Predictive Value of Neutrophil-to-Lymphocyte Ratio(NLR) and Platelet-to-Lymphocyte Ratios (PLR) for Lymph Node Metastasis in Rectal Cancer Patients: a retrospective cohort study

Predictive Value of Neutrophil-to-Lymphocyte Ratio(NLR) and Platelet-to-Lymphocyte Ratios (PLR) for Lymph Node Metastasis in Rectal Cancer Patients: a retrospective cohort study | 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 Research Article Predictive Value of Neutrophil-to-Lymphocyte Ratio(NLR) and Platelet-to-Lymphocyte Ratios (PLR) for Lymph Node Metastasis in Rectal Cancer Patients: a retrospective cohort study Yangfeng Lin, Zhijie You, Zhijing Lin, Siming Wang, Guo Hua Yang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5937143/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 May, 2025 Read the published version in BMC Gastroenterology → Version 1 posted 7 You are reading this latest preprint version Abstract Introduction: Systemic inflammatory response (SIR) indicators are predictive factors for lymph node metastasis(LNM) in various cancers. This study aimed to investigate the assiociation of platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) with LNM in rectal cancer(RC). In addition, we sought to explore the clinicopathological factors of LNM. Methods: We included 181 patients with RC admitted for surgery. NLR and PLR were calculated by collecting and analyzing preoperative blood samples, and their optimal cutoff values were analyzed using receiver operating characteristic (ROC). We examined the relationship between NLR or PLR and the clinicopathological characteristics of the patients, assessed their impact on LNM using ROC curve analysis. The risk factors for LNM were evaluated using both univariate and multivariate analyses. Results: high PLR (H-PLR) group exhibited higher rates of perineural invasion (PNI) at 54.2% (83/153), lymphovascular invasion (LVI) at 51.6% (79 /153),more elevated CEA(66/153,43.1%) and tumor deposits (TDs) at 14.4% (22/153). Additionally, this group demonstrated a greater incidence of LNM at 52.9% (81/153) and presented with a more advanced stage (stage II and stage III 124/153,81%). H-PLR were correlated with the presence of LNM, while H-NLR did not show it. The findings indicated that advanced T stage, high H-PLR, positive LVI, positive PNI, positive TDs, an increased number of cleared total lymph nodes (TLN), as well as elevated levels of carcinoembryonic antigen (CEA) and cancer antigen 19-9 (CA19-9) were associated with lymph node metastasis (LNM) according to univariate analysis. However, multivariate analysis revealed that only LVI and PNI were independent risk factors for LNM. Conclusion: H-PLR may be associated with unfavorable histopathological characteristics, positive LVI and PNI were independent risk factors for LNM in RC. Rectal cancer PLR NLR Lymph node metastasis Introduction Colorectal cancer (CRC) is the second most fatal and third most frequent type of cancer worldwide [ 1 ]. Lymph node metastasis(LNM) is a prevalent metastasis in CRC and serves as a vital risk factor that influenc es the 5-year overall survival [ 2 ]. Consequently, there is a pressing need for effective molecular biomarkers to predict lymph node metastasis in clinical practice. Inflammatory reactions linked to cancer are a defining feature of the onset and spread of the disease[ 3 ]. Mounting evidence suggests that inflammatory indicators are strongly linked to poor prognosis in CRC[ 4 ]. Hematologic al measures can represent systemic inflammatory responses , such as neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR). It has been established that a rise in these markers is detrimental to the prognosis of rectal cancer[ 5 , 6 ]. Research has indicated that NLR may be a strong predictor of LNM in breast cancer[ 7 ]. Additionally, it has been identified as a reliable predictor of LNM in head and neck squamous cell carcinoma(HNSCC) and gastric cancer[ 8 , 9 ]. Conversely,NLR has seldom been u sed as a predictor of rectal cancer,although studies have shown that a high NLR is associated with a more positive nodal status[ 10 ]. Therefore, further investigation is required to ascertain its true predictive significance. The purpose of this study was to investigate whether NLR and PLR is corrected with LNM in patients with resectable rectal cancer and to explore the risk factors for lymph node metastasis. Materials and Methods Patients Patients diagnosed with rectal cancer who underwent curative resection at our institution between May 2015 and December 2022 were included in the study. From an initial pool of 232 potential rectal cancer cases, 181 patients with complete data were selected for analysis; the remaining cases were excluded. All participants underwent CT and pelvic MRI prior to surgery. The surgical procedure was laparoscopic radical resection. This research was carried out in accordance with the guidelines established in the 1964 Declaration of Helsinki and its later revisions and was approved by the Research Ethics Committee of Fujian Provincial Hospital, under the ethics approval code K2024-07-037. Because this study was retrospective, written informed consent was obtained from all patients who had been diagnosed with rectal cancer. Including and excluding criteria Inclusion was determined according to the following criteria:(1) a diagnosis of rectal adenocarcinoma confirmed to endoscopic biopsy pathology; (2) the cancer must be situated within 15 cm of the anal verge, as determined by endoscopic evaluation; (3) an ECOG performance status of 0 to 2; (4) no prior medical history of malignant tumors or any surgical contraindications. The exclusion criteria were defined as follows: (I) incomplete clinical data; (II) existence of infections before surgery; (III) administration of drugs that increase leukocytes;(IV)patients who have undergone neoadjuvant radiotherapy or chemotherapy; (V) individuals with malignant tumors affecting other organ systems; and (VI) patients exhibiting liver or other organ metastases. Data Collection and Study Design Within a day of admission, 3 mL of peripheral blood was collected from each patient. Counts of neutrophils, lymphocytes, and platelets were retrieved from the hospital information system, and the database variables included age, sex, tumor location, NLR, PLR, and so on,as shown in table 1 . The eighth edition of the American Joint Committee on Cancer's (AJCC) eighth edition of the tumor-node-metastasis(TNM) grading system was used to stage the patient s in this study . Patients’ medical records, including their history, laboratory analyses, radiological reports, and clinical and pathological staging, were retrospectively reviewed. NLR was calculated as th e neutrophil count/lymphocyte count, and PLR was computed using th e platelet count/lymphocyte count. and the Youden index was used to establish the optimal cut -off values of NLR and PLR. Statistical analysis. Categorical data are shown as proportions, and all statistical analyses were conducted using GraphPad Prism (Version 8.4.2, San Diego, California, USA) and SPSS (R26.0, Armonk, New York, USA), and a two-sided P < 0.05, which was deemed statistically significant . The quantitative data (harvested total lymph nodes) was not a normal distribution as the Shapiro-Wilk test verified; therefore, it was shown as (median ,IQR) and was compared using the Mann-Whitney U test. The chi-square test or Fisher's exact test was used to examine categorical variables. and logistic regression analyses were used to explore the relationship between metastatic lymph nodes and different characteristics. P-values were considered statistically significant if they were less than 0.05. Results Patient characteristics This study included 232 patients with resectable rectal cancer. Following the exclusion of incomplete records and patients who were lost to follow-up, 181 patients were included in the statistical analysis. The baseline characteristics of the patients were listed in table 1. The median age of the patients was 63 years, with 113 (62.4%) males and 68 (37.5%) females. Based on the eighth edition of the TNM classification, 38 (21.0%) patients were classified as having TNM stage I disease, 57 (31.5%) as having stage II disease, and 86 (47.5%) as having stage III disease. Additionally, 90 (49.7%) patients tested positive for perineural invasion (PNI), 87 (48.1%) for lymphovascular invasion (LVI), and 22 (12.2%) for tumor