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.
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 cost-effectiveness 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 microalbuminuria involved prescreening for UAC >or=20 mg/L, followed by a confirmation test for UAE >or=30 mg/d. Other options based on combinations of albuminuria for UAC prescreening (no prescreening, and >or=10, >or=20, >or=100, and >or=200 mg/L) and UAE confirmation test (>or=15, >or=30, and >or=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 >or=50 years, and aged >or=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 euro926 (euro2003 vs euro1077), and prevention of CV deaths was estimated to gain 0.0421 discounted life-year per person. Correspondingly, the cost-effectiveness was estimated at euro22,000 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-effectiveness threshold of euro20,000, euro50,000, and euro80,000 per life-year gained, respectively. Higher albuminuria thresholds for screening and start of treatment further improved the cost-effectiveness but reduced the overall health gains achieved. Limiting screening to those subjects aged >or=50 and >or=60 years resulted in more favorable cost-effectiveness compared with population-based screening without age restriction.


CONCLUSIONS
Our analyses suggest the potentially favorable cost-effectiveness of population-based screening for albuminuria in the general Dutch population. The results offer health care decision-makers new tools for considering actual implementation of such screening.
Boersma
Cornelis
C
Unit of PharmacoEpidemiology & PharmacoEconomics, Department of Pharmacy, University of Groningen, Groningen, the Netherlands. c.boersma@rug.nl
Gansevoort
Ron T
RT
Pechlivanoglou
Petros
P
Visser
Sipke T
ST
van Toly
Flip F J
FF
de Jong-van den Berg
Lolkje T W
LT
de Jong
Paul E
PE
Postma
Maarten J
MJ
D000328:Adult; D000367:Age Factors; D000368:Aged; D000419:Albuminuria / Q000175:diagnosis* / Q000191:economics*; D015415:Biomarkers / Q000032:analysis; D002317:Cardiovascular Agents / Q000191:economics / Q000627:therapeutic use; D002318:Cardiovascular Diseases / Q000191:economics* / Q000517:prevention & control*; D015331:Cohort Studies; D003362:Cost-Benefit Analysis; D042241:Early Diagnosis; D005260:Female; D006801:Humans; D007674:Kidney Diseases / Q000191:economics* / Q000517:prevention & control*; D008297:Male; D008390:Markov Chains; D008403:Mass Screening / Q000191:economics; D008875:Middle Aged; D009426:Netherlands
D015415:Biomarkers; D002317:Cardiovascular Agents