for pretreatment ER and PR expression were 0.605 ( p = 0.006 ) and 0.580 ( p = 0.05 ), respectively, and the optimal cut-off values were 87.5% and 65%, respectively (Fig. 2 ). Next, we assessed the changes in ER and PR expression in BC patients during NACT treatment. Decreased ER and PR expression was observed after NACT treatment ( p = 0.003 & p < 0.001 , Fig. 3 A). Moreover, this decreased expression could predict a higher possibility of tumour remission ( p = 0.028 & p < 0.001 , Fig. 3 B, C). However, the ROC results indicated that decreased ER and PR expression can predict the response to NACT only in the Her-2 negative subgroup; the AUCs were 0.565 ( p = 0.044 , Fig. 4 C) and 0.648 ( p < 0.001 , Fig. 4 D), respectively, while the cut-off values of ER and PR reduction were 17.5% and 26.5%, respectively. Discussion A large number of clinical studies have shown that HR-positive BC patients have a better relative prognosis but are not as sensitive to NACT as HR-negative BC patients [ 12 ]. However, NACT is an imperative method for luminal BC patients with relatively late stages. At present, the predictive factors for the efficiency of NACT in HR-positive BC patients have not been thoroughly elucidated, and whether the response to NACT could be predicted by semiquantified ER and PR has been a matter of debate [ 13 ]. In our study, patients with larger tumour size (≥ 4 cm) or higher percent expression of Ki67 (≥ 14%) could predict a better outcome after 4-cycle NACT treatment, which was in line with prior studies [ 8 , 10 , 11 ]. Unlike previous research from other institutes, the results of our multivariable logistic regression showed that postmenopausal BC patients are more likely to obtain a better clinical therapy response in NACT compared with premenopausal BCs. To the best of our knowledge, this is the first study to describe the impact of menstrual status on NACT in HR-positive BC patients. We next assessed the interaction between quantified HR expression and clinical response. Similarly, pretreatment ER and PR expression could be used as predictors of response to NACT only for postmenopausal BC patients. This result is similar to that obtained in Raphael’s study, in which he concluded that a lower pretreatment ER expression predicted a higher clinical response rate. However, the effect of menopausal status was not discussed in his study [ 13 ]. The possible mechanism is that the oestrogen level may affect the sensitivity of tumour cells to chemotherapy [ 14 ]. Furthermore, it is well known that ER+/PR- tumours have a higher level of growth signalling than ER+/PR + tumours [ 15 , 16 ]. However, in our study, there was no significant difference when analysing the response to NACT among various ER and PR status subgroups (ER+/PR + and ER+/PR- subgroups). In the current study, the changes in ER and PR expression among non-pCR patients who received NACT were also investigated. According to our findings, decreased ER and/or PR levels were found in approximately 50% of the patients after NACT treatment. However, when considering the therapeutic response of NACT, the predictive roles of decreased ER and PR could only be observed in the Her-2 negative subgroup. This finding may be attributed to differences in tumour cell subtypes, which may activate dissimilar signalling pathways in response to chemotherapy. Another reason for this finding may be that Her-2-positive subtypes have complex growth-promoting mechanisms, which may be affected by molecularly targeted therapy drugs rather than chemotherapy [ 17 ]. Our study has the largest number of patients to date among studies exploring the relationship between semiquantitative HR and NACT treatment, but the major limitation of this study is that our data were obtained from only one single breast cancer centre, and the research followed a retrospective design. As is well known, low HR expression is be an adverse factor for endocrine therapy [ 12 ], and in this research, we observed a reduction in HR expression due to chemotherapy. Could decreased HR expression be beneficial to whole breast cancer treatment? How does it affect progression-free survival (PFS) or overall survival (OS) in patients? Further studies, especially long-term follow-up studies, should take these questions into consideration. The results of this study showed that quantified HR expression can serve as a predictor of NACT treatment response in postmenopausal BC patients. Changes in HR expression can also predict the outcomes of patients in the ER+/Her-2 negative subgroup. However, in the premenopausal and ER+/Her-2-positive subgroups, these factors were not observed to have predictive functions. In clinical work, continued chemotherapy should be considered for patients with the aforementioned features. Conclusion Semiquantified pretreatment HR expression can predict the response of NACT in postmenopausal BC patients. Decreased ER and PR expression is also associated with a reduction in tumour size in Her-2-negative subtypes treated with NACT. The findings could help in screening effective chemotherapy regimens for these patients. Abbreviations BC: Breast Cancer; CI: Confidence Interval; CR: Complete Remission; PR: Partial Remission; PD: Clinical Progressive Disease; SD: Clinical Stable Disease; pCR: Pathological Complete Remission; HR: Hormone Receptor; ER: Oestrogen Receptor; PR: Progestrone Receptor; Her-2: Human Epidermal Receptor2; FISH: Fluorescence In Situ Hybridization; IHC: Immunohistochemistry; NACT: Neoadjuvant Chemotherapy; OR: Odds Ratio; OS: Overall Survival; PFS: Progression-Free Survival; ROC: Receiver Operating Curve. Declarations Ethics approval and consent to participate This article does not contain any studies with human participants performed by any of the authors . Consent for publication Not applicable. Availability of data and material The datasets are not publicly available due to local regulations but are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests to report. Funding This study was funded by the National Natural Science Foundation of China (NSFC; no. 81272265 and 81472658). Authors' contributions Sc Liu conceived and designed the overall study. Y Ye and R Chen collected the clinical medical histories of patients and analysed the data. Y Ye and Y Fu wrote the manuscript. R Chen and Y Fu revised the manuscript. Y Peng, F Luo and Fl Qu helped perform the statistical analyses. Bg Zong, Zr Tang and Yh Wang finished data filtration and helped write the manuscript. Acknowledgements We thank the Department of Endocrine Breast Surgery in the First Affiliated Hospital of Chongqing Medical University for providing the medical histories of the enrolled patients. We also appreciate the pathological files provided by the Pathology Department of Chongqing Medical University References Zhou X, Zhang J, Yun H, Shi R, Wang Y, Wang W, et al. 