deposits (TDs). Furthermore, 86 patients (47.5%) presented with lymph node metastasis. Table1 Baseline Characteristics of the Patients Data(n,%) Age ≥65 80(44.2%) <65 101(55.8%) Sex Male 113（62.4%） Female 68（37.6%） Location ≥5cm 144（79.6%） <5cm 37（20.4%） CEA ≥5ng/ml 70（38.7%） <5ng/ml 111（61.3%） TNM Ⅰstage 38（21.0%） Ⅱ stage 57（31.5%） Ⅲ stage 86（47.5%） PNI Positive 90（49.7%） Negative 91（50.3%） LVI Positive 87（48.1%） Negative 94（51.9%） TDs Positive 22（12.2%） Negative 159（87.8%） Lymph nodes metastasis Yes 86（47.5%） No 95（52.5%） NLR H-NLR 38(21.0%) L-NLR 143(79.0%) PLR H-PLR 153(84.5%) L-PLR 28(15.5%) TLN(median,IQR) 18（15-22） Abbreviations: LVI:lymphovascular invasion;PNI:perineural invasion;CEA:carcinoembryonic antigen TDs:tumor deposits;TNM:tumor node metastasis; NLR:neutrophil-to-lymphocyte ratio PLR:platelet-to-lymphocyte ratio; H-NLR: high neutrophil-to-lymphocyte ratio L-NLR: low neutrophil-to-lymphocyte ratio ; H-PLR: high platelet-to-lymphocyte ratio L-PLR: low platelet-to-lymphocyte ratio;TLN:total lymphnode number;IQR: interquartile range Association NLR (or PLR) and clinicalpathological Characteristics The cut-off values for PLR and NLR were 89.1 and 3.4, respectively.NLR or PLR status (low or high based on the cutoff value) was used to assess the patient features. None of the parameters differed significantly between the H-NLR and L-NLR groups ( table 2). However, there were substantial differences between the H-PLR and L-PLR. The H-PLR group had a higher positive PNI (83/153,54.2%), positive LVI(79/153,51.6%),and positive TDs (22/153,14.4%), more lymph node metastases (81/153,52.9%), more elevated CEA (66/153,43.1%) and a more advanced tumor stage (stageⅡ +stageⅢ,124/153,81%). Table2 . Correlation of Clinicopathological Characteristics and NLR(or PLR) levels in Rectal Cancer . Viable NLR(n,%) P PLR(n,%) P NLR (38,21.0%) NLR (143,79.0%) H-PLR (153,84.5%) L-PLR (28,15.5%) Age（y） 0.418 0.796 ≥65 19(50.0%) 61(42.7%) 67(43.8%) 13(46.4%) <65 19(50.0%) 82(57.3%) 86(56.2%) 15(53.6%) Sex 0.826 Male 22(57.9%) 91(63.6%) 0.320 95(62.1%) 18(64.3%) Female 16(41.1%) 52(36.4%) 58(37.9%) 10(35.7%) Location (cm) 0.577 0.888 ≥5 29(76.3%) 115(80.4%) 122(79.7%) 22(78.6%) <5 9(23.7%) 28(19.6%) 31(20.3%) 6(21.4%) TNM 0.515 0.003*c Ⅰ 6(15.8%) 32(22.4%) 29(19.0%) 9(32.1%) Ⅱ 11(28.9%) 46(32.2%) 43(28.1%) 14(50%) Ⅲ 21(55.3%) 65(45.4%) 81(52.9%) 5(17.9%) PNI 0.442 0.004* Negative 17(44.7%) 74(51.7%) 70(45.8%) 21(75.0%) Positive 21(55.3%) 69(48.3%) 83(54.2%) 7(25.0%) LVI 0.172 0.025* Negative 16(42.1%) 78(54.5%) 74(48.4%) 20(71.4%) Positive 22(57.9%) 65(45.5%) 79(51.6%) 8(28.6%) TDs 0.730 a 0.028* a Negative 34(89.5%) 125(87.4%) 131(85.6%) 28(100%) Positive 4(10.5%) 18(12.6%) 22(14.4%) 0(0%) Lymph nodes metastasis 0.361 <0.001* No 17(44.7%) 78(54.5%) 72(47.1%) 23(82.1%) Yes 21(55.3%) 65(45.5%) 81(52.9%) 5(17.9%) TLN(median,IQR) 19.5 (15.0-24.7) 18 (14.0-22.0) 0.227 b 18.0(15.0-22.0) 18.5(14.0-20.0) 0.283 b CEA(ng/ml) 0.853 0.005* ≥5 14(36.8%) 56(39.2%) 66(43.1%) 4(14.3%) <5 24(63.2%) 87(60.8%) 87(56.9%) 24(85.7%) CA199 (ng/ml) 0.823 0.800 ≥27 8(21.1%) 28(19.6%) 30(19.6%) 6(21.4%) <27 30(78.9%) 115(80.4%) 123(80.4%) 22(78.6%) Data are presented as n (%),Bolded p-values indicate statistical significance at p<0.05 Abbreviations: LVI: lymphovascular invasion ; PNI:p erineural invasion ; CEA: carcinoembryonic antigen TDs:tumor deposits; TNM: tumor node metastasis; NLR:neutrophil-to-lymphocyte ratio ； PLR:platelet-to-lymphocyte ratio TLN:total lymphnode number;IQR: interquartile range using Fisher’s exact test or chi-squared test for categorical variables a P -value was estimated by the Fisher Exact test. b P -value was estimated by Mann-Whitney U test Univariate and Multivariate Analysis of LNM As shown in table 3, The results showed that advaced T stage (OR： 3.156,95%CI:1.580-6.303),positive PNI (OR:6.182,95%CI:3.242-2.268)，positive LVI (OR：10.271,95%CI:0.805-11.787), H-PLR(OR:5.175,95%CI:1.870-14.321),positive TDs(OR:0.390,95%CI:1.261-9.117),TLN(OR:1.053,95%CI:1.005-1.103),elevated CEA(OR：3.313,95%CI:1.655-5.920) and elevated CA199 (OR：2.248,95%CI:1.012-4.992) were correlated with LNM using univariate analysis,but only positive LVI(OR:6.203,95%CI:2.892-13.303) and positive PNI(OR:3.086,95%CI:1.341-7.102) were the independent risk factors for LNM using multivariate analysis. Table 3 Logistic Regression Analysis of the Relationship Between Lymph Node Metastasis and Clinicopathological Characteristics in Rectal Cancer Patients Viable Univariate Analysis OR (95% CI) P Multivariate Analysis OR (95% CI) P Age(y) 0.261 ≥65 Ref. <65 0.712(0.394-1.287) gender 0.409 male Ref. female 1.289(0.706-2.356) location 0.094 ≥5cm Ref. <5cm 0.527(0.249-1.115) T stage 0.001* 0.604 T1-2 Ref. Ref. T3-4 3.156(1.580-6.303) 1.272(0.512-3.157) PNI <0.001* 0.008* Negative Ref. Ref. Positive 6.182(3.242-2.268) 3.086(1.341-7.102) LVI <0.001* <0.001* Negative Ref. Ref. Positive 10.271(0.805-11.787) 6.203(2.892-13.303) NLR 0.283 L-NLR Ref. H-NLR 1.482(0.722-3.043) PLR 0.002* 0.063 L-PLR Ref. Ref. H-PLR 5.175(1.870-14.321) 3.146(0.939-10.538) TDs 0.016* 0.831 Negative Ref. Ref. Positive 3.390(1.261-9.117) 1.142(0.337-3.869) TLN 1.053(1.005-1.103) 0.030* 1.016(0.958-1.078) 0.593 CEA (ng/mL) <0.001* 0.204 <5 Ref. Ref. ≥5 3.313(1.655-5.920) 1.684(0.754-3.761) CA199 (ng/mL) 0.047* 0.066 <27 Ref. Ref. ≥27 2.248(1.012-4.992) 2.529(0.940-6.804) Abbreviations: LVI: lymphovascular invasion ; PNI:p erineural invasion ; CEA: carcinoembryonic antigen TDs:tumor deposits; NLR:neutrophil-to-lymphocyte ratio ； PLR:platelet-to-lymphocyte ratio;OR:odd risk Discussion Inflammation facilitates a pro-oncogenic milieu that promotes the spread of cancer [10]. By encouraging the adherence of circulating tumor cells to distant organs, neutrophils promote tumor development of tumors [11]. In addition to preventing cell death and distant metastasis, platelets can help tumor cells attach to the endothelium[12].Because lymphocytes prevent tumor cells from proliferating and cause cytotoxic cell death, they are believed to have an anti-tumor effect[13]. One study found that patients with rectal cancer who had tumor infiltration of CD4+ and CD8+ cells had a higher chance of survival [14]. The NLR and PLR are two indicators that have been found to be predictive biomarkers in patients with colorectal cancer,and elevated NLR is negative to overall survival (OS) and disease-free survival[15]. Further research indicated that a high NLR was associated with unfavorable survival outcomes in proficient mismatch repair (pMMR) colorectal cancer but not in patients with deficient mismatch repair (dMMR)[16]. Additionally, NLR can serve as a predictor of recurrence in rectal cancer[17]. Poor pathological complete response (pCR) was predicted by the percentage change in NLR from pre- to post-neoadjuvant chemoradiotherapy(nCRT) in locally advanced rectal cancer[18]. A high PLR has been associated with the occurrence of lymph node metastasis; however, it does not affect overall survival or disease-free survival in CRC[19]. Additionally, it may be a useful predictor of lateral lymph node recurrence in patients with rectal cancer[20]. Conversely, another study indicated that NLR did not demonstrate any predictive value regarding node status in rectal cancer when subjected to multivariate analysis[21]. Gaudioso et al. found that an NLR greater than 2.12 was the most dependable indicator for identifying occult lymph node metastasis in cN0 HNSCC[8]. Furthermore, the preoperative NLR may prove to be an effective supplementary tool for assessing lymph nodes in patients with gastric cancer [9]. NLR and PLR were readily assessed as they were routinely measured in every patient prior to treatment. However, elevated levels may also occur in infectious diseases, complicating the distinction from cancer-related inflammation. Various NLR thresholds have been reported in numerous retrospective investigations[22], and the cutoff values for NLR can be established through ROC analysis. Mean values have also been utilized in certain studies[5, 23]. Lymph node metastasis(LNM) is closely associated with rectal cancer T staging. Research indicates that the risk of LNM progressively increases from T1 (6%–65%) to T2 (11%–78%) in early rectal cancer[24]. Furthermore, the odds ratio for the pT stage is approximately 10 for patients with pT1/2 and > 20 for those with pT3/4[25]. In our study, we observed that patients with T3/4 stage had a higher number of positive