• 1.

    Holweger K, et al. Accurate measurement of individual glomerular filtration rate in cancer patients: An ongoing challenge. J Cancer Res Clin Oncol 2005; 131:559567. doi: 10.1007/s00432-005-0679-7

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 2.

    Launay-Vacher V, et al. Prevalence of renal insufficiency in cancer patients and implications for anticancer drug management: The Renal Insufficiency and Anticancer Medications (IRMA) study. Cancer 2007; 110:13761384. doi: 10.1002/cncr.22904

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 3.

    Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron 1976; 16:3141. doi: 10.1159/000180580

  • 4.

    Costa E Silva VT, et al. A prospective cross-sectional study estimated glomerular filtration rate from creatinine and cystatin C in adults with solid tumors. Kidney Int 2022; 101:607614. doi: 10.1016/j.kint.2021.12.010

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 5.

    Stevens LA, et al. Evaluation of the modification of diet in renal disease study equation in a large diverse population. J Am Soc Nephrol 2007; 18:27492757. doi: 10.1681/ASN.2007020199

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6.

    Levey AS, Stevens LA. Estimating GFR using the CKD epidemiology collaboration (CKD-EPI) creatinine equation: More accurate GFR estimates, lower CKD prevalence estimates, and better risk predictions. Am J Kidney Dis 2010; 55:622627. doi: 10.1053/j.ajkd.2010.02.337

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 7.

    Williams EH, et al. CamGFR v2: A new model for estimating the glomerular filtration rate from standardized or non-standardized creatinine in patients with cancer. Clin Cancer Res 2021; 27:13811390. doi: 10.1158/1078-0432.CCR-20-3201

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 8.

    Inker LA, et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. N Engl J Med 2012; 367:2029. doi: 10.1056/NEJMoa1114248

  • 9.

    Aapro M, Launay-Vacher V. Importance of monitoring renal function in patients with cancer. Cancer Treat Rev 2012; 38:235240. doi: 10.1016/j.ctrv.2011.05.001

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 10.

    Martin L, et al. Improvement of the Cockcroft-Gault equation for predicting glomerular filtration in cancer patients. Bull Cancer 1998; 85:631636. https://www.jle.com/fr/revues/bdc/e-docs/amelioration_de_lequation_de_cockcroft_gault_pour_predire_le_debit_de_filtration_glomerulaire_chez_les_patients_cancereux_70160/article.phtml?cle_doc=00011210&cle_doc=00011210

    • Search Google Scholar
    • Export Citation
  • 11.

    Wright JG, et al. Estimation of glomerular filtration rate in cancer patients. Br J Cancer 2001; 84:452459. doi: 10.1054/bjoc.2000.1643

  • 12.

    Calvert AH, et al. Carboplatin dosage: Prospective evaluation of a simple formula based on renal function. J Clin Oncol 1989; 7:17481756. doi: 10.1200/JCO.1989.7.11.1748

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 13.

    McMahon BA, Rosner MH. GFR measurement and chemotherapy dosing in patients with kidney disease and cancer. Kidney360 2020; 1:141150. doi: 10.34067/kid.0000952019

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14.

    Poole SG, et al. A comparison of bedside renal function estimates and measured glomerular filtration rate (Tc99mDTPA clearance) in cancer patients. Ann Oncol 2002; 13:949955. doi: 10.1093/annonc/mdf236

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15.

    Stevens LA, et al. Factors other than glomerular filtration rate affect serum cystatin C levels. Kidney Int 2009; 75:652660. doi: 10.1038/ki.2008.638

  • 16.

    Zhu XR, et al. Corticosteroids significantly increase cystatin C levels in the plasma by promoting cystatin C production in rats. Ren Fail 2019; 41:698703. doi: 10.1080/0886022X.2019.1638798

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 17.

    Inker LA, et al. New creatinine- and cystatin C-based equations to estimate GFR without race. N Engl J Med 2021; 385:17371749. doi: 10.1056/NEJMoa2102953

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 18.

