[Skip to Navigation]
Sign In
Figure.  Outcomes for Patients With Oral Cavity Squamous Cell Carcinoma
Outcomes for Patients With Oral Cavity Squamous Cell Carcinoma

Overall survival (A), disease-free survival (B), locoregional disease-free survival (C), and distant metastasis–free survival (D). Shaded areas represent 95% CIs.

Table 1.  Patient Demographic Characteristics
Patient Demographic Characteristics
Table 2.  Tumor and Treatment Characteristics
Tumor and Treatment Characteristics
Table 3.  Univariate Analysis of Factors Associated With Survival
Univariate Analysis of Factors Associated With Survival
Table 4.  Multivariate Analysis of Factors Associated With Survival
Multivariate Analysis of Factors Associated With Survival
1.
American Cancer Society. Cancer Facts & Figures 2016. Cancerorg. 2018. https://www.cancer.org/research/cancer-facts-statistics/all-cancer-facts-figures/cancer-facts-figures-2016.html. Accessed May 30, 2018.
2.
National Comprehensive Cancer Network. NCCN Guidelines http://www.nccn.org/professionals/physician_gls/pdf/head-and-neck.pdf. Accessed May 30, 2018.
3.
Bernier  J, Domenge  C, Ozsahin  M,  et al; European Organization for Research and Treatment of Cancer Trial 22931.  Postoperative irradiation with or without concomitant chemotherapy for locally advanced head and neck cancer.  N Engl J Med. 2004;350(19):1945-1952. PubMedGoogle ScholarCrossref
4.
Cooper  JS, Pajak  TF, Forastiere  AA,  et al; Radiation Therapy Oncology Group 9501/Intergroup.  Postoperative concurrent radiotherapy and chemotherapy for high-risk squamous-cell carcinoma of the head and neck.  N Engl J Med. 2004;350(19):1937-1944.PubMedGoogle ScholarCrossref
5.
Bernier  J, Cooper  JS, Pajak  TF,  et al.  Defining risk levels in locally advanced head and neck cancers.  Head Neck. 2005;27(10):843-850. PubMedGoogle ScholarCrossref
6.
Shrime  MG, Bachar  G, Lea  J,  et al.  Nodal ratio as an independent predictor of survival in squamous cell carcinoma of the oral cavity.  Head Neck. 2009;31(11):1482-1488. PubMedGoogle ScholarCrossref
7.
Patel  SG, Amit  M, Yen  TC,  et al; International Consortium for Outcome Research (ICOR) in Head and Neck Cancer.  Lymph node density in oral cavity cancer.  Br J Cancer. 2013;109(8):2087-2095. PubMedGoogle ScholarCrossref
8.
Reinisch  S, Kruse  A, Bredell  M, Lübbers  HT, Gander  T, Lanzer  M.  Is lymph-node ratio a superior predictor than lymph node status for recurrence-free and overall survival in patients with head and neck squamous cell carcinoma?  Ann Surg Oncol. 2014;21(6):1912-1918. PubMedGoogle ScholarCrossref
9.
Goldenberg  D, Mackley  H, Koch  W, Bann  DV, Schaefer  EW, Hollenbeak  CS.  Age and stage as determinants of treatment for oral cavity and oropharyngeal cancers in the elderly.  Oral Oncol. 2014;50(10):976-982. PubMedGoogle ScholarCrossref
10.
Adult comorbidity evaluation-27. http://cancercomorbidity.wustl.edu/ElectronicACE27.aspx. Accessed October 12, 2018.
11.
American Joint Committee on Cancer.  AJCC Cancer Staging Manual. 7th ed. New York: Springer; 2010.
12.
Radiation therapy with or without cetuximab in treating patients who have undergone surgery for locally advanced head and neck cancer. https://clinicaltrials.gov/ct2/show/NCT00956007. Accessed May 30, 2018.
13.
Osazuwa-Peters  N, Massa  ST, Christopher  KM, Walker  RJ, Varvares  MA.  Race and sex disparities in long-term survival of oral and oropharyngeal cancer in the United States.  J Cancer Res Clin Oncol. 2016;142(2):521-528. PubMedGoogle ScholarCrossref
14.
Zandberg  DP, Liu  S, Goloubeva  O,  et al.  Oropharyngeal cancer as a driver of racial outcome disparities in squamous cell carcinoma of the head and neck.  Head Neck. 2016;38(4):564-572. PubMedGoogle ScholarCrossref
15.
Pignon  JP, le Maître  A, Maillard  E, Bourhis  J; MACH-NC Collaborative Group.  Meta-analysis of chemotherapy in head and neck cancer (MACH-NC).  Radiother Oncol. 2009;92(1):4-14. PubMedGoogle ScholarCrossref
16.
Saba  NF, Goodman  M, Ward  K,  et al.  Gender and ethnic disparities in incidence and survival of squamous cell carcinoma of the oral tongue, base of tongue, and tonsils.  Oncology. 2011;81(1):12-20. PubMedGoogle ScholarCrossref
17.
Roberts  JC, Li  G, Reitzel  LR, Wei  Q, Sturgis  EM.  No evidence of sex-related survival disparities among head and neck cancer patients receiving similar multidisciplinary care.  Clin Cancer Res. 2010;16(20):5019-5027. PubMedGoogle ScholarCrossref
18.
McLean  A, LeMay  W, Vila  P, Wegner  M, Remington  P.  Disparities in oral and pharyngeal cancer incidence and mortality among Wisconsin residents, 1999-2002.  WMJ. 2006;105(6):32-35. PubMedGoogle Scholar
19.
Paleri  V, Wight  RG, Silver  CE,  et al.  Comorbidity in head and neck cancer.  Oral Oncol. 2010;46(10):712-719. PubMedGoogle ScholarCrossref
20.
Bøje  CR.  Impact of comorbidity on treatment outcome in head and neck squamous cell carcinoma.  Radiother Oncol. 2014;110(1):81-90. PubMedGoogle ScholarCrossref
21.
Kawakita  D, Hosono  S, Ito  H,  et al.  Impact of smoking status on clinical outcome in oral cavity cancer patients.  Oral Oncol. 2012;48(2):186-191. PubMedGoogle ScholarCrossref
22.
Giraldi  L, Leoncini  E, Pastorino  R,  et al.  Alcohol and cigarette consumption predict mortality in patients with head and neck cancer.  Ann Oncol. 2017;28(11):2843-2851. PubMedGoogle ScholarCrossref
23.
Mayne  ST, Cartmel  B, Kirsh  V, Goodwin  WJ  Jr.  Alcohol and tobacco use prediagnosis and postdiagnosis, and survival in a cohort of patients with early stage cancers of the oral cavity, pharynx, and larynx.  Cancer Epidemiol Biomarkers Prev. 2009;18(12):3368-3374. PubMedGoogle ScholarCrossref
24.
Leeman  JE, Li  JG, Pei  X,  et al.  Patterns of treatment failure and postrecurrence outcomes among patients with locally advanced head and neck squamous cell carcinoma after chemoradiotherapy using modern radiation techniques.  JAMA Oncol. 2017;3(11):1487-1494. PubMedGoogle ScholarCrossref
25.
Quinlan-Davidson  SR, Mohamed  ASR, Myers  JN,  et al.  Outcomes of oral cavity cancer patients treated with surgery followed by postoperative intensity modulated radiation therapy.  Oral Oncol. 2017;72:90-97. PubMedGoogle ScholarCrossref
26.
Feng  Z, Xu  QS, Wang  C,  et al.  Lymph node ratio is associated with adverse clinicopathological features and is a crucial nodal parameter for oral and oropharyngeal cancer.  Sci Rep. 2017;7(1):6708. PubMedGoogle ScholarCrossref
27.
Liao  CT, Hsueh  C, Lee  LY,  et al.  Neck dissection field and lymph node density predict prognosis in patients with oral cavity cancer and pathological node metastases treated with adjuvant therapy.  Oral Oncol. 2012;48(4):329-336. PubMedGoogle ScholarCrossref
28.
Gil  Z, Carlson  DL, Boyle  JO,  et al.  Lymph node density is a significant predictor of outcome in patients with oral cancer.  Cancer. 2009;115(24):5700-5710. PubMedGoogle ScholarCrossref
29.
Kim  KY, Cha  IH.  Risk stratification of oral cancer patients using a combined prognostic factor including lymph node density and biomarker.  J Cancer Res Clin Oncol. 2012;138(3):483-490. PubMedGoogle ScholarCrossref
30.
Kim  SY, Nam  SY, Choi  SH, Cho  KJ, Roh  JL.  Prognostic value of lymph node density in node-positive patients with oral squamous cell carcinoma.  Ann Surg Oncol. 2011;18(8):2310-2317. PubMedGoogle ScholarCrossref
31.
Amar  A, Rapoport  A, Curioni  OA, Dedivitis  RA, Cernea  CR, Brandão  LG.  The density of metastatic lymph node as prognostic factor in squamous cell carcinoma of the tongue and floor of the mouth.  Braz J Otorhinolaryngol. 2012;78(3):86-90. PubMedGoogle ScholarCrossref
32.
Amin  M, Greene  F, Edge  S,  et al.  AJCC Cancer Staging Manual. 8th ed. New York: Springer International Publishing; 2017. doi:10.1007/978-3-319-40618-3
33.
Lieng  H, Gebski  VJ, Morgan  GJ, Veness  MJ.  Important prognostic significance of lymph node density in patients with node positive oral tongue cancer.  ANZ J Surg. 2016;86(9):681-686. PubMedGoogle ScholarCrossref
Original Investigation
January 2019