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Neoadjuvant Trials in ER+ Breast Cancer: A Tool for Acceleration of Drug Development and Discovery. Cancer discovery 7: 561-574, 2017. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-16004","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":383758,"identity":"0a1d98f5-c106-4f44-890f-949f36923d3c","order_by":1,"name":"Ying Ye","email":"","orcid":"","institution":"Chongqing Medical University First Affiliated Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ying","middleName":"","lastName":"Ye","suffix":""},{"id":383759,"identity":"6e8d2544-1a58-4196-8efc-6db22e05c738","order_by":2,"name":"Rui Chen","email":"","orcid":"","institution":"Chongqing Medical University First Affiliated Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Rui","middleName":"","lastName":"Chen","suffix":""},{"id":383760,"identity":"acf0dd60-810e-4944-8757-e6e25fa6e58c","order_by":3,"name":"Yong Fu","email":"","orcid":"","institution":"Dianjiang People's Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yong","middleName":"","lastName":"Fu","suffix":""},{"id":383761,"identity":"cbe9288b-952d-4df2-98ed-4041acc183d8","order_by":4,"name":"Yang Peng","email":"","orcid":"","institution":"Chongqing Medical University First Affiliated Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Peng","suffix":""},{"id":383762,"identity":"ae687121-2bff-4303-87eb-3ae3be266ab8","order_by":5,"name":"Fanli Qu","email":"","orcid":"","institution":"Chongqing Medical University First Affiliated Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fanli","middleName":"","lastName":"Qu","suffix":""},{"id":383763,"identity":"70d979e7-ffed-4dcc-b61f-781b9eb81785","order_by":6,"name":"Zhenrong Tang","email":"","orcid":"","institution":"Chongqing Medical University First Affiliated Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhenrong","middleName":"","lastName":"Tang","suffix":""},{"id":383764,"identity":"bf37569c-1af1-4441-b67b-8a9faa2549ca","order_by":7,"name":"Beige Zong","email":"","orcid":"","institution":"Chongqing Medical University First Affiliated Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Beige","middleName":"","lastName":"Zong","suffix":""},{"id":383765,"identity":"4a63e132-eb17-45a3-8d93-ee053429fe7c","order_by":8,"name":"Yihua Wang","email":"","orcid":"","institution":"Chongqing Medical University First Affiliated Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yihua","middleName":"","lastName":"Wang","suffix":""},{"id":383766,"identity":"934a0cde-5ddc-46da-a994-36cbf4285db9","order_by":9,"name":"Feng Luo","email":"","orcid":"","institution":"Chongqing Medical University First Affiliated Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Feng","middleName":"","lastName":"Luo","suffix":""},{"id":383767,"identity":"e78fa5c6-dfdc-478f-ad82-52c83cc5711c","order_by":10,"name":"S Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIiWNgGAWjYBACPmYGBmYwSwKIEyps5PiZmQ8/wKeFDUXLgzNpxpLtbGkGeLUwIGlhfNh2KHHDeR4FCbxa2HmMPxdU3LHrn91j9iCx7YCx8WEeBgOGGpto3A7jMZOeceZZ8ow7Z8wNEs7dkTM7zHvgAcOxtNwGPFqYedsOJxtI5JhJJJQ9MzY7zJdgwNhwGJ8W48+8/2Ba2A4nbm7mMZAgoMVAmrfhsB1ES9vhxA3MBLWwlUnzHDucIHEjrUwiARjIEoeBgZyAxy/8/Ic3f+apOWzPPyN5m+QPUFT2Hz784EONDU4tMJCIqiCBgHIQsCdCzSgYBaNgFIxUAADs+VWYPy0tMwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-6886-8602","institution":"first affliated hospital of Chongqing Medical University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"S","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2020-02-29 11:42:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-16004/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-16004/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":594948,"identity":"569f51bd-a19e-44b7-94fe-6f728037a3a1","added_by":"auto","created_at":"2020-03-04 17:08:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":65828,"visible":true,"origin":"","legend":"Expression of HR between cRes and cNon-Res is affected by menstrual status.\n\nTo show the interaction between HR expression and clinical response affected by menstrual status. Figure 1A and 1B indicated that clinically responsive patients had a lower expression of ER only in the postmenopausal subgroup. Figure 1C and 1D showed that only in the postmenopausal subgroup, the higher expression of PR before NAC treatment had a lower response possibility.","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-16004/v1/Figure 1.png"},{"id":594949,"identity":"7dc3df9c-172e-4566-854e-ce2449628d77","added_by":"auto","created_at":"2020-03-04 17:08:40","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":46731,"visible":true,"origin":"","legend":"ROC curve for pretreatment ER and PR expression in the postmenopausal subgroup.\n\nShowed that the best cut-off value of primary ER and PR expression was 87.5% and 65%, respectively. The area under the curve for pretreatment ER and PR was 0.605 (P=0.006,95% CI 0.530-0.679) and 0.580(P=0.05,95% CI 0.493-0.668), respectively.","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-16004/v1/Figure 2.png"},{"id":594950,"identity":"08419f2a-99c2-434b-a2e5-11b10360ba0d","added_by":"auto","created_at":"2020-03-04 17:08:40","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":121722,"visible":true,"origin":"","legend":"Change of HR expression between biopsy and surgical specimens.\n\nDecreased expression of ER and PR between biopsy and surgery specimens was observed, and the P values were 0.028 and less than 0.000, respectively.","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-16004/v1/Figure 3.png"},{"id":594951,"identity":"24ceeb13-827a-4956-9519-5b44d6c27fe1","added_by":"auto","created_at":"2020-03-04 17:08:40","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":92945,"visible":true,"origin":"","legend":"ROC curve for the change of ER and PR expression after NAC.\n\nDecreased ER and PR can predict the response to NAC treatment in the Her-2 negative subgroup, but the predictive role was lost in Her-2 positive subgroup.