Prognostic biomarkers provide essential information about a patient’s overall outcome. However, existing biomarkers are limited in terms of either sample collection, such as requiring tissue specimens, or the process, such as prolonged time for analysis. In view of the need for convenient and non-invasive prognostic biomarkers for oral cancer, we aimed to investigate the prognostic values of neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, and platelet-to-lymphocyte ratio in patient survival. We also aimed to explore the associations of these ratios with the clinicopathologic characteristics of Japanese oral squamous cell carcinoma patients.
Methods
This study was a non-randomized retrospective cohort study in a tertiary referral center. We included 433 patients (246 men, 187 women) who underwent radical surgery for oral cancers between January 2001 and December 2013. We evaluated various risk factors for poor prognosis including neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, and platelet-to-lymphocyte ratio with univariate and multivariate analyses. The disease-specific survival and overall survival rates of patients were compared among the factors and biomarkers.
Results
In multivariable Cox proportional hazards analysis, high neutrophil-to-lymphocyte ratio (hazard ratio 2.87, 95% confidence interval 1.59–5.19, P < 0.001), moderately or poorly differentiated histology (hazard ratio 2.37, 95% confidence interval 1.32–4.25, P < 0.001), and extranodal extension (hazard ratio 1.95, 95% confidence interval 1.13–3.35, P = 0.016) were independent predictors of disease-specific survival. High neutrophil-to-lymphocyte ratio (hazard ratio 2.30, 95% confidence interval 1.42–3.72, P < 0.001), moderately or poorly differentiated (hazard ratio 1.72, 95% confidence interval 1.07–2.76, P = 0.025), and extranodal extension (hazard ratio 1.79, 95% confidence interval 1.13–2.84, P = 0.013) were independent predictors of overall survival.
Conclusions
Neutrophil-to-lymphocyte ratio might be a potential independent prognostic factor in Japanese oral squamous cell carcinoma patients.
Hinweise
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Abkürzungen
AUC
Area under the curve
DSS
Disease-specific survival
LMR
Lymphocyte-to-monocyte ratio
NLR
Neutrophil-to-lymphocyte ratio
OS
Overall survival
OSCC
Oral squamous cell carcinoma
PLR
Platelet-to-lymphocyte ratio
ROC
Receiver operating characteristic curve
Background
Oral squamous cell carcinoma (OSCC) is the most common tumor of the head and neck region, and occurs predominantly in the oral cavity (90%) [1]. There have been recent improvements in the treatment of advanced OSCC. However, the survival of oral cancer patients has not dramatically improved [2]. Prognostic biomarkers are important for treatment because they provide essential information about the patients’ overall outcome. However, molecular biomarkers that need tissue specimens for analysis impose burden on patients, as it requires an invasive approach for sample collection. The analysis time for tissue biomarkers is also long. Therefore, there is an urgent need for convenient and non-invasive prognostic biomarkers for oral cancer.
It is well known that cancer has a close relationship with inflammation [3]. Inflammatory responses cause tumor progression such as initiation, progression, and metastasis [4]. The peripheral blood cell counts of the lymphocytes, monocytes, neutrophils, and platelets are reported to be associated with prognosis in several cancers [5‐7]. These values can be activated by oxidative stress, chemokines, and cytokines during cancer initiation and progression [8, 9]. One report suggested that leukocytes work differently in patients with cancer and those without [10]. The neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR) are important hematological biomarkers and have been reported to be significant prognostic markers of head and neck cancer [11‐13]. However, the results are controversial. Furthermore, few studies have quantitatively analyzed the usefulness of NLR, LMR, and PLR in predicting the prognosis in a small number of Japanese OSCC patients [14, 15].
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In this study, we retrospectively investigated the prognostic values of NLR, LMR, and PLR in patient survival and their associations with the clinicopathologic characteristics of Japanese OSCC patients.
