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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