Literature DB >> 29511262

Neutrophil-to-lymphocyte Ratio (NLR) as a predictor for recurrence in patients with stage III melanoma.

Junjie Ma1, James Kuzman2, Abhijit Ray3, Benjamin O Lawson4, Brian Khong5, Si Xuan6, Andrew W Hahn7, Hung T Khong8.   

Abstract

Neutrophil-to-lymphocyte ratio is a strong predictor for overall survival and disease free survival in many cancers. Our study is the first investigation aiming to determine the predictive value of neutrophil-to-lymphocyte ratio on prognosis of patients with stage III melanoma. This retrospective study utilized a cohort of 107 patients with stage III melanoma treated at Huntsman Cancer Institute, University of Utah, from May 2002 to March 2016. The optimal cutoff of neutrophil-to-lymphocyte ratio was determined by the significance of log-rank tests. A total of 97 log-rank tests were conducted to find the optimal cutoff. Disease free survival was assessed using the Kaplan-Meier method, and univariable and multivariable Cox models were applied to evaluate the predictive value of neutrophil-to-lymphocyte ratio. 2.5 was identified as the optimal cutoff. Kaplan-Meier curve showed that the disease free survival rate of the low value group was significantly higher compared to that of high value group. After adjusting for confounders and other prognostic factors, the neutrophil-to-lymphocyte ratio ≥ 2.5 remained a strong predictor for disease recurrence in patients with stage III melanoma.

Entities:  

Mesh:

Year:  2018        PMID: 29511262      PMCID: PMC5840418          DOI: 10.1038/s41598-018-22425-3

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


Introduction

Melanoma kills an estimated 10,130 people in the United States annually[1]. There are five stages of melanoma (Stage 0, Stage I, Stage II, Stage III, and Stage IV). Stage III melanoma patients include those with regional metastases, either in the regional lymph nodes or intralymphatic metastases manifesting as either satellite or in-transit metastases[2]. There are three definable subgroups with statistically significant differences in survival. Patients with Stage IIIA have 5- survival rates of 78%. Patients with Stage IIIB (any thickness, with one to three lymph nodes involved and ulceration) have a 5-year survival rate of 59%. Patients with Stage IIIC (defined as one to three macroscopic lymph node metastases and ulcerated primary melanoma) were found to have a 5- year survival rate at 40%[2]. Romano et al. researched the site and timing of the first relapse in Stage III melanoma and found that for stage IIIA and IIIB patients, lung and liver were the most common first sites of systemic relapse whereas in stage IIIC patients, first sites of systemic relapses were evenly distributed among skin/subcutaneous, nodal, lung, liver, brain and bone. Within their study, central nervous system recurrence of melanoma was found in 4% of stage IIIA and 7% and 13% in stage IIIB and stage IIIC, respectively. Most importantly, Romano et al. found the estimate 5-year survivals for stages IIIA, IIIB, and IIIC from time of first relapse were 20%, 20%, and 11%, respectively[3]. Therefore, it is of the utmost importance to utilize another tool to predict recurrence in stage III melanoma patients. Neutrophil-to-lymphocyte ratio (NLR) integrated information on the inflammatory milieu and physiological stress, which makes it a strong predictor for prognosis in patients with different diseases. Prior studies have shown that increased NLR is associated with decreased overall survival (OS) and disease free survival (DFS) in melanoma, gastric cancer, breast cancer, lung cancer, and gastrointestinal cancer[4-9]. For example, Lino-Silva et al. reported that basal NLR ≥ 2 is associated with decreased OS in stage II melanoma patients[4]. Shimada et al. concluded a high preoperative NLR may be a convenient biomarker to identify patients with a poor prognosis after resection for primary gastric cancer[5]. Azab et al. discovered NLR is an independent predictor of short- and long-term mortality in breast cancer patients with NLR > 3.3[6]. Tomita et al. found a high preoperative NLR may be a convenient biomarker to identify patients with a poor prognosis after resection for non-small cell lung cancer[7]. Halazun et al. noticed an elevated NLR increases both risk of death and the risk of recurrence in patients who undergo surgery for colorectal liver metastases[8]. Moreover, a meta-analysis based 144 studies suggested that NLR is a significant prognostic indicator in gastrointestinal cancers[9]. Most of previous studies in melanoma focused on patients with advanced metastatic disease[10,11]. A retrospective cohort study conducted by Ferrucci et al. showed that baseline NLR was significantly associated with survival in patients treated with ipilimumab[10]. Similarly, Zaragoza et al. also conducted a retrospective cohort study in melanoma patients treated with ipilimumab[11]. They reported NLR is an independent prognostic indicator of poor survival in metastatic melanoma patients. The treatment and prognosis of stage III patients are very different from stage IV patients whose melanoma has spread to distant areas of body. A few studies estimated the association between NLR and long-term survival[4,12]. Lino-Silva reported that elevated NLR was associated with decreased 5-year OS in stage II melanoma patients[4]. Davis et al. found that NLR was independently associated with disease-specific death in patients with nonmetastatic melanoma[12]. However, it is still unclear whether high NLR is a passive indicator of recurrence in stage III melanoma patients. This is the first study that used NLR to predict the DFS in stage III melanoma patients. The aim of our study was to determine the predictive value of NLR on disease prognosis in stage III melanoma patients.