\nThe ROC curve showed that decreased ER and PR can predict the response to NAC treatment in the Her-2 negative subgroup, and the cut-off values of ER and PR reduction were 17.5% and 26.5%, respectively.","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-16004/v1/Figure 4.png"},{"id":13492546,"identity":"17fff80e-7878-445e-9452-614ee8f12117","added_by":"auto","created_at":"2021-09-16 22:31:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":743743,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-16004/v1/5265abc7-4603-4043-b63e-bb37160f6130.pdf"}],"financialInterests":"","formattedTitle":"Assessment of the predictive role of oestrogen and progesterone receptor status in breast cancer patients treated with neoadjuvant chemotherapy: A retrospective analysis for 689 patients","fulltext":[{"header":"Introduction","content":" \u003cp\u003eBreast cancer (BC) is the leading cause of cancer-related death among women worldwide, and approximately 75% of all BCs are hormone receptor (HR) positive [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Neoadjuvant chemotherapy (NACT) has become a well-established approach to treat large or locally advanced BCs [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], which shrinks the tumour to improve the chances of surgical resection and to evaluate the tumour response to chemotherapeutic agents [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Although HR-positive BC patients are sensitive to endocrine therapy, they have an undesirable response to NACT treatment compared to the HR-negative subtypes. However, NACT is necessary for a large number of HR\u0026thinsp;+\u0026thinsp;BC patients. Unfortunately, studies investigating the prediction of tumour response after NACT treatment among HR-positive BC patients are scarce [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOestrogen receptor (ER)/progesterone receptor (PR) status has been reported to be a predictive marker of tumour response in endocrine therapy [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], but few studies have assessed the quantitative status of ER and PR as predictive indicators in NACT. In our study, a semiquantitative method was used to evaluate the predictive effect of pretreatment ER and PR expression. In addition, the change in the semiquantitative expression of ER and PR was also evaluated as a possible predictor for NACT treatment.\u003c/p\u003e "},{"header":"Methods","content":" \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients and treatments\u003c/h2\u003e \u003cp\u003eA total of 689 BC patients characterized as ER and/or PR positive who had undergone NACT and surgery at the Department of Endocrine Breast Surgery in the First Affiliated Hospital of Chongqing Medical University between January 2012 and November 2017 were recruited. All patients received at least 3 cycles of treatment with the TEC regimen: cyclophosphamide (500\u0026nbsp;mg/m\u003csup\u003e2\u003c/sup\u003e), epirubicin (75\u0026nbsp;mg/m\u003csup\u003e2\u003c/sup\u003e), and docetaxel (75\u0026nbsp;mg/m\u003csup\u003e2\u003c/sup\u003e) every 21 days. Patients with bilateral breast cancer, male breast cancer, and a history of contralateral breast cancer were excluded. In our study, Herceptin was not used in patients with Her-2-positive status before the operation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003ePathology assessment\u003c/h2\u003e \u003cp\u003eER and PR expression were evaluated by the Pathology Department of Chongqing Medical University, and the results were evaluated as the percentage of breast cancer cells with ER/PR staining confirmed via immunohistochemistry (IHC). Samples were defined as ER (+) or PR (+) when at least 1% of nuclei were stained [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Her-2 status was considered to be positive when more than 10% of the tumour cells showed a staining intensity of 3\u0026thinsp;+\u0026thinsp;via IHC or showed a\u0026thinsp;\u0026gt;\u0026thinsp;2.2-fold increase via fluorescence in situ hybridization (FISH) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Regarding Ki67, a range of 500 to 1000 cells were counted to calculate the percentage of positive tumour cell nuclei, including hot spot areas, and 14% was defined as the best cut-off value [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eEvaluation of treatment efficacy\u003c/h2\u003e \u003cp\u003eUltrasonography and magnetic resonance imaging (MRI) were used to evaluate the response to NACT. We compared the primary imaging materials to the latest materials before the operation to evaluate tumour shrinkage. The Response Evaluation Criteria in Solid Tumours (RECIST) guidelines version 1.1 were used to evaluate the treatment response as follows: CR (complete remission) was considered if all the target lesions had disappeared, and the short axis of any pathological lymph nodes was less than 10\u0026nbsp;mm; PR (partial remission) was considered if the longest diameter of the tumour lesion was decreased by \u0026ge;\u0026thinsp;30%; PD (progressive disease) was considered if the longest tumour diameter was increased by \u0026ge;\u0026thinsp;20%; and SD (stable disease) was considered if the longest tumour diameter was decreased by less than 30% or increased by less than 20%. pCR (pathologic complete remission) was defined as no residual tumour lesion in any breast tissues or lymph nodes. Among them, patients with pCR, CR and PR were regarded as responders, while those with PD or SD were regarded as nonresponders.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical methods\u003c/h2\u003e \u003cp\u003eThe differences in clinicopathological characteristics between the responders and nonresponders were calculated with the chi-squared test and multivariate logistic regression models, while the Kruskal\u0026ndash;Wallis test was used to compare quantitative characteristics. A receiver operating characteristic (ROC) curve was used to assess the cut-off value. Differences were considered to be statistically significant at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. SPSS version 22.0 software (SPSS Inc, Chicago, USA) was used for all statistical analyses.\u003c/p\u003e \u003c/div\u003e "},{"header":"Results","content":" \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics\u003c/h2\u003e \u003cp\u003eThe average age of the enrolled patients was 48.5\u0026thinsp;\u0026plusmn;\u0026thinsp;8.92\u0026nbsp;years (range, 22 to 72\u0026nbsp;years), and 435 patients (63.2%) were menopausal. The tumour size was 3.94\u0026thinsp;\u0026plusmn;\u0026thinsp;2.15\u0026nbsp;cm at diagnosis and 2.