Optimal Cutoff for Neutrophil-to-Lymphocyte Ratio as a Tool for Pre-Chemotherapy Prognosis Stratification of Breast Cancer Patients

Optimal Cutoff for Neutrophil-to-Lymphocyte Ratio as a Tool for Pre-Chemotherapy Prognosis Stratification of Breast Cancer Patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report Optimal Cutoff for Neutrophil-to-Lymphocyte Ratio as a Tool for Pre-Chemotherapy Prognosis Stratification of Breast Cancer Patients Armita Zandi, Alyssa Qian, Regan Bucciol, Maha Othman This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6059442/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction: The neutrophil-to-lymphocyte ratio (NLR) is an established inflammatory marker in cancerpatients. The optimal cut-off as an independent prognostic factor for breast cancer (BC) progression in patients undergoing chemotherapy remains debatable, hindering the effective stratification. This study explored the optimal NLR cut-off by comparing various thresholds and assessing their effectiveness in stratifying BC patients according to prognosis. Methods: Demographic, clinical, and cancer-specific data on forty-two BC patients were recorded, including complete blood counts before and after two cycles of chemotherapy. Receiver operating characteristic curve assessed discriminatory performance. Diagnostic metrics and Youden’s J index were calculated and McNemar’s test was used to compare baseline NLR cutoffs of 2.5, 3.0, and 3.5. Kaplan-Meier curves assessed the relationship between various NLR cut-offs and other cancer prognostic markers. Results: The three NLR cutoffs demonstrated distinct diagnostic metrics and Youden’s J index values (p 3.0 were predicted to develop advanced stage BC more rapidly compared to those with pre-chemotherapy NLR < 3.0. Conclusion: We believe that a more stringent NLR cutoff of 3.0 is the most suitable predictor of prognosis in BC patients based on the ranges evaluated in literature. Oncology Clinical Oncology Chemotherapy Biomarkers Blood Cell Count Inflammation Figures Figure 1 Figure 2 Figure 3 Introduction The neutrophil-to-lymphocyte ratio (NLR) is measured from a patient’s peripheral blood count and is an established biomarker for the adaptive and innate immune system. Cancer is one of many conditions in which an elevated NLR can be observed. 1 Other conditions include fungal infections, stroke, atherosclerosis, and trauma. 2 , 3 In these pathologies, the systemic inflammatory response tends to prevent neutrophil apoptosis and reduce lymphocytes, subsequently leading to an elevated NLR. Thus, NLR has consistently been used to evaluate inflammatory-related disease progression and outcomes. In cancer patients, a higher NLR is typically associated with worse cancer prognosis with a range of 2.3-3.0 suggesting early warnings of pathological state. 4 Inflammation impacts diverse health conditions in markedly different ways, exhibited by the relationship between NLR and mortality in cardiovascular disease and absence of this relationship in cancer. 5 , 6 This complexity makes it critical to collect data across multiple time points rather than at a sole baseline measurement; allowing for the accurate assessment of impact in a variety of conditions and establishing the differences in patient survival. Despite many new methods of diagnosis and therapeutic advancements, BC remains the second cause of cancer death for women. 7 Currently, neoadjuvant chemotherapy (NACT) is used as a standard treatment for high-risk populations of women with breast cancer, such as those who have TNBC. Cancer prognosis depends on a variety of patient and cancer-specific factors, with cancer-specific factors including tumour stage and grade, molecular subtypes, metastases, and hormonal and HER2 receptor status. 7 Assessing the tumours’ responsiveness to various therapies including chemotherapy radiation and endocrine therapy – to determine prognosis - remains challenging. 8 Chemotherapy is associated with acute increase in systemic inflammation that may persist for months after treatment and can contribute to disease outcomes. 9 Prognostic biomarkers, such as NLR, would be beneficial in adapting treatments for different patients, particularly in the context of chemotherapy. Existing studies have reported a correlation between NLR and BC patient survival. 7 Many studies have recommended the use of NLR is a useful predictor for prognosis in BC, while other studies recommended against it. 10 , 11 , 12 Moreover, data regarding cut off values provide a large range, these cutoffs can further be narrowed for clinical applicability. This study analyzed the value of varying NLR thresholds as independent predictors of BC prognosis. Various NLR cutoff levels were assessed for their effectiveness in stratifying BC patients according to prognosis prior to chemotherapy, attempting to find the most suitable value. We also examined NLR changes throughout chemotherapy treatment. Methods Patient Recruitment and Data Collection This longitudinal quantitative study is part of an ongoing study where BC patients are recruited prior to their first chemotherapy treatment and are followed throughout their treatment process. A total of forty-two female patients with breast cancer, planned to receive chemotherapy as part of their standard treatment were recruited between January 2022 – January 2024. Additional inclusion criteria were good performance status, life expectancy of at least three months or more, and participants must have had no existing use of anticoagulants as convenience