Abstract
Background
Oropharyngeal cancer (OPC) involves the base of tongue, palatine tonsils, lingual tonsil, and soft palate. Established risk factors for OPC include tobacco usage, alcohol usage, and human papillomavirus infection. Although white populations tend to have the highest risk of developing OPC, Black patients are more likely to experience distant stage disease.
Methods
The aim of this study was to elucidate epidemiological factors that are associated with regional and distant stage disease at OPC diagnosis. We performed a retrospective cross-sectional analysis utilizing the Florida Cancer Data System (FCDS) from 2010 to 2017. Sociodemographic factors among Black and white patients were compared using chi-square analysis. Multivariable logistic regression analysis determined risk factors associated with distant stage diagnosis. Geographical mapping of census tract levels was performed to illustrate prevalence of distant stage disease at diagnosis in Florida.
Results
Among 8,908 OPC cases, 7,534 (84.6%) patients were white non-Hispanic, 834 (9.4%) were white Hispanic, and 540 (6.1%) were Black. Multivariable logistic regression revealed increased distant stage disease compared to local stage among those who were Black (compared to white non-Hispanic and white Hispanic; OR = 1.55 [95% CI:1.12–2.13], p = 0.007), separated/divorced/widowed (OR = 1.36 [95% CI:1.11–1.68], p = 0.004) (compared to married), and lack insurance (OR = 1.67 [95% CI:1.16–2.41], p = 0.006) or have public insurance (OR = 1.26 [95% CI:1.04–1.53], p = 0.017) (compared to those with private insurance). There was decreased regional stage disease compared to local stage among females (OR = 0.57 [95% CI:0.49–0.66], p < .001) and older patients (OR = 0.975, [95% CI:0.968–0.982], p < 0.001). Mapping revealed higher percent of distant stage diagnoses in census tracts with lower median income.
Conclusions
Distant stage at OPC diagnosis is influenced by many risk factors, including race, sex, age, marital, and insurance status. Geographical mapping analysis can help direct screening efforts to high-risk communities.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12889-025-25388-z.
Keywords: Oropharynx, Racial disparities, Distant stage diagnosis, SEER stage, Tobacco
Background
Oropharyngeal cancer (OPC) includes cancer of the base of tongue, palatine tonsils, lingual tonsil, and soft palate [1]. In 2020, there were about 98,412 new cases of OPC and 48,143 OPC-related deaths worldwide [2]. Incidence rates of OPC are twice as high among males compared to females. While the incidence of OPC has been increasing among both genders over the past decade, white men have been disproportionally affected [3–5]. This trend is seen in Florida, where the prevalence of OPC among males significantly increased from 1981–2008 [6].
Several risk factors for the development of OPC have been identified, including tobacco use, alcohol use, and infection with HPV [7, 8]. As many as 60–70% of OPC cases in the United States are HPV-positive likely due to the increase in overall number of HPV infections [3, 9]. OPC had the highest age-adjusted incidence rate of all head and neck cancers from 2004–2015, and there was a 23% increased incidence of stage IVC (metastatic) OPC [10].
The same study by Thompson-Harvey et. al determined that there is an increasing incidence of distant stage (defined as stage IVC) head and neck cancers in the United States, with males and Black patients being the most affected populations [10]. Even though white populations have been shown to be at the highest risk of developing OPC [11], Black patients are more likely to experience distant stage disease. Previous research has demonstrated that Black race, and not decreased socioeconomic status, is correlated with decreased OPC survival rates [12, 13].
In addition to racial disparities, previous research has also analyzed the impact of healthcare insurance status on OPC stage at diagnosis. After controlling for sociodemographic factors, patients with distant stage at diagnosis were more likely to be uninsured or have public insurance [14]. Rural residence has been shown to correlate with higher tumor and nodal stage OPC at presentation [15]. At the same time, patients with a higher education had an increased incidence of all stages of OPC [15].
In the US, Florida has the 9th highest state rate of oral cavity cancer and OPC. However, the geographic distribution of OPC and sociodemographic risk factors for OPC in Florida are not well understood. This paper aims to determine how epidemiological factors—such as sex, race, income, educational status, and smoking status among Floridians contribute to regional and distant stages OPC at diagnosis. Due to a lack of symptoms during the early disease course, OPC patients commonly present with a high disease burden, emphasizing the need for effective screening methods and early detection. Through these analyses, we hope to highlight high risk populations and thus opportunities for earlier prevention, screening, and treatment.
Methods
This was a retrospective database study using the Florida Cancer Data System (FCDS), a statewide cancer registry. Cancer cases in Florida from 254 hospitals statewide were reported to the database, and data was collected at the time of cancer diagnosis. No follow-up data was utilized. The study was deemed non-human subjects research and was IRB-exempt. We first selected as inclusion criteria, OPC cases diagnosed from 2010 to 2017 classified as squamous cell carcinoma of the base of tongue, uvula, soft palate, lingual tonsil, palatine tonsils, and oropharynx (ICD codes C019, C024, C051, C052, C090-C109) with histology codes: 8050, 8052, 8070, 8071, 8072, 8073, 8074, 8075, 8076, 8078, 8082, 8083, 8084, 8085, and 8086, age ≥ 18 years, SEER stage (local, regional or distant), and that the patient was not diagnosed by autopsy or death certificate (N = 72) [16]. Patients with in-situ disease per histology code were excluded. We then excluded from analysis cases due to unknown marital status, insurance, race, ethnicity, or sex. Patients with a reported race of “other” were also excluded. Our study population of 8,908 patients included patients with “unknown” tobacco status (Fig. 1).
Fig. 1.
Selection criteria for the study cohort of OPC diagnosed between 2010 to 2017
The database reports patients’ age at diagnosis, sex, race, ethnicity, marital status, smoking status (current, former, or never smoker, unknown), geographical location of residence (rural vs. urban, based on patients’ home address as determined by US census tract definition), primary insurance status, and Surveillance, Epidemiology and End Results (SEER) disease stage defined by the National Cancer Institute. Household income and patient-level education data was not available in the FCDS database. Therefore, the American Community Survey 5-Year Data from 2015 was utilized to extrapolate educational level and median household income by census tract ID from the FCDS database, and patients were further categorized by statewide quartiles.
Patients with OPC were categorized into three mutually exclusive and exhaustive groups for analysis based on their SEER stage. Specifically, individuals with a SEER stage of “local” were classified as having local stage OPC. Those falling under SEER stage regional, which includes “regional with direct extension,” “regional with nodes only,” and “regional with direct extension and nodes,” were grouped as regional stage OPC. Lastly, patients with a SEER stage of “distant” were designated as having distant stage OPC [17, 18]. Distant stage OPC at diagnosis was considered the primary, poor prognostic outcome. We assessed the effects of age, sex, race, ethnicity, marital status, insurance status, smoking status, and geographical region of residence as the potential predictors of distant or regional compared to local stage OPC. HPV status was not reported in the database and could not be evaluated as a predictor.
