Cancer Causes & Control

, Volume 26, Issue 8, pp 1153–1162 | Cite as

US trends in survival disparities among adolescents and young adults with non-Hodgkin lymphoma

  • Erin E. Kent
  • Nancy Breen
  • Denise R. Lewis
  • Janet S. de Moor
  • Ashley Wilder Smith
  • Nita L. Seibel
Original paper

Abstract

Purpose

Improvement in US survival rates among adolescents and young adults (AYAs, ages 15 through 39 years inclusive) diagnosed with non-Hodgkin lymphoma (NHL) has been documented over the last two decades. We examined national trends in survival disparities for AYAs with NHL by race/ethnicity and socioeconomic status (SES, county-level poverty) to further understand NHL and to begin monitoring health outcome disparities for this disease.

Methods

Surveillance Epidemiology and End Results data were used to calculate 5-year relative survival rates of AYAs diagnosed with NHL from 1992 to 2007 and followed through 2011. Absolute and relative disparities were computed using HD*Calc. Whether a significant linear trend was present was evaluated using Joinpoint. Analyses were replicated after excluding individuals with known HIV infection.

Results

The study sample included 9,573 total and 7,121 non-HIV cases of NHL. Five-year survival rates improved for all groups over time. Significant decreases were found in absolute disparities for race/ethnicity (non-HIV), in relative disparities for SES (total) and race/ethnicity (total and non-HIV) (all p < 0.05). Survival rates of non-Hispanic Blacks and Hispanics remained below than those of non-Hispanic Whites throughout the time period.

Conclusion

Absolute and relative disparities in 5-year survival narrowed for AYAs with NHL over the time period. To continue to promote this trend, future research should investigate factors, particularly diagnostic delays and barriers to care, which continue to contribute to SES and racial/ethnic differences in survival. These factors may be particularly relevant to identify given the recent Affordable Care Act, which is designed to increase access to medical services, particularly for young adults.

Keywords

Non-Hodgkin lymphoma Adolescents and young adults Relative survival Cancer health disparities Surveillance 