lymph nodes than those with T1/2 stages, suggesting that T3/4 is a significant risk factor for LNM based on univariate analysis,while the advanced T stage was not an indepandent risk factor for LNM in rectal cancer . Perineural invasion (PNI) has been used as a predictive factor for residual LNM in locally advanced rectal cancer after nCRT[26]. Multivariate analysis indicated that lymphovascular invasion (LVI) was significantly associated with nodal involvement in T1-2 rectal cancer[27]. This study also demonstrated that both PNI and LVI were independent factors contributing to LNM in rectal cancer. This study has several limitations. For one,compared with other comparable studies, the sample size was small, and this study was conducted within a single institution, the cut-off values for NLR or PLR necessitate external validation in additional cohorts to strengthen their credibility.For another, this study did not include radiologic assessment of nodal involvement.The additional benefit of NLR/PLR in conjunction with standard radiologic evaluations remains uncertain and warrants further investigation,and other hematologic markers, such as the lymphocyte-monocyte ratio and platelet counts, could also be investigated in future research.Furthermore,the exclusion of patients who received neoadjuvant chemotherapy or radiotherapy may lead to an underrepresentation of locally advanced rectal cancers that are typically treated with such interventions,it was a potential selection bias. Last not the least, the levels of NLR and PLR may be affected by the intrinsic limitations of retrospective studies. Conclusion NLR and PLR are not predictors of lymph node metastasis in rectal cancer. However, PNI, LVI, and high PLR may act as independent risk factors for lymph node metastasis in rectal cancer. Abbreviations SIR systemic inflammatory response LNM lymph node metastasis RC colorectal cancer OS overall survival AJCC American Joint Committee on Cancer LVI lymphovascular invasion TD tumor deposits PNI perineural invasion CEA carcinoembryonic antigen NLR neutrophil-to-lymphocyte ratio PLR platelet-to-lymphocyte ratio Declarations Acknowledgements Not applicable. Author Contribution Guohua Yang analyzed and interpreted the patient data and designed the plan. Zhijie You and performed the histological examinations. Yangfeng Lin drafted and edited the manuscript. Zhijing Lin and Siming Wang performed the follow-up and collected the patient data. All authors have read and approved the final manuscript. Funding Declaration. Fujian Provincial Health Commission Middle-Young-Generation Talent Cultivation Project（2020GGB007）. Data Availability Data is provided within supplementary information files，and it could be gotten for free. Ethics approval and consent to participate This study was approved by the Ethics Committee of the FuJian provincal Hospital.. This study was conducted in accordance with the Declaration of Helsinki, Written informed consent was obtained from each patient before receiving the start of the study. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Author details 1. Department of Gastrointestinal Surgery II, The First Hospital of Putian City Putian Putian Fujian 351100 China 2.Department of Gastrointestinal Surgery, Fujian Medical University Provincial Clinical College FuZhou FuJiang 350007 China 3 Department of Internal Medicine, Fujian Medical University Provincial Clinical College FuZhou FuJiang 350007 China References Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I and Jemal A. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2024; 74: 229-263. Benedek Z, Boer ST, Bauer O, Sardi K, Todor A, Suciu N and Coros MF. An Overview of Five-Year Survival in Rectal Cancer in Relation to Lymph Node Status. Chirurgia (Bucur) 2020; 115: 747-755. Hanahan D and Weinberg RA. Hallmarks of cancer: the next generation. Cell 2011; 144: 646-674. Yamamoto T, Kawada K and Obama K. 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Supplementary Files Youden.xlsx Cite Share Download PDF Status: Published Journal Publication published 12 May, 2025 Read the published version in BMC Gastroenterology → Version 1 posted Editorial decision: Revision requested 08 Apr, 2025 Reviewers agreed at journal 05 Apr, 2025 Reviews received at journal 31 Mar, 2025 Reviewers agreed at journal 31 Mar, 2025 Reviewers invited by journal 31 Mar, 2025 Submission checks completed at journal 31 Mar, 2025 First submitted to journal 30 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-5937143","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":436397475,"identity":"739f285a-44a8-435d-a5ed-c7ca2e965295","order_by":0,"name":"Yangfeng Lin","email":"","orcid":"","institution":"The First Hospital of Putian City Putian Putian Fujian","correspondingAuthor":false,"prefix":"","firstName":"Yangfeng","middleName":"","lastName":"Lin","suffix":""},{"id":436397476,"identity":"6f3793a7-247a-47b7-8a00-9bb7f7eed578","order_by":1,"name":"Zhijie You","email":"","orcid":"","institution":"Fujian Medical University Provincial Clinical College FuZhou","correspondingAuthor":false,"prefix":"","firstName":"Zhijie","middleName":"","lastName":"You","suffix":""},{"id":436397477,"identity":"d5297fb2-8ac5-4826-a350-18787f74557b","order_by":2,"name":"Zhijing Lin","email":"","orcid":"","institution":"Fujian Medical University Provincial Clinical College","correspondingAuthor":false,"prefix":"","firstName":"Zhijing","middleName":"","lastName":"Lin","suffix":""},{"id":436397478,"identity":"a87cd49d-1837-4f94-bddf-30188a9a39f3","order_by":3,"name":"Siming Wang","email":"","orcid":"","institution":"Fujian Medical University Provincial Clinical College","correspondingAuthor":false,"prefix":"","firstName":"Siming","middleName":"","lastName":"Wang","suffix":""},{"id":436397479,"identity":"1193266c-b89f-4b8b-9889-cb6279f033b0","order_by":4,"name":"Guo Hua Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYBACeYYDCYd/GNjYybM3EKnFsPHAw8cMFWnJhj0HiLXm8MHHxgxnDjE23EggUgdj2+E06cK2A8yMMx9vvMFQYxNNUAs7z7E06Zltd/jYpdOKLRiOpeU2ELRlxpk0Cd62Z8yMs3PMJBgbDhPWwnD//TeglsOMDTfPEKvlwIFkY54zQC03eIjUYthwIPHhDHAgA/2SQIxfQFF54AM4Kg9vvPGhxoYIhyEBA4kEUpRDtJCqYxSMglEwCkYGAAAJK0giDvMvdAAAAABJRU5ErkJggg==","orcid":"","institution":"Fujian Medical University Provincial Clinical College","correspondingAuthor":true,"prefix":"","firstName":"Guo","middleName":"Hua","lastName":"Yang","suffix":""}],"badges":[],"createdAt":"2025-01-31 14:53:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5937143/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5937143/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12876-025-03960-6","type":"published","date":"2025-05-12T15:57:32+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":83068012,"identity":"000b3dba-9a72-4ba8-a3ba-ece4a20ccdc3","added_by":"auto","created_at":"2025-05-19 16:09:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1399172,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5937143/v1/f7c0b891-5221-40cf-837c-15ecd5e8f431.pdf"},{"id":79651518,"identity":"35581f5b-2130-46e5-9c10-cf6b4850d196","added_by":"auto","created_at":"2025-04-01 07:57:00","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":18303,"visible":true,"origin":"","legend":"","description":"","filename":"Youden.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5937143/v1/d01c5f6f6508c78c11acbe04.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Predictive Value of Neutrophil-to-Lymphocyte Ratio(NLR) and Platelet-to-Lymphocyte Ratios (PLR) for Lymph Node Metastasis in Rectal Cancer Patients: a retrospective cohort study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eColorectal cancer (CRC) is the second most fatal and third most frequent type of cancer worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Lymph node metastasis(LNM) is a prevalent metastasis in CRC and serves as a vital risk factor \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethat influenc\u003c/span\u003ees the 5-year overall survival [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Consequently, there is a pressing need for effective molecular biomarkers to predict lymph node metastasis in clinical practice.