Sociodemographic factors among Black and white OPC patients were compared using chi-square analysis. To determine risk factors associated with regional and distant disease stages versus local stage at diagnosis, univariable and multivariable multinomial logistic regression analysis was performed using SPSS software. Estimates of odds ratios (ORs) with corresponding Wald 95% confidence intervals and p-values testing null hypothesis H0: OR = 1 are presented. Results were considered significant at p-value < 0.05. R package < ArcGIS Pro > was employed to perform geographic mapping of cancer incidence, showing percent of patients with distant stage diagnosis and median income at census tracts.
Results
Of the 13,941 OPC cases diagnosed between 2010–2017, 10,771 met initial inclusion criteria such as selected morphology, histology, and SEER stage. After exclusion of additional cases with unknown key predictor information (n = 1,863), 8,908 were included in the final analyses. Patients were excluded due to unknown sex (n = 3), unknown marital status (n = 387), unknown insurance status (n = 569), unknown race/ethnicity (n = 213), or unknown education and income data (n = 691) (Fig. 1).
Our population was predominantly white non-Hispanic (n = 7,534, 84.6%), male (n = 7,334, 82.3%), and urban residents (n = 6,369, 71.5%) (Table 1). Most patients had public health insurance (n = 4,977, 55.9%) or private health insurance (n = 3,418, 38.4%), and few had no form of health insurance (n = 513, 5.8%). Overall, 2,415 (27.1%) OPC patients were never smokers and only 1,923 (21.6%) were current smokers at the time of diagnosis. Most patients were regional stage at diagnosis (n = 6,204, 69.6%), and fewer were local (n = 1,175, 13.2%) or distant (n = 1,529, 17.2%) stage at diagnosis.
Table 1.
Demographics of OPC patients diagnosed from 2010–2017 by Racial Group
| All | White Non-Hispanic | White Hispanic | Black | P | |||||
|---|---|---|---|---|---|---|---|---|---|
| n | % | n | % | n | % | n | % | ||
| No. of Subjects | 8908 | 7534 | 84.6 | 834 | 9.4 | 540 | 6.1 | ||
| Age at diagnosis | <.001 | ||||||||
| Mean (SD) | 62.7 (10.4) | 62.9a (10.3) | 61.6b (11.3) | 61.3b (10) | |||||
| Median (P25, P75) | 62 (55, 69) | 62 (56,70) | 60 (54,69) | 61 (55,67) | |||||
| Sex | 0.052 | ||||||||
| Male | 7334 | 82.3 | 6217 | 82.5a | 693 | 83.1a | 424 | 78.5a | |
| Female | 1574 | 17.7 | 1317 | 17.5a | 141 | 16.9a | 116 | 21.5a | |
| Marital status | <.001 | ||||||||
| Married | 5234 | 58.8 | 4544 | 60.3a | 484 | 58.0a | 206 | 38.1b | |
| Single/Unmarried | 1914 | 21.5 | 1492 | 19.8a | 186 | 22.3a | 236 | 43.7b | |
| Separated/Divorced/Widowed | 1760 | 19.8 | 1498 | 19.9a | 164 | 19.7a | 98 | 18.1a | |
| Insurance status | <.001 | ||||||||
| Private Insurance | 3418 | 38.4 | 2946 | 39.1a | 325 | 39.0a | 147 | 27.2b | |
| Public Insurance | 4977 | 55.9 | 4196 | 55.7a | 431 | 51.7a | 350 | 64.8b | |
| Uninsured | 513 | 5.8 | 392 | 5.2a | 78 | 9.4b | 43 | 8.0b | |
| Cigarette smoking status | <.001 | ||||||||
| Never Smoker | 2415 | 27.1 | 2036 | 27.0a | 259 | 31.1b | 120 | 22.2c | |
| Current Smoker | 1923 | 21.6 | 1607 | 21.3a | 138 | 16.5b | 178 | 33.0c | |
| Former Smoker | 3154 | 35.4 | 2712 | 36.0a | 286 | 34.3a,b | 156 | 28.9b | |
| Unknown | 1416 | 15.9 | 1179 | 15.6a | 151 | 18.1a | 86 | 15.9a | |
| Medium income | <.001 | ||||||||
| ≥ 61606.1 | 2226 | 25.0 | 1963 | 26.1a | 205 | 24.6a | 58 | 10.7b | |
| 47905.1–61606 | 2225 | 25.0 | 2003 | 26.6a | 163 | 19.5b | 59 | 10.9c | |
| 37543–47905 | 2230 | 25.0 | 1937 | 25.7a | 172 | 20.6b | 121 | 22.4a,b | |
| ≤ 37542.9 | 2227 | 25.0 | 1631 | 21.6a | 294 | 35.3b | 302 | 55.9c | |
| Education (% with at least a bachelors) | <.001 | ||||||||
| ≥ 37.61 | 2213 | 24.8 | 1975 | 26.2a | 181 | 21.7b | 57 | 10.6c | |
| 24.71–37.6 | 2223 | 25.0 | 1933 | 25.7a | 216 | 25.9a | 74 | 13.7b | |
| 15.9–24.7 | 2256 | 25.3 | 1922 | 25.5a | 204 | 24.5a | 130 | 24.1a | |
| ≤ 15.89 | 2216 | 24.9 | 1704 | 22.6a | 233 | 27.9b | 279 | 51.7c | |
| SEER stage | <.001 | ||||||||
| Local | 1175 | 13.2 | 988 | 13.1a | 124 | 14.9a | 63 | 11.7a | |
| Regional | 6204 | 69.6 | 5292 | 70.2a | 583 | 69.9a | 329 | 60.9b | |
| Distant | 1529 | 17.2 | 1254 | 16.6a | 127 | 15.2a | 148 | 27.4b | |
| Geographic region | <.001 | ||||||||
| Urban | 6369 | 71.5 | 5321 | 71.0a | 689 | 82.6b | 329 | 60.9c | |
| Rural | 2539 | 28.5 | 2183 | 29.0a | 145 | 17.4b | 211 | 39.1c | |
P P-value from one-way ANOVA or chi-square test, followed by Bonferroni’s adjusted pairwise comparisons
a, b, c Values in the same row with different letters indicate statistically significant difference at P <.05
Black patients were more likely than white non-Hispanic patients to have public insurance (64.8% vs. 55.7%, p < 0.001), be uninsured (8.0% vs. 5.2%, p < 0.001), a current cigarette smoker (33.0% vs. 21.3%, p < 0.001), experience distant stage disease (27.4% vs. 16.6%, p < 0.001), and reside in rural regions (39.1% vs. 29.0%, p < 0.001). Although white non-Hispanic patients constitute 82% of those with distant stage disease, that is 2% lower than their representation in the entire population, whereas Black patients constitute 6.1% of the total population, but 9.7% of the distant stage population. When comparing the census tract median incomes and educational levels among Black patients and white non-Hispanic patients, Black patients were more likely to live in an area where the median income and educational level is less than the lowest quartile (55.9% vs. 21.6%, p < 0.001, 51.7% vs. 22.6%, p < 0.001). While Black patients’ sociodemographic characteristics differed greatly from those of white patients, white Hispanics and white non-Hispanics did not differ substantially in terms of demographics (Table 1). In addition, SEER stage was significantly affected by age, race, sex, marital status, insurance status, and smoking status when compared via chi-square analysis (Table 2). Notably, current smokers (28.3% vs. 20.3%, p < 0.001), Black patients (9.7% vs. 5.4%, p < 0.001), and those uninsured (7.9% vs 4.2%, p < 0.001) were more likely to present with a distant SEER stage than local SEER stage.
