SEARCH

SEARCH BY CITATION

Keywords:

  • Hodgkin lymphoma;
  • adolescents and young adults;
  • advanced stage;
  • health insurance;
  • socioeconomic status

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. Note Added in Proof
  9. REFERENCES

BACKGROUND:

Hodgkin lymphoma (HL) is one of the most common types of cancer among adolescents and young adults (AYAs) in the United States. Unfortunately, a greater percentage of AYAs are presenting with an advanced stage of disease at the time of diagnosis compared with their younger counterparts.

METHODS:

The objective of the current study was to examine the association between possible barriers and characteristics (including gender, race, birthplace, marital status, socioeconomic status [SES], and insurance status) that may increase the risk of advanced stage HL at the time of diagnosis in a large cohort of AYA patients with HL from the California Cancer Registry (7343 incident cases of HL diagnosed from 1988-2006, between ages 15 years-40 years).

RESULTS:

AYAs with advanced stage HL were more likely to be male, of Hispanic or black race/ethnicity, foreign born, single, of lower SES, and uninsured or to have only public health insurance (P < .05). Multivariate logistic regression analysis demonstrated that there was a significant increase in the odds of having advanced HL in males (odds ratio [OR], 1.57; 95% confidence interval [95% CI], 1.42-1.74 [P < .0001]), those with the lowest SES (OR, 1.47; 95% CI, 1.23-1.75 [P = .0003]), those without health insurance (OR, 1.76; 95% CI, 1.34-2.31 [P < .0001]), and those with public health insurance (OR, 1.45; 95% CI, 1.23-1.71 [P < .0001]).

CONCLUSIONS:

A strong association was found between male gender, lower SES, and lack of health insurance and advanced stage HL at the time of diagnosis in AYAs (See editorial on pages 000–000, this issue.) Cancer 2012. © 2012 American Cancer Society.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. Note Added in Proof
  9. REFERENCES

Hodgkin lymphoma (HL) is one of the most common types of cancer diagnosed among adolescents and young adults (AYAs; defined by the National Cancer Institute [NCI] as individuals aged 15 years-39 years at the time of diagnosis) in the United States, comprising 12% of cancers among patients aged 15 years to 29 years.1 Unfortunately, a greater percentage of AYAs are presenting with an advanced stage of disease at the time of diagnosis compared with their younger counterparts.2 Over all ages, 17% of patients with HL present with advanced disease and the 5-year relative survival rate is 63%, compared with 90% in those with regional disease.3 Advanced HL at the time of diagnosis is considered to be a poor prognostic factor for many treatment protocols4; therefore, these patients receive aggressive treatment regimens, including chemotherapy and radiotherapy, that are often associated with increased morbidity and mortality.5 Consequently, it is of importance to find risk factors that are associated with having advanced HL at the time of diagnosis to identify intervention approaches to improve survival rates for HL among AYAs. The objective of the current study was to examine the association between possible barriers and characteristics (including gender, socioeconomic status [SES], and insurance status) that may increase the risk of presenting with advanced stage HL at the time of diagnosis in a large cohort of AYA patients (7343 cases) from the California Cancer Registry (CCR).

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. Note Added in Proof
  9. REFERENCES

Study Population

We performed a retrospective case-only analysis of all patients with HL diagnosed between the ages of 15 years and 40 years in California from 1988 through 2006 using the CCR database (7343 patients). The CCR is part of the NCI's Surveillance, Epidemiology, and End Results (SEER) program, with standardized data collection and quality control protocols in place since 1988.6-9 Both case reporting and follow-up completion rates are >95% for the entire state of California.10 After data are abstracted from medical and laboratory records by trained tumor registrars, tumor site and histology are coded according to the World Health Organization's criteria in the third edition of the International Classification of Diseases for Oncology (ICD-O).11 HL was defined by morphology codes 9650 through 9667 using the ICD-O. The recorded data included gender, race/ethnicity (white, black, Hispanic, and Asian), age at diagnosis, birthplace, marital status, SES, insurance status, and stage.

