Lymph Nodes in Oral Cancer

8/4/2019 Lymph Nodes in Oral Cancer

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Lymph Node Density Is a Significant

Predictor of Outcome in PatientsWith Oral CancerZiv Gil, MD, PhD1; Diane L. Carlson, MD2; Jay O. Boyle, MD1; Dennis H. Kraus, MD1; Jatin P. Shah, MD1;

Ashok R. Shaha, MD1; Bhuvanesh Singh, MD1; Richard J. Wong, MD1; and Snehal G. Patel, MD1

BACKGROUND: The impact of lymph node metastases on prognosis in patients with oral cavity squamous

cell carcinoma (OSCC) has been well recognized. However, accurate stratification of risk for recurrence

among patients with lymph node metastases is difficult based on the existing staging systems. In the cur-

rent study, the utility of lymph node density (LND) was evaluated as an alternative method for predictingsurvival. METHODS: Three hundred eighty-six patients who underwent neck dissection were included. The

median follow-up was 67 months. Five-year overall survival (OS), disease-specific survival (DSS), and

locoregional failure (LRF) rates were calculated using the Kaplan-Meier method. LND (number of positive

lymph nodes/total number of excised lymph nodes) and tumor-node-metastasis (TNM) staging variables

were subjected to multivariate analysis. RESULTS: Using the median (LND0.06) as the cutoff point, LND

was found to be significantly associated with outcome. For patients with LND 0.06, the OS was 58 per-

cent versus 28 percent for patients with LND >0.06 (P < .001). Similarly, the DSS for patients with LND

0.06 was 65 percent and was 34 percent for those with LND >0.06 (P < .001). On univariate analysis,

pathologic T and N classification, extracapsular spread, and LND were found to be significant predictors of

outcome (P< .001). However, on multivariate analysis, LND remained the only independent predictor of OS

(P .02; hazards ratio, 2.0), DSS (P .02; hazards ratio, 2.3), and LRF (P .005; hazards ratio, 4.1). LND

was also found to be the only significant predictor of outcome in patients receiving adjuvant radiotherapy

(P < .05). Within individual subgroups of pN1 or pN2 patients, LND reliably stratified patients according to

their risk of failure (P < .05). CONCLUSIONS: After surgery for OSCC, pathologic evaluation of the neck

using LND was found to reliably stratify the risk of disease recurrence and survival. Cancer 2009;115:570010.

VC 2009 American Cancer Society.

KEY WORDS: squamous cell carcinoma, head and neck, tongue, survival, neck dissection.

Squamous cell carcinoma of the oral cavity (OSCC) is one of the common malignant tumors of the

head and neck worldwide. The management of OSCC is largely surgical and adjuvant treatment including

radiotherapy or chemoradiation is used for patients with advanced stage tumors.1,2 Because adjuvant

therapy may induce severe toxic effects, a significant challenge is to find a reliable method for stratifying

patients for the risk of tumor recurrence immediately after surgery.

Received: September 23, 2008; Revised: November 25, 2008; Accepted: January 5, 2009

Published online August 18, 2009 in Wiley InterScience (www.interscience.wiley.com)

DOI: 10.1002/cncr.24631, www.interscience.wiley.com

Corresponding author: Ziv Gil, MD, PhD, Skull Base Service, Department of Otolaryngology Head and Neck Surgery, Tel Aviv Sourasky Medical

Center, Tel Aviv 64239, Israel; Fax (011) 972-3-6973543; [email protected].

1Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, New York; 2Department of Pathology, Memorial Sloan-Kettering Cancer

Center, New York, New York

We thank Nancy Bennett for her editorial assistance and Maria Coleman and Dr. Pen-Yuan Chu for their assistance in collecting the data.

