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• W2003521069 abstract "Novel biomarkers may improve our ability to predict which patients with chronic kidney disease (CKD) are at higher risk for progressive loss of renal function. Here, we assessed the performance of urine neutrophil gelatinase–associated lipocalin (NGAL) for outcome prediction in a diverse cohort of 3386 patients with CKD in the Chronic Renal Insufficiency Cohort study. In this cohort, the baseline mean estimated glomerular filtration rate (eGFR) was 42.4ml/min per 1.73m2, the median 24-h urine protein was 0.2g/day, and the median urine NGAL concentration was 17.2ng/ml. Over an average follow-up of 3.2 years, there were 689 cases in which the eGFR was decreased by half or incident end-stage renal disease developed. Even after accounting for eGFR, proteinuria, and other known CKD progression risk factors, urine NGAL remained a significant independent risk factor (Cox model hazard ratio 1.70 highest to lowest quartile). The association between baseline urine NGAL levels and risk of CKD progression was strongest in the first 2 years of biomarker measurement. Within this time frame, adding urine NGAL to a model that included eGFR, proteinuria, and other CKD progression risk factors led to net reclassification improvement of 24.7%, but the C-statistic remained nearly identical. Thus, while urine NGAL was an independent risk factor of progression among patients with established CKD of diverse etiology, it did not substantially improve prediction of outcome events. Novel biomarkers may improve our ability to predict which patients with chronic kidney disease (CKD) are at higher risk for progressive loss of renal function. Here, we assessed the performance of urine neutrophil gelatinase–associated lipocalin (NGAL) for outcome prediction in a diverse cohort of 3386 patients with CKD in the Chronic Renal Insufficiency Cohort study. In this cohort, the baseline mean estimated glomerular filtration rate (eGFR) was 42.4ml/min per 1.73m2, the median 24-h urine protein was 0.2g/day, and the median urine NGAL concentration was 17.2ng/ml. Over an average follow-up of 3.2 years, there were 689 cases in which the eGFR was decreased by half or incident end-stage renal disease developed. Even after accounting for eGFR, proteinuria, and other known CKD progression risk factors, urine NGAL remained a significant independent risk factor (Cox model hazard ratio 1.70 highest to lowest quartile). The association between baseline urine NGAL levels and risk of CKD progression was strongest in the first 2 years of biomarker measurement. Within this time frame, adding urine NGAL to a model that included eGFR, proteinuria, and other CKD progression risk factors led to net reclassification improvement of 24.7%, but the C-statistic remained nearly identical. Thus, while urine NGAL was an independent risk factor of progression among patients with established CKD of diverse etiology, it did not substantially improve prediction of outcome events. There is a great interest currently in defining novel biomarkers that will improve our ability to predict which patients with chronic kidney disease (CKD) are at higher risk for progressive loss of renal function, adding to currently available risk factors such as amount of total proteinuria and glomerular filtration rate (GFR).1Kronenberg F. Emerging risk factors and markers of chronic kidney disease progression.Nat Rev Nephrol. 2009; 5: 677-689Crossref PubMed Scopus (124) Google Scholar,2Fassett R.G. Venuthurupalli S.K. Gobe G.C. et al.Biomarkers in chronic kidney disease: a review.Kidney Int. 2011; 80: 806-821Abstract Full Text Full Text PDF PubMed Scopus (321) Google Scholar Better risk stratification may potentially improve clinical outcomes by facilitating the application or intensification of evidence-based therapies among higher-risk patients. One such promising novel biomarker is urine neutrophil gelatinase–associated lipocalin (NGAL).3Bolignano D. Donato V. Coppolino G. et al.Neutrophil gelatinase-associated lipocalin (NGAL) as a marker of kidney damage.Am J Kidney Dis. 2008; 52: 595-605Abstract Full Text Full Text PDF PubMed Scopus (414) Google Scholar A recent comprehensive review identified urine NGAL as the most promising novel biomarker among those being evaluated as predictors of CKD progression.2Fassett R.G. Venuthurupalli S.K. Gobe G.C. et al.Biomarkers in chronic kidney disease: a review.Kidney Int. 2011; 80: 806-821Abstract Full Text Full Text PDF PubMed Scopus (321) Google Scholar NGAL was originally identified in animal models by microarray analysis to be one of the earliest induced genes and proteins in the kidney after ischemic or nephrotoxic injury.4Nickolas T.L. Barasch J. Devarajan P. Biomarkers in acute and chronic kidney disease.Curr Opin Nephrol Hypertens. 