Comparison of several model-based methods for analysing incomplete quality of life data in cancer clinical trials.
Workshop on Missing Data in Quality of Life Research in Cancer Clinical Trials : Practical and Methodological Issues. Bad Horn, CHE, 1996/07/01.
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.
Mots-clés Pascal : Etude comparative, Modèle statistique, Qualité vie, Essai clinique, Donnée manquante, Distribution longitudinale, Tumeur maligne, Traitement, Homme, Analyse sensibilité, Test hypothèse, Estimation paramètre
Mots-clés Pascal anglais : Comparative study, Statistical model, Quality of life, Clinical trial, Missing data, Longitudinal distribution, Malignant tumor, Treatment, Human, Sensitivity analysis, Hypothesis test, Parameter estimation
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Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 98-0228520
Code Inist : 002B30A01A2. Création : 11/09/1998.