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.55\u0026nbsp;cm after NACT. Two hundred ninety-six patients (42.9%) featured clinically positive lymph nodes. According to IHC and FISH, 669 (97.1%) and 514 (74.6%) patients were ER positive and PR positive, respectively, while 198 (29.0%) patients were Her-2-positive. In this study, 479 (69.6%) patients showed a response to NACT treatment, including 45 with pCR (6.50%), 67 with CR (9.70%) and 367 with PR (53.3%), based on the clinical pathological response. Additional details regarding the patient characteristics are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cdiv class=\"SimplePara\"\u003eClinicopathological features of the study cohort (n\u0026thinsp;=\u0026thinsp;689)\u003c/div\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eParameters Number(%)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003eParameters Number(%)\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eAge(year)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eER Status\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e༜40 94(13.8)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003ePositive 669(97.1)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026ge;\u0026thinsp;40 595(86.2)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003eNegative\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e20(2.90)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eMenopause\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003ePR Status\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eYes 254(36.8)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003ePositive 534(77.5)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eNo 435(63.2)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003eNegative 155(22.5)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eChemotherapy cycles\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eHer-2\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e3 18(2.6)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003ePositive 198(29.0)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e4 621(90.1)\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e5\u0026ndash;6 50(7.3)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003eNegative 385(55.7)\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003eUnknown\u003csup\u003e2\u003c/sup\u003e 106(15.3)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eSubtypes of Cancer\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eKi67(%)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eDuctal 673(97.7)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e༜14 238(34.5)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eLobular 10(1.40)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026ge;\u0026thinsp;14 451(65.5)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eOthers 6(0.90)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eSubgroup\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eTumor Size\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003eER\u0026thinsp;+\u0026thinsp;PR+ 514(74.6)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e༜2\u0026nbsp;cm 58(8.40)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003eER\u0026thinsp;+\u0026thinsp;PR- 155(22.5)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e2-4cm 391(56.8)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003eER-PR+ 20(2.90)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e༞4\u0026nbsp;cm 240(34.8)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eResponders\u003c/span\u003e\u003csup\u003e3\u003c/sup\u003e\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eClinical nodal status\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003epCR 45(6.50)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003ePositive 296(42.9)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003eCR 67(9.70)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eNegative 393(57.1)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003ePR 367(53.3)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eHistological Grade\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003eSD 189(27.4)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eI 24(3.50)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003ePD 21(3.50)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eII 451(65.5)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eIII 66(9.60)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eUnknown\u003csup\u003e1\u003c/sup\u003e 148(21.4)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eAbbreviations: pCR pathologic complete remission, CR complete remission, PR partial remission, SD stable disease, PD progressive disease.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e1: The pathology test was given but the results were unknown.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e2: IHC test was given and showed Her-2(2+), but not be verified by FISH.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e3: pCR, CR and PR were regarded as responders to NACT, while SD or PD was regarded as non-responders to NACT.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eTable.2\u003c/span\u003e Univariate analysis of baseline characteristics according to response to NAC\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eCharacteristic\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eclinical response\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eP value\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eRes\u003c/span\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eNon-Res\u003c/span\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eAge(Y)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e47.9\u0026thinsp;\u0026plusmn;\u0026thinsp;8.81\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e50.0\u0026thinsp;\u0026plusmn;\u0026thinsp;9.02\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.019\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eTumor size (cm)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e4.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.11\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.93\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.003\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eHistological Grade\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003eI\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003eII\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003eIII\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e16\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e302\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e41\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e8\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e150\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e25\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.752\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eMenopause\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003eYes\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003eNo\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e162\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e317\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e92\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e118\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.012\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eClinical