2008; 17: 127-132Crossref PubMed Scopus (160) Google Scholar It is a ubiquitous lipocalin iron-carrying protein, highly expressed in the tubular epithelium, and released from tubular epithelial cells following damage.2Fassett R.G. Venuthurupalli S.K. Gobe G.C. et al.Biomarkers in chronic kidney disease: a review.Kidney Int. 2011; 80: 806-821Abstract Full Text Full Text PDF PubMed Scopus (321) Google Scholar Although initially studied in the context of acute kidney injury, urine NGAL levels are also abnormally elevated (albeit at a much lower level) in a large number of individuals with CKD. A number of cross-sectional studies have shown that urine NGAL levels correlate with the level of GFR or severity of underlying renal parenchyma injury.5Brunner H.I. Mueller M. Rutherford C. et al.Urinary neutrophil gelatinase-associated lipocalin as a biomarker of nephritis in childhood-onset systemic lupus erythematosus.Arthritis Rheum. 2006; 54: 2577-2584Crossref PubMed Scopus (187) Google Scholar, 6Ding H. He Y. Li K. et al.Urinary neutrophil gelatinase-associated lipocalin (NGAL) is an early biomarker for renal tubulointerstitial injury in IgA nephropathy.Clin Immunol. 2007; 123: 227-234Crossref PubMed Scopus (169) Google Scholar, 7Bolignano D. Coppolino G. Campo S. et al.Neutrophil gelatinase-associated lipocalin in patients with autosomal-dominant polycystic kidney disease.Am J Nephrol. 2007; 27: 373-378Crossref PubMed Scopus (127) Google Scholar, 8Bolignano D. Coppolino G. Campo S. et al.Urinary neutrophil gelatinase-associated lipocalin (NGAL) is associated with severity of renal disease in proteinuric patients.Nephrol Dial Transplant. 2008; 23: 414-416Crossref PubMed Scopus (105) Google Scholar, 9Suzuki M. Wiers K.M. Klein-Gitelman M.S. et al.Neutrophil gelatinase-associated lipocalin as a biomarker of disease activity in pediatric lupus nephritis.Pediatr Nephrol. 2008; 23: 403-412Crossref PubMed Scopus (115) Google Scholar, 10Malyszko J. Malyszko J.S. Bachorzewska-Gajewska H. et al.Neutrophil gelatinase-associated lipocalin is a new and sensitive marker of kidney function in chronic kidney disease patients and renal allograft recipients.Transplant Proc. 2009; 41: 158-161Abstract Full Text Full Text PDF PubMed Scopus (81) Google Scholar Several small studies in selected populations have provided conflicting reports about whether urine NGAL is an independent risk factor of more rapid loss of renal function after controlling for established CKD progression risk factors (such as proteinuria and blood pressure level).11Viau A. El Karoui K. Laouari D. et al.Lipocalin 2 is essential for chronic kidney disease progression in mice and humans.J Clin Invest. 2010; 120: 4065-4076Crossref PubMed Scopus (266) Google Scholar, 12Wu Y. Su T. Yang L. et al.Urinary neutrophil gelatinase-associated lipocalin: a potential biomarker for predicting rapid progression of drug-induced chronic tubulointerstitial nephritis.Am J Med Sci. 2010; 339: 537-542Abstract Full Text Full Text PDF PubMed Scopus (14) Google Scholar, 13Bolignano D. Lacquaniti A. Coppolino G. et al.Neutrophil gelatinase-associated lipocalin (NGAL) and progression of chronic kidney disease.Clin J Am Soc Nephrol. 2009; 4: 337-344Crossref PubMed Scopus (412) Google Scholar, 14Peters H.P. Waanders F. Meijer E. et al.High urinary excretion of kidney injury molecule-1 is an independent predictor of end-stage renal disease in patients with IgA nephropathy.Nephrol Dial Transplant. 2011; 26: 3581-3588Crossref PubMed Scopus (57) Google Scholar, 15Nielsen S.E. Andersen S. Zdunek D. et al.Tubular markers do not predict the decline in glomerular filtration rate in type 1 diabetic patients with overt nephropathy.Kidney Int. 2011; 79: 1113-1118Abstract Full Text Full Text PDF PubMed Scopus (84) Google Scholar, 16Nielsen S.E. Hansen H.P. Jensen B.R. et al.Urinary neutrophil gelatinase-associated lipocalin and progression of diabetic nephropathy in type 1 diabetic patients in a four-year follow-up study.Nephron Clin Pract. 