Assessing the clinical utility of preoperative neutrophil-lymphocyte ratio as a predictor of clinicopathological parameters in patients being treated for primary breast cancer

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Jaffer, Juliette Buckley, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4481633/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Jan, 2025 Read the published version in Breast Cancer Research and Treatment → Version 1 posted 16 You are reading this latest preprint version Abstract Background There is a paucity of data supporting the role of neutrophil-lymphocyte ratios (NLR) to determine clinicopathological parameters in patients being treated for primary breast cancer. Aims To evaluate the association between preoperative NLR and clinicopathological parameters in patients diagnosed with breast cancer. Methods A retrospective cohort study was performed. This included consecutive patients indicated to undergo surgery for primary breast cancer at University Hospital Limerick between January 2010 - June 2017. NLR was expressed as a continuous variable. Univariable and multivariable linear regression analyses were used to determine the correlation between NLR and clinicopathological data. Data analytics was performed using SPSS v29.0. Results 673 patients met the inclusion criteria. Overall, the median preoperative NLR of 2.63 (standard deviation: 1.42). At univariable analysis, patient age (beta coefficient: 0.009, 95% confidence interval (CI): 0.001–0.017, P = 0.027), tumour size (beta coefficient: 0.013, 95% CI: 0.005–0.021, P = 0.001), and human epidermal growth factor receptor-2 status (beta coefficient: -0.370, 95% CI: -0.676 - -0.065, P = 0.017) were all predicted using NLR. However, at multivariable analysis, tumour size was the sole parameter predictable by NLR (beta coefficient: 0.011, 95% CI: 0.002–0.019, P = 0.013). Conclusions This study demonstrates that preoperative NLR may serve as an independent predictor of tumour size in patients being treated with primary breast cancer. Ratification of these preliminary findings is warranted before robustly adopted into clinical practice. Breast Cancer immunology oncological outcomes precision oncology personalised medicine Introduction Breast cancer is a heterogenous disease with an increasing incidence in the western world ( 1 ). Fortunately, the molecular classificiation of the disease has facilitated personalised multimodal treatment strategies, which have translated to enhanced outcomes for the majority of those diagnosed with the disease ( 2 ). It is important to note, there may be important biochemical information which is routinely available from basic patient workup, which may prove useful in predicting certain aggressive phenotypical characteristics of such tumours ( 3 ). Therefore, the identification of new low-cost diagnostic biomarkers which aid diagnosis is important, and their relevance in the context of treatment and prognosis of in breast cancer may also be of importance ( 4 – 6 ). Thus, translational research efforts have focused on the providing such biomarkers which may aid contemporary breast cancer diagnosis ( 3 ). Evaluating impact of the tumor microenvironment upon various epithelial cancer subtypes has been the objective of oncological research for several years now ( 7 ). Inflammation is a well established hallmark of cancer, which has propogated investigation to assess the clinical roll of inflammatory markers ( 8 ), such as neutrophils and lymphocytes, in both the tumor microenvironment and circulation of those who succumb to breast cancer diagnoses ( 9 ). Neutrophil-lymphocyte ratio (NLR) is a calculation of the total neutrophil count divided by total lymphocyte count, which seems to serve as a biomarker which expresses the balance of anti-tumour and tumour-promoting effects of circulating cells, thus offering potential value as a predictive biomarker into oncogeneis and development ( 8 , 9 ). At present, there is preliminarey data supporting the prognostic use of NLR in breast cancer for predicting oncological outcomes such as response to neoadjuvant chemotherapy, and survival outcomes such as recurrence-free (RFS) and overall survival (OS) outcomes ( 10 – 12 ). Furthermore, there is emerging data which suggests that NLR may provide data with utility in serving in deciphering breast cancer molecular subtype ( 13 ). In spite of these proming findings, there remains a paucity of studies which evaluate the value of using NLR to potentially predict routine clinicopathological characteristics of those treated for primary breast cancer. In particular, such a biomarker may be useful in less well resourced hospitals in healthcare economies challenged by less access to diagnostics. Accordingly, the aim of the current study was to evaluate the clinical utility of pre-operative NLR as a predictor of clinicopathological parameters in patients with primary breast cancer. Methods Local hospital ethical approval was sought and obtained. A single centre, retrospective observational cohort study was undertaken, including consecutive patients undergoing primary breast cancer surgery at an Irish tertiary referral centre (University Hospital Limerick (UHL)), with associated academic institution. (University of Limerick (UL)). Review of a prospectively maintained institutional database for patients treated in this unit was performed, with data augmented through verification of clinic letters, mammogram reports and blood work values. The study was performed and reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for observation studies ( 14 ). Patient Selection The inclusion criteria fort he current study included adult female patients, aged 18 years or older, who were diagnosed and treated a new diagnosis of breast cancer between January 1st, 2010 and June 1st, 2017 in UHL. All cancer diagnoses were confirmed by core biopsy or radiologically suspicious lesion concerning for malignancy discussed in a multidisciplinary meeting. Those that underwent primary surgery during that period were included in the analysis. Excluded from this cohort were patients who received neoadjuvant chemotherapy, had metastatic (M1) disease at presentation, patients that declined surgical intervention, as well as patients that presented with recurrent disease either from outside of the time period or from during the same time period, so as not to duplicate numbers. Patients that underwent prophylactic mastectomy which yielded histology positive for invasive carcinoma were excluded from the analysis. Participants without complete circulatory biomarker values were excluded from analysis. Patient Follow-Up Patient pollow-up was conducted in person until five years post-operatively before being discharged from the service. This was acheived using clinic letters and imaging results prior to June 1, 2022. Hospital computers were used to further delineate long-term follow-up. Last formal review of medical notes was performed in November 2023. Triple Assessment Patients presented for triple assessment in the specialised breast cancer tertiary referral centre: a consultant breast surgeon performed clinical breast examinations on presentation, tissue biopsies were analysed by a consultant pathologist with expertise in breast pathology, and radiological assessment was conducted by a specialist breast consultant radiologist by mammography and/or ultrasound scanning. Tumour staging was performed in accordance with the American Joint Committee on Cancer (AJCC), version 8 Guidelines ( 15 ). Histopathologic Assessment and Immunohistochemistry Estrogen (ER) and progesterone (PgR) receptor status on tumour specimens were analysed using the 2010 American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP) histopathological consensus guidelines, although reporting was performed using the Allred scoring system ( 16 , 17 ). Human epidermal growth factor receptor-2 (HER2/neu) status was determined using immunohistochemistry, and patients scoring 2 + proceeded for fluorescence in-situ hybridization to confirm HER2 status. Each specimen underwent histopathological grading in accordance to the Elston-Ellis modification of the Scarff-Bloom-Richardson grading system (as per the World Health Organisation Classification of Tumours Guidelines) ( 18 ). Tumour lymphatic invasion was evaluated utilising IHC staining with D2-40 ( 19 ). Vascular invasion was assessed by IHC using CD34 ( 20 ). Perineural invasion was determined using IHC staining with S-100 and a broad spectrum keratin stain (AE1/AE3) ( 21 ). Ki-69 was evaluated using MIB1 antibody testing ( 22 ). Neutrophil-Lymphocyte Ratio In the 30 days prior to cancer resection, peripheral venesection was performed as a component of formal preoperative assessment. Thereafter, neutrophil count and lymphocyte count were recorded, and neutrophil-lymphocyte ratios (NLR) were calculated using the following formula: NLR = absolute neutrophil count / absolute lymphocyte count. Statistical analysis Continuous variables are reported as medians with standard deviation (SD), while categorical variables are reported as frequencies and percentages. Linear regression results are reported as