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Precision Medicine and Imaging

CamGFR v2: A New Model for Estimating the Glomerular Filtration Rate from Standardized or Non-standardized Creatinine in Patients with Cancer

Edward H. Williams, Thomas R. Flint, Claire M. Connell, Daniel Giglio, Hassal Lee, Taehoon Ha, Eva Gablenz, Nicholas J. Bird, James M.J. Weaver, Harry Potts, Cameron T. Whitley, Michael A. Bookman, Andy G. Lynch, Hannah V. Meyer, Simon Tavaré and Tobias Janowitz
Edward H. Williams
1Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, England, United Kingdom.
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Thomas R. Flint
2Cambridge University Hospitals NHS Foundation Trust, Cambridge, England, United Kingdom.
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Claire M. Connell
1Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, England, United Kingdom.
3University of Cambridge, Cambridge, England, United Kingdom.
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Daniel Giglio
4Department of Oncology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.
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Hassal Lee
5University of Cambridge School of Clinical Medicine, Cambridge, England, United Kingdom.
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Taehoon Ha
6Cold Spring Harbor Laboratory, Cold Spring Harbor, New York.
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Eva Gablenz
6Cold Spring Harbor Laboratory, Cold Spring Harbor, New York.
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Nicholas J. Bird
2Cambridge University Hospitals NHS Foundation Trust, Cambridge, England, United Kingdom.
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James M.J. Weaver
7The Christie NHS Foundation Trust, Manchester, England, United Kingdom.
8University of Manchester, Manchester, England, United Kingdom.
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Harry Potts
5University of Cambridge School of Clinical Medicine, Cambridge, England, United Kingdom.
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Cameron T. Whitley
5University of Cambridge School of Clinical Medicine, Cambridge, England, United Kingdom.
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Michael A. Bookman
9Gynecologic Oncology Therapeutics, Kaiser Permanente, San Francisco, California.
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Andy G. Lynch
1Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, England, United Kingdom.
10School of Medicine, University of St Andrews, St Andrews, Scotland, United Kingdom.
11School of Mathematics and Statistics, University of St Andrews, St Andrews, Scotland, United Kingdom.
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Hannah V. Meyer
6Cold Spring Harbor Laboratory, Cold Spring Harbor, New York.
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Simon Tavaré
1Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, England, United Kingdom.
12Columbia University, New York, New York.
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Tobias Janowitz
6Cold Spring Harbor Laboratory, Cold Spring Harbor, New York.
13Northwell Health, New York, New York.
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  • For correspondence: Janowitz@cshl.edu
DOI: 10.1158/1078-0432.CCR-20-3201
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Abstract

Purpose: Management of patients with cancer, specifically carboplatin dosing, requires accurate knowledge of glomerular filtration rate (GFR). Direct measurement of GFR is resource limited. Available models for estimated GFR (eGFR) are optimized for patients without cancer and either isotope dilution mass spectrometry (IDMS)- or non-IDMS–standardized creatinine measurements. We present an eGFR model for patients with cancer compatible with both creatinine measurement methods.

Experimental Design: GFR measurements, biometrics, and IDMS- or non-IDMS–standardized creatinine values were collected for adult patients from three cancer centers. Using statistical modeling, an IDMS and non-IDMS creatinine-compatible eGFR model (CamGFR v2) was developed. Its performance was compared with that of the existing models Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), Modification of Diet in Renal Disease (MDRD), Full Age Spectrum (FAS), Lund–Malmö revised, and CamGFR v1, using statistics for bias, precision, accuracy, and clinical robustness.

Results: A total of 3,083 IDMS- and 4,612 non-IDMS–standardized creatinine measurements were obtained from 7,240 patients. IDMS-standardized creatinine values were lower than non-IDMS–standardized values in within-center comparisons (13.8% lower in Cambridge; P < 0.0001 and 19.3% lower in Manchester; P < 0.0001), and more consistent between centers. CamGFR v2 was the most accurate [root-mean-squared error for IDMS, 14.97 mL/minute (95% confidence interval, 13.84–16.13) and non-IDMS, 15.74 mL/minute (14.86–16.63)], most clinically robust [proportion with >20% error of calculated carboplatin dose for IDMS, 0.12 (0.09–0.14) and non-IDMS, 0.17 (0.15–0.2)], and least biased [median residual for IDMS, 0.73 mL/minute (−0.68 to 2.2) and non-IDMS, −0.43 mL/minute (−1.48 to 0.91)] eGFR model, particularly when eGFR was larger than 60 ml/minute.

Conclusions: CamGFR v2 can utilize IDMS- and non-IDMS–standardized creatinine measurements and outperforms previous models. CamGFR v2 should be examined prospectively as a practice-changing standard of care for eGFR-based carboplatin dosing.

Footnotes

  • Note: Supplementary data for this article are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/).

  • Clin Cancer Res 2021;XX:XX–XX

  • Received August 15, 2020.
  • Revision received October 27, 2020.
  • Accepted December 4, 2020.
  • Published first December 10, 2020.
  • ©2020 American Association for Cancer Research.

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This OnlineFirst version was published on January 12, 2021
doi: 10.1158/1078-0432.CCR-20-3201

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CamGFR v2: A New Model for Estimating the Glomerular Filtration Rate from Standardized or Non-standardized Creatinine in Patients with Cancer
Edward H. Williams, Thomas R. Flint, Claire M. Connell, Daniel Giglio, Hassal Lee, Taehoon Ha, Eva Gablenz, Nicholas J. Bird, James M.J. Weaver, Harry Potts, Cameron T. Whitley, Michael A. Bookman, Andy G. Lynch, Hannah V. Meyer, Simon Tavaré and Tobias Janowitz
Clin Cancer Res January 12 2021 DOI: 10.1158/1078-0432.CCR-20-3201

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CamGFR v2: A New Model for Estimating the Glomerular Filtration Rate from Standardized or Non-standardized Creatinine in Patients with Cancer
Edward H. Williams, Thomas R. Flint, Claire M. Connell, Daniel Giglio, Hassal Lee, Taehoon Ha, Eva Gablenz, Nicholas J. Bird, James M.J. Weaver, Harry Potts, Cameron T. Whitley, Michael A. Bookman, Andy G. Lynch, Hannah V. Meyer, Simon Tavaré and Tobias Janowitz
Clin Cancer Res January 12 2021 DOI: 10.1158/1078-0432.CCR-20-3201
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