\u003c/p\u003e \u003cp\u003eInflammatory reactions linked to cancer are a defining feature of the onset and spread of the disease[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Mounting evidence suggests that inflammatory indicators are strongly linked to poor prognosis in CRC[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Hematologic\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eal measures can represent systemic inflammatory responses\u003c/span\u003e, such as neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR). It has been established that a rise in these markers is detrimental to the prognosis of rectal cancer[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eResearch has indicated that NLR may be a strong predictor of LNM in breast cancer[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Additionally, it has been identified as a reliable predictor of LNM in head and neck squamous cell carcinoma(HNSCC) and gastric cancer[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eConversely,NLR\u003c/span\u003e has seldom been \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eu\u003c/span\u003esed as a predictor of rectal cancer,although studies have shown that a high NLR is associated with a more positive nodal status[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eTherefore, further investigation is required to ascertain its true predictive significance.\u003c/span\u003e The purpose of this study was to investigate whether NLR and PLR is corrected with LNM in patients with resectable rectal cancer and to explore the risk factors for lymph node metastasis.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003ePatients diagnosed with rectal cancer who underwent curative resection at our institution between May 2015 and December 2022 were included in the study. From an initial pool of 232 potential rectal cancer cases, 181 patients with complete data were selected for analysis; the remaining cases were excluded. All participants underwent CT and pelvic MRI prior to surgery. The surgical procedure was laparoscopic radical resection. This research was carried out in accordance with the guidelines established in the 1964 Declaration of Helsinki and its later revisions and was approved by the Research Ethics Committee of Fujian Provincial Hospital, under the ethics approval code K2024-07-037. Because this study was retrospective, \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ewritten informed\u003c/span\u003e consent was obtained from all patients who had been diagnosed with rectal cancer.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eIncluding and excluding criteria\u003c/h3\u003e\n\u003cp\u003eInclusion was determined according to the following criteria:(1) a diagnosis of rectal adenocarcinoma confirmed to endoscopic biopsy pathology; (2) the cancer must be situated within 15 cm of the anal verge, \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eas determined by endoscopic evaluation; (3)\u003c/span\u003e an ECOG performance status of 0 to 2; (4) no prior medical history of malignant tumors or any surgical contraindications. The exclusion \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ecriteria were defined as follows: (I) incomplete clinical data; (II)\u003c/span\u003e existence of infections before surgery; (III) administration of drugs that increase leukocytes;(IV)patients who have undergone neoadjuvant radiotherapy or chemotherapy; (V) individuals with malignant tumors affecting other organ systems; \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eand (VI) patients exhibiting liver or other organ metastases.\u003c/span\u003e\u003c/p\u003e\n\u003ch3\u003eData Collection and Study Design\u003c/h3\u003e\n\u003cp\u003eWithin a day of admission, 3 \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003emL\u003c/span\u003e of peripheral blood was collected from each patient. Counts of neutrophils, lymphocytes, and platelets were retrieved from the hospital information system, and the database variables included age, sex, tumor location, NLR, PLR, and so on,as shown in \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003etable 1\u003c/span\u003e. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eThe eighth edition of\u003c/span\u003e the American Joint Committee on Cancer's (AJCC) eighth edition of the tumor-node-metastasis(TNM) grading system was used to stage the patient\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003es in this study\u003c/span\u003e. Patients\u0026rsquo; medical records, including their history, laboratory analyses, radiological reports, and clinical and pathological staging, \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ewere retrospectively reviewed.\u003c/span\u003e\u003c/p\u003e \u003cp\u003eNLR was calculated \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eas\u003c/span\u003e th\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ee\u003c/span\u003e neutrophil count/lymphocyte count, and PLR was computed \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eusing\u003c/span\u003e th\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ee\u003c/span\u003e platelet count/lymphocyte count. and the Youden index was used to establish the optimal cut\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e-off values\u003c/span\u003e of NLR and PLR.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis.\u003c/h2\u003e \u003cp\u003eCategorical data are shown as proportions, \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eand\u003c/span\u003e all statistical analyses were conducted using GraphPad Prism (Version 8.4.2, San Diego, California, USA) and SPSS (R26.0, Armonk, New York, USA), and a two-sided P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ewhich was deemed statistically significant\u003c/span\u003e. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eThe quantitative data (harvested total lymph nodes)\u003c/span\u003e was not a normal distribution as the Shapiro-Wilk test verified; therefore, it was shown as (median ,IQR) and was compared using \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe Mann-Whitney U test.\u003c/span\u003e The chi-square test or Fisher's exact test was used to examine categorical variables. and logistic regression analyses were used to explore the relationship between metastatic lymph nodes and different characteristics. P-values were considered statistically significant if they were less than 0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePatient characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study included 232 patients with resectable rectal cancer.\u0026nbsp;Following the exclusion of incomplete records and patients who were lost to follow-up,\u0026nbsp;181 patients were included in the statistical analysis. The baseline characteristics\u0026nbsp;of the patients were\u0026nbsp;listed\u0026nbsp;in table 1. The median age of the patients was 63 years, with 113 (62.4%) males and 68 (37.5%) females.\u0026nbsp;Based on the eighth edition\u0026nbsp;of the TNM classification, 38 (21.0%) patients were classified as having TNM stage I disease, 57 (31.5%) as having stage II disease, and 86 (47.5%) as having stage III disease. Additionally, 90 (49.7%) patients tested positive for perineural invasion (PNI), 87 (48.1%) for lymphovascular invasion (LVI), and 22 (12.2%) for tumor deposits (TDs). Furthermore, 86 patients (47.5%) presented with lymph node metastasis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable1 \u0026nbsp;Baseline Characteristics of the Patients\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;Data(n,%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026ge;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e80(44.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026lt;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e101(55.