Peripheral blood monocyte count impairs benefit from radiotherapy in patients with low gross tumor volume of nasopharyngeal carcinoma

Peripheral blood monocyte count impairs benefit from radiotherapy in patients with low gross tumor volume of nasopharyngeal carcinoma | 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 Article Peripheral blood monocyte count impairs benefit from radiotherapy in patients with low gross tumor volume of nasopharyngeal carcinoma Yun-Rui Song, Li-Na Yang, Dan Li, Ming-Yue Lu, De-Qing Liu, Hong-Lei Tu, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5259457/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background and purpose: The relationship between peripheral blood monocyte count and primary gross tumor volume with survival prognosis in newly diagnosed nasopharyngeal carcinoma(NPC) patients who received radiotherapy remains unclear. Therefore, We conducted a cohort study to assess the association of peripheral blood monocyte counts and primary gross tumor volume with survival outcomes in newly diagnosed non-metastatic NPC patients who received radiotherapy. Materials/Methods: We included newly diagnosed non-metastatic NPC patients who underwent radiotherapy in our hospital from January 2013 to December 2015. General clinical characteristics such as age, gender, ECOG score and tumor stage, peripheral blood monocyte count, lymphocyte count, white blood cell count (WBC), neutrophil count, radiotherapy technology, total radiotherapy days, gross tumor volume of nasopharyngeal carcinoma (GTVnx) and gross tumor volume of cervix node(GTVnd) of patients before radiotherapy, and whether chemotherapy was induced were recorded. The primary endpoint was overall survival, the secondary endpoint was progression-free survival. Univariate and multivariate COX regression were used to analyze the relationship among peripheral blood monocyte count, GTVnx, and survival outcome. Based on the independent risk factors for OS, we further divide patients into three different risk groups, and the differences in clinical and therapeutic indicators and survival outcomes between the three groups were analyzed using a one-way analysis of variance. Results: A total of 448 participants were included in the study, the median follow-up time was 74.3 months. Of these, 97 (21.7%) died. In the univariate and multivariate Cox regression analyses, peripheral blood monocyte count and GTVnx were independently associated with OS. The high monocyte count and GTVnx were associated with the poor OS and PFS. Survival curves significantly differed among patients in different risk groups for OS (p = 0.0008) and PFS (p = 0.0007). Besides, For every increase in monocyte unit count, the OS and PFS risks of patients in the low GTVnx group increased by 2.64 and 2.31 folds, respectively,. Conclusions: Peripheral blood monocyte count combined with GTVnx is a independent predictor for overall survival and progression free-survival in newly diagnosed non-metastatic NPC patients who received radiotherapy. The benefit of patients with GTVnx< 28.5cm 3 could be remarkably attenuated by the high monocyte count. Health sciences/Diseases Health sciences/Diseases/Cancer Peripheral blood monocyte count GTVnx nasopharyngeal carcinoma radiotherapy overall survival Figures Figure 1 Figure 2 Introduction Nasopharyngeal carcinoma (NPC) is one of the head and neck malignancies, which arises in the upper lining epithelium of the nasopharynx and is often observed at the pharyngeal recess [ 1 ] . According to the International Agency for Research on Cancer, in 2020, there were about 133,354 new cases and 80,008 new deaths of nasopharyngeal carcinoma, accounting for only 0.7% of all cancers diagnosed and 0.8% of all cancers deaths [ 2 ] . Although the incidence and mortality of nasopharyngeal carcinoma are not high compared with other cancers, it has a remarkable geographical distribution, > 70% of new cases are in East and Southeast Asia. It is well known that radiotherapy is the standard treatment for this malignancy, because of the high sensitivity to ionizing radiation and anatomical location [ 1 ] . Combined with the current standard chemoradiotherapy regimens, the survival of nasopharyngeal carcinoma has been greatly improved, according to reports, the estimated 5-year overall survival (OS) after radiotherapy for stage I-II NPC is 98% and 92%, local failure-free survival (FFS) is 98% and 94%, and distant FFS is 98% and 91% [ 3 ] . Unfortunately, although the use of concurrent chemo-radiotherapy (CCRT) as the standard treatment for locally advanced nasopharyngeal carcinoma has significantly improved survival, the results for locally advanced disease are not satisfactory [ 4 ] . Therefore, an efficient, inexpensive, and valuable biochemical index is needed to predict the prognosis of patients with NPC and to promote individualized treatment to provide a better prognosis for patients. Inflammatory response plays an important role in the occurrence and development of cancer, and it has even been reported that inflammatory cells have better prognostic importance for tumors compared with histopathological results [ 5 ] . In previous studies, many inflammatory markers such as lymphocytes, neutrophils, neutrophil to lymphocyte ratio (NLR), and lymphocyte to monocyte ratio (LMR) are associated with cancer prognosis [ 6 , 7 ] . Monocytes, which can differentiate into macrophages and myeloid dendritic cells, are key immune cells in the inflammatory response [ 8 ] . The roles of monocytes are complicated, they act as a bridge between innate and adaptive immune responses, influencing the tumor microenvironment by inducing increased immune tolerance, angiogenesis, and tumor cell dissemination through multiple mechanisms [ 9 ] . It has been reported to be independently associated with the prognosis of various tumors, such as non-small cell lung cancer, squamous cell carcinoma of the head and neck, prostate cancer, and metastatic nasopharyngeal carcinoma [ 10 – 13 ] . Gross tumor volume(GTV) is an intuitive quantitative reflection of tumor burden, the longer the malignancy occurs, the larger the GTV, the wider the anatomical range of possible invasion, and the worse the therapeutic effect. Several studies have shown that GTV is an important prognostic indicator of malignant tumors [ 14 – 15 ] . GTV included gross tumor volume of nasopharyngeal carcinoma (GTVnx) and gross tumor volume of cervix node(GTVnd). Sze WM et al [ 16 ] confirmed that every 1 cm 3 increase in nasopharyngeal carcinoma volume caused a 1% increased risk of local recurrence. The purpose of the study is to determine the prognostic significance of pre-treatment peripheral blood monocytes count and GTVnx in newly diagnosed non-metastatic NPC patients treated with radiotherapy. Materials and methods Study design and participants We included 448 newly diagnosed non-metastatic nasopharyngeal carcinoma(NPC) patients who received radiotherapy at Radiation Oncology Center, Chongqing University Cancer Hospital from January 2013 to December 2015 in this study. Inclusion criteria: (1) Patients who are first diagnosed as NPC by pathology and without distant metastasis. (2) Age Over 18 and under 80. (3) ECOG Score ≤ 2. (4) Routine blood test was performed one week before radiotherapy. (5) No complications that seriously affect peripheral blood cells (i.e., acute or chronic infection, hematological system diseases, any immune deficiency disease, and diseases requiring treatment with glucocorticoid replacement). (6) The radiotherapy plan was clearly filled out, the total duration of radiotherapy did not exceed 70 days, and the total radiotherapy dose in the nasopharyngeal region was≥ 66 Gy. Informed consent was obtained from all participants at baseline and all procedures were performed in accordance with our local guidelines and clinical regulations. The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of The Chongqing University Cancer Hospital (No. CZLLYJ0252). Data collection and laboratory measurements Medical and social history were collected and recorded. Include age, gender, smoking, drinking, pre-treatment Epstein-Barr virus DNA, Charlson Comorbidity Index(CCI), Eastern Cooperative Oncology Group (ECOG) score, TNM stage (based on the American Joint Committee on Cancer (AJCC) 7th edition), induction chemotherapy(no chemotherapy was performed within 3 weeks before the peripheral blood cells counts were recorded), radiotherapy parameters (total duration of radiotherapy, GTVnx and GTVnd (cm3), body Dmean(Gy), bone Dmean(Gy), and radiation technology). After fasting for at least 8 hours overnight, all patients underwent fasting vein blood collection the next morning and were sent to the laboratory within one hour after blood collection. The blood routine was tested by an automatic hematology analyzer. Baseline peripheral blood cell counts including peripheral blood monocyte count, lymphocyte count(LC), white blood cell count (WBC), hemoglobin(Hgb), and neutrophil count were measured and recorded. LMR and NLR are defined as the ratio of lymphocyte count to monocyte count and neutrophil count to lymphocyte count. Outcome and follow-up The primary endpoint of this study was the overall survival (OS), which was defined as the time from the first day of radiotherapy to all-cause death or the last follow-up visit. The secondary endpoint was progression-free survival (PFS), which calculated the time from the start of treatment to the first failure in any part or death for any reason or final follow-up. Patients were examined every 3 months for the first 2 years after completing treatment, every 6 months for the third to fifth years, and annually after 5 years. Survival information was collected from patients' hospital records and periodic telephone follow-up records. Statistical analysis In this study, SPSS 22.0 statistical software was used for data analysis. The measurement data was represented by mean ± standard deviation (SD), and the counting data were represented by number and percentage. An Independent sample t-test or Pearson Chi-square test was used for the comparison between the two groups. Comparison among three groups using one-way analysis of variance. Then Kaplan-Meier method was used to draw the survival curves. Univariate Cox regression analyses were used to evaluate the correlation between parameters and OS. Multivariate Cox regression analyses were used for the evaluation of OS and monocyte count, GTVnx. Two-tailed p values <0.05 were considered statistically significant. Results A total of 448 NPC patients were included in the final analysis. Among them, 