Modification of diet in renal disease and Cockcroft–Gault formulas do not predict mortality (ZODIAC-6)

  1. H. J. G. Bilo1,2,
  2. S. J. J. Logtenberg1,
  3. H. Joosten1,
  4. K. H. Groenier2,3,
  5. L. J. Ubink-Veltmaat4,
  6. N. Kleefstra1,5

Article first published online: 14 MAR 2009

DOI: 10.1111/j.1464-5491.2009.02709.x

Issue

Diabetic Medicine

Diabetic Medicine

Volume 26, Issue 5, pages 478–482, May 2009

Additional Information

How to Cite

Bilo, H. J. G., Logtenberg, S. J. J., Joosten, H., Groenier, K. H., Ubink-Veltmaat, L. J. and Kleefstra, N. (2009), Modification of diet in renal disease and Cockcroft–Gault formulas do not predict mortality (ZODIAC-6). Diabetic Medicine, 26: 478–482. doi: 10.1111/j.1464-5491.2009.02709.x

Author Information

  1. 1

    Diabetes Centre, Isala Clinics, Zwolle, The Netherlands

  2. 2

    Department of Internal Medicine, University of Groningen, Groningen, The Netherlands

  3. 3

    Department of General Practice, University Medical Center Groningen, Groningen, The Netherlands

  4. 4

    General Practice ‘t Veen, Hattem, Zwolle, The Netherlands

  5. 5

    Langerhans Medical Research Group, The Netherlands

*Henk J.G. Bilo, Diabetes Centre, Isala Clinics, P.O. Box 10400, 8000 G.K., Zwolle, The Netherlands. E-mail: h.j.g.bilo@isala.nl

Publication History

  1. Issue published online: 11 MAY 2009
  2. Article first published online: 14 MAR 2009
  3. Accepted 21 February 2009

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Keywords:

  • glomerular filtration rate;
  • mortality;
  • proportional hazards models;
  • risk assessment;
  • Type 2 diabetes mellitus

Abstract

Aims  An inverse relationship between estimates of renal function, with formulas such as the Modification of diet in renal disease (MDRD) study equation or the Cockcroft–Gault formula, and mortality has been suggested. These formulas both contain the variables sex, serum creatinine and age and the latter also contains body weight. We investigated whether these formulas predict mortality better than the variables they contain together in patients with Type 2 diabetes.

Methods  In 1998, 1143 primary care patients with Type 2 diabetes participated in the Zwolle Outpatient Diabetes project Integrating Available Care (ZODIAC) Study, in the Netherlands. Clinical and laboratory data were collected at baseline. Life status was assessed after 6 years. We used Cox proportional hazard modelling to investigate the association between estimates of renal function (continuous data) and the variables they contain and mortality, adjusting for confounders. Both formulas were compared with models consisting of the variables present in the formulas. Predictability was assessed using Bayesian information criterion (BIC) and Harrell’s C statistics.

Results  At follow-up, 335 patients had died. All variables, except sex, influenced mortality. Predictive capability, indicated by lower BIC values and higher Harrell’s C values, was up to 10% better for models containing the separate variables as compared with Cockcroft–Gault or MDRD.

Conclusions  Using estimates of renal function to assess mortality risk decreases predictability as compared with the combination of the risk factors they contain. These formulas, therefore, could be used to estimate renal function; however, they should not be used as a tool to predict mortality risk.

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