We used SEER-defined categories of disease stage: in situ; regional; regional with direct extension; regional with lymph nodes; regional with extension and lymph nodes; regional, not otherwise specified; remote; not abstracted; and unknown/not otherwise specified. In the current study, we divided the patient population into 2 groups. Patients categorized as having regional; regional with direct extension; regional with lymph nodes; regional with extension and lymph nodes; and regional, not otherwise specified were combined into 1 group called regional HL and patients with remote disease were placed in the second group, which was called advanced HL. There were 545 patients not included in the current analysis: 1 patient with in situ disease, 2 patients with stage not abstracted, and 542 patients with unknown stage.

The SES variable used in the CCR and in the current study is a single index created from statewide census data measures of education, income, and occupation. The variable was created from a principle component analysis of census block group-level data, including median educational attainment, median household income, percentage living below 200% of the federal poverty level, median house value, median rent, percentage employed, and percentage of the population with “blue collar” employment.12 Each patient was assigned an SES quintile based on the SES distribution of the study population.

Insurance status was grouped into the following categories: public insurance included Medicaid (US government program for low-income or medically needy individuals) and other government-assisted programs; private insurance included health maintenance organizations, preferred provider organizations, managed care not otherwise specified, and military care; uninsured included individuals without insurance or who were self-pay; and last, unknown insurance status was also included in the current analysis. Individuals who were classified as self-pay were grouped with uninsured persons because a separate analysis (Fig. 1) demonstrated that the majority of the patients who were self-pay were also in the lowest SES (70%).

thumbnail image

Figure 1. Socioeconomic status distribution of individuals with self-pay insurance status is shown.

Download figure to PowerPoint

Marital status was divided into 4 categories: single; married; unknown marital status; and divorced, separated, or widowed. Single individuals were considered different from those who were divorced, separated, and widowed because the second group was likely to be older than the first group.

Birthplace was divided into 3 categories: US born, foreign born, and unknown. Foreign born included individuals born outside the United States and its territories.

Statistical Analysis of Risk Factors Associated With Advanced HL

The relative incidence of advanced HL in different genders, age groups, and races/ethnicities was examined and the differences in the distribution of advanced HL among these groups were analyzed using the chi-square test. To determine variables that are associated with an increased risk of advanced HL, we used multivariate logistic regression to estimate the odds ratio (OR) and associated 95% confidence intervals (95% CIs). The model was adjusted for gender, race/ethnicity, age, birthplace, marital status, SES, and insurance status and the dependent variable was advanced stage HL at the time of diagnosis. A separate model was used to examine the influence of insurance status on stage of HL using data from 2001 through 2006 (the reporting of insurance status data was required by the CCR beginning in 2001). All statistical analyses were conducted using SAS software (version 9.2; SAS Institute Inc, Cary, NC).

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. Note Added in Proof
  9. REFERENCES

The summary characteristics of the current study sample are shown in Table 1. The study population was comprised of 7343 cases of HL, 53% of whom were male and 47% of whom were female, predominantly non-Hispanic whites (65%), with the highest percentage aged 25 years to 29 years. Overall, 64% had regional disease and 35% had advanced disease. AYAs with advanced stage HL were more likely to be males, of Hispanic and black races/ethnicities, foreign born, single, of lower SES, and uninsured or to have only public health insurance (P < .05). In addition, there was a trend demonstrating that as SES increases, the percentage of patients with advanced disease decreases. Among AYAs without insurance or who were self-pay, 65% were male and 35% were female (P = .0004). Among AYAs with private insurance, the percentage of advanced HL was found to be lower compared with those without health insurance. Before 2001, the data regarding insurance status in the CCR was not required and was consequently incomplete; therefore, the association between advanced HL and health insurance status was examined and was demonstrated to be significant for patients diagnosed between 2001 and 2006, in whom the percentage of individuals with unknown insurance status was only 5%.

Table 1. Baseline Characteristics of 7343 Patients With HL Who Were Diagnosed Between 1988 and 2006 in California
 No.%Regional (No.)%Distant (No.)%
  1. Abbreviation: HL, Hodgkin lymphoma.

