Summary measures and statistics for comparison of quality of life in a clinical trial of cancer therapy.
Assessment of health related quality of life (QOL) has become an important endpoint in many clinical trials of cancer therapy. Most of these studies entail multiple QOL scales that are assessed repeatedly over time. As a result, the problem of multiple comparisons is a primary analytic challenge with these trials. The use of summary measures and statistics both reduces the number of hypotheses tested and facilitates the interpretation of trial results where the primary question is 'Does the overall QOL differ between treatment arms?' I present two classes of summary measures that are sensitive to consistent trends in the same direction across multiple assessment times or multiple QOL scales. Missing data strongly influences the choice between the two classes, where one class handles missing data on an individual basis, while the other class uses model-based strategies. I present the results from a clinical trial of adjuvant therapy for breast cancer that use summary measures with a focus on the practical issues that affect these analysis strategies, such as missing data and integration of QOL with efficacy endpoints such as survival.
Fairclough
D L
DL
Division of Biostatistics, Dana Farber Cancer Institute, Boston, MA, USA.
D000704:Analysis of Variance; D015982:Bias; D001943:Breast Neoplasms / Q000523:psychology / Q000628:therapy*; D005260:Female; D006801:Humans; D019057:Quality-Adjusted Life Years; D016032:Randomized Controlled Trials as Topic; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016019:Survival Analysis; D013997:Time Factors