The analysis, interpretation, and presentation of quality of life data.
All too often in clinical trials the assessment of quality of life is seen as a bolt-on study. Consequently insufficient consideration is often given to its design, collection, analysis and presentation, and its impact on the trial results and on clinical practice is minimal. In many trials quality of life is a key endpoint, and it is vital that quality of life expertise is involved as soon as possible in the design. Setting a priori quality of life hypotheses will focus the decisions regarding which questionnaire to use, when to administer it, the sample size required, and the primary analyses. Nevertheless quality of life data are complex, and require much skill in determining how to deal with multi-dimensional and longitudinal data, much of which is often missing. There are no agreed standard ways of analysing and presenting quality of life data, but there are guidelines, which if followed, will add transparency to the way results have been calculated. Understanding the impact of treatments on their quality of life is vital to patients, and it is up to us, as statisticians and trialists, to present the data as clearly as we can.
Stephens
Richard
R
Cancer Division, Medical Research Council Clinical Trials Unit, London, UK. rs@ctu.mrc.ac.uk
D003627:Data Interpretation, Statistical; D006801:Humans; D011788:Quality of Life; D016032:Randomized Controlled Trials as Topic / Q000379:methods* / Q000706:statistics & numerical data*; D013997:Time Factors