beta coefficient with a 95% confidence interval (CI) to decipher the relationship and directionality of clinicopathological data and NLR. All tests of significance were 2-tailed, with P < 0.050 indicating statistical significance. Descriptive analysis and regression analysis were conducted with SPSS (Version 29.0). Clinicopathological patient data were analysed using descriptive statistics. Fisher’s exact (¶), Chi-squared (χ2), one-way analysis of variance (ANOVA, ) and Kruskal Wallis (§) tests were used as appropriate. Survival outcomes and patterns of metastasis were also recorded. Results Clinicalopathological Information In total, 673 patients met the inclusion criteria. The mean age at diagnosis was 57.96 ± 13.79 years (range 26–88). Two hundred and thirteen patients were pre-menopausal, while 17 were peri-menopausal, and 328 were post-menopausal. Majority of patients (79.2%) has been diagnosed with invasive ductal carcinoma (IDC), followed by invasive lobular carcinoma (ILC) (12.5%) and ductal carcinoma in situ (DCIS) (4.9%). One hundred and eighty nine patients had associated DCIS while 54 did not. Most patients’ tumour was staged T2 (45.2%), followed by T1 (38.2%) while only 7.4% and 1.2% of the patients were T3 and T4, respectively. Fourty three patients had Tis/T0 breast cancer (BC). More than half of the patients (57.9%) had grade 2 BC while 167 had grade 3 and 59 had grade 1 BC. Four hundred and two patients had N-stage 0 along with 167 N-stage 1, 59 N-stage 2 and 34 N-stage 3. Most patients (628) had unilateral BC while 31 had bilateral BC. One hundred and fifty two patients had no lymphatic invasion while 61 had no invasion with the remaining patients’ status unknown. Majority of patients have hormone receptor positive BC; 516 ER + and 432 PR+. Five hundred and fifty three patients have HER2- and 106 have HER2 + BC. The mean tumour size was 25.71 ± 16.191mm. Table 1 Descriptive statistics of the patient population Variables Age at diagnosis Mean ± SD (range); median 57.96 ± 13.790 (62); 58 Menopausal status at diagnosis Pre-menopause 213 (31.6%) Peri-menopause 17 (2.5%) Post-menopause 328 (48.7%) Histological subtype IDC 533 (79.2%) ILC 84 (12.5%) Mucinous 8 (1.2%) Other 15 (2.2%) DCIS 33 (4.9%) Tumour stage T0 43 (6.4%) T1 257 (38.2%) T2 304 (45.2%) T3 50 (7.4%) T4 8 (1.2%) Tumour grade 0 1 (0.1%) 1 59 (8.8%) 2 390 (57.9%) 3 167 (24.8%) N-stage 0 402 (59.7%) 1 167 (24.8%) 2 59 (8.8%) 3 34 (5.1%) Tumour size Mean ± SD (range); median 25.71 ± 16.191 (100); 22 Bilateral cancer Yes 31 (4.6%) No 628 (93.3%) Lymphatic invasion Yes 61 (9.1%) No 152 (22.6%) Associated DCIS Yes 189 (28.1%) No 54 (8.0%) Neoadjuvant chemotherapy Yes 94 (14%) No 579 (86%) Adjuvant chemotherapy Yes 289 (42.9%) No 371 (55.1%) Adjuvant radiation therapy Yes 471 (70%) No 186 (27.6%) Adjuvant endocrine therapy Yes 510 (75.8%) No 158 (23.5%) Extended endocrine therapy Yes 80 (11.9%) No 239 (35.5%) ER status Positive 516 (76.7%) Negative 143 (21.2%) PR status Positive 432 (64.2%) Negative 227 (33.7%) HER2 status Positive 106 (15.8%) Negative 553 (82.2%) Recurrence Yes 121 (18%) No 552 (82%) Local recurrence Yes 50 (7.4%) No 622 (92.4%) Local recurrence at 5 years Yes 47 (7.0%) No 626 (93%) Procedure WLE 345 (51.3%) Mastectomy 326 (48.4%) Axillary procedure SLNB/SLND 427 (63.4%) ALNB/ALND 235 (34.9%) Metastasis Yes 91 (13.5%) No 581 (86.3%) Metastasis at 5 years Yes 69 (10.3%) No 604 (89.7%) Site of metastasis Bone 35 (5.2%) Brain 4 (0.6%) Contralateral breast 2 (0.3%) En Cuirasse 1 (0.1%) Liver 6 (0.9%) Lung 11 (1.6%) Lymph nodes 8 (1.2%) Omentum 1 (0.1%) Skin 1 (0.1%) Uterus 1 (0.1%) Multiple sites 19 (2.8%) Follow up time (months) Mean ± SD (range); median 66.85 ± 27.983 (140); 65.0 Time to death (years) Mean ± SD (range); median 3.61 ± 2.374 ( 10 ); 3.0 Management Strategies Three hundred and fourty five patients had breast conserving surgery while 326 patients undergone mastectomy. Four hundred and twenty seven patients had either sentinel node biopsy (SLNB) or sentinel node dissection (SLND) while 235 patients either had axillary lymph node biopsy (ALNB) or axillary lymph node dissection (ALND). Adjuvant chemotherapy was received by 371 patients (55.1%). Most patients received neoadjuvant chemotherapy (86%), adjuvant radiation therapy (70%), adjuvant endocrine therapy (75.8%). Eighty patients received extended endocrine therapy. Oncological and Survival Outcomes Eigthy two percent (552) of the patients had no recurrence while 622 patients had no local recurrence. Local recurrence at 5 years has been observed in 47 patients. Overall, 91 patients had metastatic BC with the most common site of metastasis being the bone (32) followed by multiple sites ( 19 ), lung ( 11 ), lymph nodes ( 8 ), liver ( 6 ), and brain ( 4 ). The patients were followed up after the operation for 66.85 ± 27.98 months. The average time to death was 3.61 ± 2.37 years. The descriptive statistics of the patients with primary breast cancer were shown in Table 1 . The mean pre-operative NLR value of patients included in this study was 2.98 ± 1.46 (range 0.07–13.49) which was shown in Table 2 . Table 2 Neutrophil-lymphocyte ratio Mean Median Std. Deviation Range NLR 2.98 2.64 1.46 13.42 Correaltion between Neutrophil-Lymphcyte Ratio and Clinicopathaological Data There was a positive correlation between the age at the time of surgery and the pre-operative NLR (r = 0.086) which was statistically significant (p = 0.027). The tumours size was also positively correlated with the pre-operative NLR (r = 0.164) which was statistically significant (p = 0.001). The mean difference in pre-operative NLR (0.370) among HER2 + and HER2- groups was statistically significant (p = 0.017). Menopause, tumour stage and grade, nodal involvement, histological subtype of the tumour, accompanying DCIS, LVI, ER/PR status, bilateral presence of BC, neoadjuvant chemotherapy and the type of procedure were not associated with pre-operative NLR value. The relationship between clinicopathological parameters of breast cancer and serum levels of pre-operative NLR are shown in Table 3 . Table 3 Association between clinicopathological characteristics and NLR Correlation Test Clinicopathological characteristics Pre-operative NLR Age at the time of the surgery Pearson Correlation 0.086 p-value (2-tailed) 0.027 Tumour size Pearson Correlation 0.164 p-value (2-tailed) 0.001 ANOVA Clinicopathological characteristics Sum of squares df Mean Square F p-value Menopause 434.117 467 0.930 1.005 0.503 pT 315.487 536 0.589 0.914 0.749 pN 388.627 535 0.726 0.960 0.626 Grade 179.632 507 0.354 1.206 0.118 Histological subtype 526.887 543 0.970 0.981 0.567 Independent Samples Test Clinicopathological characteristics Mean Difference 95% CI p-value Lower Upper Accompanying histology DCIS 0.157 -0.218 0.532 0.410 No DCIS LVI Yes 0.065 -0.305 0.436 0.729 No ER ER+ 0.069 -0.203 0.341 0.618 ER- PgR PgR+ 0.155 -0.081 0.390 0.198 PgR- HER2 HER2+ 0.370 0.065 0.675 0.017 HER2- Bilateral cancer Yes -0.363 -0.892 0.166 0.178 No NAC Yes -0.247 -0.567 0.072 0.129 No Procedure WLE -0.161 -0.383 0.061 0.154 Mastectomy Regression Analyses for Neutrophil-Lymphcyte Ratio and Clinicopathaological Data Univariable linear regression analysis showed that only age at the time of surgery (β = 0.009, 95% CI = 0.001–0.017, P = 0.027), tumour size (β = 0.013, 95% CI = 0.005–0.021, P = 0.001), and HER2 status (β= -0.370, 95% CI= -0.676 - -0.065, P = 0.017) were associated with pre-operative NLR. Multivariable linear regression analysis revealed that the tumour size (β = 0.011, 95% CI = 0.002–0.019, P = 0.013) was the only clinicopathological parameter correlating statistically significantly with pre-operative NLR in this study. The results of the univariable and multivariable linear regression analysis were detailed in Table 4 . Table 4 Linear regression analysis of clinicopathological characteristics and pre-operative NLR Univariable Multivariable Variables β (95% CI) p-value β (95% CI) p-value Age 0.009 (0.001–0.017) 0.027 0.007 (-0.003-0.017) 0.162 Menopause 0.037 (-0.090-0.165) 0.564 T-stage 0.034 (-0.111-0.178) 0.649 N-stage -0.031 (-0.161-0.100) 0.647 Histological subtype -0.067 (-0.180-0.045) 0.238 Grade 0.063 (-0.138-0.263) 0.539 Accompanying histology -0.157 (-0.533-0.218) 0.410 LVI -0.065 (-0.436-0.306) 0.729 Tumor size 0.013 (0.005–0.021) 0.001 0.011 (0.002–0.019) 0.013 ER -0.069 (-0.341-0.203) 0.618 PR -0.155 (-0.391-0.081) 0.198 HER2 -0.370 (-0.676- -0.065) 0.017 -0.218 (-0.612-0.176) 0.277 Bilateral cancer 0.363 (-0.166-0.892) 0.178 Discussion This study has evaluated the predictive value of the preoperative neutrophil-lymphocyte ratio in relation to clinico-pathological parameters of BC, such as age, histological subtype, tumour grade, pT stage, pN stage, LVI, tumour size, HER2/ER/PR, and menopausal status. Given the propensity for HER2 tumours to be traditionally considered of aggressive tumour biology ( 4 ), it is somewhat unsurprising that our data demonstrated a correlation between HER2 status and NLR. Moreover, aggressive tumour biology tends to be diagnosed at a later stage ( 23 ), which supports the notion that increased NLR should be associated with increased tumour burden. Although