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Sources of selection and information biases when using commercial database–derived residential histories for cancer research

  • Vincent L. Freeman
  • , Emma E. Boylan
  • , Nebiyou Y. Tilahun
  • , Sanjib Basu
  • , Mei Po Kwan

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: This study examined potential sources of selection and information biases when using residence history information from a commercial database to construct residential histories for cancer research. Methods: We searched the LexisNexis database for residence data on 3473 adults diagnosed with cancers of the prostate, colon/rectum, and female breast in a single health-care system between 2005 and 2016 using the name and address at diagnosis and the birth date. Residential histories were generated from the results using open-source statistical programs from the National Cancer Institute. Multivariable regression models analyzed the associations of the search results with demographic characteristics and all-cause mortality. Results: Racial/ethnic minorities were less likely to match to vendor residence data compared with non-Hispanic whites (odd ratios [95% confidence intervals (CIs)] for non-Hispanic blacks, Hispanics, and Asian/Pacific Islander were 1.66 [1.30, 2.12], 2.92 [2.18, 3.90], and 4.53 [2.72, 7.55], respectively). Being non-Hispanic black was negatively associated with years of residential history (vs. non-Hispanic whites, β coefficient [95% CI] = −2.57 [−3.40, −1.73]). Not matching to residence data was associated with an increased 5-year odds of death from any cause (vs. matched subjects, odd ratios [95% CI] = 5.92 [4.29, 8.50]). Conclusions: Differential ascertainment of residence history by race/ethnicity and association of ascertainment with prognosis are potential sources of selection and information biases when using residence data from a commercial database.

Original languageEnglish (US)
Pages (from-to)35-40.e1
JournalAnnals of Epidemiology
Volume51
DOIs
StatePublished - Nov 2020
Externally publishedYes

Keywords

  • Cancer
  • Database
  • Demographic factors
  • Information bias
  • Residence characteristics
  • Sampling bias

ASJC Scopus subject areas

  • Epidemiology

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