La gestione del paziente diabetico: bisogni, percorsi e strumenti Metodi per lo studio della nefropatia Giuseppe Penno Dipartimento di Medicina Clinica e Sperimentale Azienda Ospedaliera Universitaria di Pisa Pisa, OTTOBRE 2013

1.Classification of chronic kidney disease (CKD) by albuminuria and eGFR Classification of chronic kidney disease (CKD) by albuminuria and eGFRClassification of chronic kidney disease (CKD) by albuminuria and eGFR Key points

Levey AS et al, Kidney Int 80: 17-28, 2011 KDIGO: Classification of Kidney Disease by albuminuria and Association with Adverse Outcomes

Levey AS et al, Kidney Int 80: 17-28, 2011 KDIGO: Classification of Kidney Disease by eGFR and Association with Adverse Outcomes

Levey AS et al, Ann Intern Med 139: , 2003 National Kidney Foundation’s (NKF’s) Kidney Disease Outcomes Quality Initiative (KDOQI) classification Stage 0 - No CKD Stage 1 CKD Stage 2 CKD Stage 3 CKD Stage 4 CKD Stage 5 CKD MDRD

Tonelli M et al, Ann Intern Med 154: 12-21, 2011 MDRD Alberta Kidney Disease Network classification Risk category 0 Risk category 1 Risk category 2 Risk category 3 Risk category 4

Tonelli M et al, Ann Intern Med 154: 12-21, 2011 Alberta Kidney Disease Network classification

1.This risk classification system identifies fewer patients as having advanced CKD than the NFK staging system This risk classification system identifies fewer patients as having advanced CKD than the NFK staging systemThis risk classification system identifies fewer patients as having advanced CKD than the NFK staging system 2.This system could reduce unnecessary referral for care, at the cost of not referring or delaying referral for some patients who go on to develop ESRD or dieThis system could reduce unnecessary referral for care, at the cost of not referring or delaying referral for some patients who go on to develop ESRD or die Take home

KDIGO, Kidney Int Suppl 3: 1-150, 2013 CKD- EPI Kidney Disease: Improving Global Outcomes (KDIGO) classification Low risk Moderate risk High risk Very high risk

KDIGO, Kidney Int Suppl 3: 1-150, 2013 Kidney Disease: Improving Global Outcomes (KDIGO) classification Low risk Moderate risk High risk Very high risk

KDIGO, Kidney Int Suppl 3: 1-150, 2013 Kidney Disease: Improving Global Outcomes (KDIGO) classification Low risk Moderate risk High risk Very high risk

1.Classification of chronic kidney disease (CKD) by eGFR and albuminuria Classification of chronic kidney disease (CKD) by eGFR and albuminuriaClassification of chronic kidney disease (CKD) by eGFR and albuminuria 2.Renal impairment is common. Every second/third patient in our clinic might have signs of renal impairmentRenal impairment is common. Every second/third patient in our clinic might have signs of renal impairment Key points

Stages of “Diabetic nephropathy” Normo73,1% Micro22,2% Macro4,7% eGFR strata (ml/min/1.73 m 2 ) ≥9029,6% ,7% ,1% <301,7% NKF’s KDOQI CKD stages No CKD 62,5% Stage 1 ≥90 * 6,7% Stage * 12,0% Stage ,1% Stages 4, 5 <30 1,7% * Plus “kidney damage” MDRD The RIACE (Renal Insufficiency and Cardiovascular Events) study 15,773 patients with type 2 diabetes from Italy Penno G et al. J Hypertens 29: , 2011

62.5% 12.0% 6.7% 17.1% 1.7% No CKD CKD stage 1 CKD stage 2 CKD stage 3 CKD stages 4/5 Approximately 40% of patients with T2DM show signs of CKD (stages 1-5) Approximately 20% of patients with T2DM show signs of renal failure (eGFR <60 ml/min/1.73 m 2 ) Renal dysfunction is common in patients with T2DM The RIACE Study: 15,773 patients with T2DM Penno G et al. J Hypertens 29: , 2011

Severe (macro) Mild (micro) Normal eGFR ml/min/ 1.73 m 2 MDRD >90 Albuminuria Stage 2 Stage 1Stage 0 (no CKD) 62.5% Stage 3 Stage 4 Stage 1-2 albuminuric phenotype 18.7% Stages 3/5 albuminuric CKD phenotype 8.2% Stage 3/5 NON albuminuric CKD phenotype 10.6% Penno G et al. J Hypertens 29: , 2011 Renal dysfunction is common in patients with T2DM The RIACE Study: 15,773 patients with T2DM

