SEARCH

SEARCH BY CITATION

Keywords:

  • Commission on Cancer;
  • disease stage;
  • National Cancer Database;
  • oropharyngeal cancer;
  • uninsured;
  • health disparities;
  • access to care

Abstract

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES

BACKGROUND.

Although patients who have early-stage oropharyngeal cancer can be treated with little impairment of function, the treatment of advanced disease can result in decreased quality of life and mortality. Patients without insurance and with other barriers to access to care may delay seeking medical attention for early symptoms, resulting in more advanced disease at presentation. In this study, the authors examined whether patients who had no insurance or who were covered by Medicaid insurance were more likely to present with advanced oropharyngeal cancer.

METHODS.

In this retrospective cohort study from the National Cancer Database from 1996 to 2003, patients with known insurance status who were diagnosed with invasive oropharyngeal cancer at Commission on Cancer facilities (n = 40,487) were included. Adjusted and unadjusted logistic regression models were used to analyze the likelihood of presenting with more advanced stage disease.

RESULTS.

After controlling for other sociodemographic characteristics, patients with advanced oropharyngeal cancer at diagnosis were more likely to be uninsured (odds ratio [OR], 1.37; 95% confidence interval [95% CI], 1.21–1.25) or covered by Medicaid (OR, 1.31; 95% CI, 1.19–1.46) compared with patients who had private insurance. Similarly, patients were most likely to present with the largest tumors (T4 disease) if they were uninsured (OR, 2.82; 95% CI, 2.46–3.23) or covered by Medicaid (OR, 2.95; 95% CI, 2.63–3.31). They also were more likely to present with the greatest degree of lymph node involvement (N3) if they were uninsured (OR, 2.06; 95% CI, 1.76–2.40) or covered by Medicaid (OR, 1.66; 95% CI, 1.45–1.90).

CONCLUSIONS.

Individuals who lacked insurance or had Medicaid coverage were at the greatest risk for presenting with advanced oropharyngeal cancer. In the current study, the results for the Medicaid group may have been influenced by the postdiagnostic enrollment of uninsured patients. Insurance coverage appeared to be a highly modifiable predictor of cancer stage. The findings indicated that it is important to consider the impact of insurance coverage on disease stage at diagnosis and associated morbidity, mortality, and quality of life. Cancer 2007. © 2007 American Cancer Society.

Oropharyngeal cancer involves the soft palate, tonsil, base of tongue, and vallecula and is diagnosed in nearly 9000 men and women in the United States annually.1 The majority of these cancers originate in the base of tongue and tonsils, and >90% are squamous cell carcinomas.2 For many years, surgery followed by radiotherapy or radiotherapy alone was considered the standard treatment for advanced oropharyngeal cancer. Unfortunately, patients with advanced disease treated with surgical resection often suffer from impairment of swallowing and speech, leading to decreased quality of life in many aspects, including nutrition, social functioning, and personal hygiene.3

Localized oropharyngeal cancer can be treated equally well with either radiation or surgery and has a favorable 5-year relative survival rate of 75%.4 Five-year relative survival rates among patients with advanced-stage oropharyngeal cancer (those with regional extension of tumor and/or lymph node involvement) are much lower than the rates for patients with early-stage disease, ranging from 48% to 50%.4

Because disease stage at diagnosis is a key factor that influences prognosis and treatment, it is important to consider the factors associated with late diagnoses. In oropharyngeal cancer, hoarseness, dysphagia, otalgia, and odynophagia are all common symptoms that can lead to the detection of early-stage disease. It is plausible that individuals without health insurance or with other barriers to health care access would be less likely to seek medical attention for these symptoms.