Methods
This was a non-randomized retrospective cohort study. This study was approved by the institutional review board of the Kobe University Graduate School of Medicine and by the institutional review boards of the participating hospitals (Authorization number: 170086). The patient group included 433 patients (246 men, 187 women) who underwent radical surgery for OSCC between January 2001 and December 2013 at the Department of Oral and Maxillofacial Surgery, Kobe University Hospital. The mean patient age was 66.3 ± 13.5 years (range: 22–98 years). The inclusion criteria were as follows: a histological diagnosis of OSCC and the presence of a previously untreated tumor scheduled for radical surgery at initial visit. Patients with factors that could influence the NLR, LMR, and PLR such as concurrent infections, chronic inflammatory diseases, chronic hematologic diseases, and recent treatment with steroids or immunosuppressive agents were also excluded.
The data assessed for each patient included the sex, age, smoking history, alcohol consumption, performance status (PS), subsite, clinical T classification (Union Internationale Contre le Cancer/American Joint Committee on Cancer [UICC/AJCC] staging system 7th edition), clinical N classification, histological grade (well differentiated, moderately differentiated, or poorly differentiated), surgical margins, number of pathologically metastatic lymph nodes, presence of pathologic extra nodal extension (ENE), and treatment outcome. The endpoints evaluated were; the disease-specific survival (DSS) rates as the primary outcome and the overall survival (OS) rates as the secondly outcome. Survival times were calculated from the date of surgery. The peripheral NLR was calculated as the ratio of the absolute peripheral neutrophil to lymphocyte count; the peripheral LMR was calculated as the ratio of the absolute peripheral lymphocyte to monocyte count, and the peripheral PLR was calculated as the ratio of the absolute peripheral platelet to lymphocyte count. The discriminatory ability of NLR, LMR, and PLR as possible indicators of DSS was evaluated with a receiver operating characteristic (ROC) curve. This ROC curve was used to determine the cutoff values for clinical tests. The area under the resulting curve (AUC) measured the accuracy of the discrimination, ranging from 0.5 to 1. The cutoff value was chosen to minimize the number of false-positive and false-negative results. The patients were divided into two groups (the low group and high group) based on NLR, LMR, and PLR values. The DSS and OS rates of patients were compared among the patient characteristics including the NLR, LMR, and PLR.
The data were introduced into a multivariate Cox proportional hazard model in which patients were divided by age (≤ 64 years vs. ≥ 65 years), PS (0 vs. 1, 2, or 3), subsite (tongue vs. others), T stage (1 or 2 vs. 3 or 4), N stage (0 vs. others), histological grade (well vs. moderately or poorly differentiated), surgical margins (negative vs. close or positive), and number of pathologically metastatic lymph nodes (0 or 1 vs. ≥2).
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Statistical analysis
SPSS 22.0 (SPSS, Chicago, IL) and Ekuseru-Toukei 2012 (Social Survey Research Information Co., Ltd., Tokyo, Japan) were used for the statistical analyses. The association of each variable with the NLR, LMR and PLR were analyzed by the Mann-Whitney U nonparametric test for ordinal variables and the Fisher’s exact test or the Chi-squared test for categorical variables. Cumulative DSS and OS were calculated using the Kaplan–Meier product limit method. Significance among the curves was determined using the log-rank test. Probabilities of less than 0.05 were accepted as significant. All of the variables associated with the DSS or OS were introduced into multivariate Cox proportional hazard models. Hazard ratio (HR) and 95% confidence intervals (CIs) were also calculated.
Results
The mean follow-up time among the 433 patients was 59.1 (range, 1–179) months. During the follow-up period, the 5-year OS rate and DSS were 77.3 and 84.1%. The tongue was the most common site [n = 211 (48.7%)].