319 (71.2%) were males, 416 (92.9%) patients underwent intensity-modulated radiation therapy (IMRT) and 32 (7.1%) patients underwent three-dimensional conformal radiation therapy (3D-CRT). There were 428 (95.5%) patients with ECOG score 0–1 and 32 (4.5%) patients with ECOG score 2. The mean age of all NPC patients was 51 years, 425 of whom underwent induction chemotherapy before, and 110 (24.6%), 233 (52%), and 105 (23.4%) patients with comprehensive stage II, III, and IV, respectively. The median follow-up time was 74.3 months (interquartile range 24.7–87.8). At the last follow-up, 97 people (21.7%) had died from all causes. Radiotherapy parameters for all patients were as follows: mean total radiotherapy days were 47 days, mean total radiotherapy dose was 71Gy, mean body Dmean (Gy) radiotherapy dose was 19.5Gy, mean GTVnx was 37.6cc, GTVnd was 28.6cc, and mean bone dose was 21.3Gy. Baseline routine blood parameters were as follows: mean blood white blood cell count of 5.71, mean monocyte count of 0.31, mean lymphocyte count of 1.51, mean lymphocyte count to monocyte count ratio of 13.5, mean Hemoglobin is 135, mean neutrophil count is 3.77 (Table 1 ). In the univariate Cox regression analysis (Table 2 ), parameters such as monocyte count [HR 2.30, 95%CI (1.13–4.69)], age[1.03(1.01–1.05)], GTVnx[1.01(1.00-1.01)], CCI[1.28(1.09–1.50)], NLR[1.07(1.01–1.13)], Hgb[0.99(0.97–0.99)] were shown to be significantly associated with OS. In the multivariate Cox regression analyses (Table 2 ), monocyte count[2.14(1.02–4.48)] and GTVnx[1.01(1.00-1.02)] were independently associated with OS. Compared to patients in the low monocyte count group(LG), patients in the high monocyte count group(HG) had a 2.14-fold higher risk of death compared with LG. To further confirm the predictive effect of monocyte count and GTVnx on OS and PFS, we divided patients into low and high groups based on baseline median monocyte count and GTVnx. As shown in Fig. 1 , the high monocyte count group and high GTVnx group were associated with poor OS and PFS. In the two-independent sample T-test, there were no statistical differences in other clinical parameters between the two groups except baseline monocyte count, GTVnx, WBC, LMR, and NLR (Table 3 ). The clinical characteristics between the HG and LG were compared, and there were no statistical differences in age, sex, pre-treatment Epstein-Barr virus DNA, ECOG score, tumor stage, smoking history, drinking history, CCI, radiotherapy method, total radiotherapy days, whether chemotherapy was induced, radiotherapy and hematology indexes between the two groups. Based on the independent risk factors (monocyte count ≥ 0.29×10 9 /L (median), GTVnx ≥ 28.5cm 3 (median)) for OS, we further divide patients into three different risk groups: low-risk group (with < 1 risk factor), medium-risk group (with 1 risk factors), and high-risk group (with 2 risk factors). Survival curves were significantly different among patients in different risk groups for OS (p = 0.0008) and PFS (p = 0.0007) (Fig. 2 ). The characteristics of patients in the different risk groups are shown in Table 4 . As shown in Table 5 , patients in the GTVnx low group had a 2.64-fold and 2.31-fold increased risk of OS and PFS for every increase in the unit count of monocytes, and in the GTVnx high group had a 1.94-fold and 1.09-fold increase. In the low monocyte count group, the risk of OS and PFS increased by 1.01 times per unit volume increase of GTVnx, and in the high monocyte count group, GTVnx increases the risk of OS and PFS by 1.00 times per unit volume increase (Supplementary Table 1). Altogether, the benefit of patients with GTVnx < 28.5cm 3 could be remarkably attenuated by the high monocyte count. Discussion Although the role of systemic inflammation in the development of cancer has been investigated in many studies [ 17 ] , the main mechanism is still unclear. We all know that inflammation can promote the mobilization of monocytes from bone marrow to peripheral blood and further differentiation into tissue macrophages [ 8 ] . Macrophages then play a role in stimulating angiogenesis, enhancing tumor cell migration and invasion, and inhibiting anti-tumor immunity in the development of tumors [ 18 ] . GTV is a potential biological reflection of tumor burden, and is associated with the survival of tumor patients [ 19 ] . Understanding the relationship between different monocyte counts and the prognosis of tumors after radiotherapy and chemotherapy under different tumor loads is conducive to the formulation of individualized treatment decisions. In this study, it’s confirmed that pre-treatment monocyte count and GTVnx are independent predictors of survival in newly diagnosed non-metastatic nasopharyngeal carcinoma patients undergoing radiotherapy. The high monocyte count(≥ 0.29×10 9 /L) and high GTVnx(GTVnx ≥ 28.5cm 3 ) were associated with poor OS and PFS. After adjusting for a variety of confounding factors, the high monocyte count group had a 2.14-fold higher risk of death compared with the low monocyte count group. Besides, For every increase in monocyte unit count, the OS and PFS risks of patients in the low and high GTVnx groups increased by 2.64 times, 2.31 times, 1.94 times, and 1.09 times, respectively. A large number of previous studies have shown that the increase of peripheral blood monocytes is associated with poor survival of various cancers [10–13,20−22] . This is consistent with the results of our study in which NPC patients with higher baseline peripheral blood monocyte counts had worse survival outcomes than those with lower baseline peripheral blood monocyte counts. This study further verified that GTVnx and systemic inflammation, including monocytes, are important factors affecting the prognosis of NPC patients. Monocytes can secrete various proinflammatory cytokines, which have been associated with shorter survival and worse prognosis in malignancies [ 9 ] . Moreover, monocytes can also promote tumor growth and angiogenesis by releasing VEGF, epidermal growth factor (EGF), and tumor necrosis factor-α (TNF-α) [ 23 ] . However, the specific mechanism of monocytes in the development of malignancy is still not fully understood. A better understanding of the process of monocyte recruitment may lead to the development of new therapies to control the number and distribution of monocytes, thereby enhancing the therapeutic efficacy of malignancies and improving survival. When the tumor volume is large, it may lead to changes in the tumor microenvironment, and the blood supply is difficult to reach the center of the tumor, resulting in obvious hypoxic tissue in this area, which is less responsive to radiotherapy and chemotherapy. In addition, the anatomical structure of nasopharyngeal carcinoma is complex, the wider the range of tumor invasion, the closer the distance between the tumor and the optic nerve, spinal cord, and brainstem, the greater the difficulty of radiotherapy planning, resulting in decreased efficacy and poor prognosis. As one of the types of leukocyte, monocytes can be combined with GTVnx as a prognostic indicator of nasopharyngeal carcinoma due to its convenient, rapid, and low-cost detection. The results of this study showed that GTVnx ≥ 28.5cm3 and monocyte count ≥ 0.29×109/L were adverse factors for PFS and OS. In patients with GTVnx < 28.5cm3, increasing monocyte count will significantly increase the risk of poor survival and disease progression. Clinicians should be alert to the risk of local recurrence or distant metastasis and develop individualized treatment plans ( such as increasing adjuvant chemotherapy, combined immunotherapy, etc. ) for patients with nasopharyngeal carcinoma who meet these requirements according to specific conditions. Some limitations need to be mentioned. Due to the lack of post-treatment monocyte count data in this study, the relationship between post-treatment monocyte count and survival of NPC patients has not been revealed. Furthermore, this study was conducted in one medical center, so the selection bias was inevitable. Therefore, multi-center, large-sample prospective studies are needed to further confirm our findings. Conclusions In conclusion, peripheral blood monocyte count combined with gross tumor volume of nasopharyngeal carcinoma can independently predict the overall survival and progression free-survival in newly diagnosed non-metastatic NPC patients who received radiotherapy. The benefit of patients with GTVnx < 28.5cm 3 could be remarkably attenuated by the high monocyte count. These findings should be verified in more prospective studies conducted among different populations. Declarations Author Contribution Yun-rui Song.Li-Na Yang. and Dan Li.Jiang-Dong Sui. wrote the main manuscript text and Yun-rui Song.Ming-Yue Lu. De-Qing Liu. prepared Table 1-5 and figures 1-2. Hong-Lei Tu provides funding support. All authors reviewed the manuscript. Data Availability The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. References Chen Y-P, Chan ATC, Le Q-T et al. Nasopharyngeal carcinoma. The Lancet 2019; 394: 64-80. 