5700 Cancer December 15, 2009

Original Article


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The conventional tumor-node-metastasis (TNM)

staging system quantifies lymph node disease according to

the number, size, and laterality of positive cervical lymph

nodes.3 This system factors the lymph node status into

6 categories: N0, N1, N2a, N2b, N2c, and N3. The pres-ence of 1 or more positive lymph nodes is a significant pre-

dictor of poor outcome. However, modern studies using

multivariate analysis report that, among patients with posi-

tive neck metastases, lymph node stage does not necessarily

predict prognosis, especially after adjuvant radiotherapy.4-8

The extent of neck dissection, surgical technique,

and the level of histopathologic scrutiny determine the

degree to which the regional lymph nodes are examined

for neck metastasis and, hence, the probability of identify-

ing metastasis in lymph nodes at risk.9,10 Therefore, these

factors can be expected to determine the pN status (nega-tive or positive) and the pN stage of the neck disease.

Recently, lymph node density (LND) (the number of pos-

itive lymph nodes/total number of excised lymph nodes)

has emerged as an alternative staging system for predicting

survival after surgery for carcinoma of the bladder11 and

esophagus.12 In this system, the ratio of positive lymph

nodes to the total number of excised lymph nodes was

found to be superior to conventional TNM lymph node

staging in predicting survival.13,14 Because limited lymph

node dissection may result in pathologic understaging,

LND attempts to compensate for this factor by recapitu-

lating 2 pieces of information: the extent of cancer spread

to the neck (number of positive lymph nodes) and the

extent of surgical lymph node clearance or sampling (total

number of lymph nodes removed during surgery). The

purpose of this study was to evaluate the utility of LND as

a potential prognostic predictor in patients with OSCC.

MATERIALS AND METHODS

Patients and Methods

Our study cohort included 386 patients treated with pri-

mary surgery, with or without adjuvant radiotherapy,

between 1986 and 1996 for OSCC. During this period,

adjuvant chemoradiotherapy was not yet used. Thus, this

provides a relatively more uniform cohort of patients than

could be expected from more recent years. All patients

underwent a standardized modified radical neck dissec-

tion involving levels I to IV or I to V as described by the

American Head and Neck Society.15 The type of neck dis-

section was prespecified in all patients before surgery. One

hundred ninety-five patients (50.5 percent) died of their

disease, 15 (3.9 percent) of them with distant metastases.

Table 1 presents demographic and clinical data on thesepatients. The follow-up interval ranged from 4 to 184

months, with a median of 67 months.

Histopathologic Analysis

Lymph nodes were evaluated for metastasis by patholo-

gists at the Memorial Sloan-Kettering Cancer Institute.

All specimens were re-analyzed and evaluated by a single

pathologist (D.L.C.) who was blinded to the pathology

report. Overall, 5877 lymph nodes were evaluated, 457 of

which were positive.Specimen dissection and tissue sampling of the pri-

mary tumor were performed in accordance with the cur-

rent guidelines for the histopathologic assessment of head

and neck cancer carcinoma.16 Neck dissection specimens

were submitted en block with metal tags attached desig-

nating the levels. Lymph nodes were detected by palpa-

tion. All lymph nodes identified by the pathologist were

submitted for analysis. Lymph nodes were defined as

aggregates of encapsulated lymphoid tissue of any size,

which had a peripheral sinus. Extracapsular spread (ECS)

was defined as tumor extension beyond the lymph node

capsule with a desmoplastic stromal response. Each lymph

node was sectioned every 2 mm, put in a different cassette,

and embedded in paraffin. Sectioning was performed at

200-lm intervals into the block. Lymph nodes with ECS

were representatively sectioned. There were 95 patients

with 173 lymph nodes that had evidence of ECS. Of

those, 100 lymph nodes (58 percent) had microscopic

extracapsular extension and 73 (42 percent) demonstrated

macroscopic extension.3

Statistical Analysis

Five-year overall survival (OS), disease-specific survival

(DSS), and locoregional control rates were calculated

using the Kaplan-Meier method, and the difference in

survival rate was assessed by the log-rank test.17 OS was

measured from the date of surgery to the date of death or

last follow-up. For DSS, the patients who died from

causes other than OSCC were censored at the time of

Lymph Node Density and Survival in Oral Cancer/Gil et al

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death. The variables that had prognostic potential sug-

