Keywords
oral cancer - prognosis - survival - monocyte - neutrophil-to-lymphocyte ratio
Introduction
Oral cavity is one of the most frequent locations of squamous cell carcinoma in the
head and neck region. Globally, an estimated 300,400 new cases of oral cavity cancer
are diagnosed each year and it is the eleventh leading cause of cancer worldwide.
In the Indian subcontinent oral cancer is a major public health problem and ranks
among the top three types of cancer in the country.[1] Almost 80,000 cases are diagnosed and 50,000 deaths occur annually due to oral cavity
cancer in India. The 5-year survival rate for oral cancer in India is ∼37% (26–45).[2] This indicates that, despite improvement in health infrastructure and treatment
modalities, prognosis from oral cancer remains poor as compared with other Asian countries.[2] Therefore, a low-cost, standardized, reliable, and reproducible prognostic marker
for oral cancer patients is desirable to facilitate individualized treatments and,
thus, better outcomes for the patients.
Inflammation seems to play a critical role in the development and progression of numerous
cancers.[3] Tumor development and progression induced by an inflammatory response is thought
to be mediated by an interaction between proinflammatory cytokines and pathways including
nuclear factor-kappa B (NF-κB) and signal transducer & activator of transcription
3 (STAT3).[4] It has been postulated that the increased release of proinflammatory cytokines produces
a systemic inflammatory response reflected in changes in circulating markers of inflammation,
such as C-reactive protein and white blood cells.[5] There are several lines of evidence to date suggesting that the total white blood
cell count as well as its components, such as neutrophils, lymphocytes, monocytes,
and the neutrophil-to-lymphocyte ratio (NLR) can predict survival in a variety of
malignancies, including oral cavity,[6]
[7] breast cancer,[8] gastric cancer,[9] hepatocellular carcinoma,[10] Hodgkin's lymphoma[11] and lung cancer.[12] However, evidence for the use of hematologic markers of inflammation as predictors
of clinical outcome in oral cavity cancer patients is limited.[6]
[7] Given this background, the main objective of our study was to assess the role of
total and differential leukocyte counts in overall survival of oral cavity cancer
patients. The study had the approval of the Research Ethics Committee of the hospital.
Methods
We retrospectively analyzed the medical records of 471 pathologically proven oral
cavity cancer patients, residents of Mumbai, diagnosed between January 01, 2007 to
December 31, 2008, and who had not received any prior treatment. We retrospectively
collected data from medical records on routine laboratory measurements of white blood
cells (WBC) performed prior to onset of treatment, including the counts of neutrophils,
lymphocytes, and monocytes. All patients were staged according to the sixth edition
of the UICC/AJCC TNM classification system.[13]
[14] In addition, we also collected data on age at diagnosis, sex, primary tumor site,
and pretreatment tumor staging. We retrieved type of treatment received and status
of the patient (Alive/ Dead) at the end of five years from the date of diagnosis from
medical records.
Receiver operating characteristic (ROC) curve analysis to select the most appropriate
cut-off points for the counts of total WBC, neutrophil, lymphocyte, and monocyte,
and NLR was performed to stratify patients at a high risk of malignancy-related death.
We selected the score at the point with both maximum sensitivity and specificity as
the best cut-off value. In survival analysis, overall survival time was defined as
time from diagnosis until death; the follow-up of patients still alive has been censored
at their latest date of follow-up. We generated survival curves by the Kaplan–Meier
method and compared them by the log-rank test. We applied the Cox proportional hazards
model for univariate and multivariate (backward method) analysis to identify prognostic
factors. We performed statistical analyses using SPSS software v17.0 (SPSS, Chicago,
IL).
Results
The patients' characteristics are summarized in [Table 1]. As shown, the median age was 50 years (range: 25–85 years), and the percentage
of males and females were 69.9% and 30.1%, respectively. Out of the 471 patients,
347 (73.67%) were diagnosed at late stages (III and IV) and the other 124 patients
(26.33%) were at early stages (I and II). The median follow-up period was 22 months
(range, 0 to 98 months). The five-year overall survival of the cohort was 49.4% and
stage-wise survival rate for TNM stage I, II, III, and IV patients was found to be
86.4%, 68%, 57.9%, and 33.6% (p < 0.00), respectively.