Patients n. DM % Follow-up years Renal impairment No-albuminuric renal impairment Renal impairment with no albuminuria nor retinopathy UKPDS Diabetes 55: , , %67% (51%)--- DCCT/EDIC Diabetes Care 33: , , (type 1) 196.2%24%--- MacIsaac RJ et al., Diabetes Care 27: , %39%29% Kramer HJ et al., NHANES III JAMA 289: , , %36%30% Thomas MC et al., NEFRON Diabetes Care 32: , , %55%--- Ninomiya T et al., ADVANCE J Am Soc Nephrol 20: , , %62%--- Bakris GL et al., ACCOMPLISH Lancet 375: , , %46.8%--- Tube SW et al., ONTARGET/ TRASCEND Circulation 123: , , %68%--- RIACE Study Group, RIACE J Hypertens 29: , , %56.6%43.3% “Natural” history od Diabetic Retinopathy in type 1 and type 2 diabetes: new paradigms

Normoalbuminuria Normal GFR “Natural” history od Diabetic Retinopathy in type 1 and type 2 diabetes: new paradigms Microalbuminuria Macroalbuminuria Reduced eGFR ESRD Natural history of diabetic nephropathy: “albuminuric” pathway Natural history of diabetic nephropathy: “non-albuminuric” pathway Cardiovascular events, death

1.Classification of chronic kidney disease (CKD) by eGFR and albuminuria Classification of chronic kidney disease (CKD) by eGFR and albuminuriaClassification of chronic kidney disease (CKD) by eGFR and albuminuria 2.Renal impairment is common. Every second/third patient in our clinic might have signs of renal impairmentRenal impairment is common. Every second/third patient in our clinic might have signs of renal impairment 3.Albuminuria and eGFR: complementary measures of (diabetic) CKDAlbuminuria and eGFR: complementary measures of (diabetic) CKD Key points

KDIGO, Kidney Int Suppl 3: 1-150, 2013 Kidney Disease: Improving Global Outcomes (KDIGO) classification Low risk Moderate risk High risk Very high risk

Associations of Kidney Disease measures with mortality and ESRD in individuals with and without diabetes: a meta-analysis Fox CS et al., Lancet 380: , 2012 Data for 1,024,977 participants (128,505 with diabetes) from 30 general population and high-risk cardiovascular cohorts and 13 chronic kidney disease cohorts

Associations of Kidney Disease measures with mortality and ESRD in individuals with and without diabetes: a meta-analysis Fox CS et al., Lancet 380: , 2012 Data for 1,024,977 participants (128,505 with diabetes) from 30 general population and high-risk cardiovascular cohorts and 13 chronic kidney disease cohorts

Associations of Kidney Disease measures with mortality and ESRD in individuals with and without diabetes: a meta-analysis Fox CS et al., Lancet 380: , 2012 Data for 13 chronic kidney disease cohorts

Risk of coronary events in people with chronic kidney disease compared with those with diabetes: a population-level cohort study 1,268,029 participants; median follow-up of 48 months Tonelli M et al., Lancet, published online, June 19, ,268,029 participants; median follow-up of 48 months; the Alberta Kidney Disease Network 1,104,71375,871 59,11715,36812,960 eGFR by the CKD-EPI equation

Tonelli M et al., Lancet, published online, June 19, 2012 Risk of coronary events in people with chronic kidney disease compared with those with diabetes: a population-level cohort study

Intra-individual CV: 32.5% ( ) Concordance rate between a single UAE and the geometric mean: Two UAE: normo: 94.6%; micro: 83.5%; macro: 91.1%; micro/macro: 90.6%; Three UAE: normo: 94.6%; micro: 84.2%; macro: 86.8%; micro/macro: 90.8%. Predictive performance for the mean of 3 UAE values Reference line UAE one value UAE two values 4,062 subjects with at least two UAE measurements The Renal Insufficiency And Cardiovascular Events (RIACE) Italian multicentre study Pugliese G et al., Nephrol Dial Transplant 26: , 2011

The Renal Insufficiency And Cardiovascular Events (RIACE) Italian multicentre study Summary of results and conclusions l A single UAE value, thought to be encumbered with high intra- individual variability, is an accurate predictor of the stage of nephropathy in subjects with type 2 diabetes. l Multiple UAE measurements may not be necessary for classification purposes in both clinical and epidemiological settings. Pugliese G et al., Nephrol Dial Transplant 26: , 2011

KDIGO, Kidney Int Suppl 3: 1-150, 2013 Kidney Disease: Improving Global Outcomes (KDIGO) classification

KDIGO, Kidney Int Suppl 3: 1-150, 2013 Kidney Disease: Improving Global Outcomes (KDIGO) classification

KDIGO, Kidney Int Suppl 3: 1-150, 2013 Kidney Disease: Improving Global Outcomes (KDIGO) classification