Lack of dental insurance coverage also may affect access to care. Because oropharyngeal cancer signs can be seen visibly in the mouth during routine dental examination, lack of access to dental examinations can lead to delayed diagnosis. Seventy percent of individuals with dental insurance seek a dentist's care, whereas only 50% of individuals without dental insurance seek dental care.5 Furthermore, the populations at highest risk for oropharyngeal cancer eg, men, aged >40 years, lower educational attainment, and lower socioeconomic status, are far less likely to visit a dentist. Moreover, individuals without health insurance are less likely to have a regular source of medical or dental care.6

To our knowledge, no prior study has investigated the relation between stage at diagnosis of oropharyngeal cancer and health insurance status. Information on health insurance status is not compiled or collected routinely by population-based cancer registries. The National Cancer Database (NCDB) provides a unique opportunity to study the relation between insurance status and disease stage at diagnosis, because information on insurance status has been collected by the NCDB for all patients since 1996. The objective of the current study was to examine the relation between the patient's insurance status at the time of diagnosis and American Joint Commission on Cancer (AJCC) overall stage,7 tumor (T) stage, and lymph node (N) stage at presentation among patients who were diagnosed with oropharyngeal cancer from 1996 to 2003 reported to the NCDB.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES

The NCDB is a national, hospital-based cancer registry that is sponsored jointly by the American College of Surgeons and the American Cancer Society. Prior to 1997, submissions of cancer patient records to the NCDB were voluntary and were open to all cancer facilities in the United States. Beginning in 1997, data collection was mandated as a requirement of the Commission on Cancer (CoC)-approved programs. Since 1999, approximately 75% of newly diagnosed cancers in the United States have been captured in the database.8

Patients who had invasive squamous cell carcinoma of the oropharynx diagnosed from 1996 to 2003 were extracted from the NCDB using the appropriate International Classification of Diseases for Oncology, 3rd edition (ICD-O-3) site and histology codes. Data were abstracted using coding guidelines documented in the Registry Operations and Data Standards (ROADS)9 manual for the diagnosis years from 1996 to 2002; the Facility Oncology Registry Data Standards (FORDS) manual10 for the diagnosis year 2003; the fourth, fifth, and sixth editions of the AJCC Manual for Staging of Cancer7; and the second and third editions of the World Health Organization ICD-O. For patients who were diagnosed prior to 2001, reported ICD-O-2 tumor morphology codes were recoded to the ICD-O-3 codes.11 The site codes selected were C01.9 (base of tongue, not otherwise specified [NOS]), C0.24 (lingual tonsil), C0.51 through C0.59 (palate), C09.0 through C09.9 (tonsil), C10.0 through C10.9 (oropharynx), and C14.0 through C14.3 (pharynx). The histology codes captured included 8045, 8051, 8052, 8070 through 8078, 8083, 8084, 8090 through 8094, 8097, 8123, 8147, 8560, and 8570, for squamous cell and/or basal squamous cell cancer.

Among the patients who had the correct site and histology codes (N = 62,389), only patients who were treated at the reporting institution (3149 patients excluded), who had stages I through IV disease at presentation (5107 patients excluded), and who were aged ≥18 years (16 patients excluded) were included. In addition, patients with unknown insurance status (n = 5637; 10.4%) and any other unknown independent variable (n = 7993) were excluded, which left 40,487 patients for the study population. Institutional Review Board approval was not required for this study, because the database did not include individual identifiers or other protected health information.

The primary independent variable was the FORDS data element for primary payer/insurance at diagnosis. FORDS codes were grouped into the following categories: Medicaid, Medicare (which included both Medicare alone and Medicare with supplement), uninsured (which included FORDS codes for not insured-NOS, not insured-charity write-off, and not insured-self-pay), other government-funded plans (Veterans Affairs, Indian Health Service, Public Health Service, welfare, state funded-NOS, and federally funded-NOS), and private insurance plans (health maintenance organization, preferred provider organization, managed care-NOS, private insurance, the 3-option Civilian Health and Medical Program of the Uniformed Services (TRICARE/CHAMPUS), military, and insured-NOS). The plans in the private insurance category were grouped together, because these plans represent either privately purchased insurance (purchased by the individual, a family member, and/or employer) or insurance provided by the military that functions in a manner similar to that of private insurance (TRICARE/CHAMPUS). Generally, all patients aged ≥65 years are eligible for Medicare enrollment regardless of comorbidity, although some individuals in this age group have private insurance as their primary payer. Individuals aged <65 years who are either disabled or have renal failure or amyotrophic lateral sclerosis also may be covered by Medicare.12 Because individuals with Medicare insurance aged <65 years may differ substantially from individuals aged ≥65 years, the Medicare category was dichotomized by age (ages 18–64 years vs aged ≥65 years).