    Khan I, et al. Comparison of cystatin C and creatinine-based estimated glomerular filtration rate equations among elderly chronic kidney disease patients attending a tertiary care hospital: A prospective cross-sectional study. Clin Nephrol 2020; 93:217226. doi: 10.5414/CN109573

    • Crossref
    • Search Google Scholar
    • Export Citation

Performance of GFR Estimating Equations in Patients with Solid Tumors

  • 1 Paul E. Hanna, MD, MSc, and Meghan E. Sise, MD, MS, are with the Division of Nephrology, Department of Medicine, Massachusetts General Hospital, Boston.
Full access

Important decisions about diagnosing kidney disease, managing drug dosing, and considering kidney replacement therapy rely on an accurate estimation of the glomerular filtration rate (GFR), especially in patients with cancer (1, 2). Despite its continued use, the Cockcroft-Gault equation (3), originally created to assess kidney function based on serum creatinine in 1976, has significant limitations that may be even greater in patients with cancer who have sarcopenia. To address this, Costa E Silva and colleagues (4) compared the measured GFR using chromium-51-labeled ethylenediamine tetraacetic acid (51Cr-EDTA) clearance in 1200 patients

Important decisions about diagnosing kidney disease, managing drug dosing, and considering kidney replacement therapy rely on an accurate estimation of the glomerular filtration rate (GFR), especially in patients with cancer (1, 2). Despite its continued use, the Cockcroft-Gault equation (3), originally created to assess kidney function based on serum creatinine in 1976, has significant limitations that may be even greater in patients with cancer who have sarcopenia. To address this, Costa E Silva and colleagues (4) compared the measured GFR using chromium-51-labeled ethylenediamine tetraacetic acid (51Cr-EDTA) clearance in 1200 patients with solid tumors to test six GFR estimating equations. They reported both the bias (median of the differences between measured GFR and estimated GFR) and accuracy (1 minus the percentage of GFR estimates within 30% of measured GFR in mL/min/1.73 m2 [1−P30]) of each equation (Table 1). The 2012 Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) equation, using both serum creatinine and cystatin C, performed the best among all equations. Among the GFR estimating equations that used serum creatinine alone, Cockcroft-Gault and 2009 CKD-EPI had the greatest bias, and Cockcroft-Gault had the least accuracy (Table 1).

Table 1

Bias and accuracy of different GFR estimating equations

Table 1

Creatinine is a byproduct of muscle breakdown that lacks both sensitivity and specificity for measuring acute kidney injury (AKI) and CKD. Because creatinine is a muscle-derived biomarker, patients with advanced malignancies, who commonly exhibit muscle wasting, have 1) overestimation of their baseline estimated GFR when relying on creatinine-based equations and 2) underestimation of severity of AKI events when relying on accumulation of creatinine (9). Attempts to overcome these limitations in patients with cancer led to the development of population-specific GFR estimating equations, such as the Martin formula (10), the Wright formula (11), and the Calvert dose-determining formula (12); yet, even these did not generalize well and are not widely used (13, 14). Cystatin C is a low molecular weight protein that is released by all nucleated cells and freely filtered by the glomerulus and is used to estimate GFR. A major limitation of cystatin C is that it can be influenced by concurrent inflammation, history of smoking, obesity independent of the GFR (15), and corticosteroid therapy (16).

In subgroup analyses, the authors showed that several patient-specific factors strongly influenced the accuracy of GFR estimation. Creatinine-based equations were much more likely to overestimate GFR in women and in those with low body mass index (BMI [<25 kg/m2]). In these populations, the CKD-EPI 2012 equation that uses cystatin C alone was most accurate. This suggests that GFR estimation could be personalized based on patient-specific factors such as BMI and sex. The authors also demonstrate that in patients with measured GFR <60 mL/min/1.73 m2, all equations overestimated GFR. Although the new 2021 CKD-EPI race-free equation that uses both creatinine and cystatin C (17) was not used in this study, it would be reasonable to use as a new standard of care.

This serves as a call to action to change practice and personalize our approach to estimating GFR, especially in this vulnerable population of patients with cancer where treatment decisions hinge on accurate assessment of kidney function and in whom the rate of AKI is so high (18). Inaccurate assessments of kidney function could potentially preclude patients from lifesaving treatments, expose them to toxic drug levels, and delay diagnosis and treatment of AKI. Future studies are needed to determine the performance of the 2021 equations and determine the best and most cost-effective strategies for implementation of these important findings into routine cancer care.

References

  • 1.

