NEWS & VIEWS 2.
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Lambie, M. et al. Independent effects of systemic and peritoneal inflammation on peritoneal dialysis survival. J. Am. Soc. Nephrol. http://dx.doi.org/10.1681/ ASN.2013030314. Williams, J. D., Craig, K. J., Topley, N. & Williams, G. T. Peritoneal dialysis: changes to the structure of the peritoneal membrane and potential for biocompatible solutions. Kidney Int. Suppl. 63, S158–S161 (2003). Pecoits-Filho, R., Barany, P., Lindholm, B., Heimburger, O. & Stenvinkel, P. Interleukin‑6 is an independent predictor of mortality in patients starting dialysis treatment. Nephrol. Dial. Transplant. 17, 1684–1688 (2002). Oh, K. H. et al. Intra-peritoneal interleukin‑6 system is a potent determinant of the baseline peritoneal solute transport in incident peritoneal dialysis patients. Nephrol. Dial. Transplant. 25, 1639–1646 (2010). Pecoits-Filho, R., Carvalho, M. J., Stenvinkel, P., Lindholm, B. & Heimburger, O. Systemic and intraperitoneal interleukin‑6 system during the
first year of peritoneal dialysis. Perit. Dial. Int. 26, 53–63 (2006). 7. Perl, J., Huckvale, K., Chellar, M., John, B. & Davies, S. J. Peritoneal protein clearance and not peritoneal membrane transport status predicts survival in a contemporary cohort of peritoneal dialysis patients. Clin. J. Am. Soc. Nephrol. 4, 1201–1206 (2009). 8. Pecoits-Filho, R. et al. Plasma and dialysate IL‑6 and VEGF concentrations are associated with high peritoneal solute transport rate. Nephrol. Dial. Transplant. 17, 1480–1486 (2002). 9. Rodrigues, A. S. et al. Evaluation of peritoneal transport and membrane status in peritoneal dialysis: focus on incident fast transporters. Am. J. Nephrol. 27, 84–91 (2007). 10. Lopes Barreto, D., Coester, A. M., Struijk, D. G. & Krediet, R. T. Can effluent matrix metalloproteinase 2 and plasminogen activator inhibitor 1 be used as biomarkers of peritoneal membrane alterations in peritoneal dialysis patients? Perit. Dial. Int. http://dx.doi.org/ 10.3747/pdi.2012.01063.
CHRONIC KIDNEY DISEASE
Defining clinical cut-offs for albumin:creatinine ratio Stephan J. L. Bakker
Albuminuria is rapidly gaining recognition as a marker of the presence and of the progression of chronic kidney disease (CKD). In a new study, Naresh et al. attempt to define cut-off values for percentage change in urinary albumin:creatinine ratio that reflect changes in CKD status rather than random biological variation. Bakker, S. J. L. Nat. Rev. Nephrol. 9, 710–712 (2013); published online 5 November 2013; doi:10.1038/nrneph.2013.233
Albuminuria level can be used as a diagnostic marker for chronic kidney disease (CKD) in individuals with and without diabetes.1 The historical reference test for quantification of albuminuria is albumin excretion measured using a 24 h urine sample. Use of this test is, however, hampered by the need for timed urine collection—a cumbersome proc edure that is subject to timing and collection inaccur acies.2 Measurement of the albumin concentration in a spot urine sample is a more practical method, but is subject to variation introduced by sample dilution. Assuming that the muscle mass of an individual remains fairly stable, the problem of sample dilution can be overcome by correcting for urinary creatinine concentration.3 Albumin:creatinine ratio (ACR) has been repeatedly shown to correlate closely with 24 h urinary albumin excretion,2 and is as predictive of cardiovascular morbidity and all-cause mortality as is 24 h urinary 710 | DECEMBER 2013 | VOLUME 9
albumin excretion.4 Many key guideline groups now advocate the use of spot urine ACR as an alternative to 24 h urine collection for quantification of albuminuria,5,6 but the extent of day-to-day random biological variation in ACR measurements is still unclear. In a new study, Naresh et al. have attempted to address this issue and define cut-off values for changes in ACR that indicate genuine changes in CKD status rather than random biological variations.7 At first glance, the findings of Naresh et al. seem to cast doubt on the clinical utility of ACR as a marker for the presence and progression of CKD. 7 The researchers report that for patients in the normo albuminu ric range, a change in ACR of more than 467% is required to indicate a substantial change in level of albuminuria, whereas in patients with microalbumin uria, macroalbuminuria or nephroticrange proteinuria, changes in ACR of 170%, 83%, and 48%, respectively, are required.
