Estimating the frequency of indolent breast cancer in screening trials

Yu Shen, Wenli Dong, Roman Gulati, Marc D. Ryser, Ruth Etzioni

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Cancer screening can detect cancer that would not have been detected in a patient’s lifetime without screening. Standard methods for analyzing screening data do not explicitly account for the possibility that a fraction of tumors may remain latent indefinitely. We extend these methods by representing cancers as a mixture of those that progress to symptoms (progressive) and those that remain latent (indolent). Given sensitivity of the screening test, we derive likelihood expressions to simultaneously estimate (1) the rate of onset of preclinical cancer, (2) the average preclinical duration of progressive cancers, and (3) the fraction of preclinical cancers that are indolent. Simulations demonstrate satisfactory performance of the estimation approach to identify model parameters subject to precise specifications of input parameters and adequate numbers of interval cancers. In application to four breast cancer screening trials, the estimated indolent fraction among preclinical cancers varies between 2% and 35% when assuming 80% test sensitivity and varying specifications for the earliest time that participants could plausibly have developed cancer. We conclude that standard methods for analyzing screening data can be extended to allow some indolent cancers, but accurate estimation depends on correctly specifying key inputs that may be difficult to determine precisely in practice.

Original languageEnglish (US)
Pages (from-to)1261-1271
Number of pages11
JournalStatistical methods in medical research
Issue number4
StatePublished - Apr 1 2019
Externally publishedYes


  • Breast cancer
  • indolent cancer
  • mammography screening
  • maximum likelihood estimation
  • overdiagnosis
  • randomized controlled trials

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability
  • Health Information Management


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