Association Between Lymph Node Ratio and Recurrence and Survival Outcomes in Patients With Oral Cavity Cancer

Author Affiliations
  • 1Department of Radiation Oncology, University of Colorado Denver, Aurora
  • 2Department of Health Systems, Management and Policy, University of Colorado Cancer Center, Aurora
  • 3Department of Otolaryngology and Head and Neck Surgery, University of Colorado Denver, Aurora
  • 4Department of Radiation Oncology, City of Hope National Medical Center, Duarte, California
  • 5Department of Pathology, University of Colorado Denver, Aurora
  • 6Division of Medical Oncology, University of Colorado Denver, Aurora
JAMA Otolaryngol Head Neck Surg. 2019;145(1):53-61. doi:10.1001/jamaoto.2018.2974
Key Points

Question  What is the prognostic association between lymph node ratio and tumor recurrence and survival outcomes of oral cavity squamous cell carcinoma and how does it relate to other histopathologic prognostic factors?

Findings  In this single-institution study of 149 patients with oral cavity cancer who received upfront surgery, lymph node ratio was the strongest independent prognostic factor for overall, disease-free, and distant metastasis–free survivals, regardless of neck dissection or postoperative adjuvant therapy status. Lymph node ratio was also found to correlate significantly with other adverse pathologic features.

Meaning  Lymph node ratio may have implications for risk stratification and treatment intensification in patients with oral cavity squamous cell carcinoma.