sampling was used, correlating an existing study that did not require anticoagulants. Baseline demographic data, including age, weight, body mass index (BMI), and comorbidities, were collected from the participants with complete blood counts (CBC) conducted prior to and after two cycles of chemotherapy. NLR was calculated for all participants prior to the start of chemotherapy and after the first and second cycles. Additional cancer-specific data such as cancer stage, lymphovascular invasion, and the receptor information including ER, PR, and HER-2 status were also recorded. Statistical Analysis Descriptive statistics, percentages and frequency were used to analyze patients’ and cancer specific characteristics. A Shapiro–Wilk test was conducted and concluded that the data collected was not normally distributed (p < 0.001). Hence, non-parametric equivalents of statistical tests were employed. Receiver operating characteristic (ROC) curves were generated for each diagnostic test to assess their discriminatory performance. From these curves, sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and Youden’s J index were calculated to characterize test performance comprehensively. Additionally, McNemar’s test was performed to statistically compare the selected cutoffs within the same patient cohort, ensuring that differences in diagnostic performance metrics were rigorously evaluated. Furthermore, Kaplan-Meier curves were generated to assess and compare the cancer prognostic factors when baseline NLR was above or below 3.0, evaluating the potential of NLR as a breast cancer prognostic factor. Results and Discussion Patient cohort A total of forty-two breast cancer patients with age (Mean (M) = 57.9, standard deviation (SD) = 11.9, range (R) 34.0–85.0), and BMI (M = 28.7, SD = 8.7, 20.0-58.6) were examined. Twenty-three patients had early-stage cancer (Stages I, II) and 19 had advanced stages (III, IV). Additionally, the average NLR before chemotherapy was (M = 2.8, SD = 1.3, 0.9–12.2), after Cycle 1 (M = 4.7, SD = 5.1, 0.8–27.8), and after Cycle 2 was (M = 7.5, SD = 7.7, 1.0-31.5). Details of patient and cancer specific data are shown in Supplemental Table 1. Pre-chemotherapy NLR was negatively correlated with patient age (r=-0.19, p = 0.12) and positively correlated with BMI (r=-0.08, p = 0.30), cancer staging (r = 0.09, p = 0.30), lymphovascular invasion (r = 0.11, p = 0.25), PR negative (r = 0.08, p = 0.30, HER2-negative (r = 0.05, p = 0.38). Statistically significant negative correlations were seen between pre-chemotherapy NLR and ER-negative (r = 0.30, p = 0.029) and triple-negative breast cancer (TNBC) subtype (r = 0.37, p = 0.008). The TNBC subtype has been shown in the literature to have a worse prognosis compared to other breast cancer subtypes. This significant relationship between pre-chemotherapy NLR and TNBC suggests a potential link between NLR and overall prognosis, highlighting its possible prognostic value. Comparison of Various NLR Cutoffs regarding their Effectiveness in BC Prognosis The most clinically relevant pre-chemotherapy NLR cutoff, which, according to the literature, is 2.3 to 3. 13 Expanding from this value, potential NLR cutoffs include 2.5 (close to the median of baseline NLR), 3, and 3.5. As summarized in Table 1, the sensitivity of the baseline NLR cutoffs of 2.5, 3.0, and 3.5 were 90.5%, 33.3%, and 57.1%, respectively, with corresponding specificities of 11.4%, 80.0%, and 34.3%. At the 2.5 cutoff, the accuracy, PPV, NPV, and Youden’s J index were 41.1%, 38.0%, 66.7%, and 0.019, respectively (Table 1). For the 3.0 cutoff, these values were 62.5%, 50.0%, 66.7%, and 0.133, and for the 3.5 cutoff, they were 42.9%, 34.3%, 57.1%, and − 0.086, respectively (Table 1). McNemar’s test demonstrated statistically significant differences in the diagnostic performance across all three cutoff values (p < 0.001 for all comparisons). Differential Prognosis in Groups of Low and High NLR We then investigated the differences in breast cancer prognostic factors between patients’ groups with low ( 3.0) pre-chemotherapy NLRs. There was a significant difference in the presence of ER-negative (p = 0.038) and TNBC (p = 0.014), between the two patient groups. However, the difference in cancer staging, lymphovascular invasion, metastasis, and presence of PR, HER2 receptors were not significant. Additionally, according to the Kaplan-Meier curve (Fig. 2), a pre-chemotherapy NLR below 3 predicted an approximately 400-week delay in developing advanced stage, lymphvaoscular invasion and metastasis. This data supports the association between high NLR and two important cancer specific prognostic markers. We further examined NLR as a dependent predictive biomarker for advanced cancer stages alongside ER-negative and TNBC. Figure 3 shows pre-chemotherapy NLR is a significant predictive biomarker (p = 0.013). Patients with high pre-chemotherapy NLR combined with ER-negative or TNBC were estimated to develop advanced cancer stages approximately 100 weeks sooner than those with lower pre-chemotherapy NLRs (Fig. 3). This study re-visited the use of NLR, an established marker of inflammation and a previously reported cancer prognostic marker and provided more analyses in relation to clinically relevant pre-chemotherapy NLR cutoff levels. Additionally, NLR changes following chemotherapy were assessed. Pre-chemotherapy NLRs exceeding 3.0 was found to be a strong predictor of poor BC outcomes. Our positive correlation data reflects NLR sensitivity to hormone receptor expressions (ER-negative and TNBC) which was confirmed in a recent meta-analysis involving 2069 patients from 10 studies. 