Inference for Mutually Exclusive Competing Events Through a Mixture of Generalized Gamma Distributions
Year: 2010
Type: article
Abstract: BACKGROUND: Time-to-event data with 2 or more types of endpoints are found in many epidemiologic settings. Instead of treating the times for one of the endpoints as censored observations for the other, we present an alternative approach where we treat competing events as distinct outcomes in a mixture. Our objective was to determine if and how the mixture was modified in response to an intervention. METHODS: We used a mixture of generalized gamma distributions to concatenate the overall frequency and distribution of the times of 2 competing events commonly observed in critical care trials, namely (1) unassisted breathing followed by discharge home alive and (2) in-hospital death. We applied our proposed methods to data from 2 randomized clinical trials of critically ill patients. RESULTS: Mechanical ventilation with lower tidal volumes modified the mixture (P = 0.103) when compared with traditional tidal volumes by lowering the overall frequency of death (P = 0.005), rather than through affecting either the distributions of times to unassisted breathing (P = 0.477) or times to death (P = 0.718). Likewise, use of a conservative versus a liberal fluid management modified the mixture (P < 0.001) by achieving earlier times to unassisted breathing (P < 0.001) and not through affecting the overall frequency of death (P = 0.202) or the distribution of times to death (P = 0.693). CONCLUSIONS: A mixture approach to competing risks provides a means to determine the overall effect of an intervention and insights into how this intervention modifies the components of the mixture.
Source: Epidemiology
Authors: William Checkley, Roy G. Brower, Alvaro Muñoz
Institution: Johns Hopkins University
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
Awards: Novel approaches to the epidemiology analysis of clinical outcomes in ARDS, G2629771443, CCTG NETWORK FOR ARDS TREATMENT, G3805585402, G6242769113, G6659628656, Acute Lung Injury: Application of Novel Approaches to Longitudinal Data Analysis, The Kidney Disease in Children Data Management and Analysis Center (KIDMAC), G792043582, Acute Lung Injury: Application of Novel Approaches to Longitudinal Data Analysis
OpenAlex ID: W2094922717