Each year, approximately 140,000 Americans develop acute respiratory distress syndrome (ARDS), and 40% of these patients die. Yet, only 5% of all ARDS randomized clinical trials (RCTs) designed to detect reductions in mortality have been able to identify new, successful interventions. In addition to improving survival, a 2009 NHLBI workshop identified several priorities for future ARDS RCTs, including the development of strategies to enroll fewer patients and a focus on longer-term patient-centered endpoints for ARDS survivors. Although the critical care community has sought to identify interventions' effects on post intensive care unit (ICU) endpoints such as quality of life (QOL) and physical and cognitive functioning, there are several methodological challenges in assessing non-mortal endpoints among ARDS patients. These include missing data resulting from high patient mortality rates (i.e., censoring from death), heterogeneous treatment effects among subsets of ARDS patients, and the lack of validated, early surrogate endpoints for long-term patient-centered outcomes. The overall goal of this research and training plan is to execute three interrelated studies as the subject of a doctoral dissertation in clinical epidemiology that will have immediate relevance in improving the conduct, analysis and application of findings from RCTs for ARDS patients. First, in Aim 1, we will advance an innovative statistical framework for the analysis of short- and long-term non-mortal outcomes that addresses the biases resulting from death-induced missing data. Specifically, we will utilize a joint modeling framework with longitudinal and survival components, resulting in gains in statistical power (potentially reducing the needed sample sizes in RCTs), while offering greater clinical and statistical inference than current methods commonly used in RCTs. Next, in Aim 2, we will generate a multivariable risk score based on patient-level data that can be used to guide more individualized treatment recommendations among heterogeneous ARDS patients, and integrate it into our joint modeling framework. Finally, in Aim 3, we will seek to identify threshold effects of ICU ventilation exposure (e.g., time requiring mechanical ventilation, ventilator-free days) that predict long-term mortality and post-ICU QOL. A rigorous curriculum including didactic and experiential learning in critical care, statistics, and advanced epidemiology will round out the applicant's training, preparing him to be an independent and collaborative faculty investigator and critical care trialis at the completion of his PhD.
To develop more successful therapies for acute respiratory distress syndrome patients, investigators must address several methodological challenges inherent in studying a very sick and diverse population. Using real clinical trial data to inform statistical simulations, this proposal will improve upon the strategies available to surmount problems of missing data due to high death rates, identify treatments' differential effects among variable patient types, and efficiently quantify interventions' effects on patient-centered outcomes such as quality-of-life following an ICU stay.
Showing the most recent 10 out of 24 publications