14 The negative correlation of NLR with patients’ age can be explained by the decline in neutrophil counts and elevation of lymphocyte counts as one ages. 15 Studies have found that neutrophil proliferation response was less sensitive among older adults. 15 Another plausible consideration is menopause, although there had been mixed findings reported on the effect of menopause on neutrophil and lymphocyte counts. Some have reported no significant difference in neutrophil counts between pre- and post-menopausal women while others found reduced neutrophil counts and elevated lymphocyte counts in postmenopausal individuals. 16 , 17 Specifically regarding NLR, current literature suggests no significant associations between NLR and menopause, except when postmenopausal women have osteoporosis. 17 , 18 Lastly, the positive correlation between high NLR and other cancer prognosis markers confirms the association with high risks of a more aggressive subtype of breast cancer. This study concluded a NLR cutoff of 3.0 as a strong predictor of poor breast cancer outcomes, particularly when combined with other known prognostic factors TNBC or ER-negative BC. Furthermore, our detailed data on the various cut off levels and the comparative analysis of patients with NLR above and below 3 data have indicated the individualization of patients’ assessment is possible. We, as others, believe that with CBC being a routine evaluation in cancer follow up clinics, NLR could be a cost-efficient and convenient prognostic marker specially if combined with other prognostic cancer specific factors. This can help clinicians accurately and effectively assess patients over the course of therapy. Among the three evaluated cutoffs, the NLR cutoff of 3.0 provided the best overall balance between sensitivity, specificity, and Youden’s J index. While a cutoff of 2.5 achieves the highest sensitivity (90.5%), its specificity is very low (11.4%), resulting in a large proportion of false positives and a low Youden’s J index (0.019). At the other extreme, a cutoff of 3.5 offers a moderate sensitivity (57.1%) but only a 34.3% specificity and ultimately reduces Youden’s J to a negative value (– 0.086), indicating poorer overall performance. In contrast, the 3.0 cutoff improves specificity substantially to 80.0% with a sensitivity of 33.3%, delivering a better balance between identifying true cases and minimizing false positives. This balanced performance is reflected in the highest Youden’s J index (0.133) among the three cutoffs, along with a higher overall accuracy (62.5%). Thus, by all-round measures—particularly Youden’s J, which integrates both sensitivity and specificity—3.0 emerges as the most effective cutoff. The study has several limitations, including a small sample size, which hindered the finding’s generalizability. Additionally, the study could not access patients' survival information and, therefore, was unable to examine NLR’s correlation with patients' overall and recurrence-free survival. In conclusion, this study re-visited NLR, an established marker for inflammation and its effectiveness in stratifying BC patients and predicting prognosis. We showed that NLR cutoff of 3.0 was most suitable in breast cancer prognosis. We also demonstrated how NLR increased throughout chemotherapy and was associated with ER-negative, TNBC, and chemotherapy progress. We encourage the use of NLR in future clinical practices towards better care of breast cancer patients. Declarations We received ethics approval for this project from St. Lawerence College in Kingston, Ontario and from Queen’s University in Kingston, Ontario. Conflict of Interest: N/A Acknowledgements: N/A Author contributions: AZ and AQ developed the study, conducted data analysis and wrote the manuscript. RB assisted with data analysis. MO designed the study, interpreted data, wrote manuscript and supervised all stages of the research. All coauthors reviewed data and manuscript. References Lee PY, Oen KQX, Lim GRS, et al. Neutrophil-to-Lymphocyte Ratio Predicts Development of Immune-Related Adverse Events and Outcomes from Immune Checkpoint Blockade: A Case-Control Study. Cancers (Basel) . 2021;13(6):1308. Published 2021 Mar 15. doi:10.3390/cancers13061308 Lowsby R, Gomes C, Jarman I, et al. Neutrophil to lymphocyte count ratio as an early indicator of blood stream infection in the emergency department. Emerg Med J . 2015;32(7):531-534. doi:10.1136/emermed-2014-204071 Park JM. Neutrophil-to-lymphocyte ratio in trauma patients. J Trauma Acute Care Surg . 2017;82(1):225-226. doi:10.1097/TA.0000000000001266 Howard, R., Kanetsky, P.A. & Egan, K.M. Exploring the prognostic value of the neutrophil-to-lymphocyte ratio in cancer. Sci Rep 9, 19673 (2019). https://doi.org/10.1038/s41598-019-56218-z Shah N, Parikh V, Patel N, et al. Neutrophil lymphocyte ratio significantly improves the Framingham risk score in prediction of coronary heart disease mortality: insights from the National Health and Nutrition Examination Survey-III. Int J Cardiol . 2014;171(3):390-397. doi:10.1016/j.ijcard.2013.12.019 Ellis L, Woods LM, Estève J, Eloranta S, Coleman MP, Rachet B. Cancer incidence, survival and mortality: explaining the concepts. Int J Cancer . 2014;135(8):1774-1782. doi:10.1002/ijc.28990 Grassadonia A, Graziano V, Iezzi L, et al. Prognostic Relevance of Neutrophil to Lymphocyte Ratio (NLR) in Luminal Breast Cancer: A Retrospective Analysis in the Neoadjuvant Setting. Cells . 