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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/373

Title: Summary measures and statistics in the analysis of quality of life data: An example from an EORTC-NCIC-SAKK locally advanced breast cancer study
Authors: Curran, Desmond
Aaronson, Neil
Standaert, Baudouin
Molenberghs, Geert
Therasse, Patrick
Ramirez, A.
Koopmanschap, M.
Erder, Haim M.
Piccart, M.
Keywords: Missing data
Clinical trials
Issue Date: 2000
Publisher: PERGAMON-ELSEVIER SCIENCE LTD
Citation: European Journal of Cancer, 36(7). p. 834-844
Abstract: Quality of Life (QL) is now included as an endpoint in many phase III cancer clinical trials. Numerous statistical techniques have been presented in the literature to analyse QL data but there is still no agreement as to what is the optimal approach of analysis. In this paper we, therefore, present and compare various techniques which have all appeared in the literature and which may be globally described as summary measures and summary statistics. These techniques are illustrated using data from an EORTC clinical trial in locally advanced breast cancer (EORTC trial 10921). It is also explained in this paper how and when these techniques may be used in other cancer settings. For EORTC trial 10921, it is shown that by choosing different techniques different conclusions may be drawn concerning the QL outcome. This highlights the importance of choosing an appropriate primary statistical method and for describing it a priori in the protocol and analysis plan. In this paper, we show the importance of performing sensitivity or supportive analysis to support conclusions drawn from the primary analysis.
URI: http://hdl.handle.net/1942/373
DOI: 10.1016/S0959-8049(00)00056-3
ISI #: 000087093100011
ISSN: 0959-8049
Category: A1
Type: Journal Contribution
Validation: ecoom, 2001
Appears in Collections: Research publications

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