No.7343 475264.7259135.3
Sex      
 Male390753.2232459.5158340.5
 Female343646.8242870.7100829.3
P<.0001      
Race      
 White480865.5319666.5161233.5
 Black5036.930961.419438.6
 Hispanic157321.494259.963140.1
 Asian3795.225467.012533.0
 Unknown801.15163.82936.3
P<.0001      
Age group, y      
 15-19110815.172865.738034.3
 20-24163122.2105264.557935.5
 25-29171223.3112965.958334.1
 30-34159221.7105266.154033.9
 35-39130017.779160.850939.2
P=.0218      
Birthplace      
 US born355048.3230264.8124835.2
 Foreign born84011.447856.936243.1
 Unknown295340.2197266.898133.2
P<.0001      
Marital status      
 Single417556.9263463.1154136.9
 Married262535.7176567.286032.8
 Divorced/separated/widowed3785.125166.412733.6
 Unknown1652.210261.86338.2
P=.0042      
Socioeconomic status      
 1st quintile (lowest)101013.856856.244243.8
 2nd quintile138018.886562.751537.3
 3rd quintile156721.3101164.555635.5
 4th quintile175823.9118467.357432.7
 5th quintile (highest)162822.2112469.050431.0
P<.0001      
Insurance status      
 No insurance2393.312050.211949.8
 Private/military insurance331945.2229369.1102630.9
 Public insurance80911.045856.635143.4
 Unknown297640.5188163.2109536.8
P<.0001      
Insurance status (1988-2006)      
 No insurance1195.25647.16352.9
 Private/military insurance167272.7115369.051931.0
 Public insurance37916.522258.615741.4
 Unknown1305.79069.24030.8
P<0.0001      

Chi-square analysis of advanced disease in AYAs indicated that among the patients aged 15 years to 24 years and 25 years to 34 years, there was a significant percentage of males with advanced disease compared with females (P < .0001) (Fig. 2). Among males aged 15 years to 24 years, there was a significant percentage (54%) of black patients with advanced HL (Fig. 3) (P = .02). Among the older age groups (those aged 25-34 years and 35-39 years), there was a significant percentage (46% and 53%, respectively) of Hispanic males with advanced HL (Fig. 3) (P = .02 and P = .02, respectively). Conversely, in females, there was a significant percentage of Hispanics among those aged 35 years to 39 years with advanced HL (Fig. 4).

thumbnail image

Figure 2. The percentage distribution of advanced Hodgkin lymphoma in males and females of different age groups is shown. * indicates P value was <.05 using chi-square analysis of incidence rates.

Download figure to PowerPoint

thumbnail image

Figure 3. The percentage distribution of advanced Hodgkin lymphoma in males of different race/ethnicity and age groups is shown. * indicates P value was <.05 using chi-square analysis of incidence rates.

Download figure to PowerPoint

thumbnail image

Figure 4. The percentage distribution of advanced Hodgkin lymphoma in females of different race/ethnicity and age groups is shown. * indicates P value was <.05 using chi-square analysis of incidence rates.

Download figure to PowerPoint

Multivariate logistic regression analysis as summarized in Table 2 demonstrated a significant impact of gender, age, birthplace, marital status, SES, and insurance status on the stage of HL at the time of diagnosis. A significant increase in the odds of advanced HL was noted in males (OR, 1.57; 95% CI, 1.42-1.74 [P < .0001]) and older age groups (OR, 1.34; 95% CI, 1.11-1.61 [P = .01]). The odds of having advanced HL was found to be significantly increased among AYAs who were single (OR, 1.21; 95% CI, 1.07-1.36 [P = .01]) and foreign born (OR, 1.24; 95% CI, 1.05-1.47 [P = .009]). In addition, the odds of having advanced HL significantly increased with lower SES (Table 2) (Fig. 5 Top). AYAs with the lowest SES were found to have the highest risk of having advanced HL at the time of diagnosis (OR, 1.47; 95% CI, 1.23-1.75 [P = .0003]) compared with those with higher SES. Finally, patients without health insurance were found to have an increased risk of having advanced HL at the time of diagnosis (OR, 1.76; 95% CI, 1.34- 2.31 [P < .0001]). In addition, those with public health insurance had an increased risk of having advanced HL (OR, 1.45; 95% CI, 1.23-1.71 [P < .0001]), but it was lower than that of patients without health insurance (Fig. 5 Bottom). Analysis of cases between 2001 and 2006 with only 5% having an unknown insurance status demonstrated strikingly similar results, with a significant increase in the odds of advanced HL in patients without health insurance (OR, 1.84; 95% CI, 1.24-2.73 [P = .008]) and in patients with only public health insurance (OR, 1.30; 95% CI, 1.01-1.66 [P = .008]) (Fig. 5 Bottom). On the multivariate logistic regression, after adjusting for insurance status and SES, black and Hispanic race/ethnicity, previously shown to be associated with advanced HL, was found to be no longer significant.