2021;10(7):1685. Published 2021 Jul 3. doi:10.3390/cells10071685 Ethier JL, Desautels D, Templeton A, Shah PS, Amir E. Prognostic role of neutrophil-to-lymphocyte ratio in breast cancer: a systematic review and meta-analysis. Breast Cancer Res . 2017;19(1):2. Published 2017 Jan 5. doi:10.1186/s13058-016-0794-1 Bower JE, Ganz PA, Irwin MR, Cole SW, Carroll J, Kuhlman KR, Petersen L, Garet D, Asher A, Hurvitz SA, Crespi CM. Acute and Chronic Effects of Adjuvant Therapy on Inflammatory Markers in Breast Cancer Patients. JNCI Cancer Spectr . 2022 Jul 1;6(4):pkac052. doi: 10.1093/jncics/pkac052. Heshmat-Ghahdarijani K, Sarmadi V, Heidari A, Falahati Marvasti A, Neshat S, Raeisi S. The neutrophil-to-lymphocyte ratio as a new prognostic factor in cancers: a narrative review. Front Oncol . 2023;13:1228076. Published 2023 Oct 4. doi:10.3389/fonc.2023.1228076 Corbeau I, Jacot W, Guiu S. Neutrophil to Lymphocyte Ratio as Prognostic and Predictive Factor in Breast Cancer Patients: A Systematic Review. Cancers (Basel) . 2020;12(4):958. Published 2020 Apr 13. doi:10.3390/cancers12040958 Sifón MDR, Marcolini N, Barber MJ, Mclean I, Rizzo M, Rivero S, Costanzo MV, Nervo A, Crimi G, Perazzo F, Levy EM, Mandó P. Lack of Prognostic Value of Pretreatment Neutrophil-to-Lymphocyte Ratio in Early Breast Cancer. Breast Care (Basel). 2022 Dec;17(6):546-553. doi: 10.1159/000525287. Epub 2022 Jun 3. Setakornnukul J, Chanvimalueng W, Patumanond J, Thephamongkhol K. Cutoff point of neutrophil-to-lymphocyte ratio for predicting survival in nasopharyngeal carcinoma. Medicine (Baltimore) . 2021;100(34):e27095. doi:10.1097/MD.0000000000027095 Liu Y, He M, Wang C, Zhang X, Cai S. Prognostic value of neutrophil-to-lymphocyte ratio for patients with triple-negative breast cancer: A meta-analysis. Medicine (Baltimore). 2022 Jul 15;101(28):e29887. doi: 10.1097/MD.0000000000029887. Chatta GS, Andrews RG, Rodger E, Schrag M, Hammond WP, Dale DC. Hematopoietic progenitors and aging: alterations in granulocytic precursors and responsiveness to recombinant human G-CSF, GM-CSF, and IL-3. J Gerontol . 1993;48(5):M207-M212. doi:10.1093/geronj/48.5.m207 Abildgaard J, Tingstedt J, Zhao Y, et al. Increased systemic inflammation and altered distribution of T-cell subsets in postmenopausal women. PLoS One . 2020;15(6):e0235174. Published 2020 Jun 23. doi:10.1371/journal.pone.0235174 Didevar N, Rezasoltani P, Pourgholaminejad A, Kazemnezhad Leyli E, Seyednoori T, Zahiri Sorouri Z. Interleukin-17, C-reactive protein, Neutrophil-to-Lymphocyte ratio, Lymphocyte-to-Monocyte ratio, and lipid profiles in healthy menopausal women with or without hot flashes: A cross-sectional study. PLoS One . 2023;18(11):e0291804. Published 2023 Nov 22. doi:10.1371/journal.pone.0291804 Salimi M, Khanzadeh M, Nabipoorashrafi SA, et al. Association of neutrophil to lymphocyte ratio with bone mineral density in post-menopausal women: a systematic review and meta-analysis. BMC Womens Health . 2024;24(1):169. Published 2024 Mar 9. doi:10.1186/s12905-024-03006-1 Additional Declarations The authors declare no competing interests. Supplementary Files NLRSupplementalTable.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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06:51:40","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":44754,"visible":true,"origin":"","legend":"","description":"","filename":"NLRSupplementalTable.docx","url":"https://assets-eu.researchsquare.com/files/rs-6059442/v1/84c3278b40aa9399c9acd100.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eOptimal Cutoff for Neutrophil-to-Lymphocyte Ratio as a Tool for Pre-Chemotherapy Prognosis Stratification of Breast Cancer Patients\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe neutrophil-to-lymphocyte ratio (NLR) is measured from a patient\u0026rsquo;s peripheral blood count and is an established biomarker for the adaptive and innate immune system. Cancer is one of many conditions in which an elevated NLR can be observed.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Other conditions include fungal infections, stroke, atherosclerosis, and trauma.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e In these pathologies, the systemic inflammatory response tends to prevent neutrophil apoptosis and reduce lymphocytes, subsequently leading to an elevated NLR. Thus, NLR has consistently been used to evaluate inflammatory-related disease progression and outcomes. In cancer patients, a higher NLR is typically associated with worse cancer prognosis with a range of 2.3-3.0 suggesting early warnings of pathological state.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eInflammation impacts diverse health conditions in markedly different ways, exhibited by the relationship between NLR and mortality in cardiovascular disease and absence of this relationship in cancer.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e This complexity makes it critical to collect data across multiple time points rather than at a sole baseline measurement; allowing for the accurate assessment of impact in a variety of conditions and establishing the differences in patient survival.\u003c/p\u003e \u003cp\u003eDespite many new methods of diagnosis and therapeutic advancements, BC remains the second cause of cancer death for women.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Currently, neoadjuvant chemotherapy (NACT) is used as a standard treatment for high-risk populations of women with breast cancer, such as those who have TNBC. Cancer prognosis depends on a variety of patient and cancer-specific factors, with cancer-specific factors including tumour stage and grade, molecular subtypes, metastases, and hormonal and HER2 receptor status.