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Tables Table1: Clinical characteristics of the total Nasopharyngeal Carcinoma patients Characteristics Values Age, years 51.19 ±10.15 Male 319(71.2) IMRT 416(92.9) 3D-CRT 32(7.1) ECOG 0 36(8.0) 1 392(87.5) 2 20(4.5) Induction chemotherapy 425(94.9) T-stage 1 40(8.9) 2 208(46.4) 3 127(28.3) 4 73(16.3) N-stage 0 36(8.0) 1 183(40.8) 2 190(42.4) 3 39(8.7) Clinical stage II 110(24.6) III 233(52.0) IVa Pre-treatment Epstein-Barr virus DNA Positive Negative Unknown 105(23.4) 65(14.5) 110(24.6) 273(60.9) Total radiotherapy days 46.70 ±5.75 Total radiotherapy dose(Gy) 70.96 ±1.49 Body Dmean(Gy) 19.49 ±3.34 GTVnx 37.60 ±29.62 GTVnd 28.63 ±38.87 Bone Dmean(Gy) 21.30 ±15.49 CCI 3.04 ±1.10 OS time(m) PFS time(m) 59.46 ±33.83 54.95 ±35.81 WBC 5.71 ±2.17 Monocyte 0.31 ±0.25 Lymphocyte 1.51 ±0.54 LMR(Lymphocyte to monocyte ratio) NLR(Neutrophil to Lymphocyte ratio) 13.49 ±23.01 2.87±2.28 Haemoglobin 135.13 ±16.78 Neutrophil 3.77 ±1.92 Smoking 199(44.4) Drinking 115(25.7) Values are mean±SD, n(%). Table2：Univariate and Multivariable Cox regression analysis Variables Univariate analysis Multivariable analysis Hazard ratio (95% CI) P Hazard ratio (95% CI) P Monocyte 2.30(1.13-4.69) 0.022 2.14(1.02-4.48) 0.044 Age 1.03(1.01-1.05) 0.008 1.02(0.98-1.05) 0.272 Male Radiotherapy technique Induction chemotherapy Concurrent chemoradiotherapy Pre-treatment Epstein-Barr virus DNA 0.83(0.53-1.31) 1.20(0.49-2.97) 1.12(0.49-2.57) 0.41(0.06-2.94) 1.65(0.94-2.90) 0.417 0.686 0.784 0.299 0.081 Total radiotherapy days Total radiotherapy dose(Gy) 1.02(0.99-1.06) 1.11(0.96-1.27) 0.211 0.161 BodyDmean（Gy） 1.05(0.99-1.12) 0.173 GTVnx 1.01(1.00-1.01) 0.021 1.01(1.00-1.02) 0.033 Bone Dmean（Gy） 1.00(0.99-1.01) 0.380 CCI 1.28(1.09-1.50) 0.002 1.12(0.86-1.45) 0.399 Smoking 1.34(0.90-2.00) 0.149 Drinking 1.41(0.92-2.16) 0.116 Lymphocyte 0.99(0.98-1.01) 0.220 NLR 1.07(1.01-1.13) 0.043 1.05(0.99-1.12) 0.077 Haemoglobin 0.99(0.97-0.99) 0.017 0.99(0.98-1.01) 0.228 Table 3: Comparison of clinical characteristics between two monocyte count groups monocyte-low（223） monocyte-high（225） P value Age, years 50.85±10.21 51.53 ±10.11 0.959 Male 161(72.2) 158(70.2) 0.644 ECOG 0.670 0 18(8.1) 18(8.0) 1 197(88.3) 195(86.7) 2 8(3.6) 12(5.3) Induction chemotherapy 216(96.9) 209(92.9) 0.057 T-stage 0.500 1 23(10.3) 17(7.6) 2 105(47.1) 103(45.8) 3 57(25.6) 70(31.1) 4 38(17.0) 35(15.6) N-stage 0.336 0 13(5.8) 23(10.2) 1 93(41.7) 90(40.0) 2 99(44.4) 91(40.4) 3 18(8.1) 21(9.3) Clinical stage 0.752 2 57(25.6) 53(23.5) 3 112(50.2) 121(53.8) 4 Pre-treatment Epstein-Barr virus DNA(Positive) 54(24.2) 30(6.7) 51(22.7) 35(7.8) 0.408 Total radiotherapy days Total radiotherapy dose(Gy) 46.52±5.81 70.96±1.51 46.87 ±5.71 70.95±1.47 0.766 0.943 Body Dmean（Gy） 20.00±3.19 18.99 ±3.42 0.501 GTVnx 35.78 ±26.24 39.39 ±32.58 0.005 GTVnd 28.79 ±39.00 28.48 ±38.83 0.692 Bone Dmean（Gy） 21.92 ±15.41 20.68 ±15.58 0.843 CCI 3.01 ±1.07 3.08 ±1.14 0.350 WBC 5.23 ±1.92 6.19 ±2.30 0.005 Monocyte 0.13 ±0.09 0.49 ±0.22 0.000 Lymphocyte 1.39 ±0.50 1.62 ±0.55 0.233 LMR NLR 23.42 ±29.49 3.07±2.71 3.69 ±1.47 2.66±1.73 0.000 0.000 Haemoglobin 135.35 ±16.05 134.91 ±17.50 0.254 Neutrophil 3.60 ±1.88 3.93 ±1.94 0.424 Smoking 94(42.5) 106(47.1) 0.335 Drinking 57(25.7) 58(25.8) 0.936 Values are mean±SD, n(%). Table 4: Characteristics of patients in different risk groups Low-risk group （117） Medium-risk group(215) High-risk group （116） P value Age, years 51.02±9.59 50.96±10.51 51.66±10.02 0.827 Male 78(67.2) 155(70.9) 86(74.1) 0.178 ECOG 0.052 0 13(11.2) 17(7.9) 6(5.2) 1 99(85.3) 189(87.9) 103(88.8) 2 4(3.5) 9(4.2) 7(6.0) Induction chemotherapy 111(95.6) 203(94.4) 111(95.6) 0.662 T-stage 0.000 1 18(15.5) 20(9.3) 1(0.8) 2 75(64.7) 103(47.9) 30(25.9) 3 14(12.1) 58(26.9) 56(48.3) 4 9(7.8) 34(15.8) 29(25.0) N-stage 0.610 0 7(6.0) 19(8.8) 10(8.6) 1 55(47.4) 85(39.5) 43(37.1) 2 47(40.5) 92(42.8) 51(44.0) 3 7(6.0) 19(8.8) 12(10.3) Clinical stage 0.000 2 48(41.4) 51(23.7) 11(9.5) 3 51(44.0) 116(54.0) 66(56.9) 4 Pre-treatment Epstein-Barr virus DNA(Positive) 17(14.6) 12(10.3) 48(22.3) 24(11.2) 39(33.6) 29(25) 0.151 Total radiotherapy days Total radiotherapy dose(Gy) 45.59±5.20 70.74±1.75 46.90±5.82 71.03±1.29 47.48 ±6.03 71.04±1.55 0.034 0.189 Body Dmean（Gy） 19.19±2.95 19.78±3.35 19.25 ±3.66 0.203 GTVnx 17.15 ±7.16 36.19 ±26.44 60.65 ±33.01 0.000 GTVnd 22.90 ±26.31 30.34 ±40.40 31.51 ±46.17 0.201 Bone Dmean（Gy） 19.96 ±3.54 21.78 ±15.68 21.72 ±21.41 0.564 CCI 2.96 ±1.13 3.07 ±1.08 3.08 ±1.13 0.625 WBC 5.40 ±1.92 5.52 ±2.15 6.41 ±2.31 0.000 Monocyte 0.16 ±0.13 0.29 ±0.23 0.49 ±0.25 0.000 Lymphocyte 1.42 ±0.48 1.49 ±0.54 1.61 ±0.57 0.019 LMR NLR 22.36 ±30.79 3.01 ±2.59 13.96 ±22.37 2.86 ±2.43 3.80 ±1.97 2.77 ±1.56 0.000 0.712 Haemoglobin 136.42 ±15.13 135.08 ±16.65 134.02 ±18.58 0.550 Neutrophil 3.65 ±1.97 3.66 ±1.88 4.10 ±1.91 0.102 Smoking 38(32.8) 99(46.0) 62(53.4) 0.018 Drinking 23(19.8) 57(26.5) 35(30.2) 0.237 Values are mean±SD, n(%). Table 5: The effect of monocyte count per unit increase on OS and PFS in different groups Risk groups OS PFS HR (95% CI) P HR (95% CI) P GTVnx-low 2.64(0.72-9.63) 0.142 2.31(1.04-5.12) 0.040 GTVnx-high 1.94(1.25-3.00) 0.003 1.09(0.72-1.64) 0.694 Additional Declarations No competing interests reported. Supplementary Files SupplementaryTable.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies 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-5259457","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":375492289,"identity":"856679e3-150e-4945-8a1f-a78e8b3966d1","order_by":0,"name":"Yun-Rui Song","email":"","orcid":"","institution":"Chongqing University Cancer Hospital,School of Medicine, Chongqing University,","correspondingAuthor":false,"prefix":"","firstName":"Yun-Rui","middleName":"","lastName":"Song","suffix":""},{"id":375492290,"identity":"ab47ae55-6c0e-4234-927b-8b30e8088322","order_by":1,"name":"Li-Na Yang","email":"","orcid":"","institution":"Chongqing University Cancer Hospital,School of Medicine, Chongqing University,","correspondingAuthor":false,"prefix":"","firstName":"Li-Na","middleName":"","lastName":"Yang","suffix":""},{"id":375492291,"identity":"2bd6259c-7a2f-435b-969b-23a9fbec6f40","order_by":2,"name":"Dan Li","email":"","orcid":"","institution":"Chongqing University Cancer Hospital,School of Medicine, Chongqing University,","correspondingAuthor":false,"prefix":"","firstName":"Dan","middleName":"","lastName":"Li","suffix":""},{"id":375492292,"identity":"065b44da-2262-4634-9306-2f4f7af1c224","order_by":3,"name":"Ming-Yue Lu","email":"","orcid":"","institution":"Chongqing University Cancer Hospital,School of Medicine, Chongqing University,","correspondingAuthor":false,"prefix":"","firstName":"Ming-Yue","middleName":"","lastName":"Lu","suffix":""},{"id":375492293,"identity":"09a47c5c-3b9c-4704-92a4-7b195eaa64e9","order_by":4,"name":"De-Qing Liu","email":"","orcid":"","institution":"Chongqing University Cancer Hospital,School of Medicine, Chongqing University,","correspondingAuthor":false,"prefix":"","firstName":"De-Qing","middleName":"","lastName":"Liu","suffix":""},{"id":375492294,"identity":"f740f51e-98c4-488a-b2fd-752be9b6783e","order_by":5,"name":"Hong-Lei Tu","email":"","orcid":"","institution":"Chongqing University Cancer Hospital,School of Medicine, Chongqing University,","correspondingAuthor":false,"prefix":"","firstName":"Hong-Lei","middleName":"","lastName":"Tu","suffix":""},{"id":375492295,"identity":"3aae7782-5956-494d-878f-7f725cea5631","order_by":6,"name":"Jiang-Dong sui","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIiWNgGAWjYBACxmYQyQblJVRAaAkStJwhQgsEwLQwthGhhbmd+dnDL2U2efIO7M8kHs6zk91wgPngbR4GuzzcDmMzN5Y5l1ZseIDHTCJxW7LxhgNsydY8DMnFePxiJi3ZdjhxYwMPG1DLgcQNQL3SPAwHEhtwamH/BtUCdFjiHJAW/m8EtPCYSX4EapnPwAB0WAPYFjZCWsqkGc6lJW5g5jG2SDiWbDzzMJux5RyDZJxaDPuPb5P8UWaTOL+9/eHNHzV2sn3Hmx/eeFNhh1sLUIKZB8gwOAy1toEZRBngUA8E8iBVP0CMBpgW3IpHwSgYBaNghAIAVUFVDMStLdgAAAAASUVORK5CYII=","orcid":"","institution":"Chongqing University Cancer Hospital,School of Medicine, Chongqing University,","correspondingAuthor":true,"prefix":"","firstName":"Jiang-Dong","middleName":"","lastName":"sui","suffix":""},{"id":375492296,"identity":"fca0e5ee-e5b1-49a7-9b30-d9a5d5f3cc05","order_by":7,"name":"Yue Xie","email":"","orcid":"","institution":"Chongqing University Cancer Hospital,School of Medicine, Chongqing University,","correspondingAuthor":false,"prefix":"","firstName":"Yue","middleName":"","lastName":"Xie","suffix":""},{"id":375492297,"identity":"cef64bc9-faf5-4f8e-a493-66eb87d66e71","order_by":8,"name":"Ying Wang","email":"","orcid":"","institution":"Chongqing University Cancer Hospital,School of Medicine, Chongqing University,","correspondingAuthor":false,"prefix":"","firstName":"Ying","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-10-14 08:38:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5259457/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5259457/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":70035697,"identity":"c3f71c45-28c8-4a6f-902b-0d510c50eac7","added_by":"auto","created_at":"2024-11-27 17:14:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":81447,"visible":true,"origin":"","legend":"\u003cp\u003eThe Kaplan–Meier survival curves of PBMC (A), GTVnx (B) based on the overall survival (OS) and progression-free survival (PFS) in NPC patients.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5259457/v1/77d969a2f3491bfebc94d99c.png"},{"id":70035699,"identity":"890e4ee5-3fff-4c1d-a657-34ca903fbc8c","added_by":"auto","created_at":"2024-11-27 17:14:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":97214,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier curves of overall survival (A) and progression free-survival (B) of patients in different risk groups.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5259457/v1/d0fa13b83709ec8e52f0fff4.png"},{"id":70556625,"identity":"0ec9db3d-52a9-4abe-a1c4-8970bb9b2292","added_by":"auto","created_at":"2024-12-04 11:08:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":825826,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5259457/v1/8eb519ed-0160-42e4-a825-a365182b65a1.pdf"},{"id":70035696,"identity":"abfc41da-549b-48ac-8032-35bec01ae723","added_by":"auto","created_at":"2024-11-27 17:14:10","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":11693,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable.docx","url":"https://assets-eu.researchsquare.com/files/rs-5259457/v1/c9ad68991141f738da3b021a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Peripheral blood monocyte count impairs benefit from radiotherapy in patients with low gross tumor volume of nasopharyngeal carcinoma","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNasopharyngeal carcinoma (NPC) is one of the head and neck malignancies, which arises in the upper lining epithelium of the nasopharynx and is often observed at the pharyngeal recess\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. According to the International Agency for Research on Cancer, in 2020, there were about 133,354 new cases and 80,008 new deaths of nasopharyngeal carcinoma, accounting for only 0.7% of all cancers diagnosed and 0.8% of all cancers deaths \u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Although the incidence and mortality of nasopharyngeal carcinoma are not high compared with other cancers, it has a remarkable geographical distribution, \u0026gt;\u0026thinsp;70% of new cases are in East and Southeast Asia. It is well known that radiotherapy is the standard treatment for this malignancy, because of the high sensitivity to ionizing radiation and anatomical location\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Combined with the current standard chemoradiotherapy regimens, the survival of nasopharyngeal carcinoma has been greatly improved, according to reports, the estimated 5-year overall survival (OS) after radiotherapy for stage I-II NPC is 98% and 92%, local failure-free survival (FFS) is 98% and 94%, and distant FFS is 98% and 91%\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eUnfortunately, although the use of concurrent chemo-radiotherapy (CCRT) as the standard treatment for locally advanced nasopharyngeal carcinoma has significantly