Table 1
Patients' characteristics
|
Parameter
|
No. of patients
|
Percentage (%)
|
|
Age
|
|
mean
|
50 Years
|
--
|
|
Range
|
25–85 Years
|
--
|
|
Sex
|
|
Male
|
329
|
69.9
|
|
Female
|
142
|
30.1
|
|
T Classification
|
|
T1
|
41
|
8.7
|
|
T2
|
142
|
30.1
|
|
T3
|
56
|
11.9
|
|
T4
|
232
|
49.3
|
|
N Classification
|
|
N0
|
208
|
44.2
|
|
N+
|
263
|
55.8
|
|
M Classification
|
|
M0
|
469
|
99.6
|
|
M1
|
2
|
0.4
|
|
Tumor Stage, AJCC
|
|
I
|
32
|
6.8
|
|
II
|
92
|
19.5
|
|
III
|
76
|
16.1
|
|
IV
|
271
|
57.5
|
Abbreviations: AJCC, American Joint Committee on Cancer.
We determined the cut-off value of total WBC, neutrophil, lymphocyte, monocyte counts,
and neutrophil lymphocyte ratio (NLR) for survival outcomes by ROC curve analyses.
We selected the NLR cut-off point of 2.38 for the survival analyses and divided all
patients into either high (NLR ≥ 2.38) or low (NLR < 2.38) NLR groups. Additionally,
to ensure comparability with other studies, we also conducted an analysis using NLR
cut-off of 5; however, only 72 (15.3%) patients had NLR of ≤ 5. Similarly, we selected
as the optimal cut-off points for survival analyses, a total WBC count of 7.900 × 109/L, neutrophil count of 4.900 × 109/L, lymphocyte count of 1.980 × 109/L, and monocyte count of 0.500 × 109/L.
We performed a univariate analysis of age, gender, overall stage, lymph node involvement,
treatment modality, total WBC count, neutophil count, lymphocyte count, monocyte count,
and NLR to assess their role as prognostic factors for overall survival. Univariate
analysis revealed that lower WBC count (<7.900 × 109/L; p = 0.026), monocyte count (< 0.500 × 109/L; p = 0.001), and NLR level (< 2.38; p < 0.001) were associated with superior survival, but when we used traditional NLR
cut-off of 5, we did not find it to be significantly associated with survival (p = 0.091). In addition, advanced disease (TNM stage, III + IV; p< 0.001) and lymph nodal involvement (p < 0.001) were found to be associated with poorer prognosis. Other factors such as
age, gender, neutrophil count, lymphocyte count, and treatment modality were not significantly
associated with survival of oral cavity cancer patients.
We included all the characteristics, such as age, gender, overall stage, lymph node
involvement, treatment modality, total WBC count, neutophil count, lymphocyte count,
monocyte count, and NLR in the multivariate analysis. The results showed that higher
NLR level (HR = 1.392, 95% CI = 1.045 - 1.855; p< 0.001), monocyte count (HR = 1.385, 95% CI = 1.049 - 1.829; p< 0.001), advanced stage disease (HR = 1.921, 95% CI = 1.193 - 3.092; p < 0.001), and lymph node involvement (HR = 1.715, 95% CI = 1.200 - 2.451; p < 0.001) were independent predictors for poor overall survival of oral cavity cancer
patients ([Table 2]).
Table 2
Univariate and multivariate analysis of prognostic factors for overall survival in
patients with oral cavity
|
Univariate
|
Multivariate
|
|
Parameter
|
HR
(95% CI)
|
p
|
HR
(95% CI)
|
p
|
|
Age, ≥65 years
|
1.088
(0.745 - 1.589)
|
0.664
|
--
|
--
|
|
Sex, (male)
|
1.244
(0.928 - 1.669)
|
0.145
|
--
|
--
|
|
TNM stage (III + IV)
|
3.155
(2.168 - 4.591)
|
0.000**
|
1.921
(1.19 3 - 3.092)
|
0.007**
|
|
Lymph node mets
|
2.492
(1.876 - 3.310)
|
0.000**
|
1.715
(1.200 - 2.451)
|
0.003**
|
|
Neutrophil ≥4.900 109/L
|
1.290
(0.989 - 1.683)
|
0.060
|
--
|
--
|
|
Lymphocyte ≤1.980 109/L
|
1.224
(0.941 - 1.592)
|
0.131
|
--
|
--
|
|
Monocyte ≥0.500 109/L
|
1.558
(1.190 - 2.040)
|
0.001**
|
1.385
(1.049 - 1.829)
|
0.021**
|
|
WBC ≥7.900 109/L
|
1.352
(1.037 - 1.764)
|
0.026**
|
|
0.164
|
|
Neutrophil/ lymphocyte ratio (NLR), ≥2.38
|
1.676
(1.271 - 2.209)
|
0.000**
|
1.392
(1.045 - 1.855)
|
0.024**
|
|
Neutrophil/ lymphocyte ratio (NLR), ≥5
|
1.348
(0.954 - 1.904)
|
0.091
|
--
|
--
|
|
Treatment (single/ multi-modality)
|
0.924
(0.712–1.200)
|
0.555
|
--
|
--
|
Abbreviations: CI, confidence interval; HR, hazard ratio. ** Significant (p < 0.05).
