Analysis of colorectal adenoma recurrence data subject to informative censoring

Chiu-Hsieh Hsu, Jeremy M G Taylor, Qi Long, David S Alberts

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The treatment effect of a colorectal polyp prevention trial is often evaluated from the colorectal adenoma recurrence status at the end of the trial. However, early colonoscopy from some participants complicates estimation of the final study end recurrence rate. The early colonoscopy could be informative of status of recurrence and induce informative differential follow-up into the data. In this article, we use midpoint imputation to handle interval-censored observations. We then apply a weighted Kaplan-Meier method to the imputed data to adjust for potential informative differential follow-up, while estimating the recurrence rate at the end of the trial. In addition, we modify the weighted Kaplan-Meier method to handle a situation with multiple prognostic covariates by deriving a risk score of recurrence from a working logistic regression model and then use the risk score to define risk groups to perform weighted Kaplan-Meier estimation. We argue that midpoint imputation will produce an unbiased estimate of recurrence rate at the end of the trial under an assumption that censoring only depends on the status of early colonoscopy. The method described here is illustrated with an example from a colon polyp prevention study.

Original languageEnglish (US)
Pages (from-to)712-717
Number of pages6
JournalCancer Epidemiology Biomarkers and Prevention
Volume18
Issue number3
DOIs
StatePublished - Mar 2009

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Adenoma
Recurrence
Colonoscopy
Polyps
Logistic Models
Colon

ASJC Scopus subject areas

  • Epidemiology
  • Oncology

Cite this

Analysis of colorectal adenoma recurrence data subject to informative censoring. / Hsu, Chiu-Hsieh; Taylor, Jeremy M G; Long, Qi; Alberts, David S.

In: Cancer Epidemiology Biomarkers and Prevention, Vol. 18, No. 3, 03.2009, p. 712-717.

Research output: Contribution to journalArticle

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