Results

A total of 107 patients were enrolled in this study. The baseline characteristics are presented in Table 1. We conducted 97 log-rank tests to determine the optimal cutoff.The association between NLR value and p-value of log-rank tests are presented in Fig. 1. The NLR cutoff value was determined at 2.5.
Table 1

Baseline characteristics of stage III melanoma patients according to the NLR.

No. (%)No. (%)No. (%)p-value
Total (N = 107)NLR < 2.5 (N = 60)NLR ≥ 2.5 (N = 47)
Age of diagnosis (years) 0.435
<3523(21.5)14(23.3)9(19.2)
35–4922(20.6)15(25.0)7(14.9)
50–6438(35.5)20(33.3)18(38.3)
65+24(22.4)11(18.3)13(27.7)
Gender 0.066
Female40(37.4)27(45.0)13(27.7)
Male67(62.6)33(55.0)34(72.3)
Site 0.539
Head and Neck28(26.4)17(28.3)11(23.9)
Trunk42(39.6)21(35.0)21(45.7)
Limb36(34.0)22(36.7)14(30.4)
BRAF 0.102
Negative16(14.9)7(11.7)9(19.2)
Positive18(16.8)7(11.7)11(23.4)
Unknown73(68.2)46(76.7)27(57.4)
Stage III 0.221
A33(31.4)20(34.5)13(27.7)
B44(41.9)20(34.5)24(51.1)
C28(26.7)18(31.0)10(21.3)
N stage 0.748
03(3.0)2(3.6)1(2.2)
162(61.4)36(65.5)26(56.5)
225(24.8)12(21.8)13(28.3)
311(10.9)5(9.1)6(13.0)
Adjuvant therapy 0.044
No52(48.6)24(40.0)28(59.6)
Yes55(51.4)36(60.0)19(40.4)
Radiation 0.836
No61(57.0)33(55.0)28(59.6)
Yes9(8.4)6(10.0)3(6.38)
Unknown37(34.6)21(35.0)16(34.0)
T stage 0.687
T119(17.8)13(21.7)6(12.8)
T233(30.8)18(30.0)15(31.9)
T322(20.6)10(16.7)12(25.5)
T417(15.9)10(16.7)7(14.9)
Unknown16(15.0)9(15.0)7(14.9)
Ulceration 0.280
No48(44.9)24(40.0)24(51.1)
Yes44(41.1)25(41.7)19(40.4)
Unknown15(14.0)11(18.3)4(8.5)
TIL 0.177
No58(55.2)36(61.0)22(47.8)
Yes47(44.8)23(39.0)24(52.2)
Median IQR Median IQR Median IQR
WBC 6.66(5.34, 8.33)6.27(5.10, 7.62)7.03(5.48, 9.01)0.036
ANC 4.30(3.10, 5.40)3.55(2.80, 4.65)5.00(3.90, 6.40)<0.001
ALC 1.90(1.40, 2.30)2.30(1.75, 2.55)1.50(1.20, 1.90)<0.001
NLR 2.27(1.71, 3.00)1.72(1.27, 2.05)3.11(2.70, 4.06)<0.001
Breslow 1.65(1.15, 3.35)1.60(0.93, 3.65)1.90(1.25, 3.28)0.508

*TIL, tumor-infiltrating lymphocytes; WBC, white blood cell counts; ANC, absolute neutrophil count; ALC absolute lymphocyte count; NLR, neutrophil-to-lymphocyte ratio; Breslow, Breslow’s thickness measures in millimeters.

Figure 1

Association between NLR value and p-value of log-rank tests.

