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Substudies of the Childhood Asthma Management Program [Control. Clin. Trials20 (1999) 91-120; N. Engl. J. Med. 343 (2000) 1054-1063] seek to identifypatient characteristics associated with asthma symptoms and lung function. Todetermine if genetic measures are associated with trajectories of lung functionas measured by forced vital capacity (FVC), children in the primary cohortstudy retrospectively had candidate loci evaluated. Given participant burdenand constraints on financial resources, it is often desirable to target asubsample for ascertainment of costly measures. Methods that can leverage thelongitudinal outcome on the full cohort to selectively measure informativeindividuals have been promising, but have been restricted in their use toanalysis of the targeted subsample. In this paper we detail two multipleimputation analysis strategies that exploit outcome and partially observedcovariate data on the nonsampled subjects, and we characterize alternativedesign and analysis combinations that could be used for future studies ofpulmonary function and other outcomes. Candidate predictor (e.g., IL10 cytokinepolymorphisms) associations obtained from targeted sampling designs can beestimated with very high efficiency compared to standard designs. Further, eventhough multiple imputation can dramatically improve estimation efficiency forcovariates available on all subjects (e.g., gender and baseline age),relatively modest efficiency gains were observed in parameters associated withpredictors that are exclusive to the targeted sample. Our results suggest thatfuture studies of longitudinal trajectories can be efficiently conducted by useof outcome-dependent designs and associated full cohort analysis.

Biased sampling designs to improve research efficiency: Factors influencing pulmonary function over time in children with asthma