there is a growing body of knowledge on this topic, the findings are inconsistent with existing literature, demonstrating the novelty of these results, and also the requirement for more robust analyses of NLR in the clinical setting. These results demonstrated that preoperative NLR may have a potential predictive value of age, tumour size, and HER2 status in patients with primary BC. Contrary to this study, Zhu et al. previously reported that NLR was significantly higher in younger and premenopausal women, refuting the results of the current study ( 24 ). Concordant with the current study, Jadoon et al. demonstrated that NLR was significantly correlated with tumour size while no difference in histological grading, metastasis, surgical modality, sentinel or axillary node status were observed ( 25 ). However, they also illustrate NLR to be associated with tumour stage 1 and nodal stage 2/3 which is not consistent with the results of the present study. Moreover, Yang et al. reported that NLR had no significant association with age, tumor size, ER/PR/HER2 status and Ki67 expression assays, however did have a correlation with p53 expression and lymph node metastasis ( 26 ). Sun et al. also described no correlation between NLR and clinicopathological parameters including age, HER2 status, and tumor size ( 27 ). While these results add fuel to this clinical conundrum, it is of importance to note that the current data was derived from a significantly larger database from a high-volume tertiary referral centre retrospectively for treatment of patients diagnosed with primary breast cancer. These results also demonstrated that there is a significant relationship between NLR and tumour size, thus suggesting that increased acute phase reactants may be expected with increasing tumour burden. Interestingly, Takeuchi et al. also reported significant relationship between NLR and tumor size in their previous analysis ( 28 ), supporting these findings. There are limitations to this study. Firstly, this study is of retrospective design rendering it likely to be subject to selection, confounding and ascertainment biases. Secondly, this study did not use an external validation cohort, which would prove fruitful in further ascertaining the relevance of these findings in clinical practice. Finally, while these results are of interest for translational research purposes, this study fails to cast light into the relavance of such results into clinical practice, as formal staging and histopathological tumour evaluation through the multidiciplinary process will not be deterred by NLR. In conclusion, this study demonstrates that preoperative NLR has an independent predictive value in terms of tumour size in patients being treated with primary BC. Ratification of these preliminary findings is warranted before robustly adopted into clinical practice. Declarations Author Contribution BI, MG, AJ wrote the main manuscript text. BI and MG prepared the tables. All authors reviewed the manuscript. Data Availability Data is provided within the manuscript. References Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A (2018) Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. 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Cite Share Download PDF Status: Published Journal Publication published 20 Jan, 2025 Read the published version in Breast Cancer Research and Treatment → Version 1 posted Editorial decision: Revision requested 05 Aug, 2024 Reviews received at journal 05 Aug, 2024 Reviews received at journal 18 Jul, 2024 Reviewers agreed at journal 16 Jul, 2024 Reviewers agreed at journal 10 Jul, 2024 Reviewers agreed at journal 09 Jul, 2024 Reviewers agreed at journal 09 Jul, 2024 Reviews received at journal 03 Jul, 2024 Reviewers agreed at journal 30 Jun, 2024 Reviews received at journal 19 Jun, 2024 Reviewers agreed at journal 09 Jun, 2024 Reviewers agreed at journal 09 Jun, 2024 Reviewers invited by journal 09 Jun, 2024 Submission checks completed at journal 27 May, 2024 Editor assigned by journal 27 May, 2024 First submitted to journal 26 May, 2024 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board 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-4481633","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":313605660,"identity":"57d40954-fdaf-41b6-935b-047e12e749d1","order_by":0,"name":"Burce Isik","email":"data:image/png;base64,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","orcid":"","institution":"University of Limerick School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Burce","middleName":"","lastName":"Isik","suffix":""},{"id":313605663,"identity":"447ada82-ab4a-49ea-a210-e28ba10f2110","order_by":1,"name":"Matthew G Davey","email":"","orcid":"","institution":"University Hospital Limerick","correspondingAuthor":false,"prefix":"","firstName":"Matthew","middleName":"G","lastName":"Davey","suffix":""},{"id":313605665,"identity":"86815db6-f405-48da-b564-2845274c6f4e","order_by":2,"name":"Alisha A. Jaffer","email":"","orcid":"","institution":"University of Limerick School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Alisha","middleName":"A.","lastName":"Jaffer","suffix":""},{"id":313605666,"identity":"013bebfe-7510-4a85-8822-f10205a5ec3a","order_by":3,"name":"Juliette Buckley","email":"","orcid":"","institution":"University Hospital Limerick","correspondingAuthor":false,"prefix":"","firstName":"Juliette","middleName":"","lastName":"Buckley","suffix":""},{"id":313605667,"identity":"ada04d30-ac9e-4f57-a886-bbef59a5974b","order_by":4,"name":"Chwanrow Baban","email":"","orcid":"","institution":"University Hospital Limerick","correspondingAuthor":false,"prefix":"","firstName":"Chwanrow","middleName":"","lastName":"Baban","suffix":""},{"id":313605669,"identity":"4b98b616-be54-4031-9902-ab8500d4f4bb","order_by":5,"name":"Bridget Anne Merrigan","email":"","orcid":"","institution":"University Hospital Limerick","correspondingAuthor":false,"prefix":"","firstName":"Bridget","middleName":"Anne","lastName":"Merrigan","suffix":""},{"id":313605671,"identity":"6f5169e1-83c3-497d-8893-23ba000c6e43","order_by":6,"name":"Shona Tormey","email":"","orcid":"","institution":"University Hospital Limerick","correspondingAuthor":false,"prefix":"","firstName":"Shona","middleName":"","lastName":"Tormey","suffix":""}],"badges":[],"createdAt":"2024-05-27 00:57:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4481633/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4481633/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10549-025-07615-8","type":"published","date":"2025-01-20T15:57:03+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":74858301,"identity":"e097b06c-a6a2-4d52-8e0c-cb511fe12bd5","added_by":"auto","created_at":"2025-01-27 16:06:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1568948,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4481633/v1/57343d06-7bec-4dbe-bef0-efd23598438f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessing the clinical utility of preoperative neutrophil-lymphocyte ratio as a predictor of clinicopathological parameters in patients being treated for primary breast cancer","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBreast cancer is a heterogenous disease with an increasing incidence in the western world (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Fortunately, the molecular classificiation of the disease has facilitated personalised multimodal treatment strategies, which have translated to enhanced outcomes for the majority of those diagnosed with the disease (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). It is important to note, there may be important biochemical information which is routinely available from basic patient workup, which may prove useful in predicting certain aggressive phenotypical characteristics of such tumours (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Therefore, the identification of new low-cost diagnostic biomarkers which aid diagnosis is important, and their relevance in the context of treatment and prognosis of in breast cancer may also be of importance (\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Thus, translational research efforts have focused on the providing such biomarkers which may aid contemporary breast cancer diagnosis (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEvaluating impact of the tumor microenvironment upon various epithelial cancer subtypes has been the objective of oncological research for several years now (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Inflammation is a well established hallmark of cancer, which has propogated investigation to assess the clinical roll of inflammatory markers (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), such as neutrophils and lymphocytes, in both the tumor microenvironment and circulation of those who succumb to breast cancer diagnoses (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Neutrophil-lymphocyte ratio (NLR) is a calculation of the total neutrophil count divided by total lymphocyte count, which seems to serve as a biomarker which expresses the balance of anti-tumour and tumour-promoting effects of circulating cells, thus offering potential value as a predictive biomarker into oncogeneis and development (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAt present, there is preliminarey data supporting the prognostic use of NLR in breast cancer for predicting oncological outcomes such as response to neoadjuvant chemotherapy, and survival outcomes such as recurrence-free (RFS) and overall survival (OS) outcomes (\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Furthermore, there is emerging data which suggests that NLR may provide data with utility in serving in deciphering breast cancer molecular subtype (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). In spite of these proming findings, there remains a paucity of studies which evaluate the value of using NLR to potentially predict routine clinicopathological characteristics of those treated for primary breast cancer. In particular, such a biomarker may be useful in less well resourced hospitals in healthcare economies challenged by less access to diagnostics. Accordingly, the aim of the current study was to evaluate the clinical utility of pre-operative NLR as a predictor of clinicopathological parameters in patients with primary breast cancer.