2c Laryngoscope, 2017.

Background: The United States population is aging, and cancer is the second most common cause of death in the elderly. Head and neck squamous cell carcinoma (HNSCC) incidence is increasing and contributes 2.2% of all cancer mortality. HNSCC research often excludes elderly patients due to disqualifying comorbidities, similar to many cancer sites. These patients also may not receive adequate therapy due to age despite evidence of equal survival after controlling for comorbidities. Beyond oncologic variables, demographic factors have been shown to impact HNSCC survival, including age, socioeconomic status, race, sex, poverty, insurance, and marriage. Whether these associations are maintained in elderly patients is unknown. This study aims to compare demographic predictors of HNSCC survival between age cohorts. Methods: Adult patients with squamous cell carcinoma of mucosal head and neck sites were selected from the Surveillance, Epidemiology and End Result database from 2004 to 2013. Patients were excluded with previous malignancies or missing data for follow-up, marital status, and surgical treatment. Demographic and tumor data were collected, including site, stage, treatment, age, race, sex, insurance, and median county-level income. Patients were divided into three age cohorts: younger (18-49 years), middle (50-74 years), and older (>75 years). Cohorts were compared with two-tailed chi-squared and ANOVA tests as appropriate with p < 0.05 considered significant. Previously identified predictors of HNSCC survival were assessed in each cohort using multivariate Fine and Gray competing risk models controlled for oncologic variables. Subdistribution hazard ratios (sHR) with 95% confidence intervals (CI) are reported. Sensitivity analyses were performed by (1) excluding inadequately treated patients, (2) removing adjuvant therapies from the model, and (3) varying the cutoff between age cohorts. Inadequate treatment was considered less than 1 modality for stage I-II or less than 2 modalities for stage III-IV. Results: The study cohort consisted of 69,098 patients with a majority white (75.4%), male (76.7%), married (55.2%), and insured (56.3%). The median age at diagnosis was 61.7 years with 14.3% below 50 years and 15.3% 75 years or above. Compared to the young and middle-aged cohorts, the older cohort was significantly more often female (35% vs 25.1 and 20.4%), white (78.7% vs 69.4 and 75.9%), and insured (63.5% vs 46.5% and 56.8%), but received adequate treatment less often (72.0% vs 86.3% and 82.7%) (p < 0.001 for all). In the survival models, several demographic factors showed different effects on cancer survival between age cohorts. Male sex was associated with lower mortality in the older group (sHR 0.92, CI 0.85-1.00), but not in other cohorts. In the young and middle-aged cohort, Black race was associated with increased mortality (sHR 1.43 and 1.23, CI 1.27-1.60 and 1.17-1.30, respectively), but this is not found in the older cohort (sHR 1.07, CI 0.94-1.22). In all cohorts, single marital status was associated with higher mortality, but the effect was greatest in the younger cohort (sHR 1.52, CI 1.37-1.68) and least in the oldest cohort (sHR 1.14, CI 1.01-1.28). These effects were preserved in the sensitivity analyses and with varying the age cutoff between middle and older cohorts as low as 65 years. Conclusion: A substantial proportion of HNSCC patients are elderly. These patients are less often treated with adequate curative therapy and differ demographically from their younger peers. Uniquely in the older HNSCC patients, female sex is a risk factor for cancer mortality, while the impact of race and marital status was reduced compared to the younger cohorts. While future research investigates the mechanisms by which demographics affect survival, the differences between age cohorts must be considered. Citation Format: Sean T. Massa, Lauren Cass, Sai Challapalli, Zisansha Zahirsha, Matt Simpson, Nosayaba Osazuwa-Peters, Gregory Ward. Age differences in demographic predictors of head and neck cancer survival [abstract]. In: Proceedings of the Tenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2017 Sep 25-28; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2018;27(7 Suppl):Abstract nr A88.

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ObjectiveDetermine trends and survival implications of adjuvant systemic therapy use for lower risk head and neck cancer.Study DesignRetrospective cohort study.SettingUS National Cancer Database, 2010 to 2019.MethodsPatients with mucosal head and neck squamous cell carcinoma treated with surgery and postoperative radiation therapy were identified. Adjuvant systemic therapy trends in those with and without extranodal extension or positive margins were assessed as annual percent change by JoinPoint analysis. Factors associated with adjuvant systemic therapy and overall survival were assessed with multivariable models and cox proportional hazard models, respectively.ResultsFrom 2010 to 2019, approximately one‐third of head and neck cancer patients without extranodal extension or positive margins received adjuvant systemic therapy. This rate decreased throughout the study period, with the highest annual percent change from 2016 to 2019 (12.21%; 95% confidence interval: 3.73%‐19.95%). Younger age, male sex, Hispanic ethnicity, community program setting, advanced stage, and lymphovascular invasion increased the odds a patient would receive adjuvant systemic therapy. Adjuvant systemic therapy was associated with inferior overall survival when used in those without extranodal extension or positive margins after controlling for covariates.ConclusionThough decreasing, adjuvant systemic therapy use is still common in the absence of extranodal extension and positive margins, and a variety of patient, provider, and oncologic factors may influence its use. The inferior overall survival after adjuvant systemic therapy in the absence of high‐risk features suggests any oncologic benefit may not outweigh the costs and morbidity of the therapy.

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