The mean NLR, LMR, and PLR were 2.50 ± 1.73, 5.51 ± 3.47, and 143.4 ± 71.7, respectively. The optimal cutoff values of NLR, LMR, and PLR were 2.22, 4.35, and 134.3, respectively. The AUC of the NLR ROC curve was 0.72 (sensitivity, 0.71; specificity, 0.58). The AUC of the LMR ROC curve was 0.66 (sensitivity, 0.62; specificity, 0.62). The AUC of the PLR ROC curve was 0.60 (sensitivity, 0.56; specificity, 0.59).
There were significant differences between the two NLR groups in the presence of pathological multiple lymph node metastases (P = 0.044) in the univariate analysis (Table 1). There were no significant differences in other factors (Table 1). There were significant differences between the patients with high PS (P = 0.002), subsite other than the tongue (P = 0.015), high T stage (P = 0.003), and high N stage (P = 0.007) in the patients with low LMR in the univariate analysis (Table 2). There were no significant differences in other factors (Table 2). There were significant differences between the females (P < 0.001) and no smoking history (P = 0.002) in the high PLR group in the univariate analysis (Table 3). There were no significant differences in other factors (Table 3).
Table 1
Characteristics of patients according to NLR
Variables
NLR
P value
Low, n (%)
High, n (%)
Number of patients
233 (53.8)
200 (46.2)
Sex
Male
142 (60.9)
104 (52.0)
0.065 *
Female
91 (39.1)
96 (48.0)
Age
Range (Years)
27–98
22–92
Mean ± SD
65.7 ± 13.0
67.0 ± 14.0
0.170 **
≥ 64
95 (40.8)
78 (39.0)
0.768 *
≤ 65
138 (59.2)
122 (61.0)
Smoking history
No
112 (48.1)
107 (53.5)
0.179 *
Yes
47 (20.2)
22 (11.0)
Unknown
74 (31.8)
71 (35.5)
Alcohol consumption
No
81 (34.8)
71 (35.5)
0.472 *
Yes
76 (32.6)
55 (27.5)
Unknown
76 (32.6)
74 (37.0)
Performance status
0
131 (56.2)
96 (48.0)
0.121 *
≥ 1
101 (43.4)
101 (50.5)
unknown
1 (0.4)
3 (1.5)
Subsite
Tongue
116 (49.8)
95 (47.5)
0.700 *
Other
117 (50.2)
105 (52.5)
T classification
1, 2
167 (71.7)
134 (67.0)
0.297 *
3, 4a/b
66 (28.3)
66 (33.0)
N classification
0
168 (72.1)
128 (64.0)
0.078 *
Others
65 (27.9)
72 (36.0)
Pathological status
Pathological extranodal extensions
ENE -
44 (57.9)
45 (54.9)
0.750 *
ENE +
32 (42.1)
37 (45.1)
Number of pathological lymph node metastases
0, 1
101 (69.2)
72 (57.1)
0.044 *
≥ 2
45 (30.8)
54 (42.9)
Surgical margins
Negative
180 (77.3)
147 (73.5)
0.358 *
Involved margins
49 (21.0)
50 (25.0)
Unknown
4 (1.7)
3 (1.5)
Histological differentiation
Well differentiated
135 (57.9)
126 (63.0)
0.372 *
Moderately or poorly differentiated
95 (40.8)
73 (36.5)
Unknown
3 (1.3)
1 (0.5)
ENE Extranodal extension; NLR Neutrophil-lymphocyte ratio
*: Fisher’s exact test **: Mann–Whitney U test
Table 2
Characteristics of patients according to LMR
Variables
LMR
P value
Low, n (%)
High, n (%)
Number of patients
180 (41.6)
253 (58.4)
Sex
Male
112 (62.2)
134 (53.0)
0.062 *
Female
68 (37.8)
119 (47.0)
Age
Range (Years)
22–92
23–98
Mean ± SD
67.8 ± 12.9
65.3 ± 13.8
0.057 **
≥ 64
66 (36.7)
107 (42.3)
0.273 *
≤ 65
114 (63.3)
146 (57.7)
Smoking history
No
94 (52.2)
125 (49.4)
0.680 *
Yes
32 (17.8)
37 (14.6)
Unknown
54 (30.0)
91 (36.0)
Alcohol consumption
No
63 (35.0)
89 (35.2)
0.282 *
Yes