Baseline characteristics of stage III melanoma patients according to the NLR. *TIL, tumor-infiltrating lymphocytes; WBC, white blood cell counts; ANC, absolute neutrophil count; ALC absolute lymphocyte count; NLR, neutrophil-to-lymphocyte ratio; Breslow, Breslow’s thickness measures in millimeters. Association between NLR value and p-value of log-rank tests. The high NLR group had 47 patients whose NLR was ≥ 2.5, and the low NLR group had 60 patients whose NLR was < 2.5. There were no statistically significant differences in age, gender, site of melanoma, BRAF mutation status, stage IIIA, B or C status, lymph node status (N stage), the tumor size (T stage), ulceration status, tumor-infiltrating lymphocytes (TILs), and the Breslow depth (Table 1). There were more female patients in the low NLR group compared with the high NLR group. The low NLR group had 27 (45.0%) female patients, while the high NLR group had 13 (27.7%) female patients, although the difference was not significant (p = 0.066). Compared with the high NLR group, the low NLR group had more patients who received adjuvant therapy (36, 60.0% vs. 19, 40.4%, p = 0.044). The white blood cell (WBC) count of the low NLR group was slightly lower than that of the high NLR group [Median 6.27 (±IQR 5.10, 7.62) vs Median 7.03 (±IQR 5.48, 9.01), p = 0.036]. The median (range) of follow-up period was 21.1 (2.9, 123.2) months. The Kaplan-Meier (KM) curve showed that the DFS rate of the low NLR group was significantly higher compared to that of the high NLR group (Fig. 2). The p-value of log-rank test was 0.001. The univariable model showed that patients with baseline NLR < 2.5 had a significantly improved DFS [Hazard Ratio (HR) 2.99, 95% Confidence Interval (CI) 1.50 to 5.94, p-value = 0.002]. In the multivariable Cox proportional hazard model, we adjusted for age of diagnosis, gender, site of melanoma, stage IIIA, B or C status, lymph node status (N stage), adjuvant therapy, the tumor size (T stage), ulceration status, white blood cell counts, tumor-infiltrating lymphocytes (TILs), and the Breslow depth. The adjusted hazard ratio of DFS for patients with baseline NLR ≥ 2.5 was 3.82 (95% CI 1.26 to 11.56, p-value = 0.018) compared to patients with baseline NLR < 2.5. Schoenfeld’s global test indicated the proportional hazards assumption was not violated (p = 0.409 for the multivariable Cox model). Hazard ratios for the disease free survival are presented in Table 2.
Figure 2

Kaplan-Meier survival curves showing the DFS by NLR.

Table 2

Hazard ratios for the disease free survival in stage III melanoma patients.

ModelHR95% CI Lower95% CI UpperP-value
Univariable model2.991.505.940.002
Multivariable model*3.821.2611.560.018

*Adjusted for age of diagnosis, gender, site of melanoma, stage IIIA, B or C status, lymph node status (N stage), adjuvant therapy, the tumor size (T stage), ulceration status, white blood cell counts, tumor-infiltrating lymphocytes (TILs), and the Breslow depth.

Kaplan-Meier survival curves showing the DFS by NLR. Hazard ratios for the disease free survival in stage III melanoma patients. *Adjusted for age of diagnosis, gender, site of melanoma, stage IIIA, B or C status, lymph node status (N stage), adjuvant therapy, the tumor size (T stage), ulceration status, white blood cell counts, tumor-infiltrating lymphocytes (TILs), and the Breslow depth.