Abstract

Importance  Oral cavity squamous cell carcinoma (OCSCC) is associated with often-delayed clinical diagnosis, poor prognosis, and expensive therapeutic approaches. Prognostic accuracy is important in improving treatment outcomes of patients with this disease.

Objectives  To assess lymph node ratio (LNR) and other factors in estimating response to treatment and provide prognostic information helpful for clinical decision making.

Design, Setting, and Participants  A retrospective cohort study was conducted from January 1, 2000, to December 31, 2015, at an academic hospital in Denver, Colorado. Participants included 149 patients with primary OCSCC who received curative-intent surgery and/or postoperative adjuvant therapies. Analysis was performed from December 8, 2017, to August 15, 2018.

Main Outcomes and Measures  Overall survival (OS), disease-free survival (DFS), locoregional disease-free survival (LRDFS), and distant metastasis–free survival (DMDFS) adjusted for known prognostic risk factors, as well as correlation of LNR with other histopathologic prognostic factors.

Results  Of the 149 patients included in analysis, 105 were men (70.5%); the median age at diagnosis was 59 years (range, 28-88 years). Using the Kaplan-Meier method, the 5-year survival estimates for OS rate was 40.4% (95% CI, 31.3%-49.3%); DFS, 48.6% (95% CI, 38.6%-58.0%); LRDFS, 57.7% (95% CI, 46.6%-67.2%); and DMDFS, 74.7% (95% CI, 65.1%-82.0%). The median follow-up was 20 months for all patients and 34.5 months (range, 0-137 months) for surviving patients. Nonwhite race (hazard ratio [HR], 2.15; 95% CI, 1.22-3.81), T3-T4 category (HR, 1.99; 95% CI, 1.18-3.35), and LNR greater than 10% (HR, 2.71; 95% CI, 1.39-5.27) were associated with poorer OS. Nonwhite patients also had higher risk of locoregional failures (HR, 2.47; 95% CI, 1.28-4.79), whereas women were more likely to have distant metastasis (HR, 2.55; 95% CI, 1.14-5.71). Floor-of-mouth subsite had fewer locoregional recurrences than did other subsites (HR, 0.45, 95% CI, 0.21-0.99). An LNR greater than 10% independently was associated with worse OS (HR, 2.71; 95% CI, 1.39-5.27), DFS (HR, 2.48; 95% CI, 1.18-5.22), and DMDFS (HR, 6.05; 95% CI, 1.54-23.71). The LNR was associated with N-stage (Cramer V, 0.69; 95% CI, 0.58-0.78), extracapsular extension (Cramer V, 0.55; 95% CI, 0.44-0.66), lymphovascular invasion (Cramer V, 0.46; 95% CI, 0.27-0.61); number of excised lymph nodes (Cramer V, 0.24; 95% CI, 0.06-0.37), margin (Cramer V, 0.22; 95% CI, 0.05-0.38), and tumor thickness combined with depth of invasion (Cramer V, 0.25; 95% CI, 0.05-0.38).

Conclusions and Relevance  Locoregional treatment failure remained the predominant pattern of failure. An advanced pathologic stage and nonwhite race were found to be associated with worse outcomes. The findings from this study suggest that LNR is the most robust prognostic factor and appears to have implications for risk stratification in this disease.

Introduction

Oral squamous cell carcinoma (OSCC) portends high rates of mortality and cervical lymph node metastasis.1 Treatment of OSCC includes upfront surgical resection of the primary tumor with appropriate neck dissection, followed by postoperative radiotherapy with or without chemotherapy in the presence of adverse histopathologic features.2-5 Even with trimodality therapy, the prognosis of OSCC remains poor.6 The current lack of specific molecular markers and biomarkers for OSCC underscores the importance of prognostic accuracy in improving treatment outcomes. In addition, substantial advancements in technology and increasing sophistication of surgical and radiotherapy treatments have been achieved, which calls for a reevaluation of disease and survival outcomes among the milieu of evolving management and changing cancer epidemiologic aspects.

The primary purpose of our study was to assess institutional outcomes of patients with locally advanced OSCC. We evaluated various prognostic variables in association with survival, including the emerging lymph node ratio (LNR), defined as the ratio of positive lymph nodes to total number of lymph nodes excised, which has been reported to convey a superior prognostic accuracy for survival outcomes.7-9 We also examined the influence of socioeconomic factors, such as race, sex, and insurance status, and patient behavioral characteristics, such as tobacco and alcohol use, on survival outcomes.

Methods
Study Design and Patient Eligibility

We reviewed the electronic medical records of 207 patients with a biopsy-proven diagnosis of oral cavity cancer (OCC) who received either curative-intent surgery or postoperative radiotherapy with or without chemotherapy at the University of Colorado Hospital in Denver between January 1, 2000, and December 31, 2015. Data analysis was performed from December 8, 2017, to August 15, 2018. Patient, histopathologic, and treatment-related variables were collected, and an OCC database was established. Patients with OCC as a second primary, distant metastases at the time of diagnosis, radiotherapy and/or chemotherapy without upfront surgery, a history of prior treatment for a malignant tumor of any head or neck site, or tumors of non–squamous cell carcinoma histologic characteristics were excluded from the study (n = 58).

A total of 149 patients with a diagnosis of primary oral cavity squamous cell carcinoma (OCSCC) were identified and constituted the study sample. All patients had surgical resection of a primary OCSCC lesion. Neck dissection at the time of surgery and/or adjuvant radiotherapy or chemoradiotherapy was individualized for patients as determined by the treatment team. The National Comprehensive Cancer Network guidelines were followed for adjuvant radiotherapy.2 The year of diagnosis was grouped into three 5-year periods: 2000-2005, 2006-2010, and 2011-2015. The University of Colorado Institutional Review Board approved the study, with waiver of informed consent. Data were deidentified.