2011; 118: c130-c135Crossref PubMed Scopus (20) Google Scholar, 17Parikh C.R. Dahl N.K. Chapman A.B. et al.Evaluation of urine biomarkers of kidney injury in polycystic kidney disease.Kidney Int. 2012; 81: 784-790Abstract Full Text Full Text PDF PubMed Scopus (52) Google Scholar, 18Nauta F.L. Bakker S.J. van Oeveren W. et al.Albuminuria, proteinuria, and novel urine biomarkers as predictors of long-term allograft outcomes in kidney transplant recipients.Am J Kidney Dis. 2011; 57: 733-743Abstract Full Text Full Text PDF PubMed Scopus (70) Google Scholar We undertook the present study to assess the performance of urine NGAL as a novel independent risk factor of CKD progression in a large prospective diverse cohort of individuals with CKD. Of the 3939 enrolled Chronic Renal Insufficiency Cohort (CRIC) study participants, 229 did not have a specimen available for NGAL testing and 3386 had valid NGAL measurements. The characteristics of the 3386 study participants are shown in Table 1. Urine NGAL distribution was highly skewed with a median of 17.2ng/ml and interquartile range 8.1–39.2ng/ml; 5% of the highest measurements were between 178.9 and 3069.6ng/ml. The 24-h urine protein distribution was also highly skewed with a median of 0.2g/day and interquartile range of 0.1–1.0g/day; 5% of the highest measurements were between 5.3–30.1g/day. The mean estimated GFR (eGFR) was 42.4±13.6 (s.d.) ml/min per 1.73m2. The mean serum creatinine was 1.9±0.7mg/dl, blood urea nitrogen 30±14mg/dl, total cholesterol 183±46mg/dl, hemoglobin 12.6±1.8g/dl, parathyroid hormone 76±71ng/l, and C-reactive protein 5.7±10.0mg/l.Table 1Baseline patient characteristics: overall and by quintiles of urine NGAL concentrationUrine NGAL concentration (ng/ml)Characteristics≤6.9(N=681)>6.9 to ≤12.9(N=678)>12.9 to ≤22.6(N=673)>22.6 to ≤49.5(N=677)>49.5(N=677)All(N=3386)P-valueAge, Mean (s.d.)58.7 (10.3)59.4 (10.0)59.5 (10.9)57.5 (11.3)56.1 (11.9)58.2 (11.0)<0.0001Sex Female103 (15.1%)258 (38.1%)381 (56.6%)444 (65.6%)406 (60.0%)1592 (47.0%)<0.0001Race/ethnicity Nonhispanic white396 (58.1%)331 (48.8%)263 (39.1%)240 (35.5%)180 (26.6%)1410 (41.6%)<0.0001 Nonhispanic black206 (30.2%)277 (40.9%)314 (46.7%)332 (49.0%)311 (45.9%)1440 (42.5%) Hispanic40 (5.9%)43 (6.3%)76 (11.3%)83 (12.3%)162 (23.9%)404 (11.9%)Diabetes303 (44.5%)270 (39.8%)304 (45.2%)357 (52.7%)400 (59.1%)1634 (48.3%)<0.000124-h proteinuria (g/day) Mean (s.d.)0.3 (0.4)0.5 (0.8)0.7 (1.1)1.2 (1.7)3.1 (4.3)1.1 (2.4)<0.0001 Median (IQR)0.1 (0.1–0.3)0.1 (0.1–0.5)0.2 (0.1–0.7)0.3 (0.1–1.7)1.1 (0.2–4.4)0.2 (0.1–1.0)Estimated GFR (ml/min per 1.73m2) Mean (s.d.)47.9 (12.0)45.9 (12.4)42.3 (12.7)40.2 (13.6)35.6 (13.5)42.4 (13.6)<0.0001 Median (IQR)48.0 (39.5–56.1)44.7 (37.1–54.1)41.2 (33.1–50.8)38.0 (29.2–49.9)33.8 (25.1–43.6)41.6 (32.1–51.5)Systolic BP (mmHg) Mean (s.d.)123 (18)126 (20)127 (22)131 (23)137 (25)129 (22)<0.0001Diastolic BP (mmHg) Mean (s.d.)71 (12)71 (12)71 (13)72 (13)73 (14)72 (13)0.0002Body mass index (kg/m2) Mean (s.d.)31.2 (6.7)31.6 (6.9)32.3 (7.8)33.5 (8.8)32.5 (9.0)32.2 (7.9)<0.0001History of cardiovascular disease233 (34.2%)201 (29.6%)228 (33.9%)212 (31.3%)242 (35.7%)1116 (33.0%)0.12Use of ACE inhibitor or ARB499 (73.7%)468 (69.5%)451 (67.3%)437 (64.9%)429 (64.0%)2284 (67.9%)0.0008Abbreviations: ACE, angiotensin-converting enzyme; ARB, angiotensin receptor blocker; BP, blood pressure; GFR, glomerular filtration rate; IQR, interquartile range; NGAL, neutrophil gelatinase–associated lipocalin. Open table in a new tab Abbreviations: ACE, angiotensin-converting enzyme; ARB, angiotensin receptor blocker; BP, blood pressure; GFR, glomerular filtration rate; IQR, interquartile range; NGAL, neutrophil gelatinase–associated lipocalin. We divided the participants into quintiles of urine NGAL concentrations as shown in Table 1 (≤6.9, >6.9–≤12.9, >12.9–≤22.6, >22.6–≤49.5, and >49.5ng/ml). Patients with higher urine NGAL concentrations were more likely to have lower eGFR and have higher levels of proteinuria. They were also more likely to be female patients, nonwhite, with diabetes mellitus (DM) and higher blood pressure. Over a mean follow-up period of 3.2 years, there were 689 cases of halving of eGFR or incident end-stage renal disease (ESRD) (incidence rate 6.37 per 100 person-years). In unadjusted analysis, there was a strong graded relationship between urine NGAL concentration and risk of CKD progression (Table 2). Compared with those with urine NGAL concentration ≤6.9ng/ml, CRIC participants with urine NGAL concentration >49.5 were nearly 10 times more