Skip to main content
Scientific Reports logoLink to Scientific Reports
. 2017 Oct 26;7:14117. doi: 10.1038/s41598-017-06452-0

Recommendation for incorporation of a different lymph node scoring system in future AJCC N category for oral cancer

Ching-Chih Lee 1,2,3,4,5, Yu-Chieh Su 6,7, Shih-Kai Hung 8,9, Po-Chun Chen 10, Chung-I Huang 11, Wei-Lun Huang 12, Yu-Wei Lin 13,14, Ching-Chieh Yang 13,14,15,
PMCID: PMC5658398  PMID: 29074847

Abstract

To compare the prognostic value of 3 different lymph node scoring systems “ log odds of positive nodes (LODDS), lymph node ratio (rN), and lymph node yield “ in an effort to improve the staging of oral cancer. We identified 3958 oral cancer patients from Surveillance, Epidemiology, and End Results database from 2007 to 2013. In univariate analysis, LODDS, pN, rN, and lymph node yield were prognostic factors for 5-year disease-specific survival (DSS) and overall survival (OS). Multivariate analysis indicated that patients with LODDS 4 had worst 5-year DSS and OS. Stage migration occurred in pN1 and pN2 patients with LODDS 4. In pN1 patients, those with LODDS 4 had the worst 5-year DSS (41.2%) and OS (31.6%) than patients with pN1 and LODDS 2–3. In pN2 patients, those with LODDS4 had the worst 5-year DSS (34.5%) and OS (27.4%) than patients with pN2 and LODDS 2–3. The proposed staging system, which incorporates LODDS with AJCC pN, had better discriminability and prediction accuracy for predicting survival. We also noted that patients with LODDS 4 given adjuvant radiotherapy had better 5-year DSS and OS. The LODDS should be considered as a future candidate measurement for N category in oral cancer.

Introduction

Most oncologists stage oral cancer using the American Joint Committee on Cancer (AJCC) tumor, node, metastasis (TNM) system, and also use this system for clinical decision-making and development of therapeutic strategies1. Although the most recent (8th edition) TNM classification for oral cancer, which considers extra-capsular extension, will be introduced in the near future, the impact of other clinical and pathological factors on survival indicates the need for a better staging tool2,3. One of the most important factors are lymph node number status, such as total lymph nodes retrieved, ratio of positive lymph nodes (rN), and log odds of positive lymph nodes (LODDS)46. Therefore, a study of the prognostic value of different lymph node scoring systems in oral cancer may aide in development of the forthcoming staging system.

Many studies have confirmed that the number of evaluated lymph nodes correlates with outcomes, and recommend that at least 18 lymph nodes be examined in patients with oral cancer6,7. Patients with inadequate lymph node harvests might experience stage migration and subsequent underestimation of disease severity8,9. Besides lymph node yield, other studies have analyzed the prognostic impact of rN–the ratio of positive lymph nodes to total examined nodes–in the staging of oral cancer4,10. In fact, the rN category is a reliable predictor of oral cancer outcomes4. Recent studies indicate that the LODDS may provide a more accurate prediction of survival than the AJCC pN and rN categories1113. In particular, LODDS can discriminate among patients who have the same ratio of node metastasis but different survival rates, especially patients without positive lymph nodes or with an insufficient number of retrieved nodes11,14. Although there is limited literature on the use of LODDS in oral cancer, our prior studies showed that LODDS had better discriminability of oral cancer patients from different single institution5,15.

The objective of the current study of oral cancer patients was to use multivariate analysis to compare different measures of lymph node status–LODDS, AJCC pN, rN, and lymph node yield–to identify the system with the greatest prognostic power. We used the Surveillance, Epidemiology, and End Results (SEER) database to compare all features of patients, so that the large number of cases provides sufficient statistical power. We also propose a new staging system that can identify the high-risk group using an independent factor to adjust risk features for a future prospective study.

Results

Demographic data

Table 1 summarizes the demographic and clinical characteristics of the study cohort. There were 3958 cases with newly diagnosed oral cancer (2528 men [63.9%] and 1430 women [36.1%]). The mean age at diagnosis was 59 ± 13 years. About 52% of the patients had tongue cancer and 25% had inadequate lymph node dissection. The mean lymph node yield was 33 ± 17, and the mean number of positive lymph nodes was 1.31 ± 2.65.

Table 1.

Demographic and clinical characteristics of the oral cancer patients, n = 3958.