63 (35.0)
68 (26.9)
Unknown
54 (30.0)
96 (37.9)
Performance status
0
78 (43.3)
149 (58.9)
0.002 *
≥ 1
100 (55.6)
102 (40.3)
Unknown
2 (1.1)
2 (0.8)
Subsite
Tongue
75 (41.7)
136 (53.8)
0.015 *
Other
105 (58.3)
117 (46.2)
T classification
1, 2
111 (61.7)
190 (75.1)
0.003 *
3, 4a/b
69 (38.3)
63 (24.9)
N classification
0
110 (61.1)
186 (73.5)
0.007 *
Others
70 (38.9)
67 (26.5)
Pathological status
Pathological extranodal extension
ENE -
41 (52.6)
48 (60.0)
0.423 *
ENE +
37 (47.4)
32 (40.0)
Number of pathological lymph node metastases
0, 1
74 (58.3)
99 (68.3)
0.101 *
≥ 2
53 (41.7)
46 (31.7)
Surgical margins
Negative
133 (73.9)
194 (76.7)
0.417 *
Involved margins
45 (25.0)
54 (21.3)
Unknown
2 (1.1)
5 (2.0)
Histological differentiation
Well differentiated
107 (59.4)
154 (60.9)
0.736 *
Moderately or poorly differentiated
72 (40.0)
96 (37.9)
Unknown
1 (0.6)
3 (1.2)
ENE Extranodal extension; LMR Lymphocyte-to-monocyte ratio
*: Fisher’s exact test **: Mann–Whitney U test
Table 3
Characteristics of patients according to PLR
Variables
PLR
P value
Low, n (%)
High, n (%)
Number of patients
240 (55.4)
193 (44.6)
Sex
Male
156 (65.0)
90 (46.6)
< 0.001 *
Female
84 (35.0)
103 (53.4)
Age
Range (Years)
27–98
22–92
Mean ± SD
66.1 ± 12.7
66.6 ± 14.4
0.253 **
≥ 64
100 (41.7)
73 (37.8)
0.431 *
≤ 65
140 (58.3)
120 (62.2)
Smoking history
No
115 (47.9)
104 (53.9)
0.002 *
Yes
51 (21.3)
18 (9.3)
Unknown
74 (30.8)
71 (36.8)
Alcohol consumption
No
84 (35.0)
68 (35.2)
0.473 *
Yes
78 (32.5)
53 (27.5)
Unknown
78 (32.5)
72 (37.3)
Performance status
0
135 (56.3)
92 (47.7)
0.081 *
≥ 1
103 (38.8)
99 (41.3)
Unknown
2 (0.8)
2 (1.0)
Subsite
Tongue
126 (52.5)
85 (44.0)
0.083 *
Other
114 (47.5)
108 (56.0)
T classification
1, 2
176 (73.3)
125 (64.8)
0.059 *
3, 4a/b
64 (26.7)
68 (35.2)
N classification
0
168 (70.0)
128 (66.3)
0.467 *
Others
72 (30.0)
65 (33.7)
Pathological status
Pathological extranodal extension
ENE -
49 (57.6)
40 (54.8)
0.750 *
ENE +
36 (42.4)
33 (45.2)
Number of pathological lymph node metastases
0, 1
94 (63.9)
79 (63.2)
0.900 *
≥ 2
53 (36.1)
46 (36.8)
Surgical margins
Negative
184 (76.7)
143 (74.1)
0.421 *
Involved margins
51 (21.3)
48 (24.9)
Unknown
5 (2.1)
2 (1.0)
Histological differentiation
Well differentiated
142 (59.2)
119 (61.7)
0.691 *
Moderately or poorly differentiated
95 (39.6)
73 (37.8)
Unknown
3 (1.3)
1 (0.5)
ENE Extranodal extension; PLR Platelet-to-lymphocyte ratio
*: Fisher’s exact test **: Mann–Whitney U test
Univariate analysis showed that high T stage (P < 0.001), high N stage (P < 0.001), high NLR (P < 0.001), low LMR (P < 0.001), high PLR (P = 0.044), ENE (P = 0.004), pathological multiple lymph node metastases (P < 0.001), involved margins (P = 0.030), and moderately or poorly differentiated histology (P < 0.001) were associated with poor 5-year DSS (Table 4). Univariate analysis showed that high PS (P = 0.025), high T stage (P < 0.001), high N stage (P < 0.001), high NLR (P < 0.001), low LMR (P = 0.001), ENE (P = 0.012), pathological multiple lymph node metastases (P < 0.001), involved margins (P = 0.043), and moderately or poorly differentiated histology (P = 0.001) were associated with poor 5-year OS (Table 4).