gested by univariate analysis were subjected to multivari-

ate analysis with the Cox proportional hazards regression

model.18 All statistics were 2-sided (JMP; SAS Institute

Inc, Cary, NC). A value ofP< .05 was considered to indi-

cate statistical significance. Variables used to stratify

lymph node metastases included the total number of

lymph nodes dissected, the number of positive lymph

nodes, pN stage (pN0, pN1, pN2a, pN2b, pN2c, and

pN3), ECS of tumor, and the LND. The sixth edition of

the TNM staging system for OSCC was used for staging.3

LND distribution was evaluated as a continuous variable,and the active data plot was best fitted by 4 Gaussian

equations using chi-square analysis (Microcal Origin;

Microcal Software Inc, Northampton, Mass). For analysis

of outcome, an LND cutoff point of or > the median

distribution (LND0.06) was used. Other cutoff points

tested were the intersection of the first and second Gaus-

sian equations (LND 0.05), the second and third Gaus-

sian equations (LND 0.076), or the third and fourth

Gaussian equations (LND 0.1). The 0.06 cutoff was

selected because the results of exploratory analysis demon-

strated no significant survival advantages over the otherratios, except for risk stratification among a subgroup of

patients with pN2 disease and those undergoing therapeu-

tic neck dissections, for whom a cutoff point of 0.1 was

found to be a better predictor of outcome. Correlation

analysis was performed using Pearson regression

coefficient.

The study was approved by the institutional review

board committee.

RESULTSKaplan-Meier estimates of 5-year OS and DSS rates were

61 percent and 70 percent, respectively. The management

and outcome of the entire cohort of 386 patients included

in the current study is summarized in Figure 1. On histo-

pathologic examination, 167 (43 percent) of the patients

had lymph node-positive disease. The 5-year OS rate for

patients with pathologically negative neck lymph nodes

was 76 percent and that for patients with positive lymph

nodes was 42 percent (P< .0001). The 5-year DSS of

patients with pathologically negative neck lymph nodes

was 85 percent and that for patients with positive lymph

nodes was 50 percent (P< .0001). Figure 2 shows the

Kaplan-Meier curves of OS and DSS according to the

lymph node (N) status.

Patients were further analyzed on the basis of the

pathologic status of their lymph nodes at the time of sur-

gery using the American Joint Committee on Cancer

(AJCC) TNM classification system. There were 219

patients with pN0 disease (57 percent), 72 patients with

Table 1. Patient Demographics

Variable No. ofPatients

%

Mean age, y 58 14 (range, 14-88) 386 100

Gender Male 227 59Female 159 41

Tobacco exposure No 54 33

Yes 258 67

Alcohol exposure No 68 18

Yes 189 82

Site Oral tongue 175 45

Floor of mouth 79 20

Upper gum 4 1

Lower gum 66 17

Hard palate 2 1

Retromolar trigone 36 9

Buccal mucosa 24 6

Treatment Surgery 162 42

Surgery and

adjuvant radiation

224 58

Type of neckdissection

Elective 264 68Therapeutic 122 32

Extent of neck

dissection

Selective neck

dissection

229 59

Modified radical

neck dissection

65 17

Radical neck

dissection

50 13

Bilateral neck

dissection

46 12

T classification 1 56 15

2 168 44

3 70 18

4 92 24

N classification N0 219 57

N1 72 19

N2a 2 1N2b 83 22

N2c 8 2

N3 2 1

Overall TNM stage I 44 11

II 103 27

III 90 23

IV 149 39

Follow-up of all

patients, mo

Mean: 65 49 219 57

Median: 67

Range: 4-184

Follow-up of

N patients, mo

Mean: 51 48 167 43

Median: 24

Range: 4-184

indicates positive; TNM, tumor-node-metastasis.