Patient Demographic and Behavioral Characteristic Variables

Binary categorization was adopted for sex (male or female) and race (white or nonwhite as self-reported by each patient). Age at diagnosis was categorized as 60 years or younger and older than 60 years. Tobacco use was grouped as never smokers, 10 pack-years or less, and more than 10 pack-years. Alcohol use was categorized as 7 or less and more than 7 drinks per week. The overall severity of comorbidity for each patient was scored on a scale of 0 to 3 (0, none; 1, mild; 2, moderate; 3, severe), using the Adult Comorbidity Evaluation–27 (ACE-27).10 Insurance status was categorized as private, Veterans Affairs/Tricare, Medicaid or uninsured, and Medicare.

Histopathologic Analysis and Variables

Histopathologic assessments were performed by pathologists experienced in head and neck carcinomas. A comprehensive array of histopathologic features was examined. T and N staging was based on American Joint Committee on Cancer Staging Manual, Seventh Edition (AJCC),11 and analyzed as categorical variables. Depth of invasion and tumor thickness were combined as 1 variable and categorized as 5 mm or less or larger than 5 mm. Surgical margins were categorized as either positive or negative with close margins, per Radiation Therapy Oncology Group 0920s definition,12 categorized as negative. Perineural invasion (PNI), lymphovascular invasion (LVSI), and extracapsular extension (ECE) were categorized as absent or present. A history of leukoplakia and/or oral lichen planus was considered to be present with either a clinical or histopathologic diagnosis. The OCSCC subsites were divided into oral tongue, floor of mouth, and other.

Lymph Node Ratio

The lymph node ratio (LNR) is defined as the number of positive lymph nodes divided by the total number of lymph nodes excised, regardless of the extent of neck dissection. Based on the median LNR value of 0.09, an LNR cutoff value of 10% was selected to stratify patients into roughly equal-sized groups.

Study End Points

The primary end points were overall survival (OS), disease-free survival (DFS), locoregional disease-free survival (LRDFS), and distant metastasis–free survival (DMFS). The secondary end points were to validate the prognostic association between LNR and OS, DFS, LRDFS, and DMFS and explore the association of LNR with other histopathologic features.

Statistical Analysis

All survival measures (OS, DFS, LRDFS, and DMFS) were defined as the number of months from the date of diagnosis to the event of interest. Patients who had local recurrence or regional lymph node metastasis without evidence of distant metastasis during their follow-up visits until their last oncology-related office visit were considered to have locoregional-only failure, whereas patients who had distance metastasis without evidence of local or regional failures were reported as having distant metastasis–only failure. Both locoregional and distant recurrence were considered events in DFS. For all recurrence-related measures, patients who died without recurrence were censored.

We used the Kaplan-Meier method to produce survival curves and test for univariate differences in survival using the log-rank test, and used Cox proportional hazards modeling to obtain univariate and multivariate hazard ratios (HRs). Only covariates with less than 10% missing values were considered for multivariate analyses (MVAs). From these, we selected covariates with either an overall log rank P value <.10 or any class-level P value <.10 in univariate survival analysis to include in multivariate Cox proportional hazards models. If several multivariate models were evaluated, we compared the Akaike information criterion values to select the better fitting model. We used χ2 tests to assess univariate associations with categorical characteristics, such as lymph node involvement. We report the Cramer V statistic (range, 0 [no correlation] to 1 [strong correlation]) as a measure of association, with 95% CI calculated using bootstrapping. Bootstrapping was performed using Stata, version 15 (StataCorp), and remaining analyses were performed using SAS, version 9.4 (SAS Institute Inc). We defined tests with 2-sided P < .05 as significant.

Results
Patient and Treatment Characteristics

Table 1 reports the complete patient demographics and clinical characteristics of the 149 included patients. Most of the patients were male (105 [70.5%]), white (117 [78.5%]), with a history of heavy tobacco (90 [60.4%] with >10 pack-year history) and alcohol (82 [55.0%] with >7 drinks per week) use, and with moderate decompensation of vital organs (101 [67.8%] with ACE-7 grade 2). The median age at diagnosis was 59 years (range, 28-88 years).

Histopathologic and treatment characteristics are summarized in Table 2. Most patients had T3-T4 category tumor at diagnosis (63 [42.3%]), and the most common primary tumor site was oral tongue (61 [40.9%]). Few patients had ECE (35 [23.5%]) or positive margins (48 [32.2%]), and 29 patients (19.5%) had a history of leukoplakia or oral lichen planus. Most patients (127 [85.2%]) received neck dissection with a median of 29 lymph nodes dissected (range, 1-110). The median number of positive nodes was 2, yielding a median LNR of 0.09. Most patients (50 [33.6%]) had an LNR of 10% or less, while 35 (23.5%) had an LNR greater than 10%, and 42 (28.2%) had no positive lymph nodes. Most patients (123 [82.6%]) received adjuvant radiation therapy with 90 patients (60.4%) also receiving concurrent chemotherapy.