Table 4
Characteristics of patients according to DSS and OS
Variables
n (%)
5-year DSS (%)
P value
5-year OS (%)
P value
Sex
Male
246 (56.8)
83.1
0.684 *
74.6
0.126 *
Female
187 (43.2)
84.8
80.5
Age
Range (Years)
22–98
Mean ± SD
66.3 ± 13.5
≥ 64
173 (40.0)
79.9
0.120 *
73.7
0.608 *
≤ 65
260 (60.0)
86.6
79.6
Smoking history
No
219 (50.6)
88.2
0.548 *
82.5
0.179 *
Yes
69 (15.9)
85.3
76.7
Unknown
145 (33.5)
Alcohol consumption
No
152 (35.1)
83.9
0.105 *
77.3
0.391 *
Yes
131 (30.3)
91.2
84.6
Unknown
150 (34.6)
Performance status
0
227 (52.4)
85.2
0.274 *
79.6
0.025 *
≥ 1
202 (46.7)
81.9
74.3
unknown
4 (0.9)
Subsite
Tongue
211 (48.7)
85.4
0.311 *
80.2
0.083 *
Other
222 (51.3)
82.2
73.9
T classification
1, 2
301 (69.5)
88.5
< 0.001 *
83.1
< 0.001 *
3, 4a/b
132 (30.5)
72.2
62.4
N classification
0
296 (68.4)
91.6
< 0.001 *
85.6
< 0.001 *
Others
137 (31.6)
66.4
58.5
NLR
Low (2.22 <)
233 (53.8)
91.4
< 0.001 *
84.6
< 0.001 *
High (2.22 ≥)
200 (46.2)
75.5
68.8
LMR
Low (4.35 <)
253 (58.4)
76.3
< 0.001 *
70.0
0.001 *
High (4.35 ≥)
180 (41.6)
89.1
82.1
PLR
Low (134.3 <)
240 (55.4)
86.6
0.044 *
78.4
0.232 *
High (134.3 ≥)
193 (44.6)
80.6
75.6
Pathological status
Pathological extra nodal metastasis
ENE -
89 (56.3)
72.8
0.004 *
63.7
0.012 *
ENE +
69 (43.7)
50.7
42.4
Number of pathological lymph node metastases
0, 1
173 (63.6)
84.7
< 0.001 *
78.1
< 0.001 *
≥ 2
99 (36.4)
60.8
50.1
Surgical margins
Negative
314 (72.5)
85.5
0.030 *
78.7
0.043 *
Involved margins
112 (25.9)
79.1
72.1
unknown
7 (1.6)
Histological differentiation
Well differentiated
261 (60.3)
91.5
< 0.001 *
83.3
0.001 *
Moderately or poorly differentiated
168 (38.8)
71.7
67.0
unknown
4 (0.9)
DSS Disease- specific survival; ENE Extranodal extension; LMR Lymphocyte-to-monocyte ratio; NLR Neutrophil-to-lymphocyte ratio; OS Overall survival; PLR Platelet-to-lymphocyte ratio
*: Log-rank test
The 5-year DSS rates of patients with high and low NLR were 75.5 and 91.4%, respectively (Fig. 1). The 5-year OS rates of patients with high and low NLR were 68.8 and 84.6%, respectively. The 5-year DSS rates of patients with high and low LMR were 89.1 and 76.3%, respectively (Fig. 2). The 5-year OS rates of patients with high and low LMR were 82.1 and 70.0%, respectively. The 5-year DSS rates of patients with high and low PLR were 80.6 and 86.6%, respectively (Fig. 3). The 5-year OS rates of patients with high and low PLR were 75.6 and 78.4%, respectively.