Variables Number, n (%)
Age (Mean ± SD) 59 ± 13
Gender
  Male 2528 (63.9%)
  Female 1430 (36.1%)
Race
  White 3316 (83.8%)
  Black/other 642 (16.2%)
Marital status
  Married 2240 (56.6%)
  Other status 1718 (43.4%)
Tumor subsite
  Tongue 2041 (51.6%)
  Lip 160 (4.0%)
  Floor of mouth 671 (17.0%)
  Gum and retromolar trigone 680 (17.2%)
  Buccal mucosa 268 (6.8%)
  Hard palate 55 (1.4%)
  Other areas 83 (2.1%)
Differentiation
  Well/moderately 3060 (77.3%)
  Poorly/undifferentiated 898 (22.7%)
Regional lymph nodes examined
  Adequate 2969 (75.0%)
  Inadequate 989 (25.0%)
AJCC pT
  T1 1398 (35.3%)
  T2 1353 (34.2%)
  T3 474 (12.0%)
  T4 733 (18.5%)
AJCC pN
  N0 2132 (53.9%)
  N1 826 (20.9%)
  N2 967 (24.4%)
  N3 33 (0.8%)
LODDS
  LODDS1 (LODDS ≦ -1.68) 1360 (34.4%)
  LODDS2 (-1.68 < LODDS ≦ -1.29) 1214 (30.7%)
  LODDS3 (-1.29 < LODDS ≦ -0.88) 795 (20.1%)
  LODDS4 (-0.88 < LODDS) 589 (14.9%)
rN
  N0 (rN = 0) 2139 (54.0%)
  N1 (0 < rN ≦ 0.2) 1626 (41.1%)
  N2 (0.2 < rN ≦ 0.4) 159 (4.0%)
  N3 (0.4 < rN) 34 (0.9%)
Radiotherapy
  No 1851 (46.8%)
  Yes 2107 (53.2%)
Year of diagnosis
  2007 432 (10.9%)
  2008 488 (12.3%)
  2009 588 (14.9%)
  2010 575 (14.5%)
  2011 587 (14.8%)
  2012 648 (16.4%)
  2013 640 (16.2%)

Abbreviation: LODDS, log odds of positive lymph nodes; rN, ratio-based lymph node system.

Univariate and multivariate analysis of different lymph node measurements

Before our analysis, the multicollinearity and the reciprocal action effects among LODDS, AJCC pN, rN, and lymph node yield have been checked and presented no interaction between these measurements (Supplementary Table 1). Univariate analysis indicated that LODDS, pN, rN, and regional lymph nodes were significantly associated with 5-year DSS and OS (Fig. 1 and Supplementary Table 2). However, multivariate analysis indicated that only LODDS and rN measurements were significantly associated with 5-year OS (Table 2). In particular, patients with LODDS4 had poorer 5-year DSS (HR: 1.91, 95% CI: 1.28–2.83) and OS (HR: 1.86, 95% CI: 1.32–2.61) than those with LODDS1–3. Patients classified as rN3 had the worst 5-year OS (HR: 4.10, 95% CI, 0.93–18.19).

Figure 1.

Figure 1

Kaplan-Meier curves for (a,b) LODDS in DSS and OS, (c,d) AJCC pN in DSS and OS, (e,f) rN in 5-year DSS and OS, and regional lymph nodes examined (g,h) from Surveillance, Epidemiology, and End Results (SEER) database.

Table 2.

Multivariate analysis for 5-year disease-specific survival and overall survival, n = 3958*.

Variables Disease-specific survival Overall survival
HR 95% CI p value HR 95% CI p value
Age 1.02 (1.01–1.02) <0.0001 1.02 (1.02–1.03) <0.0001
Race
  White 1
  Black/other 1.11 (0.93–1.32) 0.250
Marital status
  Married 1 1
  Other status 1.11 (0.97–1.28) 0.118 1.25 (1.11–1.41) 0.000
Tumor subsite
  Tongue 1 1
  Lip 0.43 (0.27–0.70) 0.001 0.57 (0.40–0.82) 0.002
  Floor of mouth 1.08 (0.90–1.30) 0.423 1.14 (0.97–1.33) 0.123
  Gum and retromolar trigone 0.94 (0.78–1.14) 0.551 0.98 (0.83–1.15) 0.765
  Buccal mucosa 0.95 (0.73–1.24) 0.700 0.87 (0.68–1.11) 0.263
  Hard palate 1.09 (0.67–1.79) 0.728 1.03 (0.65–1.62) 0.913
  Other areas 1.16 (0.77–1.77) 0.480 1.25 (0.88–1.78) 0.215
Differentiation
  Well/moderately 1 1
  Poorly/undifferentiated 1.11 (0.96–1.29) 0.171 1.15 (1.01–1.31) 0.042
Regional lymph nodes examined
  Adequate 1 1
  Inadequate 0.89 (0.75–1.06) 0.187 0.93 (0.80–1.08) 0.317
AJCC pT
  T1 1 1
  T2 1.76 (1.45–2.14) <0.0001 1.61 (1.37–1.90) <0.0001
  T3 3.04 (2.41–3.83) <0.0001 2.79 (2.29–3.39) <0.0001
  T4 3.31 (2.67–4.10) <0.0001 2.84 (2.36–3.42) <0.0001
AJCC pN
  N0 1 1
  N1 1.83 (0.45–7.39) 0.397 1.20 (0.30–4.85) 0.796
  N2 1.85 (0.46–7.49) 0.390 1.27 (0.31–5.11) 0.740
  N3 0.94 (0.20–4.50) 0.941 0.87 (0.20–3.90) 0.858
LODDS
  LODDS1 1 1
  LODDS2 0.86 (0.66–1.12) 0.251 0.97 (0.79–1.20) 0.800
  LODDS3 1.36 (0.95–1.94) 0.096 1.30 (0.96–1.77) 0.089
  LODDS4 1.91 (1.28–2.83) 0.002 1.86 (1.32–2.61) 0.000
rN
  N0 1 1
  N1 1.36 (0.33–5.59) 0.668 1.72 (0.42–7.00) 0.450
  N2 2.48 (0.59–10.42) 0.214 2.88 (0.69–11.97) 0.145
  N3 4.10 (0.93–18.19) 0.063 5.25 (1.21–22.74) 0.027
Radiotherapy
  No 1 1
  Yes 0.78 (0.67–0.91) 0.002 0.71 (0.62–0.81) <0.0001