Patterns of Failure and Survival Outcomes

The median follow-up, measured from the end of treatment until last oncology-related follow-up, was 20 months (range, 0-137 months) for all patients and 34.5 months (range, 0-137 months) for surviving patients. Estimated 2- and 5-year OS survival rates were 70.4% (95% CI, 62.1%-77.3%) for 2 years and 40.4% (95% CI, 31.3%-49.3%) for 5 years (Figure, A). Estimated DFS was 58.9% (95% CI, 49.6%-67.1%) for 2 years and 48.7% (95% CI, 38.6%-58.0%) for 5 years (Figure, B). An estimated 70.7% (95% CI, 61.4%-78.1%) of patients were free from locoregional recurrence at 2 years and an estimated 57.7% (95% CI, 46.6%-67.2%) at 5 years (Figure, C). An estimated 77.7% (95% CI, 68.9%-84.3%) patients were free from distant metastasis at 2 years and an estimated 74.7% (95% CI, 65.1%-82.0%) at 5 years (Figure, D). Our Kaplan-Meier analyses, after stratifying patients with an LNR cutoff value of 10%, revealed significant differences in OS, DFS, and DMFS between high (LNR>10%) and low LNR (LNR≤10%) survival curves (eFigure in the Supplement). The HRs for the high and low LNR groups were as follows: OS, 2.35 (95% CI, 1.30-4.27) vs 0.87 (95% CI, 0.47-1.64); DFS, 3.08 (95% CI, 1.53-6.21) vs 1.20 (95% CI, 0.59-2.46); and DMFS, 5.30 (95% CI, 1.68-16.70) vs 2.10 (95% CI, 0.65-6.81).

Prognostic Factors by Survival Outcomes

In the univariate analysis (Table 3), OS was adversely associated with races other than white (HR, 2.07; 95% CI, 1.25-3.41), Medicaid or being uninsured (HR, 1.84; 95% CI, 1.06-3.19), T3-T4 tumor category (HR, 1.83; 95% CI, 1.16-2.89), positive margin (HR, 2.10; 95% CI, 1.33-3.32), PNI (HR, 2.06; 95% CI, 1.19-3.54), and LNR greater than 10% (HR, 2.35; 95% CI, 1.30-4.27). Leukoplakia/lichen planus was associated with a lower risk of death (HR, 0.42; 95% CI, 0.21-0.85). In the MVA, being nonwhite (HR, 2.15; 95% CI, 1.22-3.81), along with having T3-T4 tumor category (HR, 1.99; 95% CI, 1.18-3.35) and LNR greater than 10% (HR, 2.71; 95% CI, 1.39-5.27), remained strong predictors for worse OS (Table 4).

Poorer DFS, as indicated in the univariate analysis, was predicted by N2-N3 nodal category (HR, 2.09; 95% CI, 1.07-4.10), positive margin (HR, 2.27; 95% CI, 1.35-3.79), LVSI (HR, 2.00; 95% CI, 1.09-3.68), and LNR greater than 10% (HR, 3.08; 95% CI, 1.53-6.21), whereas tumors originating in the floor of mouth were associated with better disease control compared with those arising from other subsites (HR, 0.50; 95% CI, 0.26-0.96). Factors adversely affecting OS, such as having Medicaid or being uninsured (HR, 1.72; 95% CI, 0.92-3.22), T3-T4 tumor category (HR, 1.56; 95% CI, 0.93-2.60), and positive PNI (HR, 1.75; 95% CI, 0.95-3.25) also portended an increased risk of disease recurrence. Two separate MVA models were examined to compare the use of nodal stage vs LNR as a predictor. The model with LNR had the lower Akaike information criterion score and was selected as the final MVA model. In the MVA, only LNR greater than 10% (HR, 2.48; 95% CI, 1.18-5.22) remained independently associated with decreased DFS.

Poorer locoregional control was associated with race other than white (HR, 2.17; 95% CI, 1.14-4.17) and positive surgical margins (HR, 1.98; 95% CI, 1.09-3.60) in the univariate analysis. Multivariate analysis revealed that nonwhite race continued to predict for an increased risk of locoregional recurrence (HR, 2.47; 95% CI, 1.28-4.79), while floor-of-mouth subsite was independently associated with significantly decreased recurrence (HR, 0.45; 95% CI, 0.21-0.99).

For DMDFS, univariate analysis identified the N2-N3 nodal category (HR, 3.38; 95% CI, 1.12-10.20), positive margins (HR, 2.50; 95% CI, 1.19-5.25), PNI (HR, 4.04; 95% CI, 1.39-11.74), LVSI (HR, 2.65; 95% CI, 1.07-6.58), and LNR greater than10% (HR, 5.30; 95% CI, 1.68-16.70) to be associated with a higher risk of distant metastasis. Two separate MVA models were examined to compare the use of nodal stage vs LNR as a predictor. The model with LNR had the lower Akaike information criterion score and was selected as the final MVA model. In the MVA, LNR greater than 10% (HR, 6.05; 95% CI, 1.54-23.71) remained a significant prognostic factor. Female sex (HR, 2.55; 95% CI, 1.14-5.71) emerged as an independent factor associated with more than a 2-fold increased risk of distant metastasis, while leukoplakia and/or lichen planus was associated with improved control of distant disease (HR, 0.22; 95% CI, 0.05-0.96).

Correlation of LNR With Histopathologic Factors

Correlation analysis between LNR and other histopathologic factors (eTable in the Supplement) revealed that LNR was strongly associated with N category (Cramer V, 0.69; 95% CI, 0.58-0.78), ECE (Cramer V, 0.55; 95% CI, 0.44-0.66), and LVSI (Cramer V, 0.46; 95% CI, 0.27-0.61). Moderate associations were also identified between LNR and the number of LNs dissected (Cramer V, 0.24; 95% CI, 0.06-0.37), margin (Cramer V, 0.22; 95% CI, 0.05-0.38), and tumor thickness/depth of invasion (Cramer V, 0.25; 95% CI, 0.05-0.38).