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e Local hospital ethical approval was sought and obtained. A single centre, retrospective observational cohort study was undertaken, including consecutive patients undergoing primary breast cancer surgery at an Irish tertiary referral centre (University Hospital Limerick (UHL)), with associated academic institution. (University of Limerick (UL)). Review of a prospectively maintained institutional database for patients treated in this unit was performed, with data augmented through verification of clinic letters, mammogram reports and blood work values. The study was performed and reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for observation studies (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatient Selection\u003c/h2\u003e \u003cp\u003e The inclusion criteria fort he current study included adult female patients, aged 18 years or older, who were diagnosed and treated a new diagnosis of breast cancer between January 1st, 2010 and June 1st, 2017 in UHL. All cancer diagnoses were confirmed by core biopsy or radiologically suspicious lesion concerning for malignancy discussed in a multidisciplinary meeting. Those that underwent primary surgery during that period were included in the analysis. Excluded from this cohort were patients who received neoadjuvant chemotherapy, had metastatic (M1) disease at presentation, patients that declined surgical intervention, as well as patients that presented with recurrent disease either from outside of the time period or from during the same time period, so as not to duplicate numbers. Patients that underwent prophylactic mastectomy which yielded histology positive for invasive carcinoma were excluded from the analysis. Participants without complete circulatory biomarker values were excluded from analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003ePatient Follow-Up\u003c/h2\u003e \u003cp\u003ePatient pollow-up was conducted in person until five years post-operatively before being discharged from the service. This was acheived using clinic letters and imaging results prior to June 1, 2022. Hospital computers were used to further delineate long-term follow-up. Last formal review of medical notes was performed in November 2023.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eTriple Assessment\u003c/h2\u003e \u003cp\u003ePatients presented for triple assessment in the specialised breast cancer tertiary referral centre: a consultant breast surgeon performed clinical breast examinations on presentation, tissue biopsies were analysed by a consultant pathologist with expertise in breast pathology, and radiological assessment was conducted by a specialist breast consultant radiologist by mammography and/or ultrasound scanning. Tumour staging was performed in accordance with the American Joint Committee on Cancer (AJCC), version 8 Guidelines (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eHistopathologic Assessment and Immunohistochemistry\u003c/h2\u003e \u003cp\u003eEstrogen (ER) and progesterone (PgR) receptor status on tumour specimens were analysed using the 2010 American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP) histopathological consensus guidelines, although reporting was performed using the Allred scoring system (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Human epidermal growth factor receptor-2 (HER2/neu) status was determined using immunohistochemistry, and patients scoring 2\u0026thinsp;+\u0026thinsp;proceeded for fluorescence in-situ hybridization to confirm HER2 status. Each specimen underwent histopathological grading in accordance to the Elston-Ellis modification of the Scarff-Bloom-Richardson grading system (as per the World Health Organisation Classification of Tumours Guidelines) (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Tumour lymphatic invasion was evaluated utilising IHC staining with D2-40 (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Vascular invasion was assessed by IHC using CD34 (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Perineural invasion was determined using IHC staining with S-100 and a broad spectrum keratin stain (AE1/AE3) (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Ki-69 was evaluated using MIB1 antibody testing (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eNeutrophil-Lymphocyte Ratio\u003c/h2\u003e \u003cp\u003eIn the 30 days prior to cancer resection, peripheral venesection was performed as a component of formal preoperative assessment. Thereafter, neutrophil count and lymphocyte count were recorded, and neutrophil-lymphocyte ratios (NLR) were calculated using the following formula:\u003c/p\u003e \u003cp\u003e \u003cem\u003eNLR\u0026thinsp;=\u0026thinsp;absolute neutrophil count / absolute lymphocyte count.\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables are reported as medians with standard deviation (SD), while categorical variables are reported as frequencies and percentages. Linear regression results are reported as beta coefficient with a 95% confidence interval (CI) to decipher the relationship and directionality of clinicopathological data and NLR. All tests of significance were 2-tailed, with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.050 indicating statistical significance. Descriptive analysis and regression analysis were conducted with SPSS (Version 29.0). Clinicopathological patient data were analysed using descriptive statistics. Fisher\u0026rsquo;s exact (\u0026para;), Chi-squared (χ2), one-way analysis of variance (ANOVA, ) and Kruskal Wallis (\u0026sect;) tests were used as appropriate. Survival outcomes and patterns of metastasis were also recorded.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eClinicalopathological Information\u003c/h2\u003e \u003cp\u003eIn total, 673 patients met the inclusion criteria. The mean age at diagnosis was 57.96\u0026thinsp;\u0026plusmn;\u0026thinsp;13.79 years (range 26\u0026ndash;88). Two hundred and thirteen patients were pre-menopausal, while 17 were peri-menopausal, and 328 were post-menopausal. Majority of patients (79.2%) has been diagnosed with invasive ductal carcinoma (IDC), followed by invasive lobular carcinoma (ILC) (12.5%) and ductal carcinoma in situ (DCIS) (4.9%). One hundred and eighty nine patients had associated DCIS while 54 did not. Most patients\u0026rsquo; tumour was staged T2 (45.2%), followed by T1 (38.2%) while only 7.4% and 1.2% of the patients were T3 and T4, respectively. Fourty three patients had Tis/T0 breast cancer (BC). More than half of the patients (57.9%) had grade 2 BC while 167 had grade 3 and 59 had grade 1 BC. Four hundred and two patients had N-stage 0 along with 167 N-stage 1, 59 N-stage 2 and 34 N-stage 3. Most patients (628) had unilateral BC while 31 had bilateral BC. One hundred and fifty two patients had no lymphatic invasion while 61 had no invasion with the remaining patients\u0026rsquo; status unknown. Majority of patients have hormone receptor positive BC; 516 ER\u0026thinsp;+\u0026thinsp;and 432 PR+. Five hundred and fifty three patients have HER2- and 106 have HER2\u0026thinsp;+\u0026thinsp;BC. The mean tumour size was 25.71\u0026thinsp;\u0026plusmn;\u0026thinsp;16.191mm.\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 \u003cp\u003eDescriptive statistics of the patient population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at diagnosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (range); median\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57.96\u0026thinsp;\u0026plusmn;\u0026thinsp;13.790 (62); 58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eMenopausal status at diagnosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePre-menopause\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e213 (31.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePeri-menopause\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePost-menopause\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e328 (48.