×
×
×
In multivariable Cox proportional hazard analysis, high NLR (Hazard ratio, HR 2.87; 95% confidence interval, CI 1.59–5.19; P < 0.001), moderately or poorly differentiated histology (HR 2.37, 95% CI 1.32–4.25, P < 0.001), and ENE (HR 1.95, 95% CI 1.13–3.35, P = 0.016) were independent predictors of DSS (Table 5). Also, high NLR (HR 2.30, 95% CI 1.42–3.72, P < 0.001), moderately or poorly differentiated (HR 1.72, 95% CI 1.07–2.76, P = 0.025), and ENE (HR 1.79, 95% CI 1.13–2.84, P = 0.013) were independent predictors of OS (Table 6).
Table 5
Results of multivariate Cox proportional hazards analysis of predictors of disease-specific survival
Variable
P value
Hazards ratio
95% CI
Lower
Upper
High NLR (2.22 ≥)
< 0.001
2.87
1.59
5.19
Moderately or poorly differentiated histology
< 0.001
2.37
1.32
4.25
Extranodal extension
0.016
1.95
1.13
3.35
CI Confidence interval; NLR Neutrophil-to-lymphocyte ratio
Table 6
Results of multivariate Cox proportional hazards analysis of predictors of overall survival (OS)
Variable
P value
Hazards ratio
95% CI
Lower
Upper
High NLR (2.22 ≥)
< 0.001
2.30
1.42
3.72
Moderately or poorly differentiated histology
0.025
1.72
1.07
2.76
Extra nodal extension
0.013
1.79
1.13
2.84
CI Confidence interval; NLR Neutrophil-to-lymphocyte ratio
Discussion
We successfully investigated the prognostic values of NLR, LMR, and PLR in patient survival and their associations with the clinicopathologic characteristics of Japanese OSCC patients. In particular, high NLR was associated with poor prognosis.
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The association between NLR and prognostic factors have been reported in various cancers [6, 16]. The measurement of NLR is very accessible and affordable because blood sampling is used. Therefore, NLR could be used as a simple indicator of systemic inflammatory responses in cancer patients. Neutrophils secrete matrix metalloproteinase 9 to promote carcinogenesis and tumor cell proliferation into the cancer microenvironment [17, 18]. In contrast, lymphocytes suppress tumor progression and are associated with an increased survival in various cancers [19, 20]. In this study, like other reports, a high NLR was associated with poor DSS and OS [15, 21, 22]. In multivariable Cox proportional hazards analysis, high NLR (HR 2.87) was an independent predictor of poor prognosis. The cutoff value of NLR ranged from 1.77 to 5 [23]. In Japan, Nakashima et al. and Sano et al. reported that the cutoff values were 2.4 and 2.36, respectively [15, 24]. In this study, the cutoff value was 2.22, like in these reports. The association between NLR and clinicopathological factors such as lymph node metastasis, T stage, differentiation, and perineural invasion was reported [23]. In this study, there were significant differences in the presence of pathological multiple lymph node metastases in the patients with high NLR like in several reports [14, 21, 22]. Therefore, NLR may be useful in predicting multiple lymph node metastasis.