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pN1 disease (18.5 percent), 93 patients with pN2 disease

(24 percent), and 2 patients with pN3 disease (0.5 per-

cent). The group of patients with N-positive disease

(n167) was analyzed to identify prognostic predictors

that reliably stratify the risk for adverse outcome within

this group. Among these patients, the number of lymph

nodes removed ranged from 6 to 114 (mean, 35 19

lymph nodes) and the number of positive lymph nodes

was between 1 and 22 (mean, 2.72.8 lymph nodes).

LND was calculated as the ratio of positive lymph nodes

to the total number of lymph nodes removed. The distri-

bution of LND among the study population is shown in

Figure 3A. The LND frequency distribution could be reli-

ably fit by 4 Gaussian equations (P< .05). The median

LND was 0.06. The remainders of the parameters for

each of the 4 Gaussian equations are depicted in Figure

3A. The distribution of LND according to pN classifica-

tion is shown in Figure 3B. In the pN1 group (n 72),

the mean LND was 0.05 0.03 (range, 0.018-0.19); in

the pN2 group (n93), the mean LND was 0.12 0.09

(range, 0.01-0.5); and in the N3 group (n2), the mean

LND was 0.19 0.18 (range, 0.06-0.32). Statistical anal-

ysis demonstrated a significant difference in LND distri-

bution between the different pN classification groups (P

< .0001).

We next investigated whether an LND model can be

used to predict patient outcome. On univariate analysis,

pathologic T classification, pN classification, ECS, num-

ber of positive lymph nodes, and LND were found to be

significant predictors of outcome (P< .001). The total

number of excised lymph nodes was not found to be asso-

ciated with survival. An increase in the pN classification

was associated with decreased 5-year OS and DSS rates

(Fig. 4A and 4B, respectively). Similar to pN classifica-

tion, LND was also found to be significantly associated

with 5-year OS and DSS (Figs. 4C-4F). For patients with

LND0.06, the 5-year OS rate was 58 percent, versus 28

percent for patients with LND>0.06 (P< .001), as dem-

onstrated by the Kaplan-Meier curves. Similarly, the 5-

year DSS rate was 65 percent for patients with LND

0.06, versus 34 percent for patients with LND>0.06 (P

< .001). Based on the frequency distribution of LND,

FIGURE 2. Kaplan-Meier curves of overall and disease-spe-

cific survival are shown according to the lymph node (N) sta-

tus. The difference in the survival rate was assessed using the

log-rank test (P < .0001). Red line indicates pathologic neck

status (pN) negative (-); green line, pN positive ().

FIGURE 1. The (A) management and (B) outcome of 386

patients who participated in the study are shown. cN indi-

cates clinical lymph node (N) status (negative [-] or positive

[]); pN, pathologic neck status (negative or positive); END,

elective neck dissection; TND, therapeutic neck dissection;

OS, overall survival; DSS, disease-specific survival.

Lymph Node Density and Survival in Oral Cancer/Gil et al

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analysis was performed with the data set using an LND

separation point of 0.05, 0.076, and 0.1. These analyses

yielded similar results (P< .001).

To investigate whether LND predicts the prognosis

of patients with positive cervical lymph nodes, we first cre-

ated a multivariate model with all relevant variables except

LND and then added LND to the model. The variables

compared were T classification, pN classification, overall

pathologic stage, ECS, total number of lymph nodes

excised, and total number of positive cervical lymph

nodes. On the first model (without LND), pN classifica-

tion was found to be the only significant predictor of OS

(P .03) and DSS (P .04). However when LND with a

separation point of 0.06 (median value) was introduced to

the multivariate model, the only significant predictor of

outcome was LND (OS, P .02; DSS, P .02; and

locoregional control, P .005), whereas the traditional

variables were not found to be independent predictors of

survival (Tables 2-4). In all analyses (of OS, DSS, and

locoregional control), the whole model proportional haz-

ards fits (-log likelihood and Pvalue) were better for the

model including LND than the model without LND

(Table 5). Similarly, when classification of the neck dis-

ease to N1, N2 and N3, was added to the model as an in-

dependent variable instead of pN classification, LND

remained the only significant predictor of outcome. In

addition, when patients with pN2 and pN3 disease were

grouped together, LND remained the only significant in-

dependent predictor of outcome (P< .05). We also used

3 other separation points in this analysis, as suggested by

the Gaussian function fit of the LND distribution: 0.05,

0.076, and 0.1. These analyses yielded similar results;however, the 0.1 cutoff did not reach statistical signifi-

cance on multivariate analysis for DSS.