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eHistological subtype\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eIDC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e533 (79.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eILC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84 (12.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMucinous\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOther\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (2.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDCIS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eTumour stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eT0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43 (6.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eT1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e257 (38.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eT2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e304 (45.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eT3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (7.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eT4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eTumour grade\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59 (8.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e390 (57.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e167 (24.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eN-stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e402 (59.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e167 (24.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59 (8.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumour size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (range); median\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.71\u0026thinsp;\u0026plusmn;\u0026thinsp;16.191 (100); 22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eBilateral cancer\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e628 (93.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eLymphatic invasion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (9.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e152 (22.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eAssociated DCIS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e189 (28.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (8.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eNeoadjuvant chemotherapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94 (14%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e579 (86%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eAdjuvant chemotherapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e289 (42.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e371 (55.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eAdjuvant radiation therapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e471 (70%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e186 (27.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eAdjuvant endocrine therapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e510 (75.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e158 (23.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eExtended endocrine therapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80 (11.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e239 (35.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eER status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e516 (76.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNegative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e143 (21.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003ePR status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e432 (64.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNegative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e227 (33.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eHER2 status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106 (15.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNegative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e553 (82.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eRecurrence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e121 (18%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e552 (82%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eLocal recurrence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (7.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e622 (92.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eLocal recurrence at 5 years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (7.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e626 (93%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eProcedure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eWLE\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e345 (51.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMastectomy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e326 (48.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eAxillary procedure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSLNB/SLND\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e427 (63.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eALNB/ALND\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e235 (34.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMetastasis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91 (13.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e581 (86.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMetastasis at 5 years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69 (10.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e604 (89.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"10\" rowspan=\"11\"\u003e \u003cp\u003e\u003cb\u003eSite of metastasis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eBone\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (5.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eBrain\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eContralateral breast\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eEn Cuirasse\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLiver\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLung\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLymph nodes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOmentum\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSkin\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eUterus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMultiple sites\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFollow up time (months)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (range); median\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.85\u0026thinsp;\u0026plusmn;\u0026thinsp;27.983 (140); 65.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTime to death (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (range); median\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.61\u0026thinsp;\u0026plusmn;\u0026thinsp;2.374 (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e); 3.0\u003c/p\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=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eManagement Strategies\u003c/h2\u003e \u003cp\u003eThree hundred and fourty five patients had breast conserving surgery while 326 patients undergone mastectomy. Four hundred and twenty seven patients had either sentinel node biopsy (SLNB) or sentinel node dissection (SLND) while 235 patients either had axillary lymph node biopsy (ALNB) or axillary lymph node dissection (ALND). Adjuvant chemotherapy was received by 371 patients (55.1%). Most patients received neoadjuvant chemotherapy (86%), adjuvant radiation therapy (70%), adjuvant endocrine therapy (75.8%). Eighty patients received extended endocrine therapy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eOncological and Survival Outcomes\u003c/h2\u003e \u003cp\u003eEigthy two percent (552) of the patients had no recurrence while 622 patients had no local recurrence. Local recurrence at 5 years has been observed in 47 patients. Overall, 91 patients had metastatic BC with the most common site of metastasis being the bone (32) followed by multiple sites (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), lung (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), lymph nodes (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), liver (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), and brain (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). The patients were followed up after the operation for 66.85\u0026thinsp;\u0026plusmn;\u0026thinsp;27.98 months. The average time to death was 3.61\u0026thinsp;\u0026plusmn;\u0026thinsp;2.37 years. The descriptive statistics of the patients with primary breast cancer were shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe mean pre-operative NLR value of patients included in this study was 2.98\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46 (range 0.07\u0026ndash;13.49) which was shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNeutrophil-lymphocyte