Abbreviation: HR, hazard ratio; 95% CI, 95% confidence interval; LODDS, log odds of positive lymph nodes; rN, ratio-based lymph node system. *Variables with a p value < 0.05 in univairate analysis (Supplementary Table 2) were included in multivariate analysis.

Stage migration in different pN categories

We performed stratified analysis to check whether stage migration developed in the different pN and LODDS groups (Table 3 and Fig. 2). In pN0 patients, the LODDS1 and LODDS2 groups had similar survival rates; in pN1-2 patients, the LODDS4 group had the worst survival rate. Stage migration occurred in pN1 and pN2 patients with LODDS 4. In pN1 patients, those with LODDS4 had the worst 5-year DSS (41.2%) and OS (31.6%) than patients with pN1 and LODDS2-3. In pN2 patients, those with LODDS4 had the worst 5-year DSS (34.5%) and OS (27.4%) than patients with pN2 and LODDS2-3. We also examined the presence of stage migration for rN according to pN status, but observed no stage migration, presumably because only a few patients had rN3 disease (Supplementary Table 3).

Table 3.

The 5-year overall survival and disease-specific survival of the oral cancer patients according to different AJCC pN plus LODDS, n = 3958.

New N category Inclusion AJCC pN LODDS Disease-specific survival Overall survival
Case Events Survival rate (%) Case Events Survival rate (%)
N0 pN0 LODDS1 1331 159 80.3% 1331 239 71.1%
pN0 LODDS2 801 78 84.3% 801 137 73.1%
pN0 LODDS3 0 0 0 0
pN0 LODDS4 0 0 0 0
N1 pN1 LODDS1 23 9 33.8% 23 10 29.6%
pN1 LODDS2 314 72 66.5% 314 98 54.8%
pN1 LODDS3 375 119 57.3% 375 139 51.3%
N2 pN1 LODDS4 114 54 41.2% 114 65 31.6%
pN2 LODDS1 6 2 60.0% 6 2 60.0%
pN2 LODDS2 93 25 63.1% 93 33 49.1%
pN2 LODDS3 407 132 51.8% 407 152 45.1%
N3 pN2 LODDS4 461 223 34.5% 461 263 27.4%
pN3 LODDS1 0 0 0 0
pN3 LODDS2 6 0 6 1 66.7%
pN3 LODDS3 13 5 54.0% 13 7 44.9%
pN3 LODDS4 14 3 71.8% 14 5 61.1%

Abbreviation: LODDS, log odds of positive lymph nodes.

Figure 2.

Figure 2

Kaplan-Meier curves for 5-year DSS and OS according to different AJCC pN plus LODDS.

Performance of AJCC TNM stage and hypothetical system

Due to the effect of stage migration of pN1 and pN2 cancer, modification of N category was proposed, similar to our previous literature (Table 3)15. As described in the ‘Material and Methods’, subgroups with fewer than 30 OSCC patients were not included in this analysis. This led to a new N category in which each patient was placed into one of four groups: new N0 (pN0 and LODDS1-2); new N1 (pN1 and LODDS2-3); new N2 (pN1 and LODDS4, pN2 and LODDS2-3); and new N3 (pN2 and LODDS4). Thus, we compared the stage-specific DSS and OS survival rates according to current AJCC TNM staging and our new system (Fig. 3). There was no difference in DSS (p = 0.63) and OS (p = 0.985) between the AJCC stage IVa and IVb disease. However, the new system discriminated stage IVa and IVb in terms of DSS (p < 0.001) and OS (p < 0.001). In prediction of DSS, the new system outperformed the AJCC TNM system with a higher linear chi-square value (397 vs. 327), a lower AIC (13275 vs. 13329), and a higher Harrell’s C statistic (0.722 vs. 0.703) (Table 4). Similarly, a comparison of these 2 systems in terms of OS indicated the new system had higher linear chi-square (407 vs. 326), a lower AIC (17454 vs. 17514), and a higher Harrell’s C statistic (0.692 vs. 0.673). These results were in agreement with our previous single center study15. Moreover, our multivariate analysis indicated these results were robust (Table 5). Thus, the new model had better discriminatability and better prediction of DSS and OS than the existing AJCC TNM system. Supplementary Tables 4 and 5 show the detailed results of the Cox regression model.

