Comparison of several model-based methods for analysing incomplete quality of life data in cancer clinical trials

Diane L. Fairclough*, Harriet F. Peterson, David Cella, Phil Bonomi

*Corresponding author for this work

Research output: Contribution to journalArticle

92 Scopus citations

Abstract

This paper considers five methods of analysis of longitudinal assessment of health related quality of life (QOL) in two clinical trials of cancer therapy. The primary difference in the two trials is the proportion of participants who experience disease progression or death during the period of QOL assessments. The sensitivity of estimation of parameters and hypothesis tests to the potential bias as a consequence of the assumptions of missing completely at random (MCAR), missing at random (MAR) and non-ignorable mechanisms are examined. The methods include complete case analysis (MCAR), mixed-effects models (MAR), a joint mixed-effects and survival model and a pattern-mixture model. Complete case analysis overestimated QOL in both trials. In the adjuvant breast cancer trial, with 15 per cent disease progression, estimates were consistent across the remaining four methods. In the advanced non-small-cell lung cancer trial, with 35 per cent mortality, estimates were sensitive to the missing data assumptions and methods of analysis.

Original languageEnglish (US)
Pages (from-to)781-796
Number of pages16
JournalStatistics in Medicine
Volume17
Issue number5-7
StatePublished - Mar 15 1998

ASJC Scopus subject areas

  • Epidemiology

Fingerprint Dive into the research topics of 'Comparison of several model-based methods for analysing incomplete quality of life data in cancer clinical trials'. Together they form a unique fingerprint.

  • Cite this