Table 2. Adjusted OR (With 95% CIs) of the Likelihood of Having Advanced HL at Diagnosis for AYAs in California, 1988 to 2006, Using Multivariate Regression Analysis
 OR95% CI
  1. Abbreviations: 95% CI, 95% confidence interval; AYAs, adolescents and young adults; HL, Hodgkin lymphoma; LCL, lower 95% confidence level; OR, odds ratio; P value, P value for trend was determined using chi-square analysis; UCL, upper 95% confidence level.

Sex  
 Male1.571.42–1.74
 Female1 
 P≤.0001 
Race  
 White1 
 Black1.060.87–1.3
 Hispanic1.100.96–1.26
 Asian0.960.76–1.21
 P=.64 
Age group, y  
 15-191 
 20-241.050.89–1.24
 25-291.060.89–1.25
 30-341.090.91–1.30
 35-391.341.11–1.61
 P=.01 
Birthplace  
 US born1 
 Foreign born1.241.05–1.47
 P=.009 
Marital status  
 Married1 
 Single1.211.07–1.36
 Divorced/separated/widowed0.970.77–1.23
 P=.01 
Socioeconomic status  
 1st quintile (lowest)1.471.22–1.75
 2nd quintile1.221.04–1.43
 3rd quintile1.201.03–1.39
 4th quintile1.060.91–1.22
 5th quintile (highest)1 
 P=.0003 
Insurance status  
 Private/military insurance1 
 Public insurance1.451.23–1.71
 No insurance1.761.34–2.31
 P≤.0001 
Insurance status (1998-2006)  
 Private/military insurance1 
 Public insurance1.301.01–1.66
 No insurance1.841.24–2.73
 P=.008 
thumbnail image

Figure 5. (Top) Adjusted odds ratio (OR) for advanced Hodgkin lymphoma (HL) among different quintiles of socioeconomic status (SES) for all HL patients diagnosed between 1988 and 2006 are shown using multivariate regression analysis. The model covariates included sex, race, age, birthplace, insurance status, and marital status. The fifth quintile was used as the reference group. Chi-square analysis indicated a P value for trend of .0003. (Bottom) Adjusted OR for advanced HL among different types of insurance status for all HL patients diagnosed between 1988 and 2006 and between 2001 and2006 are shown using multivariate regression analysis. The model covariates included sex, race, age, birthplace, SES, and marital status. Private insurance was used as the reference group. Chi-square analysis indicated a P value for trend < .0001 for the period 1988 through 2006 and a P value for trend of .008 for 2001 to 2006.

Download figure to PowerPoint

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. Note Added in Proof
  9. REFERENCES

The main finding of the current study was that AYAs who were male, of lower SES, and uninsured or only had public health insurance had a substantially increased risk of being diagnosed with advanced HL.

These findings are supported by previous studies that considered insurance status as a risk factor for being diagnosed with advanced HL. Halpern et al found that adult patients who were uninsured or had Medicaid were significantly more likely to present with advanced stage cancer than privately insured adult patients.13 The current study findings demonstrate evidence that insurance and cost-related barriers are critical in the screening practices and outcomes of cancer care in adults. Martin and Ulrich examined delays in cancer diagnosis specifically in underinsured AYAs and found that AYAs with cancer (including HL) are likely to have a delay in diagnosis because of inadequate health insurance and tend to present with a more advanced stage of disease.14 Because health insurance coverage data have shown that the persons aged 18 to 34 years comprise the highest percentage of the population without health insurance coverage,15 a solution is needed to improve the health insurance coverage of young people in the United States to decrease their risk of being diagnosed with advanced HL as well as other cancers that are common in AYAs.

