title: Optimal strategies for identifying kidney disease in diabetes: properties of screening tests, progression of renal dysfunction and impact of treatment - systematic review and modelling of progression and cost-effectiveness.
abstract: BACKGROUND
  Annual screening for adults with type 2 diabetes to detect the early onset of kidney disease is widely recommended, but the recommendations are based on a limited methodological approach. In addition, there are continuing uncertainties about underlying rates of progression of the condition and the benefits of treatments with angiotensin-converting enzyme inhibitors and angiotensin receptor blockers.
  
  
  OBJECTIVE
  We aimed to estimate the clinical value and cost-effectiveness of different screening intervals to diagnose early diabetic kidney disease.
  
  
  METHODS
  We used the following databases for the literature review (searched January 2005 to August 2010): MEDLINE, EMBASE and the Cochrane Database of Systematic Reviews. Individual patient data were obtained from the Oxford Regional Prospective Diabetes Study and the Collaborative Atorvastatin Diabetes Study.
  
  
  METHODS
  Data from systematically identified randomised trials reporting the impact on renal outcomes of angiotensin-converting enzyme inhibitors and angiotensin 2 receptor blockers for type 1 and type 2 diabetes patients with normoalbuminuria and microalbuminuria were pooled to derive estimates of effect. Individual patient data for type 1 and type 2 diabetes patients were used to obtain parameters describing progression and variability of measurement over time for the albumin-to-creatinine ratio (ACR) and estimated glomerular filtration rate. Based on accepted diagnostic thresholds, we modelled whether these tests accurately identified patients who were developing early diabetic kidney disease and required intensification of treatment. Cost-effectiveness analyses were carried out using simulation outcome models to estimate the incremental costs per quality-adjusted life-year (QALY) for different screening intervals.
  
  
  RESULTS
  In total, 49 trials (n = 34,082 patients) were eligible for inclusion in the systematic review. For type 1 diabetes, pooled estimates of urinary albumin excretion (UAE) for treated patients with microalbuminuria were on average 67% [95% confidence interval (CI) 54% to 77%] lower at the end of the trial than for untreated patients. There was no significant treatment effect for patients with normoalbuminuria (p interaction = 0.006). For treated patients with type 2 diabetes and normoalbuminuria or microalbuminuria, UAE was lower by, on average, 21% (95% CI 97% to 32%) or 27% (95% CI 15% to 38%), respectively. The proportion (95% CI) of men and women with type 1 diabetes screened annually for microalbuminuria over 6 years and inaccurately identified as having microalbuminuria would be 48% (43% to 53%) and 55% (48% to 61%), respectively. The corresponding proportions for type 2 diabetes are 36% (32% to 42%) and 48% (41% to 55%). Decreasing the screening interval to 3-yearly would reduce this for men with type 1 diabetes to 38% (33% to 44%), with an increase in those not identified over 6 years from 1.5% (95% CI 1% to 2%) to 4% (95% CI 3% to 5%). For type 1 diabetes, incremental cost per QALY [standard deviation (SD)] of a 5-yearly compared with a 4-yearly screening interval was £3612 (£6586), increasing to £9601 (£34,112) for annual compared with 2-yearly screening. The probability that the intervention is cost saving is around 25%, and it has around an 80% chance of being below a cost-effectiveness threshold of £30,000. For type 2 diabetes, incremental cost per QALY (SD) of a yearly compared with a 2-yearly screening interval was £606 (£1782). The intervention is almost certainly below a cost-effectiveness threshold of £5000.
  
  
  CONCLUSIONS
  These results support current UK guidance, which recommends annual screening with ACR to identify early kidney disease in patients with diabetes, despite a high false-positive rate leading to, at worst, unnecessary or, at best, early therapeutic intervention. For type 1 diabetes, screening costs for annual compared with 2-yearly screening are well within the bounds of accepted cost-effectiveness. Annual screening is even more cost-effective in type 2 diabetes than in type 1 diabetes. Identification of alternative markers for developing diabetic nephropathy may improve targeting of treatment for those at high risk.
  
  
  BACKGROUND
  The National Institute for Health Research Health Technology Assessment programme.
authors.affiliation: Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Farmer
authors.affiliation: Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
authors.forename: Richard
authors.initials: R
authors.lastname: Stevens
authors.affiliation: Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
authors.forename: Jennifer
authors.initials: J
authors.lastname: Hirst
authors.affiliation: Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia.
authors.forename: Tom
authors.initials: T
authors.lastname: Lung
authors.affiliation: Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
authors.forename: Jason
authors.initials: J
authors.lastname: Oke
authors.affiliation: Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia.
authors.forename: Philip
authors.initials: P
authors.lastname: Clarke
authors.affiliation: Centre for Research in Evidence-Based Practice, Bond University, Gold Coast, QLD, Australia.
authors.forename: Paul
authors.initials: P
authors.lastname: Glasziou
authors.affiliation: Wolfson College, University of Oxford, Oxford, UK.
authors.forename: Andrew
authors.initials: A
authors.lastname: Neil
authors.affiliation: Department of Paediatrics, University of Cambridge, Cambridge, UK.
authors.forename: David
authors.initials: D
authors.lastname: Dunger
authors.affiliation: Population Health Sciences, University of Dundee, Dundee, UK.
authors.forename: Helen
authors.initials: H
authors.lastname: M Colhoun
authors.affiliation: Nuffield Department of Medicine, University of Oxford, Oxford, UK.
authors.forename: Christopher
authors.initials: C
authors.lastname: Pugh
authors.affiliation: School of Public Health, University of Sydney, Sydney, NSW, Australia.
authors.forename: Germain
authors.initials: G
authors.lastname: Wong
authors.affiliation: Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
authors.forename: Rafael
authors.initials: R
authors.lastname: Perera
authors.affiliation: Department of Clinical Biochemistry, Oxford University Hospitals Trust, Oxford, UK.
authors.forename: Brian
authors.initials: B
authors.lastname: Shine
mesh_terms: D000368:Aged; D057911:Angiotensin Receptor Antagonists / Q000627:therapeutic use; D000806:Angiotensin-Converting Enzyme Inhibitors / Q000627:therapeutic use; D003362:Cost-Benefit Analysis; D003922:Diabetes Mellitus, Type 1 / Q000150:complications*; D003924:Diabetes Mellitus, Type 2 / Q000150:complications*; D003928:Diabetic Nephropathies / Q000175:diagnosis* / Q000188:drug therapy; D003955:Diagnostic Tests, Routine / Q000191:economics*; D018450:Disease Progression; D005260:Female; D006801:Humans; D007677:Kidney Function Tests; D008297:Male; D017063:Outcome Assessment, Health Care; D012307:Risk Factors
chemical_list: D057911:Angiotensin Receptor Antagonists; D000806:Angiotensin-Converting Enzyme Inhibitors