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Assessing the tumours\u0026rsquo; responsiveness to various therapies including chemotherapy radiation and endocrine therapy \u0026ndash; to determine prognosis - remains challenging.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e Chemotherapy is associated with acute increase in systemic inflammation that may persist for months after treatment and can contribute to disease outcomes. \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003ePrognostic biomarkers, such as NLR, would be beneficial in adapting treatments for different patients, particularly in the context of chemotherapy. Existing studies have reported a correlation between NLR and BC patient survival.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Many studies have recommended the use of NLR is a useful predictor for prognosis in BC, while other studies recommended against it.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Moreover, data regarding cut off values provide a large range, these cutoffs can further be narrowed for clinical applicability.\u003c/p\u003e \u003cp\u003eThis study analyzed the value of varying NLR thresholds as independent predictors of BC prognosis. Various NLR cutoff levels were assessed for their effectiveness in stratifying BC patients according to prognosis prior to chemotherapy, attempting to find the most suitable value. We also examined NLR changes throughout chemotherapy treatment.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatient Recruitment and Data Collection\u003c/h2\u003e \u003cp\u003eThis longitudinal quantitative study is part of an ongoing study where BC patients are recruited prior to their first chemotherapy treatment and are followed throughout their treatment process. A total of forty-two female patients with breast cancer, planned to receive chemotherapy as part of their standard treatment were recruited between January 2022 \u0026ndash; January 2024. Additional inclusion criteria were good performance status, life expectancy of at least three months or more, and participants must have had no existing use of anticoagulants as convenience sampling was used, correlating an existing study that did not require anticoagulants. Baseline demographic data, including age, weight, body mass index (BMI), and comorbidities, were collected from the participants with complete blood counts (CBC) conducted prior to and after two cycles of chemotherapy. NLR was calculated for all participants prior to the start of chemotherapy and after the first and second cycles. Additional cancer-specific data such as cancer stage, lymphovascular invasion, and the receptor information including ER, PR, and HER-2 status were also recorded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eDescriptive statistics, percentages and frequency were used to analyze patients\u0026rsquo; and cancer specific characteristics. A Shapiro\u0026ndash;Wilk test was conducted and concluded that the data collected was not normally distributed (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Hence, non-parametric equivalents of statistical tests were employed. Receiver operating characteristic (ROC) curves were generated for each diagnostic test to assess their discriminatory performance. From these curves, sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and Youden\u0026rsquo;s J index were calculated to characterize test performance comprehensively. Additionally, McNemar\u0026rsquo;s test was performed to statistically compare the selected cutoffs within the same patient cohort, ensuring that differences in diagnostic performance metrics were rigorously evaluated. Furthermore, Kaplan-Meier curves were generated to assess and compare the cancer prognostic factors when baseline NLR was above or below 3.0, evaluating the potential of NLR as a breast cancer prognostic factor.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results and Discussion","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003ePatient cohort\u003c/h2\u003e \u003cp\u003eA total of forty-two breast cancer patients with age (Mean (M)\u0026thinsp;=\u0026thinsp;57.9, standard deviation (SD)\u0026thinsp;=\u0026thinsp;11.9, range (R) 34.0\u0026ndash;85.0), and BMI (M\u0026thinsp;=\u0026thinsp;28.7, SD\u0026thinsp;=\u0026thinsp;8.7, 20.0-58.6) were examined. Twenty-three patients had early-stage cancer (Stages I, II) and 19 had advanced stages (III, IV). Additionally, the average NLR before chemotherapy was (M\u0026thinsp;=\u0026thinsp;2.8, SD\u0026thinsp;=\u0026thinsp;1.3, 0.9\u0026ndash;12.2), after Cycle 1 (M\u0026thinsp;=\u0026thinsp;4.7, SD\u0026thinsp;=\u0026thinsp;5.1, 0.8\u0026ndash;27.8), and after Cycle 2 was (M\u0026thinsp;=\u0026thinsp;7.5, SD\u0026thinsp;=\u0026thinsp;7.7, 1.0-31.5). Details of patient and cancer specific data are shown in Supplemental Table\u0026nbsp;1. Pre-chemotherapy NLR was negatively correlated with patient age (r=-0.19, p\u0026thinsp;=\u0026thinsp;0.12) and positively correlated with BMI (r=-0.08, p\u0026thinsp;=\u0026thinsp;0.30), cancer staging (r\u0026thinsp;=\u0026thinsp;0.09, p\u0026thinsp;=\u0026thinsp;0.30), lymphovascular invasion (r\u0026thinsp;=\u0026thinsp;0.11, p\u0026thinsp;=\u0026thinsp;0.25), PR negative (r\u0026thinsp;=\u0026thinsp;0.08, p\u0026thinsp;=\u0026thinsp;0.30, HER2-negative (r\u0026thinsp;=\u0026thinsp;0.05, p\u0026thinsp;=\u0026thinsp;0.38). Statistically significant negative correlations were seen between pre-chemotherapy NLR and ER-negative (r\u0026thinsp;=\u0026thinsp;0.30, p\u0026thinsp;=\u0026thinsp;0.029) and triple-negative breast cancer (TNBC) subtype (r\u0026thinsp;=\u0026thinsp;0.37, p\u0026thinsp;=\u0026thinsp;0.008). The TNBC subtype has been shown in the literature to have a worse prognosis compared to other breast cancer subtypes. This significant relationship between pre-chemotherapy NLR and TNBC suggests a potential link between NLR and overall prognosis, highlighting its possible prognostic value.