likely to experience ESRD or halving of eGFR (hazard ratio (HR) 9.34; 95% confidence interval (CI) 6.86–12.72; P<0.001). This relationship was similar after adjustment for demographic attributes (Table 2). The association between urine NGAL concentration and ESRD or halving of eGFR was substantially attenuated when eGFR and 24-urine protein were taken into account (HR 1.58 for urine NGAL concentration >49.5 vs. ≤6.9ng/ml; 95% CI 1.09–2.29; P=0.01). Additional adjustment for other risk factors for CKD progression gave similar results (HR 1.70 for urine NGAL concentration >49.5 vs. ≤6.9ng/ml; 95% CI 1.16–2.48; P=0.006) (Table 2).Table 2Association between the quintiles of urine NGAL concentration and the risk of progressive CKD (halving of eGFR or ESRD)Quintiles of baseline urine NGAL concentration (ng/ml)EventsRate (per 100 person-years)Unadjusted HR (95% confidence intervals)Age, sex, and race/ethnicity adjusted HRAdditionally adjusted for baseline eGFR and 24-h urine proteinAdditionally adjusted for other baseline covariatesaDiabetes mellitus status, systolic blood pressure, body mass index, use of angiotensin-converting enzyme inhibitor or angiotensin receptor blocker, history of cardiovascular disease, and education attainment.≤6.9471.9Ref.Ref.Ref.Ref.>6.9 to ≤12.9773.31.75 (1.22–2.51)2.01 (1.40–2.89)1.26 (0.87–1.82)1.37 (0.94–1.98)>12.9 to ≤22.61054.82.52 (1.79–3.56)3.15 (2.22–4.47)1.21 (0.84–1.74)1.24 (0.86–1.79)>22.6 to ≤49.51738.14.30 (3.11–5.93)5.72 (4.10–7.97)1.31 (0.92–1.88)1.39 (0.97–2.00)>49.528716.99.34 (6.86–12.72)11.65 (8.45–16.05)1.58 (1.09–2.29)1.70 (1.16–2.48)HR per 1 unit increase in log (urine NGAL)1.75 (1.66–1.85)P<0.00011.78 (1.69–1.88)P<0.00011.09 (1.001–1.18)P=0.04711.11 (1.01–1.21)P=0.0230Abbreviations: CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; ESRD, end-stage renal disease; HR, hazard ratio; NGAL, neutrophil gelatinase–associated lipocalin; Ref., reference.a Diabetes mellitus status, systolic blood pressure, body mass index, use of angiotensin-converting enzyme inhibitor or angiotensin receptor blocker, history of cardiovascular disease, and education attainment. Open table in a new tab Abbreviations: CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; ESRD, end-stage renal disease; HR, hazard ratio; NGAL, neutrophil gelatinase–associated lipocalin; Ref., reference. Results were consistent when urine NGAL was analyzed as a linear term with an HR of 1.11 per one standard deviation increase in log urine NGAL in the fully adjusted model (HR 1.11; 95% CI 1.01–1.21; P=0.02). Compared with urine protein and eGFR the effect size of urine NGAL is much more modest (Figure 1). Similar results were seen when the exposure was changed to urine NGAL/urine creatinine ratio or when the outcome was defined using ESRD alone in sensitivity analyses (results not shown). There were no statistically significant interactions between urine NGAL and proteinuria (P=0.27) or eGFR (P=0.42), nor with diabetes status (P=0.78), age (P=0.13), sex (P=0.32), and race (P=0.18). The C-statistic for the final model was 0.847. Removal of urine NGAL from the final model did not change the C-statistic to the third decimal place (0.847). In an exploratory analysis, we relaxed the assumption of a constant HR over time by modeling urine NGAL and renal progression within each of the four time intervals (<2, 2 to <3, 3 to <4, and >4 years). We noted that the effect of urine NGAL was stronger in the first 2 years after measurement of urine NGAL vs. more than 2 years of follow-up (Figure 2). The HR per SD of urine NGAL for outcomes occurring within 2 years of biomarker measurement was 1.27 (95% CI 1.14–1.42). The HRs were 0.97 (95% CI 0.83–1.12), 1.00 (95% CI 0.84–1.20), and 0.98 (95% CI 0.78–1.22) for the later three time intervals, respectively. The C-statistic for the model limited to 2 years of follow-up was 0.880. Removal of urine NGAL from the final model lowered the C-statistic minimally to 0.879. To assess reclassification in the arena of potentially the most promising clinical use—which would be prediction of outcome in the first 2 years following biomarker ascertainment—we examined category-free as well as category-based Net Reclassification Improvement (NRI) within a 2-year horizon. We a priori defined clinically meaningful differences in risks of 0–5%, 5–10%, and >10% event rate per year. The category-free NRI for events was 4.4% (95% CI -5.9 to 16.8%) and that for nonevents was 