Meta-Analysis

. 2020 Sep 15;173(6):426-435.

doi: 10.7326/M20-0529. Epub 2020 Jul 14.

Conversion of Urine Protein-Creatinine Ratio or Urine Dipstick Protein to Urine Albumin-Creatinine Ratio for Use in Chronic Kidney Disease Screening and Prognosis : An Individual Participant-Based Meta-analysis

Keiichi Sumida¹, Girish N Nadkarni², Morgan E Grams³, Yingying Sang³, Shoshana H Ballew³, Josef Coresh³, Kunihiro Matsushita³, Aditya Surapaneni³, Nigel Brunskill⁴, Steve J Chadban⁵, Alex R Chang⁶, Massimo Cirillo⁷, Kenn B Daratha⁸, Ron T Gansevoort⁹, Amit X Garg¹⁰, Licia Iacoviello¹¹, Takamasa Kayama¹², Tsuneo Konta¹², Csaba P Kovesdy¹³, James Lash¹⁴, Brian J Lee¹⁵, Rupert W Major⁴, Marie Metzger¹⁶, Katsuyuki Miura¹⁷, David M J Naimark¹⁸, Robert G Nelson¹⁹, Simon Sawhney²⁰, Nikita Stempniewicz²¹, Mila Tang²², Raymond R Townsend²³, Jamie P Traynor²⁴, José M Valdivielso²⁵, Jack Wetzels²⁶, Kevan R Polkinghorne²⁷, Hiddo J L Heerspink²⁸; Chronic Kidney Disease Prognosis Consortium

Collaborators, Affiliations

Collaborators

Chronic Kidney Disease Prognosis Consortium:
Kevan R. Polkinghorne, Steven J. Chadban, Robert Atkins, Adeera Levin, Ognjenka Djurdjev, Mila Tang, Hernan Rincon Choles, Edward Horwitz, Farsad Afshinnia, Raymond R. Townsend, Katherine R. Tuttle, Kenn B. Daratha, Radica Alicic, Cami R. Jones, Alex R. Chang, Gurmukteshwar Singh, Jamie Green, H. Lester Kirchner, Simon Sawhney, Corri Black, Angharad Marks, Lynn Robertson, Amit X. Garg, Hiddo J.L. Heerspink, Brian J. Lee, Nigel Brunskill, Rupert W. Major, David Shepherd, James Medcalf, Jack Wetzels, Peter Blankestijn, Arjan van Zuilen, Jan van de Brand, Massimo Cirillo, Licia Iacoviello, Girish N. Nadkarni, Erwin P. Bottinger, Ruth J.F. Loos, Stephen B. Ellis, José M. Valdivielso, Marcelino Bermúdez-López, Milica Bozic, Serafí Cambray, Benedicte Stengel, Marie Metzger, Martin Flamant, Pascal Houillier, Jean-Philippe Haymann, Katsuyuki Miura, Akira Okayama, Aya Kadota, Sachiko Tanaka, Nikita Stempniewicz, John Cuddeback, Elizabeth Ciemins, Emily Carbonara, Stephan Dunning, Robert G. Nelson, William C. Knowler, Helen C. Looker, Csaba P. Kovesdy, Keiichi Sumida, Miklos Molnar, Praveen Potukuchi, Michelle Pena, Dick de Zeeuw, David M.J. Naimark, Navdeep Tangri, Takamasa Kayama, Tsuneo Konta, Patrick B. Mark, Jamie P. Traynor, Peter C. Thomson, Colin C. Geddes, Josef Coresh, Shoshana H. Ballew, Ron T. Gansevoort, Morgan E. Grams, Orlando Gutierrez, Anna Köttgen, Andrew S. Levey, Kunihiro Matsushita, Elke Schäffner, Mark Woodward, Luxia Zhang, Jingsha Chen, Yingying Sang, Aditya Surapeneni