ratio\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStd. Deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNLR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.42\u003c/p\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=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCorrealtion between Neutrophil-Lymphcyte Ratio and Clinicopathaological Data\u003c/h2\u003e \u003cp\u003eThere was a positive correlation between the age at the time of surgery and the pre-operative NLR (r\u0026thinsp;=\u0026thinsp;0.086) which was statistically significant (p\u0026thinsp;=\u0026thinsp;0.027). The tumours size was also positively correlated with the pre-operative NLR (r\u0026thinsp;=\u0026thinsp;0.164) which was statistically significant (p\u0026thinsp;=\u0026thinsp;0.001). The mean difference in pre-operative NLR (0.370) among HER2\u0026thinsp;+\u0026thinsp;and HER2- groups was statistically significant (p\u0026thinsp;=\u0026thinsp;0.017). Menopause, tumour stage and grade, nodal involvement, histological subtype of the tumour, accompanying DCIS, LVI, ER/PR status, bilateral presence of BC, neoadjuvant chemotherapy and the type of procedure were not associated with pre-operative NLR value. The relationship between clinicopathological parameters of breast cancer and serum levels of pre-operative NLR are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between clinicopathological characteristics and NLR\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c10\" namest=\"c4\"\u003e \u003cp\u003eCorrelation Test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eClinicopathological characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c10\" namest=\"c4\"\u003e \u003cp\u003ePre-operative NLR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c3\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eAge at the time of the surgery\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003ePearson Correlation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003ep-value (2-tailed)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.027\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c3\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eTumour size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003ePearson Correlation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003ep-value (2-tailed)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c11\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003eANOVA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinicopathological characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSum of squares\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003edf\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003eMean Square\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMenopause\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e434.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003e1.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.503\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003epT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e315.487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003e0.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.749\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003epN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e388.627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003e0.960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.626\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGrade\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e179.632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003e1.206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHistological subtype\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e526.887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.970\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003e0.981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e0.567\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c11\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003eIndependent Samples Test\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eClinicopathological characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c5\" namest=\"c3\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMean Difference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c11\" namest=\"c9\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eLower\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003eUpper\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eAccompanying histology\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDCIS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c5\" namest=\"c3\" rowspan=\"2\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-0.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c8\" namest=\"c7\" rowspan=\"2\"\u003e \u003cp\u003e0.532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c11\" namest=\"c9\" rowspan=\"2\"\u003e \u003cp\u003e0.410\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo DCIS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eLVI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c5\" namest=\"c3\" rowspan=\"2\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-0.305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c8\" namest=\"c7\" rowspan=\"2\"\u003e \u003cp\u003e0.436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c11\" namest=\"c9\" rowspan=\"2\"\u003e \u003cp\u003e0.729\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eER\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eER+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c5\" namest=\"c3\" rowspan=\"2\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-0.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c8\" namest=\"c7\" rowspan=\"2\"\u003e \u003cp\u003e0.341\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c11\" namest=\"c9\" rowspan=\"2\"\u003e \u003cp\u003e0.618\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eER-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003ePgR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePgR+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c5\" namest=\"c3\" rowspan=\"2\"\u003e \u003cp\u003e0.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-0.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c8\" namest=\"c7\" rowspan=\"2\"\u003e \u003cp\u003e0.390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c11\" namest=\"c9\" rowspan=\"2\"\u003e \u003cp\u003e0.198\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePgR-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eHER2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eHER2+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c5\" namest=\"c3\" rowspan=\"2\"\u003e \u003cp\u003e0.370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c8\" namest=\"c7\" rowspan=\"2\"\u003e \u003cp\u003e0.675\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c11\" namest=\"c9\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.017\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eHER2-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eBilateral cancer\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c5\" namest=\"c3\" rowspan=\"2\"\u003e \u003cp\u003e-0.363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-0.892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c8\" namest=\"c7\" rowspan=\"2\"\u003e \u003cp\u003e0.166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c11\" namest=\"c9\" rowspan=\"2\"\u003e \u003cp\u003e0.178\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNAC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c5\" namest=\"c3\" rowspan=\"2\"\u003e \u003cp\u003e-0.247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-0.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c8\" namest=\"c7\" rowspan=\"2\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c11\" namest=\"c9\" rowspan=\"2\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eProcedure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eWLE\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c5\" namest=\"c3\" rowspan=\"2\"\u003e \u003cp\u003e-0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-0.383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c8\" namest=\"c7\" rowspan=\"2\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c11\" namest=\"c9\" rowspan=\"2\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMastectomy\u003c/b\u003e\u003c/p\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=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eRegression Analyses for Neutrophil-Lymphcyte Ratio and Clinicopathaological Data\u003c/h2\u003e \u003cp\u003eUnivariable linear regression analysis showed that only age at the time of surgery (β\u0026thinsp;=\u0026thinsp;0.009, 95% CI\u0026thinsp;=\u0026thinsp;0.001\u0026ndash;0.017, P\u0026thinsp;=\u0026thinsp;0.027), tumour size (β\u0026thinsp;=\u0026thinsp;0.013, 95% CI\u0026thinsp;=\u0026thinsp;0.005\u0026ndash;0.021, P\u0026thinsp;=\u0026thinsp;0.001), and HER2 status (β= -0.370, 95% CI= -0.676 - -0.065, P\u0026thinsp;=\u0026thinsp;0.017) were associated with pre-operative NLR. Multivariable linear regression analysis revealed that the tumour size (β\u0026thinsp;=\u0026thinsp;0.011, 95% CI\u0026thinsp;=\u0026thinsp;0.002\u0026ndash;0.019, P\u0026thinsp;=\u0026thinsp;0.013) was