70 research outputs found
Fitting and Interpreting Continuous-Time Latent Markov Models for Panel Data
Multistate models are used to characterize disease processes within an individual. Clinical studies often observe the disease status of individuals at discrete time points, making exact times of transitions between disease states unknown. Such panel data pose considerable modeling challenges. Assuming the disease process progresses according a standard continuous-time Markov chain (CTMC) yields tractable likelihoods, but the assumption of exponential sojourn time distributions is typically unrealistic. More flexible semi-Markov models permit generic sojourn distributions yet yield intractable likelihoods for panel data in the presence of reversible transitions. One attractive alternative is to assume that the disease process is characterized by an underlying latent CTMC, with multiple latent states mapping to each disease state. These models retain analytic tractability due to the CTMC framework but allow for flexible, duration-dependent disease state sojourn distributions. We have developed a robust and efficient expectation-maximization (EM) algorithm in this context. Our complete data state space consists of the observed data and the underlying latent trajectory, yielding computationally efficient expectation and maximization steps. Our algorithm outperforms alternative methods measured in terms of time to convergence and robustness. We also examine the frequentist performance of latent CTMC point and interval estimates of disease process functionals based on simulated data. The performance of estimates depends on time, functional, and data-generating scenario. Finally, we illustrate the interpretive power of latent CTMC models for describing disease processes on a data-set of lung transplant patients. We hope our work will encourage wider use of these models in the biomedical setting
Imatinib ameliorates bronchiolitis obliterans via inhibition of fibrocyte migration and differentiation
Assessing the Causal Effect of Organ Transplantation on the Distribution of Residual Lifetime
Cytomegalovirus disease in lung transplantation: impact of recipient seropositivity and duration of antiviral prophylaxis
Survival after Bronchiolitis Obliterans Syndrome among Bilateral Lung Transplant Recipients
Rationale: Despite the importance of bronchiolitis obliterans syndrome (BOS) in lung transplantation, little is known regarding the factors that influence survival after the onset of this condition, particularly among bilateral transplant recipients
Spirometrically Significant Acute Rejection Increases the Risk for BOS and Death After Lung Transplantation
Quantitative chest CT for subtyping chronic lung allograft dysfunction and its association with survival
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