improved survival, the results for locally advanced disease are not satisfactory \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Therefore, an efficient, inexpensive, and valuable biochemical index is needed to predict the prognosis of patients with NPC and to promote individualized treatment to provide a better prognosis for patients. Inflammatory response plays an important role in the occurrence and development of cancer, and it has even been reported that inflammatory cells have better prognostic importance for tumors compared with histopathological results\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. In previous studies, many inflammatory markers such as lymphocytes, neutrophils, neutrophil to lymphocyte ratio (NLR), and lymphocyte to monocyte ratio (LMR) are associated with cancer prognosis\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMonocytes, which can differentiate into macrophages and myeloid dendritic cells, are key immune cells in the inflammatory response\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. The roles of monocytes are complicated, they act as a bridge between innate and adaptive immune responses, influencing the tumor microenvironment by inducing increased immune tolerance, angiogenesis, and tumor cell dissemination through multiple mechanisms\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. It has been reported to be independently associated with the prognosis of various tumors, such as non-small cell lung cancer, squamous cell carcinoma of the head and neck, prostate cancer, and metastatic nasopharyngeal carcinoma\u003csup\u003e[\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGross tumor volume(GTV) is an intuitive quantitative reflection of tumor burden, the longer the malignancy occurs, the larger the GTV, the wider the anatomical range of possible invasion, and the worse the therapeutic effect. Several studies have shown that GTV is an important prognostic indicator of malignant tumors\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. GTV included gross tumor volume of nasopharyngeal carcinoma (GTVnx) and gross tumor volume of cervix node(GTVnd). Sze WM et al \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e confirmed that every 1 cm\u003csup\u003e3\u003c/sup\u003e increase in nasopharyngeal carcinoma volume caused a 1% increased risk of local recurrence.\u003c/p\u003e \u003cp\u003eThe purpose of the study is to determine the prognostic significance of pre-treatment peripheral blood monocytes count and GTVnx in newly diagnosed non-metastatic NPC patients treated with radiotherapy.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003eStudy design and participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe included 448 newly diagnosed non-metastatic nasopharyngeal carcinoma(NPC) patients who received radiotherapy at Radiation Oncology Center, Chongqing University Cancer Hospital from January 2013 to December 2015 in this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInclusion criteria: (1) Patients who are first diagnosed as NPC by pathology and without distant metastasis. (2) Age Over 18 and under 80. (3) ECOG Score ≤ 2. (4) Routine blood test was performed one week before radiotherapy. (5) No complications that seriously affect peripheral blood cells (i.e., acute or chronic infection, hematological system diseases, any immune deficiency disease, and diseases requiring treatment with glucocorticoid replacement). (6) The radiotherapy plan was clearly filled out, the total duration of radiotherapy did not exceed 70 days, and the total radiotherapy dose in the nasopharyngeal region was≥ 66 Gy.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all participants at baseline and all procedures were performed in accordance with our local guidelines and clinical regulations. The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of The Chongqing University Cancer Hospital (No. CZLLYJ0252).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection and laboratory measurements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMedical and social history were collected and recorded. Include age, gender, smoking, drinking, pre-treatment Epstein-Barr virus DNA, Charlson Comorbidity Index(CCI), Eastern Cooperative Oncology Group (ECOG) score, TNM stage (based on the American Joint Committee on Cancer (AJCC)\u0026nbsp;7th edition), induction chemotherapy(no chemotherapy was performed within 3 weeks before the peripheral blood cells counts were recorded), radiotherapy parameters (total duration of radiotherapy, GTVnx and GTVnd (cm3), body Dmean(Gy), bone Dmean(Gy), and radiation technology). After fasting for at least 8 hours overnight, all patients underwent fasting vein blood collection the next morning and were sent to the laboratory within one hour after blood collection. The blood routine was tested by an automatic hematology analyzer. Baseline peripheral blood cell counts including peripheral blood monocyte count, lymphocyte count(LC), white blood cell count (WBC), hemoglobin(Hgb), and neutrophil count were measured and recorded. LMR and NLR are defined as the ratio of lymphocyte count to monocyte count\u0026nbsp;and neutrophil count to lymphocyte count.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOutcome and follow-up\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe primary endpoint of this study was the overall survival (OS), which was defined as the time from the first day of radiotherapy to all-cause death or the last follow-up visit. The secondary endpoint was progression-free survival (PFS), which calculated the time from the start of treatment to the first failure in any part or death for any reason or final follow-up. Patients were examined every 3 months for the first 2 years after completing treatment, every 6 months for the third to fifth years, and annually after 5 years. Survival information was collected from patients' hospital records and periodic telephone follow-up records.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, SPSS 22.0 statistical software was used for data analysis. The measurement data was represented by mean ± standard deviation (SD), and the counting data were represented by number and percentage. An Independent sample t-test or Pearson Chi-square test was used for the comparison between the two groups. Comparison among three groups using one-way analysis of variance. Then Kaplan-Meier method was used to draw the survival curves. Univariate Cox regression analyses were used to evaluate the correlation between parameters and OS. Multivariate Cox regression analyses were used for the evaluation of OS and monocyte count, GTVnx. Two-tailed p values \u0026lt;0.05 were considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 448 NPC patients were included in the final analysis. Among them, 319 (71.2%) were males, 416 (92.9%) patients underwent intensity-modulated radiation therapy (IMRT) and 32 (7.1%) patients underwent three-dimensional conformal radiation therapy (3D-CRT). There were 428 (95.5%) patients with ECOG score 0\u0026ndash;1 and 32 (4.5%) patients with ECOG score 2. The mean age of all NPC patients was 51 years, 425 of whom underwent induction chemotherapy before, and 110 (24.6%), 233 (52%), and 105 (23.4%) patients with comprehensive stage II, III, and IV, respectively. The median follow-up time was 74.3 months (interquartile range 24.7\u0026ndash;87.8). At the last follow-up, 97 people (21.7%) had died from all causes. Radiotherapy parameters for all patients were as follows: mean total radiotherapy days were 47 days, mean total radiotherapy dose was 71Gy, mean body Dmean (Gy) radiotherapy dose was 19.5Gy, mean GTVnx was 37.6cc, GTVnd was 28.6cc, and mean bone dose was 21.3Gy. Baseline routine blood parameters were as follows: mean blood white blood cell count of 5.71, mean monocyte count of 0.31, mean lymphocyte count of 1.51, mean lymphocyte count to monocyte count ratio of 13.5, mean Hemoglobin is 135, mean neutrophil count is 3.77 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the univariate Cox regression analysis (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), parameters such as monocyte count [HR 2.30, 95%CI (1.13\u0026ndash;4.69)], age[1.03(1.01\u0026ndash;1.05)], GTVnx[1.01(1.00-1.01)], CCI[1.28(1.09\u0026ndash;1.50)], NLR[1.07(1.01\u0026ndash;1.13)], Hgb[0.99(0.97\u0026ndash;0.99)] were shown to be significantly associated with OS. In the multivariate Cox regression analyses (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), monocyte count[2.14(1.02\u0026ndash;4.48)] and GTVnx[1.01(1.00-1.02)] were independently associated with OS. Compared to patients in the low monocyte count group(LG), patients in the high monocyte count group(HG) had a 2.14-fold higher risk of death compared with LG.\u003c/p\u003e \u003cp\u003eTo further confirm the predictive effect of monocyte count and GTVnx on OS and PFS, we divided patients into low and high groups based on baseline median monocyte count and GTVnx. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the high monocyte count group and high GTVnx group were associated with poor OS and PFS. In the two-independent sample T-test, there were no statistical differences in other clinical parameters between the two groups except baseline monocyte count, GTVnx, WBC, LMR, and NLR (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The clinical characteristics between the HG and LG were compared, and there were no statistical differences in age, sex, pre-treatment Epstein-Barr virus DNA, ECOG score, tumor stage, smoking history, drinking history, CCI, radiotherapy method, total radiotherapy days, whether chemotherapy was induced, radiotherapy and hematology indexes between the two groups.\u003c/p\u003e \u003cp\u003eBased on the independent risk factors (monocyte count\u0026thinsp;\u0026ge;\u0026thinsp;0.29\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L (median), GTVnx\u0026thinsp;\u0026ge;\u0026thinsp;28.5cm\u003csup\u003e3\u003c/sup\u003e (median)) for OS, we further divide patients into three different risk groups: low-risk group (with \u0026lt;\u0026thinsp;1 risk factor), medium-risk group (with 1 risk factors), and high-risk group (with 2 risk factors). Survival curves were significantly different among patients in different risk groups for OS (p\u0026thinsp;=\u0026thinsp;0.0008) and PFS (p\u0026thinsp;=\u0026thinsp;0.0007) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The characteristics of patients in the different risk groups are shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, patients in the GTVnx low group had a 2.64-fold and 2.31-fold increased risk of OS and PFS for every increase in the unit count of monocytes, and in the GTVnx high group had a 1.94-fold and 1.09-fold increase. In the low monocyte count group, the risk of OS and PFS increased by 1.01 times per unit volume increase of GTVnx, and in the high monocyte count group, GTVnx increases the risk of OS and PFS by 1.00 times per unit volume increase (Supplementary Table\u0026nbsp;1). Altogether, the benefit of patients with GTVnx\u0026thinsp;\u0026lt;\u0026thinsp;28.5cm\u003csup\u003e3\u003c/sup\u003e could be remarkably attenuated by the high monocyte count.