Figure 3.

Figure 3

Kaplan-Meier curves for (a,b) TNM stage in DSS and OS, and (c,d) hypothetical T-new N-M system in 5-year DSS and OS.

Table 4.

Discriminatory ability between AJCC TNM stage and T- New N-M stage system, n = 3958.

Subgroups Linear trend χ2 AIC Harrell’s c-statistics
Performance of DSS prediction
  AJCC TNM stage I, II, III, IVA, IVB 327 13329 0.703
  T-New N-M stage I, II, III, IVA, IVB 397 13275 0.722
Performance of OS prediction
  AJCC TNM stage I, II, III, IVA, IVB 326 17514 0.673
  T-New N-M stage I, II, III, IVA, IVB 407 17454 0.692

Abbreviation: DSS, disease-specific survival; OS, overall survival; AIC, Akaike information criterion.

Table 5.

Multivariate analysis of 5-year disease-specific survival & overall survival and model discrimination, n = 3958*.

Variables Model 1: AJCC TNM-based model Model 2: T-new N-M-based model
HR 95% CI p value HR 95% CI p value
DSS performance
  AJCC pN
  N0 1
  N1 3.11 2.59–3.74 <0.001
  N2 4.38 3.66–5.24 <0.001
  N3 2.22 1.08–4.54 0.029
New N category
  N0 1
  N1 2.86 2.35–3.47 <0.001
  N2 3.53 2.89–4.30 <0.001
  N3 5.79 4.75–7.06 <0.001
Discriminatory ability
  Linear trend χ2 273 316
  AIC 13164 13131
  Harrell’s c-statistic 0.757 0.762
OS performance
AJCC pN
  N0 1
  N1 2.55 2.18–2.98  < 0.001
  N2 3.55 3.05–4.14  < 0.001
  N3 2.49 1.42–4.38 0.001
New N category
  N0 1
  N1 2.36 2.00–2.79 <0.001
  N2 2.83 2.38–3.36 <0.001
  N3 4.77 4.02–5.66 <0.001
Discriminatory ability
  Linear trend χ2 279 335
  AIC 17243 17200
  Harrell’s c-statistic 0.735 0.741

*Adjusted for age, gender, tumor subsite, AJCC pT, differentiation, radiotherapy, marital status, race and year of diagnosis. Abbreviation: DSS, disease-specific survival; OS, overall survival; HR, hazard ratio; 95% CI, 95% confidence interval; AIC, Akaike information criterion.

Role of adjuvant radiotherapy for high-risk patients

We further analyzed the effect of adjuvant radiotherapy in patients with different LODDS. Among patients with LODDS 4, those treated with adjuvant radiotherapy had better 5-year DSS (aHR: 0.56, 95% CI: 0.42–0.73) and OS (aHR: 0.52; 95% CI: 0.41–0.67) than those not receiving adjuvant radiotherapy after adjusting other factors (Fig. 4).

Figure 4.

Figure 4

The adjusted Kaplan-Meier curves for adjuvant radiotherapy effect in 5-year DSS (a) and OS (b) among LODDS 4 patients.

Discussion

We comprehensively analyzed the use of different lymph node scoring systems in patients with oral cancer using the SEER database, and validated the prognostic independency of LODDS for oral cancer in the United States. In particular, oral cancer patients with LODDS 4 (LODDS > -0.88) had 91% greater mortality in our 5-year DSS analysis and 86% greater mortality in our 5-year OS analysis relative to those with LODDS1 (LODDS ≤ -1.68) after adjustment for confounding. Stage migration occurred in pN1 and in pN2 with LODDS 4. The new system had better discriminability and prediction accuracy than the existing AJCC TNM system. Furthermore, our multivariate analysis indicated that high-risk patients (LODDS 4) benefitted from adjuvant radiotherapy. LODDS is therefore a reliable method that can be easily used by clinical practitioners, and should be considered as a future candidate measurement for nodal classification of oral cancer.

Currently, oral cancer patients with positive lymph nodes are staged as AJCC stage III–IV, and recommended for adjuvant radiotherapy or chemo-radiotherapy16. Due to multiple shortcomings of the N category in the current AJCC TNM staging system (7th edition), the new updated version (8th edition) has incorporated extra-capsular spread in the clinical and pathological N category. However, there is continued discussion regarding the use of other prognostic factors, such as lymph node count, rN, and LODDS, for reducing stage migration4,5,8. This motivated our present research to assess the use of different lymph node scoring systems to develop a new N staging category that better stratifies high-risk patients for more intense therapy.