    Holweger K, et al. Accurate measurement of individual glomerular filtration rate in cancer patients: An ongoing challenge. J Cancer Res Clin Oncol 2005; 131:559567. doi: 10.1007/s00432-005-0679-7

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 2.

    Launay-Vacher V, et al. Prevalence of renal insufficiency in cancer patients and implications for anticancer drug management: The Renal Insufficiency and Anticancer Medications (IRMA) study. Cancer 2007; 110:13761384. doi: 10.1002/cncr.22904

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 3.

    Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron 1976; 16:3141. doi: 10.1159/000180580

  • 4.

    Costa E Silva VT, et al. A prospective cross-sectional study estimated glomerular filtration rate from creatinine and cystatin C in adults with solid tumors. Kidney Int 2022; 101:607614. doi: 10.1016/j.kint.2021.12.010

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 5.

    Stevens LA, et al. Evaluation of the modification of diet in renal disease study equation in a large diverse population. J Am Soc Nephrol 2007; 18:27492757. doi: 10.1681/ASN.2007020199

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6.

    Levey AS, Stevens LA. Estimating GFR using the CKD epidemiology collaboration (CKD-EPI) creatinine equation: More accurate GFR estimates, lower CKD prevalence estimates, and better risk predictions. Am J Kidney Dis 2010; 55:622627. doi: 10.1053/j.ajkd.2010.02.337

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 7.

    Williams EH, et al. CamGFR v2: A new model for estimating the glomerular filtration rate from standardized or non-standardized creatinine in patients with cancer. Clin Cancer Res 2021; 27:13811390. doi: 10.1158/1078-0432.CCR-20-3201

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 8.

    Inker LA, et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. N Engl J Med 2012; 367:2029. doi: 10.1056/NEJMoa1114248

  • 9.

    Aapro M, Launay-Vacher V. Importance of monitoring renal function in patients with cancer. Cancer Treat Rev 2012; 38:235240. doi: 10.1016/j.ctrv.2011.05.001

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 10.

    Martin L, et al. Improvement of the Cockcroft-Gault equation for predicting glomerular filtration in cancer patients. Bull Cancer 1998; 85:631636. https://www.jle.com/fr/revues/bdc/e-docs/amelioration_de_lequation_de_cockcroft_gault_pour_predire_le_debit_de_filtration_glomerulaire_chez_les_patients_cancereux_70160/article.phtml?cle_doc=00011210&cle_doc=00011210

    • Search Google Scholar
    • Export Citation
  • 11.

    Wright JG, et al. Estimation of glomerular filtration rate in cancer patients. Br J Cancer 2001; 84:452459. doi: 10.1054/bjoc.2000.1643

  • 12.

    Calvert AH, et al. Carboplatin dosage: Prospective evaluation of a simple formula based on renal function. J Clin Oncol 1989; 7:17481756. doi: 10.1200/JCO.1989.7.11.1748

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 13.

    McMahon BA, Rosner MH. GFR measurement and chemotherapy dosing in patients with kidney disease and cancer. Kidney360 2020; 1:141150. doi: 10.34067/kid.0000952019

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14.

    Poole SG, et al. A comparison of bedside renal function estimates and measured glomerular filtration rate (Tc99mDTPA clearance) in cancer patients. Ann Oncol 2002; 13:949955. doi: 10.1093/annonc/mdf236

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15.

    Stevens LA, et al. Factors other than glomerular filtration rate affect serum cystatin C levels. Kidney Int 2009; 75:652660. doi: 10.1038/ki.2008.638

  • 16.

    Zhu XR, et al. Corticosteroids significantly increase cystatin C levels in the plasma by promoting cystatin C production in rats. Ren Fail 2019; 41:698703. doi: 10.1080/0886022X.2019.1638798

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 17.

    Inker LA, et al. New creatinine- and cystatin C-based equations to estimate GFR without race. N Engl J Med 2021; 385:17371749. doi: 10.1056/NEJMoa2102953

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 18.

    Khan I, et al. Comparison of cystatin C and creatinine-based estimated glomerular filtration rate equations among elderly chronic kidney disease patients attending a tertiary care hospital: A prospective cross-sectional study. Clin Nephrol 2020; 93:217226. doi: 10.5414/CN109573

    • Crossref
    • Search Google Scholar
    • Export Citation
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