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAlthough the role of systemic inflammation in the development of cancer has been investigated in many studies\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e, the main mechanism is still unclear. We all know that inflammation can promote the mobilization of monocytes from bone marrow to peripheral blood and further differentiation into tissue macrophages\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Macrophages then play a role in stimulating angiogenesis, enhancing tumor cell migration and invasion, and inhibiting anti-tumor immunity in the development of tumors\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. GTV is a potential biological reflection of tumor burden, and is associated with the survival of tumor patients \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. Understanding the relationship between different monocyte counts and the prognosis of tumors after radiotherapy and chemotherapy under different tumor loads is conducive to the formulation of individualized treatment decisions.\u003c/p\u003e \u003cp\u003eIn this study, it\u0026rsquo;s confirmed that pre-treatment monocyte count and GTVnx are independent predictors of survival in newly diagnosed non-metastatic nasopharyngeal carcinoma patients undergoing radiotherapy. The high monocyte count(\u0026ge;\u0026thinsp;0.29\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L) and high GTVnx(GTVnx\u0026thinsp;\u0026ge;\u0026thinsp;28.5cm\u003csup\u003e3\u003c/sup\u003e) were associated with poor OS and PFS. After adjusting for a variety of confounding factors, the high monocyte count group had a 2.14-fold higher risk of death compared with the low monocyte count group. Besides, For every increase in monocyte unit count, the OS and PFS risks of patients in the low and high GTVnx groups increased by 2.64 times, 2.31 times, 1.94 times, and 1.09 times, respectively. A large number of previous studies have shown that the increase of peripheral blood monocytes is associated with poor survival of various cancers\u003csup\u003e[10\u0026ndash;13,20\u0026minus;22]\u003c/sup\u003e. This is consistent with the results of our study in which NPC patients with higher baseline peripheral blood monocyte counts had worse survival outcomes than those with lower baseline peripheral blood monocyte counts. This study further verified that GTVnx and systemic inflammation, including monocytes, are important factors affecting the prognosis of NPC patients.\u003c/p\u003e \u003cp\u003eMonocytes can secrete various proinflammatory cytokines, which have been associated with shorter survival and worse prognosis in malignancies \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Moreover, monocytes can also promote tumor growth and angiogenesis by releasing VEGF, epidermal growth factor (EGF), and tumor necrosis factor-α (TNF-α)\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. However, the specific mechanism of monocytes in the development of malignancy is still not fully understood. A better understanding of the process of monocyte recruitment may lead to the development of new therapies to control the number and distribution of monocytes, thereby enhancing the therapeutic efficacy of malignancies and improving survival.\u003c/p\u003e \u003cp\u003eWhen the tumor volume is large, it may lead to changes in the tumor microenvironment, and the blood supply is difficult to reach the center of the tumor, resulting in obvious hypoxic tissue in this area, which is less responsive to radiotherapy and chemotherapy. In addition, the anatomical structure of nasopharyngeal carcinoma is complex, the wider the range of tumor invasion, the closer the distance between the tumor and the optic nerve, spinal cord, and brainstem, the greater the difficulty of radiotherapy planning, resulting in decreased efficacy and poor prognosis.\u003c/p\u003e \u003cp\u003eAs one of the types of leukocyte, monocytes can be combined with GTVnx as a prognostic indicator of nasopharyngeal carcinoma due to its convenient, rapid, and low-cost detection. The results of this study showed that GTVnx\u0026thinsp;\u0026ge;\u0026thinsp;28.5cm3 and monocyte count\u0026thinsp;\u0026ge;\u0026thinsp;0.29\u0026times;109/L were adverse factors for PFS and OS. In patients with GTVnx\u0026thinsp;\u0026lt;\u0026thinsp;28.5cm3, increasing monocyte count will significantly increase the risk of poor survival and disease progression. Clinicians should be alert to the risk of local recurrence or distant metastasis and develop individualized treatment plans ( such as increasing adjuvant chemotherapy, combined immunotherapy, etc. ) for patients with nasopharyngeal carcinoma who meet these requirements according to specific conditions.\u003c/p\u003e \u003cp\u003eSome limitations need to be mentioned. Due to the lack of post-treatment monocyte count data in this study, the relationship between post-treatment monocyte count and survival of NPC patients has not been revealed. Furthermore, this study was conducted in one medical center, so the selection bias was inevitable. Therefore, multi-center, large-sample prospective studies are needed to further confirm our findings.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, peripheral blood monocyte count combined with gross tumor volume of nasopharyngeal carcinoma can independently predict the overall survival and progression free-survival in newly diagnosed non-metastatic NPC patients who received radiotherapy. The benefit of patients with GTVnx\u0026thinsp;\u0026lt;\u0026thinsp;28.5cm\u003csup\u003e3\u003c/sup\u003e could be remarkably attenuated by the high monocyte count. These findings should be verified in more prospective studies conducted among different populations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eYun-rui Song.Li-Na Yang. and Dan Li.Jiang-Dong Sui. wrote the main manuscript text and Yun-rui Song.Ming-Yue Lu. De-Qing Liu. prepared Table 1-5 and figures 1-2. Hong-Lei Tu provides funding support. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eChen Y-P, Chan ATC, Le Q-T et al. Nasopharyngeal carcinoma. The Lancet 2019; 394: 64-80.\u003c/li\u003e\n \u003cli\u003eSung H, Ferlay J, Siegel RL et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: A Cancer Journal for Clinicians 2021; 71: 209-249.\u003c/li\u003e\n \u003cli\u003ePan JJ, Ng WT, Zong JF et al. Proposal for the 8th edition of the AJCC/UICC staging system for nasopharyngeal cancer in the era of intensity‐modulated radiotherapy. Cancer 2015; 122: 546-558.\u003c/li\u003e\n \u003cli\u003eZhang B, Li MM, Chen WH et al. Association of Chemoradiotherapy Regimens and Survival Among Patients With Nasopharyngeal Carcinoma. JAMA Network Open 2019; 2.\u003c/li\u003e\n \u003cli\u003eGalon Jrm, Costes A, Sanchez-Cabo F et al. Type, Density, and Location of Immune Cells Within Human Colorectal Tumors Predict Clinical Outcome. Science 2006; 313: 1960-1964.\u003c/li\u003e\n \u003cli\u003eAarstad HJ, Vintermyr OK, Ulvestad E et al. Peripheral blood monocyte and T‐lymphocyte activation levels at diagnosis predict long‐term survival in head and neck squamous cell carcinoma patients. Apmis 2015; 123: 305-314.\u003c/li\u003e\n \u003cli\u003eQu Z, Lu Y-j, Feng J-W et al. Preoperative Prognostic Nutritional Index and Neutrophil-to-Lymphocyte Ratio Predict Survival Outcomes of Patients With Hepatocellular Carcinoma After Curative Resection. Frontiers in Oncology 2022; 11.\u003c/li\u003e\n \u003cli\u003eShi C, Pamer EG. Monocyte recruitment during infection and inflammation. Nature Reviews Immunology 2011; 11: 762-774.\u003c/li\u003e\n \u003cli\u003eUgel S, Can\u0026egrave; S, De Sanctis F, Bronte V. Monocytes in the Tumor Microenvironment. Annual Review of Pathology: Mechanisms of Disease 2021; 16: 93-122.\u003c/li\u003e\n \u003cli\u003eKwiecień I, Rutkowska E, Polubiec-Kownacka M et al. Blood Monocyte Subsets with Activation Markers in Relation with Macrophages in Non-Small Cell Lung Cancer. Cancers 2020; 12.\u003c/li\u003e\n \u003cli\u003eSakakura K, Takahashi H, Motegi S-I et al. Immunological features of circulating monocyte subsets in patients with squamous cell carcinoma of the head and neck. Clinical Immunology 2021; 225.\u003c/li\u003e\n \u003cli\u003eJiang R, Cai X-Y, Yang Z-H et al. Elevated peripheral blood lymphocyte-to-monocyte ratio predicts a favorable prognosis in the patients with metastatic nasopharyngeal carcinoma. Chinese Journal of Cancer 2015; 34.\u003c/li\u003e\n \u003cli\u003eMagrowski Ł, Masri O, Ciepał J et al. Pre-Treatment Hemoglobin Concentration and Absolute Monocyte Count as Independent Prognostic Factors for Survival in Localized or Locally Advanced Prostate Cancer Patients Undergoing Radiotherapy. Biomedicines 2022; 10.\u003c/li\u003e\n \u003cli\u003eLiu W et al.(2021).The relationship between primary gross tumor volume and tumor response of locally advanced rectal cancer:pGTV as a more accurate tumor size indicator.J Invest Surg.34(2):181-190.\u003c/li\u003e\n \u003cli\u003eReymen B et al.(2013).Total gross tumor volume is an independent prognostic factor in patients treated with selective nodal irradiation for stage I to III small cell lung cancer.Int JRadiat Oncol Biol Phys.85(5):1319-1324.\u003c/li\u003e\n \u003cli\u003eSZE WM，LEE A W，YAU T K，et al．Primary tumor volume of nasopharyngeal carcinoma: prognostic significance for local control［J］．Int J Ｒadiat Oncol Biol Phys，2004，59( 1) : 21 －\u003c/li\u003e\n \u003cli\u003eKhandia R, Munjal A. Interplay between inflammation and cancer. In Inflammatory Disorders, Part A. 2020; 199-245.\u003c/li\u003e\n \u003cli\u003eQian B-Z, Pollard JW. Macrophage Diversity Enhances Tumor Progression and Metastasis. Cell 2010; 141: 39-51.\u003c/li\u003e\n \u003cli\u003eLIN Y H，HUANG T L，CHIEN C Y，et al．Pretreatment prognostic factors of survival and late toxicities for patients with nasopharyngeal carcinoma treated by simultaneous integrated boost\u003c/li\u003e\n \u003cli\u003eintensity-modulated radiotherapy［J］．Ｒadiat Oncol，2018，13( 1) : 45 － 53．