Developments and challenges in statistical methods in cancer surveillance

Huann Sheng Chen, Angela B. Mariotto, Li Zhu, Hyune Ju Kim, Hyunsoon Cho, Eric J. Feuer

Research output: Contribution to journalArticlepeer-review

Abstract

Cancer surveillance includes the monitoring of population levels and trends in incidence, survival, mortality, and prevalence. In addition, data are collected on the factors that influence these basic statistics across the entire cancer control continuum, such as healthy populations at risk of cancer, new diagnosis of cancer, treatment of cancer, living with cancer, and dying of cancer or other causes. To interpret the cancer statistics that are collected, an entire area of statistical methodology has been developed at the U.S. National Cancer Institute (NCI) and other institutions throughout the world. Most of these developments took place in the last 20 years, and the field is still evolving. In this review, we provide an overview of these methods, including the motivation for their development and how the methods compare with more general mainstream statistical methodology; available software; and relevant literature references.

Original languageEnglish (US)
Pages (from-to)135-151
Number of pages17
JournalStatistics and its Interface
Volume7
Issue number1
DOIs
StatePublished - 2014

Keywords

  • Cancer surveillance
  • Delay adjustment model
  • Incidence
  • Joinpoint regression model
  • Mortality
  • Prevalence
  • Spatial statistics
  • Survival analysis

ASJC Scopus subject areas

  • Statistics and Probability
  • Applied Mathematics

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