the only clinicopathological parameter correlating statistically significantly with pre-operative NLR in this study. The results of the univariable and multivariable linear regression analysis were detailed in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLinear regression analysis of clinicopathological characteristics and pre-operative NLR\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnivariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMultivariable\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eβ (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.009 (0.001\u0026ndash;0.017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.027\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.007 (-0.003-0.017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMenopause\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.037 (-0.090-0.165)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eT-stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.034 (-0.111-0.178)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.649\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eN-stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.031 (-0.161-0.100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHistological subtype\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.067 (-0.180-0.045)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGrade\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.063 (-0.138-0.263)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.539\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAccompanying histology\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.157 (-0.533-0.218)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLVI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.065 (-0.436-0.306)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.729\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumor size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.013 (0.005\u0026ndash;0.021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.011 (0.002\u0026ndash;0.019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eER\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.069 (-0.341-0.203)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.618\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.155 (-0.391-0.081)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHER2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.370 (-0.676- -0.065)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.017\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.218 (-0.612-0.176)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.277\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBilateral cancer\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.363 (-0.166-0.892)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study has evaluated the predictive value of the preoperative neutrophil-lymphocyte ratio in relation to clinico-pathological parameters of BC, such as age, histological subtype, tumour grade, pT stage, pN stage, LVI, tumour size, HER2/ER/PR, and menopausal status. Given the propensity for HER2 tumours to be traditionally considered of aggressive tumour biology (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), it is somewhat unsurprising that our data demonstrated a correlation between HER2 status and NLR. Moreover, aggressive tumour biology tends to be diagnosed at a later stage (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), which supports the notion that increased NLR should be associated with increased tumour burden.\u003c/p\u003e \u003cp\u003eAlthough there is a growing body of knowledge on this topic, the findings are inconsistent with existing literature, demonstrating the novelty of these results, and also the requirement for more robust analyses of NLR in the clinical setting.\u003c/p\u003e \u003cp\u003eThese results demonstrated that preoperative NLR may have a potential predictive value of age, tumour size, and HER2 status in patients with primary BC. Contrary to this study, Zhu et al. previously reported that NLR was significantly higher in younger and premenopausal women, refuting the results of the current study (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eConcordant with the current study, Jadoon et al. demonstrated that NLR was significantly correlated with tumour size while no difference in histological grading, metastasis, surgical modality, sentinel or axillary node status were observed (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). However, they also illustrate NLR to be associated with tumour stage 1 and nodal stage 2/3 which is not consistent with the results of the present study. Moreover, Yang et al. reported that NLR had no significant association with age, tumor size, ER/PR/HER2 status and Ki67 expression assays, however did have a correlation with p53 expression and lymph node metastasis (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Sun et al. also described no correlation between NLR and clinicopathological parameters including age, HER2 status, and tumor size (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). While these results add fuel to this clinical conundrum, it is of importance to note that the current data was derived from a significantly larger database from a high-volume tertiary referral centre retrospectively for treatment of patients diagnosed with primary breast cancer.\u003c/p\u003e \u003cp\u003eThese results also demonstrated that there is a significant relationship between NLR and tumour size, thus suggesting that increased acute phase reactants may be expected with increasing tumour burden. Interestingly, Takeuchi et al. also reported significant relationship between NLR and tumor size in their previous analysis (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), supporting these findings.\u003c/p\u003e \u003cp\u003eThere are limitations to this study. Firstly, this study is of retrospective design rendering it likely to be subject to selection, confounding and ascertainment biases. Secondly, this study did not use an external validation cohort, which would prove fruitful in further ascertaining the relevance of these findings in clinical practice. Finally, while these results are of interest for translational research purposes, this study fails to cast light into the relavance of such results into clinical practice, as formal staging and histopathological tumour evaluation through the multidiciplinary process will not be deterred by NLR.\u003c/p\u003e \u003cp\u003eIn conclusion, this study demonstrates that preoperative NLR has an independent predictive value in terms of tumour size in patients being treated with primary BC. Ratification of these preliminary findings is warranted before robustly adopted into clinical practice.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eBI, MG, AJ wrote the main manuscript text. BI and MG prepared the tables. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is provided within the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A (2018) Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 68(6):394\u0026ndash;424\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavey MG, Ryan \u0026Eacute;J, Folan PJ, O\u0026rsquo;Halloran N, Boland MR, Barry MK et al (2021) The impact of progesterone receptor negativity on oncological outcomes in oestrogen-receptor-positive breast cancer. BJS Open 5(3):zrab040\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZagami P, Carey LA (2022) Triple negative breast cancer: Pitfalls and progress. npj Breast Cancer 8(1):95\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavey MG, Browne F, Miller N, Lowery AJ, Kerin MJ (2022) Pathological complete response as a surrogate to improved survival in human epidermal growth factor receptor-2-positive breast cancer: systematic review and meta-analysis. BJS Open 6(3):zrac028\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavey MG, Kerin E, O\u0026rsquo;Flaherty C, Maher E, Richard V, McAnena P et al (2021) Clinicopathological response to neoadjuvant therapies and pathological complete response as a biomarker of survival in human epidermal growth factor receptor-2 enriched breast cancer \u0026ndash; A retrospective cohort study. Breast 59:67\u0026ndash;75\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavey MG, Ryan \u0026Eacute;J, McAnena PF, Boland MR, Barry MK, Sweeney KJ et al (2021) Disease recurrence and oncological outcome of patients treated surgically with curative intent for estrogen receptor positive, lymph node negative breast cancer. Surg Oncol 37:101531\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHodi FS, Dranoff G (2010) The biologic importance of tumor-infiltrating lymphocytes. J Cutan Pathol 37(s1):48\u0026ndash;53\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNaszai M, Kurjan A, Maughan TS (2021) The prognostic utility of pre-treatment neutrophil‐to‐lymphocyte‐ratio (NLR) in colorectal cancer: A systematic review and meta‐analysis. Cancer Med 10(17):5983\u0026ndash;5997\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaram A, Boland MR, Kelly ME, Bolger