Table 2.
Demographics of OPC patients diagnosed from 2010–2017 by stage at diagnosis
| All | Local Stage | Regional Stage | Distant Stage | ||||||
|---|---|---|---|---|---|---|---|---|---|
| n | % | n | % | n | % | n | % | P | |
| No. of Subjects | 8908 | 1175 | 13.2 | 6204 | 69.6 | 1529 | 17.2 | ||
| Age at diagnosis | <.001 | ||||||||
| Mean (SD) | 62.7 (10.4) | 65 (11.2)a | 62.4 (10.2)b | 62.1 (10.3)b | |||||
| Median (P25, P75) | 62 (55, 69) | 65 (57,73) | 62 (55,69) | 61 (55,69) | |||||
| Race/Ethnicity | <.001 | ||||||||
| White Non-Hispanic | 7534 | 84.6 | 988 | 84.1a,b | 5292 | 85.3a | 1254 | 82.0b | |
| White Hispanic | 834 | 9.4 | 124 | 10.6a | 583 | 9.4a | 127 | 8.3a | |
| Black | 540 | 6.1 | 63 | 5.4a | 329 | 5.3a | 148 | 9.7b | |
| Sex | <.001 | ||||||||
| Male | 7334 | 82.3 | 868 | 73.9a | 5166 | 83.3b | 1300 | 85.0b | |
| Female | 1574 | 17.7 | 307 | 26.1a | 1038 | 16.7b | 229 | 15.0b | |
| Marital status | <.001 | ||||||||
| Married | 5234 | 58.8 | 701 | 59.7a | 3743 | 60.3a | 790 | 51.7b | |
| Single/Unmarried | 1914 | 21.5 | 249 | 21.2a | 1247 | 20.1a | 418 | 27.3b | |
| Separated/Divorced/Widowed | 1760 | 19.8 | 225 | 19.1a | 1214 | 19.6a | 321 | 21.0a | |
| Insurance status | <.001 | ||||||||
| Private Insurance | 3418 | 38.4 | 412 | 35.1a | 2500 | 40.3b | 506 | 33.1a | |
| Public Insurance | 4977 | 55.9 | 714 | 60.8a | 3361 | 54.2b | 902 | 59.0a | |
| Uninsured | 513 | 5.8 | 49 | 4.2a | 343 | 5.5a | 121 | 7.9b | |
| Cigarette (tobacco) smoking status | <.001 | ||||||||
| Never Smoker | 2415 | 27.1 | 291 | 24.8a | 1778 | 28.7b | 346 | 22.6a | |
| Current Smoker | 1923 | 21.6 | 239 | 20.3a | 1251 | 20.2a | 433 | 28.3b | |
| Former Smoker | 3154 | 35.4 | 441 | 37.5a | 2216 | 35.7a,b | 497 | 32.5b | |
| Unknown | 1416 | 15.9 | 204 | 17.4a | 959 | 15.5a | 253 | 16.5a | |
| Medium income | <.001 | ||||||||
| ≥ 61606.1 | 2226 | 25.0 | 284 | 24.2a | 1636 | 26.4a | 306 | 20.0b | |
| 47905.1–61606 | 2225 | 25.0 | 302 | 25.7a | 1553 | 25.0a | 370 | 24.2a | |
| 37543–47905 | 2230 | 25.0 | 299 | 25.4a | 1538 | 24.8a | 393 | 25.7a | |
| ≤ 37542.9 | 2227 | 25.0 | 290 | 24.7a | 1477 | 23.8a | 460 | 30.1b | |
| Education (% with at least a bachelors) | <.001 | ||||||||
| ≥ 37.61 | 2213 | 24.8 | 287 | 24.4a | 1613 | 26.0a | 313 | 20.5b | |
| 24.71–37.6 | 2223 | 25.0 | 301 | 25.6a | 1558 | 25.1a | 364 | 23.8a | |
| 15.9–24.7 | 2256 | 25.3 | 307 | 26.1a | 1544 | 24.9a | 405 | 26.5a | |
| ≤ 15.89 | 2216 | 24.9 | 280 | 23.8a | 1489 | 24.0a | 447 | 29.2b | |
| Geographic region | 0.087 | ||||||||
| Urban | 6369 | 71.5 | 854 | 72.7a | 4456 | 71.8b | 1059 | 69.3c | |
| Rural | 2539 | 28.5 | 321 | 27.3a | 1748 | 28.2b | 470 | 30.7c | |
P P-value from one-way ANOVA or chi-square test, followed by Bonferroni’s adjusted pairwise comparisons
a, b, c Values in the same row with different letters indicate statistically significant difference at P <.05
Univariable (UVA) and multivariable (MVA) multinomial logistic regression assessing predictors of distant and regional stages versus local disease stage are presented in Table 3. MVA revealed a decreased risk of distant stage OPC compared to local stage among older patients (OR = 0.974 per year increase in age [95% CI:0.965–0.982], p < 0.001) and females (OR = 0.46 [95% CI:0.38–0.56], p < 0.001) (Table 3). White Hispanics had decreased risk of distant stage OPC compared to local disease (OR = 0.76 [95% CI:0.58–0.99]. There was a greater risk of distant stage OPC compared to local stage among Black patients (OR = 1.55 [95% CI:1.12–2.13], p = 0.007), those without insurance (OR = 1.67 [95% CI:1.16–2.41], p = 0.006) or with public insurance (OR = 1.26 [95% CI:1.04–1.53], p = 0.017), and patients who were separated/divorced/widowed (OR = 1.36 [95% CI:1.11–1.68], p = 0.004) (Table 3). Patients residing in census tracts with lower educational attainment and median income levels had a slightly increased risk of distant stage OPC in UVA, but these factors were not significant on MVA. In addition, there was a decreased risk of regional stage OPC as compared to local stage per year increase in age (OR = 0.98 [95% CI:0.97–0.98], p < 0.001) and females (OR = 0.57 [95% CI:0.49–0.66], p < 0.001) (Table 3) while there was an increase in risk in regional stage OPC compared to local stage in patients who were separated/divorced/widowed (OR = 1.21[95%CI: 1.02–1.44]).
Table 3.