nodal status\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003ePositive\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003enegative\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e217\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e262\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e79\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e131\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.061\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eMolecular subtype\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003eER\u0026thinsp;+\u0026thinsp;PR+\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003eER\u0026thinsp;+\u0026thinsp;PR-\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e351\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e112\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e163\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e43\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.408\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003ePR status\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003ePositive\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003enegative\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e367\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e112\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e167\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e43\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.427\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eHer2 status\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003epositive\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003enegative\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e149\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e261\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e49\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e124\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.062\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eKi67 expression (%)\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e༜14\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026ge;\u0026thinsp;14\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e144\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e333\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e94\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e118\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e༜0.001\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e1: including pCR, CR and PR;\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e2: including PD and SD.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eUnivariate and multivariable analysis of clinicopathological characteristics based on the response to NACT\u003c/h2\u003e \u003cp\u003eUnivariate analysis and multivariate logistic regression models were used to analyse the relationship between treatment response and baseline characteristics (Tables\u0026nbsp;2 and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Histological grade, molecular subtype and PR status did not show a statistically significant association with the response to NACT treatment (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eall p\u0026thinsp;\u0026gt;\u0026thinsp;0.05\u003c/span\u003e). In contrast, a larger tumour size (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eOR 1.657 CI 1.186\u0026ndash;2.313 p\u0026thinsp;=\u0026thinsp;0.003\u003c/span\u003e), postmenopausal status (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eOR 1.458 CI 1.039\u0026ndash;2.045 p\u0026thinsp;=\u0026thinsp;0.029\u003c/span\u003e) and higher Ki67 index (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eOR 1.735 CI 1.231\u0026ndash;2.444 p\u0026thinsp;=\u0026thinsp;0.002\u003c/span\u003e) predicted a better therapy response. In addition, clinical nodal status showed a marginal P value (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ep\u0026thinsp;=\u0026thinsp;0.061\u003c/span\u003e) in the univariate analysis but no statistical significance in the multivariate logistic regression analysis (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eOR 1.212 CI 0.860\u0026ndash;1.707 p\u0026thinsp;=\u0026thinsp;0.272\u003c/span\u003e).\u003c/p\u003e\n\n\u003ctable align=\"left\" border=\"1\" cellpadding=\"0\" cellspacing=\"0\" style=\"border-collapse:collapse;border:none;margin-left:6.75pt;margin-right:6.75pt;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 134.4pt;border-top: 1pt solid windowtext;border-left: none;border-bottom: 1.5pt solid windowtext;border-right: none;padding: 0in 5.4pt;height: 21pt;vertical-align: top;\" valign=\"top\" width=\"39.51434878587197%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 133.25pt;border-top: 1pt solid windowtext;border-left: none;border-bottom: 1pt solid windowtext;border-right: none;padding: 0in 5.4pt;height: 21pt;vertical-align: top;\" valign=\"top\" width=\"39.29359823399559%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;text-indent:26.35pt;\"\u003e\u003cstrong\u003eclinical response\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 71.9pt;border-top: 1pt solid windowtext;border-left: none;border-bottom: 1.5pt solid windowtext;border-right: none;padding: 0in 5.4pt;height: 21pt;vertical-align: top;\" valign=\"top\" width=\"21.192052980132452%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u003cstrong\u003e\u003cspan style=\"color:red;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u003cstrong\u003e\u003cspan style=\"color:black;\"\u003eP value\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 65.3pt;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1.5pt solid windowtext;padding: 0in 5.4pt;height: 22pt;vertical-align: top;\" valign=\"top\" width=\"48.87640449438202%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u003cstrong\u003e\u003cspan style=\"font-family:\u0026quot;Arial\u0026quot;,sans-serif;color:#333333;background:white;\"\u003eRes\u003c/span\u003e\u003c/strong\u003e\u003csup\u003e\u003cspan style=\"font-family:\u0026quot;Arial\u0026quot;,sans-serif;color:#333333;background:white;\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67.95pt;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1.5pt solid windowtext;padding: 0in 5.4pt;height: 22pt;vertical-align: top;\" valign=\"top\" width=\"51.12359550561798%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u003cstrong\u003eNon-Res\u003c/strong\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 134.4pt;border: none;padding: 0in 5.4pt;height: 16.1pt;vertical-align: top;\" valign=\"top\" width=\"39.51434878587197%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u003cstrong\u003eAge(Y)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65.3pt;border: none;padding: 0in 5.4pt;height: 16.1pt;vertical-align: top;\" valign=\"top\" width=\"19.205298013245034%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e47.9\u003cspan style=\"font-family:SimSun;\"\u003e±\u003c/span\u003e8.