Imputing missing quality of life data as covariate in survival analysis of the International Breast Cancer Study Group Trials VI and VII

Marion Procter, Charles Robertson

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
47 Downloads (Pure)

Abstract

Quality of life (QoL) was an important endpoint in the adjuvant breast cancer trials International Breast Cancer Study Group (IBCSG) Trial VI and VII. Here, QoL was considered as a time-dependent effect. The hypothesis explored is that poorer QoL throughout the trial is associated with poorer disease-free survival (DFS) and vice-versa. Potential bias in the parameter estimates is an important concern associated with missing observations. Standard simple and multiple imputation methods were applied to missing QoL assessments before analysis in a time-dependent Cox model. There was no evidence that the patient's QoL is related to the patient's DFS.
Original languageEnglish
Pages (from-to)1-11
Number of pages11
JournalCommunications in Statistics - Simulation and Computation
Early online date30 Oct 2017
DOIs
Publication statusPublished - 15 Dec 2017

Keywords

  • informative missing data
  • multiple imputation
  • potential bias
  • qualify of life
  • simple imputation
  • time-dependent Cox model

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