Acute lung injury (ALI) affects approximately 190,000 patients per year and is associated with more deaths annually in the United States than breast cancer or HIV/AIDS. Clinical research in ALI is challenging because events recorded through time are complex and difficult to analyze. Physicians make decisions about the care of ALI patients using information gathered through time; however, clinical trials commonly use outcomes at 28 days such as mortality and ventilator-free days to evaluate treatments effects. When the effects through time are ignored, valuable information on morbidity outcomes is lost. Additionally, outcomes in critically ill-patients fulfill the setting of 'competing risks,' as death hinders the observation of morbidity outcomes. The classical approach to consider one event as an incomplete observation for the other violates the assumptions of standard methods in survival analysis, does not describe the realities of critical care outcomes, and only provides a limited view ofthe complexities of these competing events.
Aim 1 is to fully characterize the effects of interventions through time on morbidity outcomes with mixtures of generalized gamma distributions, which offer a flexible framework to model competing events, using data from 3 clinical trials.
Aim 2 is to describe the association of prognostic factors measured repeatedly through time and clinical outcomes in ALI patients. We hypothesize that the information gained from time-varying factors will perform better than baseline predictors at prognosticating patient outcomes.
Aim 3 is to collect prospective data in ALI patients and to study the association between in trajectories in plateau pressure through time and patient outcomes. Plateau pressure is routinely measured 4 times daily to monitor ventilator therapy; however, this frequent number of recordings is not available in current databases. Valuable information that may correlate with disease progression is Ipjst. We hypothesize that plateau pressure measured repeatedly through time may serve as a useful surrogate for clinical endpoints in ALI patients. We plan to conduct a prospective study in 300 ALI patients. We will visit these patients 4 times daily to record plateau pressure in the first 7 days and daily until the patient either achieves unassisted breathing, dies, or until day 28.
The use of analytical approaches that account for the effects through time may improve our ability to evaluate therapies more efficiently with studies of shorter duration or fewer patients, evaluate benefit or harm earlier in clinical trials, detect therapies that may be beneficial despite no difference in mortality, and aid clinical decision making in real-time. We will explore new statistical methods to address these complexities.
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