References

  1. 1.
    Adolescent and Young Adult Oncology Progress Review Group (2006) Closing the gap: research and care imperatives for adolescents and young adults with cancer (NIH Publication No. 06-6067). Bethesda, MDGoogle Scholar
  2. 2.
    Pulte D, Gondos A, Brenner H (2009) Trends in survival after diagnosis with hematologic malignancy in adolescence or young adulthood in the United States, 1981–2005. Cancer 115:4973–4979PubMedCrossRefGoogle Scholar
  3. 3.
    Pulte D, Redaniel MT, Brenner H, Jeffreys M (2012) Changes in survival by ethnicity of patients with cancer between 1992–1996 and 2002–2006: is the discrepancy decreasing? Ann Oncol 23:2428–2434PubMedCrossRefGoogle Scholar
  4. 4.
    Li Y, Wang Y, Wang Z, Yi D, Ma S (2015) Racial differences in three major NHL subtypes: descriptive epidemiology. Cancer Epidemiol 39:8–13PubMedCrossRefGoogle Scholar
  5. 5.
    Kato I, Booza J, Quarshie WO, Schwartz K (2012) Persistent socioeconomic inequalities in cancer survival in the United States: 1973–2007 Surveillance, Epidemiology and End Results (SEER) data for breast cancer and non-Hodgkin’s lymphoma. J Regist Manag 39:158–166Google Scholar
  6. 6.
    Kent EE, Morris RA, Largent JA, Ziogas A, Sender LS, Anton-Culver H (2010) Socioeconomic impacts on survival differ by race/ethnicity among adolescents and young adults with non-Hodgkin’s lymphoma. J Cancer EpidemiolGoogle Scholar
  7. 7.
    Howlader N, Ries LA, Mariotto AB, Reichman ME, Ruhl J, Cronin KA (2010) Improved estimates of cancer-specific survival rates from population-based data. J Natl Cancer Inst 102:1584–1598PubMedCentralPubMedCrossRefGoogle Scholar
  8. 8.
    Shiels MS, Engels EA, Linet MS et al (2013) The epidemic of non-Hodgkin lymphoma in the United States: disentangling the effect of HIV, 1992–2009. Cancer Epidemiol Biomark Prev 22:1069–1078CrossRefGoogle Scholar
  9. 9.
    Breen N, Scott S, Percy-Laurry A, Lewis D, Glasgow R (2014) Health disparities calculator: a methodologically rigorous tool for analyzing inequalities in population health. Am J Public Health 104:1589–1591PubMedCrossRefGoogle Scholar
  10. 10.
    Harper S, Lynch J, Meersman SC, Breen N, Davis WW, Reichman MC (2009) Trends in area-socioeconomic and race–ethnic disparities in breast cancer incidence, stage at diagnosis, screening, mortality, and survival among women ages 50 years and over (1987–2005). Cancer Epidemiol Biomark Prev 18:121–131CrossRefGoogle Scholar
  11. 11.
    An Q, Prejean J, Hall HI (2012) Racial disparity in U.S. diagnoses of acquired immune deficiency syndrome, 2000–2009. Am J Prev Med 43:461–466PubMedCrossRefGoogle Scholar
  12. 12.
    Barr RD, Holowaty EJ, Birch JM (2006) Classification schemes for tumors diagnosed in adolescents and young adults. Cancer 106:1425–1430PubMedCrossRefGoogle Scholar
  13. 13.
    Fritz A, Percy C, Jack A et al (2000) International classification of diseases for oncology (ICD-O), 3rd edn. World Health Organization, GenevaGoogle Scholar
  14. 14.
    NAACCR Race and Ethnicity Work Group (2011) NAACCR guideline for enhancing Hispanic/Latino identification: revised NAACCR Hispanic/Latino identification algorithm [NHIA v2.2.1]. North American Association of Central Cancer Registries, Springfield, ILGoogle Scholar
  15. 15.
    Cho H, Howlader N, Mariotto AB, Cronin KA (2011) Estimating relative survival for cancer patients from the SEER Program using expected rates based on Ederer I versus Ederer II method. Surveillance Research Program, National Cancer Institute, Bethesda, MD Google Scholar
  16. 16.
    Health Disparities Calculator Version 1.2.4—October 29 2013. Division of Cancer Control and Population Sciences, Surveillance Research Program and Applied Research Program, National Cancer InstituteGoogle Scholar
  17. 17.
    Harper S, Lynch J (2005) Methods for measuring cancer disparities: using data relevant to Healthy People 2010 cancer-related objectives. NCI Cancer Surveillance Monograph Series. National Cancer Institute, Bethesda, MDGoogle Scholar
  18. 18.
    Harper S, Lynch J (2005) Selected comparisons of measures of health disparities: a review using databases relevant to Healthy People 2010 cancer-related objectives. National Cancer Institute, Bethesda, MDGoogle Scholar
  19. 19.
    Surveillance E, and End Results (SEER) Program (www.seer.cancer.gov). SEER*Stat Database: Incidence—SEER 18 Regs Research Data, Nov 2011 Sub (1973–2010) <Katrina/Rita Population Adjustment>—Linked To County Attributes—Total U.S., 1969–2010 Counties, National Cancer Institute, DCCPS, Surveillance Research Program, Surveillance Systems Branch, released April 2013, based on the November 2012 submission
  20. 20.
    Statistical Methodology and Applications Branch SRP, National Cancer Institute. Joinpoint Regression Program, Version 4.0.4—May 2013Google Scholar
  21. 21.