In the current study, public health insurance was also associated with an increased risk of presenting with advanced HL. One possible explanation is that the majority of the patients who were identified as having public health insurance were actually uninsured at the time of diagnosis and eventually qualified for public health insurance after diagnosis. Another possible explanation is that public health insurance is as inadequate as not having insurance because of limited access to health care.16 A review of the impact of health insurance coverage on health noted that many adults with Medicaid coverage frequently fare no better, and sometimes fare worse, than uninsured patients in their health-related outcomes, including cancer.17 In addition, results of the National Health Interview Survey (NHIS) indicated that fewer physicians are accepting new patients with Medicaid and national surveys have demonstrated that a greater percentage of individuals who have Medicaid or are uninsured had a delay in medical care or did not receive medical care because of cost.15 Patients who are insured by government programs face significant barriers to obtaining general health care needs, especially access to specialists and diagnostic tests that are usually critical in making a diagnosis of cancer. Consequently, this may lead to delays in diagnosis and eventually an advanced stage of cancer being noted at the time of diagnosis.

In addition to insurance status, the results of the current study found that low SES is a significant risk factor for being diagnosed with advanced HL. Previous studies have found that SES was an independent predictor of stage of disease at diagnosis, with patients from the highest SES group more likely to present with local stage disease than those from the lowest SES group.18 In addition, strong evidence for socioeconomic differences in cancer survival and mortality has been revealed by many studies, including a comprehensive review by Kogevinas et al.19 Some studies have found either an increase in the survival rates of patients with HL with decreasing SES or no association between the survival of patients with HL and SES.20, 21 Other studies have found decreasing survival rates for patients with HL with decreasing SES.22-24 Some of the differences in these findings may be attributable to different health care systems, with European countries having universal health care and the United States having a government-supported health insurance for select groups of people. A study by Boyd et al found that the association between SES and cancer survival was stronger in the United States than in Ontario, Canada, which may reflect the success of the Canadian medical system in removing financial barriers to access to care.25 Variability in survival rates can also be attributed to different treatment regimens, depending on the treatment protocol.5

Aside from the association between insurance status and SES and being diagnosed with advanced disease, comorbidities and health behaviors may also influence outcomes. There is evidence that smoking among cancer patients varies with SES.26 Such differentials in high-risk behaviors may then lead to poorer health status and comorbidities. In addition, it has been postulated that better nutrition among the affluent may also influence a person's ability to withstand treatment and eventually influence survival.27 Although SES may be confounded by many other factors, it has been demonstrated by many studies to be a major risk factor in predicting the stage of cancer at the time of diagnosis and survival from the disease.

Last, we also found male gender to be a significant risk factor for being diagnosed with advanced HL. In previous studies, male gender was considered as one of the pretreatment factors associated with adverse outcomes.28-30 The ratio of national mortality to SEER incidence for HL indicated that there were more males than females dying of the disease between the ages of 15 years and 40 years than expected.1 Last, females are known to present with a more favorable history and a less advanced stage of disease.31 These findings could be secondary to the underuse of screening services, with men having sporadic sick visits and women having scheduled routine visits. Bertakis et al demonstrated that women had a significantly higher mean number of visits to their primary care clinic and diagnostic services than men.32 Low use of health services may eventually contribute to major disease morbidity and a lower life expectancy in men.33 In addition to health care practices, gender differences in immune function and genetic composition as well as differences in etiology and the pathogenesis of HL could also contribute to males having a worse prognosis compared with females.

In the current study, we also demonstrated that being single was associated with an increased risk of being diagnosed with advanced HL. Married individuals have been found to have significantly better survival in some studies,34-36 possibly because the increased social support leads to appropriate diagnosis and treatment being sought in a more timely fashion. In addition, we also found that being born in a foreign country was associated with an increased risk of advanced HL. This could be secondary to language barriers and differences in educational level and cultural beliefs as well as inherent differences in biological and genetic composition between different races and individuals of different ethnic backgrounds. In the current analysis, Hispanic and black patients were found to have more advanced disease compared with non-Hispanic white patients. A study by Hu et al found similar results, with black and Hispanic individuals more frequently presenting with advanced HL compared with white patients.37 Other studies have found nonwhite race to be a significant predictor of poor survival in patients with HL.38, 39 Despite the higher incidence of HL among non-Hispanic white patients, black and Hispanic race/ethnicity continues to be a significant predictor for being diagnosed with advanced disease and poor survival in patients with HL.

The current study is unique in that it focused on HL in the AYA population and included a large number of patients. In addition, we found that SES and insurance status were significant risk factors for predicting the stage of HL at the time of diagnosis in AYAs, which is consistent with large epidemiological studies performed in adults with multiple types of cancers.13 In addition, information regarding SES was available for all the patients and was based on education, income, and occupation, which is considered to be more reliable than using addresses and census tract data to measure SES.40 Finally, to the best of our knowledge, the current study is one of the few published to date that examined risk factors associated with an advanced stage of HL. The majority of studies concerning HL have examined risk factors associated with poor survival from HL and have found SES and insurance status to be significant.