Discussion

To our best knowledge, this is the first study to evaluate the predictive value of NLR on melanoma recurrence in patients diagnosed with stage III melanoma. Our analyses indicated that NLR is a significant predictor for recurrence in stage III melanoma patients. Such data are critical to determine which patients would benefit from adjuvant treatment. Current regimens provide modest benefits coupled with very common and significant toxicities that result in decreased quality of life. High dose interferon alpha raises recurrence free survival (RFS) by approximately 11% in 5 years but has associated severe toxicities in the large majority of patients including granulocytopenias, liver toxicity, thyroid toxicity, and severe fatigue[13]. Ipilimumab, which increases 5 year RFS, distant metastasis free survival, and OS by approximately 10%, has nearly all patients suffer some adverse events (AEs) with half suffering significant grade 3 or 4 AEs of dermatologic, gastrointestinal, endocrine, and hepatic failure[14]. Because of the frequency and severity of these toxicities, NLR as a prognostic factor would allow for better selection of patients for adjuvant treatment. Our study suggests that females have better outcomes and survival than male patients with stage III melanoma. This finding is consistent with several prior studies including one that found there were more females in NLR < 5 group compared with NLR ≥ 5 group (35.6% vs 29.5%), which evaluated the predictive value of NLR for survival in patients with colorectal liver cancer[8]. Even though one has yet to discover the main reason for improved melanoma survival among females compared to males, many studies have suggested potential possibilities including their better self-detection rates, closer follow up to health-care providers, and are more likely to engage in preventative behaviors[15-17]. Our study suggests that the survival advantage is in part due to having a low NLR. In addition, the WBC count in the low NLR group is lower compared to that in the high NLR group. This finding might be explained by patients with high NLR have more inflammatory response. Because NLR integrates information on the inflammatory milieu and physiological stress, many studies indicated it is superior to other leukocyte parameters such as leukocyte counts for predicting prognosis of different disease[18-21]. In addition, NLR is more stable when it is used to predict the prognosis because other leukocyte counts could be impacted by many factors such as smoking, weight, hemoglobin, and diastolic blood pressure. In this study, we used the NLR with most significant log-rank test p-value as the optimal cutoff. The optimal cutoff point used in this study was 2.5, which is different from the values used in prior studies. Lino-Silva used 2 as the NLR cutoff to predict overall survival in melanoma patients. They did not differentiate between different stages when they determined the cutoff using operating characteristic (ROC) curve analysis[4]. Bhat et al. also used ROC curve analysis to determine the optimal cutoff of 5 in patients with Stage III or IV unresectable melanoma[22]. Zaragoza J et al. used 4, also determined using ROC analysis, as the cutoff of NLR to evaluate the usefulness of NLR for predicting overall survival in stage III or IV melanoma patients[10]. The difference of cutoff point could be because the study population was dissimilar between the studies. The study population in our study is stage III melanoma patients without histologically proven recurrence. In contrast, prior studies did not differentiate stage III from other stages. This difference may be also due to the methods used to determine the optimal cutoff. Since ROC curves do not account for time to event and right censoring, the method used in our study is more appropriate for prognostic questions[23]. There are several limitations of this study. First, this is a single-center retrospective cohort study. The majority of the patients were from Utah where there is approximately 66% of sun exposure annually and prolonged sun exposure has been suggested to be an important risk factor for developing melanoma[11]. The results from this study need to be applied to other population with cautiousness. Second, we only evaluated the DFS due to the limited follow-up data. Evaluating the long-term OS might give us a deeper insight into the usefulness of NLR for predicting prognosis and recurrence in patients with melanoma. Third, this study only focused on stage III melanoma patients. The predictive value of NLR might be different in patients diagnosed with other stages of melanoma. In conclusion, the NLR is a strong predictor of disease recurrence in patients with stage III melanoma. The conclusion should be validated by larger prospective studies. Especially, the association between long-term OS and the NLR needs to be further studied.

Methods

This retrospective study utilized a cohort of patients diagnosed with stage III melanoma treated at Huntsman Cancer Institute, University of Utah, from May 2002 to March 2016. Inclusion criteria included patients with stage III melanoma, without histologically proven recurrence, an absolute neutrophil count (ANC) and an absolute lymphocyte count (ALC) available at baseline. A total of 107 patients who met the inclusion criteria were included in this study. The optimal cutoff of NLR was determined by the significance of log-rank tests[24]. A total of 97 log-rank tests were conducted to find the optimal cutoff. DFS was assessed using the Kaplan–Meier method, and univariable and multivariable Cox models were applied to evaluate the association between predictive value of NLR and DFS. Data were obtained from clinical medical records, which include demographic variables, site of melanoma, date of diagnosis, adjuvant therapy, radiation therapy, the tumor size (T stage), lymph node status (N stage) and mitotic count. The medical records for the patients were reviewed by two investigators independently. The study was approved by the Institutional Review Board (IRB) at University of Utah, and a waiver of consent was permitted. All analyses were conducted in compliance with the approved study protocol. The datasets generated and analysed during the study are available from the corresponding authors on reasonable request. To determine the optimal cutoff point of NLR in our study, we performed 97 log-rank tests based on all possible NLR values of this cohort. The optimal cutoff was defined as the NLR value with the smallest p-value of log-rank tests. After determining the optimal NLR cutoff, we classified patients into two groups based on their NLR values. Patients were categorized as having high NLR if their NLR values were above or equal to the cutoff point, and individuals were categorized as having low NLR if their NLR values were below the optimal cutoff value. Distributions of continuous variables were summarized as median and interquartile range (IQR), and distributions of categorical variables were described as frequencies and percentages. Rank sum test and chi-squared test were used to compare continuous variables and categorical variables, respectively. DFS was assessed using the KM method. In addition, univariable and multivariable Cox proportional hazard models were used to evaluate the association between NLR cutoff value and DFS. The multivariable model controlled for age of diagnosis, gender, site of melanoma, stage IIIA, B or C status, lymph node status (N stage), adjuvant therapy, the tumor size (T stage), ulceration status, white blood cell counts, tumor-infiltrating lymphocytes (TILs), and the Breslow depth. HRs and their corresponding 95% CIs were estimated. The proportional-hazards assumption was checked by scaled Schoenfeld residuals. The statistical significance for P value was designated as less than 0.05. All the analyses were conducted using STATA 14.0 (Stata, College Station, TX) and R software version 3.4.0.
  23 in total