The Renal Insufficiency And Cardiovascular Events (RIACE) Italian multicentre study Pugliese G et al., Atherosclerosis 218: , ,773 (100.0%) 258 (1.7%) 2,701 (17.1%) 1,897 (12.0%) 1,052 (6.7%) 9,865 (62.5%) Total 304 (1.9%) 256 (1.6%) 48 (0.3%) 4-5 2,411 (15.3%) 2 (0.1%) 2,342 (14.8%) 23 (0.1%) 44 (0.3%) 3 1,743 (11.1%) 77 (0.5%) 1,591 (10.1%) 75 (0.5%) 2 1,260 (8.0%) 283 (1.8%) 977 (6.2%) 1 10,055 (63.8%) 234 (1.5%) 9,821 (62.3%) No CKD No CKD TotalMDRD Study CKD stage CKD-EPI CKD Stage Soggetti riclassificati con la equazione CKD-EPI sopra sotto Prevalence of stages 3-5 CKD in type 2 diabetes MDRD Study: 2,959 (18.8%) CKD-EPI: 2,715 (17.2%)

The Renal Insufficiency And Cardiovascular Events (RIACE) Italian multicentre study Pugliese G et al., Atherosclerosis 218: , 2011 Prevalence of stages 3-5 CKD in type 2 diabetes MDRD Study: 2,959 (18.8%) CKD-EPI: 2,715 (17.2%)

The Renal Insufficiency And Cardiovascular Events (RIACE) Italian multicentre study Summary of results and conclusions l Estimating GFR in patients with type 2 diabetes using the CKD- EPI equation provides a better definition of the cardiovascular burden associated with CKD, in terms of CVD prevalence and CHD risk score. Pugliese G et al., Atherosclerosis 218: , 2011

Matsushita K et al, JAMA 307: , 2012 Comparison of risk prediction using the CKD-EPI Equation and the MDRD Study Equation for Estimated Glomerular Filtration Rate Distribution of estimated GFR Data from 1.1 million adults from 25 general population cohorts, 7 high-risk cohorts (of vascular disease), and 13 CKD cohorts

Matsushita K et al, JAMA 307: , 2012 Comparison of risk prediction using the CKD-EPI Equation and the MDRD Study Equation for Estimated Glomerular Filtration Rate Reclassification across estimated GFR categories

Matsushita K et al, JAMA 307: , 2012 Comparison of risk prediction using the CKD-EPI Equation and the MDRD Study Equation for Estimated Glomerular Filtration Rate Net reclassification improvements for all-cause mortality, cardiovascular mortality, and ESRD

1.Classification of chronic kidney disease (CKD) by eGFR and albuminuria Classification of chronic kidney disease (CKD) by eGFR and albuminuriaClassification of chronic kidney disease (CKD) by eGFR and albuminuria 2.Renal impairment is common. Every second/third patient in our clinic might have signs of renal impairment.Renal impairment is common. Every second/third patient in our clinic might have signs of renal impairment. 3.Albuminuria and eGFR: complementary measures of (diabetic) CKDAlbuminuria and eGFR: complementary measures of (diabetic) CKD 4.Cystatin CCystatin C Key points

KDIGO, Kidney Int Suppl 3: 1-150, 2013 Kidney Disease: Improving Global Outcomes (KDIGO) classification

KDIGO, Kidney Int Suppl 3: 1-150, 2013 Kidney Disease: Improving Global Outcomes (KDIGO) classification

KDIGO, Kidney Int Suppl 3: 1-150, 2013 Kidney Disease: Improving Global Outcomes (KDIGO) classification

Inker LA et al, N Engl J Med 367: 20-29, 2012 ….. the combined equation improved the classification of measured GFR ….. and correctly reclassified 16.9% of those with an estimated GFR of 45 to 59 ml per minute per 1.73 m 2 as having a GFR of 60 ml or higher per minute per 1.73 m 2.

Pucci L et al., Clin Chem 53: , 2007 Cystatin C and estimates of renal function: searching for a better measure of kidney function in diabetic patients

Shlipak MG et al, N Engl J Med 369: , 2013

13.7% 9.7% 10.0%

Shlipak MG et al, N Engl J Med 369: ,

Shlipak MG et al, N Engl J Med 369: , 2013

1.Classification of chronic kidney disease (CKD) by eGFR and albuminuria Classification of chronic kidney disease (CKD) by eGFR and albuminuriaClassification of chronic kidney disease (CKD) by eGFR and albuminuria 2.Renal impairment is common. Every second/third patient in our clinic might have signs of renal impairment.Renal impairment is common. Every second/third patient in our clinic might have signs of renal impairment. 3.Albuminuria and eGFR: complementary measures of (diabetic) CKDAlbuminuria and eGFR: complementary measures of (diabetic) CKD 4.Cystatin CCystatin C 5.Measuring GFRMeasuring GFR Key points

KDIGO, Kidney Int Suppl 3: 1-150, 2013 Kidney Disease: Improving Global Outcomes (KDIGO) classification

Pucci L et al, Diabet Med 18: , 2001

Agarwal R et al, Clin J Am Soc Nephrol 4: 77-85, 2009 We suggest an eight-sample technique to adequately capture the entire plasma pharmacokinetic profile. Sampling at 5, 15, 30, 45, 60, 120, 240, and 360 (or longer) min after bolus iothalamate should adequately capture the distribution and elimination phase of this drug. Others have suggested a similar approach (Pucci L et al. Diabet Med, 2001)