The five-year survival rate of patients with high monocyte count (≥ 0.500 × 109/L) was found to be 43.9%, which was significantly (p < 0.001) less than the 55.4% survival rate for patients with lower monocyte count
([Fig. 1]). Similarly, we found five yearś survival rate for patients with higher (≥ 2.38)
and lower NLR was 42.2% and 58.6%, respectively (p< 0.001) ([Fig. 2]). We categorized patient characteristics including hematological parameters as high
/ low NLR and monocyte counts ([Table 3]). Patients with high NLR level (≥2.38) had a higher incidence of advanced T, N,
and overall stages (p = 0.001, p = 0.015, and p = 0.003, respectively). Lifestyle factors such as tobacco chewing, smoking and alcohol
consumption did not appear to be associated with NLR or monocyte count (p > 0.05).
Fig. 1 Kaplan–Meier survival curves of cumulative survival rates in patients with oral cavity
cancer classified into two groups according to monocyte count.
Fig. 2 Kaplan–Meier survival curves of cumulative survival rates in patients with oral cavity
cancer classified into two groups according to NLR.
Table 3
Baseline clinical characteristics of the 471 Oral cavity carcinoma patients according
to high/ low Neutrophil lymphocyte ratio (NLR) and monocyte count
|
Characteristic
|
NLR < 2.38
(n = 199)
|
NLR ≥2.38
(n = 272)
|
p
|
LM Count
< 500 (109/L)
(n = 206)
|
HM Count
≥ 500 (109/L)
(n = 265)
|
p
|
|
Mean age (years)
|
50.20 ± 12.01
|
51.84 ± 12.48
|
0.152
|
50.37 ± 11.53
|
51.75 ± 12.85
|
0.225
|
|
Tobacco, no. (%)
|
|
Non-chewers
|
82 (41.2)
|
120 (44.1)
|
0.528
|
92 (44.7)
|
110 (41.5)
|
0.493
|
|
Chewers
|
117 (58.8)
|
152 (55.9)
|
--
|
114 (55.3)
|
155 (58.5)
|
--
|
|
Non-smokers
|
144 (72.4)
|
212 (77.9)
|
0.164
|
153 (74.3)
|
203 (76.6)
|
0.559
|
|
Smokers
|
55 (27.6)
|
60 (22.1)
|
--
|
53 (25.7)
|
62 (23.4)
|
--
|
|
Alcohol, no. (%)
|
|
Non-drinker
|
156 (78.4)
|
229 (84.2)
|
0.108
|
171 (83.0)
|
214 (80.8)
|
0.530
|
|
Drinker
|
43 (21.6)
|
43 (15.8)
|
--
|
35 (17.0)
|
51 (19.2)
|
--
|
|
T-classification
|
|
T1–T2
|
105 (52.8)
|
78 (28.7)
|
0.000**
|
86 (47.0)
|
97 (53.0)
|
0.256
|
|
T3–T4
|
94 (47.2)
|
194 (71.3)
|
--
|
120 (58.3)
|
168 (63.4)
|
--
|
|
N-classification
|
|
N0
|
101 (50.8)
|
107 (39.5)
|
0.015**
|
99 (48.1)
|
109 (41.3)
|
0.143
|
|
N+
|
98 (49.2)
|
164 (60.5)
|
--
|
107 (51.9)
|
155 (58.7)
|
--
|
|
Overall stage
|
|
I–II
|
75 (37.7)
|
49 (18.0)
|
0.000**
|
63 (30.6)
|
61 (23.0)
|
0.064
|
|
III–IV
|
124 (62.3)
|
223 (82.0)
|
--
|
143 (69.4)
|
204 (77.0)
|
--
|
|
Treatment
|
|
Uni-modality
|
98 (49.2)
|
127 (46.7)
|
0.583
|
100 (48.5)
|
125 (47.2)
|
0.767
|
|
Dual/ Multi-modality
|
101 (50.8)
|
145 (53.3)
|
--
|
106 (51.5)
|
140 (52.8)
|
--
|
|
Hematological Parameters
|
|
Red blood cell, X106 /lL
|
4.60 ± 0.64
|
4.57 ± 0.70
|
0.145
|
4.52 ± 0.69
|
4.53 ± 0.67
|
0.888
|
|
Hemoglobin, g/dL
|
12.8 ± 2.1
|
12.7 ± 2.2
|
0.528
|
12.7 ± 2.2
|
12.7 ± 2.2
|
0.987
|
|
Hematocrit, %
|
38.6 ± 5.9
|
38.2 ± 6.4
|
0.464
|
38.3 ± 6.2
|
38.4 ± 6.2
|
0.884
|
|
MCV, fL
|
84.4 ± 10.0
|
85.8 ± 9.6
|
0.144
|
85.1 ± 9.3
|
85.2 ± 10.1
|
0.925
|
|
MCH, pg/cell
|
28.0 ± 3.8
|
28.5 ± 3.7
|
0.165
|
28.3 ± 3.7
|
28.3 ± 3.9
|
0.994
|
|
MCHC, g/dL
|
33.1 ± 1.3
|
33.2 ± 1.3
|
0.688
|
33.2 ± 1.3
|
33.1 ± 1.3
|
0.640
|
Abbreviations: HM, high monocyte; LM, low monocyte; MCH, mean corpuscular hemoglobin;
MCHC, mean corpuscular-hemoglobin concentration; MCV, mean corpuscular volume. Ŧ Data
are means ± SD; ** Significant (p < 0.05).
Discussion
The total and differential white blood cell (WBC) count has been historically used
as a marker of infection and inflammation. Nonetheless, its role has gone beyond the
assessment of infectious processes and it has become an important prognostic measurement
of outcomes in cancer treatment. Thus, while a link between inflammation and cancer
has been known for more than a century, compelling recent evidence have suggested
a strong association between pretreatment peripheral inflammatory cells and prognosis
in different kinds of cancers.[6]
[7]
[8]
[9]
[10]
[11]
[12] As part of the functional relevance, inflammatory responses lead to chronic oxidative