Other independent variables included sex (men and women), race (white, black, Hispanic, and other, which included Asian American/Pacific Islander and Native American), age (categorized as covariates into quartiles of 18–52 years, 53–60 years, 61–69 years, and ≥70 years), United States Census region of residence (West, Midwest, Northeast, and South),13 and area-based variables, which captured education (proportion in patient's zip code of residence without a high school degree based on national quartiles of the 2000 United States Census as ≥29%, 20–28.9%, 14–19.9%, and <14%) and household income (median value in patient's zip code of residence based on national quartiles of the 2000 United States Census as <$30,000, $30,000–34,999, $35,000–45,999, and ≥$46,000).

The type of treatment facility (categorized by the CoC as community hospital, community cancer facility, and teaching/research facility) also was included as an independent variable, because prior analyses have demonstrated variation in disease stage at presentation by facility type. Community hospitals treat ≥300 patients with cancer each year and have a full range of services for cancer care, although patients require a referral for portions of their treatment. Community cancer centers are facilities that offer the same range of services as the community hospitals but treat ≥750 patients with cancer each year and conduct weekly cancer conferences. Teaching/research facilities differ from community cancer facilities in that the teaching/research facilities have residency programs and ongoing cancer research. Twenty-nine of the 39 National Cancer Institute (NCI)-designated Comprehensive Cancer Programs participate in the CoC approvals program and were included among the teaching/research facilities in this study.

Three separate analyses were performed. The first analysis used a dichotomized, dependent variable that described stage at diagnosis and was categorized as either early (stages I and II) or advanced (stages III and IV).7 In the second analysis, the dependent variable was the reported T stage at diagnosis and was categorized as T1, T2, T3, or T4.7 In the third analysis, the dependent variable was the reported N stage at diagnosis and was categorized as N0, N1, N2, or N3.7

Analyses were performed with SAS software (version 9.1; SAS Statistical Institute, Cary, NC). Statistical testing was conducted by using the SAS procedure for logistic regression (PROC LOGISTIC). Initial (unadjusted) logistic regression models analyzed the likelihood of presenting with advanced-stage versus early-stage disease and of presenting at more advanced T stage and N stage based separately on each independent variable (ie, 1 at a time). Additional regression analyses controlled for all independent variables that were identified as statistically significant in the univariate models. We used a generalized logistic model (the SAS glogit link option for PROC LOGISTIC) to compare patients with T2, T3, or T4 stage at diagnosis separately using T1 as the referent group and to compare patients with N1, N2, or N3 neck disease at diagnosis separately using N0 as the referent group. All 40,487 patients were eligible for the analysis of T stage, and 39,283 patients were included in the analysis of N stage (after eliminating 1204 patients who had missing N stage information). We assessed whether the adjusted models (ie, models that included all significant independent variables) had a significantly better fit than the unadjusted models (ie, models that included only insurance status). Goodness of fit was tested by computing the change in deviance (ΔD) from the adjusted models to the unadjusted models and assessing the significance using the likelihood-ratio statistic. Statistical significance was defined as α < .05.

RESULTS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES

In total, 40,487 patients with oropharyngeal cancer were eligible for analyses. Table 1 compares the characteristics of patients who presented with early-stage versus advanced-stage disease. There were 9825 patients with early-stage disease (20%) and 38,628 patients (80%) with advanced-stage disease. The distribution of T stage included 10,170 patients (22%) with T1 disease, 16,068 patients (33%) with T2 disease, 9953 patients (20%) with T3 disease, and 11,942 patients (25%) with T4 disease. The distribution of N stage included 12,155 patients (30%) with N0 disease, 7805 patients (19%) with N1 disease, 16,375 patients (40%) with N2 disease, 2948 patients (25%) with N3 disease, and 1204 patients (3%) with unknown N stage disease. More advanced-stage disease (47%) was treated at teaching/research facilities, whereas community facilities treated more early-stage disease. More men were likely to present with advanced-stage disease compared with women.