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67.95pt;border: none;padding: 0in 5.4pt;height: 16.1pt;vertical-align: top;\" valign=\"top\" width=\"20.08830022075055%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e50.0\u003cspan style=\"font-family:SimSun;\"\u003e±\u003c/span\u003e9.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71.9pt;border: none;padding: 0in 5.4pt;height: 16.1pt;vertical-align: top;\" valign=\"top\" width=\"21.192052980132452%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 134.4pt;border: none;padding: 0in 5.4pt;height: 16.1pt;vertical-align: top;\" valign=\"top\" width=\"39.51434878587197%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u003cstrong\u003eTumor size (cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65.3pt;border: none;padding: 0in 5.4pt;height: 16.1pt;vertical-align: top;\" valign=\"top\" width=\"19.205298013245034%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e4.1\u003cspan style=\"font-family:SimSun;\"\u003e±\u003c/span\u003e2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67.95pt;border: none;padding: 0in 5.4pt;height: 16.1pt;vertical-align: top;\" valign=\"top\" width=\"20.08830022075055%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e3.7\u003cspan style=\"font-family:SimSun;\"\u003e±\u003c/span\u003e1.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71.9pt;border: none;padding: 0in 5.4pt;height: 16.1pt;vertical-align: top;\" valign=\"top\" width=\"21.192052980132452%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 134.4pt;border: none;padding: 0in 5.4pt;height: 42.15pt;vertical-align: top;\" valign=\"top\" width=\"39.51434878587197%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u003cstrong\u003eHistological Grade\u003c/strong\u003e\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003eI\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003eII\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65.3pt;border: none;padding: 0in 5.4pt;height: 42.15pt;vertical-align: top;\" valign=\"top\" width=\"19.205298013245034%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e16\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e302\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67.95pt;border: none;padding: 0in 5.4pt;height: 42.15pt;vertical-align: top;\" valign=\"top\" width=\"20.08830022075055%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e8\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e150\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71.9pt;border: none;padding: 0in 5.4pt;height: 42.15pt;vertical-align: top;\" valign=\"top\" width=\"21.192052980132452%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e0.752\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 134.4pt;border: none;padding: 0in 5.4pt;height: 42.15pt;vertical-align: top;\" valign=\"top\" width=\"39.51434878587197%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u003cstrong\u003eMenopause\u003c/strong\u003e\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003eYes\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65.3pt;border: none;padding: 0in 5.4pt;height: 42.15pt;vertical-align: top;\" valign=\"top\" width=\"19.205298013245034%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e162\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67.95pt;border: none;padding: 0in 5.4pt;height: 42.15pt;vertical-align: top;\" valign=\"top\" width=\"20.08830022075055%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e92\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71.9pt;border: none;padding: 0in 5.4pt;height: 42.15pt;vertical-align: top;\" valign=\"top\" width=\"21.192052980132452%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e0.012\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 134.4pt;border: none;padding: 0in 5.4pt;height: 42.15pt;vertical-align: top;\" valign=\"top\" width=\"39.51434878587197%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u003cstrong\u003eClinical nodal status\u003c/strong\u003e\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003ePositive\u003c/p\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003enegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65.3pt;border: none;padding: 0in 5.4pt;height: 42.15pt;vertical-align: top;\" valign=\"top\" width=\"19.205298013245034%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp 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style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e1: including pCR, CR and PR;\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e2: including PD and SD.\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\u003cstrong\u003eTable.2\u0026nbsp;\u003c/strong\u003eUnivariate analysis of baseline characteristics according to response to NAC\u003c/p\u003e\u003cbr\u003e\u003cbr\u003e\n \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cdiv class=\"SimplePara\"\u003eMultivariate logistic regression models of baseline characteristics according to response to NAC\u003c/div\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eCharacteristic\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eclinical response\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eP value\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eHR\u003c/span\u003e\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e95%CI\u003c/span\u003e\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eReference\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.907\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eTumor size\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.657\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.186\u0026ndash;2.313\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.003\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eMenopause\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.458\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.039\u0026ndash;2.045\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.029\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eClinical nodal status\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.212\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.860\u0026ndash;1.707\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.272\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eKi67 expression\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.735\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.231\u0026ndash;2.444\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.002\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003ePredictive value of pretreatment and decreased ER and PR expression\u003c/h2\u003e \u003cp\u003eThe interaction between pretreatment HR expression and clinical response was further evaluated. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e1\u003c/span\u003e, in the postmenopausal subgroup, the patients who exhibited a clinical response showed lower ER expression before NACT (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003en\u0026thinsp;=\u0026thinsp;244, p\u0026thinsp;=\u0026thinsp;0.006\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), but this phenomenon was not observed in the premenopausal subgroup (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003en\u0026thinsp;=\u0026thinsp;425, p\u0026thinsp;=\u0026thinsp;0.157\u003c/span\u003e). Similarly, Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e1\u003c/span\u003eC and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e1\u003c/span\u003eD show that in the postmenopausal subgroup patients had higher PR expression prior to NACT, reducing their chances of achieving a response (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003en\u0026thinsp;=\u0026thinsp;182, p\u0026thinsp;=\u0026thinsp;0.05\u003c/span\u003e). Moreover, ROC curve analysis was used to define the optimal cut-off value for primary HR expression in the postmenopausal subgroup (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The area under the curve for pretreatment ER and PR expression were 0.605 (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ep\u0026thinsp;=\u0026thinsp;0.006\u003c/span\u003e) and 0.580 (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ep\u0026thinsp;=\u0026thinsp;0.05\u003c/span\u003e), respectively, and the optimal cut-off values were 87.5% and 65%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNext, we assessed the changes in ER and PR expression in BC patients during NACT treatment. Decreased ER and PR expression was observed after NACT treatment (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ep\u0026thinsp;=\u0026thinsp;0.003 \u0026amp; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Moreover, this decreased expression could predict a higher possibility of tumour remission (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ep\u0026thinsp;=\u0026thinsp;0.028 \u0026amp; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, C). However, the ROC results indicated that decreased ER and PR expression can predict the response to NACT only in the Her-2 negative subgroup; the AUCs were 0.565 (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ep\u0026thinsp;=\u0026thinsp;0.044\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003eC) and 0.648 (\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003eD), respectively, while the cut-off values of ER and PR reduction were 17.5% and 26.5%, respectively.\u003c/p\u003e \u003c/div\u003e "},{"header":"Discussion","content":" \u003cp\u003eA large number of clinical studies have shown that HR-positive BC patients have a better relative prognosis but are not as sensitive to NACT as HR-negative BC patients [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, NACT is an imperative method for luminal BC patients with relatively late stages. At present, the predictive factors for the efficiency of NACT in HR-positive BC patients have not been thoroughly elucidated, and whether the response to NACT could be predicted by semiquantified ER and PR has been a matter of debate [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn our study, patients with larger tumour size (\u0026ge;\u0026thinsp;4\u0026nbsp;cm) or higher percent expression of Ki67 (\u0026ge;\u0026thinsp;14%) could predict a better outcome after 4-cycle NACT treatment, which was in line with prior studies [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Unlike previous research from other institutes, the results of our multivariable logistic regression showed that postmenopausal BC patients are more likely to obtain a better clinical therapy response in NACT compared with premenopausal BCs. To the best of our knowledge, this is the first study to describe the impact of menstrual status on NACT in HR-positive BC patients.\u003c/p\u003e \u003cp\u003eWe next assessed the interaction between quantified HR expression and clinical response. Similarly, pretreatment ER and PR expression could be used as predictors of response to NACT only for postmenopausal BC patients. This result is similar to that obtained in Raphael\u0026rsquo;s study, in which he concluded that a lower pretreatment ER expression predicted a higher clinical response rate. However, the effect of menopausal status was not discussed in his study [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The possible mechanism is that the oestrogen level may affect the sensitivity of tumour cells to chemotherapy [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Furthermore, it is well known that ER+/PR- tumours have a higher level of growth signalling than ER+/PR\u0026thinsp;+\u0026thinsp;tumours [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, in our study, there was no significant difference when analysing the response to NACT among various ER and PR status subgroups (ER+/PR\u0026thinsp;+\u0026thinsp;and ER+/PR- subgroups).