stress and generate oxygen free radicals, which have been shown to stimulate cancer
initiation, promotion, and progression.[15]
[16] Here, we have performed a retrospective medical record based study on oral cavity
cancer to evaluate the prognostic values of total WBC, neutrophil, lymphocyte, monocyte
counts, and NLR together with the other clinical factors. Our results confirmed the
previous findings that factors such as absence of nodal involvement and early stage,
were associated with favorable prognosis for oral cavity cancer patients.[17]
[18] More importantly, we found that an elevated neutrophil lymphocyte ratio (NLR) and
monocyte count were significantly associated with poorer overall survival and were
independent of other variables to predict the prognosis for oral cavity cancer patients.
These results were in consonance with other published studies that implicate role
of monocyte count (Tsai et al, n = 213)[6] and NLR (Perisanidis et al, n = 97)[7] in prognostication of oral cavity cancer patients. However, these studies relied
on a relatively smaller sample and the cut-off value for monocyte count was based
on a median value of circulating monocyte count. In the present study, to exclude
empirical bias, we used ROC curve to determine the optimal cut-off value to predict
risk of malignancy related death.
In the present study, we found that monocyte count was an independent prognostic factor
for patients with oral cavity cancer. There is substantial evidence that, in advanced
cancer, the host systemic immune response is an important independent predictor of
outcome, and that pretreatment measurements of the systemic inflammatory immune response
can be used to independently predict cancer survival.[6]
[19] Sasaki and colleagues[20]
[21] studied the pre-operative absolute monocyte count in patients who had liver resection
due to hepatocellular carcinoma, as well as in patients who underwent hepatic surgery
due to colorectal metastasis and found that pretreatment absolute monocyte count was
an independent prognostic indicator of tumor recurrence and survival in patients with
hepatocellular carcinoma. Similarly, absolute monocyte count has been reported to
be independent prognostic indicator for breast cancer,[8] gastric cancer,[9] Hodgkin's lymphoma,[11] Colorectal cancer,[21] and Ovarian cancer.[22]
The exact underlying mechanism explaining the association between the elevated number
of monocytes and unfavorable cancer prognosis is unclear. However, a possible explanation
can be that monocytes secrete various proinflammatory cytokines, such as interleukin
(IL)-1, IL-6, IL-10, and TNF-α, which have been associated with shorter survival and
worse prognosis in malignances.[23]
[24] Moreover, monocytes upon stimulation are known to release monocyte chemo-attractant
protein (MCP-1)-1 and mediate tumor-associated macrophage infiltration in solid tumors,
which could produce a variety of chemokines such as TGF-α, TNF-α, IL-1, and IL-6 to
promote tumorigenesis, angiogenesis, and distant metastasis of malignant tumors.[24]
[25] Further, studies have linked monocyte with an increased number of bone marrow-derived
myelomonocytic cells. These cells infiltrate the tumor and differentiate into tumor-associated
macrophages, which in turn release many angiogenic factors and have been shown to
be associated with poor prognosis in cancers.[24]
[26]
[27]
The other main finding of our analysis was that high pretreatment NLR was significantly
associated with poor survival in oral cavity cancer patients. This result is in accordance
with previous observations on the association between NLR and a variety of cancers
such as lung cancer, colorectal cancer, cholangiocarcinoma, and Pancreatic cancer.[28]
[29]
[30]
[31]
[32] More specifically, in Head and Neck cancers, elevated pretreatment NLR has been
shown to be significantly associated with worse survival in two studies of nasopharyngeal
cancer patients[33]
[34] and only one study of oral cavity cancer patients.[7] In all three studies, NLR cut-off was taken on the basis of either median value