Affiliations

¹ University of Tennessee Health Science Center, Memphis, Tennessee (K.S.).
² Icahn School of Medicine at Mount Sinai, New York, New York (G.N.N.).
³ Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland (M.E.G., Y.S., S.H.B., J.C., K.M., A.S.).
⁴ Leicester General Hospital, University Hospitals of Leicester NHS Trust, and University of Leicester, Leicester, United Kingdom (N.B., R.W.M.).
⁵ Royal Prince Alfred Hospital and Kidney Node, University of Sydney, Sydney, New South Wales, Australia (S.J.C.).
⁶ Geisinger Health, Danville, Pennsylvania (A.R.C.).
⁷ University of Naples "Federico II," Naples, Italy (M.C.).
⁸ Providence Sacred Heart Medical Center and Gonzaga University School of Anesthesia, Spokane, Washington (K.B.D.).
⁹ University Medical Center Groningen, University of Groningen, Groningen, the Netherlands (R.T.G.).
¹⁰ ICES and Western University, London, Ontario, Canada (A.X.G.).
¹¹ IRCCS Neuromed, Pozzilli, Italy, and University of Insubria, Varese, Italy (L.I.).
¹² Yamagata University, Yamagata, Japan (T.K., T.K.).
¹³ Memphis Veterans Affairs Medical Center and University of Tennessee Health Science Center, Memphis, Tennessee (C.P.K.).
¹⁴ University of Illinois at Chicago, Chicago, Illinois (J.L.).
¹⁵ Kaiser Permanente, Hawaii Region, and Moanalua Medical Center, Honolulu, Hawaii (B.J.L.).
¹⁶ Paris Saclay University, Paris-Sud University, UVSQ, CESP, INSERM U1018, Villejuif, France (M.M.).
¹⁷ Shiga University of Medical Science Seta-Tsukinowa-cho, Shiga, Japan (K.M.).
¹⁸ Sunnybrook Hospital, University of Toronto, Toronto, Ontario, Canada (D.M.N.).
¹⁹ National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona (R.G.N.).
²⁰ University of Aberdeen, Aberdeen, Scotland (S.S.).
²¹ American Medical Group Association, Alexandria, Virginia (N.S.).
²² University of British Columbia, Vancouver, British Columbia, Canada (M.T.).
²³ Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania (R.R.T.).
²⁴ Queen Elizabeth University Hospital, Glasgow, Scotland (J.P.T.).
²⁵ Institute of Biomedical Research of Lleida and Spanish Research Network for Renal Diseases, Lleida, Spain (J.M.V.).
²⁶ Radboud University Medical Center, Nijmegen, the Netherlands (J.W.).
²⁷ Monash University, Clayton, Victoria, Australia (K.R.P.).
²⁸ University of Groningen, University Medical Center, Groningen, the Netherlands, and The George Institute for Global Health, Sydney, New South Wales, Australia (H.J.H.).

PMID: 32658569
PMCID: PMC7780415
DOI: 10.7326/M20-0529

Meta-Analysis

Conversion of Urine Protein-Creatinine Ratio or Urine Dipstick Protein to Urine Albumin-Creatinine Ratio for Use in Chronic Kidney Disease Screening and Prognosis : An Individual Participant-Based Meta-analysis

Keiichi Sumida et al. Ann Intern Med. 2020.

. 2020 Sep 15;173(6):426-435.

doi: 10.7326/M20-0529. Epub 2020 Jul 14.

Authors

Collaborators

Chronic Kidney Disease Prognosis Consortium:
Kevan R. Polkinghorne, Steven J. Chadban, Robert Atkins, Adeera Levin, Ognjenka Djurdjev, Mila Tang, Hernan Rincon Choles, Edward Horwitz, Farsad Afshinnia, Raymond R. Townsend, Katherine R. Tuttle, Kenn B. Daratha, Radica Alicic, Cami R. Jones, Alex R. Chang, Gurmukteshwar Singh, Jamie Green, H. Lester Kirchner, Simon Sawhney, Corri Black, Angharad Marks, Lynn Robertson, Amit X. Garg, Hiddo J.L. Heerspink, Brian J. Lee, Nigel Brunskill, Rupert W. Major, David Shepherd, James Medcalf, Jack Wetzels, Peter Blankestijn, Arjan van Zuilen, Jan van de Brand, Massimo Cirillo, Licia Iacoviello, Girish N. Nadkarni, Erwin P. Bottinger, Ruth J.F. Loos, Stephen B. Ellis, José M. Valdivielso, Marcelino Bermúdez-López, Milica Bozic, Serafí Cambray, Benedicte Stengel, Marie Metzger, Martin Flamant, Pascal Houillier, Jean-Philippe Haymann, Katsuyuki Miura, Akira Okayama, Aya Kadota, Sachiko Tanaka, Nikita Stempniewicz, John Cuddeback, Elizabeth Ciemins, Emily Carbonara, Stephan Dunning, Robert G. Nelson, William C. Knowler, Helen C. Looker, Csaba P. Kovesdy, Keiichi Sumida, Miklos Molnar, Praveen Potukuchi, Michelle Pena, Dick de Zeeuw, David M.J. Naimark, Navdeep Tangri, Takamasa Kayama, Tsuneo Konta, Patrick B. Mark, Jamie P. Traynor, Peter C. Thomson, Colin C. Geddes, Josef Coresh, Shoshana H. Ballew, Ron T. Gansevoort, Morgan E. Grams, Orlando Gutierrez, Anna Köttgen, Andrew S. Levey, Kunihiro Matsushita, Elke Schäffner, Mark Woodward, Luxia Zhang, Jingsha Chen, Yingying Sang, Aditya Surapeneni