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eComparison of Various NLR Cutoffs regarding their Effectiveness in BC Prognosis\u003c/h3\u003e\n\u003cp\u003eThe most clinically relevant pre-chemotherapy NLR cutoff, which, according to the literature, is 2.3 to 3.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e Expanding from this value, potential NLR cutoffs include 2.5 (close to the median of baseline NLR), 3, and 3.5. As summarized in Table\u0026nbsp;1, the sensitivity of the baseline NLR cutoffs of 2.5, 3.0, and 3.5 were 90.5%, 33.3%, and 57.1%, respectively, with corresponding specificities of 11.4%, 80.0%, and 34.3%. At the 2.5 cutoff, the accuracy, PPV, NPV, and Youden\u0026rsquo;s J index were 41.1%, 38.0%, 66.7%, and 0.019, respectively (Table\u0026nbsp;1). For the 3.0 cutoff, these values were 62.5%, 50.0%, 66.7%, and 0.133, and for the 3.5 cutoff, they were 42.9%, 34.3%, 57.1%, and \u0026minus;\u0026thinsp;0.086, respectively (Table\u0026nbsp;1). McNemar\u0026rsquo;s test demonstrated statistically significant differences in the diagnostic performance across all three cutoff values (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for all comparisons).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDifferential Prognosis in Groups of Low and High NLR\u003c/h2\u003e \u003cp\u003eWe then investigated the differences in breast cancer prognostic factors between patients\u0026rsquo; groups with low (\u0026lt;\u0026thinsp;3.0) and high (\u0026gt;\u0026thinsp;3.0) pre-chemotherapy NLRs. There was a significant difference in the presence of ER-negative (p\u0026thinsp;=\u0026thinsp;0.038) and TNBC (p\u0026thinsp;=\u0026thinsp;0.014), between the two patient groups. However, the difference in cancer staging, lymphovascular invasion, metastasis, and presence of PR, HER2 receptors were not significant. Additionally, according to the Kaplan-Meier curve (Fig.\u0026nbsp;2), a pre-chemotherapy NLR below 3 predicted an approximately 400-week delay in developing advanced stage, lymphvaoscular invasion and metastasis. This data supports the association between high NLR and two important cancer specific prognostic markers.\u003c/p\u003e \u003cp\u003eWe further examined NLR as a dependent predictive biomarker for advanced cancer stages alongside ER-negative and TNBC. Figure\u0026nbsp;3 shows pre-chemotherapy NLR is a significant predictive biomarker (p\u0026thinsp;=\u0026thinsp;0.013). Patients with high pre-chemotherapy NLR combined with ER-negative or TNBC were estimated to develop advanced cancer stages approximately 100 weeks sooner than those with lower pre-chemotherapy NLRs (Fig.\u0026nbsp;3).\u003c/p\u003e \u003cp\u003eThis study re-visited the use of NLR, an established marker of inflammation and a previously reported cancer prognostic marker and provided more analyses in relation to clinically relevant pre-chemotherapy NLR cutoff levels. Additionally, NLR changes following chemotherapy were assessed. Pre-chemotherapy NLRs exceeding 3.0 was found to be a strong predictor of poor BC outcomes.\u003c/p\u003e \u003cp\u003eOur positive correlation data reflects NLR sensitivity to hormone receptor expressions (ER-negative and TNBC) which was confirmed in a recent meta-analysis involving 2069 patients from 10 studies.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e The negative correlation of NLR with patients\u0026rsquo; age can be explained by the decline in neutrophil counts and elevation of lymphocyte counts as one ages.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Studies have found that neutrophil proliferation response was less sensitive among older adults.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Another plausible consideration is menopause, although there had been mixed findings reported on the effect of menopause on neutrophil and lymphocyte counts. Some have reported no significant difference in neutrophil counts between pre- and post-menopausal women while others found reduced neutrophil counts and elevated lymphocyte counts in postmenopausal individuals.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Specifically regarding NLR, current literature suggests no significant associations between NLR and menopause, except when postmenopausal women have osteoporosis.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e Lastly, the positive correlation between high NLR and other cancer prognosis markers confirms the association with high risks of a more aggressive subtype of breast cancer.\u003c/p\u003e \u003cp\u003eThis study concluded a NLR cutoff of 3.0 as a strong predictor of poor breast cancer outcomes, particularly when combined with other known prognostic factors TNBC or ER-negative BC. Furthermore, our detailed data on the various cut off levels and the comparative analysis of patients with NLR above and below 3 data have indicated the individualization of patients\u0026rsquo; assessment is possible. We, as others, believe that with CBC being a routine evaluation in cancer follow up clinics, NLR could be a cost-efficient and convenient prognostic marker specially if combined with other prognostic cancer specific factors. This can help clinicians accurately and effectively assess patients over the course of therapy.