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003e\u0026nbsp; Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e113（62.4%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e68（37.6%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eLocation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003e\u0026ge;5cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e144（79.6%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003e\u0026lt;5cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e37（20.4%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eCEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003e\u0026ge;5ng/ml\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e70（38.7%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003e\u0026lt;5ng/ml\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e111（61.3%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eTNM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eⅠstage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e38（21.0%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eⅡ stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e57（31.5%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eⅢ stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e86（47.5%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003ePNI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e90（49.7%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e91（50.3%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eLVI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e87（48.1%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e94（51.9%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eTDs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e22（12.2%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e159（87.8%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eLymph nodes metastasis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e86（47.5%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e95（52.5%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eH-NLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e38(21.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eL-NLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e143(79.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003ePLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eH-PLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e153(84.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eL-PLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e28(15.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 218px;\"\u003e\n \u003cp\u003eTLN(median,IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e18（15-22）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations: \u0026nbsp;LVI:lymphovascular invasion;PNI:perineural invasion;CEA:carcinoembryonic antigen\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTDs:tumor deposits;TNM:tumor node metastasis; NLR:neutrophil-to-lymphocyte ratio\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePLR:platelet-to-lymphocyte ratio; \u0026nbsp;H-NLR: high neutrophil-to-lymphocyte ratio\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eL-NLR: low neutrophil-to-lymphocyte ratio ; H-PLR: high platelet-to-lymphocyte ratio\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eL-PLR: low platelet-to-lymphocyte ratio;TLN:total lymphnode number;IQR:\u003c/strong\u003e\u003cstrong\u003einterquartile range\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociation NLR (or PLR) and clinicalpathological Characteristics\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe cut-off values for PLR and NLR were 89.1 and 3.4, respectively.NLR or PLR status (low or high based on the cutoff value) was used to assess the patient features. None of the parameters differed significantly between the H-NLR and L-NLR groups ( table 2). However, there were substantial differences between the H-PLR and L-PLR. The H-PLR group had a higher positive PNI (83/153,54.2%), positive LVI(79/153,51.6%),and positive TDs (22/153,14.4%), more lymph node metastases (81/153,52.9%), more elevated CEA (66/153,43.1%) and a more advanced tumor stage (stageⅡ +stageⅢ,124/153,81%).\u003cstrong\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable2\u0026nbsp;\u003c/strong\u003e. \u003cstrong\u003eCorrelation of Clinicopathological Characteristics and NLR(or PLR) levels in Rectal Cancer .\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"586\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eViable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eNLR(n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003ePLR(n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eP\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003col\u003e\n \u003cli\u003eNLR\u003c/li\u003e\n \u003c/ol\u003e\n \u003cp\u003e(38,21.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003col\u003e\n \u003cli\u003eNLR\u003c/li\u003e\n \u003c/ol\u003e\n \u003cp\u003e(143,79.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eH-PLR\u003c/p\u003e\n \u003cp\u003e(153,84.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eL-PLR\u003c/p\u003e\n \u003cp\u003e(28,15.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eAge（y）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.418\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.796\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026ge;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e19(50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e61(42.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e67(43.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e13(46.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026lt;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e19(50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e82(57.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e86(56.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e15(53.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.826\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp; Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e22(57.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e91(63.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e95(62.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e18(64.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e16(41.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e52(36.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e58(37.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e10(35.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eLocation\u003c/p\u003e\n \u003cp\u003e(cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.577\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.888\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026ge;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e29(76.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e115(80.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e122(79.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e22(78.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026lt;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e9(23.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e28(19.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e31(20.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e6(21.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eTNM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.515\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.003*c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eⅠ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e6(15.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e32(22.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e29(19.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e9(32.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eⅡ\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e11(28.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e46(32.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e43(28.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e14(50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eⅢ\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e21(55.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e65(45.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e81(52.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e5(17.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003ePNI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.004*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e17(44.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e74(51.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e70(45.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e21(75.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e21(55.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e69(48.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e83(54.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e7(25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eLVI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.025*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e16(42.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e78(54.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e74(48.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e20(71.