Affiliations

¹ University of Tennessee Health Science Center, Memphis, Tennessee (K.S.).
² Icahn School of Medicine at Mount Sinai, New York, New York (G.N.N.).
³ Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland (M.E.G., Y.S., S.H.B., J.C., K.M., A.S.).
⁴ Leicester General Hospital, University Hospitals of Leicester NHS Trust, and University of Leicester, Leicester, United Kingdom (N.B., R.W.M.).
⁵ Royal Prince Alfred Hospital and Kidney Node, University of Sydney, Sydney, New South Wales, Australia (S.J.C.).
⁶ Geisinger Health, Danville, Pennsylvania (A.R.C.).
⁷ University of Naples "Federico II," Naples, Italy (M.C.).
⁸ Providence Sacred Heart Medical Center and Gonzaga University School of Anesthesia, Spokane, Washington (K.B.D.).
⁹ University Medical Center Groningen, University of Groningen, Groningen, the Netherlands (R.T.G.).
¹⁰ ICES and Western University, London, Ontario, Canada (A.X.G.).
¹¹ IRCCS Neuromed, Pozzilli, Italy, and University of Insubria, Varese, Italy (L.I.).
¹² Yamagata University, Yamagata, Japan (T.K., T.K.).
¹³ Memphis Veterans Affairs Medical Center and University of Tennessee Health Science Center, Memphis, Tennessee (C.P.K.).
¹⁴ University of Illinois at Chicago, Chicago, Illinois (J.L.).
¹⁵ Kaiser Permanente, Hawaii Region, and Moanalua Medical Center, Honolulu, Hawaii (B.J.L.).
¹⁶ Paris Saclay University, Paris-Sud University, UVSQ, CESP, INSERM U1018, Villejuif, France (M.M.).
¹⁷ Shiga University of Medical Science Seta-Tsukinowa-cho, Shiga, Japan (K.M.).
¹⁸ Sunnybrook Hospital, University of Toronto, Toronto, Ontario, Canada (D.M.N.).
¹⁹ National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona (R.G.N.).
²⁰ University of Aberdeen, Aberdeen, Scotland (S.S.).
²¹ American Medical Group Association, Alexandria, Virginia (N.S.).
²² University of British Columbia, Vancouver, British Columbia, Canada (M.T.).
²³ Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania (R.R.T.).
²⁴ Queen Elizabeth University Hospital, Glasgow, Scotland (J.P.T.).
²⁵ Institute of Biomedical Research of Lleida and Spanish Research Network for Renal Diseases, Lleida, Spain (J.M.V.).
²⁶ Radboud University Medical Center, Nijmegen, the Netherlands (J.W.).
²⁷ Monash University, Clayton, Victoria, Australia (K.R.P.).
²⁸ University of Groningen, University Medical Center, Groningen, the Netherlands, and The George Institute for Global Health, Sydney, New South Wales, Australia (H.J.H.).

PMID: 32658569
PMCID: PMC7780415
DOI: 10.7326/M20-0529

Abstract

Background: Although measuring albuminuria is the preferred method for defining and staging chronic kidney disease (CKD), total urine protein or dipstick protein is often measured instead.

Objective: To develop equations for converting urine protein-creatinine ratio (PCR) and dipstick protein to urine albumin-creatinine ratio (ACR) and to test their diagnostic accuracy in CKD screening and staging.

Design: Individual participant-based meta-analysis.

Setting: 12 research and 21 clinical cohorts.