    Bleyer A, Choi M, Fuller CD, Thomas CR Jr, Wang SJ (2009) Relative lack of conditional survival improvement in young adults with cancer. Semin Oncol 36:460–467PubMedCrossRefGoogle Scholar
  22. 22.
    Frederiksen BL, Dalton SO, Osler M, Steding-Jessen M, de Nully Brown P (2012) Socioeconomic position, treatment, and survival of non-Hodgkin lymphoma in Denmark—a nationwide study. Br J Cancer 106:988–995PubMedCentralPubMedCrossRefGoogle Scholar
  23. 23.
    Woods LM, Rachet B, Coleman MP (2006) Origins of socio-economic inequalities in cancer survival: a review. Ann Oncol 17:5–19PubMedCrossRefGoogle Scholar
  24. 24.
    Koroukian SM, Bakaki PM, Raghavan D (2012) Survival disparities by Medicaid status: an analysis of 8 cancers. Cancer 118:4271–4279PubMedCentralPubMedCrossRefGoogle Scholar
  25. 25.
    Sandlund JT (2007) Should adolescents with NHL be treated as old children or young adults? Hematology/the Education Program of the American Society of Hematology. American Society of Hematology. Education Program, pp 297–303Google Scholar
  26. 26.
    Keegan TH, Moy LM, Foran JM et al (2013) Rituximab use and survival after diffuse large B-cell or follicular lymphoma: a population-based study. Leuk Lymphoma 54:743–751PubMedCrossRefGoogle Scholar
  27. 27.
    Flowers CR, Fedewa SA, Chen AY et al (2012) Disparities in the early adoption of chemoimmunotherapy for diffuse large B-cell lymphoma in the United States. Cancer Epidemiol Biomark Prev 21:1520–1530CrossRefGoogle Scholar
  28. 28.
    Bruce CJ (2007) Rituxan® anniversary: 10 years of progress. Oncol Bus Rev (November):18–19 Google Scholar
  29. 29.
    Cronin DP, Harlan LC, Clegg LX, Stevens JL, Yuan G, Davis TA (2005) Patterns of care in a population-based random sample of patients diagnosed with non-Hodgkin’s lymphoma. Hematol Oncol 23:73–81PubMedCrossRefGoogle Scholar
  30. 30.
    Komrokji RS, Al Ali NH, Beg MS et al (2011) Outcome of diffuse large B-Cell lymphoma in the United States has improved over time but racial disparities remain: review of SEER data. Clin Lymphoma Myeloma Leuk 11:257–260PubMedCrossRefGoogle Scholar
  31. 31.
    Frey CM, McMillen MM, Cowan CD, Horm JW, Kessler LG (1992) Representativeness of the surveillance, epidemiology, and end results program data: recent trends in cancer mortality rates. J Natl Cancer Inst 84:872–877PubMedCrossRefGoogle Scholar
  32. 32.
    Yu M, Tatalovich Z, Gibson JT, Cronin KA (2014) Using a composite index of socioeconomic status to investigate health disparities while protecting the confidentiality of cancer registry data. Cancer Causes Control 25:81–92PubMedCrossRefGoogle Scholar
  33. 33.
    Levit L, Balogh E, Nass S, Ganz PA (2013) Delivering high-quality cancer care: charting a new course for a system in crisis. The National Academies Press, Washington, DCGoogle Scholar
  34. 34.
    Zebrack B, Isaacson S (2012) Psychosocial care of adolescent and young adult patients with cancer and survivors. J Clin Oncol 30:1221–1226PubMedCrossRefGoogle Scholar
  35. 35.
    Guy GP Jr, Yabroff KR, Ekwueme DU et al (2014) Estimating the health and economic burden of cancer among those diagnosed as adolescents and young adults. Health Aff (Millwood) 33:1024–1031CrossRefGoogle Scholar
  36. 36.
    Keegan TH, Tao L, Derouen MC et al (2014) Medical care in adolescents and young adult cancer survivors: what are the biggest access-related barriers? J Cancer Surviv 8:282–292PubMedCentralPubMedCrossRefGoogle Scholar
  37. 37.
    Aizer AA, Falit B, Mendu ML et al (2014) Cancer-specific outcomes among young adults without health insurance. J Clin Oncol 32:2025–2030Google Scholar
  38. 38.
    Pew Hispanic Center (2011) Census 2010: 50 million Latinos: Hispanics account for more than half of the nation’s growth in past decade. Pew Research CenterGoogle Scholar

Copyright information

© Springer International Publishing Switzerland (outside the USA) 2015

Authors and Affiliations

  1. 1.Outcomes Research Branch, Healthcare Delivery Research Program, Division of Cancer Control and Population SciencesNational Cancer InstituteRockvilleUSA
  2. 2.Health Systems and Interventions Research Branch, Healthcare Delivery Research Program, Division of Cancer Control and Population SciencesNational Cancer InstituteRockvilleUSA
  3. 3.Data Quality, Analysis, and Interpretation Branch, Surveillance Research Program, Division of Cancer Control and Population SciencesNational Cancer InstituteRockvilleUSA
  4. 4.Healthcare Assessment Research Branch, Healthcare Delivery Research Program, Division of Cancer Control and Population SciencesNational Cancer InstituteRockvilleUSA
  5. 5.Clinical Investigations Branch, Cancer Therapy Evaluation Program, Division of Cancer Treatment and DiagnosisNational Cancer InstituteRockvilleUSA

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