or ROC analysis and none of them have considered traditional NLR cut-off of 5.[7]
[33]
[34] In our study, oral cancer survival was also found to be associated with an ROC-based
NLR cut-off of 2.38, but failed to achieve statistical significance with the traditional
NLR cut-off of 5. This can be due to the small sample size, from which few patients
had an NLR above 5.
Thus, to establish a ROC-based lower NLR cut-off for predicting survival in oral cancer
patients larger, multicenter prospective studies are needed. In our study, we also
assessed the prognostic value of the individual components of NLR, that is, neutrophil
and lymphocyte count. Individually, however, neither was significantly associated
with survival of oral cavity cancer patients. Similarly, Perisanidis et al also reported
a significant relationship between NLR and oral cancer survival but not with its individual
components.[7] It has been suggested that, in cancer patients, NLR is superior to other individual
leukocyte parameters.[35] This superiority of NLR can be attributed to the stability of NLR compared with
the absolute counts that could be altered by various physiological, pathological,
and physical factors. Moreover, NLR may represent the two opposing inflammatory and
immune pathways that exist together in cancer patients.[7] Therefore, NLR can be considered as the balance between pro-tumor inflammatory status
and anti-tumor immune status. Patients with elevated NLR have a relative neutrophilic
leukocytosis and lymphocytopenia, which denotes that the balance is inclined in favor
of pro-tumor inflammatory and is associated with poor outcome.[34]
[35]
The mechanisms underlying the association of high NLR and poor outcome of cancer patients
are poorly understood. One potential mechanism underlying the prognostic impact of
NLR may be an association of high NLR with inflammation. An elevated NLR has been
associated with an increase in the peritumoral infiltration of macrophages and an
increase in interleukin (IL-17).[36] Neutrophils and other cells such as macrophages have been reported to secrete tumor
growth promoting factors, including vascular endothelial growth factor,[37] hepatocyte growth factor,[38] IL-6,[39] IL-8,[40] matrix metalloproteinases,[41] and elastases,[42] and, thus, likely contribute to a stimulating tumor microenvironment. It is a consensus
that the adaptive immune system carries out immune surveillance and can eliminate
newborn tumors, but effective adaptive immune responses are always suppressed in established
tumors through several pathways, including inhibition of dendritic cell differentiation
and activation, infiltration of regulatory T cells.[43] Lymphocytes are crucial components of adaptive immune system, and studies have reported
infiltrating lymphocytes to indicate the generation of an effective antitumor cellular
immune response.[44] A low peripheral lymphocyte level may indicate a poorer lymphocyte-mediated immune
response to tumor and suggests poor prognosis.[45]
[46] NLR may be explained by the diverse effects of neutrophils and lymphocytes on tumor
progression. In vitro studies have shown that the cytolytic activity of lymphocytes
and natural killer cells was suppressed when cocultured with neutrophils, and the
extent of suppression was proportionally enhanced to the addition of neutrophils,[46]
[47]
[48] implying that high NLR was associated with poor prognosis.[33]
Conclusion
We found that both NLR and monocyte counts are independent predictors of overall survival
for patients with oral cavity cancer. Given the low cost, easy accessibility, and
reproducibility of a full blood count, both NLR and monocyte counts seem promising
candidates for use in clinical practice. However, the findings of the study are based
on a retrospective design in a single center, thus, further studies in either multicenter
or prospective manner should be undertaken to validate and determine the clinical
usages of NLR and monocyte count as prognostic markers for oral cavity cancer patients.
