Modeling the effect of a preventive intervention on the natural history of cancer: Application to the Prostate Cancer Prevention Trial

Paul Pinsky, Ruth Etzioni, Nadia Howlader, Phyllis Goodman, Ian M. Thompson

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

The Prostate Cancer Prevention Trial (PCPT) recently demonstrated a significant reduction in prostate cancer incidence of about 25% among men taking finasteride compared to men taking placebo. However, the effect of finasteride on the natural history of prostate cancer is not well understood. We adapted a convolution model developed by Pinsky (2001) to characterize the natural history of prostate cancer in the presence and absence of finasteride. The model was applied to data from 10,995 men in PCPT who had disease status determined by interim diagnosis of prostate cancer or end-of-study biopsy. Prostate cancer cases were either screen-detected by Prostate- Specific Antigen (PSA), biopsy-detected at the end of the study, or clinically detected, that is, detected by methods other than PSA screening. The hazard ratio (HR) for the incidence of preclinical disease on finasteride versus placebo was 0.42 (95% CI: 0.20-0.58). The progression from preclinical to clinical disease was relatively unaffected by finasteride, with mean sojourn time being 16 years for placebo cases and 18.5 years for finasteride cases (p-value for difference = 0.2). We conclude that finasteride appears to affect prostate cancer primarily by preventing the emergence of new, preclinical tumors with little impact on established, latent disease.

Original languageEnglish (US)
Article number12
JournalInternational Journal of Biostatistics
Volume2
Issue number1
DOIs
StatePublished - Jan 1 2006

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Keywords

  • Chemoprevention
  • Convolution model
  • Lead time
  • Sojourn time

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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