Multiple studies have investigated lymph node count as a prognostic factor in stomach cancer, colon cancer, and head and neck cancer, and also as a potential quality metric for neck dissection7,8. Divi et al. performed a large cohort study to examine these associations using a nation-wide database from the United States8. Their results showed an independent and significant association between fewer than 18 lymph nodes examined and increased risk of death (HR: 1.18, 95% CI: 1.13 to 1.22). In addition, when stratified by clinical nodal stage, there was an increased risk of death in the node-negative group (HR: 1.24, 95% CI: 1.17 to 1.32) and the node-positive group (HR: 1.12; 95% CI: 1.05 to 1.19). Thus, there is a significant overall survival advantage when more than 18 lymph nodes are examined after neck dissection. However, lymph node yield may depend on the specific hospitals, cancer severity, patient age, and patient performance status. Furthermore, the lymph node count may not reflect the real impact of positive lymph nodes on survival, so the lymph node ratio system should be still considered for pN stage assessment. The results of our univariate analysis showed a difference in DSS and OS according to LODDS, pN, rN, and regional lymph nodes examined (Fig. 1 and Supplementary Table 2). However, only LODDS and rN remained statistically significant in the multivariate analysis (Table 2). Thus, rN or LODDS system should be considered for improvement of the AJCC pN stage.

The current AJCC pN category for oral cancer is based on the size, number, and location of resected lymph nodes. However, when there is stage migration, the pN category underestimates the true extent of lymph node disease, and is therefore considered imperfect for prognostic purposes. For example, patients with the same pN classification, but a different number of examined nodes, will be given different prognoses. Therefore, the rN and LODDS systems, two new classifications for nodal estimation and behavior, are better than the traditional number-based pN system9,17. In our previous studies of oral cancer5,15, we found that LODDS performed better than the pN and rN systems. The main reason is that there is a non-linear association between the LODDS distribution and number of pathologically positive nodes11. Therefore, compared with rN, LODDS can discriminate among patients without positive lymph nodes or with a few positive nodes when insufficient nodes are retrieved. For example, a pN1 patient with a high LODDS should not be treated the same as a pN1 patient with low LODDS, because the former has a higher risk of occult metastases and worse prognosis. In this context, it is noteworthy that LODDS was a reliable lymph node measurement, and may be considered an alternative to pN stage.

Previous studies have successfully used LODDS in the study of breast, gastric, and colorectal cancer11,17,18. Besides our own former experience from two specific hospitals, there is little data on use of LODDS on outcome from oral cancer. Yildiz et al. reported a study of 225 surgically treated head and neck cancer patients, and reported LODDS as the only independent predictor for 5-year OS when comparing pN and rN19. The present SEER study confirms and validates that LODDS especially LOODS 4 is an independent prognostic factor, among various lymph node assessments, for oral cancer in the United States. In pN1 patients, those with LODDS4 had the worst 5-year DSS (41.2%) and OS (31.6%) than patients with pN1 and LODDS2-3. In pN2 patients, those with LODDS4 had the worst 5-year DSS (34.5%) and OS (27.4%) than patients with pN2 and LODDS2-3. Therefore LODDS 4 can compensate for the effect of migration of the AJCC pN stage. Furthermore, previous studies have outlined the importance of lymph node yield7,8. What is the value of LODDS in modification of oral cancer staging system? Our multivariate analysis indicated the lymph node yield was not an independent prognosticator when LODDS was in the model simultaneously. Furthermore, LODDS has better discriminability then lymph node yield and patients with inadequate node dissection had worse survival8. The current literature provides little advice for oral cancer patients who received inadequate node dissection. In the present study, LODDS helped to stratify patients and select the most appropriate therapy for those with LODDS4 (LODDS > -0.88, who had better prognosis when adjuvant radiotherapy was administered. In summary, lymph node yield could be regarded as “quality measure” of neck dissection, just as “surgical margin” may be a proxy of surgical technique. However, LODDS can be regarded as an reliable lymph node measurement for oral cancer, and an indicator of the suitability for adjuvant therapy.