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e22(57.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e65(45.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e79(51.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e8(28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eTDs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.730\u003csub\u003ea\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.028*\u003csub\u003ea\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e34(89.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e125(87.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e131(85.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e28(100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e4(10.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e18(12.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e22(14.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0(0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eLymph nodes metastasis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.361\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e17(44.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e78(54.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e72(47.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e23(82.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e21(55.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e65(45.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e81(52.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e5(17.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eTLN(median,IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e19.5\u003c/p\u003e\n \u003cp\u003e(15.0-24.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003cp\u003e(14.0-22.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.227\u003csub\u003eb\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e18.0(15.0-22.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e18.5(14.0-20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.283\u003csub\u003eb\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eCEA(ng/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.853\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.005*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026ge;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e14(36.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e56(39.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e66(43.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e4(14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026lt;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e24(63.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e87(60.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e87(56.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e24(85.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eCA199\u003c/p\u003e\n \u003cp\u003e(ng/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.823\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.800\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026ge;27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e8(21.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e28(19.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e30(19.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e6(21.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026lt;27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e30(78.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e115(80.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e123(80.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e22(78.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eData are presented as n (%),Bolded p-values indicate statistical significance at p\u0026lt;0.05\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;LVI:\u003c/strong\u003e\u003cstrong\u003elymphovascular invasion\u003c/strong\u003e\u003cstrong\u003e;\u003c/strong\u003e\u003cstrong\u003ePNI:p\u003c/strong\u003e\u003cstrong\u003eerineural invasion\u003c/strong\u003e\u003cstrong\u003e;\u003c/strong\u003e\u003cstrong\u003eCEA:\u003c/strong\u003e\u003cstrong\u003ecarcinoembryonic antigen\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eTDs:tumor deposits;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTNM:\u003c/strong\u003e\u003cstrong\u003etumor node metastasis;\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eNLR:neutrophil-to-lymphocyte ratio\u003c/strong\u003e\u003cstrong\u003e；\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ePLR:platelet-to-lymphocyte ratio\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTLN:total lymphnode number;IQR:\u003c/strong\u003e\u003cstrong\u003einterquartile range\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eusing Fisher\u0026rsquo;s exact test or chi-squared test for categorical variables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003cstrong\u003e-value was estimated by the Fisher Exact test.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003cstrong\u003e-value was estimated by\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eMann-Whitney U test\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUnivariate and Multivariate Analysis of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eLNM\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in table 3, The results showed that advaced T stage (OR：\u0026nbsp;3.156,95%CI:1.580-6.303),positive PNI (OR:6.182,95%CI:3.242-2.268)，positive LVI (OR：10.271,95%CI:0.805-11.787), H-PLR(OR:5.175,95%CI:1.870-14.321),positive TDs(OR:0.390,95%CI:1.261-9.117),TLN(OR:1.053,95%CI:1.005-1.103),elevated CEA(OR：3.313,95%CI:1.655-5.920) and elevated CA199 (OR：2.248,95%CI:1.012-4.992) were correlated with LNM using univariate analysis,but only positive LVI(OR:6.203,95%CI:2.892-13.303) and positive PNI(OR:3.086,95%CI:1.341-7.102) were the independent risk factors for LNM using multivariate analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e\u0026nbsp; \u003cstrong\u003eLogistic Regression Analysis of the Relationship Between Lymph Node Metastasis and Clinicopathological Characteristics in Rectal Cancer Patients\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"554\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eViable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eUnivariate Analysis\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;OR (95% CI)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003eMultivariate Analysis\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eAge(y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026ge;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026lt;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e0.712(0.394-1.287)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003egender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.409\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp; female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.289(0.706-2.356)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003elocation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026ge;5cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026lt;5cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e0.527(0.249-1.115)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eT stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e0.604\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eT1-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eT3-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e3.156(1.580-6.303)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e1.272(0.512-3.157)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003ePNI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e0.008*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e6.182(3.242-2.268)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e3.086(1.341-7.102)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eLVI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e10.271(0.805-11.787)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e6.203(2.892-13.303)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.283\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eL-NLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eH-NLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.482(0.722-3.043)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003ePLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.002*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eL-PLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eH-PLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e5.175(1.870-14.321)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e3.146(0.939-10.538)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eTDs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.016*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e0.831\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e3.390(1.261-9.117)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e1.142(0.337-3.869)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eTLN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.053(1.005-1.103)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.030*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e1.016(0.958-1.078)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e0.593\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eCEA\u003c/p\u003e\n \u003cp\u003e(ng/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e0.204\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026lt;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026ge;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e3.313(1.655-5.920)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e1.684(0.754-3.761)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eCA199\u003c/p\u003e\n \u003cp\u003e(ng/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.047*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026lt;27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026ge;27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e2.248(1.012-4.992)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003e2.529(0.940-6.804)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;LVI:\u003c/strong\u003e\u003cstrong\u003elymphovascular invasion\u003c/strong\u003e\u003cstrong\u003e;\u003c/strong\u003e\u003cstrong\u003ePNI:p\u003c/strong\u003e\u003cstrong\u003eerineural invasion\u003c/strong\u003e\u003cstrong\u003e;\u003c/strong\u003e\u003cstrong\u003eCEA:\u003c/strong\u003e\u003cstrong\u003ecarcinoembryonic antigen\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eTDs:tumor deposits;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;NLR:neutrophil-to-lymphocyte ratio\u003c/strong\u003e\u003cstrong\u003e；\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ePLR:platelet-to-lymphocyte ratio;OR:odd risk\u003c/strong\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eInflammation facilitates a pro-oncogenic milieu that promotes the spread of cancer [10]. By encouraging the adherence of circulating tumor cells to distant organs, neutrophils promote tumor development of tumors [11]. In addition to preventing cell death and distant metastasis, platelets can help tumor cells attach to the endothelium[12].Because lymphocytes prevent tumor cells from proliferating and cause cytotoxic cell death, they are believed to have an anti-tumor effect[13]. One study found that patients with rectal cancer who had tumor infiltration of CD4+ and CD8+ cells had a higher chance of survival [14]. The NLR and PLR are two indicators that have been found to be predictive biomarkers in patients with colorectal cancer,and elevated NLR is negative to overall survival (OS) and disease-free survival[15]. Further research indicated that a high NLR was associated with unfavorable survival outcomes in proficient mismatch repair (pMMR) colorectal cancer but not in patients with deficient mismatch repair (dMMR)[16]. Additionally, NLR can serve as a predictor of recurrence in rectal cancer[17]. Poor pathological complete response (pCR) was predicted by the percentage change in NLR from pre- to post-neoadjuvant chemoradiotherapy(nCRT) in locally advanced rectal cancer[18].\u003c/p\u003e\n\u003cp\u003eA high PLR has been associated with the occurrence of lymph node metastasis; however, it does not affect overall survival or disease-free survival in CRC[19]. Additionally, it may be a useful predictor of lateral lymph node recurrence in patients with rectal cancer[20]. Conversely, another study indicated that NLR did not demonstrate any predictive value regarding node status in rectal cancer when subjected to multivariate analysis[21]. Gaudioso et al. found that an NLR greater than 2.12 was the most dependable indicator for identifying occult lymph node metastasis in cN0 HNSCC[8]. Furthermore, the preoperative NLR may prove to be an effective supplementary tool for assessing lymph nodes in patients with gastric cancer [9].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNLR and PLR were readily assessed as they were routinely measured in every patient prior to treatment. However, elevated levels may also occur in infectious diseases, complicating the distinction from cancer-related inflammation. Various NLR thresholds have been reported in numerous retrospective investigations[22], and the cutoff values for NLR can be established through ROC analysis. Mean values have also been utilized in certain studies[5, 23].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLymph node metastasis(LNM) is closely associated with rectal cancer T staging. Research indicates that the risk of LNM progressively increases from T1 (6%\u0026ndash;65%) to T2 (11%\u0026ndash;78%) in early rectal cancer[24]. Furthermore, the odds ratio for the pT stage is approximately 10 for patients with pT1/2 and \u0026gt; 20 for those with pT3/4[25]. In our study, we observed that patients with T3/4 stage had a higher number of positive lymph nodes than those with T1/2 stages, suggesting that T3/4 is a significant risk factor for LNM based on univariate analysis,while the advanced T stage was not an indepandent risk factor for \u0026nbsp;LNM in rectal cancer .\u003c/p\u003e\n\u003cp\u003ePerineural invasion (PNI) has been used as a predictive factor for residual LNM in locally advanced rectal cancer after nCRT[26]. Multivariate analysis indicated that lymphovascular invasion (LVI) was significantly associated with nodal involvement in T1-2 rectal cancer[27]. This study also demonstrated that both PNI and LVI were independent factors contributing to LNM in rectal cancer.\u003c/p\u003e\n\u003cp\u003eThis study has several limitations. For one,compared with other comparable studies, the sample size was small, and this study was conducted within a single institution, the cut-off values for NLR or PLR necessitate external validation in additional cohorts to strengthen their credibility.For another, this study did not include radiologic assessment of nodal involvement.The additional benefit of NLR/PLR in conjunction with standard radiologic evaluations remains uncertain and warrants further investigation,and other hematologic markers, such as the lymphocyte-monocyte ratio and platelet counts, could also be investigated in future research.Furthermore,the exclusion of patients who received neoadjuvant chemotherapy or radiotherapy may lead to an underrepresentation of locally advanced rectal cancers that are typically treated with such interventions,it was a potential selection bias. Last not the least, the levels of NLR and PLR may be affected by the intrinsic limitations of retrospective studies.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eNLR and PLR are not predictors of lymph node metastasis in rectal cancer. However, PNI, LVI, and high PLR may act as independent risk factors for lymph node metastasis in rectal cancer.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eSIR \u0026nbsp; \u0026nbsp; \u0026nbsp; systemic inflammatory response\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLNM \u0026nbsp; \u0026nbsp; lymph node metastasis\u003c/p\u003e\n\u003cp\u003eRC \u0026nbsp; \u0026nbsp; \u0026nbsp; colorectal cancer\u003c/p\u003e\n\u003cp\u003eOS \u0026nbsp; \u0026nbsp; \u0026nbsp; overall survival\u003c/p\u003e\n\u003cp\u003eAJCC \u0026nbsp; \u0026nbsp; American Joint Committee on Cancer\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLVI \u0026nbsp; \u0026nbsp; \u0026nbsp; lymphovascular invasion\u003c/p\u003e\n\u003cp\u003eTD \u0026nbsp; \u0026nbsp; \u0026nbsp; tumor deposits\u003c/p\u003e\n\u003cp\u003ePNI \u0026nbsp; \u0026nbsp; \u0026nbsp;perineural invasion\u003c/p\u003e\n\u003cp\u003eCEA \u0026nbsp; \u0026nbsp; carcinoembryonic antigen\u003c/p\u003e\n\u003cp\u003eNLR \u0026nbsp; neutrophil-to-lymphocyte ratio\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePLR \u0026nbsp; platelet-to-lymphocyte ratio\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGuohua Yang analyzed and interpreted the patient data and designed the plan. Zhijie You and performed the histological examinations.