20.3% (95% CI 6.5 to 26.0%). The overall category-free NRI was thus 24.7% (95% CI 0.4 to 38.5%). The three-category NRI for events was -0.3% (95% CI -2.8 to 2.9%) and that for nonevents was 0.4% (95% CI -0.4 to 1.1%). The overall three-category NRI was thus 0.1% (95% CI -2.7 to 3.5%). In the entire cohort, predicted probability of CKD progression was similar in models with and without urine NGAL. Table 3 summarizes the different metrics used to assess incremental improvement in risk reclassification.Table 3Summary of the measures of risk reclassificationC-statisticCategory-free NRI (95% confidence interval)3-Category (<5%, 5–10%, and >10% annual event rate) NRI (95% confidence interval)Overall Without NGALaWith base model already including age, sex, race/ethnicity, estimated glomerular filtration rate (eGFR), 24-h urine protein, diabetes mellitus status, systolic blood pressure, body mass index, use of angiotensin-converting enzyme inhibitor or angiotensin receptor blocker, history of cardiovascular disease, and education attainment.0.847 With NGAL0.8472-Year time horizon Without NGALaWith base model already including age, sex, race/ethnicity, estimated glomerular filtration rate (eGFR), 24-h urine protein, diabetes mellitus status, systolic blood pressure, body mass index, use of angiotensin-converting enzyme inhibitor or angiotensin receptor blocker, history of cardiovascular disease, and education attainment.0.87924.7%(0.4 to 38.5%)0.1%(-2.7 to 3.5%) With NGAL0.880Abbreviations: NGAL, neutrophil gelatinase–associated lipocalin; NRI, Net Reclassification Improvement.a With base model already including age, sex, race/ethnicity, estimated glomerular filtration rate (eGFR), 24-h urine protein, diabetes mellitus status, systolic blood pressure, body mass index, use of angiotensin-converting enzyme inhibitor or angiotensin receptor blocker, history of cardiovascular disease, and education attainment. Open table in a new tab Abbreviations: NGAL, neutrophil gelatinase–associated lipocalin; NRI, Net Reclassification Improvement. In this large and diverse cohort of individuals with CKD, the urine NGAL level was elevated in a substantial fraction of the study population. Urine NGAL levels correlated with severity of CKD at baseline as patients with lower eGFR and higher 24-h proteinuria had higher urine NGAL levels. Baseline urine NGAL levels correlated strongly with the risk of CKD progression, defined as halving of eGFR or development of ESRD. The strength of this association was substantially attenuated after adjustment for a priori defined ‘traditional’ risk factors, but urine NGAL remained an independent risk factor for CKD progression (with those in the highest quintile at 70% increased risk compared with those in the lowest quintile). Our results are consistent with some but not all of the prior literature. In a study of 63 patients with type 1 DM and a mean GFR of 87ml/min per 1.73m2, Nielsen et al.15Nielsen S.E. Andersen S. Zdunek D. et al.Tubular markers do not predict the decline in glomerular filtration rate in type 1 diabetic patients with overt nephropathy.Kidney Int. 2011; 79: 1113-1118Abstract Full Text Full Text PDF PubMed Scopus (84) Google Scholar showed that elevated NGAL was predictive of more rapid decline in 51Cr-EDTA-measured GFR; however, it was no longer an independent risk factor after adjusting for known promoters of progression. In a study of 65 patients with IgA nephropathy, Peters et al.14Peters H.P. Waanders F. Meijer E. et al.High urinary excretion of kidney injury molecule-1 is an independent predictor of end-stage renal disease in patients with IgA nephropathy.Nephrol Dial Transplant. 2011; 26: 3581-3588Crossref PubMed Scopus (57) Google Scholar found that urine NGAL was a risk factor of ESRD risk in univariable analysis but not after adjusting for other factors such as serum creatinine. Nielson et al.16Nielsen S.E. Hansen H.P. Jensen B.R. et al.Urinary neutrophil gelatinase-associated lipocalin and progression of diabetic nephropathy in type 1 diabetic patients in a four-year follow-up study.Nephron Clin Pract. 