Discussion

Oral cavity squamous cell carcinoma is a heterogeneous group of head and neck cancers whose prognosis depends on diverse patient-, disease-, and treatment-related factors. Our data identified various demographic and disease characteristics implicated in survival outcomes of patients with OCSCC. Significant disparities among racial groups have been reported in recently published analyses, with nonwhite patients having worse outcomes both in OS and in disease-specific survival than white patients with OCSCC.13,14 Consistent with these studies, our data revealed that being nonwhite was associated with a greater than 2-fold increased risk of locoregional recurrence and death from OCSCC. The narrow 95% CI of our finding further supports the strong prognostic significance of race for both locoregional recurrence and OS.

Age at diagnosis is also often considered an independent predictor of survival outcomes.9,15 Our findings, however, did not show an increased risk of death among older patients as previously reported. This discrepancy is likely because these patients, despite their older age or advanced disease, were treated with multimodality therapy. In addition, in the setting of increased OCSCC in women,16 the role that sex plays in survival outcomes has yet to be validated.17,18 Our data, although not demonstrating significant sex disparity in OS, DFS, or LRDFS, revealed a strong correlation between women and a more than 2.5-fold increased risk of distant metastasis that warrants further evaluation.

Medical comorbidities have been suggested to affect survival of patients with head and neck cancers.19,20 The severity of comorbidities was not shown to have an independent association with survival in our analyses. However, with most patients in our cohort having an ACE-27 score of 2, an appreciable association remained, with narrow 95% CIs showing a decrease in OS with increasing comorbidity severity. The clinical relevance of comorbidity severity may need to be taken into consideration in treatment planning in addition to the traditional TNM classification. A body of literature has linked smoking to poorer survival.21-23 We could not detect the prognostic significance of smoking with a binary cutoff value of 10 pack-years. Similarly, we did not find a significant association between alcohol consumption and survival, which differs from previously published data showing that alcohol consumption before and after diagnosis adversely affected head and neck cancer survival.23 This difference could be because of our small sample size, underreporting of tobacco and alcohol use, or the limitation of our data in not accounting for smoking or drinking during or after treatment.

A main determinant of survival for head and neck cancers is the stage of cancer at diagnosis.9 Our results were consistent with previous studies showing that patients presenting with advanced primary tumor site (42.3%, T3-T4 category) had decreased OS. Similar to other published studies,24,25 our pattern of failure analysis revealed that, despite most patients receiving trimodality therapy, locoregional failure remained the predominant pattern of unsuccessful therapy. The treatment options for OCSCC expanded in 2004 when level 1 evidence was established with the findings of the Radiation Therapy Oncology Group 9501 and European Organization for Research and Treatment of Cancer 22931 trials.3,4 Based in part on these landmark trials, many centers today have adopted trimodality therapy consisting of surgery with adjuvant chemoradiotherapy for advanced-stage OCC, particularly in those with pathologically high-risk features, defined as ECE or positive surgical margins. Our data showed a 2.30- and 2.50-fold increase in risk of distant metastasis in the presence of ECE and positive margins, respectively, supporting their prognostic importance in distant disease control.

A major finding of our analyses is the association between LNR and survival outcomes. There is growing evidence that LNR is superior to the traditional nodal staging system in predicting outcomes in OCSCC.7-9 We found that LNR was the most salient prognostic factor for OS and DFS, with a high LNR independently predicting more than a 2.5-fold increased risks of death and disease recurrence. The association between a high LNR and DMFS was also evident, with a 6-fold increased risk of distant metastasis, although the precision of such a conclusion may be limited owing to its relatively wide 95% CI. Further studies with a larger sample size may help to assess the degree of influence of LNR on distant metastasis more accurately. Similar to the previous studies,26 we also found LNR to be correlated with adverse pathologic features, such as ECE, LVSI, advanced N category, positive margins, and tumor thickness/depth of invasion.

Our findings therefore join those of numerous other analyses suggesting the superiority of LNR to the conventional nodal staging in predicting outcomes.7-9,27-31 At present, the updated TNM staging system does not incorporate LNR into risk stratification,32 nor does the National Comprehensive Cancer Network factor LNR into treatment recommendations.2 By current guidelines, intensification of adjuvant therapy remains indicated only in the setting of ECE or positive margins.2 Although the nodal staging system incorporates the raw number of positive nodes dissected, the nodal sampling procedure is frequently overlooked. Multiple institutional, multi-institutional, and international analyses7,8,27-31,33have provided a growing body of evidence that LNR independently identifies patients at high risk for disease recurrence and mortality, raising the possibility of incorporating LNR into risk-stratification schema and into the selection of adjuvant therapies. Further research may involve the development of surgical and pathologic quality metrics for proper assessment of LNR and the testing of metrics in prospective trials for establishing LNR as a prognostic or predictive factor.

Limitations

Our study contains limitations inherent to a retrospective analysis, including a relatively small sample size and selection bias. Other limitations may stem from unmeasured confounders and the inclusion of heterogeneous tumor subsites, varied tumor stages, and diversified radiotherapy and chemotherapy regimens in terms of such factors as dosage, agents, and timing. In addition, during the 2 decades of our study period, the sophistication of diagnostic imaging increased; surgical techniques, especially for reconstruction, have changed, the use of chemotherapy has become more common, and the radiotherapy technique has evolved. In our analysis, it was not possible to isolate all of the variables that could influence outcome. In addition, although the LNR cutoff value of 10% is in line with values used in other studies, which have ranged from 4.8% to 16%,33 the 10% level was specific to the data set of our institution and thus may limit its generalizability.