The authors conclude that substantial day-to-day variability in ACR measurements may limit the clinical utility of spot ACR. However, this conclusion is rather far reaching and the analysis requires careful evaluation. Naresh et al. used spot urine samples collected on two consecutive days to measure the ACRs of 157 clinically stable outpatients with CKD. They report mean ACRs of 133.2 ± 233 mg/mmol on day 1 and 128.1 ± 199 mg/mmol on day 2.7 The difference between the mean values was not stat istically significant (5.1 mg/mmol, 95% CI –26 mg/mmol to 13 mg/mmol, P = 0.2). 7 However, the high standard deviations compared to the mean values must indicate a skewed distribution because if the distribution was normal many ACRs would be less than zero, which is biologically impossible. It would, therefore, have been appropriate to report the medians and interquartile ranges of the ACR values rather than the means and standard deviations. Also, rather than testing differences between ACRs on consecutive days using unprocessed data, it would have been appropriate to either use the nonpara metric Wilcoxon signed rank test for paired samples or to log-transform the data prior to analysis. To illustrate the effect of logtransformation, I generated a subsample of the PREVEND study 3 database that contained data from 583 individuals with urine albumin >50 mg/l during prescreening and ACR 50 mg/l during pre-screening and ACR
3.
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Lambie, M. et al. Independent effects of systemic and peritoneal inflammation on peritoneal dialysis survival. J. Am. Soc. Nephrol. http://dx.doi.org/10.1681/ ASN.2013030314. Williams, J. D., Craig, K. J., Topley, N. & Williams, G. T. Peritoneal dialysis: changes to the structure of the peritoneal membrane and potential for biocompatible solutions. Kidney Int. Suppl. 63, S158–S161 (2003). Pecoits-Filho, R., Barany, P., Lindholm, B., Heimburger, O. & Stenvinkel, P. Interleukin‑6 is an independent predictor of mortality in patients starting dialysis treatment. Nephrol. Dial. Transplant. 17, 1684–1688 (2002). Oh, K. H. et al. Intra-peritoneal interleukin‑6 system is a potent determinant of the baseline peritoneal solute transport in incident peritoneal dialysis patients. Nephrol. Dial. Transplant. 25, 1639–1646 (2010). Pecoits-Filho, R., Carvalho, M. J., Stenvinkel, P., Lindholm, B. & Heimburger, O. Systemic and intraperitoneal interleukin‑6 system during the
first year of peritoneal dialysis. Perit. Dial. Int. 26, 53–63 (2006). 7. Perl, J., Huckvale, K., Chellar, M., John, B. & Davies, S. J. Peritoneal protein clearance and not peritoneal membrane transport status predicts survival in a contemporary cohort of peritoneal dialysis patients. Clin. J. Am. Soc. Nephrol. 4, 1201–1206 (2009). 8. Pecoits-Filho, R. et al. Plasma and dialysate IL‑6 and VEGF concentrations are associated with high peritoneal solute transport rate. Nephrol. Dial. Transplant. 17, 1480–1486 (2002). 9. Rodrigues, A. S. et al. Evaluation of peritoneal transport and membrane status in peritoneal dialysis: focus on incident fast transporters. Am. J. Nephrol. 27, 84–91 (2007). 10. Lopes Barreto, D., Coester, A. M., Struijk, D. G. & Krediet, R. T. Can effluent matrix metalloproteinase 2 and plasminogen activator inhibitor 1 be used as biomarkers of peritoneal membrane alterations in peritoneal dialysis patients? Perit. Dial. Int. http://dx.doi.org/ 10.3747/pdi.2012.01063.