Univariable (UVA) and multivariable (MVA) multinomial logistic regression analysis for likelihood of regional stage and of distant stage versus local stage (reference group) at time of diagnosis (N = 8908)
| A. UVA Regional vs. Local | B. MVA Regional vs. Local | C. UVA Distant vs. Local | D. MVA Distant vs. Local | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| OR | 95% CI | P | OR | 95% CI | P | OR | 95% CI | P | OR | 95% CI | P | |
| Age, in years | 0.977 | 0.971–0.982 | <.001 | 0.975 | 0.968–0.982 | <.001 | 0.974 | 0.967–0.981 | <.001 | 0.974 | 0.965–0.982 | <.001 |
| Race/Ethnicity | ||||||||||||
| White Non-Hispanic | 1 | Ref | 1 | Ref | 1 | Ref | 1 | Ref | ||||
| White Hispanic | 0.878 | 0.715–1.078 | 0.213 | 0.836 | 0.678–1.031 | 0.094 | 0.807 | 0.622–1.048 | 0.107 | 0.758 | 0.581–0.990 | 0.042 |
| Black | 0.975 | 0.738–1.287 | 0.858 | 0.994 | 0.745–1.324 | 0.965 | 1.851 | 1.362–2.514 | <.001 | 1.546 | 1.124–2.128 | 0.007 |
| Sex | ||||||||||||
| Male | 1 | Ref | 1 | Ref | 1 | Ref | 1 | Ref | ||||
| Female | 0.568 | 0.491–0.658 | <.001 | 0.565 | 0.486–0.656 | <.001 | 0.498 | 0.411–0.603 | <.001 | 0.462 | 0.380–0.562 | <.001 |
| Marital status | ||||||||||||
| Married | 1 | Ref | 1 | Ref | 1 | Ref | 1 | Ref | ||||
| Single/Unmarried | 0.938 | 0.801–1.099 | 0.427 | 0.89 | 0.753–1.051 | 0.17 | 1.49 | 1.236–1.796 | <.001 | 1.172 | 0.960–1.431 | 0.118 |
| Separated/Divorced/Widowed | 1.01 | 0.858–1.190 | 0.9 | 1.211 | 1.019–1.438 | 0.03 | 1.266 | 1.038–1.544 | 0.02 | 1.361 | 1.105–1.677 | 0.004 |
| Insurance Status | ||||||||||||
| Private Insurance | 1 | Ref | 1 | Ref | 1 | Ref | 1 | Ref | ||||
| Public Insurance | 0.776 | 0.680–0.885 | <.001 | 1.033 | 0.883–1.209 | 0.684 | 1.029 | 0.874–1.211 | 0.734 | 1.264 | 1.043–1.531 | 0.017 |
| Uninsured | 1.154 | 0.840–1.584 | 0.377 | 1.204 | 0.870–1.666 | 0.263 | 2.011 | 1.408–2.872 | <.001 | 1.672 | 1.158–2.414 | 0.006 |
| Cigarette smoking status | ||||||||||||
| Never Smoker | 1 | Ref | 1 | Ref | 1 | Ref | 1 | Ref | ||||
| Current Smoker | 0.857 | 0.711–1.032 | 0.103 | 0.827 | 0.682–1.003 | 0.053 | 1.524 | 1.220–1.902 | <.001 | 1.089 | 0.826–1.437 | 0.545 |
| Former Smoker | 0.822 | 0.700–0.966 | 0.017 | 0.879 | 0.747–1.035 | 0.122 | 0.948 | 0.775–1.160 | 0.603 | 1.083 | 0.842–1.392 | 0.536 |
| Unknown | 0.769 | 0.633–0.935 | 0.009 | 0.789 | 0.647–0.962 | 0.019 | 1.043 | 0.819–1.328 | 0.732 | 1.209 | 0.889–1.644 | 0.227 |
| Medium Income | ||||||||||||
| ≥ 61606.1 | 1 | Ref | 1 | Ref | 1 | Ref | 1 | Ref | ||||
| 47905.1–61,606 | 0.74 | 0.748–1.065 | 0.207 | 0.946 | 0.775–1.156 | 0.588 | 1.137 | 0.911–1.419 | 0.256 | 1.083 | 0.842–1.392 | 0.536 |
| 37543–47,905 | 0.893 | 0.748–1.066 | 0.209 | 0.952 | 0.762–1.188 | 0.661 | 1.22 | 0.978–1.521 | 0.078 | 1.089 | 0.826–1.437 | 0.545 |
| ≤ 37542.9 | 0.884 | 0.740–1.056 | 0.175 | 0.954 | 0.743–1.224 | 0.709 | 1.472 | 1.183–1.831 | <.001 | 1.209 | 0.889–1.644 | 0.227 |
| Education (% with at least a bachelors) | ||||||||||||
| ≥ 37.61 | 1 | Ref | 1 | Ref | 1 | Ref | 1 | Ref | ||||
| 24.71–37.6 | 0.921 | 0.772–1.098 | 0.359 | 0.97 | 0.798–1.179 | 0.76 | 1.109 | 0.889–1.384 | 0.36 | 1.04 | 0.814–1.329 | 0.752 |
| 15.9–24.7 | 0.895 | 0.751–1.066 | 0.215 | 0.931 | 0.747–1.160 | 0.524 | 1.21 | 0.972–1.505 | 0.088 | 1.016 | 0.774–1.336 | 0.907 |
| ≤ 15.89 | 0.946 | 0.791–1.132 | 0.545 | 1.003 | 0.782–1.287 | 0.979 | 1.464 | 1.176–1.822 | <.001 | 1.088 | 0.802–1.475 | 0.588 |
| Geographic Region | ||||||||||||
| Urban | 1 | Ref | 1 | Ref | 1 | Ref | 1 | Ref | ||||
| Rural | 1.044 | 0.908–1.2 | 0.549 | 0.999 | 0.867–1.152 | 0.99 | 1.181 | 0.998–1.397 | 0.053 | 1.078 | 0.908–1.280 | 0.392 |
OR (95% CI) odds ratio and corresponding 95% confidence interval
P P value from Wald test, OR 1 (same risk in both groups). Bold indicates results statistically significant at p < 0.05
To better understand demographic trends over the years due to the increasing prevalence of HPV-positive disease, we analyzed whether there were significant trends in demographic variables and SEER stage (Supplemental Table 1). Overtime, OPC cancer affected more current and former smokers (p < 0.001), males (p = 0.002), and older patients (p < 0.001). Notably, after the Affordable Care Act (ACA) was fully implemented in 2014, there was an increase in privately insured patients from 35.5% to 40.7% (Supplemental Table 1). Likewise, the number of uninsured patients with OPC significantly decreased with time (p = 0.002). Shortly after the implementation of the ACA, the percentage of patients with distant stage diagnoses significantly decreased from 19.3% in 2012–2013 to 12.9% from 2016–2017 (p < 0.001).
Geographical mapping of OPC cumulative incidence and median household income by census tracts shows large OPC case incidence in the Southeastern Florida coastal region from the Florida Keys to West Palm Beach, which is served by a large university cancer center (Fig. 2A). Upon inspection of Miami-Dade County (Fig. 2B), there is no clear trend depicting higher cumulative incidence of OPC among lower median income census tracts. In contrast to a lack of relationship between OPC cumulative incidence and income, the percentage of OPC distant stage diagnosis and income was significant. In Miami-Dade County, there is a higher percentage of distant stage OPC diagnosis in census tracts with lower median incomes (Fig. 3B).