\u003c/p\u003e \u003cp\u003eAmong the three evaluated cutoffs, the NLR cutoff of 3.0 provided the best overall balance between sensitivity, specificity, and Youden\u0026rsquo;s J index. While a cutoff of 2.5 achieves the highest sensitivity (90.5%), its specificity is very low (11.4%), resulting in a large proportion of false positives and a low Youden\u0026rsquo;s J index (0.019). At the other extreme, a cutoff of 3.5 offers a moderate sensitivity (57.1%) but only a 34.3% specificity and ultimately reduces Youden\u0026rsquo;s J to a negative value (\u0026ndash; 0.086), indicating poorer overall performance.\u003c/p\u003e \u003cp\u003eIn contrast, the 3.0 cutoff improves specificity substantially to 80.0% with a sensitivity of 33.3%, delivering a better balance between identifying true cases and minimizing false positives. This balanced performance is reflected in the highest Youden\u0026rsquo;s J index (0.133) among the three cutoffs, along with a higher overall accuracy (62.5%). Thus, by all-round measures\u0026mdash;particularly Youden\u0026rsquo;s J, which integrates both sensitivity and specificity\u0026mdash;3.0 emerges as the most effective cutoff.\u003c/p\u003e \u003cp\u003eThe study has several limitations, including a small sample size, which hindered the finding\u0026rsquo;s generalizability. Additionally, the study could not access patients' survival information and, therefore, was unable to examine NLR\u0026rsquo;s correlation with patients' overall and recurrence-free survival.\u003c/p\u003e \u003cp\u003eIn conclusion, this study re-visited NLR, an established marker for inflammation and its effectiveness in stratifying BC patients and predicting prognosis. We showed that NLR cutoff of 3.0 was most suitable in breast cancer prognosis. We also demonstrated how NLR increased throughout chemotherapy and was associated with ER-negative, TNBC, and chemotherapy progress. We encourage the use of NLR in future clinical practices towards better care of breast cancer patients.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eWe received ethics approval for this project from St. Lawerence College in Kingston, Ontario and from Queen\u0026rsquo;s University in Kingston, Ontario.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest:\u003c/strong\u003e\u0026nbsp;N/A\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e N/A\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e\u0026nbsp;AZ and AQ developed the study, conducted data analysis and wrote the manuscript. RB assisted with data analysis. MO designed the study, interpreted data, wrote manuscript and supervised all stages of the research. All coauthors reviewed data and manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eLee PY, Oen KQX, Lim GRS, et al. Neutrophil-to-Lymphocyte Ratio Predicts Development of Immune-Related Adverse Events and Outcomes from Immune Checkpoint Blockade: A Case-Control Study. \u003cem\u003eCancers (Basel)\u003c/em\u003e. 2021;13(6):1308. Published 2021 Mar 15. doi:10.3390/cancers13061308\u003c/li\u003e\n \u003cli\u003eLowsby R, Gomes C, Jarman I, et al. Neutrophil to lymphocyte count ratio as an early indicator of blood stream infection in the emergency department. \u003cem\u003eEmerg Med J\u003c/em\u003e. 2015;32(7):531-534. doi:10.1136/emermed-2014-204071\u003c/li\u003e\n \u003cli\u003ePark JM. Neutrophil-to-lymphocyte ratio in trauma patients. \u003cem\u003eJ Trauma Acute Care Surg\u003c/em\u003e. 2017;82(1):225-226. doi:10.1097/TA.0000000000001266\u003c/li\u003e\n \u003cli\u003eHoward, R., Kanetsky, P.A. \u0026amp; Egan, K.M. Exploring the prognostic value of the neutrophil-to-lymphocyte ratio in cancer. \u003cem\u003eSci Rep\u003c/em\u003e 9, 19673 (2019). https://doi.org/10.1038/s41598-019-56218-z\u003c/li\u003e\n \u003cli\u003eShah N, Parikh V, Patel N, et al. Neutrophil lymphocyte ratio significantly improves the Framingham risk score in prediction of coronary heart disease mortality: insights from the National Health and Nutrition Examination Survey-III. \u003cem\u003eInt J Cardiol\u003c/em\u003e. 2014;171(3):390-397. doi:10.1016/j.ijcard.2013.12.019\u003c/li\u003e\n \u003cli\u003eEllis L, Woods LM, Est\u0026egrave;ve J, Eloranta S, Coleman MP, Rachet B. Cancer incidence, survival and mortality: explaining the concepts. \u003cem\u003eInt J Cancer\u003c/em\u003e. 2014;135(8):1774-1782. doi:10.1002/ijc.28990\u003c/li\u003e\n \u003cli\u003eGrassadonia A, Graziano V, Iezzi L, et al. Prognostic Relevance of Neutrophil to Lymphocyte Ratio (NLR) in Luminal Breast Cancer: A Retrospective Analysis in the Neoadjuvant Setting. \u003cem\u003eCells\u003c/em\u003e. 2021;10(7):1685. Published 2021 Jul 3. doi:10.3390/cells10071685\u003c/li\u003e\n \u003cli\u003eEthier JL, Desautels D, Templeton A, Shah PS, Amir E. Prognostic role of neutrophil-to-lymphocyte ratio in breast cancer: a systematic review and meta-analysis. \u003cem\u003eBreast Cancer Res\u003c/em\u003e. 2017;19(1):2. Published 2017 Jan 5. doi:10.1186/s13058-016-0794-1\u003c/li\u003e\n \u003cli\u003eBower JE, Ganz PA, Irwin MR, Cole SW, Carroll J, Kuhlman KR, Petersen L, Garet D, Asher A, Hurvitz SA, Crespi CM. Acute and Chronic Effects of Adjuvant Therapy on Inflammatory Markers in Breast Cancer Patients. \u003cem\u003eJNCI Cancer Spectr\u003c/em\u003e. 2022 Jul 1;6(4):pkac052. doi: 10.1093/jncics/pkac052.