4.3 Article

Geographic clustering of cutaneous T-cell lymphoma in New Jersey: an exploratory analysis using residential histories

Journal

CANCER CAUSES & CONTROL
Volume 32, Issue 9, Pages 989-999

Publisher

SPRINGER
DOI: 10.1007/s10552-021-01452-y

Keywords

Lymphoma; Non-hodgkin; CTCL; Geographic information systems; Geographic clustering; Residential histories

Funding

  1. National Science Foundation [1560888]
  2. National Cancer Institute
  3. Surveillance, Epidemiology, and End Results Program [HHSN261201300021I]
  4. Centers for Disease Control and Prevention's National Program of Cancer Registries [5U58DP003931-02/NU58DP006279-02-00]
  5. State of New Jersey
  6. Rutgers Cancer Institute of New Jersey
  7. Division Of Behavioral and Cognitive Sci
  8. Direct For Social, Behav & Economic Scie [1560888] Funding Source: National Science Foundation

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Geographic clustering of CTCL cases in New Jersey based on past residences is evident. Further studies are needed to understand the reasons for the higher incidence of CTCL in this specific area in the 8-14 years prior to diagnosis.
Purpose Cutaneous T-cell lymphoma (CTCL) is a rare type of non-Hodgkin lymphoma. Previous studies have reported geographic clustering of CTCL based on the residence at the time of diagnosis. We explore geographic clustering of CTCL using both the residence at the time of diagnosis and past residences using data from the New Jersey State Cancer Registry. Methods CTCL cases (n = 1,163) diagnosed between 2006-2014 were matched to colon cancer controls (n = 17,049) on sex, age, race/ethnicity, and birth year. Jacquez's Q-Statistic was used to identify temporal clustering of cases compared to controls. Geographic clustering was assessed using the Bernoulli-based scan-statistic to compare cases to controls, and the Poisson-based scan-statisic to compare the observed number of cases to the number expected based on the general population. Significant clusters (p < 0.05) were mapped, and standard incidence ratios (SIR) reported. We adjusted for diagnosis year, sex, and age. Results The Q-statistic identified significant temporal clustering of cases based on past residences in the study area from 1992 to 2002. A cluster was detected in 1992 in Bergen County in northern New Jersey based on the Bernoulli (1992 SIR 1.84) and Poisson (1992 SIR 1.86) scan-statistics. Using the Poisson scan-statistic with the diagnosis location, we found evidence of an elevated risk in this same area, but the results were not statistically significant. Conclusion There is evidence of geographic clustering of CTCL cases in New Jersey based on past residences. Additional studies are necessary to understand the possible reasons for the excess of CTCL cases living in this specific area some 8-14 years prior to diagnosis.

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