Table 1. Characteristics of Patients Diagnosed With Early-stage Versus Advanced-stage Oropharyngeal Cancer: National Cancer Database, 1996–2003 (n = 40,487)
CharacteristicNo. of patients (%)P% With advanced-stage disease
Early stage, n=8234* No. (%)Advanced stage, n=32,253 No. (%)
  • *

    Referent group.

  • Wald chi-square statistic (results from univariate logistic regression analyses).

  • Veterans Affairs, Indian Health Service, Public Health Service.

  • §

    Health maintenance organization, preferred provider organization, managed care, the 3-option Civilian Health and Medical Program of the Uniformed Services military, insured-not otherwise specified.

  • US 2000 Census data for zip code of residence.

Primary payer/insurance
 Uninsured322 (3.9)2080 (6.5)<.000186.6
 Medicaid547 (6.6)3350 (10.4)<.000186
 Medicare
  Ages 18–64 y424 (5.2)1663 (5.2).113279.7
  Aged ≥65 y2989 (36.3)8307 (25.7)<.000173.5
 Other government-funded plans484 (5.9)1952 (6.1)<.242480.1
 Private insurance plans*§3468 (42.1)14,901 (46.2)*81.1
Sex
 Women*2523 (30.6)6939 (21.5)*73.3
 Men5711 (69.4)25,314 (78.5)<.000181.6
Race
 White*6841 (83.1)25,748 (79.8)*79
 Black1031 (12.5)4897 (15.2)<.000182.6
 Hispanic235 (2.9)1055 (3.3).016381.8
 Other127 (1.54)553 (1.7).142381.3
Age, y
 18–52*1615 (19.6)9227 (28.6)*85.1
 53–601763 (21.4)8352 (25.9)<.000182.6
 61–692198 (26.7)7481 (23.2)<.000177.3
 ≥702658 (32.3)7193 (22.3)<.000173
Facility type
 Community hospital1287 (15.6)4298 (13.3)<.000177
 Community cancer center3435 (41.7)12,027 (37.3)<.000177.8
 Teaching/research facility*3512 (42.7)15,928 (49.4)*81.9
Census region of residence
 West1764 (21.4)6989 (21.7).675779.8
 Midwest1786 (21.7)6966 (21.6).991379.6
 Northeast*1639 (19.9)6390 (19.8)*79.6
 South3045 (37)11,908 (36.9).928879.6
Proportion without high school degree, %
 ≥291620 (19.7)7152 (22.2)<.000181.5
 20–28.92089 (25.4)8390 (26).004980.1
 14–19.91935 (23.5)7231 (22.4).540178.9
 <14*2590 (31.5)9480 (29.4)*78.5
Median household income
 <$30,0001413 (17.2)6059 (18.8).001381.1
 $30,000–34,9991690 (20.5)6572 (20.4).572079.5
 $35,000–45,9992349 (28.5)9013 (27.9).845279.3
 ≥$46,000*2782 (33.8)10,609 (32.9)*79.2

Table 2 presents corresponding logistic regression results for analyses relating insurance type to the likelihood of presenting with advanced disease controlling for patient sex, age, race, treatment facility type, zip code-based education and income categories, and United States Census region. The likelihood-ratio test statistic for the adjusted model was statistically significant (ΔD = 466.2; P < .05). Controlling for covariates, patients who were uninsured (odds ratio [OR], 1.37; 95% confidence interval [95% CI], 1.21–1.55) or who had Medicaid insurance (OR, 1.31; 95% CI, 1.19–1.46) were significantly more likely to present with advanced-stage disease than patients who had private insurance. Patients who were men, aged ≥52 years, or resided in zip codes with low proportions of high school graduates also were at increased risk of presenting with advanced-stage cancer. Patients with advanced disease were more likely to be treated at a teaching/research facility.

