Microalbuminuria Screening for Detecting Chronic Kidney Disease in the General Population: A Systematic Review

Figures & data

Figure 1.  Summary of trial identification and selection.

Table 1. Characteristics of articles included in the systematic review.

Study	Year	Design	Evaluation type	Country and race	Population	Participant number	Mean age (years)	Sex (female)	Follow-up (months)	Note
Hoy et al.^14	2003	Controlled study	Screening program	Australian Aborigines, Australia	Screen general population. Treat HTN, DM, albuminuric subjects	267	43.4	53%	40.7
Gansevoort et al.^16	2005	Cross-sectional	Screening program	Caucasian (95.4%), The Netherlands	General population (28–75 years)	2527	48.8	52.9%	—	PREVENDstudy
Atthobari et al.^13	2006	RCT, double-blind, placebo-controlled	CEA, use of Euros/LYG	Caucasian (95%), The Netherlands	Screen general population (28–75 years). Treat microalbuminuric subjects	864	51	35%	46	PREVEND study
Jafar et al.^17	2007	Cross-sectional	Screening program	Indo-Asian, Pakistan	General population (>40 years)	577	51.8	54.4%	—
Hoerger et al.^18	2010	Cost-effectiveness model simulation	CEA, use ofUS$/QALY	USA	General population (50–90 years)	—	—	—	—
van der Velde et al.^15	2010	Cohort study	Screening program	Caucasian (95%), The Netherlands	General population (28–75 years)	3398	49	55%	84	PREVEND study

Note: RCT, randomized controlled trial; CEA, cost-effectiveness analysis; DM, diabetes mellitus; HTN, hypertension; LYG, life-year gained; QALY, quality-adjusted life-years; PREVEND study, Prevention of Renal and Vascular Endstage Disease study.

Table 2.  Intervention and outcomes of articles included in the systematic review.

Study	Year	Intervention	Main outcomes	Sensitivity and specificity	Comments	Note
Hoy et al.^14	2003	ACR. Perindopril (n = 267) vs. historical matched controls (n = 327)	Treatment group showed 50%reduction in deaths and 57% reduction in renal failure.		Screening ACR in the high riskpopulation may be cost-effective.
Gansevoort et al.^16	2005	UAC, ACR.	UAC was comparable to ACR, diagnostic performance was satisfactory in both exams.	UAC: AUC 0.92, DV 11.2 mg/L,Sen 85%, Spe 85%.	To keep the cost lower,screening UAC in the generalpopulation is suggested.	PREVEND study
				ACR: AUC 0.93, DV 9.9 mg/g,Sen 88%, Spe 88%.
Atthobari et al.^13	2006	UAC. Fosinopril 20 mg + pravastatin 40 mg (n = 431)vs. placebo (n = 433), 2 × 2 factorial	Lower CV events in fosinoprilgroup.The cost-effectiveness of screening was 16,700 Euros/LYG.		Screening UAC in the general population and treat high-risk subjects with fosinopril maybe cost-effective.	PREVEND study
Jafar et al.^17	2007	UAC, ACR.	Both UAC and ACR were acceptable for population screening, but Sen was suboptimal (especially female).	Female	Lowering the existingthresholds of UAC or ACR is suggested.
				UAC: AUC 0.86, DV 0.5 mg/dL,Sen 87%, Spe 75%.
				ACR: AUC 0.86, DV 9.3 mg/g,Sen 74%, Spe 81%.
				Male
				UAC: AUC 0.88, DV 1.7 mg/dL,Sen 74%, Spe 94%.
				ACR: AUC 0.90, DV 6.7 mg/g,Sen 90%, Spe 77%.
Hoerger et al.^18	2010	ACR.	Universal annual screening had a cost-effectiveness ratio of 73,000 US$/QALY relative to no screening.	Model parameterACR: Sen 73%, Spe 96%.	Screening ACR is cost-effective for DM or HTN population,but not for the generalpopulation.
van der Velde et al.^15	2010	UAC (>10 or >20 mg/dL) vs. high CV risk vs. high CV risk + age >55 years	Only UAC prescreening approaches detected CKD patients with accelerated renal function loss and increased CV risk.	UAC >10 mg/dL: Sen 40%, Spe 96%.	UAC is the most efficientscreening method comparedto risk factor screening inthe general population.	PREVEND study
				UAC >20 mg/dL: Sen 58%, Spe 81%.
				High CV risk: Sen 28%, Spe 90%.
				High CV risk + age >55 years: Sen 65%, Spe 71%.