Participants: 919 383 adults with same-day measures of ACR and PCR or dipstick protein.

Measurements: Equations to convert urine PCR and dipstick protein to ACR were developed and tested for purposes of CKD screening (ACR ≥30 mg/g) and staging (stage A2: ACR of 30 to 299 mg/g; stage A3: ACR ≥300 mg/g).

Results: Median ACR was 14 mg/g (25th to 75th percentile of cohorts, 5 to 25 mg/g). The association between PCR and ACR was inconsistent for PCR values less than 50 mg/g. For higher PCR values, the PCR conversion equations demonstrated moderate sensitivity (91%, 75%, and 87%) and specificity (87%, 89%, and 98%) for screening (ACR >30 mg/g) and classification into stages A2 and A3, respectively. Urine dipstick categories of trace or greater, trace to +, and ++ for screening for ACR values greater than 30 mg/g and classification into stages A2 and A3, respectively, had moderate sensitivity (62%, 36%, and 78%) and high specificity (88%, 88%, and 98%). For individual risk prediction, the estimated 2-year 4-variable kidney failure risk equation using predicted ACR from PCR had discrimination similar to that of using observed ACR.

Limitation: Diverse methods of ACR and PCR quantification were used; measurements were not always performed in the same urine sample.

Conclusion: Urine ACR is the preferred measure of albuminuria; however, if ACR is not available, predicted ACR from PCR or urine dipstick protein may help in CKD screening, staging, and prognosis.

Primary funding source: National Institute of Diabetes and Digestive and Kidney Diseases and National Kidney Foundation.

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Figures

**Figure 1.**
Relationship between urine protein-to-creatinine (PCR) and urine albumin-to-creatinine (ACR) values in individual cohorts (multicolored lines) and after random effects meta-analysis (thick black line) in the crude model Associations were estimated using log-transformed urine albumin-to-creatinine ratio (ACR) and urine protein-to-creatinine ratio (PCR), with the latter modeled using linear splines with knots at 50 mg/g and 500 mg/g.

See this image and copyright information in PMC

Comment in

From Proteinuria to Albuminuria: Great Expectations for Kidney Failure Risk Prediction.
Harrison TG, Hemmelgarn BR. Harrison TG, et al. Ann Intern Med. 2020 Sep 15;173(6):492-493. doi: 10.7326/M20-4211. Epub 2020 Jul 14. Ann Intern Med. 2020. PMID: 32658572 No abstract available.

References

1. Hemmelgarn BR, Manns BJ, Lloyd A, James MT, Klarenbach S, Quinn RR, et al. Relation between kidney function, proteinuria, and adverse outcomes. JAMA. 2010;303(5):423–9. - PubMed
1. Lea J, Greene T, Hebert L, Lipkowitz M, Massry S, Middleton J, et al. The relationship between magnitude of proteinuria reduction and risk of end-stage renal disease: results of the African American study of kidney disease and hypertension. Arch Intern Med. 2005;165(8):947–53. - PubMed
1. Matsushita K, van der Velde M, Astor BC, Woodward M, Levey AS, de Jong PE, et al. Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis. Lancet. 2010;375(9731):2073–81. - PMC - PubMed
1. Astor BC, Matsushita K, Gansevoort RT, van der Velde M, Woodward M, Levey AS, et al. Lower estimated glomerular filtration rate and higher albuminuria are associated with mortality and end-stage renal disease. A collaborative meta-analysis of kidney disease population cohorts. Kidney Int. 2011;79(12):1331–40. - PMC - PubMed
1. van der Velde M, Matsushita K, Coresh J, Astor BC, Woodward M, Levey A, et al. Lower estimated glomerular filtration rate and higher albuminuria are associated with all-cause and cardiovascular mortality. A collaborative meta-analysis of high-risk population cohorts. Kidney Int. 2011;79(12):1341–52. - PubMed

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Conversion of Urine Protein-Creatinine Ratio or Urine Dipstick Protein to Urine Albumin-Creatinine Ratio for Use in Chronic Kidney Disease Screening and Prognosis : An Individual Participant-Based Meta-analysis

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Conversion of Urine Protein-Creatinine Ratio or Urine Dipstick Protein to Urine Albumin-Creatinine Ratio for Use in Chronic Kidney Disease Screening and Prognosis : An Individual Participant-Based Meta-analysis

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