Table 2. Adjusted Odds Ratios for Patients With Advanced-stage Versus Early-stage Oropharyngeal Cancer: National Cancer Database, 1996–2003 (n = 40,487)
VariableOR (95% CI)P
  • OR indicates odds ratio; 95% CI, 95% confidence interval.

  • *

    Veterans Affairs, Indian Health Service, Public Health Service.

  • Health maintenance organization, preferred provider organization, managed care, Civilian Health and Medical Program of the Uniformed Services, military, insured-not otherwise specified.

  • US 2000 Census data for zip code of residence.

Primary payer/insurance
 Uninsured1.37 (1.21–1.55)<.0001
 Medicaid1.31 (1.19–1.46)<.0001
 Medicare
  Ages 18–64 y0.90 (0.80–1.01).0791
  Aged ≥65 y0.95 (0.88–1.03).2032
 Other government plans*0.86 (0.77–0.96).0084
 Private insurance plans1.00 
Sex
 Men1.49 (1.41–1.58)<.0001
 Women1.00 
Age, y
 18–521.00 
 53–600.85 (0.79–0.91)<.0001
 61–690.66 (0.61–0.71)<.0001
 ≥700.57 (0.52–0.63)<.0001
Race
 Black1.05 (0.97–1.14).2276
 Hispanic1.06 (0.92–1.23).4226
 Other1.08 (0.89–1.32).4365
 White1.00 
Facility type
 Community hospital0.78 (0.73–0.84)<.0001
 Community cancer center0.84 (0.79–0.89)<.0001
 Teaching/research facility1.00 
Proportion without high school degree, %
 ≥291.16 (1.05–1.28).0028
 20–28.91.10 (1.02–1.20).0164
 14–19.91.05 (0.97–1.13).2449
 <141.00 
Median household income
 <$30,0000.95 (0.86–1.05).2793
 $30,000–34,9990.94 (0.87–1.03).1842
 $35,000–45,9990.97 (0.90–1.04).3781
 ≥$46,0001.00 

Tables 3 and 4 present the logistic regression models that predict M stage and T stage, respectively, by insurance type while controlling for sex, age, race, treatment facility type, zip code-level education and income, and United States Census region. The likelihood-ratio test statistic for the adjusted models, again, were statistically significant (Dgr;D = 1046; P < .05 for T stage; ΔD = 1126.6; P < .05 for N stage). Similar to the results shown in Tables 3 and 4, uninsured patients and those with Medicaid insurance were significantly more likely than patients who had private insurance to present with more advanced T stages; this association was strongest for the most advanced stage (T4; OR, 2.82 and 2.95, respectively). In addition, the patients who had Medicare aged <65 years, Medicare aged ≥65 years, and other government plans also were at increased risk of developing T4 disease than patients who had private insurance (OR, 1.73, 1.33, and 1.57, respectively). Patients who were uninsured or who had Medicaid also had a higher risk for presenting with N3 disease compared with N0 disease (OR, 2.06 and 1.66, respectively). In addition, patients who had other government health insurance plans also had an increased risk of developing N3 disease (OR, 1.25).

Table 3. Odds Ratios for Lymph Node Stage Adjusted for Sex, Age, Race, Facility Type, Census Region of Residence, Proportion Without High School Degree, and Median Household Income for Patients With Oropharyngeal Cancer: National Cancer Database, 1996–2003*
Primary payer/InsuranceN0 vs N1, N2, and N3 oropharyngeal cancer (n=39,283)
N1N2N3
OR (95% CI)POR (95% CI)POR (95% CI)P
  • N0-N3 indicates lymph node stage, OR, odds ratio; 95% CI, 95% confidence interval.

  • *

    Education and income levels were based on 2000 US Census data for zip code of residence.