The association between LMR and prognostic factors were reported in head and neck cancers [12]. Ong et al. reported that low pretreatment LMR indicated poor survival in patients with early tongue cancer [24]. In this study, low LMR was associated with poor DSS and OS like their report. A low LMR may mean a relative decrease in lymphocytes and increase in monocytes. The decreasing lymphocytes may be related to high NLR or high PLR. Tsai et al. reported that a higher pretreatment count of circulating monocytes was independently associated with poor prognosis in patients with oral cancer [25]. Chronic inflammation including cancer increases the monocyte count by the secretion of various cytokines such as TNF-α, IL-1, and IL-6 [26]. Generally, the monocytes differentiate into macrophages. Pollard et al. reported that an increased number of tumor-associated macrophages was associated with poor prognosis in cancers [27]. The cutoff value of LMR ranged from 2.35 to 5.22 [12, 24]. In this study, the cutoff value was 4.35 like these reports.
The relationship between PLR and poor prognosis is controversial. Several investigators suggested that a high PLR indicated poor prognosis in patients with head and neck SCC [13, 24]. In this study, a high PLR was associated with poor DSS. In contrast, Yu et al. indicated that preoperative PLR was not associated with survival or relapse in oral, pharyngeal, and lip cancer [28]. There are several possibilities, although the exact mechanism of the association between a high PLR and poor prognosis is not clear. Platelets can promote tumor progression by increasing angiogenesis through secretion of vascular endothelial growth factor, and invasion, and metastasis through epithelial-mesenchymal transition [13, 29‐32]. The cutoff value of PLR ranged from 82 to 150 [13]. In patients with oral cancer, Chen et al. and Ong et al. reported that the cutoff values were 135 and 129 [24, 33]. In this study, the cutoff value was 134 like those reports. In multivariable Cox proportional hazards analysis of this study, a low LMR and high PLR were not independent predictors of poor prognosis. Therefore, unlike NLR and other factors, LMR and PLR may not be useful in Japanese OSCC patients.
This study had several limitations. First, this study was conducted in Japanese OSCC patients. Each cutoff value was different from other studies. Therefore, it may be clinically difficult to be used in patients of other countries. Second, the present study was retrospective and nonrandomized. Therefore, bias could not be completely excluded, although multivariate analysis was performed to decrease the effect of confounding factors as much as possible. Future research should involve a large-scale prospective cohort study to evaluate predictors of prognosis and NLR, LMR, or PLR.
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Conclusions
High NLR, moderately or poorly differentiated histology, and ENE were independent predictors of DSS and OS. In particular, high NLR was associated with poor prognosis. The NLR might be a potential independent prognostic factor in Japanese OSCC patients.
This study was approved by the institutional review board of Kobe University Graduate School of Medicine and by the institutional review boards of the participating hospitals. Informed consent from participants was waived, as this is a retrospective study. Instead, we published the information regarding this study and granted occasions of refusing to participate in this study.
Consent for publication
Not applicable.
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Competing interests
All authors declare that they have no conflict of interest.
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Frauen mit unbehandelter oder neu auftretender Hypertonie haben ein deutlich erhöhtes Risiko für Uterusmyome. Eine Therapie mit Antihypertensiva geht hingegen mit einer verringerten Inzidenz der gutartigen Tumoren einher.
Nach einer Prostatabiopsie treten häufig Probleme beim Wasserlassen auf. Ob sich das durch den periinterventionellen Einsatz von Alphablockern verhindern lässt, haben australische Mediziner im Zuge einer Metaanalyse untersucht.
Trastuzumab deruxtecan scheint auch jenseits von Lungenkrebs gut gegen solide Tumoren mit HER2-Mutationen zu wirken. Dafür sprechen die Daten einer offenen Pan-Tumor-Studie.
Frauen mit lokalem oder metastasiertem Brustkrebs, die Statine einnehmen, haben eine niedrigere krebsspezifische Mortalität als Patientinnen, die dies nicht tun, legen neue Daten aus den USA nahe.
Update Onkologie
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