Does finasteride affect the severity of prostate cancer? A causal sensitivity analysis

Bryan E. Shepherd, Mary W. Redman, Donna P. Ankerst

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

In 2003 Thompson and colleagues reported that daily use of finasteride reduced the prevalence of prostate cancer by 25% compared to placebo. These results were based on the double-blind randomized Prostate Cancer Prevention Trial (PCPT), which followed 18,882 men with no prior or current indications of prostate cancer annually for 7 years. Enthusiasm for the risk reduction afforded by the chemopreventative agent and adoption of its use in clinical practice, however, was severely dampened by the additional finding in the trial of an increased absolute number of high-grade (Gleason score = 7) cancers on the finasteride arm. The question arose as to whether this finding truly implied that finasteride increased the risk of more severe prostate cancer or was a study artifact due to a series of possible postrandomization selection biases, including differences among treatment arms in patient characteristics of cancer cases, differences in biopsy verification of cancer status due to increased sensitivity of prostate-specific antigen under finasteride, differential grading by biopsy due to prostate volume reduction by finasteride, and nonignorable dropout. Via a causal inference approach implementing inverse probability weighted estimating equations, this analysis addresses the question of whether finasteride caused more severe prostate cancer by estimating the mean treatment difference in prostate cancer severity between finasteride and placebo for the principal stratum of participants who would have developed prostate cancer regardless of treatment assignment. We perform sensitivity analyses that sequentially adjust for the numerous potential postrandomization biases conjectured in the PCPT.

Original languageEnglish (US)
Pages (from-to)1392-1404
Number of pages13
JournalJournal of the American Statistical Association
Volume103
Issue number484
DOIs
StatePublished - Dec 2008

Keywords

  • Causal inference
  • Principal stratification
  • Selection bias
  • Treatment effects

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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