2011; 118: c130-c135Crossref PubMed Scopus (20) Google Scholar showed in another cohort of 78 type 1 DM patients that elevated urine NGAL was not related to decline in GFR during a 4-year follow-up; it was associated with the development of ESRD but not after adjustment (albeit confidence intervals were wide). Nauta et al.18Nauta F.L. Bakker S.J. van Oeveren W. et al.Albuminuria, proteinuria, and novel urine biomarkers as predictors of long-term allograft outcomes in kidney transplant recipients.Am J Kidney Dis. 2011; 57: 733-743Abstract Full Text Full Text PDF PubMed Scopus (70) Google Scholar found in 606 kidney transplant recipients that urine NGAL did not predict graft failure after albuminuria was accounted for. Viau et al.11Viau A. El Karoui K. Laouari D. et al.Lipocalin 2 is essential for chronic kidney disease progression in mice and humans.J Clin Invest. 2010; 120: 4065-4076Crossref PubMed Scopus (266) Google Scholar examined 87 subjects with polycystic kidney disease who had GFR 33±20ml/min per 1.73m2 and reported that urine NGAL levels were higher in patients who progressed to ESRD. No attempts were made to adjust for other known risk factors for CKD progression. In contrast, Parikh et al.17Parikh C.R. Dahl N.K. Chapman A.B. et al.Evaluation of urine biomarkers of kidney injury in polycystic kidney disease.Kidney Int. 2012; 81: 784-790Abstract Full Text Full Text PDF PubMed Scopus (52) Google Scholar found that urine NGAL levels did not correlate with changes in total kidney volume or kidney function in 209 patients with polycystic kidney disease and preserved GFR (mean 89ml/min per 1.73m2). In a study by Wu et al.12Wu Y. Su T. Yang L. et al.Urinary neutrophil gelatinase-associated lipocalin: a potential biomarker for predicting rapid progression of drug-induced chronic tubulointerstitial nephritis.Am J Med Sci. 2010; 339: 537-542Abstract Full Text Full Text PDF PubMed Scopus (14) Google Scholar, of 36 patients with drug-induced chronic tubulointerstitial nephritis (GFR 37±20ml/min per 1.73m2), urine NGAL was predictive of renal function decline and the only risk factor with a P<0.05 in their multivariable models. Bolignano et al.13Bolignano D. Lacquaniti A. Coppolino G. et al.Neutrophil gelatinase-associated lipocalin (NGAL) and progression of chronic kidney disease.Clin J Am Soc Nephrol. 2009; 4: 337-344Crossref PubMed Scopus (412) Google Scholar reported that among 96 patients with CKD of various etiologies (GFR 42±19ml/min per 1.73m2), urine NGAL (but not proteinuria) was an independent risk factor for CKD progression. We noted that the association between baseline urine NGAL levels and risk of CKD progression was strongest within the first 2 years of the biomarker measurement. Even within this time frame though, urine NGAL did not substantially improve risk classification. The major strengths of this study include the large sample size, the detailed and rigorous phenotyping of study participants, the rigorous statistical analysis (encompassing both assessment of prediction and risk reclassification), and the diversity of the study population (in terms of both race-ethnicity as well as disease etiology). Limitations of this study include the fact that NGAL measurements were made on urine samples that were not rapidly processed after voiding under conditions fully controlled by the research team. To the extent that suboptimal handling may have resulted in random error from protein degradation or other processes, this would bias our results toward the null. The CRIC study comprised persons who volunteered for research and so our results may not be generalizable to all CKD patients. By design, some underlying causes of CKD, such as polycystic kidney disease, were not represented. Exact underlying kidney disease etiologies were not ascertained systematically or with certainty in CRIC by means such as kidney biopsies. The urine NGAL concentration was ascertained only at one point in time. Our subgroups and the 2-year time horizon were defined post hoc and hence those results should be regarded as hypothesis-generating findings that may be due to chance. With regard to possible explanations for the latter finding, we speculate that, perhaps as an injury marker, urine NGAL levels may fluctuate over time because of (subtle) acute renal insults such as excessive lowering of blood pressure, for example. The impact of these transitory insults may be most evident in the short term. To summarize, we determined that urine NGAL levels correlated with severity of CKD and was an independent risk factor for CKD progression, particularly in the first 2 years following measurement. However, this novel marker only very modestly improved prediction of outcome events. Thus, it would be premature to consider introducing urine NGAL into clinical practice. Further