A Health Policy Model of CKD: 1. Model Construction, Assumptions, and Validation of Health Consequences
A cost-effectiveness model that accurately represents disease progression, outcomes, and associated costs is necessary to evaluate the cost-effectiveness of interventions for chronic kidney disease (CKD).
We developed a microsimulation model of the incidence, progression, and treatment of CKD. The model was validated by comparing its predictions with survey and epidemiologic data sources.
US patients. MODEL, PERSPECTIVE, & TIMEFRAME: The model follows up disease progression in a cohort of simulated patients aged 30 until age 90 years or death. The model consists of 7 mutually exclusive states representing no CKD, 5 stages of CKD, and death. Progression through the stages is governed by a person's glomerular filtration rate and albuminuria status. Diabetes, hypertension, and other risk factors influence CKD and the development of CKD complications in the model. Costs are evaluated from the health care system perspective.
Usual care, including incidental screening for persons with diabetes or hypertension.
Progression to CKD stages, complications, and mortality.
The model provides reasonably accurate estimates of CKD prevalence by stage. The model predicts that 47.1% of 30-year-olds will develop CKD during their lifetime, with 1.7%, 6.9%, 27.3%, 6.9%, and 4.4% ending at stages 1-5, respectively. Approximately 11% of persons who reach stage 3 will eventually progress to stage 5. The model also predicts that 3.7% of persons will develop end-stage renal disease compared with an estimate of 3.0% based on current end-stage renal disease lifetime incidence.
The model synthesizes data from multiple sources rather than a single source and relies on explicit assumptions about progression. The model does not include acute kidney failure.
The model is well validated and can be used to evaluate the cost-effectiveness of CKD interventions. The model also can be updated as better data for CKD progression become available.
Available from: link.springer.com
- "In addition there were four health states of low GFR chronic kidney disease (CKD: CKD and diabetes mellitus with and without proteinuria and CKD and non-diabetes mellitus with and without proteinuria) and one state of ESRD. Different stages of low GFR CKD were not used but rather a composite state which included stage 3 and 4. Hazard risks for mortality and kidney disease progression were taken from the literature [see Additional file 1: Tables S1 and S2, [6-11]]. Mortality in the general and ESRD population were taken from published vital statistics and the US Renal Data System (USRDS), respectively [12,13]. "
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ABSTRACT: Long term studies of live kidney donation do not show evidence of appreciable risks to the donor. However nephrectomy reduces total glomerular filtration rates (GFR) and is associated with increased rates of proteinuria and possibly hypertension. It is not clear to what extent these changes are associated with reduced life expectancy (LE) or increased risk of end stage renal disease (ESRD) since follow up is incomplete in most reports.
In a computer simulation model based on a US population chronic kidney disease model, increased hazard rates for higher blood pressure, proteinuria and low GFR were applied to healthy individuals undergoing donor nephrectomy. Subsequent LE and cumulative risk of ESRD were calculated.
Kidney donation is projected to reduce LE by 0.83 years and increase the absolute cumulative risk of ESRD by 0.89% for a 40-year-old white male. White females were predicted to have slightly greater loss of life and less added ESRD risk. Conversely, Blacks have greater risks of ESRD after donation. Older donors with hypertension were predicted to lose less life years and lower cumulative ESRD risks than young donors. Despite these increased risks most donors will have better life expectancy and lower ESRD rates than the general population since they are a highly selected cohort.
This study attempts to quantify increases in death and ESRD from donor nephrectomy assuming the risk factors of hypertension, low GFR and proteinuria have the same significance in this population as in the general population. Further study is required to better estimate the risks of donation and test whether these assumptions are valid.
02/2013; 2(1):2. DOI:10.1186/2047-1440-2-2
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ABSTRACT: Microalbuminuria screening may detect chronic kidney disease in its early stages, allowing for treatment that delays or prevents disease progression. The cost-effectiveness of microalbuminuria screening has not been determined.
A cost-effectiveness model simulating disease progression and costs.
US patients. MODEL, PERSPECTIVE, AND TIMEFRAME: The microsimulation model follows up disease progression and costs in a cohort of simulated patients from age 50 to 90 years or death. Costs are evaluated from the health care system perspective.
Microalbuminuria screening at 1-, 2-, 5-, or 10-year intervals followed by treatment with angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers. We considered universal screening, as well as screening targeted at persons with diabetes, persons with hypertension but no diabetes, and persons with neither diabetes nor hypertension.
Costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios.
For the full model population, universal screening increases costs and increases QALYs. Universal annual screening starting at age 50 years has a cost-effectiveness ratio of $73,000/QALY relative to no screening and $145,000/QALY relative to usual care. Cost-effectiveness ratios improved with longer screening intervals. Relative to no screening, targeted annual screening has cost-effectiveness ratios of $21,000/QALY, $55,000/QALY, and $155,000/QALY for persons with diabetes, those with hypertension, and those with neither current diabetes nor current hypertension, respectively.
Results necessarily are based on a microsimulation model because of the long time horizon appropriate for chronic kidney disease. The model includes only health care costs.
Microalbuminuria screening is cost-effective for patients with diabetes or hypertension, but is not cost-effective for patients with neither diabetes nor hypertension unless screening is conducted at longer intervals or as part of existing physician visits.
American Journal of Kidney Diseases 03/2010; 55(3):463-73. DOI:10.1053/j.ajkd.2009.11.017 · 5.90 Impact Factor
Available from: Meda E Pavkov
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ABSTRACT: Chronic kidney disease (CKD) is a significant public health problem in the United States. However, data from the United States Renal Data System and other sources suggest that care for people with CKD does not meet recommended standards. The Federal government has developed the infrastructure to promote population-based interventions which have reduced the burden of other chronic illnesses. An effective, coordinated response by Federal health agencies to the public health challenge of CKD could have a significant effect on the morbidity, mortality, and costs associated with CKD. In recent years, initiatives undertaken by three Federal agencies have made important advances in coordinating efforts. The Centers for Disease Control and Prevention has begun to develop public health infrastructure for monitoring the burden of CKD. The Centers for Medicare and Medicaid Services has, through the successful Fistula First Breakthrough Initiative (FFBI) and inclusion of CKD in the scope of work of Quality Improvement Organizations, promoted earlier diagnosis and treatment of CKD. The National Institute of Diabetes and Digestive and Kidney Diseases, through its National Kidney Disease Education Program, has reinvigorated and expanded the Kidney Interagency Coordinating Committee so that it is a robust vehicle to share information about activities, identify and disseminate promising practices and tools, and foster cross-agency collaboration. Collaboration among Federal health agencies has the potential to enhance efforts to reduce the burden of CKD.
Advances in chronic kidney disease 05/2010; 17(3):282-8. DOI:10.1053/j.ackd.2010.03.006 · 2.05 Impact Factor
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