Original Investigation
Pathogenesis and Treatment of Kidney Disease
The Role of Cystatin C in Improving GFR Estimation in the General Population

https://doi.org/10.1053/j.ajkd.2011.09.001Get rights and content

Background

The equations used to estimate glomerular filtration rate (GFR) based on serum creatinine level are limited by their dependence on muscle mass. Although cystatin C level predicts clinical outcomes better than creatinine level in the general population, its role in estimating GFR in the reference range is unclear. Cystatin C level is not influenced by muscle mass, but by several other non-GFR determinants. We investigated whether regression models using cystatin C level alone or in combination with creatinine level in principle would improve GFR estimation in the general population compared with models using creatinine level alone.

Study Design

Study of diagnostic accuracy.

Setting & Participants

A representative sample (n = 1,621; aged 50-62 years) of the general population in Tromsø, Norway, without coronary heart disease, stroke, diabetes mellitus, or kidney disease. Individuals had participated in the Renal Iohexol Clearance Survey (RENIS-T6), part of the sixth Tromsø Study.

Index Test

Performance of multiple linear and fractional polynomial regression models with plasma creatinine and/or cystatin C levels as independent variables and measured GFR as a dependent variable.

Reference Test

Plasma iohexol clearance.

Other Measurements

Creatinine measured with an enzymatic method. Cystatin C measured with a particle-enhanced turbidimetric immunoassay.

Results

In internal validation of models with cystatin C, creatinine, or both levels, percentages of GFR estimates within 10% of measured GFR were 61% (95% CI, 58%-63%), 62% (95% CI, 59%-64%), and 68% (95% CI, 65%-70%), respectively. Models with either cystatin C or creatinine level had very similar precision and ability to detect GFR <90 mL/min/1.73 m2, whereas models based on both markers performed better.

Limitations

Only middle-aged individuals of European ancestry were investigated. Lack of standardization between cystatin C assays. No external validation of regression models.

Conclusions

Models based on cystatin C alone are not superior to those based on creatinine, but models based on both markers can improve GFR estimation in the reference range.

Section snippets

Participants

RENIS-T6 is a substudy of the sixth Tromsø Study (Tromsø 6). In the main part of Tromsø 6, a representative sample of 12,984 persons of the 65,286 inhabitants of Tromsø municipality in Northern Norway were studied with questionnaires and a wide range of biochemical and other measurements between October 2007 and December 2008. Among those invited to participate in the main part of Tromsø 6 was a random sample of 40% of persons aged 50-59 years and all persons aged 60-62 years; 5,464 persons in

Results

Of 1,632 investigated persons, 5 were excluded because their iohexol-clearance measurements were technical failures, leaving 1,627 persons included in the RENIS-T6 cohort. In the present study, 6 of these were excluded because they used prednisolone. Accordingly, we examined 1,621 persons (Fig 1), whose characteristics are listed in Table 1. A comparison between the 1,627 participants in the RENIS-T6 cohort and all 2,825 eligible persons has been reported previously and showed that the cohort

Discussion

In the middle-aged general population, we found that models with either cystatin C or creatinine level had almost identical fit to GFR measurements. Including both markers in the same model improved fit significantly, but little was gained by including height and body weight or using nonlinear modeling with multivariable fractional polynomials (Table 2).

The internal validation found almost identical precision and accuracy for models with either cystatin C or creatinine level and significant

Acknowledgements

We thank Britt-Ann Winther Eilertsen, Bjørg Skog Høgset, Saskia van Heusden, and the rest of the staff at the Clinical Research Unit (University Hospital of North Norway) for performing the study; Harald Strand and the staff at the Department of Medical Biochemistry (University Hospital of North Norway) for HPLC analyses of iohexol; Inger Sperstad and Ingrid Dorthea Sandstad (Clinical Research Centre, University Hospital of North Norway) for database support; and Tom Wilsgaard, Sriharan

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    Originally published online October 17, 2011.

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