Conclusions

Our institutional outcomes showed that locoregional failure remained the predominant pattern of failure for OSCC. We identified variables associated with survival and disease control that may be hypothesis generating for treatment intensification given the current lack of specific biomarkers for prognosis. In particular, LNR served as a possible robust predictor of survival outcomes and warrants consideration in prospective studies aimed at determining optimal risk stratification and treatment strategies for adjuvant therapy for this disease.

Back to top
Article Information

Corresponding Author: Sana D. Karam, MD, PhD, Department of Radiation Oncology, University of Colorado, 1665 Aurora Ct, Ste 1032, Aurora, CO 80045 (sana.karam@ucdenver.edu).

Accepted for Publication: September 6, 2018.

Published Online: November 15, 2018. doi:10.1001/jamaoto.2018.2974

Author Contributions: Dr Karam had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Ding, Stokes, Eguchi, Sumner, Amini.

Acquisition, analysis, or interpretation of data: Ding, Stokes, Eguchi, Hararah, Sumner, Goddard, Somerset, Bradley, McDermott, Raben, Karam.

Drafting of the manuscript: Ding, Eguchi, Bradley, Karam.

Critical revision of the manuscript for important intellectual content: Ding, Stokes, Hararah, Sumner, Amini, Goddard, Somerset, Bradley, McDermott, Raben, Karam.

Statistical analysis: Stokes, Eguchi, Hararah, Bradley, Karam.

Obtained funding: Karam.

Administrative, technical, or material support: Eguchi, Somerset, Bradley, McDermott.

Supervision: Amini, Goddard, Bradley.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.

Funding/Support: This project was supported by Population Health Shared Resource, University of Colorado Cancer Center, grant P30CA046934 and National Institutes of Health grant P30-CA046934. Dr Karam is supported by the Paul Calabresi Career Development Award for Clinical Oncology K12, CA086913, Radiological Society of North America grant RSD1713, Golfer’s against Cancer, Cancer League of Colorado Grant, and the Marsico fund.

Role of the Funder/Sponsor: The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