There are several limitations in this study. First, the SEER database provides no information on whether the patients underwent bilateral neck dissection. We tried to minimize this confounding effect in lymph node yield, through exclusion of patients with pN2c disease, as previously suggested6,20. Moreover, we are currently conducting research using the Taiwan Cancer Database, which has clinical and pathological TNM data, and this may help to resolve this limitation. Second, the cutoff points for rN and LODDS were selected by our recent studies5,21. Modification of these cutoff points may be necessary to prevent subgroups with too few patients for analysis. Third, multivariable analysis indicated that lymph node yield was not an independent factor when LODDS was in the model. We did not perform further stratified analysis due to lack of statistical independence. Our study was not aimed to challenge the prognostic value of lymph node yield, but to find additional prognostic useful indicators. In fact, LODDS may be considered almost as a proxy of lymph node yield. Current guidelines recommend extensive extirpation of lymph nodes, without adverse damage to vessels and nerves, when performing neck dissection. Fourth, the SEER database provided no information on use of adjuvant chemotherapy, extra-capsular invasion and margin status. Some other unmeasured biases may also exist. Further research linked to Medicare claims (provide longitudinal utilization information for the cancer cases in SEER) or the use of instrumental variable analysis may help us to resolve these important issues22. Although this study describes the protective effect of adjuvant radiotherapy in those with LODDS4 after adjusting for confounding, these findings should be verified by a prospective study. Finally, the number of patients in some of our subgroups (pN0 with LODDS3-4; pN1 with LODDS1; pN2 with LODDS1; pN3) was small (fewer than 30) for survival analysis, so we did not estimate their survival rates using our new classification. Future researchers should consider recruitment of patients with pN3 disease, although several researchers recommend against surgical interventions for N3 disease due to the poor survival and high comorbidity of these patients23.

In conclusion, multivariate analysis indicated that LODDS4 was a reliable prognostic indicator for patients with oral cancer. We observed stage migration in patients classified as pN1 or as pN2 with LODDS4. This study validated that prognostic utility of the newly proposed system, which incorporated LODDS with AJCC pN, compared with AJCC TNM stage. The LODDS should be considered as a future reliable lymph node measurement for N category in oral cancer.

Material and Methods

Data source and study population

Data were obtained from the SEER database, sponsored by the National Cancer Institute, and consists of 18 population-based cancer registries. SEER data is an open access resource from United States used for cancer-based epidemiology and survival analyses. The Surveillance Research Program, using National Cancer Institute SEER*Stat software (seer.cancer.gov/seerstat) version 8.3.2, was used to identify eligible patients. All authors provided signed authorization to access this dataset. All methods were performed in accordance with the relevant guidelines and regulations of SEER database. The study design was approved by the Ethics Committee of the Institutional Review Board of Kaohsiung Veterans General Hospital.

Patients with new diagnoses of oral cancer after major surgery, with or without adjuvant radiotherapy, were identified from 2007 to 2013.Oral cancer patients were identified using the International Classification of Disease for Oncology, third edition (ICD-O-3). The ICD-O-3 categories included in this study were cancer of the lip (C00) and oral cavity (C02-C05.0; C06). To allow comparison of results with current AJCC N categories, any oral cancer patient without a clear AJCC TNM stage was excluded. All cases were staged according to the 6th edition AJCC system24. Patients with a previous cancer, distant metastasis at initial diagnosis, pN2c disease, fewer than 10 examined LN, or who received any treatments prior to surgery (e.g. radiotherapy) were excluded. Patients with pN2c disease were also excluded because there may be confounding with the number of lymph nodes examined20. Patients with fewer than 10 lymph nodes examined may be regarded as not having received neck dissection according to our cancer center consensus. Finally, we examined the records of 3958 patients.

We examined the prognostic value of different features of neck lymph nodes in patients with oral cancer. The 3 lymph node scoring systems were:

  1. Log odds of positive lymph node (LODDS).

    This is calculated as log10[(pnod + 0.5)/(tnod − pnod + 0.5)], in which pnod is the number of positive neck lymph nodes and tnod is the total number of cervical lymph nodes examined25. In this formula, 0.5 was added to the numerator and denominator to avoid division by 0. The cutoff points of LODDS were 35%, 60%, and 85% according to our previous publication5.

  2. Number of cervical lymph nodes retrieved.

    This number was classified as adequate or inadequate, according to previous research20. Patients with pN0 disease with nodal yield more than 15 or those with pN1-3 disease with nodal yield more than 25 were categorized as having an adequate lymph nodes retrieval. All others were classified as having inadequate retrieval.

  3. Ratio-based lymph node system (rN).

This ratio is calculated as the number of positive regional lymph nodes examined divided by the total number of regional lymph nodes examined. The cutoff points were 0.2 and 0.4, as in our previous study21.

Measurements

The main endpoints were 5-year disease-specific survival (DSS) and overall survival (OS). Deaths from cancer and other conditions were extracted from the SEER database.

Other variables

Basic characteristics, including age, sex, tumor subsite, AJCC pT, cell differentiation, receipt of radiotherapy, marital status, race, and year of diagnosis were also analyzed.

