Background Changes in the epidemiology of end stage liver disease may lead to increased risk of dropout from the liver transplant waitlist. Anticipating the future of liver transplant waitlist characteristics is vital when considering organ allocation policy. Methods We performed a discrete event simulation to forecast patient characteristics and rate of waitlist dropout. Estimates were simulated from 2015–2025. The model was informed by data from the Organ Procurement and Transplant Network, 2003–2014. National data are estimated along with forecasts for 2 regions. Results NASH will increase from 18% of waitlist additions to 22% by 2025. Hepatitis C will fall from 30% to 21%. Listings over age 60 will increase from 36% to 48%. The hazard of dropout will increase from 41% to 46% nationally. Wait times for transplant for patients listed with a MELD between 22 and 27 will double. Region 5, which transplants at relatively higher MELD scores, will experience an increase from 53% to 64% waitlist dropout. Region 11, which transplants at lower MELD scores, will have an increase in waitlist dropout from 30% to 44%. Conclusions The liver transplant waitlist size will remain static over the next decade due to patient dropout. Liver transplant candidates will be older, more likely to have NASH and will wait for transplantation longer even when listed at a competitive MELD score. There will continue to be significant heterogeneity among transplant regions where some patients will be more likely to drop out of the waitlist than receive a transplant.

BackgroundThe tobacco epidemic in the U.S. has matured in the past decade. However, due to rapidly changing social policy and commercial environments, tailored prevention and interventions are needed to support further reduction in smoking.MethodsUsing Tobacco Use Supplement to the Current Population Survey (TUS-CPS) 2002–2003 and 2010–2011 longitudinal cohorts, five smoking states are defined including daily-heavy, daily-light, non-daily, former and non-smoker. We quantified the changes between smoking states for the two longitudinal cohorts, and used a series of multivariable logistic regression models to examine the association of socio-demographic attributes and initial smoking states on smoking initiation, cessation, and relapse between waves within each cohort.ResultsThe prevalence of adult heavy smoking decreased from 9.9% (95% CI: 9.6%, 10.2%) in 2002 to 7.1% (95% CI: 6.9%, 7.4%) in 2010. Non-daily smokers were less likely to quit in the 2010–2011 cohort than the 2002–2003 cohort (37.0% vs. 44.9%). Gender, age group, smoker type, race and marital status exhibit similar patterns in terms of their association to the odds of initiation, cessation and relapse between the two cohorts, while education groups showed some inconsistent results between the two cohorts regarding the odds of cessation.ConclusionsTransitions between smoking states are complex and increasingly unstable, requiring a holistic, population-based perspective to understand the stocks and flows that ultimately dictate the public health impact of cigarette smoking behavior. This knowledge helps to identify groups in need of increased tobacco control prevention and intervention efforts.

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