Fig. 2.
Oropharyngeal cancer cumulative incidence (2010–2019) and Median Household Income by Census Tract. Maps depict incidence and income in Florida (A) and Miami-Dade County (B). Greater county income displayed with darker green shade and larger cumulative incidence displayed with larger yellow circles
Fig. 3.
Oropharyngeal cancer percent distant stage diagnosis (2010–2019) and Median Household Income by Census Tract. Maps depict percent distant stage diagnosis and income in Central and North Florida (A) and Miami-Dade County (B). Greater county income displayed with darker green shade and larger cumulative incidence displayed with larger yellow circles
Discussion
The study results demonstrate that distant stage OPC at diagnosis is more common than local stage OPC among Floridian patients who are younger, Black, male, separated/divorced/widowed, have public insurance or are uninsured, and that regional stage OPC at diagnosis is more common than local stage among younger patients, separated/divorced/widowed patients, and males. The most significant factors contributing to distant stage OPC at diagnosis include lack of insurance and Black race, with odds ratios of 1.67 and 1.55 respectively. Therefore, sociodemographic disparities among Floridians seem to affect the odds of distant stage diagnosis when patients have increased risk of morbidity and mortality. While residing in a census tract with lower educational attainment and median income may increase individuals’ cancer risk, these factors did not significantly increase the risk of distant stage OPC in our multivariable analysis. Moreover, when we performed geospatial mapping, there is a higher percentage of distant stage OPC in census tracts with lower median incomes in Miami-Dade County. These at-risk regions may contain higher populations of subjects with characteristics that were significantly associated with distant presentation such as Black race and uninsured status.
Our results are consistent with prior studies that demonstrate increased distant stage OPC presentation among Black patients and those without insurance coverage [12–14]. For example, a 2014 Alabama study found greater OPC tumor size and decreased P16 expression among Black vs. white patients, despite similar rates of HPV-positivity. In Michigan, increased likelihood of Stage IV HPV-negative OPC was observed among Black patients compared to white patients (72.09% vs 48.84%) [19]. On a larger scale, a 2021 SEER study found Black race to be associated with unresectable disease when adjusted for demographics, HPV, and insurance status (OR = 1.34 [95%CI1.10–1.63]) [20]. In addition, National Cancer Database studies have found increased risks of advanced OPC and tumor size among uninsured and Medicaid OPC patients vs privately insured patients [21]. Nevertheless, the protective role of private insurance on staging has not been established in all settings, as a Pennsylvania study found no significance between insurance status and advanced stage [21]. In general, compared to our findings, prior studies have shown relatively consistent results, but there remain regional variations. In the state of Florida, a survey study of over 300 Black residents revealed that the greatest barriers to OPC screening are lack of resources (finances, insurance, time, transportation), lack of desire to know the results, and lack of provider screening recommendations [22]. Increased transportation access, provider screening recommendations, and health insurance access could decrease the rate of distant stage OPC among Black patients and thus increase survival. Furthermore, Black patients in our analysis were more likely than white non-Hispanic patients to live in rural Florida regions, further solidifying the need for enhanced transportation access.
Notably, younger patients were more likely to present with regional and distant stage OPC at diagnosis, compared to their older counterparts. The increased prevalence of regional stage OPC among younger patients may be explained by HPV-positive cancer, which commonly presents as regional stage at diagnosis. Our yearly analysis showed that regional disease increased overtime, consistent with increasing numbers of HPV-positive disease. However, the more common presentation of distant stage OPC among younger patients is likely caused by other factors. It is possible that younger patients were diagnosed later in the disease course as they are less likely to undergo screening due to non-traditional risk factors such number of sexual partners, oral sex behaviors, history of cervical dysplasia, and HIV status [23–26].
Substantial research has investigated the relationship between age and head and neck cancer stage, with conflicting results. A retrospective study of about 2,000 head and neck cancer patients demonstrated that patients younger than 45 were more likely to present with distant metastases upon diagnosis, consistent with our findings [27]. Furthermore, additional studies have revealed that younger oral and oropharyngeal cancer patients are more likely than older patients to present with nodal disease, experience locoregional failure, and have reduced overall survival [28–30]. However, other studies have demonstrated that increased age is associated with more advanced tumor stage at diagnosis [31, 32]. Soudry et al. postulated that younger oral cancer patients may consist of two distinct cohorts: one that experiences mortality within 2 years and another that experiences an indolent disease course [33]. Pathologic studies revealed an increased susceptibility to chromosomal and microsatellite instability in younger head and neck cancer patients, despite decreased alcohol and tobacco use, likely contributing to the cohort presenting with more aggressive disease [34, 35]. While somatic mutations of mismatch repair genes are common in hereditary forms of cancer, and increase microsatellite instability, they are uncommon in head and neck cancer. One mechanistic theory is that hypermethylation of the mismatch repair gene promoter sequence, caused by environmental stressors, may lead to increased microsatellite instability and poor survival among younger head and neck cancer patients [36]. Future studies should continue to investigate how tumor biology such as microsatellite instability, risk factors, and survival may differ among younger and older head and neck cancer patients.
Independently of all other factors, patients who were separated/widowed/divorced had an increased risk of distant stage OPC presentation. Even though there are few studies regarding patients’ relationship status and OPC, past research indicates an increased odds ratio of distant stage breast cancer and melanoma among those who are unmarried [37]. Marriage status has been postulated to contribute to earlier stage cancer diagnosis due to better financial circumstances, contribution of health knowledge, and practical assistance support [38]. Interestingly, smoking status did not increase the risk of distant disease in MVA, underscoring the importance of age, race, marital status, insurance, and sex in local verses distant presentation of this disease.
While previous studies indicate that rural residence increases distant stage presentation of OPC [15], this was not upheld by our analysis, as rural vs. urban MVA did not reach statistical significance. Additionally, there were more patients with distant stage diagnosis in census tracts with lower median income, reinforcing how sociodemographic disparities exist within counties. Therefore, geographically mapping the percent of distant stage OPC cases by census tract can help to identify communities in the greatest need of screening and prevention efforts.
Florida is one of 10 states that declined to expand Medicaid up to 138 percent of the federal poverty level and is thus an ideal state to investigate health disparities [39]. Our temporal analysis revealed that the percentage of patients with distant stage diagnoses significantly decreased after the full implementation of the ACA in 2014, when there was a significant increase in the number of patients with private insurance and decrease in patients with no insurance. Other studies have demonstrated that Medicaid expansion led to fewer uninsured head and neck cancer patients [40], as well as a lower proportion of head and neck cancer patients with advanced stage disease [41]. Given our findings and past research, it is reasonable to conclude that Medicaid expansion in Florida would similarly benefit the early detection of oropharyngeal cancer. To further reduce the percentage of distant stage diagnoses in high-risk census tracts, nearby cancer centers should utilize a mobile unit to administer free or reduced cost head and neck exams to continue to address gaps in healthcare access. Additionally, healthcare workers should educate patients in these regions about concerning symptoms that may indicate early signs of head and neck cancer.