Statistical analysis

All statistical analyses employed SPSS (version 15, SPSS Inc., Chicago, IL, USA). The 5-year OS and DSS rates for different lymph node scoring systems (LODDS, lymph node yield, pN, and rN,) were compared by the Kaplan-Meier method. Survival curves were measured from the time of initial diagnosis. Death from cancer was regarded as the event in DSS analysis, and death from all causes as the event in OS analysis. In multivariate analysis, the prognostic effect of different lymph node features were analyzed after adjusting for age, sex, T stage, cell differentiation, year of diagnosis, marital status, and treatment modality. The lymph node features that remained statistically significant during multivariate analyses were selected for further analysis. We also checked whether stage migration developed among patients in different AJCC N categories and with new lymph node features. Then, we constructed a new N staging system by adding LODDS into the AJCC pN category to improve the accuracy of 5 year predictions of DSS and OS, and compared the new staging system with the existing AJCC staging system. Subgroups with fewer than 30 OSCC patients were not included in the analysis because the small number of patients could lead to unreliable estimates of the 5-year DSS and OS.

Three indices were used to evaluate the prediction accuracy and discriminability of each model: a linear trend chi-square test, the Akaike information criterion (AIC), and Harrell’s C-statistic14,26,27. For Harrell’s C-statistic, a value of 0.5 indicates a value no better than chance; a value of 0.7–0.8 indicates an acceptable model; a value of 0.8–0.9 indicates an excellent model; and a value of 0.9–1 indicates an outstanding model. A linear trend chi-square test was used to assess monotonicity, in which a higher value indicates stronger monotonicity. Comparison of different staging system was also performed using mutltivariate analysis. A two-sided p-value below 0.05 was considered significant28.

Electronic supplementary material

Acknowledgements

The authors acknowledge the efforts of the Surveillance, Epidemiology, and End Results (SEER) Program tumor registries in the creation of the SEER database. The interpretation of these data is the sole responsibility of the authors. This study was partly supported by grant DTCRD103(2)-I-20.

Author Contributions

C.C.L., Y.C.S., S.K.H., P.C.C., C.I.H., W.L.H., Y.W.L. and C.C.Y. designed the research; C.C.L., Y.C.S. and C.C.Y. performed the research; C.C.L. and C.C.Y. analyzed data and wrote the manuscript. All authors reviewed the manuscript.

Competing Interests

The authors declare that they have no competing interests.

Footnotes

Electronic supplementary material

Supplementary information accompanies this paper at doi:10.1038/s41598-017-06452-0