\u0026nbsp;Yangfeng Lin drafted and edited the manuscript. Zhijing Lin and Siming Wang performed the follow-up and collected the patient data. All authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Declaration.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFujian Provincial Health Commission Middle-Young-Generation Talent Cultivation Project（2020GGB007）.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData is provided within \u0026nbsp;supplementary information files，and it could be gotten for free.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of the FuJian provincal Hospital..\u0026nbsp;This study was conducted in accordance with the Declaration of Helsinki, Written informed consent was obtained from each patient before receiving\u0026nbsp;the start of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1. Department of Gastrointestinal Surgery II, The First Hospital of Putian City Putian \u0026nbsp;Putian \u0026nbsp;Fujian 351100 China\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2.Department of Gastrointestinal Surgery, Fujian Medical University Provincial Clinical College \u0026nbsp;FuZhou \u0026nbsp; FuJiang 350007 China\u003c/p\u003e\n\u003cp\u003e3 Department of Internal Medicine, Fujian Medical University Provincial Clinical College \u0026nbsp; FuZhou \u0026nbsp;FuJiang 350007 China\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I and Jemal A. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2024; 74: 229-263.\u003c/li\u003e\n\u003cli\u003eBenedek Z, Boer ST, Bauer O, Sardi K, Todor A, Suciu N and Coros MF. An Overview of Five-Year Survival in Rectal Cancer in Relation to Lymph Node Status. 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The predictive value of serum NLR, SII, and OPNI for lymph node metastasis in breast cancer patients with internal mammary lymph nodes after thoracoscopic surgery. Open Life Sci 2024; 19: 20220763.\u003c/li\u003e\n\u003cli\u003eGaudioso P, Borsetto D, Polesel J, Tirelli G, Emanuelli E, Menegaldo A, Molteni G, Nicolai P, Tomasoni M, Montenegro C, Piazza C, Bossi P, Ciorba A, Canzi P, Giacomarra V, Giudici F, Fussey J and Boscolo-Rizzo P. Blood Markers Predicting Clinically Occult Lymph Node Metastasis in Head and Neck Squamous Cell Carcinoma. Orl 2024; 86: 32-40.\u003c/li\u003e\n\u003cli\u003eHouhong Wang1* HG, Amao Tang3 and YC. Neutrophil/lymphocyte ratio predicts lymph node metastasis in patients with gastric cancer. Am J Transl Res 2023;15(2):1412-1420 \u003c/li\u003e\n\u003cli\u003eAfify SM, Hassan G, Seno A and Seno M. Cancer-inducing niche: the force of cORonic inflammation. British Journal of Cancer 2022; 127: 193-201.\u003c/li\u003e\n\u003cli\u003eZhu K, Li P, Mo Y, Wang J, Jiang X, Ge J, Huang W, Liu Y, Tang Y, Gong Z, Liao Q, Li X, Li G, Xiong W, Zeng Z and Yu J. Neutrophils: Accomplices in metastasis. Cancer Letters 2020; 492: 11-20.\u003c/li\u003e\n\u003cli\u003eBian X, Yin S, Yang S, Jiang X, Wang J, Zhang M and Zhang L. Roles of platelets in tumor invasion and metastasis: A review. Heliyon 2022; 8: e12072.\u003c/li\u003e\n\u003cli\u003eLiu D, Heij LR, Czigany Z, Dahl E, Lang SA, Ulmer TF, Luedde T, Neumann UP and Bednarsch J. The role of tumor-infiltrating lymphocytes in cholangiocarcinoma. J Exp Clin Cancer Res 2022; 41: 127.\u003c/li\u003e\n\u003cli\u003eOrhan A, Khesrawi F, Tvilling Madsen M, Peuliche Vogelsang R, DoORn N, Kanstrup Fiehn AM and G\u0026ouml;genur I. Tumor-Infiltrating Lymphocytes as Biomarkers of Treatment Response and Long-Term Survival in Patients with Rectal Cancer: A Systematic Review and Meta-Analysis. 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Ann Surg Oncol 2012; 19: 2477-2484.\u003c/li\u003e\n\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":"bmc-gastroenterology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmge","sideBox":"Learn more about [BMC Gastroenterology](http://bmcgastroenterol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmge/default.aspx","title":"BMC Gastroenterology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Rectal cancer, PLR, NLR, Lymph node metastasis","lastPublishedDoi":"10.21203/rs.3.rs-5937143/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5937143/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction: \u003c/strong\u003eSystemic inflammatory response (SIR) indicators are predictive factors for \u0026nbsp;lymph node metastasis(LNM) in various cancers. This study aimed to investigate the assiociation of platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) with LNM in rectal cancer(RC). In addition, we sought to explore the clinicopathological factors of LNM.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe included 181 patients with RC admitted for surgery. NLR and PLR were calculated by collecting and analyzing preoperative blood samples, and their optimal cutoff values were analyzed using receiver operating characteristic (ROC). We examined the relationship between NLR or PLR and the clinicopathological characteristics of the patients, assessed their impact on LNM using ROC curve analysis. The risk factors for LNM were evaluated using both univariate and multivariate analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003ehigh PLR (H-PLR) group exhibited higher rates of perineural invasion (PNI) at 54.2% (83/153), lymphovascular invasion (LVI) at 51.6% (79 /153),more elevated CEA(66/153,43.1%) \u0026nbsp;and tumor deposits (TDs) at 14.4% (22/153). Additionally, this group demonstrated a greater incidence of LNM at 52.9% (81/153) and presented with a more advanced stage (stage II and stage III 124/153,81%). H-PLR were correlated with the presence of LNM, while H-NLR did not show it. The findings indicated that advanced T stage, high H-PLR, positive LVI, positive PNI, positive TDs, an increased number of cleared total lymph nodes (TLN), as well as elevated levels of carcinoembryonic antigen (CEA) and cancer antigen 19-9 (CA19-9) were associated with lymph node metastasis (LNM) according to univariate analysis. However, multivariate analysis revealed that only LVI and PNI were independent risk factors for LNM.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eH-PLR may be associated with unfavorable histopathological characteristics, positive LVI and PNI were independent risk factors for LNM in RC.\u003c/p\u003e","manuscriptTitle":"Predictive Value of Neutrophil-to-Lymphocyte Ratio(NLR) and Platelet-to-Lymphocyte Ratios (PLR) for Lymph Node Metastasis in Rectal Cancer Patients: a retrospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-01 07:40:56","doi":"10.21203/rs.3.rs-5937143/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-08T07:06:20+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"202275973521433036491215236870988429736","date":"2025-04-05T16:30:29+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-31T14:21:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"78897670715236449363569897070810338244","date":"2025-03-31T14:19:20+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-31T12:11:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-31T10:34:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Gastroenterology","date":"2025-03-30T11:59:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-gastroenterology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmge","sideBox":"Learn more about [BMC Gastroenterology](http://bmcgastroenterol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmge/default.aspx","title":"BMC Gastroenterology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"67556ae0-d9b7-4aa3-bfcf-0b36536dc45a","owner":[],"postedDate":"April 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-19T16:06:13+00:00","versionOfRecord":{"articleIdentity":"rs-5937143","link":"https://doi.org/10.1186/s12876-025-03960-6","journal":{"identity":"bmc-gastroenterology","isVorOnly":false,"title":"BMC Gastroenterology"},"publishedOn":"2025-05-12 15:57:32","publishedOnDateReadable":"May 12th, 2025"},"versionCreatedAt":"2025-04-01 07:40:56","video":"","vorDoi":"10.1186/s12876-025-03960-6","vorDoiUrl":"https://doi.org/10.1186/s12876-025-03960-6","workflowStages":[]},"version":"v1","identity":"rs-5937143","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5937143","identity":"rs-5937143","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}