The strengths of the current study include the large number of cases (7343 cases) with complete data available from the CCR, including stage of disease, SES, and insurance status; however, limitations include those challenges that are inherent in using a registry as a source of data. For example, 40% of patients diagnosed before 2001 had unknown insurance status because of incomplete reporting; therefore, we analyzed the data from 2001 through 2006, in which only 5% of patients had unknown insurance status. Similarly, a large number of patients had an unknown birthplace and therefore the data regarding the association between birthplace and stage of HL at the time of diagnosis must be interpreted with caution. In addition, the CCR does not include data such as time from the appearance of symptoms to diagnosis and the number of physician visits before diagnosis. These are important measures of delay in diagnosis that can be used to correlate with the stage of disease. Finally, the CCR does not include Ann Arbor staging data for HL, which is more specific and accurate for HL compared with the SEER categories of staging used in the current study. Despite the limitations of this study, its findings make a significant contribution to our knowledge of HL diagnosed in AYAs.

The results of the current study suggest that gender and indicators of adequate access to health care such as SES and insurance status predict the risk of advanced HL at the time of diagnosis among the AYA population. Although HL is a highly treatable type of cancer, survival rates among AYAs continue to decline; therefore, targeted efforts to expand access to health care for young males with lower SES and for those without adequate health insurance are needed to improve the stage of disease at the time of diagnosis and consequently improve survival rates in these groups. Efforts to increase health care use among AYA males can prevent delays in the diagnosis of HL and decrease the risk of advanced disease. With the Patient Protection and Affordable Care Act, children aged ≥ 26 years can be covered under their parents' insurance. Data from the NHIS indicate that since the policy took effect in September 2010, the percentage of adults aged 19 years to 25 years who were covered by a private health insurance plan increased significantly, with approximately 2.5 million more AYAs having insurance coverage compared with the number of AYAs who would have been insured without the law.41 By closing the gap in health care use among young males and improving health care access, we can decrease the risk of advanced stage HL in AYAs as well as other cancers in this age group.

FUNDING SUPPORT

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. Note Added in Proof
  9. REFERENCES

Supported by the Lon V. Smith Foundation grant LVS-39420. The collection of cancer incidence data used in this study under subcontract No. 050N-8707-S1527 with the Public Health Institute of the State of California was supported by the California Department of Health Services as part of the statewide cancer reporting program mandated by California Health and Safety Code Sections 103875 and 103885; the National Cancer Institute's Surveillance, Epidemiology, and End Results Program; and the Centers for Disease Control and Prevention National Program of Cancer Registries. The ideas and opinions expressed herein are those of the authors and endorsement by the State of California, Department of Health Services, the National Cancer Institute, the Centers for Disease Control and Prevention, and/or the Genetic Epidemiology Research Institute of the University of California at Irvine is not intended nor should be inferred.

Note Added in Proof

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. Note Added in Proof
  9. REFERENCES