JC, Waldron RM, Kerin MJ (2017) The prognostic value of neutrophil-to‐lymphocyte ratio in colorectal cancer: A systematic review. J Surg Oncol 115(4):470\u0026ndash;479\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGao S, Tang W, Zuo B, Mulvihill L, Yu J, Yu Y (2023) The predictive value of neutrophil-to-lymphocyte ratio for overall survival and pathological complete response in breast cancer patients receiving neoadjuvant chemotherapy. Front Oncol 12:1065606\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChae S, Kang KM, Kim HJ, Kang E, Park SY, Kim JH et al (2018) Neutrophil\u0026ndash;Lymphocyte Ratio Predicts Response to Chemotherapy in Triple-Negative Breast Cancer. Curr Oncol 25(2):113\u0026ndash;119\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Y, Shi XE, Tian JH, Yang XJ, Wang YF, Yang KH (2018) Survival benefit of neoadjuvant chemotherapy for resectable breast cancer: A meta-analysis. Medicine 97(20):e10634\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen D, Wang Q, Dong M, Chen F, Huang A, Chen C et al (2023) Analysis of neoadjuvant chemotherapy for breast cancer: a 20-year retrospective analysis of patients of a single institution. BMC Cancer 23(1):984\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVon Elm E, Altman DG, Egger M, Pocock SJ, G\u0026oslash;tzsche PC, Vandenbroucke JP (2007) The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet 370(9596):1453\u0026ndash;1457\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmin MB(2017) American Joint Committee on Cancer, American Cancer Society, editors. AJCC cancer staging manual. Eight edition / editor-in-chief, Mahul B. Amin, MD, FCAP ; editors, Stephen B. Edge, MD, FACS [and 16 others] ; Donna M. Gress, RHIT, CTR-Technical editor ; Laura R. Meyer, CAPM-Managing editor. Chicago IL: American Joint Committee on Cancer, Springer 1024 p\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAllred DC (2010) Issues and updates: evaluating estrogen receptor-α, progesterone receptor, and HER2 in breast cancer. Mod Pathol 23:S52\u0026ndash;S59\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHammond MEH, Hayes DF, Wolff AC, Mangu PB, Temin S (2010) American Society of Clinical Oncology/College of American Pathologists Guideline Recommendations for Immunohistochemical Testing of Estrogen and Progesterone Receptors in Breast Cancer. 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Sci Rep 11(1):1350\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJadoon SK, Soomro R, Ahsan MN, Ijaz Khan RM, Iqbal S, Yasmin F et al (2023) Association of neutrophil-to-lymphocyte ratio with clinical, pathological, radiological, laboratory features and disease outcomes of invasive breast cancer patients: A retrospective observational cohort study. Medicine 102(20):e33811\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang L, Wang H, Ma J, Hao J, Zhang C, Ma Q et al Association between the platelet to lymphocyte ratio, neutrophil to lymphocyte ratio and axillary lymph node metastasis in cT1N0 breast cancer patients\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun H, Yin C, qing, Liu Q, Wang F, Yuan Chui (2017) Clinical Significance of Routine Blood Test-Associated Inflammatory Index in Breast Cancer Patients. Med Sci Monit 23:5090\u0026ndash;5095\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTakeuchi H, Kawanaka H, Fukuyama S, Kubo N, Hiroshige S, Yano T (2017) Comparison of the prognostic values of preoperative inflammation-based parameters in patients with breast cancer. Coleman WB, editor. PLoS ONE. ;12(5):e0177137\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"breast-cancer-research-and-treatment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"brea","sideBox":"Learn more about [Breast Cancer Research and Treatment](https://www.springer.com/journal/10549)","snPcode":"10549","submissionUrl":"https://submission.nature.com/new-submission/10549/3","title":"Breast Cancer Research and Treatment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Breast Cancer, immunology, oncological outcomes, precision oncology, personalised medicine","lastPublishedDoi":"10.21203/rs.3.rs-4481633/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4481633/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThere is a paucity of data supporting the role of neutrophil-lymphocyte ratios (NLR) to determine clinicopathological parameters in patients being treated for primary breast cancer.\u003c/p\u003e\u003ch2\u003eAims\u003c/h2\u003e \u003cp\u003eTo evaluate the association between preoperative NLR and clinicopathological parameters in patients diagnosed with breast cancer.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA retrospective cohort study was performed. This included consecutive patients indicated to undergo surgery for primary breast cancer at University Hospital Limerick between January 2010 - June 2017. NLR was expressed as a continuous variable. Univariable and multivariable linear regression analyses were used to determine the correlation between NLR and clinicopathological data. Data analytics was performed using SPSS v29.0.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e673 patients met the inclusion criteria. Overall, the median preoperative NLR of 2.63 (standard deviation: 1.42). At univariable analysis, patient age (beta coefficient: 0.009, 95% confidence interval (CI): 0.001\u0026ndash;0.017, P\u0026thinsp;=\u0026thinsp;0.027), tumour size (beta coefficient: 0.013, 95% CI: 0.005\u0026ndash;0.021, P\u0026thinsp;=\u0026thinsp;0.001), and human epidermal growth factor receptor-2 status (beta coefficient: -0.370, 95% CI: -0.676 - -0.065, P\u0026thinsp;=\u0026thinsp;0.017) were all predicted using NLR. However, at multivariable analysis, tumour size was the sole parameter predictable by NLR (beta coefficient: 0.011, 95% CI: 0.002\u0026ndash;0.019, P\u0026thinsp;=\u0026thinsp;0.013).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis study demonstrates that preoperative NLR may serve as an independent predictor of tumour size in patients being treated with primary breast cancer. Ratification of these preliminary findings is warranted before robustly adopted into clinical practice.\u003c/p\u003e","manuscriptTitle":"Assessing the clinical utility of preoperative neutrophil-lymphocyte ratio as a predictor of clinicopathological parameters in patients being treated for primary breast cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-14 20:05:43","doi":"10.21203/rs.3.rs-4481633/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-05T23:26:47+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-05T11:51:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-18T04:54:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"112696660947726254251708016167266577807","date":"2024-07-16T06:48:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"119687531048379845040500472680877895811","date":"2024-07-10T04:21:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"98676290962230810369121656906932004624","date":"2024-07-09T09:20:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"322388124663227092368489011082081354998","date":"2024-07-09T09:18:07+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-03T17:00:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"327310580696289772137532229630250006554","date":"2024-06-30T18:31:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-19T13:47:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"72626458576033966981740648619315609966","date":"2024-06-09T15:46:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"79853347246269420256023211943334801094","date":"2024-06-09T07:33:54+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-09T07:27:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-27T12:36:27+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-27T12:36:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"Breast Cancer Research and Treatment","date":"2024-05-27T00:56:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"breast-cancer-research-and-treatment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"brea","sideBox":"Learn more about [Breast Cancer Research and Treatment](https://www.springer.com/journal/10549)","snPcode":"10549","submissionUrl":"https://submission.nature.com/new-submission/10549/3","title":"Breast Cancer Research and Treatment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"8001ef78-caf6-45f7-88e8-66f04f6d603a","owner":[],"postedDate":"June 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-01-27T15:59:32+00:00","versionOfRecord":{"articleIdentity":"rs-4481633","link":"https://doi.org/10.1007/s10549-025-07615-8","journal":{"identity":"breast-cancer-research-and-treatment","isVorOnly":false,"title":"Breast Cancer Research and Treatment"},"publishedOn":"2025-01-20 15:57:03","publishedOnDateReadable":"January 20th, 2025"},"versionCreatedAt":"2024-06-14 20:05:43","video":"","vorDoi":"10.1007/s10549-025-07615-8","vorDoiUrl":"https://doi.org/10.1007/s10549-025-07615-8","workflowStages":[]},"version":"v1","identity":"rs-4481633","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4481633","identity":"rs-4481633","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}