\u003c/li\u003e\n \u003cli\u003eHeshmat-Ghahdarijani K, Sarmadi V, Heidari A, Falahati Marvasti A, Neshat S, Raeisi S. The neutrophil-to-lymphocyte ratio as a new prognostic factor in cancers: a narrative review. \u003cem\u003eFront Oncol\u003c/em\u003e. 2023;13:1228076. Published 2023 Oct 4. doi:10.3389/fonc.2023.1228076\u003c/li\u003e\n \u003cli\u003eCorbeau I, Jacot W, Guiu S. Neutrophil to Lymphocyte Ratio as Prognostic and Predictive Factor in Breast Cancer Patients: A Systematic Review. \u003cem\u003eCancers (Basel)\u003c/em\u003e. 2020;12(4):958. Published 2020 Apr 13. doi:10.3390/cancers12040958\u003c/li\u003e\n \u003cli\u003eSif\u0026oacute;n MDR, Marcolini N, Barber MJ, Mclean I, Rizzo M, Rivero S, Costanzo MV, Nervo A, Crimi G, Perazzo F, Levy EM, Mand\u0026oacute; P. Lack of Prognostic Value of Pretreatment Neutrophil-to-Lymphocyte Ratio in Early Breast Cancer. Breast Care (Basel). 2022 Dec;17(6):546-553. doi: 10.1159/000525287. Epub 2022 Jun 3.\u003c/li\u003e\n \u003cli\u003eSetakornnukul J, Chanvimalueng W, Patumanond J, Thephamongkhol K. Cutoff point of neutrophil-to-lymphocyte ratio for predicting survival in nasopharyngeal\u0026nbsp;\u003cspan lang=\"EN-CA\"\u003ecarcinoma. \u003cem\u003eMedicine (Baltimore)\u003c/em\u003e. 2021;100(34):e27095. doi:10.1097/MD.0000000000027095\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003eLiu Y, He M, Wang C, Zhang X, Cai S. Prognostic value of neutrophil-to-lymphocyte ratio for patients with triple-negative breast cancer: A meta-analysis. Medicine (Baltimore). 2022 Jul 15;101(28):e29887. doi: 10.1097/MD.0000000000029887.\u003c/li\u003e\n \u003cli\u003e\u003cspan lang=\"EN-CA\"\u003eChatta GS, Andrews RG, Rodger E, Schrag M, Hammond WP, Dale DC. Hematopoietic progenitors and aging: alterations in granulocytic precursors and responsiveness to recombinant human G-CSF, GM-CSF, and IL-3. \u003cem\u003eJ Gerontol\u003c/em\u003e. 1993;48(5):M207-M212. doi:10.1093/geronj/48.5.m207\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003eAbildgaard J, Tingstedt J, Zhao Y, et al. Increased systemic inflammation and altered distribution of T-cell subsets in postmenopausal women. \u003cem\u003ePLoS One\u003c/em\u003e. 2020;15(6):e0235174. Published 2020 Jun 23. doi:10.1371/journal.pone.0235174\u003c/li\u003e\n \u003cli\u003eDidevar N, Rezasoltani P, Pourgholaminejad A, Kazemnezhad Leyli E, Seyednoori T, Zahiri Sorouri Z. Interleukin-17, C-reactive protein, Neutrophil-to-Lymphocyte ratio, Lymphocyte-to-Monocyte ratio, and lipid profiles in healthy menopausal women with or without hot flashes: A cross-sectional study. \u003cem\u003ePLoS One\u003c/em\u003e. 2023;18(11):e0291804. 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Published 2024 Mar 9. doi:10.1186/s12905-024-03006-1\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Queen's University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Clinical Oncology, Chemotherapy, Biomarkers, Blood Cell Count, Inflammation","lastPublishedDoi":"10.21203/rs.3.rs-6059442/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6059442/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction:\u003c/strong\u003e The neutrophil-to-lymphocyte ratio (NLR) is an established inflammatory marker in cancerpatients. The optimal cut-off as an independent prognostic factor for breast cancer (BC) progression in patients undergoing chemotherapy remains debatable, hindering the effective stratification. This study explored the optimal NLR cut-off by comparing various thresholds and assessing their effectiveness in stratifying BC patients according to prognosis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eDemographic, clinical, and cancer-specific data on forty-two BC patients were recorded, including complete blood counts before and after two cycles of chemotherapy. Receiver operating characteristic curve assessed discriminatory performance. Diagnostic metrics and Youden’s J index were calculated and McNemar’s test was used to compare baseline NLR cutoffs of 2.5, 3.0, and 3.5. Kaplan-Meier curves assessed the relationship between various NLR cut-offs and other cancer prognostic markers.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The three NLR cutoffs demonstrated distinct diagnostic metrics and Youden’s J index values (p \u0026lt; 0.001), with the 3.0 cutoff providing the most balanced performance. Patients with pre-chemotherapy NLR \u0026gt; 3.0 were predicted to develop advanced stage BC more rapidly compared to those with pre-chemotherapy NLR \u0026lt; 3.0.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eWe believe that a more stringent NLR cutoff of 3.0 is the most suitable predictor of prognosis in BC patients based on the ranges evaluated in literature.\u003c/p\u003e","manuscriptTitle":"Optimal Cutoff for Neutrophil-to-Lymphocyte Ratio as a Tool for Pre-Chemotherapy Prognosis Stratification of Breast Cancer Patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-27 06:51:35","doi":"10.21203/rs.3.rs-6059442/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"82a1b9c1-37d2-4351-a006-5a9e9952557d","owner":[],"postedDate":"February 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":44537658,"name":"Oncology"}],"tags":[],"updatedAt":"2025-02-27T06:51:35+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-27 06:51:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6059442","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6059442","identity":"rs-6059442","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}