studies, are needed to refine our understanding, in particular, ones in which urine collection and handling conditions were optimized. The CRIC study is a multicenter observational cohort that enrolled patients from seven clinical centers (consisting 13 enrolling sites) located throughout the United States. Patients with reduced GFR (in the range of stages 2–4 CKD) between the ages of 21 and 74 years were eligible for participating in the study. Those with polycystic kidney disease, multiple myeloma, or glomerulonephritis on active immunosuppression were excluded, as were those who had undergone kidney transplantation. Enrollment started in June 2003 and ended in August 2008. A total of 3939 participants were enrolled. The CRIC basic study design and baseline characteristics have been published.19Feldman H.I. Appel L.J. Chertow G.M. et al.The Chronic Renal Insufficiency Cohort (CRIC) Study: Design and Methods.J Am Soc Nephrol. 2003; 14: S148-S153Crossref PubMed Google Scholar,20Lash J.P. Go A.S. Appel L.J. et al.Chronic Renal Insufficiency Cohort (CRIC) Study: baseline characteristics and associations with kidney function.Clin J Am Soc Nephrol. 2009; 4: 1302-1311Crossref PubMed Scopus (420) Google Scholar The CRIC protocol called for collection of a 24-h urine specimen at baseline. Enrollees were allowed to start this timed collection at home up to a week before their in-person visit. They were instructed to keep the urine refrigerated or on ice before bringing it to the clinical center. Samples were rejected and recollection attempted if total urine volumes were below 500 cc or collection times were below 22h or more than 26h. After proper mixing, samples from the 24-h urine were then transferred into airtight 10ml cryovials (filled to 9ml). The urine NGAL measurements for this analysis were made on urine aliquots stored at 4°C and then shipped overnight within 72h to the CRIC central lab with cold gel packs placed in the bottom of the mailing container. Upon receipt at the central lab, the urine samples were further aliquoted into four 2ml aliquots and frozen at -80°C. The urine for the current studies therefore have undergone one freeze–thaw cycle. The urine NGAL concentration was measured using a two-step assay using the chemiluminescent microparticle immunoassay technology on an Abbott ARCHITECT i2000SR (Abbott Laboratories, Abbott Park, IL) (total imprecision was 3.8%). All but 12 of the urine creatinines at baseline were measured on a BioTek Plate Reader ELX 808 (BioTek, Winooski, VT) using a Jaffe reaction with a colorimetric end point and reagents from Sigma-Aldrich (St Louis, MO) (mean CV was 5.0%). A Roche Module P analyzer (Roche Diagnostics, Indianapolis, IN) was used to quantify urine total protein using a turbidimetric reaction with benzethonium chloride (CV 5.2%). The primary outcome was progressive CKD, defined as a composite end point of incident ESRD or halving of eGFR (from baseline) using the Modification of Diet in Renal Disease study equation after calibration of serum creatinine.21Levey A.S. Coresh J. Greene T. et al.Expressing the Modification of Diet in Renal Disease Study equation for estimating glomerular filtration rate with standardized serum creatinine values.Clin Chem. 2007; 53: 766-772Crossref PubMed Scopus (1449) Google Scholar ESRD was defined as receipt of chronic dialysis or kidney transplant. Ascertainment of ESRD in the CRIC study has been supplemented by cross-linkage with the US Renal Data System. Time to eGFR halving was imputed assuming a linear decline in kidney function between in-person annual visit measures. Follow-up for this analysis was performed through June 2009. Time-to-event analysis was conducted using Cox proportional hazard models. Recognizing that ESRD or halving of eGFR represents different degrees of loss of renal function depending on baseline renal function,22Hunsicker L.G. Adler S. Caggiula A. et al.Predictors of the progression of renal disease in the Modification of Diet in Renal Disease Study.Kidney Int. 1997; 51: 1908-1919Abstract Full Text PDF PubMed Scopus (601) Google Scholar we adjusted for baseline eGFR in all analyses. We also adjusted for 24-h urine proteinuria and other potential confounders on the basis of the literature of known risk factors for CKD progression. For the latter, we a priori selected demographics (age, sex, and race/ethnicity), presence or absence of DM status (defined by fasting blood glucose ≥126mg/dl