Predicting US- and state-level cancer counts for the current calendar year: Part II: Evaluation of spatiotemporal projection methods for incidence

Li Zhu, Linda W. Pickle, Kaushik Ghosh, Deepa Naishadham, Kenneth Portier, Huann Sheng Chen, Hyune Ju Kim, Zhaohui Zou, James Cucinelli, Betsy Kohler, Brenda K. Edwards, Jessica King, Eric J. Feuer, Ahmedin Jemal

Research output: Contribution to journalArticle

41 Scopus citations

Abstract

BACKGROUND. The current study was undertaken to evaluate the spatiotemporal projection models applied by the American Cancer Society to predict the number of new cancer cases. METHODS. Adaptations of a model that has been used since 2007 were evaluated. Modeling is conducted in 3 steps. In step I, ecologic predictors of spatiotemporal variation are used to estimate age-specific incidence counts for every county in the country, providing an estimate even in those areas that are missing data for specific years. Step II adjusts the step I estimates for reporting delays. In step III, the delay-adjusted predictions are projected 4 years ahead to the current calendar year. Adaptations of the original model include updating covariates and evaluating alternative projection methods. Residual analysis and evaluation of 5 temporal projection methods were conducted. RESULTS. The differences between the spatiotemporal model-estimated case counts and the observed case counts for 2007 were < 1%. After delays in reporting of cases were considered, the difference was 2.5% for women and 3.3% for men. Residual analysis indicated no significant pattern that suggested the need for additional covariates. The vector autoregressive model was identified as the best temporal projection method. CONCLUSIONS. The current spatiotemporal prediction model is adequate to provide reasonable estimates of case counts. To project the estimated case counts ahead 4 years, the vector autoregressive model is recommended to be the best temporal projection method for producing estimates closest to the observed case counts.

Original languageEnglish (US)
Pages (from-to)1100-1109
Number of pages10
JournalCancer
Volume118
Issue number4
DOIs
StatePublished - Feb 15 2012

Keywords

  • National Program of Cancer Registries (NPCR)
  • Surveillance, Epidemiology, and End Results (SEER)
  • cancer incidence
  • cancer surveillance
  • projection methods
  • spatiotemporal

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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    Zhu, L., Pickle, L. W., Ghosh, K., Naishadham, D., Portier, K., Chen, H. S., Kim, H. J., Zou, Z., Cucinelli, J., Kohler, B., Edwards, B. K., King, J., Feuer, E. J., & Jemal, A. (2012). Predicting US- and state-level cancer counts for the current calendar year: Part II: Evaluation of spatiotemporal projection methods for incidence. Cancer, 118(4), 1100-1109. https://doi.org/10.1002/cncr.27405