To further assess the ability of LND to predict treat-

ment response in a more homogeneous population and to

account for the potential impact of adjuvant treatment,

only those patients who receive postoperative radiother-

apy were subjected to multivariate analysis (n154).

Also in this subpopulation, LND was found to be the only

independent predictor of outcome on multivariate analy-

sis (P< .05).

The majority of the patients without clinical orradiologic evidence of neck metastases (N-) underwent

selective neck dissection involving levels I to IV (80 per-

cent). The remaining patients underwent comprehensive

neck dissection. For patients with clinical evidence of

lymph node metastases (N), we performed a modified

radical neck dissection involving levels I to V in 84 per-

cent of the patients. Table 6 shows the different levels dis-

sected in patients undergoing elective or therapeutic neck

dissection. The multivariate analysis was repeated for elec-

tive neck dissections (clinically negative necks) and thera-

peutic neck dissections (clinically positive necks)

separately. LND was found to be the most significant pre-

dictor of outcome for patients undergoing elective neck

dissection (P< .004). For therapeutic neck dissections,

none of the variables reached statistic significant when a

LND of 0.06 was used as the cutoff point. However,

when a separation point of 0.1 was used, LND remained

the only significant predictor of outcome (P< .04). Table

6 shows an increase in the yield of positive lymph nodes

and in the overall number of lymph nodes when therapeu-

tic neck dissection was used compared with elective neck

dissection (P< .0001), with no change in LND noted.

Finally, individual pN subgroups (pN1 alone or

pN2 alone) were stratified by LND at a cutoff of 0.06

using Kaplan-Meier analysis and the log-rank test. This

analysis demonstrates the ability of LND to predict OS (P

< .0002) and DSS (P< .001), even in the subgroup of

patients with pN1 disease. Similar results were found for

cutoff points of 0.05, 0.076, and 0.1 (P< .05). In the

pN2 subgroup, the ability of LND to predict OS and

FIGURE 3. The distribution of lymph node density (LND)

among the patients with positive neck lymph nodes is shown.

(A) The LND frequency distribution could be reliably fit by 4

Gaussian equations (P< .05). The median LND was 0.06. The

rest of the parameters for each 1 of the 4 Gaussian equations

are depicted. (B) The distribution of LND according to patho-

logic neck status (pN) classification is shown. Statistical anal-

ysis demonstrated significant differences in LND distribution

between the different pN classification groups (P< .0001).

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DSS was significant only for a cutoff point of 0.1. The

pN3 subgroup consisted of only 2 patients and therefore

was not included in this type of analysis. Figure 5 shows

the ability of LND to distinguish between low-risk and

high-risk patients within individual pN classification

subgroups.

DISCUSSION

Resection of the primary tumor with an appropriate neck

dissection is considered the standard of care for patients

with OSCC. Analysis of the patterns of failure in patients

with oral cancers reveals that approximately 33% of them

will fail due to regional metastases.7,19-21 Some of the risk

factors for recurrence include T classification, surgical

margin status, depth of invasion, and major nerve inva-

sion.22 In addition, 1 of the most significant prognostic

factors in this population is the presence of neck metasta-

sis.19,23 Lymph node status and the number of positive

lymph nodes are primarily based on the lymph node sam-

pling procedure (ie, neck dissection) and secondarily on

examination by the pathologist. It was shown that cervical

metastases are more likely to be found for a lymph node

yield>20.9,10

Obviously, 1 of the weaknesses of the current study

is inconsistency in the analysis of the pathologic speci-

mens. In the current study cohort, the mean number of

lymph nodes removed was 35, with a standard deviation

FIGURE 4. The 5-year overall survival and disease-specific survival rates as calculated using the Kaplan-Meier method in patients

with positive cervical lymph nodes are shown (A and B) using the tumor-node-metastasis (TNM) lymph node classification (P30

No. of positive lymph nodes 1 .57

>1

HR indicates hazards ratio; 95% CI, 95% confidence interval; TNM, tumor-

node-metastasis.