CHRONIC KIDNEY DISEASE
Defining clinical cut-offs for albumin:creatinine ratio Stephan J. L. Bakker
Albuminuria is rapidly gaining recognition as a marker of the presence and of the progression of chronic kidney disease (CKD). In a new study, Naresh et al. attempt to define cut-off values for percentage change in urinary albumin:creatinine ratio that reflect changes in CKD status rather than random biological variation. Bakker, S. J. L. Nat. Rev. Nephrol. 9, 710–712 (2013); published online 5 November 2013; doi:10.1038/nrneph.2013.233
Albuminuria level can be used as a diagnostic marker for chronic kidney disease (CKD) in individuals with and without diabetes.1 The historical reference test for quantification of albuminuria is albumin excretion measured using a 24 h urine sample. Use of this test is, however, hampered by the need for timed urine collection—a cumbersome proc edure that is subject to timing and collection inaccur acies.2 Measurement of the albumin concentration in a spot urine sample is a more practical method, but is subject to variation introduced by sample dilution. Assuming that the muscle mass of an individual remains fairly stable, the problem of sample dilution can be overcome by correcting for urinary creatinine concentration.3 Albumin:creatinine ratio (ACR) has been repeatedly shown to correlate closely with 24 h urinary albumin excretion,2 and is as predictive of cardiovascular morbidity and all-cause mortality as is 24 h urinary 710 | DECEMBER 2013 | VOLUME 9
albumin excretion.4 Many key guideline groups now advocate the use of spot urine ACR as an alternative to 24 h urine collection for quantification of albuminuria,5,6 but the extent of day-to-day random biological variation in ACR measurements is still unclear. In a new study, Naresh et al. have attempted to address this issue and define cut-off values for changes in ACR that indicate genuine changes in CKD status rather than random biological variations.7 At first glance, the findings of Naresh et al. seem to cast doubt on the clinical utility of ACR as a marker for the presence and progression of CKD. 7 The researchers report that for patients in the normo albuminu ric range, a change in ACR of more than 467% is required to indicate a substantial change in level of albuminuria, whereas in patients with microalbumin uria, macroalbuminuria or nephroticrange proteinuria, changes in ACR of 170%, 83%, and 48%, respectively, are required.
The authors conclude that substantial day-to-day variability in ACR measurements may limit the clinical utility of spot ACR. However, this conclusion is rather far reaching and the analysis requires careful evaluation. Naresh et al. used spot urine samples collected on two consecutive days to measure the ACRs of 157 clinically stable outpatients with CKD. They report mean ACRs of 133.2 ± 233 mg/mmol on day 1 and 128.1 ± 199 mg/mmol on day 2.7 The difference between the mean values was not stat istically significant (5.1 mg/mmol, 95% CI –26 mg/mmol to 13 mg/mmol, P = 0.2). 7 However, the high standard deviations compared to the mean values must indicate a skewed distribution because if the distribution was normal many ACRs would be less than zero, which is biologically impossible. It would, therefore, have been appropriate to report the medians and interquartile ranges of the ACR values rather than the means and standard deviations. Also, rather than testing differences between ACRs on consecutive days using unprocessed data, it would have been appropriate to either use the nonpara metric Wilcoxon signed rank test for paired samples or to log-transform the data prior to analysis. To illustrate the effect of logtransformation, I generated a subsample of the PREVEND study 3 database that contained data from 583 individuals with urine albumin >50 mg/l during prescreening and ACR 50 mg/l during pre-screening and ACR