The primary limitation of this study is the lack of data on HPV status, which hindered the stratification of HPV-positive and HPV-negative OPC cases. Nonetheless, changing HPV epidemiology is an essential factor for interpreting our findings. Over time, HPV-positive OPC has continued to increase, especially in higher-income countries [42]. Although Black patients historically exhibited a higher likelihood of HPV-negative disease, which could explain some of our findings, more recent data show rising prevalence of HPV-positive disease across all racial and ethnic groups [43]. Nonetheless, the incidence of HPV-positive OPC remains highest among young, White, non-Hispanic men [44, 45]. Recent studies further demonstrate that HPV-positive OPC now accounts for the majority of cases even among Black and Hispanic individuals [46]. Importantly, the age distribution of HPV-positive OPC is also shifting, with increasing prevalence among older cohorts, likely reflecting the lack of HPV vaccination among older generations [45]. At the same time, it is important to note that patients who are non-White, female, and non-privately insured are less likely to undergo pathologic HPV testing, contributing to persistent research and clinical disparities [47].
As previously stated, we found that regional disease increased over time likely due to the increasing prevalence of HPV-related disease. However, over the years there was an increased number of patients who were older and current or former smokers, consistent with an HPV-negative demographic. Similarly, if the results were confounded by HPV subtype, we would expect that HPV-positive distant metastases would be more common among non-Hispanic white patients rather than Black patients, as shown by prior research [48]. In contrast, our results show increased risk of distant stage disease among Black adults, suggesting that both socioeconomic barriers and persistence of HPV-negative biology remain important drivers of disparity [49]. At the same time, younger age increases the risk of distant stage disease in our study, which is consistent with an HPV-positive demographic. Therefore, these varied demographics are unlikely to be explained solely by HPV status. Future studies with linked HPV testing are critical to disentangle the contributions of changing epidemiology versus structural inequities in explaining racial differences in OPC outcomes. Furthermore, our dataset spans the years 2010–2017, preceding the implementation of the American Joint Committee on Cancer's (AJCC) updated staging guidelines effective from January 2018 that consider HPV positivity as a favorable prognostic indicator for OPC outcomes [50].
Database studies have inherent limitations including underreporting, overreporting, and missing data. Our study included a limited percentage of Black (6.1%) and white Hispanic (9.4%) OPC patients compared to the state population, as well as a large percentage of missing SEER stage and tobacco usage. Even though Black patients are disproportionately affected by cancer diagnoses [51], they are underreported in SEER stage databases [52]. Similarly, Black/uninsured patients are less likely to receive care at Commission on Cancer-accredited high-volume hospitals, the only centers to report data to the National Cancer Database [53]. Research demonstrates that Black and uninsured oropharyngeal cancer patients are significantly less likely to have pathologic HPV testing results reported in the National Cancer Database, as this test requires additional resources to perform and update the database with those results [54]. Another major limitation was the absence of information about patients’ co-morbidities present at the time of diagnosis, as this may have affected disease progression. Since our study utilized a statewide database, our results cannot be extrapolated to all geographic regions in the United States. Lastly, our analysis may have included an under-reporting of patients with OPC in rural areas due to patients’ limited access to comprehensive cancer centers.
Conclusions
Distant stage OPC at diagnosis is more common than local stage OPC among Floridian patients who are younger, Black, male, separated/divorced/widowed, have public insurance or are uninsured. OPC screening efforts prove difficult as patients who present with distant stage disease experience many independent sociodemographic risk factors such as race, sex, insurance status, and relationship status. Geographical mapping analysis is a critical tool that can help direct OPC screening initiatives to communities with a heightened percentage of distant stage disease occurrences. The pertinent sociodemographic risk factors and incidence mapping could offer valuable guidance to clinicians and communities in their efforts to screen for and detect OPC within Florida and throughout the United States.
Supplementary Information
Acknowledgements
Not applicable.
Abbreviations
- CI
Confidence interval
- FCDS
Florida cancer data system
- HPV
Human papillomavirus
- MVA
Multivariable analysis
- OPC
Oropharyngeal cancer
- OR
Odds ratio
- P
p-Value
- UVA
Univariable analysis
Authors’ contributions
Sophia Peifer- analysis, manuscript writing, presentation, Holly LoTurco- analysis and manuscript writing, Uche Ezeh- analysis, research conduction, Garrett Forman- analysis and manuscript writing, Abdurrahman Al-Awady – analysis and manuscript writing, Ming Lee, M.D., PhD- graphical mapping and analysis, Tonya Aaron, M.S.—manuscript review and editing, Jason Leibowitz M.D.—manuscript review and editing, Zoukaa Sargi M.D., MPH—manuscript review and editing, Erin Kobetz, PhD, MPH- manuscript review and editing, Isildinha Reis, PhD – statistical analysis, project design, Elizabeth Franzmann, M.D.- project design and research conduction. Please consider Dr. Reis and Dr. Franzmann as co-senior authors.
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Data availability
All de-identified patient data is accessible from the Florida Cancer Data System (https://fcds.med.miami.edu/). All census tract data about income level is freely accessible online via the American Community Survey (https://www.census.gov/data/developers/data-sets/acs-5year.html).
Declarations
Ethics approval and consent to participate
Ethical Approval for review and analysis of database was exempt from review, approval, or oversight by the University of Miami Institutional Review Board (IRB) considering the data from the Florida Cancer Data System (FCDS) contained de-identified information and did not involve interactions with living human subjects, all of which do not meet the institution’s definition of human subject research.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Isildinha M. Reis and Elizabeth Franzmann are co-senior authors on this manuscript.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Psyrri A, Prezas L, Burtness B. Oropharyngeal cancer. Clin Adv Hematol Oncol: Published online; 2008. [PubMed] [Google Scholar]
- 2.Oropharynx. Published online 2020. https://gco.iarc.fr/today. Accessed 10 Apr 2023.