Table 3. Multivariate Analysis of Prognostic Factors for

Overall Survival

Variable P HR 95% CI

T classification 1 .656

2

3

4

N classification N0 .22

N1

N2a

N2b

N2c

N3

Overall TNM stage I .95

II

IIIIV

Extracapsular spread No .6

Yes

Lymph node density 0.06 .02 2.0 1.1-3.5

>0.06

Total no. of lymph nodes 1-30 .36

>30


>1

HR indicates hazards ratio; 95% CI, 95% confidence interval; TNM, tumor-

node-metastasis.


Locoregional Disease-Free Survival

Variable P HR 95% CI

T classification 1 .29

23

4

N classification N0 .24

N1

N2a

N2b

N2c

N3

Overall TNM stage I .31

II

III

IV

Extracapsular spread No .4

Yes

Lymph node density 0.06 .005 4.1 1.5-11.8

>0.06Total no. of lymph nodes 1-30 .12

>30


>1

HR indicates hazards ratio; 95% CI, confidence interval; TNM, tumor-node-

metastasis.


Distant Metastases Disease-Free Survival

Cox Regression Model Without LND With LND

Overall survival

-Log likelihood 6.05 8.5

P .06 .01

Disease-specific survival


P .01 .0028

Locoregional control


P .4 .04

LND indicates lymph node density.

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in the number of lymph nodes retrieved from the speci-

mens in the current study are, therefore, similar to other

studies. Furthermore, even after we excluded cases with


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conventional lymph node staging.11,12,14,26,27 Simple to

calculate, LND is a ratio of the number of positive lymph

nodes divided by the total number of lymph nodes exam-

ined by the pathologist. It was postulated that LND may

have a greater prognostic value, because it takes into con-sideration 3 factors: 1) tumor factors (number of positive

lymph nodes), 2) treatment factors (number of lymph

nodes removed during neck dissection), and 3) staging

factors (completeness of the sampling procedure, includ-

ing those related to the surgeon and pathologist). This

model proposes, for example, that a patient with 1 posi-

tive lymph node among 20 examined (LND 0.05) has a

better prognosis than a patient with 1 positive lymph

node out of 5 excised lymph nodes (LND0.2).

Although both patients will have the same pN classifica-

tion, the latter patient is more likely to have positivelymph nodes left behind and therefore would be under-

staged by the conventional TNM system. Thus, the

patient with a higher ratio is expected to fare worse than

the patient with a lower ratio, although each has a similar

number of positive lymph nodes examined.

In the current study, we have evaluated for the first

time, to our knowledge, the value of LND in comparison

with the conventional staging system to determine its abil-

ity to predict OS, DSS, and locoregional recurrence-free

survival in patients undergoing neck dissection. Using

multivariate analysis, we found that, in patients with posi-

tive cervical lymph nodes, LND is superior to the conven-

tional N classification system (AJCC) in predicting OS,

DSS, and locoregional control. Our data also indicated

that LND is superior to T classification, ECS, overall

stage, and number of positive lymph nodes in predicting

survival. Within the subgroups of patients with pN1 or

pN2 neck disease, LND reliably distinguished between

low-risk and high-risk patients. Most importantly, multi-

variate analysis also demonstrated that LND is a better

predictor than conventional N classification for predicting

treatment failure in 3 groups of patients: those under-

going elective neck dissection, those undergoing therapeu-

tic neck dissection, and those receiving adjuvant

radiotherapy.