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  • 1.Pfister DG, et al. NCCN Practice Guidelines for Head and Neck Cancers. Oncology (Williston Park) 2000;14:163–194. [PubMed] [Google Scholar]
  • 2.Rubright WC, et al. Risk factors for advanced-stage oral cavity cancer. Arch Otolaryngol Head Neck Surg. 1996;122:621–626. doi: 10.1001/archotol.1996.01890180029009. [DOI] [PubMed] [Google Scholar]
  • 3.Larsen SR, Johansen J, Sorensen JA, Krogdahl A. The prognostic significance of histological features in oral squamous cell carcinoma. J Oral Pathol Med. 2009;38:657–662. doi: 10.1111/j.1600-0714.2009.00797.x. [DOI] [PubMed] [Google Scholar]
  • 4.Ebrahimi A, et al. Lymph node ratio as an independent prognostic factor in oral squamous cell carcinoma. Head Neck. 2011;33:1245–1251. doi: 10.1002/hed.21600. [DOI] [PubMed] [Google Scholar]
  • 5.Lee CC, et al. The Prognostic Ability of Log Odds of Positive Lymph Nodes in Oral Cavity Squamous Cell Carcinoma. Medicine (Baltimore) 2015;94:e1069. doi: 10.1097/MD.0000000000001069. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Lemieux A, Kedarisetty S, Raju S, Orosco R, Coffey C. Lymph Node Yield as a Predictor of Survival in Pathologically Node Negative Oral Cavity Carcinoma. Otolaryngol Head Neck Surg. 2016;154:465–472. doi: 10.1177/0194599815622409. [DOI] [PubMed] [Google Scholar]
  • 7.Ebrahimi A, Zhang WJ, Gao K, Clark JR. Nodal yield and survival in oral squamous cancer: Defining the standard of care. Cancer. 2011;117:2917–2925. doi: 10.1002/cncr.25834. [DOI] [PubMed] [Google Scholar]
  • 8.Divi V, et al. Lymph Node Count From Neck Dissection Predicts Mortality in Head and Neck Cancer. J Clin Oncol. 2016 doi: 10.1200/JCO.2016.67.3863. [DOI] [PubMed] [Google Scholar]
  • 9.Gil Z, et al. Lymph node density is a significant predictor of outcome in patients with oral cancer. Cancer. 2009;115:5700–5710. doi: 10.1002/cncr.24631. [DOI] [PubMed] [Google Scholar]
  • 10.Yang S, Wang D, Mao C. [Prognostic significance of positive lymph node ratio in oral squamous cell carcinoma] Zhonghua Kou Qiang Yi Xue Za Zhi. 2015;50:696–698. [PubMed] [Google Scholar]
  • 11.Sun Z, et al. Log odds of positive lymph nodes: a novel prognostic indicator superior to the number-based and the ratio-based N category for gastric cancer patients with R0 resection. Cancer. 2010;116:2571–2580. doi: 10.1002/cncr.24989. [DOI] [PubMed] [Google Scholar]
  • 12.Arslan NC, Sokmen S, Canda AE, Terzi C, Sarioglu S. The prognostic impact of the log odds of positive lymph nodes in colon cancer. Colorectal Dis. 2014;16:O386–392. doi: 10.1111/codi.12702. [DOI] [PubMed] [Google Scholar]
  • 13.Chen LJ, Chung KP, Chang YJ, Chang YJ. Ratio and log odds of positive lymph nodes in breast cancer patients with mastectomy. Surg Oncol. 2015;24:239–247. doi: 10.1016/j.suronc.2015.05.001. [DOI] [PubMed] [Google Scholar]
  • 14.Qiu MZ, et al. The tumor-log odds of positive lymph nodes-metastasis staging system, a promising new staging system for gastric cancer after D2 resection in China. PLoS One. 2012;7:e31736. doi: 10.1371/journal.pone.0031736. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Lee CC, et al. Incorporation of log odds of positive lymph nodes into the AJCC TNM classification improves prediction of survival in oral cancer. Clin Otolaryngol. 2016 doi: 10.1111/coa.12809. [DOI] [PubMed] [Google Scholar]
  • 16.Bernier J, et al. Defining risk levels in locally advanced head and neck cancers: a comparative analysis of concurrent postoperative radiation plus chemotherapy trials of the EORTC (#22931) and RTOG (# 9501) Head Neck. 2005;27:843–850. doi: 10.1002/hed.20279. [DOI] [PubMed] [Google Scholar]
  • 17.Lee CW, Wilkinson KH, Sheka AC, Leverson GE, Kennedy GD. The Log Odds of Positive Lymph Nodes Stratifies and Predicts Survival of High-Risk Individuals Among Stage III Rectal Cancer Patients. Oncologist. 2016;21:425–432. doi: 10.1634/theoncologist.2015-0441. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Wen J, et al. Development and validation of a prognostic nomogram based on the log odds of positive lymph nodes (LODDS) for breast cancer. Oncotarget. 2016;7:21046–21053. doi: 10.18632/oncotarget.8091. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Yildiz MM, Petersen I, Eigendorff E, Schlattmann P, Guntinas-Lichius O. Which is the most suitable lymph node predictor for overall survival after primary surgery of head and neck cancer: pN, the number or the ratio of positive lymph nodes, or log odds? J Cancer Res Clin Oncol. 2016;142:885–893. doi: 10.1007/s00432-015-2104-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Kuo P, et al. Proposing prognostic thresholds for lymph node yield in clinically lymph node-negative and lymph node-positive cancers of the oral cavity. Cancer. 2016;122:3624–3631. doi: 10.1002/cncr.30227. [DOI] [PubMed] [Google Scholar]
  • 21.Chen YL, et al. Prognostic influences of lymph node ratio in major cancers of Taiwan: a longitudinal study from a single cancer center. Journal of cancer research and clinical oncology. 2015;141:333–343. doi: 10.1007/s00432-014-1810-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Angrist JD IG, R. D. Indentification of causal effects using instrumental variables. J Am Stat Assoc 444–455 (1996).
  • 23.Karakaya E, et al. Outcomes following chemoradiotherapy for N3 head and neck squamous cell carcinoma without a planned neck dissection. Oral oncology. 2013;49:55–59. doi: 10.1016/j.oraloncology.2012.07.010. [DOI] [PubMed] [Google Scholar]
  • 24.Edge SB, Compton CC. The American Joint Committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM. Ann Surg Oncol. 2010;17:1471–1474. doi: 10.1245/s10434-010-0985-4. [DOI] [PubMed] [Google Scholar]
  • 25.Wang J, Hassett JM, Dayton MT, Kulaylat MN. The prognostic superiority of log odds of positive lymph nodes in stage III colon cancer. J Gastrointest Surg. 2008;12:1790–1796. doi: 10.1007/s11605-008-0651-3. [DOI] [PubMed] [Google Scholar]
  • 26.Wang W, et al. Tumor-ratio-metastasis staging system as an alternative to the 7th edition UICC TNM system in gastric cancer after D2 resection–results of a single-institution study of 1343 Chinese patients. Ann Oncol. 2011;22:2049–2056. doi: 10.1093/annonc/mdq716. [DOI] [PubMed] [Google Scholar]
  • 27.DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44:837–845. doi: 10.2307/2531595. [DOI] [PubMed] [Google Scholar]
  • 28.McGinn, T. G. et al. Users’ guides to the medical literature: XXII: how to use articles about clinical decision rules. Evidence-Based Medicine Working Group. JAMA284, 79–84, doi:jml90005 [pii] (2000). [DOI] [PubMed]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials


Articles from Scientific Reports are provided here courtesy of Nature Publishing Group

RESOURCES