\u003c/li\u003e\n \u003cli\u003eTridandapani S, Hu S, Zou Z et al. The Preoperative Peripheral Blood Monocyte Count Is Associated with Liver Metastasis and Overall Survival in Colorectal Cancer Patients. Plos One 2016; 11.\u003c/li\u003e\n \u003cli\u003eShibutani M, Maeda K, Nagahara H et al. The peripheral monocyte count is associated with the density of tumor-associated macrophages in the tumor microenvironment of colorectal cancer: a retrospective study. BMC Cancer 2017; 17.\u003c/li\u003e\n \u003cli\u003eFeng F, Zheng G, Wang Q et al. Low lymphocyte count and high monocyte count predicts poor prognosis of gastric cancer. BMC Gastroenterology 2018; 18.\u003c/li\u003e\n \u003cli\u003eYang JG, Wang LL, Ma DC. Effects of vascular endothelial growth factors and their receptors on megakaryocytes and platelets and related diseases. Br J Haematol 2018; 180: 321-334.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable1: Clinical characteristics of the total Nasopharyngeal Carcinoma patients\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"461\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003eValues\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eAge, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e51.19 \u0026plusmn;10.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e319(71.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eIMRT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e416(92.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003e3D-CRT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e32(7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eECOG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e36(8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e392(87.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e20(4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eInduction chemotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e425(94.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eT-stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e40(8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e208(46.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e127(28.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e73(16.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eN-stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e36(8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e183(40.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e190(42.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e39(8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eClinical stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e110(24.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e233(52.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eIVa\u003c/p\u003e\n \u003cp\u003ePre-treatment Epstein-Barr virus DNA\u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003cp\u003ePositive\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e105(23.4)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e65(14.5)\u003c/p\u003e\n \u003cp\u003e110(24.6)\u003c/p\u003e\n \u003cp\u003e273(60.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eTotal radiotherapy days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e46.70 \u0026plusmn;5.75\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eTotal radiotherapy dose(Gy)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e70.96 \u0026plusmn;1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eBody Dmean(Gy)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e19.49 \u0026plusmn;3.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eGTVnx\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e37.60 \u0026plusmn;29.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eGTVnd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e28.63 \u0026plusmn;38.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eBone Dmean(Gy)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e21.30 \u0026plusmn;15.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eCCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e3.04 \u0026plusmn;1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eOS time(m)\u003c/p\u003e\n \u003cp\u003ePFS time(m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e59.46 \u0026plusmn;33.83\u003c/p\u003e\n \u003cp\u003e54.95 \u0026plusmn;35.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eWBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e5.71 \u0026plusmn;2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eMonocyte\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e0.31 \u0026plusmn;0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eLymphocyte\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e1.51 \u0026plusmn;0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eLMR(Lymphocyte to monocyte ratio)\u003c/p\u003e\n \u003cp\u003eNLR(Neutrophil to Lymphocyte ratio)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e13.49 \u0026plusmn;23.01\u003c/p\u003e\n \u003cp\u003e2.87\u0026plusmn;2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eHaemoglobin\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e135.13 \u0026plusmn;16.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eNeutrophil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e3.77 \u0026plusmn;1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e199(44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.5683%;\"\u003e\n \u003cp\u003eDrinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41.4317%;\"\u003e\n \u003cp\u003e115(25.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eValues are mean\u0026plusmn;SD, n(%).\u003c/p\u003e\n\u003cp\u003eTable2：Univariate and Multivariable Cox regression analysis\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"613\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003eUnivariate analysis\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003eMultivariable analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003eHazard ratio\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003eHazard ratio (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003eMonocyte\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e2.30(1.13-4.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2.14(1.02-4.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e1.03(1.01-1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e1.02(0.98-1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.272\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003eRadiotherapy technique\u003c/p\u003e\n \u003cp\u003eInduction chemotherapy\u003c/p\u003e\n \u003cp\u003eConcurrent chemoradiotherapy\u003c/p\u003e\n \u003cp\u003ePre-treatment Epstein-Barr virus DNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e0.83(0.53-1.31)\u003c/p\u003e\n \u003cp\u003e1.20(0.49-2.97)\u003c/p\u003e\n \u003cp\u003e1.12(0.49-2.57)\u003c/p\u003e\n \u003cp\u003e0.41(0.06-2.94)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.65(0.94-2.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.417\u003c/p\u003e\n \u003cp\u003e0.686\u003c/p\u003e\n \u003cp\u003e0.784\u003c/p\u003e\n \u003cp\u003e0.299\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\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: 107px;\"\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: 183px;\"\u003e\n \u003cp\u003eTotal radiotherapy days\u003c/p\u003e\n \u003cp\u003eTotal radiotherapy dose(Gy)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e1.02(0.99-1.06)\u003c/p\u003e\n \u003cp\u003e1.11(0.96-1.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.211\u003c/p\u003e\n \u003cp\u003e0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\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: 183px;\"\u003e\n \u003cp\u003eBodyDmean（Gy）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e1.05(0.99-1.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\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: 183px;\"\u003e\n \u003cp\u003eGTVnx\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e1.01(1.00-1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e1.01(1.00-1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003eBone Dmean（Gy）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e1.00(0.99-1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\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: 183px;\"\u003e\n \u003cp\u003eCCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e1.28(1.09-1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e1.12(0.86-1.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.399\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e1.34(0.90-2.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\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: 183px;\"\u003e\n \u003cp\u003eDrinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e1.41(0.92-2.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\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: 183px;\"\u003e\n \u003cp\u003eLymphocyte\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e0.99(0.98-1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\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: 183px;\"\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e1.07(1.01-1.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e1.05(0.99-1.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003eHaemoglobin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e0.99(0.97-0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.99(0.98-1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0.228\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3: Comparison of clinical characteristics between two monocyte count groups\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"546\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003emonocyte-low（223）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003emonocyte-high（225）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003eAge, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e50.85\u0026plusmn;10.21\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e51.53 \u0026plusmn;10.11\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e0.959\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e161(72.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e158(70.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e0.644\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003eECOG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e0.670\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e18(8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e18(8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e197(88.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e195(86.