References
1.
American Cancer Society. Cancer Facts & Figures 2016. Cancerorg. 2018. https://www.cancer.org/research/cancer-facts-statistics/all-cancer-facts-figures/cancer-facts-figures-2016.html. Accessed May 30, 2018.
2.
National Comprehensive Cancer Network. NCCN Guidelines http://www.nccn.org/professionals/physician_gls/pdf/head-and-neck.pdf. Accessed May 30, 2018.
3.
Bernier  J, Domenge  C, Ozsahin  M,  et al; European Organization for Research and Treatment of Cancer Trial 22931.  Postoperative irradiation with or without concomitant chemotherapy for locally advanced head and neck cancer.  N Engl J Med. 2004;350(19):1945-1952. PubMedGoogle ScholarCrossref
4.
Cooper  JS, Pajak  TF, Forastiere  AA,  et al; Radiation Therapy Oncology Group 9501/Intergroup.  Postoperative concurrent radiotherapy and chemotherapy for high-risk squamous-cell carcinoma of the head and neck.  N Engl J Med. 2004;350(19):1937-1944.PubMedGoogle ScholarCrossref
5.
Bernier  J, Cooper  JS, Pajak  TF,  et al.  Defining risk levels in locally advanced head and neck cancers.  Head Neck. 2005;27(10):843-850. PubMedGoogle ScholarCrossref
6.
Shrime  MG, Bachar  G, Lea  J,  et al.  Nodal ratio as an independent predictor of survival in squamous cell carcinoma of the oral cavity.  Head Neck. 2009;31(11):1482-1488. PubMedGoogle ScholarCrossref
7.
Patel  SG, Amit  M, Yen  TC,  et al; International Consortium for Outcome Research (ICOR) in Head and Neck Cancer.  Lymph node density in oral cavity cancer.  Br J Cancer. 2013;109(8):2087-2095. PubMedGoogle ScholarCrossref
8.
Reinisch  S, Kruse  A, Bredell  M, Lübbers  HT, Gander  T, Lanzer  M.  Is lymph-node ratio a superior predictor than lymph node status for recurrence-free and overall survival in patients with head and neck squamous cell carcinoma?  Ann Surg Oncol. 2014;21(6):1912-1918. PubMedGoogle ScholarCrossref
9.
Goldenberg  D, Mackley  H, Koch  W, Bann  DV, Schaefer  EW, Hollenbeak  CS.  Age and stage as determinants of treatment for oral cavity and oropharyngeal cancers in the elderly.  Oral Oncol. 2014;50(10):976-982. PubMedGoogle ScholarCrossref
10.
Adult comorbidity evaluation-27. http://cancercomorbidity.wustl.edu/ElectronicACE27.aspx. Accessed October 12, 2018.
11.
American Joint Committee on Cancer.  AJCC Cancer Staging Manual. 7th ed. New York: Springer; 2010.
12.
Radiation therapy with or without cetuximab in treating patients who have undergone surgery for locally advanced head and neck cancer. https://clinicaltrials.gov/ct2/show/NCT00956007. Accessed May 30, 2018.
13.
Osazuwa-Peters  N, Massa  ST, Christopher  KM, Walker  RJ, Varvares  MA.  Race and sex disparities in long-term survival of oral and oropharyngeal cancer in the United States.  J Cancer Res Clin Oncol. 2016;142(2):521-528. PubMedGoogle ScholarCrossref
14.
Zandberg  DP, Liu  S, Goloubeva  O,  et al.  Oropharyngeal cancer as a driver of racial outcome disparities in squamous cell carcinoma of the head and neck.  Head Neck. 2016;38(4):564-572. PubMedGoogle ScholarCrossref
15.
Pignon  JP, le Maître  A, Maillard  E, Bourhis  J; MACH-NC Collaborative Group.  Meta-analysis of chemotherapy in head and neck cancer (MACH-NC).  Radiother Oncol. 2009;92(1):4-14. PubMedGoogle ScholarCrossref
16.
Saba  NF, Goodman  M, Ward  K,  et al.  Gender and ethnic disparities in incidence and survival of squamous cell carcinoma of the oral tongue, base of tongue, and tonsils.  Oncology. 2011;81(1):12-20. PubMedGoogle ScholarCrossref
17.
Roberts  JC, Li  G, Reitzel  LR, Wei  Q, Sturgis  EM.  No evidence of sex-related survival disparities among head and neck cancer patients receiving similar multidisciplinary care.  Clin Cancer Res. 2010;16(20):5019-5027. PubMedGoogle ScholarCrossref
18.
McLean  A, LeMay  W, Vila  P, Wegner  M, Remington  P.  Disparities in oral and pharyngeal cancer incidence and mortality among Wisconsin residents, 1999-2002.  WMJ. 2006;105(6):32-35. PubMedGoogle Scholar
19.
Paleri  V, Wight  RG, Silver  CE,  et al.  Comorbidity in head and neck cancer.  Oral Oncol. 2010;46(10):712-719. PubMedGoogle ScholarCrossref
20.
Bøje  CR.  Impact of comorbidity on treatment outcome in head and neck squamous cell carcinoma.  Radiother Oncol. 2014;110(1):81-90. PubMedGoogle ScholarCrossref
21.
Kawakita  D, Hosono  S, Ito  H,  et al.  Impact of smoking status on clinical outcome in oral cavity cancer patients.  Oral Oncol. 2012;48(2):186-191. PubMedGoogle ScholarCrossref
22.
Giraldi  L, Leoncini  E, Pastorino  R,  et al.  Alcohol and cigarette consumption predict mortality in patients with head and neck cancer.  Ann Oncol. 2017;28(11):2843-2851. PubMedGoogle ScholarCrossref
23.
Mayne  ST, Cartmel  B, Kirsh  V, Goodwin  WJ  Jr.  Alcohol and tobacco use prediagnosis and postdiagnosis, and survival in a cohort of patients with early stage cancers of the oral cavity, pharynx, and larynx.  Cancer Epidemiol Biomarkers Prev. 2009;18(12):3368-3374. PubMedGoogle ScholarCrossref
24.
Leeman  JE, Li  JG, Pei  X,  et al.  Patterns of treatment failure and postrecurrence outcomes among patients with locally advanced head and neck squamous cell carcinoma after chemoradiotherapy using modern radiation techniques.  JAMA Oncol. 2017;3(11):1487-1494. PubMedGoogle ScholarCrossref
25.
Quinlan-Davidson  SR, Mohamed  ASR, Myers  JN,  et al.  Outcomes of oral cavity cancer patients treated with surgery followed by postoperative intensity modulated radiation therapy.  Oral Oncol. 2017;72:90-97. PubMedGoogle ScholarCrossref
26.
Feng  Z, Xu  QS, Wang  C,  et al.  Lymph node ratio is associated with adverse clinicopathological features and is a crucial nodal parameter for oral and oropharyngeal cancer.  Sci Rep. 2017;7(1):6708. PubMedGoogle ScholarCrossref
27.
Liao  CT, Hsueh  C, Lee  LY,  et al.  Neck dissection field and lymph node density predict prognosis in patients with oral cavity cancer and pathological node metastases treated with adjuvant therapy.  Oral Oncol. 2012;48(4):329-336. PubMedGoogle ScholarCrossref
28.
Gil  Z, Carlson  DL, Boyle  JO,  et al.  Lymph node density is a significant predictor of outcome in patients with oral cancer.  Cancer. 2009;115(24):5700-5710. PubMedGoogle ScholarCrossref
29.
Kim  KY, Cha  IH.  Risk stratification of oral cancer patients using a combined prognostic factor including lymph node density and biomarker.  J Cancer Res Clin Oncol. 2012;138(3):483-490. PubMedGoogle ScholarCrossref
30.
Kim  SY, Nam  SY, Choi  SH, Cho  KJ, Roh  JL.  Prognostic value of lymph node density in node-positive patients with oral squamous cell carcinoma.  Ann Surg Oncol. 2011;18(8):2310-2317. PubMedGoogle ScholarCrossref
31.
Amar  A, Rapoport  A, Curioni  OA, Dedivitis  RA, Cernea  CR, Brandão  LG.  The density of metastatic lymph node as prognostic factor in squamous cell carcinoma of the tongue and floor of the mouth.  Braz J Otorhinolaryngol. 2012;78(3):86-90. PubMedGoogle ScholarCrossref
32.
Amin  M, Greene  F, Edge  S,  et al.  AJCC Cancer Staging Manual. 8th ed. New York: Springer International Publishing; 2017. doi:10.1007/978-3-319-40618-3
33.
Lieng  H, Gebski  VJ, Morgan  GJ, Veness  MJ.  Important prognostic significance of lymph node density in patients with node positive oral tongue cancer.  ANZ J Surg. 2016;86(9):681-686. PubMedGoogle ScholarCrossref
×