  • Veterans Affairs, Indian Health Service, Public Health Service, welfare, state funded-not otherwise specified (NOS), federally funded-NOS.

  • Health maintenance organization, preferred provider organization, managed care-NOS, Civilian Health and Medical Program of the Uniformed Services, military, insured-NOS.

Uninsured0.89 (0.78–1.02).09481.01 (0.90–1.12).93662.06 (1.76–2.40)<.0001
Medicaid0.92 (0.82–1.03).14410.96 (0.87–1.05).33511.66 (1.45–1.90)<.0001
Medicare
 Ages 18–64 y0.76 (0.66–0.87)<.00010.76 (0.68–0.85)<.00010.93 (0.77–1.13).4707
 Aged ≥65 y0.90 (0.82–0.98).02160.86 (0.79–0.93).00011.05 (0.91–1.22).5076
Other government plans0.69 (0.60–0.80)<.00010.90 (0.81–1.00).05281.25 (1.05–1.48).0108
Private insurance plans1.00 1.00 1.00 
Table 4. Odds Ratios for Tumor Stage Adjusted for Sex, Age, Race, Facility Type, Census Region of Residence, Proportion Without High School Degree, and Median Household Income for Patients With Oropharyngeal Cancer: National Cancer Database, 1996–2003*
Primary payer/InsuranceT1 vs T2, T3, and T4 oropharyngeal cancer (n = 40,487)
T2T3T4
OR (95% CI)POR (95% CI)POR (95% CI)P
  • T1-T4 indicates tumor stage; OR, odds ratio; 95% CI, 95% confidence interval.

  • *

    Education and income levels were based on 2000 US Census data for zip code of residence.

  • Veterans Affairs, Indian Health Service, Public Health Service, welfare, state funded-not otherwise specified (NOS), federally funded-NOS.

  • Health maintenance organization, preferred provider organization, managed care-NOS, Civilian Health and Medical Program of the Uniformed Services, military, insured-NOS.

Uninsured1.29 (1.12–1.49).00031.96 (1.70–2.27)<.00012.82 (2.46–3.23)<.0001
Medicaid1.26 (1.12–1.41).00012.00 (1.77–2.26)<.00012.95 (2.63–3.31)<.0001
Medicare
 Ages 18–64 y1.17 (1.02–1.33).02651.47 (1.27–1.70)<.00011.73 (1.50–1.99)<.0001
 Aged ≥65 y1.07 (0.98–1.18).13821.07 (0.96–1.19).21801.33 (1.20–1.47)<.0001
Other government plans1.00 (0.88–1.14).95391.10 (0.95–1.27).19101.57 (1.38–1.80)<.0001
Private insurance plans1.00 1.00 1.00 

Because most younger patients do not have Medicare insurance and most older patients are covered by Medicare, we also explored the interactions between age (categorized as ages <65 years and ≥65 years) and each of the nonage-related, independent variables (data not shown). Very few of these interactions were statistically significant. Overall, we conclude that age did not modify the association appreciably between insurance status and disease stage at presentation.

DISCUSSION

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES

The principal finding of the current study was that, for patients who were diagnosed with oropharyngeal cancer from 1996 to 2003 at American College of Surgeons CoC-approved hospitals, health insurance status was an important predictor of advanced stage, larger primary tumor size, and greater lymph node involvement. Compared with patients who had private insurance, patients who were uninsured or who had Medicaid insurance had greater likelihoods of being diagnosed with advanced overall stage, T stage, and N stage compared with patients who had private insurance. Other factors that were associated with more advanced disease at diagnosis were sex (men were at higher risk), age (younger patients were at higher risk), treatment facility type (patients who were treated at teaching/research facilities were at higher risk), and residence in a zip codes with a higher proportion of individuals without a high school degree.