Note: ACR, urine albumin creatinine ratio; AUC, area under the curve; DV, discriminator value; DM, diabetes mellitus; CKD, chronic kidney disease; CV, cardiovascular; HTN, hypertension; Sen, sensitivity; Spe, specificity; UAC, urine albumin concentration; PREVEND study, Prevention of Renal and Vascular Endstage Disease study.

Table 3.  Quality assessment of articles reporting methodological quality of test accuracy.

The QUADAS tool		Hoy et al.(2003)^14	Gansevoort et al. (2005)^16	Jafar et al. (2007)^17	van der Velde et al. (2010)^15
1.	Was the spectrum of patients representative of the patients who will receive the test in practice?	Yes	Yes	Yes	Yes
2.	Were selection criteria clearly described?	Yes	Yes	Yes	Yes
3.	Is the reference standard likely to correctly classify the target condition?	Yes	Yes	Yes	Yes
4.	Is the time period between reference standard and index test short enough to be reasonably sure that the target condition did not change between the two tests?	Yes	Unclear	Yes	Unclear
5.	Did the whole sample or a random selection of the sample receive verification using a reference standard of diagnosis?	Yes	Yes	Yes	Yes
6.	Did patients receive the same reference standard regardless of the index test result?	Yes	Yes	Yes	Yes
7.	Was the reference standard independent of the index test (i.e., the index test did not form part of the reference standard)?	Yes	Yes	Yes	Yes
8.	Was the execution of the index test described in sufficient detail to permit replication of the test?	Yes	Yes	Yes	Yes
9.	Was the execution of the reference standard described in sufficient detail to permit its replication?	Yes	Yes	Yes	Yes
10.	Were the index test results interpreted without knowledge of the results of the reference standard?	Unclear	Yes	Unclear	Yes
11.	Were the reference standard results interpreted without knowledge of the results of the index test?	Unclear	Unclear	Unclear	Unclear
12.	Were the same clinical data available when test results were interpreted as would be available when the test is used in practice?	Unclear	Unclear	Unclear	Unclear
13.	Were uninterpretable/intermediate test results reported?	No	No	No	No
14.	Were withdrawals from the study explained?	No	No	No	No

Note: QUADAS, Quality Assessment of Diagnostic Accuracy Studies.

Table 4.  Quality assessment of articles reporting the elements of economic evaluation.

Drummond’s checklist	Atthobari et al. (2006)^13	Hoerger et al. (2010)^18
1. Was a well-defined question posed in answerable form?	Yes	Yes
2. Was a comprehensive description of the competing alternatives given?	Yes	Yes
3. Was the effectiveness of the program or services established?	Yes—double-blind RCT	Unsure—model simulation
4. Were all the important and relevant costs and consequences for each alternative identified?	Yes	Yes
5. Were costs and consequences measured accurately in appropriate physical units?	Yes	Yes
6. Were the cost and consequences valued credibly?	Yes	Yes
7. Were costs and consequences adjusted for differential timing?	Yes	Yes
8. Was an incremental analysis of costs and consequences of alternatives performed?	Yes—use of Euros/LYG	Yes—use of US$/QALY
9. Was allowance made for uncertainty in the estimates of costs and consequences?	Yes—1-way SA	Yes—1-way SA
10. Did the presentation and discussion of study results include all issues of concern to users?	Yes	Yes

Note: RCT, randomized controlled trial; LYG, life-year gained; SA, sensitivity analyses; QALY, quality-adjusted life-years.

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Atthobari J, Asselbergs FW, Boersma C, . Cost-effectiveness of screening for albuminuria with subsequent fosinopril treatment to prevent cardiovascular events: A pharmaco economic analysis linked to the prevention of renal and vascular endstage disease (PREVEND) study and the prevention of renal and vascular endstage disease intervention trial (PREVEND IT). Clin Ther. 2006;28:432–444.

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van der Velde M, de Jong PE, Gansevoort RT. Comparison of the yield of different screening approaches to detect chronic kidney disease. Nephrol Dial Transplant. 2010;25:3222–3230.

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