Markov Chain Monte Carlo simulation for projection of end stage renal disease patients in Greece

A Systematic Review of Kidney Transplantation Decision Modelling Studies

BACKGROUND

Genome-based precision medicine strategies promise to minimize premature graft loss after renal transplantation, through precision approaches to immune compatibility matching between kidney donors and recipients. The potential adoption of this technology calls for important changes to clinical management processes and allocation policy. Such potential policy change decisions may be supported by decision models from health economics, comparative effectiveness research and operations management.

OBJECTIVE

We used a systematic approach to identify and extract information about models published in the kidney transplantation literature and provide an overview of the status of our collective model-based knowledge about the kidney transplant process.

METHODS

Database searches were conducted in MEDLINE, Embase, Web of Science and other sources, for reviews and primary studies. We reviewed all English-language papers that presented a model that could be a tool to support decision making in kidney transplantation. Data were extracted on the clinical context and modelling methods used.

RESULTS

A total of 144 studies were included, most of which focused on a single component of the transplantation process, such as immunosuppressive therapy or donor-recipient matching and organ allocation policies. Pre- and post-transplant processes have rarely been modelled together.

CONCLUSION

A whole-disease modelling approach is preferred to inform precision medicine policy, given its potential upstream implementation in the treatment pathway. This requires consideration of pre- and post-transplant natural history, risk factors for allograft dysfunction and failure, and other post-transplant outcomes. Our call is for greater collaboration across disciplines and whole-disease modelling approaches to more accurately simulate complex policy decisions about the integration of precision medicine tools in kidney transplantation.

On the Use of Markov Models in Pharmacoeconomics: Pros and Cons and Implications for Policy Makers

We present an overview of the main methodological features and the goals of pharmacoeconomic models that are classified in three major categories: regression models, decision trees, and Markov models. In particular, we focus on Markov models and define a semi-Markov model on the cost utility of a vaccine for Dengue fever discussing the key components of the model and the interpretation of its results. Next, we identify some criticalities of the decision rule arising from a possible incorrect interpretation of the model outcomes. Specifically, we focus on the difference between median and mean ICER and on handling the willingness-to-pay thresholds. We also show that the life span of the model and an incorrect hypothesis specification can lead to very different outcomes. Finally, we analyse the limit of Markov model when a large number of states is considered and focus on the implementation of tools that can bypass the lack of memory condition of Markov models. We conclude that decision makers should interpret the results of these models with extreme caution before deciding to fund any health care policy and give some recommendations about the appropriate use of these models.

Projecting demands for renal replacement therapy in the Northern Territory: a stochastic Markov model

Objective The aim of the present study was to evaluate the potential effects of different health intervention strategies on demand for renal replacement therapy (RRT) services in the Northern Territory (NT). Methods A Markov chain simulation model was developed to estimate demand for haemodialysis (HD) and kidney transplantation (Tx) over the next 10 years, based on RRT registry data between 2002 and 2013. Four policy-relevant scenarios were evaluated: (1) increased Tx; (2) increased self-care dialysis; (3) reduced incidence of end-stage kidney disease (ESKD); and (4) reduced mortality. Results There were 957 new cases of ESKD during the study period, with most patients being Indigenous people (85%). The median age was 50 years at onset and 57 years at death, 12 and 13 years younger respectively than Australian medians. The prevalence of RRT increased 5.6% annually, 20% higher than the national rate (4.7%). If current trends continue (baseline scenario), the demand for facility-based HD (FHD) would approach 100000 treatments (95% confidence interval 75000-121000) in 2023, a 5% annual increase. Increasing Tx (0.3%), increasing self-care (5%) and reducing incidence (5%) each attenuate demand for FHD to ~70000 annually by 2023. Conclusions The present study demonstrates the effects of changing service patterns to increase Tx, self-care and prevention, all of which will substantially attenuate the growth in FHD requirements in the NT. What is known about the topic? The burden of ESKD is projected to increase in the NT, with demand for FHD doubling every 15 years. Little is known about the potential effect of changes in health policy and clinical practice on demand. What does this paper add? This study assessed the usefulness of a stochastic Markov model to evaluate the effects of potential policy changes on FHD demand. What are the implications for practitioners? The scenarios simulated by the stochastic Markov models suggest that changes in current ESKD management practices would have a large effect on future demand for FHD.

Is the Rise in the Prevalence of Renal Replacement Therapy at Older Ages the Price for Living Longer?

Background

Renal replacement therapy (RRT) is one of the most expensive in renal medicine. Cross-sectional studies suggest that life expectancy increases in the general population are associated with a higher burden of RRT. This study tests this hypothesis in a prospective setting among people aged 75+ living in Western Europe.

Methods

We gathered sex-specific data for 11 Western European countries in 2005-2014. RRT prevalence on country level was extracted from the ERA-EDTA registry, while data on population size and life expectancy for the 75+ age group came from the Eurostat database. GDP per capita was extracted from the OECD database. To measure the association between RRT prevalence and life expectancy, we performed Poisson regression models separately for each country and for all countries combined. To adjust for confounding, GDP per capita as well as time and country-fixed effects were included.

Results

Our analysis revealed that living longer coincides with rising RRT prevalence at ages 75+ in Western Europe between 2005 and 2014. On average, a 1-year increase in life expectancy was associated with a roughly 20% increase in RRT prevalence [(95% CI) 21-23% in men and 19-22% in women]. However, after adjustments for confounding were made, the association became insignificant among women and became weaker among men, falling to a level of 11% [(95% CI) 6-17%].

Conclusion

Living longer was not necessarily associated with a higher burden of RRT in Western European countries.

Maintenance Dialysis throughout the World in Years 1990 and 2010

Rapidly rising global rates of chronic diseases portend a consequent rise in ESRD. Despite this, kidney disease is not included in the list of noncommunicable diseases (NCDs) targeted by the United Nations for 25% reduction by year 2025. In an effort to accurately report the trajectory and pattern of global growth of maintenance dialysis, we present the change in prevalence and incidence from 1990 to 2010. Data were extracted from the Global Burden of Disease 2010 epidemiologic database. The results are on the basis of an analysis of data from worldwide national and regional renal disease registries and detailed systematic literature review for years 1980-2010. Incidence and prevalence estimates of provision of maintenance dialysis from this database were updated using a negative binomial Bayesian meta-regression tool for 187 countries. Results indicate substantial growth in utilization of maintenance dialysis in almost all world regions. Changes in population structure, changes in aging, and the worldwide increase in diabetes mellitus and hypertension explain a significant portion, but not all, of the increase because increased dialysis provision also accounts for a portion of the rise. These findings argue for the importance of inclusion of kidney disease among NCD targets for reducing premature death throughout the world.