\u003c/p\u003e \u003cp\u003eIn the current study, the changes in ER and PR expression among non-pCR patients who received NACT were also investigated. According to our findings, decreased ER and/or PR levels were found in approximately 50% of the patients after NACT treatment. However, when considering the therapeutic response of NACT, the predictive roles of decreased ER and PR could only be observed in the Her-2 negative subgroup. This finding may be attributed to differences in tumour cell subtypes, which may activate dissimilar signalling pathways in response to chemotherapy. Another reason for this finding may be that Her-2-positive subtypes have complex growth-promoting mechanisms, which may be affected by molecularly targeted therapy drugs rather than chemotherapy [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study has the largest number of patients to date among studies exploring the relationship between semiquantitative HR and NACT treatment, but the major limitation of this study is that our data were obtained from only one single breast cancer centre, and the research followed a retrospective design. As is well known, low HR expression is be an adverse factor for endocrine therapy [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], and in this research, we observed a reduction in HR expression due to chemotherapy. Could decreased HR expression be beneficial to whole breast cancer treatment? How does it affect progression-free survival (PFS) or overall survival (OS) in patients? Further studies, especially long-term follow-up studies, should take these questions into consideration.\u003c/p\u003e \u003cp\u003eThe results of this study showed that quantified HR expression can serve as a predictor of NACT treatment response in postmenopausal BC patients. Changes in HR expression can also predict the outcomes of patients in the ER+/Her-2 negative subgroup. However, in the premenopausal and ER+/Her-2-positive subgroups, these factors were not observed to have predictive functions. In clinical work, continued chemotherapy should be considered for patients with the aforementioned features.\u003c/p\u003e "},{"header":"Conclusion","content":" \u003cp\u003eSemiquantified pretreatment HR expression can predict the response of NACT in postmenopausal BC patients. Decreased ER and PR expression is also associated with a reduction in tumour size in Her-2-negative subtypes treated with NACT. The findings could help in screening effective chemotherapy regimens for these patients.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cp\u003eBC: Breast Cancer; CI: Confidence Interval; CR: Complete Remission; PR: Partial Remission; PD: Clinical Progressive Disease; SD: Clinical Stable Disease; pCR: Pathological Complete Remission; HR: Hormone Receptor; ER: Oestrogen Receptor; PR: Progestrone Receptor; Her-2: Human Epidermal Receptor2; FISH: Fluorescence In Situ Hybridization; IHC: Immunohistochemistry; NACT: Neoadjuvant Chemotherapy; OR: Odds Ratio; OS: Overall Survival; PFS: Progression-Free Survival; ROC: Receiver Operating Curve.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis article does not contain any studies with human participants performed by any of the authors\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets are not publicly available due to local regulations but are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests to report.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the National Natural Science Foundation of China (NSFC; no. 81272265 and 81472658).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSc Liu conceived and designed the overall study. Y Ye and R Chen collected the clinical medical histories of patients and analysed the data. Y Ye and Y Fu wrote the manuscript.\u003c/p\u003e\n\u003cp\u003eR Chen and Y Fu revised the manuscript. Y Peng, F Luo and Fl Qu helped perform the statistical analyses. Bg Zong, Zr Tang and Yh Wang finished data filtration and helped write the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the Department of Endocrine Breast Surgery in the First Affiliated Hospital of Chongqing Medical University for providing the medical histories of the enrolled patients.\u003c/p\u003e\n\u003cp\u003eWe also appreciate the pathological files provided by the Pathology Department of Chongqing Medical University\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eZhou X, Zhang J, Yun H, Shi R, Wang Y, Wang W, et al. 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Neoadjuvant Trials in ER+ Breast Cancer: A Tool for Acceleration of Drug Development and Discovery. \u003cem\u003eCancer discovery \u003c/em\u003e7: 561-574, 2017.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Breast Cancer; Menstruation; Neoadjuvant Chemotherapy; Oestrogen Receptor; Progesterone Receptor.","lastPublishedDoi":"10.21203/rs.3.rs-16004/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-16004/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground : To explore the predictive indicators in hormone receptor (HR)-positive breast cancer (BC) patients receiving neoadjuvant chemotherapy (NACT) and to evaluate the value of quantitative oestrogen receptor (ER) and progesterone receptor (PR) in predicting tumour response. Methods : Six hundred eighty-nine BC patients with HR-positive status who were treated with anthracycline, epirubicin and taxane NACT treatment were retrospectively analysed. Clinical and pathological features of the patients were used to evaluate the response to NACT. Results : Patients with larger tumour sizes ( OR 1.657 CI 1.186-2.313 p=0.003 ), those who were in a premenopausal status ( OR 1.458 CI 1.039-2.045 p=0.029 ) and those with higher Ki67 levels ( OR 1.735 CI 1.231-2.444 p=0.002 ) exhibited a better therapy response. Among the patients in the postmenopausal subgroup, a lower pretreatment ER or PR expression were associated with a reduction in tumour size, and the cut-off values for ER and PR were 87.5% and 65%, respectively ( p=0.006 and p=0.05 ). Decreased expression of ER and PR was also observed after NACT treatment ( p=0.028 and p\u0026lt;0.001, respectively ) but played only a predictive role in the Her-2-negative subgroup; the cut-off values for decreased ER and PR were 17.5% and 26.5%, respectively ( p=0.044 and p\u0026lt;0.001 ). Conclusions : Semiquantified pretreatment HR expression can be used to predict the response of NACT in postmenopausal BC patients. Decreased ER and PR expression is also associated with a reduction in tumour size in Her-2-negative subtypes treated with NACT.\u003c/p\u003e","manuscriptTitle":"Assessment of the predictive role of oestrogen and progesterone receptor status in breast cancer patients treated with neoadjuvant chemotherapy: A retrospective analysis for 689 patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-03-04 17:08:39","doi":"10.21203/rs.3.rs-16004/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"46e2f306-9b5c-4df5-bab1-ad25018dddba","owner":[],"postedDate":"March 4th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":66029,"name":"Oncology"}],"tags":[],"updatedAt":"","versionOfRecord":[],"versionCreatedAt":"2020-03-04 17:08:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-16004","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-16004","identity":"rs-16004","version":["v1"]},"buildId":"omnImTCwR2MFx8CMYfrG7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}