1.  Usefulness of the neutrophil-to-lymphocyte ratio in predicting short- and long-term mortality in breast cancer patients.

Authors:  Basem Azab; Vijaya R Bhatt; Jaya Phookan; Srujitha Murukutla; Nina Kohn; Terenig Terjanian; Warren D Widmann
Journal:  Ann Surg Oncol       Date:  2011-06-03       Impact factor: 5.344

2.  Gender-related differences in outcome for melanoma patients.

Authors:  Charles R Scoggins; Merrick I Ross; Douglas S Reintgen; R Dirk Noyes; James S Goydos; Peter D Beitsch; Marshall M Urist; Stephan Ariyan; Jeffrey J Sussman; Michael J Edwards; Anees B Chagpar; Robert C G Martin; Arnold J Stromberg; Lee Hagendoorn; Kelly M McMasters
Journal:  Ann Surg       Date:  2006-05       Impact factor: 12.969

Review 3.  Interferon alpha adjuvant therapy in patients with high-risk melanoma: a systematic review and meta-analysis.

Authors:  Simone Mocellin; Sandro Pasquali; Carlo R Rossi; Donato Nitti
Journal:  J Natl Cancer Inst       Date:  2010-02-23       Impact factor: 13.506

4.  Site and timing of first relapse in stage III melanoma patients: implications for follow-up guidelines.

Authors:  Emanuela Romano; Michael Scordo; Stephen W Dusza; Daniel G Coit; Paul B Chapman
Journal:  J Clin Oncol       Date:  2010-05-17       Impact factor: 44.544

Review 5.  Neutrophil to lymphocyte ratio and cardiovascular diseases: a review.

Authors:  Tariq Bhat; Sumaya Teli; Jharendra Rijal; Hilal Bhat; Muhammad Raza; Georges Khoueiry; Mustafain Meghani; Muhammad Akhtar; Thomas Costantino
Journal:  Expert Rev Cardiovasc Ther       Date:  2013-01

6.  Pretreatment neutrophil/lymphocyte ratio is superior to platelet/lymphocyte ratio as a predictor of long-term mortality in breast cancer patients.

Authors:  Basem Azab; Neeraj Shah; Jared Radbel; Pamela Tan; Vijaya Bhatt; Steven Vonfrolio; Ayman Habeshy; Antonio Picon; Scott Bloom
Journal:  Med Oncol       Date:  2013-01-03       Impact factor: 3.064

7.  Neutrophil-lymphocyte ratio is a reliable predictive marker for early-stage diabetic nephropathy.

Authors:  Wanjing Huang; Jinhua Huang; Qingxing Liu; Fuchuan Lin; Zhihao He; Zhenhua Zeng; Lei He
Journal:  Clin Endocrinol (Oxf)       Date:  2014-09-26       Impact factor: 3.478

8.  Neutrophil-to-lymphocyte ratio as a quick and reliable predictive marker to diagnose the severity of diabetic retinopathy.

Authors:  Sena Memnune Ulu; Mustafa Dogan; Ahmet Ahsen; Abdullah Altug; Kasım Demir; Gürsel Acartürk; Sibel Inan
Journal:  Diabetes Technol Ther       Date:  2013-08-06       Impact factor: 6.118

9.  High neutrophil to lymphocyte ratio measured before starting ipilimumab treatment is associated with reduced overall survival in patients with melanoma.

Authors:  J Zaragoza; A Caille; N Beneton; G Bens; F Christiann; H Maillard; L Machet
Journal:  Br J Dermatol       Date:  2015-11-25       Impact factor: 9.302

Review 10.  Neutrophil-to-lymphocyte ratio as prognostic indicator in gastrointestinal cancers: a systematic review and meta-analysis.