CONFLICT OF INTEREST DISCLOSURES

The authors made no disclosures.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SUPPORT
  8. Note Added in Proof
  9. REFERENCES
  • 1
    O'Leary M, Sheaffer J, Keller F, Shu X, Cheson B. Lymphomas and reticuloendothelial neoplasms. In: Bleyer A, O'Leary M, Barr R, Ries L, eds. Cancer Epidemiology in Older Adolescents and Young Adults 15 to 29 Years of Age. Including SEER Incidence and Survival: 1975-2000. Bethesda, MD: National Cancer Institute; 2006: 25-38.
  • 2
    Punnett A, Tsang RW, Hodgson DC. Hodgkin lymphoma across the age spectrum: epidemiology, therapy, and late effects. Semin Radiat Oncol. 2010; 20: 30-44.
  • 3
    Ries LAG, Young JL, Keel GE, Eisner MP, Lin YD, Horner M-J, eds. Surveillance, Epidemiology and End Results (SEER) Survival Monograph: Cancer Survival Among Adults: US SEER Program, 1988-2001, Patient and Tumor Characteristics. NIH Pub. No. 07-6215. Bethesda, MD: SEER Program, National Cancer Institute; 2007: 227-234.
  • 4
    Hasenclever D, Diehl V. A prognostic score for advanced Hodgkin's disease. International Prognostic Factors Project on Advanced Hodgkin's Disease. N Engl J Med. 1998; 339: 1506-1514.
  • 5
    Hodgson DC, Hudson MM, Constine LS. Pediatric hodgkin lymphoma: maximizing efficacy and minimizing toxicity. Semin Radiat Oncol. 2007; 17: 230-242.
  • 6
    Cancer Surveillance Section.Cancer Reporting in California: Standards for Automated Reporting. California Cancer Reporting System Standards. Vol II. Sacramento, CA: California Department of Health Services, Cancer Surveillance Section; 1997.
  • 7
    Cancer Surveillance Section.Cancer Reporting in California: Data Standard for Regional Registries and California Cancer Registry. California Cancer Reporting System Standards. Vol III. Sacramento, CA: California Department of Health Services, Cancer Surveillance Section, 1997.
  • 8
    Cancer Surveillance Section. Abstract and Coding Procedures for Hospitals. California Cancer Reporting System Standards. Vol I. Sacramento, CA: California Department of Health Services, Cancer Surveillance Section, 1997.
  • 9
    Cancer Surveillance Section. Reporting Procedures for Physicians. California Cancer Reporting System Standards. Vol IV. Sacramento, CA: California Department of Health Services, Cancer Surveillance Section, 1997.
  • 10
    California Cancer Registry. How complete are California Cancer Registry Data? Sacramento, CA: California Cancer Registry; 2008.
  • 11
    Fritz A, Jack A, Parkin DM, et al. International Classification of Diseases for Oncology. 3rd ed. Geneva, Switzerland: World Health Organization; 2000.
  • 12
    Yost K, Perkins C, Cohen R, Morris C, Wright W. Socioeconomic status and breast cancer incidence in California for different race/ethnic groups. Cancer Causes Control. 2001; 12: 703-711.
  • 13
    Halpern M, Ward EM, Pavluck AL, Schrag NM, Bian J, Chen AY. Association of insurance status and ethnicity with cancer stage at diagnosis for 12 cancer sites: a retrospective analysis. Lancet Oncol. 2008; 9: 222-231.
  • 14
    Martin S, Ulrich C, Munsell M, Taylor S, Lange G, Bleyer A. Delays in cancer diagnosis in underinsured young adults and older adolescents. Oncologist. 2007; 12: 816-824.
  • 15
    Cohen RA, Martinez ME. Health Insurance Coverage: Early Release of Estimates From the National Health Interview Survey, 2006. Atlanta, GA: Centers for Disease Control and Prevention; 2007.
  • 16
    Ward E, Halpern M, Schrag N, et al. Association of insurance with cancer care utilization and outcomes. CA Cancer J Clin. 2008; 58: 9-31.
  • 17
    Committee on the Consequences of Uninsurance, Board on Health Care Services, Institute of Medicine. Care Without Coverage: Too Little, Too Late. Washington, DC: National Academy Press; 2002.
  • 18
    Schwartz KL, Crossley-May H, Vigneau FD, Brown K, Banerjee M. Race, socioeconomic status and stage at diagnosis for five common malignancies. Cancer Causes Control. 2003; 14: 761-766.
  • 19
    Kogevinas M, Porta M. Socioeconomic differences in cancer survival: a review of the evidence. IARC Sci Publ. 1997;( 138): 177-206.
  • 20
    Holzner B, Fischhofer M, Kemmler G, et al. Is higher income and educational status associated with poorer outcome in patients with Hodgkin's disease? Eur J Haematol. 2004; 73: 318-324.