or random blood glucose ≥200mg/dl or patient self-report of use of insulin or oral diabetes medication), systolic blood pressure, body mass index, use of an angiotensin-converting enzyme inhibitor or angiotensin receptor blocker at baseline, history of cardiovascular disease, and education attainment (as a proxy for socioeconomic status).22Hunsicker L.G. Adler S. Caggiula A. et al.Predictors of the progression of renal disease in the Modification of Diet in Renal Disease Study.Kidney Int. 1997; 51: 1908-1919Abstract Full Text PDF PubMed Scopus (601) Google Scholar,23Hsu C.Y. Iribarren C. McCulloch C.E. et al.Risk factors for end-stage renal disease: 25-year follow-up.Arch Intern Med. 2009; 169: 342-350Crossref PubMed Scopus (428) Google Scholar (We also adjusted for CRIC clinical centers in final analyses). We explored the nonlinear relationship between urine NGAL and renal progression using splines24Greenland S. Dose-response and trend analysis in epidemiology: alternatives to categorical analysis.Epidemiology. 1995; 6: 356-365Crossref PubMed Scopus (888) Google Scholar and discovered that by expressing urine NGAL on a natural logarithmic scale, a linear term of urine NGAL is sufficient to describe the relationship with CKD progression. For proteinuria and eGFR, the two strongest predictors for CKD progression,25Gansevoort R.T. Matsushita K. van der VeldeM et al.Lower estimated GFR and higher albuminuria are associated with adverse kidney outcomes. A collaborative meta-analysis of general and high-risk population cohorts.Kidney Int. 2011; 80: 93-104Abstract Full Text Full Text PDF PubMed Scopus (549) Google Scholar we relaxed the linearity assumptions for their relationships with progression using quadratic splines (with one knot at the median) of eGFR and natural log-transformed proteinuria. We calculated the C-statistic to measure the overall model fit.26Heagerty P.J. Zheng Y. Survival model predictive accuracy and ROC curves.Biometrics. 2005; 61: 92-105Crossref PubMed Scopus (918) Google Scholar To explore whether there was effective modification, we entered multiplicative interaction terms into our statistical models for urine NGAL and proteinuria, eGFR, diabetes status, age, sex, or race. To explore whether and how the association between urine NGAL and progression changed over time, we refit the Cox proportional hazard model assuming different HRs for urine NGAL in the following four time intervals: <2, 2 to <3, 3 to <4, and >4 years. We found that the effect of NGAL was strongest over the first 2 years after measurement. Thus, improved model predictability due to NGAL was quantified using NRI over a 2-year time horizon. We calculated both category-free NRI and NRI based on three categories (a priori defined risks of <5%, 5–10%, and >10% annual event rates)27Pencina M.J. D'Agostino R.B. Steyerberg E.W. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers.Stat Med. 2011; 30: 11-21Crossref PubMed Scopus (1747) Google Scholar for the risk of renal progression. Funding for the CRIC Study was obtained under a cooperative agreement from the National Institute of Diabetes and Digestive and Kidney Diseases (U01DK060990, U01DK060984, U01DK061022, U01DK061021, U01DK061028, U01DK60980, U01DK060963, and U01DK060902). In addition, this work was supported partly by K01DK92353, K24DK02651, University of Pennsylvania CTRC CTSA UL1 RR-024134, Johns Hopkins University UL1 RR-025005, University of Maryland GCRC M01 RR-16500, Case Western Reserve University Clinical and Translational Science Collaborative (University Hospitals of Cleveland, Cleveland Clinic Foundation, and MetroHealth) UL1 RR-024989, University of Michigan GCRC grant number M01 RR-000042 CTSA grant number UL1 RR-024986, University of Illinois at Chicago CTSA UL1RR029879, Tulane Clinical and Translational Research, Education, and Commercialization Project (CTRECP), Kaiser NIH/NCRR UCSF-CTSI UL1 RR-024131. KDL, HIF, and CYH are also supported by U01DK85649 as members of the CKD Biomarker Consortium, and CYH is additionally supported by K24 DK92291. We would like to thank Ted Mifflin and Steve Masters at Penn Central Lab for technical assistance with the urine NGAL assays." @default.
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• W2003521069 title "Urine neutrophil gelatinase–associated lipocalin levels do not improve risk prediction of progressive chronic kidney disease" @default.
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