Inference in randomized trials with death and missingness

Research output: Contribution to journalArticlepeer-review

Abstract

In randomized studies involving severely ill patients, functional outcomes are often unobserved due to missed clinic visits, premature withdrawal, or death. It is well known that if these unobserved functional outcomes are not handled properly, biased treatment comparisons can be produced. In this article, we propose a procedure for comparing treatments that is based on a composite endpoint that combines information on both the functional outcome and survival. We further propose a missing data imputation scheme and sensitivity analysis strategy to handle the unobserved functional outcomes not due to death. Illustrations of the proposed method are given by analyzing data from a recent non-small cell lung cancer clinical trial and a recent trial of sedation interruption among mechanically ventilated patients.

Original languageEnglish (US)
Pages (from-to)431-440
Number of pages10
JournalBiometrics
Volume73
Issue number2
DOIs
StatePublished - Jun 2017

Keywords

  • Composite endpoint
  • Death-truncated data
  • Missing data
  • Sensitivity analysis

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

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