- 3.Marur S, D’Souza G, Westra WH, Forastiere AA. HPV-associated head and neck cancer: a virus-related cancer epidemic. Lancet Oncol. 2010;11(8):781–9. 10.1016/S1470-2045(10)70017-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Liederbach E, Kyrillos A, Wang CH, Liu JC, Sturgis EM, Bhayani MK. The national landscape of human papillomavirus-associated oropharynx squamous cell carcinoma. Int J Cancer. 2017;140(3):504–12. 10.1002/IJC.30442. [DOI] [PubMed] [Google Scholar]
- 5.Liao CI, Francoeur AA, Kapp DS, Caesar MAP, Huh WK, Chan JK. Trends in human papillomavirus-associated cancers, demographic characteristics, and vaccinations in the US, 2001–2017. JAMA Netw Open. 2022;5(3):E222530. 10.1001/JAMANETWORKOPEN.2022.2530. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.McGorray SP, Guo Y, Logan H. Trends in incidence of oral and pharyngeal carcinoma in Florida: 1981–2008. J Public Health Dent. 2012;72(1):68–74. 10.1111/J.1752-7325.2011.00285.X. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Hashibe M, Brennan P, Chuang SC, et al. Interaction between tobacco and alcohol use and the risk of head and neck cancer: pooled analysis in the International Head and Neck Cancer Epidemiology Consortium. Cancer Epidemiol Biomarkers Prev. 2009;18(2):541–50. 10.1158/1055-9965.EPI-08-0347. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Anantharaman D, Marron M, Lagiou P, et al. Population attributable risk of tobacco and alcohol for upper aerodigestive tract cancer. Oral Oncol. 2011;47(8):725–31. 10.1016/J.ORALONCOLOGY.2011.05.004. [DOI] [PubMed] [Google Scholar]
- 9.Chaturvedi AK, Engels EA, Pfeiffer RM, et al. Human papillomavirus and rising oropharyngeal cancer incidence in the United States. J Clin Oncol. 2011;29(32):4294–301. 10.1200/JCO.2011.36.4596. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Thompson-Harvey A, Yetukuri M, Hansen AR, et al. Rising incidence of late-stage head and neck cancer in the United States. Cancer. 2020;126(5):1090–101. 10.1002/CNCR.32583. [DOI] [PubMed] [Google Scholar]
- 11.Weatherspoon DJ, Chattopadhyay A, Boroumand S, Garcia I. Oral cavity and oropharyngeal cancer incidence trends and disparities in the United States: 2000–2010. Cancer Epidemiol. 2015;39(4):497–504. 10.1016/J.CANEP.2015.04.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Megwalu UC, Ma Y. Racial disparities in oropharyngeal cancer survival. Oral Oncol. 2017;65:33–7. 10.1016/J.ORALONCOLOGY.2016.12.015. [DOI] [PubMed] [Google Scholar]
- 13.Freedman RL, Sibley H, Williams AM, Chang SS. Race, not socioeconomic disparities, correlates with survival in human papillomavirus-negative oropharyngeal cancer: a retrospective study. Am J Otolaryngol. 2021. 10.1016/J.AMJOTO.2020.102816. [DOI] [PubMed] [Google Scholar]
- 14.Chen AY, Schrag NM, Halpern MT, Ward EM. The impact of health insurance status on stage at diagnosis of oropharyngeal cancer. Cancer. 2007;110(2):395–402. 10.1002/CNCR.22788. [DOI] [PubMed] [Google Scholar]
- 15.Lawrence LA, Heuermann ML, Javadi P, Sharma A. Socioeconomic status and rurality among patients with head and neck cancer. Otolaryngol Head Neck Surg. 2022;166(6):1028–37. 10.1177/01945998211019278. [DOI] [PubMed] [Google Scholar]
- 16.Chaturvedi AK, Engels EA, Pfeiffer RM, et al. Human papillomavirus and rising oropharyngeal cancer incidence in the United States. J Clin Oncol. 2011;29(32):4294. 10.1200/JCO.2011.36.4596. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Stage at Diagnosis | Data Visualizations Tool Technical Notes | CDC. https://www.cdc.gov/cancer/uscs/technical_notes/stat_methods/stage-at-diagnosis.htm#print. Accessed 19 Aug 2023.
- 18.Summary Staging | SEER Training. https://training.seer.cancer.gov/staging/systems/summary/. Accessed 16 Sept 2023.
- 19.Freedman RL, Sibley H, Williams AM, Chang SS. Race, not socioeconomic disparities, correlates with survival in human papillomavirus-negative oropharyngeal cancer: a retrospective study. Am J Otolaryngol. 2021;42(1):102816. 10.1016/J.AMJOTO.2020.102816. [DOI] [PubMed] [Google Scholar]
- 20.Shukla N, Ma Y, Megwalu UC. The role of insurance status as a mediator of racial disparities in oropharyngeal cancer outcomes. Head Neck. 2021;43(10):3116–24. 10.1002/HED.26807. [DOI] [PubMed] [Google Scholar]
- 21.Zhao J, Han X, Nogueira L, et al. Health insurance status and cancer stage at diagnosis and survival in the United States. CA Cancer J Clin. 2022;72(6):542–60. 10.3322/CAAC.21732. [DOI] [PubMed] [Google Scholar]
- 22.Shepperd JA, Howell JL, Logan H. A survey of barriers to screening for oral cancer among rural Black Americans. Psychooncology. 2014;23(3):276. 10.1002/PON.3415. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Drake VE, Fakhry C, Windon MJ, et al. Timing, number, and type of sexual partners associated with risk of oropharyngeal cancer. Cancer. 2021;127(7):1029–38. 10.1002/CNCR.33346. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Chancellor JA, Ioannides SJ, Elwood JM. Oral and oropharyngeal cancer and the role of sexual behaviour: a systematic review. Community Dent Oral Epidemiol. 2017;45(1):20–34. 10.1111/CDOE.12255. [DOI] [PubMed] [Google Scholar]
- 25.Gillison ML. Oropharyngeal cancer: a potential consequence of concomitant HPV and HIV infection. Curr Opin Oncol. 2009;21(5):439–44. 10.1097/CCO.0B013E32832F3E1B. [DOI] [PubMed] [Google Scholar]
- 26.Ebisch RMF, Rutten DWE, IntHout J, et al. Long-lasting increased risk of human papillomavirus-related carcinomas and premalignancies after cervical intraepithelial neoplasia grade 3: a population-based cohort study. J Clin Oncol. 2017;35(22):2542–50. 10.1200/JCO.2016.71.4543. [DOI] [PubMed] [Google Scholar]
- 27.Garavello W, Ciardo A, Spreafico R, Gaini RM. Risk factors for distant metastases in head and neck squamous cell carcinoma. Arch Otolaryngol Head Neck Surg. 2006;132(7):762–6. 10.1001/ARCHOTOL.132.7.762. [DOI] [PubMed] [Google Scholar]
- 28.Sarkaria JN, Harari PM. Oral tongue cancer in young adults less than 40 years of age: rationale for aggressive therapy. Head Neck. 1994;16(2):107–11. 10.1002/HED.2880160202. [DOI] [PubMed] [Google Scholar]
- 29.Cariati P, Cabello-Serrano A, Perez-De Perceval-Tara M, Monsalve-Iglesia F, Martínez-Lara I. Oral and oropharyngeal squamous cell carcinoma in young adults: A retrospective study in Granada University Hospital. Med Oral Patol Oral Cir Bucal. 2017;22(6):e679. 10.4317/MEDORAL.21755. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Sturgis EM, Moore BA, Glisson BS, Kies MS, Shin DM, Byers RM. Neoadjuvant chemotherapy for squamous cell carcinoma of the oral tongue in young adults: a case series. Head Neck. 2005;27(9):748–56. 10.1002/HED.20240. [DOI] [PubMed] [Google Scholar]
