The chronic kidney disease model: a general purpose model of disease progression and treatment.
Abstract
<h4>Background</h4>Chronic kidney disease (CKD) is the focus of recent national policy
efforts; however, decision makers must account for multiple therapeutic options, comorbidities
and complications. The objective of the Chronic Kidney Disease model is to provide
guidance to decision makers. We describe this model and give an example of how it
can inform clinical and policy decisions.<h4>Methods</h4>Monte Carlo simulation of
CKD natural history and treatment. Health states include myocardial infarction, stroke
with and without disability, congestive heart failure, CKD stages 1-5, bone disease,
dialysis, transplant and death. Each cycle is 1 month. Projections account for race,
age, gender, diabetes, proteinuria, hypertension, cardiac disease, and CKD stage.
Treatment strategies include hypertension control, diabetes control, use of HMG-CoA
reductase inhibitors, use of angiotensin converting enzyme inhibitors, nephrology
specialty care, CKD screening, and a combination of these. The model architecture
is flexible permitting updates as new data become available. The primary outcome is
quality adjusted life years (QALYs). Secondary outcomes include health state events
and CKD progression rate.<h4>Results</h4>The model was validated for GFR change/year
-3.0 ± 1.9 vs. -1.7 ± 3.4 (in the AASK trial), and annual myocardial infarction and
mortality rates 3.6 ± 0.9% and 1.6 ± 0.5% vs. 4.4% and 1.6% in the Go study. To illustrate
the model's utility we estimated lifetime impact of a hypothetical treatment for primary
prevention of vascular disease. As vascular risk declined, QALY improved but risk
of dialysis increased. At baseline, 20% and 60% reduction: QALYs = 17.6, 18.2, and
19.0 and dialysis = 7.7%, 8.1%, and 10.4%, respectively.<h4>Conclusions</h4>The CKD
Model is a valid, general purpose model intended as a resource to inform clinical
and policy decisions improving CKD care. Its value as a tool is illustrated in our
example which projects a relationship between decreasing cardiac disease and increasing
ESRD.
Type
Journal articleSubject
HumansDisease Progression
Monte Carlo Method
Risk Factors
Comorbidity
Quality-Adjusted Life Years
Models, Theoretical
Renal Insufficiency, Chronic
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https://hdl.handle.net/10161/22838Published Version (Please cite this version)
10.1186/1472-6947-11-41Publication Info
Orlando, Lori A; Belasco, Eric J; Patel, Uptal D; & Matchar, David B (2011). The chronic kidney disease model: a general purpose model of disease progression and
treatment. BMC medical informatics and decision making, 11(1). pp. 41. 10.1186/1472-6947-11-41. Retrieved from https://hdl.handle.net/10161/22838.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
David Bruce Matchar
Professor of Medicine
My research relates to clinical practice improvement - from the development of clinical
policies to their implementation in real world clinical settings. Most recently my
major content focus has been cerebrovascular disease. Other major clinical areas in
which I work include the range of disabling neurological conditions, cardiovascular
disease, and cancer prevention. Notable features of my work are: (1) reliance on
analytic strategies such as meta-analysis, simulation, decision analy
Lori Ann Orlando
Professor of Medicine
Dr. Lori A. Orlando, MD MHS MMCI is a Professor of Medicine and Director of the Precision
Medicine Program in the Center for Applied Genomics and Precision Medicine at Duke
University. She attended Tulane Medical Center for both medical school (1994-1998)
and Internal Medicine residency (1998-2000). There she finished AOA and received a
number of awards for teaching and clinical care from the medical school and the residency
programs, including the Musser-Burch-Puschett award in 2000 for acad
Uptal Dinesh Patel
Adjunct Professor in the Department of Medicine
Uptal Patel, MD is an Adjunct Professor interested in population health with a broad
range of clinical and research experience. As an adult and pediatric nephrologist
with training in health services and epidemiology, his work seeks to improve population
health for patients with kidney diseases through improvements in prevention, diagnosis
and treatment. Prior efforts focused on four inter-related areas that are essential
to improving kidney health: i) reducing the progressi
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