Screen-and-treat strategies for albuminuria to prevent cardiovascular and renal disease: Cost-effectiveness of nationwide and targeted interventions based on analysis of cohort data from the Netherlands

• Published in: Clinical therapeutics 2010-06, Vol.32 (6), p.1103-1121
• Main Authors: Boersma, Cornelis, PhD, Gansevoort, Ron T., MD, PhD, Pechlivanoglou, Petros, MSc, Visser, Sipke T., MSc, van Toly, Flip F.J., MSc, de Jong-van den Berg, Lolkje T.W., PhD, de Jong, Paul E., MD, PhD, Postma, Maarten J., PhD
• Format: Article
• Language: English
• Subjects: Adult; Age Factors; Aged; Albuminuria - diagnosis; Albuminuria - economics; Biological and medical sciences; Biomarkers - analysis; Cardiovascular Agents - economics; Cardiovascular Agents - therapeutic use; Cardiovascular disease; Cardiovascular Diseases - economics; Cardiovascular Diseases - prevention & control; Chronic illnesses; Cohort Studies; Cost analysis; Cost-Benefit Analysis; cost-effectiveness; Diabetes; Disease prevention; Early Diagnosis; Epidemiology; Expected values; Female; Humans; Hypertension; Internal Medicine; Kidney diseases; Kidney Diseases - economics; Kidney Diseases - prevention & control; Male; Markov Chains; Mass Screening - economics; Medical Education; Medical sciences; microalbuminuria; Middle Aged; Mortality; Nephrology; Nephrology. Urinary tract diseases; Netherlands; Pharmacoeconomics; Pharmacology. Drug treatments; Pharmacy; Public health; renal disease; Risk factors; screening; Urinary system involvement in other diseases. Miscellaneous; Urinary tract. Prostate gland
• ISSN: 0149-2918; 1879-114X
• DOI: 10.1016/j.clinthera.2010.06.013

Abstract Background: Albuminuria is a marker for renal and cardiovascular (CV) risk, allowing early diagnosis of subjects with elevated renal and CV risk. Objective: This study aimed to estimate the costeffectiveness and budget impact of various population-based screen-and-treat scenarios for elevated albuminuria levels (ie, microalbuminuria) in the Netherlands. Methods: A multistate transition Markov model was developed to simulate the natural course of albuminuria-based disease progression to dialysis and occurrence of CV events. Several population-based strategies directed at screening for elevated albuminuria were evaluated. These strategies depended on urinary albumin concentration (UAC), urinary albumin excretion (UAE), and age. Transition probabilities were derived from the observational community-based Prevention of Renal and Vascular End Stage Disease (PREVEND) cohort study. Health care costs (in year-2008 euros) and life-years gained were calculated over an 8-year period. In the base-case analysis, we analyzed screening for and treatment of microalbuminuria. Screening for microal-buminuria involved prescreening for UAC ≥20 mg/L, followed by a confirmation test for UAE ≥30 mg/d. Other options based on combinations of albuminuria for UAC prescreening (no prescreening, and ≥10, ≥20, ≥100, and ≥200 mg/L) and UAE confirmation test (≥15, ≥30, and ≥300 mg/d) for treatment were investigated in scenario analyses. Furthermore, these various strategies based on UAC and UAE values were analyzed in different subgroups based on age (all ages, aged ≥50 years, and aged ≥60 years). Results: The PREVEND study included 8592 Dutch residents aged 28 to 75 years at the time of initial screening. Among a hypothetical cohort of 1000 subjects identified and treated in the base-case analysis, it was estimated (based on PREVEND follow-up data) that, in the screening/treatment and no-screening scenarios, 76 versus 124 CV events occurred, 16 versus 27 CV deaths, and 3 versus 5 dialysis cases, respectively. The per-person difference in net costs for screening was calculated at €926 (€2003 vs €1077), and prevention of CV deaths was estimated to gain 0.0421 discounted life-year per person. Correspondingly, the cost-effectiveness was estimated at €22,000 per life-year gained. In the base-case analysis, probabilistic sensitivity analysis indicated that the likelihood of cost-effectiveness of a screen-and-treat strategy was 54%, 90%, and 95% for a maximum acceptable cost-effective