- 31.Megwalu UC, Ma Y. Racial disparities in oropharyngeal cancer stage at diagnosis. Anticancer Res. 2017;37(2):835–40. 10.21873/ANTICANRES.11386. [DOI] [PubMed] [Google Scholar]
- 32.Funk GF, Karnell LH, Robinson RA, Zhen WK, Trask DK, Hoffman HT. Presentation, treatment, and outcome of oral cavity cancer: a National cancer data base report. Head Neck. 2002;24(2):165–80. 10.1002/HED.10004. [DOI] [PubMed] [Google Scholar]
- 33.Soudry E, Preis M, Hod R, et al. Squamous cell carcinoma of the oral tongue in patients younger than 30 years: clinicopathologic features and outcome. Clin Otolaryngol. 2010;35(4):307–12. 10.1111/J.1749-4486.2010.02164.X. [DOI] [PubMed] [Google Scholar]
- 34.Majchrzak E, Szybiak B, Wegner A, et al. Oral cavity and oropharyngeal squamous cell carcinoma in young adults: a review of the literature. Radiol Oncol. 2014;48(1):1. 10.2478/RAON-2013-0057. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Wang Y, Irish J, MacMillan C, et al. High frequency of microsatellite instability in young patients with head-and-neck squamous-cell carcinoma: lack of involvement of the mismatch repair genes hMLH1 and hMSH2. Int J Cancer. 2001;93(3):353–60. 10.1002/IJC.1337. [DOI] [PubMed] [Google Scholar]
- 36.Zuo C, Zhang H, Spencer HJ, et al. Increased microsatellite instability and epigenetic inactivation of the hMLH1 gene in head and neck squamous cell carcinoma. Otolaryngol Head Neck Surg. 2009;141(4):484–90. 10.1016/J.OTOHNS.2009.07.007. [DOI] [PubMed] [Google Scholar]
- 37.Buja A, Lago L, Lago S, Vinelli A, Zanardo C, Baldo V. Marital status and stage of cancer at diagnosis: a systematic review. Eur J Cancer Care (Engl). 2018;27(1):e12755. 10.1111/ECC.12755. [DOI] [PubMed] [Google Scholar]
- 38.Lillard LA, Waite LJ. ’Til death do us part: marital disruption and mortality. Am J Sociol. 1995;100(5):1131–56. 10.1086/230634. [Google Scholar]
- 39.Florida advocates want the state to be the next to expand Medicaid : NPR. https://www.npr.org/2024/03/22/1240124290/medicaid-florida-health-care-ballot-voters-expansion-obamacare. Accessed 27 Nov 2024.
- 40.Cannon RB, Shepherd HM, McCrary H, et al. Association of the Patient Protection and Affordable Care Act with insurance coverage for head and neck cancer in the SEER database. JAMA Otolaryngol Head Neck Surg. 2018;144(11):1052–7. 10.1001/JAMAOTO.2018.1792. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Patel KB, Shabani S, Padhya T, et al. The impact of the Affordable Care Act on insurance coverage and stage among head and neck squamous cell carcinoma patients. J Health Care Poor Underserved. 2022;33(3):1322–36. 10.1353/HPU.2022.0115. [DOI] [PubMed] [Google Scholar]
- 42.Roman BR, Aragones A. Epidemiology and incidence of HPV-related cancers of the head and neck. J Surg Oncol. 2021;124(6):920. 10.1002/JSO.26687. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Faraji F, Rettig EM, Tsai HL, et al. The prevalence of human papillomavirus in oropharyngeal cancer is increasing regardless of sex or race, and the influence of sex and race on survival is modified by human papillomavirus tumor status. Cancer. 2019;125(5):761–9. 10.1002/CNCR.31841. [DOI] [PubMed] [Google Scholar]
- 44.Tsegaye AT, Shing JZ, Vo JB, Kreimer AR, Shiels MS. Racial and ethnic differences in HPV-related cancer incidence in the United States, 2001–2020. JNCI J Natl Cancer Inst. 2025;117(8):1655–63. 10.1093/JNCI/DJAF107. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Tota JE, Best AF, Zumsteg ZS, Gillison ML, Rosenberg PS, Chaturvedi AK. Evolution of the oropharynx cancer epidemic in the United States: moderation of increasing incidence in younger individuals and shift in the burden to older individuals. J Clin Oncol. 2019;37(18):1538–46. 10.1200/JCO.19.00370. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Scott-Wittenborn N, D’Souza G, Tewari S, et al. Prevalence of human papillomavirus in head and neck cancers at tertiary care centers in the United States over time. Cancer. 2022;128(9):1767–74. 10.1002/CNCR.34124. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Carlson KM, Abdul-Rahman NH, Deek RA, et al. Trends in human papillomavirus testing among patients with oropharyngeal cancer. JAMA Netw Open. 2025;8(7):e2523917–e2523917. 10.1001/JAMANETWORKOPEN.2025.23917. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Villalona S, Stroup AM, Villalona S, Ferrante JM. Racial/ethnic disparities in HPV-related oropharyngeal cancer outcomes among males in the United States: a national cohort study. Ann Cancer Epidemiol. 2022;6:4–4. 10.21037/ACE-22-1. [Google Scholar]
- 49.Settle K, Posner MR, Schumaker LM, et al. Racial survival disparity in head and neck cancer results from low prevalence of human papillomavirus infection in black oropharyngeal cancer patients. Cancer Prev Res (Phila). 2009;2(9):776–81. 10.1158/1940-6207.CAPR-09-0149. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Machczyński P, Majchrzak E, Niewinski P, Marchlewska J, Golusiński W. A review of the 8th edition of the AJCC staging system for oropharyngeal cancer according to HPV status. Eur Arch Otorhinolaryngol. 2020;277(9):2407. 10.1007/S00405-020-05979-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Giaquinto AN, Miller KD, Tossas KY, Winn RA, Jemal A, Siegel RL. Cancer statistics for African American/Black people 2022. CA Cancer J Clin. 2022;72(3):202–29. 10.3322/CAAC.21718. [DOI] [PubMed] [Google Scholar]
- 52.Howlader N, Ries LA, Stinchcomb DG, Edwards BK. The impact of underreported Veterans Affairs data on national cancer statistics: analysis using population-based SEER registries. J Natl Cancer Inst. 2009;101(7):533–7. 10.1093/JNCI/DJN517. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Wasif N, Etzioni D, Habermann EB, et al. Racial and socioeconomic differences in the use of high-volume commission on Cancer-accredited hospitals for cancer surgery in the United States. Ann Surg Oncol. 2018;25(5):1116–25. 10.1245/S10434-018-6374-0. [DOI] [PubMed] [Google Scholar]
- 54.Mazul AL, Colditz GA, Zevallos JP. Factors associated with HPV testing in oropharyngeal cancer in the National Cancer Data Base from 2013 to 2015. Oral Oncol. 2020. 10.1016/J.ORALONCOLOGY.2020.104609. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
All de-identified patient data is accessible from the Florida Cancer Data System (https://fcds.med.miami.edu/). All census tract data about income level is freely accessible online via the American Community Survey (https://www.census.gov/data/developers/data-sets/acs-5year.html).