  • 21
    Roswall N, Olsen A. Christensen J, Rugbjerg K, Mellemkjaer L. Social inequality and incidence of and survival from Hodgkin lymphoma, non-Hodgkin lymphoma and leukaemia in a population-based study in Denmark, 1994-2003. Eur J Cancer. 2008; 44: 2058-2073.
  • 22
    Keegan TH, Clarke CA, Chang ET, Shema SJ, Glaser SL. Disparities in survival after Hodgkin lymphoma: a population-based study. Cancer Causes Control. 2009; 20: 1881-1892.
  • 23
    Soares A, Biasoli I, Scheliga A, et al. Socioeconomic inequality and short-term outcome in Hodgkin's lymphoma. Int J Cancer. 2007; 120: 875-879.
  • 24
    Cella DF, Orav EJ, Kornblith AB. Socioeconomic status and cancer survival. J Clin Oncol. 1991; 9: 1500-1509.
  • 25
    Boyd C, Zhang-Salomons JY, Groome PA, Mackillop WJ. Associations between community income and cancer survival in Ontario, Canada, and the United States. J Clin Oncol. 1999; 17: 2244-2255.
  • 26
    Begum G, Dunn JA, Bryan RT, Bathers S, Wallace DM; West Midlands Urological Research Group. Socio-economic deprivation and survival in bladder cancer. BJU Int. 2004; 94: 539-543.
  • 27
    Auvinen A, Karjalainen S. Possible explanations for social class differences in cancer patient survival. IARC Sci Publ. 1997;( 138): 377-397.
  • 28
    Metzger ML, Castellino SM, Hudson MM, et al. Effect of race on the outcome of pediatric patients with Hodgkin's lymphoma. J Clin Oncol. 2008; 26: 1282-1288.
  • 29
    Ruhl U, Albrecht M, Dieckmann K, et al. Response-adapted radiotherapy in the treatment of pediatric Hodgkin's disease: an interim report at 5 years of the German GPOH-HD 95 trial. Int J Radiat Oncol Biol Phys. 2001; 51: 1209-1218.
  • 30
    Clarke CA, Glaser SL, Prehen AW. Age-specific survival after Hodgkin's disease in a population-based cohort (United States). Cancer Causes Control. 2001; 12: 803-812.
  • 31
    Mueller N, Grufferman S. The epidemiology of Hodgkin's disease. In: Mauch P, Armitage J, Diehl V, Hoppe R, Weiss L, eds. Hodgkin's Disease. Philadelphia: Lippincott Williams & Wilkins; 1999: 61-78.
  • 32
    Bertakis KD, Azari R, Helms LJ, Callahan EJ, Robbins JA. Gender differences in the utilization of health care services. J Fam Pract. 2000; 49: 147-152.
  • 33
    Pinkhasov RM, Wong J, Kashanian J. Are men shortchanged on health? Perspective on health care utilization and health risk behavior in men and women in the United States. Int J Clin Pract. 2010; 64: 475-487.
  • 34
    Harvei S, Kravdal O. The importance of marital and socioeconomic status in incidence and survival of prostate cancer. An analysis of complete Norwegian birth cohorts. Prev Med. 1997; 26( 5 pt 1): 623-632.
  • 35
    Meng L, Maskarinec G, Wilkens L. Ethnic differences and factors related to breast cancer survival in Hawaii. Int J Epidemiol. 1997; 26: 1151-1158.
  • 36
    Polednak AP. Survival of breast cancer patients in Connecticut in relation to socioeconomic and health care access indicators. J Urban Health. 2002; 79: 211-218.
  • 37
    Hu E, Hufford S, Lukes R, et al. Third-World Hodgkin's disease at Los Angeles County-University of Southern California Medical Center. J Clin Oncol. 1988; 6: 1285-1292.
  • 38
    Davis S, Dahlberg S, Myers MH, Chen A, Steinhorn SC. Hodgkin's disease in the United States: a comparison of patient characteristics and survival in the Centralized Cancer Patient Data System and the Surveillance, Epidemiology, and End Results Program. J Natl Cancer Inst. 1987; 78: 471-478.
  • 39
    Zaki A, Nataranjan N, Mettlin CJ. Early and late survival in Hodgkin's disease among whites and blacks living in the United States. Cancer. 1993; 72: 602-606.
  • 40
    Clarke CA, Glaser SL, Keegan TH, Stroup A. Neighborhood socioeconomic status and Hodgkin's lymphoma incidence in California. Cancer Epidemiol Biomarkers Prev. 2005; 14: 1441-1447.
  • 41
    New data: Affordable Care Act helps 2.5 million additional young adults get health insurance: expanded coverage from the health care law has continued to grow [news release]. Washington, DC: US Department of Health and Human Services; December 14, 2011. http://www.hhs.gov/news/press/2011pres/12/20111214d.html. Access date.