Design and Analysis of Quality of Life Studies in Clinical Trials

Introduction and Examples Health-related quality of life (HRQoL) Measuring health-related quality of life Study 1: Adjuvant breast cancer trial Study 2: Migraine prevention trial Study 3: Advanced lung cancer trial Study 4: Renal cell carcinoma trial Study 5: Chemoradiation (CXRT) trial Study 6: Osteoarthritis trial Study Design and Protocol Development Introduction Background and rationale Research objectives and goals Selection of subjects Longitudinal designs Selection of measurement instrument(s) Conduct of HRQoL assessments Scoring instruments Models for Longitudinal Studies I Introduction Building models for longitudinal studies Building repeated measures models: The mean structure Building repeated measures models: The covariance structure Estimation and hypothesis testing Models for Longitudinal Studies II Introduction Building growth curve models: The mean (fixed effects) structure Building growth curve models: The covariance structure Model reduction Hypothesis testing and estimation An alternative growth-curve model Moderation and Mediation Introduction Moderation Mediation Other exploratory analyses Characterization of Missing Data Introduction Patterns and causes of missing data Mechanisms of missing data Missing completely at random (MCAR) Missing at random (MAR) Missing not at random (MNAR) Example for trial with variation in timing of assessments Example with different patterns across treatment arms Analysis of Studies with Missing Data Introduction MCAR Ignorable missing data Non-ignorable missing data Simple Imputation Introduction to imputation Missing items in a multi-item questionnaire Regression-based methods Other simple imputation methods Imputing missing covariates Underestimation of variance Final comments Multiple Imputation Introduction Overview of multiple imputation Explicit univariate regression Closest neighbor and predictive mean matching Approximate Bayesian bootstrap (ABB) Multivariate procedures for non-monotone missing data Analysis of the M data sets Miscellaneous issues Pattern Mixture and Other Mixture Models Introduction Pattern mixture models Restrictions for growth curve models Restrictions for repeated measures models Variance estimation for mixture models Random Effects Dependent Dropout Introduction Conditional linear model Varying coefficient models Joint models with shared parameters Selection Models Introduction Outcome selection model for monotone dropout Multiple Endpoints Introduction General strategies for multiple endpoints Background concepts and definitions Single step procedures Sequentially rejective methods Closed testing and gatekeeper procedures Composite Endpoints and Summary Measures Introduction Choosing a composite or summary measure Summarizing across HRQoL domains or subscales Summary measure across time Composite endpoints across time Quality Adjusted Life-Years (QALYs) and Q-TWiST Introduction QALYs Q-TWiST Analysis Plans and Reporting Results Introduction General analysis plan Sample size and power Reporting results Appendix C: Cubic Smoothing Splines Appendix P: PAWS/SPSS Notes Appendix R: R Notes Appendix S: SAS Notes References A Summary appears at the end of each chapter.