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e8(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e12(5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003eInduction chemotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e216(96.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e209(92.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e0.057\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003eT-stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e0.500\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e23(10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e17(7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e105(47.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e103(45.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e57(25.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e70(31.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e38(17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e35(15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003eN-stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e0.336\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e13(5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e23(10.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e93(41.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e90(40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e99(44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e91(40.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e18(8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e21(9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003eClinical stage\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e0.752\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e57(25.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e53(23.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e112(50.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e121(53.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003ePre-treatment Epstein-Barr virus DNA(Positive)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e54(24.2)\u003c/p\u003e\n \u003cp\u003e30(6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e51(22.7)\u003c/p\u003e\n \u003cp\u003e35(7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003cp\u003e0.408\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003eTotal radiotherapy days\u003c/p\u003e\n \u003cp\u003eTotal radiotherapy dose(Gy)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e46.52\u0026plusmn;5.81\u003c/p\u003e\n \u003cp\u003e70.96\u0026plusmn;1.51\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e46.87 \u0026plusmn;5.71\u003c/p\u003e\n \u003cp\u003e70.95\u0026plusmn;1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e0.766\u003c/p\u003e\n \u003cp\u003e0.943\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003eBody Dmean（Gy）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e20.00\u0026plusmn;3.19\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e18.99 \u0026plusmn;3.42\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e0.501\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003eGTVnx\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e35.78 \u0026plusmn;26.24\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e39.39 \u0026plusmn;32.58\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\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: 34.5521%;\"\u003e\n \u003cp\u003eGTVnd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e28.79 \u0026plusmn;39.00\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e28.48 \u0026plusmn;38.83\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e0.692\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003eBone Dmean（Gy）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e21.92 \u0026plusmn;15.41\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e20.68 \u0026plusmn;15.58\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e0.843\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003eCCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e3.01 \u0026plusmn;1.07\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e3.08 \u0026plusmn;1.14\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e0.350\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003eWBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e5.23 \u0026plusmn;1.92\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e6.19 \u0026plusmn;2.30\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\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: 34.5521%;\"\u003e\n \u003cp\u003eMonocyte\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e0.13 \u0026plusmn;0.09\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e0.49 \u0026plusmn;0.22\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003eLymphocyte\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e1.39 \u0026plusmn;0.50\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e1.62 \u0026plusmn;0.55\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e0.233\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003eLMR\u003c/p\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e23.42 \u0026plusmn;29.49\u003c/p\u003e\n \u003cp\u003e3.07\u0026plusmn;2.71\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e3.69 \u0026plusmn;1.47\u003c/p\u003e\n \u003cp\u003e2.66\u0026plusmn;1.73\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003eHaemoglobin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e135.35 \u0026plusmn;16.05\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e134.91 \u0026plusmn;17.50\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e0.254\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003eNeutrophil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e3.60 \u0026plusmn;1.88\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e3.93 \u0026plusmn;1.94\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e0.424\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e94(42.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e106(47.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e0.335\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.5521%;\"\u003e\n \u003cp\u003eDrinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2176%;\"\u003e\n \u003cp\u003e57(25.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.4004%;\"\u003e\n \u003cp\u003e58(25.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.83%;\"\u003e\n \u003cp\u003e0.936\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eValues are mean\u0026plusmn;SD, n(%).\u003c/p\u003e\n\u003cp\u003eTable 4: Characteristics of patients in different risk groups\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"589\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003eLow-risk group\u003c/p\u003e\n \u003cp\u003e（117）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003eMedium-risk group(215)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003eHigh-risk group\u003c/p\u003e\n \u003cp\u003e（116）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eAge, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e51.02\u0026plusmn;9.59\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e50.96\u0026plusmn;10.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e51.66\u0026plusmn;10.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.827\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e78(67.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e155(70.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e86(74.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.178\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eECOG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.052\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e13(11.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e17(7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e6(5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e99(85.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e189(87.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e103(88.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e4(3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e9(4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e7(6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eInduction chemotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e111(95.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e203(94.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e111(95.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.662\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eT-stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e18(15.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e20(9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e1(0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e75(64.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e103(47.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e30(25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e14(12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e58(26.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e56(48.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e9(7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e34(15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e29(25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eN-stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.610\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e7(6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e19(8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e10(8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e55(47.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e85(39.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e43(37.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e47(40.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e92(42.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e51(44.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e7(6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e19(8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e12(10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eClinical stage\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e48(41.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e51(23.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e11(9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e51(44.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e116(54.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e66(56.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003ePre-treatment Epstein-Barr virus DNA(Positive)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e17(14.6)\u003c/p\u003e\n \u003cp\u003e12(10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e48(22.3)\u003c/p\u003e\n \u003cp\u003e24(11.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e39(33.6)\u003c/p\u003e\n \u003cp\u003e29(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003cp\u003e0.151\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eTotal radiotherapy days\u003c/p\u003e\n \u003cp\u003eTotal radiotherapy dose(Gy)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e45.59\u0026plusmn;5.20\u003c/p\u003e\n \u003cp\u003e70.74\u0026plusmn;1.75\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e46.90\u0026plusmn;5.82\u003c/p\u003e\n \u003cp\u003e71.03\u0026plusmn;1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e47.48 \u0026plusmn;6.03\u003c/p\u003e\n \u003cp\u003e71.04\u0026plusmn;1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003cp\u003e0.189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eBody Dmean（Gy）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e19.19\u0026plusmn;2.95\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e19.78\u0026plusmn;3.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e19.25 \u0026plusmn;3.66\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.203\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eGTVnx\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e17.15 \u0026plusmn;7.16\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e36.19 \u0026plusmn;26.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e60.65 \u0026plusmn;33.01\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eGTVnd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e22.90 \u0026plusmn;26.31\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e30.34 \u0026plusmn;40.40\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e31.51 \u0026plusmn;46.17\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.201\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eBone Dmean（Gy）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e19.96 \u0026plusmn;3.54\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e21.78 \u0026plusmn;15.68\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e21.72 \u0026plusmn;21.41\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.564\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eCCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e2.96 \u0026plusmn;1.13\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e3.07 \u0026plusmn;1.08\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e3.08 \u0026plusmn;1.13\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.625\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eWBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e5.40 \u0026plusmn;1.92\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e5.52 \u0026plusmn;2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e6.41 \u0026plusmn;2.31\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eMonocyte\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e0.16 \u0026plusmn;0.13\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e0.29 \u0026plusmn;0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e0.49 \u0026plusmn;0.25\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eLymphocyte\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e1.42 \u0026plusmn;0.48\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e1.49 \u0026plusmn;0.54\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e1.61 \u0026plusmn;0.57\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eLMR\u003c/p\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e22.36 \u0026plusmn;30.79\u003c/p\u003e\n \u003cp\u003e3.01 \u0026plusmn;2.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e13.96 \u0026plusmn;22.37\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.86 \u0026plusmn;2.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e3.80 \u0026plusmn;1.97\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.77 \u0026plusmn;1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003cp\u003e0.712\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eHaemoglobin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e136.42 \u0026plusmn;15.13\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e135.08 \u0026plusmn;16.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e134.02 \u0026plusmn;18.58\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.550\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eNeutrophil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e3.65 \u0026plusmn;1.97\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e3.66 \u0026plusmn;1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e4.10 \u0026plusmn;1.91\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.102\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e38(32.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e99(46.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e62(53.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.4092%;\"\u003e\n \u003cp\u003eDrinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.0153%;\"\u003e\n \u003cp\u003e23(19.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6757%;\"\u003e\n \u003cp\u003e57(26.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8642%;\"\u003e\n \u003cp\u003e35(30.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0357%;\"\u003e\n \u003cp\u003e0.237\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eValues are mean\u0026plusmn;SD, n(%).\u003c/p\u003e\n\u003cp\u003eTable 5: The effect of monocyte count per unit increase on OS and PFS in different groups\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"566\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003eRisk groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 219px;\"\u003e\n \u003cp\u003eOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003ePFS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eHR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003eHR (95% CI)\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 \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003eGTVnx-low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 121px;\"\u003e\n \u003cp\u003e2.64(0.72-9.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 98px;\"\u003e\n \u003cp\u003e0.142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 109px;\"\u003e\n \u003cp\u003e2.31(1.04-5.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003eGTVnx-high\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1.94(1.25-3.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 98px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 109px;\"\u003e\n \u003cp\u003e1.09(0.72-1.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.694\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Peripheral blood monocyte count, GTVnx, nasopharyngeal carcinoma, radiotherapy, overall survival","lastPublishedDoi":"10.21203/rs.3.rs-5259457/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5259457/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground and purpose: \u003c/strong\u003eThe relationship between peripheral blood monocyte count and primary gross tumor volume with survival prognosis in newly diagnosed nasopharyngeal carcinoma(NPC) patients who received radiotherapy remains unclear. Therefore, We conducted a cohort study to assess the association of peripheral blood monocyte counts and primary gross tumor volume with survival outcomes in newly diagnosed non-metastatic NPC patients who received radiotherapy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials/Methods: \u003c/strong\u003eWe included newly diagnosed non-metastatic NPC patients who underwent radiotherapy in our hospital from January 2013 to December 2015. General clinical characteristics such as age, gender, ECOG score and tumor stage, peripheral blood monocyte count, lymphocyte count, white blood cell count (WBC), neutrophil count, radiotherapy technology, total radiotherapy days, gross tumor volume of nasopharyngeal carcinoma (GTVnx) and gross tumor volume of cervix node(GTVnd) of patients before radiotherapy, and whether chemotherapy was induced were recorded. The primary endpoint was overall survival, the secondary endpoint was progression-free survival. Univariate and multivariate COX regression were used to analyze the relationship among\u0026nbsp;peripheral blood monocyte count, GTVnx, and survival outcome.\u0026nbsp;Based on the independent risk factors\u0026nbsp;for OS, we further divide patients into three different risk groups,\u0026nbsp;and the differences in clinical and therapeutic indicators and survival outcomes between the three groups were analyzed using a one-way analysis of variance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eA total of 448 participants were included in the study,\u0026nbsp;the median follow-up time was 74.3 months. Of these, 97 (21.7%) died.\u0026nbsp;In the univariate\u0026nbsp;and multivariate Cox regression analyses, peripheral blood\u0026nbsp;monocyte count and GTVnx were independently associated with OS. The high monocyte count and GTVnx were associated with the poor OS and PFS. Survival curves significantly differed among patients in different risk groups for OS (p = 0.0008) and PFS (p = 0.0007). Besides, For every increase in monocyte unit count, the OS and PFS risks of patients in the low GTVnx group increased by 2.64 and 2.31 folds, respectively,.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003ePeripheral blood monocyte count combined with GTVnx is a independent predictor for overall survival and progression free-survival in newly diagnosed non-metastatic NPC patients who received radiotherapy. The benefit of patients with GTVnx\u0026lt; 28.5cm\u003csup\u003e3\u003c/sup\u003e could be remarkably attenuated by the high monocyte count.\u003c/p\u003e","manuscriptTitle":"Peripheral blood monocyte count impairs benefit from radiotherapy in patients with low gross tumor volume of nasopharyngeal carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-27 17:14:05","doi":"10.21203/rs.3.rs-5259457/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4782b72c-fba9-45a2-8eb5-0191b7365644","owner":[],"postedDate":"November 27th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":39975099,"name":"Health sciences/Diseases"},{"id":39975100,"name":"Health sciences/Diseases/Cancer"}],"tags":[],"updatedAt":"2024-12-04T11:08:38+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-27 17:14:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5259457","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5259457","identity":"rs-5259457","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}