Authors:  Randy C Bowen; Nancy Ann B Little; Joshua R Harmer; Junjie Ma; Luke G Mirabelli; Kyle D Roller; Andrew Mackay Breivik; Emily Signor; Alec B Miller; Hung T Khong
Journal:  Oncotarget       Date:  2017-05-09
View more
  15 in total

1.  Pre-treatment neutrophils count as a prognostic marker to predict chemotherapeutic response and survival outcomes in glioma: a single-center analysis of 288 cases.

Authors:  Zhiliang Wang; Liyun Zhong; Guanzhang Li; Ruoyu Huang; Qiangwei Wang; Zheng Wang; Chuanbao Zhang; Baoshi Chen; Tao Jiang; Wei Zhang
Journal:  Am J Transl Res       Date:  2020-01-15       Impact factor: 4.060

2.  High neutrophil-to-lymphocyte ratio (NLR) is associated with treatment failure and death in patients who have melanoma treated with PD-1 inhibitor monotherapy.

Authors:  Edmund K Bartlett; Jessica R Flynn; Katherine S Panageas; Richard A Ferraro; Jessica M Sta Cruz; Michael A Postow; Daniel G Coit; Charlotte E Ariyan
Journal:  Cancer       Date:  2019-10-04       Impact factor: 6.860

3.  Perioperative change in neutrophil-to-lymphocyte ratio (NLR) is a prognostic factor in patients with completely resected primary pulmonary sarcomatoid carcinoma.

Authors:  Yong Won Seong; Sung Joon Han; Woohyun Jung; Jae Hyun Jeon; Sukki Cho; Sanghoon Jheon; Kwhanmien Kim
Journal:  J Thorac Dis       Date:  2019-03       Impact factor: 2.895

4.  Systemic immune-inflammation index (SII) is useful to predict survival outcomes in patients with surgically resected non-small cell lung cancer.

Authors:  Wei Guo; Songhua Cai; Fan Zhang; Fei Shao; Guochao Zhang; Yang Zhou; Liang Zhao; Fengwei Tan; Shugeng Gao; Jie He
Journal:  Thorac Cancer       Date:  2019-02-07       Impact factor: 3.500

5.  Analysis of Clinical Characteristics and Poor Prognostic Predictors in Patients With an Initial Diagnosis of Autoimmune Encephalitis.

Authors:  Xiaowei Qiu; Haiqing Zhang; Dongxu Li; Jing Wang; Zhigang Jiang; Yuanzhong Zhou; Ping Xu; Jun Zhang; Zhanhui Feng; Changyin Yu; Zucai Xu
Journal:  Front Immunol       Date:  2019-06-07       Impact factor: 7.561

6.  Prognostic Value of Peripheral Inflammatory Markers in Preoperative Mucosal Melanoma: A Multicenter Retrospective Study.

Authors:  Yixi Wang; Hao Zhang; Yuhan Yang; Tao Zhang; Xuelei Ma
Journal:  Front Oncol       Date:  2019-10-09       Impact factor: 6.244

Review 7.  Neutrophil Heterogeneity in Cancer: From Biology to Therapies.

Authors:  Pacôme Lecot; Matthieu Sarabi; Manuela Pereira Abrantes; Julie Mussard; Leo Koenderman; Christophe Caux; Nathalie Bendriss-Vermare; Marie-Cécile Michallet
Journal:  Front Immunol       Date:  2019-09-20       Impact factor: 7.561

8.  Prognostic value of systemic inflammatory markers for oral cancer patients based on the 8th edition of AJCC staging system.

Authors:  Sanghoon Lee; Dong Wook Kim; Sunmo Kwon; Hyung Jun Kim; In-Ho Cha; Woong Nam
Journal:  Sci Rep       Date:  2020-07-21       Impact factor: 4.379

9.  The impact of skeletal muscle mass on survival outcome in biliary tract cancer patients.

Authors:  Panita Limpawattana; Daris Theerakulpisut; Kosin Wirasorn; Aumkhae Sookprasert; Narong Khuntikeo; Jarin Chindaprasirt
Journal:  PLoS One       Date:  2018-10-10       Impact factor: 3.240

10.  Prognostic value of neutrophil-to-lymphocyte ratio in melanoma: Evidence from a PRISMA-compliant meta-analysis.

Authors:  Yingguo Ding; Shan Zhang; Jianjun Qiao
Journal:  Medicine (Baltimore)       Date:  2018-07       Impact factor: 1.889

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.