Recent studies have demonstrated slight improve-

ments in 5-year survival rates after adjuvant concurrent

chemoradiotherapy over radiotherapy alone for patients

with advanced head and neck SCC.1 However, due to the

significant morbidity of adding chemotherapy to radio-

therapy, considerable controversy remains regarding the

pathologic tumor characteristics that predict the need for

more aggressive adjuvant treatment. Furthermore, a

recent meta-analysis suggested that ECS and microscopi-

cally involved surgical margins, not pathologic N classifi-cation, may serve as predictors of outcome and, therefore,

can potentially help determine the type of adjuvant treat-

ment needed.8 The data from the current study indicate

that LND may be useful as an adjunct to the conventional

staging system in clinical studies investigating the role of

adjuvant therapy after surgery for patients with OSCC.

The LND ratio introduces into the equation the

expected variability in the extent of lymph node dissection

and may be even more important when surgeons perform

varying degrees of lymph node dissection. The value of

LND was studied in our institution, in which a standardneck dissection is performed. For patients undergoing

very limited neck dissections and with very poor lymph

node yields, it is expected that LND will be higher than

that reported in the current study. Whether LND will

remain a significant predictor of outcome when different

techniques or types of neck dissection are used awaits fur-

ther evaluation.

Collinearity may exist when there are high correla-

tions among sets of independent variables.28 It is also

known that, when the collinearity is extreme (correlation

coefficiency R>0.85), the numeric accuracy of the multi-

variate model can be affected.29 Therefore, we studied the

correlation between LND and pN classification or the

number of positive lymph nodes using regression analysis.

In this analysis, the correlations were low (R 0.4

between LND and pN classification and R 0.6 between

LND and number of positive lymph nodes). These results

preclude profound effects on the multivariate model.29

We also found no significant correlation between the total

number of excised lymph nodes (positive and negative)

and the number of positive lymph node in the specimen

(R 0.3). This precludes the possibility of an inherent

bias in the number of lymph nodes removed during sur-

gery (ie, if the surgeon decides on the number of lymph

nodes to be resected during surgery, when there are multi-

ple positive lymph nodes).

Although the current study data provide a strong

argument in favor of lymph node ratios to stratify risk of

disease recurrence, other factors related to lymph node

status such as the size and volume of the occupied lymph

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node, lymph node site, presence of occult micrometastases

discovered by molecular methods, and extent of ECS may

also be significant predictors of outcome and their inter-

play needs elaboration. Furthermore, the results of the

current study represent a single institutional experience,with a relatively high median number of lymph nodes

examined by our pathologist (N30). Thus, it does not

necessarily comply with more limited dissections, in which

a denominator (total number of excised lymph nodes) of


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23. Mamelle G, Pampurik J, Luboinski B, Lancar R, Lusinchi A, Bosq J. Lymph node prognostic factors in head andneck squamous cell carcinomas. Am J Surg. 1994;168:494-498.

24. Agrama MT, Reiter D, Topham AK, Keane WM. Node

counts in neck dissection: are they useful in outcomesresearch? Otolaryngol Head Neck Surg. 2001;124:433-435.

25. Jose J, Coatesworth AP, MacLennan K. Cervical metastasesin upper aerodigestive tract squamous cell carcinoma: histo-pathologic analysis and reporting. Head Neck. 2003;25:194-197.

26. Kassouf W, Leibovici D, Munsell MF, Dinney CP, Gross-man HB, Kamat AM. Evaluation of the relevance of lymph

node density in a contemporary series of patients under-going radical cystectomy. J Urol. 2006;176:53-57; discus-sion 57.

27. Roder JD, Busch R, Stein HJ, Fink U, Siewert JR. Ratio ofinvaded to removed lymph nodes as a predictor of survival

in squamous cell carcinoma of the oesophagus. Br J Surg.1994;81:410-413.

28. Fraser GE, Stram DO. Regression calibration in studieswith correlated variables measured with error. Am J Epide-miol. 2001;154:836-844.

29. Smith KR, Slattery ML, French TK. Collinear nutrientsand the risk of colon cancer. J Clin Epidemiol. 1991;44:715-723.

Original Article


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Lymph Nodes in Oral Cancer