In multivariate analysis, the type of health insurance remained the strongest predictor of stage at diagnosis and tumor size, with the OR for larger primary tumors (T stage) at diagnosis increasing in a stepwise fashion from T1 to T4 for all insurance types relative to private insurance. Similarly, the type of health insurance remained the strongest predictor of N stage at diagnosis, with the OR for larger neck disease (N stage) at diagnosis increasing in a stepwise fashion from N0 to N3 for all insurance types relative to private insurance. The median household income in the zip code of residence was not predictive of overall stage, T stage, or N stage at diagnosis.

Health insurance type may be related to the likelihood of having a regular health care provider and seeking care for symptomatic disease, ie, the delay between first seeking care and a definitive diagnosis. Lack of health insurance has been associated strongly with barriers to access for health care in other studies. For example, according to the National Health Interview Survey, in 2002/2003, 46.7% of uninsured adults ages 18 years to 64 years had no usual source of health care compared with 9.3% of adults who had health insurance.6 In 2003, 38.1% of adults aged <65 years with no health insurance reported no visits to physicians' offices, emergency departments, or home visits in the past 12 months compared with 12.8% of insured adults.6 Individuals without health insurance are also less likely to report the use of cancer preventive services, such as mammography, Papanicolaou tests, and colorectal cancer testing.6, 4 In a prior study that linked Florida cancer registry records with hospital discharge records to obtain insurance status, it was observed that patients without insurance coverage or with Medicaid insurance were more likely to be diagnosed with late-stage cancer at a several sites (colon-rectum, melanoma, breast, and prostate) than patients with commercial indemnity insurance.15 One recent study reported that, regardless of income, uninsured individuals used recommended health care services less often than individuals who were insured.16

Little has been published about factors that affect stage at diagnosis among patients with oropharyngeal cancer. Hoarseness, dysphagia, otalgia, and voice changes commonly appear in early-stage disease; however, despite these early symptoms, most patients present with advanced-stage disease.4 The relation between a lack of insurance or being underinsured and advanced-stage disease also may reflect a delay in seeking medical care by uninsured or underinsured, symptomatic patients because of the lack of available, qualified providers or other barriers. In such instances, by the time an uninsured or Medicaid recipient receives medical attention, the disease is more likely to be advanced.

There were several limitations to this study. First, some patients who were categorized as qualified for Medicaid may have presented with no insurance coverage; the application for Medicaid coverage may have commenced upon diagnosis, and coverage may have been extended retroactively to the date of diagnosis. Previous studies suggest that patients who enroll in Medicaid at the time of cancer diagnosis may have more advanced-stage disease than patients who enroll in Medicaid prior to diagnosis17; although, after those investigators controlled for disease stage at diagnosis, there were no significant differences in survival between early-stage and late-stage Medicaid enrollees.18 We may have undercounted the actual number of patients who were uninsured at the time of diagnosis, because information on the date of Medicaid enrollment is not available in the NCDB, and we were unable to adjust for uninsured patients who became eligible for Medicaid after diagnosis. Similarly, no information was available on the consistency of the type of insurance coverage prior to cancer diagnosis. Many individuals in the United States may experience periods of being uninsured, and these periods generally are longer among individuals with lower incomes.19 The impact of a lack of consistent insurance coverage on cancer stage at diagnosis is unknown.

We also did not have information on the distance traveled to diagnostic or treatment facility, which may relate to access to care. We did not have individual-level information on income, education, or other socioeconomic status measures and relied on zip code-based estimates. In addition, we lacked information on the time delay between the presentation of symptoms and the diagnosis of oropharyngeal cancer. This information may have helped to define where lapses or potential gaps in access to care occurred when individuals were not insured or were underinsured.

In conclusion, the current analyses provide the first assessment to our knowledge of the strong association between medical insurance status and disease stage of oropharyngeal cancer at diagnosis among a large, generalizable cohort. Being uninsured or having Medicaid health insurance coverage predicts a greater likelihood of advanced disease at diagnosis and, thus, leads to a greater need for invasive treatments (which increase morbidity) and decreased life expectancy. Increasing access to health care, including dental care, among uninsured or Medicaid-insured individuals likely would allow for the more frequent detection of early-stage oropharyngeal cancer.

REFERENCES

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES