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Agreement and Precision Analyses
of Various Estimated Glomerular
Filtration Rate Formulae in Cancer
Patients
Wiwat Chancharoenthana
1,2*, Salin Wattanatorn3, Somratai Vadcharavivad
4,
Somchai Eiam-Ong3 & Asada Leelahavanichkul2,5*
The accuracy of the estimated glomerular ltration rate (eGFR) in cancer patients is very important for
dose adjustments of anti-malignancy drugs to reduce toxicities and enhance therapeutic outcomes.
Therefore, the performance of eGFR equations, including their bias, precision, and accuracy, was
explored in patients with varying stages of chronic kidney disease (CKD) who needed anti-cancer
drugs. The reference glomerular ltration rate (GFR) was assessed by the 99mTc-diethylene triamine
penta-acetic acid (99mTc-DTPA) plasma clearance method in 320 patients and compared with the GFRs
estimated by i) the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation, ii) the
unadjusted for body surface area (BSA) CKD-EPI equation, iii) the re-expressed Modication of Diet in
Renal Disease (MDRD) study equation with the Thai racial factor, iv) the Thai eGFR equation, developed
in CKD patients, v) the 2012 CKD-EPI creatinine-cystatin C, vi) the Cockcroft-Gault formula, and vii)
the Janowitz and Williams equations for cancer patients. The mean reference GFR was 60.5 ± 33.4 mL/
min/1.73 m2. The bias (mean error) values for the estimated GFR from the CKD-EPI equation, BSA-
unadjusted CKD-EPI equation, re-expressed MDRD study equation with the Thai racial factor, and
Thai eGFR, 2012 CKD-EPI creatinine-cystatin-C, Cockcroft-Gault, and Janowitz and Williams equations
were −2.68, 1.06, −7.70, −8.73, 13.37, 1.43, and 2.03 mL/min, respectively, the precision (standard
deviation of bias) values were 6.89, 6.07, 14.02, 11.54, 20.85, 10.58, and 8.74 mL/min, respectively,
and the accuracy (root-mean square error) values were 7.38, 6.15, 15.97, 14.16, 24.74, 10.66, and
8.96 mL/min, respectively. In conclusion, the estimated GFR from the BSA-unadjusted CKD-EPI
equation demonstrated the least bias along with the highest precision and accuracy. Further studies
on the outcomes of anti-cancer drug dose adjustments using this equation versus the current standard
equation will be valuable.
e coexistence of chronic kidney disease (CKD) and cancer is common due to the increased incidence of cancer in
patients with CKD1 and the fact that CKD worsens the mortality rate of cancer patients2. A precise GFR assessment
is fundamental to several aspects of cancer therapy, including chemotherapy dose adjustment, decisions regarding
surgery eligibility with perioperative management, and preparation of long-term care. An underestimated GFR in a
patient with cancer could lead to inappropriate care, such as in the case of a patient being deemed ineligible for both
medical chemotherapy and surgical treatment because their GFR is too low. Conversely, overestimation of the GFR
could put a patient at unnecessary risk of drug overdose and unfavorable complications. Because most cancer chem-
otherapeutic agents are excreted mainly through the kidneys, the accuracy of the estimated glomerular ltration rate
(eGFR) in patients with cancer is crucial to balancing treatment ecacy and the risk of adverse events. Although
1Nephrology Research Unit, Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol
University, Bangkok, Thailand. 2Immunology Unit, Department of Microbiology, Faculty of Medicine, Chulalongkorn
University, Bangkok, Thailand. 3Division of Nephrology, Department of Medicine, Faculty of Medicine,
Chulalongkorn University, Bangkok, Thailand. 4Department of Pharmacy Practice, Faculty of Pharmaceutical
Sciences, Chulalongkorn University, Bangkok, Thailand. 5Translational Research in Inammation and Immunology
Research Unit (TRIRU), Department of Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok,
Thailand. *email: wiwat.cha@mahidol.ac.th; a_leelahavanit@yahoo.com
OPEN
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the eGFR calculated from serum creatinine (SCr) is widely used in general practice, overestimation of the GFR
due to a patient’s reduced muscle mass and food intake due to malignancy is very common. Despite the increased
accuracy of eGFRs obtained by determining the measured GFR (mGFR) using the clearance of exogenous ltration
markers, this method has not been widely used due to the necessity of a 24-hour urine collection. Indeed, a standard
reference for the eGFR for chemotherapeutic agent dose-adjustments remains undecided. e International Society
of Geriatric Oncology preferred eGFRs using the Modication of Diet in Renal Disease (MDRD) equation over
the Cockcro-Gault equation for patients over 65 years old. Nevertheless, the equation from the Chronic Kidney
Disease Epidemiology Collaboration (CKD-EPI) in a recent large-scale, retrospective study appeared to be superior
to the MDRD equation for the eGFR assessment in patients with cancer3.
In general, a consensus of the international guideline group of KDIGO (Kidney Disease: Improving Global
Outcomes) recommends creatinine-based equations for initial testing, with other conrmatory tests for the esti-
mation of kidney function in CKD patients4. Similarly, the Society of Geriatric Oncology guidelines prefer mGFR
in anti-cancers that are mainly excreted through the kidney (or with apparent nephrotoxicity) or in cases of
possibly inaccurate eGFRs5. It is important to recognize that both the MDRD and the CKD-EPI equations were
developed using data from CKD patients, from which patients with malignancy are excluded6–11. Patients with
malignancy, in contrast to those with CKD alone, mostly suer from more severe sarcopenia, resulting in lower
SCr (due to less creatinine production) and overestimated GFRs. As such, accurately estimated renal function is
likely necessary for the proper adjustment of cancer chemotherapy. Although the MDRD and CKD-EPI equa-
tions are widely used to predict the GFR in the United States and Europe, some corrections are necessary for other
ethnic groups, as is the case for the coecient factor for the isotope-dilution mass-spectrometry (IDMS) tracer
in the re-expressed MDRD equation proposed as 1.129 for the ai population10. However, the validation of the
eGFR derived from these equations in ai patients with cancer has not yet been investigated.
Moreover, serum cystatin C (CysC) is considered a potential replacement for SCr as a ltration marker, but the
correlation between the eGFRs derived from CysC and SCr are still uncertain12–14. In addition, increased serum
CysC levels found in both solid and hematologic malignancies are likely related to the tumor’s nature as a cysteine
protease inhibitor15–17. No studies have examined whether an equation based on serum CysC would improve GFR
estimation in cancer patients compared to the estimates obtained by other equations. erefore, the aim of the
present study was to investigate the agreement and precision of the currently published eGFR formulae, including
the CKD-EPI7, the body surface area (BSA)-unadjusted CKD-EPI, the re-expressed MDRD study equation with
the ai racial factor10,18, the ai eGFR10, the 2012 CKD-EPI creatinine-cystatin C13, the Cockcro-Gault19, and
the most recent cancer patient-derived eGFR equation by Janowitz and Williams3, compared to the standard GFR
measurement by 99mTc-DTPA.
Materials and Methods
Study design and patient selection. The study was performed in compliance with the Helsinki
Declaration. All participants were informed and provided written informed consent to participate in this study,
which was approved by the Human Research Ethics Committee of Chulabhorn Research Institute (No. 017/2559)
and local institutional review boards. e inclusion criteria were adults aged 18–70 years old with the following
conditions: (i) pathologically or cytologically proven solid or hematologic malignancy with a performance status
according to the Eastern Cooperative Oncology Group (ECOG) of 0–1 and ii) CKD in stable condition at various
stages (G1–G5) according to the KDIGO criteria4. e exclusion criteria were as follows: i) history of active med-
ical or surgical treatment for related malignancy within the past 6 months; (ii) acute deterioration of malignancy
or related complications, including gastrointestinal bleeding, infection, severe malnutrition with an edematous
state, acute kidney injury superimposed on CKD, congestive heart failure, and arterial or venous thrombosis; (iii)
dialysis dependence; (iv) amputation; (v) breastfeeding or pregnancy; (vi) end-of-life status; (vii) current hospi-
talization; and (viii) current use of medications with SCr interference, including ascorbic acid, corticosteroids,
trimethoprim, cimetidine, ucytosine, methyldopa, and levodopa.
Reference GFR measurement. The reference GFR in the present study was determined by the
99mTc-diethylene triamine penta-acetic Acid (99mTc-DTPA) plasma clearance method with a radiopurity of >95%
and the percentage bound to plasma protein <5%. e reference GFR by 99mTc-DTPA plasma clearance was read
by a radiologist who was blinded to the clinical data. All participants were measured for plasma radioactivity
of 99mTc-DTPA at 5, 30, 60, 120, 180, and 240 minutes aer a single intravenous bolus of 99mTc-DTPA, following
the institutional protocol. en, plasma radioactive activities were plotted as a function of time to create a time–
activity curve to calculate the GFR normalized by BSA20 as well as the measured GFR (mGFR) according to the
following equation (D, dosage of drug injected; t, time of blood sampling):21
∫
=−=∞ct t
GFR
D
area undertimeactivitycurve
D
()d
0
Measurements of serum creatinine, serum cystatin C, and the 24-hour urine creatinine clearance.
e serum creatinine (SCr) of individuals was evaluated by an enzymatic assay with the COBAS INTRGRA®
400 plus autoanalyzer (Roche Diagnostic, Indianapolis, IN, USA) adjusted with a traceable high-level IDMS
reference. Serum cystatin C (CysC) was measured by an automated particle-enhanced turbidimetric immuno-
assay (PETIA) on an ARCHITECT AEROSET analyzer (Abbott Diagnostics, IL, USA). e coecient of var-
iation for the serum CysC assay was 2.1%. Both SCr and serum CysC were measured within 30 days of the
99mTc-DTPA–reference GFR measurement. No patient-identiable data were used. Anonymized data included
age, sex, height, weight, BSA, blood pressure, SCr, serum CysC, and serum albumin, all measured on the same
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day. Body composition was assessed by bioimpedance analysis using a Body Composition Analyzer (InBody 230,
Biospace Corp., Seoul, Korea).
Evaluation of renal function by the eGFR. Seven dierent commonly used methods of GFR estima-
tion were tested in this study, including the re-expressed MDRD study equation with the ai racial factor,
the CKD-EPI equation with and without the BSA adjustment, and the 2012 CKD-EPI creatinine-cystatin C,
Cockcro-Gault, ai eGFR, and Janowitz and Williams equations, as shown in Table1. It is interesting to note
that the estimated GFR calculated from all of the selected equations, except the Janowitz and Williams equations
and Cockcro-Gault equation, are already adjusted for BSA by intrinsic design; therefore the unit is already
expressed as “mL/min/1.73 m2” without the necessity for BSA adjustment in calculated eGFR values”. e units
of the Janowitz and Williams equations and estimated creatinine clearance by Cockcro-Gault equation express
as “mL/min”3,19. In addition, a BSA-unadjusted GFR for those equations are calculated by the following formulae:
BSA-unadjusted GFR (mL/min) = eGFR (mL/min/1.73 m2) x [BSA (m2)/1.73].
Statistical analysis. e baseline characteristics of the patients are presented as the mean ± standard devia-
tion (SD). Other data are presented as median ± interquartile ranges (IQR). Student’s t-test or the Mann–Whitney
U test and the χ2 or Fischer’s exact test were conducted to compare continuous variables and categorical variables,
respectively. Bland-Altman plots were used to assess the agreement between the reference GFR and eGFR22. e
dierence between the reference GFR and eGFR (reference GFR minus eGFR) was also calculated. e per-
formances of the eGFR equations were evaluated for bias and precision. Bias measurements were expressed as
the mean error (ME)23. Meanwhile, precision was dened as the standard deviation (SD) of the mean absolute
dierence24. Accuracy was dened as the root-mean square error (RMSE), which was calculated according to the
following formula (n represents the sample size):25
=∑−
=
RMSE (P O)
n
iii
1
n2
In addition to the RMSE, the accuracy of the equations was also calculated using the percentage of the eGFR
falling within the range of 10%, 15%, and 30% of the reference GFR. Statistical analyses were performed using
STATA version 13.1 (StataCorp., College Station, TX, USA). A p-value < 0.05 was considered a statistically sig-
nicant dierence.
Results
Participants’ baseline characteristics. e patient characteristics are summarized in Table2. A total of
320 cancer patients were studied, of which 299 (93.4%) and 21 (6.6%) patients had solid malignancy and hemato-
logic malignancy, respectively. e median 99mTc-DTPA clearance (the reference GFR) was 50.4 mL/min/1.73 m2
(interquartile range [IQR] from 32.6 to 86.6 mL/min/1.73 m2), with almost 80% of patients categorized with
stages G1–G3b of chronic kidney disease (CKD) according to the KDIGO classication. Notably, there was no
participant with an extreme GFR (i.e., greater than 150 mL/min/1.73 m2) during the observation period. e aver-
age body mass index (BMI) and body surface area (BSA) were 21.6 ± 3.1 kg/m2 and 1.68 ± 0.2 m2, respectively.
e mean serum creatinine (SCr) was 2.5 ± 1.6 mg/dL (95% condence interval [CI] of 1.48 to 3.29 mg/dL). In
eGFR equations [ref.] Gender SCr Formulas
CKD-EPI7
Female CrEnz ≤0.7 mg/
dL 144 × (CrEnz/0.7)−0.329 × (0.993)Age
Female CrEnz >0.7 mg/
dL 144 × (CrEnz/0.7)−1.209 × (0.993)Age
Male CrEnz ≤0.9 mg/
dL 141 × (CrEnz/0.9)−0.411 × (0.993)Age
Male CrEnz >0.9 mg/
dL 141 × (CrEnz/0.9)−1.209 × (0.993)Age
BSA-unadjusted CKD-EPI — CrEnz eGFR (from CKD-EPI, in mL/min/1.73 m2) × BSA (in m2) /1.73
Re-expressed MDRD study with the ai racial factor10 — CrEnz 175 × (CrEnz)−1.154 × (Age)−0.203 × (0.742 if female) × (1.129 if ai)
ai eGFR10 — CrEnz 375.5 × (CrEnz)−0.848 × (Age)−0.364 × (0.712 if female)
2012 CKD-EPI creatinine-cystatin C13 — —
135 × min(CrEnz/κ, 1)α × max(CrEnz/κ, 1)−0.601 × min(CysC/0.8, 1)−0.375 × max(CysC/0.8,
1)−0.711 × 0.995Age [×0.969 if female] [×1.08 if black]
where κ is 0.7 for females and 0.9 for males, α is −0.248 for females and −0.207 for males, min
indicates the minimum of Scr/κ or 1, and max indicates the maximum of Scr/κ or 1.
Cockcro-Gault19 — CrEnz [(140–Age) × BW/CrEnz × 72] × (0.85 if female)
Janowitz & Williams3— — =. +. +. −. −.
+. −. ×+.+
.=
GFR18140 001914Age 47328BSA 37162 log(Cr )09142 log(Cr )
10628 log(Cr )00297Age BSA(00202 00125Age)[if Sexmale]
Enz Enz
2
Enz
3
Table 1. Estimated glomerular ltration rate (eGFR) equations used in the present study. Age units are years.
BSA, body surface area (with units of m2, calculated using the DuBois equation); BW, body weight (with units of
kilograms); CKD-EPI, Chronic Kidney Disease Epidemiology Collaboration; CrEnz, serum creatinine measured
by enzymatic method (with units of mg/dL); CysC, serum cystatin C (with units of mg/L); eGFR, estimated
glomerular ltration rate; MDRD, Modication of Diet in Renal Disease; ref., reference; SCr, serum creatinine.
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addition, the median muscle mass and so lean mass were 22.5 ± 5.8 and 39.6 ± 8.7 kg, respectively, which was
signicantly lower than those in normal-weight and lean populations26 (p < 0.01).
Dierence between the reference GFR and the GFR estimated from various equations. e
performances of seven published models of estimated GFR (eGFR) (see Methods) in patients with cancer were
compared with those of the reference GFR. Among them, the eGFR from the BSA-unadjusted CKD-EPI equa-
tion demonstrated the greatest accuracy according to the root-mean square error (RMSE) (6.15 mL/min; 95%
CI, 5.82 to 7.61 mL/min) with the least bias (mean error [ME], 1.06 mL/min; 95% limits of agreement, −10.83
to 12.95 mL/min). e novel model of the Janowitz and Williams equation was the third most accurate and least
biased model for the eGFR; the RMSE and ME were 8.96 mL/min (95% CI, 6.96 to 9.77 mL/min) and 2.03 mL/
min (95% limits of agreement, −15.11 to 19.16 mL/min), respectively. For the re-expressed MDRD study equa-
tion with the ai racial factor, the RMSE and ME were 15.97 mL/min (95% CI, 14.96 to 17.38 mL/min) and
−7.70 mL/min (95% limits of agreement, −35.17 to 19.78 mL/min), respectively. For the ai eGFR equation,
the RMSE and ME were 14.16 mL/min (95% CI, 13.08 to 16.31 mL/min) and −8.73 mL/min (95% limits of agree-
ment, −31.36 to 13.89 mL/min), respectively. Notably, the 2012 CKD-EPI creatinine-cystatin C equation demon-
strated the most bias with the least accuracy compared with the other equations (Table3). We also determined the
eect of adjusting BSA on various estimated GFR accuracy (RMSE) as shown in Table4.
Diagnostic performance of various estimated GFR equations compared to the reference GFR.
e agreement between the measurements by Bland-Altman and residual plots indicated that the BSA-unadjusted
CKD-EPI equation showed the most accurate, least biased, and least heteroscedastic results, i.e., the most con-
stant variance in dierent subpopulations, compared to those from the other equations (Fig.1). Regarding sex
dierences, the BSA-unadjusted CKD-EPI equation demonstrated the most homogeneity between male and
Characteristics All
(n = 320) Female
(n = 154) Male
(n = 166)
Age (years) 55 ± 16.4 52 ± 15.3 57 ± 13.8
Weight (kg) 50.5 ± 13.8 48 ± 12.1 53 ± 14.5
Height (m) 1.65 ± 0.2 1.57 ± 0.1 1.68 ± 0.2
BMI (kg/m2) 21.6 ± 3.1 18.8 ± 1.3 20.3 ± 3.6
BSA (m2) 1.68 ± 0.2 1.63 ± 0.2 1.72 ± 0.2
Muscle mass (kg) 22.5 ± 5.8 19.8 ± 3.8 21.9 ± 10.8
So lean mass (kg) 39.6 ± 8.7 38.6 ± 4.4 41.3 ± 8.0
Body fat mass (kg) 10.4 ± 9.6 10.7 ± 8.1 11.8 ± 4.2
Fat free mass (kg) 41.3 ± 7.3 40.8 ± 2.7 41.4 ± 7.7
Proteinuria (g/day) 0.42 ± 0.5 0.42 ± 0.3 0.43 ± 0.6
Blood urea nitrogen (mg/dL) 27.3 ± 19.4 25.7 ± 18.2 30.8 ± 20.4
Serum creatinine (mg/dL) 2.5 ± 1.6 2.4 ± 1.2 2.6 ± 1.7
Serum albumin (g/dL) 2.6 ± 1.7 2.5 ± 1.8 2.6 ± 1.5
Mean arterial blood pressure (mmHg) 72.6 ± 11.6 71.8 ± 12.4 72.1 ± 14.2
Hypertension (n, (%)) 33 (10.3) 14 (9.1) 19 (11.4)
Reference GFR (mL/min/1.73 m2) 60.5 ± 33.4 54.6 ± 31.8 62.3 ± 28.7
Reference GFR by category of CKD (n, (%))
G1 (eGFR ≥ 90 mL/min/1.73 m2)77 (24.1) 35 (22.7) 42 (25.3)
G2 (eGFR 60–89 mL/min/1.73 m2)62 (19.4) 34 (22.1) 28 (16.9)
G3a (eGFR 45–59 mL/min/1.73 m2)49 (15.3) 22 (14.3) 27 (16.3)
G3b (eGFR 30–44 mL/min/1.73 m2)69 (21.5) 31 (20.1) 38 (22.9)
G4 (eGFR 15–29 mL/min/1.73 m2)38 (11.9) 20 (13.0) 18 (10.8)
G5 (eGFR < 15 mL/min/1.73 m2)25 (7.8) 12 (7.8) 13 (7.8)
Types of primary malignancy (n, (%))
Solid malignancy 299 (93.4) 146 (94.8) 153 (92.2)
Hematologic malignancy 21 (6.6) 8 (5.2) 13 (7.8)
Stages of malignancy (n, (%))
Stage 1 164 (51.3) 87 (56.5) 77 (46.4)
Stage 2 139 (43.4) 61 (39.6) 78 (47.0)
Stage 3 17 (5.3) 6 (3.9) 11 (6.6)
Stage 4 0 (0) 0 (0) 0 (0)
Table 2. Baseline characteristics of participants. Data are shown as the mean ± SD unless otherwise specied.
BMI, body mass index; BSA, body surface area; CKD, chronic kidney disease.
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female patients compared to the other eGFR equations. Notably, the ai eGFR equation clearly demonstrated an
overestimation of GFR in males in comparison to that in females (Fig.1).
We also investigated the utility of these eGFR equations with the reference GFR in the CKD population grouped
according to GFR range as following: i) GFR ≥60 mL/min, ii) GFR 30–59 mL/min, and iii) GFR <30 mL/min.
As shown in Fig.2, the BSA-unadjusted CKD-EPI equation was the least biased model for estimating the GFR,
illustrated by the violin plot in all CKD categories. Although the Cockcro-Gault equation was the second least
biased model calculated by ME (Table2), it underestimated the GFR, particularly in patients with GFR ≥60 mL/
min (Fig.2A). Similar to the BSA-unadjusted CKD-EPI equation, both the Janowitz and Williams equation and
the CKD-EPI equation yielded estimates that were compatible with the reference GFR (i.e., less dierent from the
reference GFR) in all GFR ranges. Meanwhile, both the ai eGFR equation and the re-expressed MDRD study
equation with the ai racial factor demonstrated overestimation of the GFR in advanced CKD (Fig.2B,C).
Sensitivity and specicity of the eGFR equations for identifying various CKD stages. e perfor-
mances of the published models were also analyzed according to the KDIGO classication (CKD stage G1–G5),
as shown in Table5. e re-expressed MDRD study equation with the ai racial factor demonstrated the highest
sensitivity (91.7%) and specicity (100%) in CKD stage G1. Meanwhile, the BSA-unadjusted CKD-EPI equation was
the model with the best performance across CKD stages G2–G5. Interestingly, most of the published models showed
less sensitivity and specicity in advanced CKD. It should be noted that only the CKD-EPI equation, regardless nor-
malization by BSA, was suitable for determining CKD stage G5 based on the eGFR. In fact, the greatest sensitivity
(89.7%) and specicity (100%) for CKD stage G5 were demonstrated by the BSA-unadjusted CKD-EPI equation.
Discussion
Our study showed that the body surface area (BSA)-unadjusted CKD-EPI equation showed the best performance
for GFR estimation in terms of both precision and accuracy, followed (in order) by the CKD-EPI equation as
well as the Janowitz and Williams equation for patients with cancer, the Cockcro-Gault equation, and the ai
eGFR equations. Meanwhile, the 2012 CKD-EPI creatinine-cystatin C equation was the least precise and the least
Estimated GFR models GFR* (n = 320)
Bias Precision Accuracy
ME 95% limits of
agreement SD of bias RMSE P10 (%) P15 (%) P30 (%)
Reference GFR 50.4 (32.6–86.5), 7.9–142.3 — — — — — — —
CKD-EPI 55.7 (35.8–84.6), 9.3–130.2 −2.68 −16.18 to 10.83 6.89 7.38 51.88 72.81 96.25
BSA-unadjusted CKD-EPI 51.4 (33.1–81.6), 7.7–143.8 1.06 −10.83 to 12.95 6.07 6.15 71.88 87.50 99.06
Re-expressed MDRD study
with the ai racial factor 57.3 (37.9–85.8), 10.0–196.4 −7.70 −35.17 to 19.78 14.02 15.97 37.19 54.69 86.25
ai eGFR 62.9 (43.5–83.5), 17.0–159.3 −8.73 −31.36 to 13.89 11.54 14.16 25.94 35.31 58.13
2012 CKD-EPI creatinine-
cystatin C 36.3 (24.2–57.6), 3.3–192.1 13.37 −27.49 to 54.23 20.85 24.74 17.19 26.56 55.31
Cockcro-Gault 51.1 (33.2–74.4), 8.3–158.4 1.43 −19.30 to 22.17 10.58 10.66 44.69 65.63 91.25
Janowitz & Williams 55.0 (35.3–76.7), 5.7–128.4 2.03 −15.11 to 19.16 8.74 8.96 54.69 77.50 95.00
Table 3. e means of the reference GFR and the eGFRs calculated by the dierent eGFR equations. e bias
between the mean eGFR and the reference GFR and the range of the bias are shown. CKD-EPI, Chronic Kidney
Disease Epidemiology Collaboration; eGFR, estimated glomerular ltration rate; MDRD, Modication of Diet
in Renal Disease; ME, mean error (negative values signify overestimation); Pn, percentage of participants with
an eGFR within ± n % of the reference GFR; RMSE, root-mean square error; SD, standard deviation. *Data
presented as median (IQR), range with the units of mL/min/1.73 m2 (except the BSA-unadjusted CKD-EPI,
Cockcro-Gault, and Janowitz & Williams which demonstrated as the units of mL/min).
Methods of GFR assessment
Root mean square error (mL/min)
BSA-adjusted BSA-unadjusted
Reference — —
CKD-EPI 7.38 6.15
Re-expressed MDRD study with the ai racial factor 15.97 22.07
ai eGFR 14.16 19.75
2012 CKD-EPI creatinine-cystatin C 24.74 23.53
Cockcro-Gault 11.14 10.66
Janowitz & Williams 8.96 11.82
Table 4. Comparisons between the accuracy (determined by the root-mean square error (RMSE)) of various
estimated glomerular ltration rate (eGFR) model (BSA-adjusted vs. BSA-unadjusted) equations and the
reference GFR. BSA, body surface area; CKD-EPI, Chronic Kidney Disease Epidemiology Collaboration; eGFR,
estimated glomerular ltration rate; MDRD, Modication of Diet in Renal Disease.
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accurate eGFR equation in cancer patients as determined by the standard deviation of the absolute dierence and
root-mean square error (RMSE), respectively.
GFR is currently the standard measurement for determining renal function27, and patients with cancer com-
monly present with impaired renal function28. At present, there are three most commonly used formulae in
oncology worldwide—the Cockcro-Gault, the MDRD study, and the CKD-EPI equations7,18,19—as well as the
ai eGFR equation, which is being adopted in practice nationwide10. While the CKD-EPI equation is recom-
mended for use in routine clinical practice by the KDOQI and the National Kidney Foundation (NKF), most
cancer centers use the MDRD study equation, following the International Society of Geriatric Oncology recom-
mendation5. Nevertheless, the CKD-EPI equation is more accurate than the MDRD study equation in patients
with reduced muscle mass, as eGFRs of 45–60 mL/min/1.73 m2 estimated by the MDRD study equation might be
estimated as above 60 mL/min/1.73 m2 by the CKD-EPI equation11. Moreover, Asians have been shown to have a
higher percentage of body fat for the same level of BMI than Caucasians, suggesting lower levels of muscle mass;29
this suggests ethnic interference and the necessity for robust validation of eGFRs in patients with cancer.
In our study, the BSA-unadjusted CKD-EPI equation was the least biased equation (Figs.1 and 2); it was less
biased than the Cockcro-Gault equation and the re-expressed MDRD study equation with the ai racial factor.
Although the Cockcro-Gault equation demonstrated the second least bias of the eGFR equations (mean error
1.43 mL/min), the precision and accuracy were less than the those of BSA-unadjusted CKD-EPI, CKD-EPI, and
Janowitz and Williams equations (Table3). e re-expressed MDRD study equation with the ai racial factor, a
preferable equation for CKD in the ai population10, showed widest bias in eGFRs < 60 mL/min with a tendency
of overestimation (Fig.2), possibly due to sarcopenia in patients with cancer30. Indeed, the participants in the
present study had an 8.5% lower mean muscle mass compared to those of patients with HIV infection (22.5 ± 5.8
vs. 24.6 ± 5.6 kg, p < 0.001), another chronic illness population31. Additionally, the BSA-unadjusted CKD-EPI
equation would be more applicable than the re-expressed MDRD study equation for calculation of eGFR in
cancer patients with higher sensitivity and specicity in CKD determination, particularly in patients with CKD
stage G2–G5 (Table5). However, the use of BSA in corporation with eGFR formulas should be interpreted with
caution particularly in CKD stages of KDIGO because the unit of eGFR in KDIGO naturally presents as mL/min/
m2 4. In other words, there must be no dierence between BSA-adjusted equations and BSA-unadjusted equations
in term of the KDIGO guideline.
Although the 2012 CKD-EPI creatinine-cystatin C equation was favorable in conditions of low SCr pro-
duction, such as in the case of loss of muscle mass from limb amputations or neurological diseases32, the 2012
CKD-EPI creatinine-cystatin C eGFRs had low precision and accuracy in our results, possibly due to the lack
of patients with cancer during the standardization of this equation13,33. Interestingly, the ai eGFR equation
demonstrated better performance than the 2012 CKD-EPI creatinine-cystatin C equation and the re-expressed
MDRD study equation with the ai racial factor, possibly due to the increased generalizability to the CKD pop-
ulation of the ai eGFR equation and/or the dierent methods used for the reference GFR determination10. A
Figure 1. Bland-Altman plots of estimated GFR (eGFR) versus the reference GFR for each model’s equation are
shown. e mean of the reference GFR and eGFR was plotted against the dierence between the two. Positive
and negative dierences indicate under- and overestimation, respectively. e plots are shown in ascending
order of the precision of the eGFR from top le to bottom right, where the precision is calculated by the root-
mean-squared error. e solid black line on each plot represents the mean of the dierence, the solid gray line
marks the line of identity, and the dashed line is drawn at the mean ± 1.96 times the standard deviation of the
dierence. Points are colored by sex (blue and orange represent female and male, respectively). BSA, body
surface area; CKD-EPI, Chronic Kidney Disease Epidemiology Collaboration; MDRD, Modication of Diet in
Renal Disease.
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further validation study in patients with cancer might be necessary to identify proper serum CysC-based and/
or SCr-based eGFR equations for the ai population. Moreover, the spread of bias among the BSA-unadjusted
CKD-EPI, CKD-EPI, and Janowitz and Williams equations from the reference GFR was evenly distributed
(Fig.1) despite the increased deviation from the reference in patients with eGFR <60 mL/min with the Janowitz
Figure 2. Violin plot of the dierences between the model equations’ outcomes and the reference GFR
according to the GFR ranges: (A) GFR ≥60 mL/min, (B) GFR 30–59 mL/min, and (C) GFR <30 mL/min.
e solid black lines in the le panels refer to the medians of the eGFR for each eGFR model, while the black
circles on the right panels represent the medians of the dierence for each eGFR model. Positive and negative
dierences indicate over- and underestimation, respectively. BSA, body surface area; CKD-EPI, Chronic Kidney
Disease Epidemiology Collaboration; MDRD, Modication of Diet in Renal Disease.
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and Williams equation (Fig.2B,C). is phenomenon might be explained by the low sensitivity for advanced
CKD stage with the Janowitz and Williams equation. Although the Janowitz and Williams equation is a some-
what sophisticated mathematical formula and is weak in its assessment of advanced CKD, it was impressive in
assessments of early-stage CKD and is available as an online calculation tool (http://tavarelab.cruk.cam.ac.uk/
JanowitzWilliamsGFR/)34.
Given the validation of several common eGFR calculations, the CKD-EPI equation (regardless of BSA adjust-
ment) is the most appropriate for determining the CKD stage in patients with malignancy (malnourishment or
severe emaciation are common). Our ndings support the 2016 cancer chemotherapy guidelines for treatment
of renal injury, which states that i) eGFR (or creatinine clearance) without correcting BSA is used for drugs that
the doses are xed (BSA independent) and ii) eGFR (or creatinine clearance) corrected for BSA is used for drugs
that the dose depends on BSA35. Although there is currently no guideline consensus which method of eGFR is
preferred in cancer patients, our ndings are consistent with the most recent study by Janowitz and colleagues3,
which demonstrate better predictive performance of the BSA-unadjusted CKD-EPI over the CKD-EPI equation.
While the CKD-EPI equation is recommended for use in routine clinical practice by the KDOQI and the National
Kidney Foundation (NKF), the CKD-EPI equation showed less accuracy compared with the BSA-unadjusted
CKD-EPI in the present study. is paradox could be explained by the fact that the CKD-EPI equations included
populations with mean BSA of 1.93 ± 0.2 m2 and BMI of 28 ± 6 kg/m2, reecting the large number of overweight
participants in the CKD-EPI study7. Interestingly, Levey et al.7 also reported the mean measured GFR of their
Estimated GFR
models
Chronic kidney disease stage
G1 G2 G3 G4 G5
CKD-EPI
Sensitivity 85.5 79.0 84.8 87.4 88.6
Specicity 100.0 75.0 44.4 100.0 100.0
PPV 100.0 89.0 95.2 100.0 100.0
NPV 24.6 13.0 18.2 11.1 25.0
BSA-unadjusted CKD-EPI
Sensitivity 80.6 90.7 89.9 97.3 89.7
Specicity 100.0 62.5 55.6 100.0 100.0
PPV 100.0 94.2 96.1 100.0 100.0
NPV 26.3 50.0 31.3 50.0 40.0
Re-expressed MDRD study with the ai racial factor
Sensitivity 91.7 90.7 87.2 83.8 52.1
Specicity 100.0 62.5 55.6 100.0 100.0
PPV 100.0 94.2 95.9 100.0 100.0
NPV 45.5 50.0 26.3 14.3 15.4
ai eGFR
Sensitivity 76.4 88.9 70.6 32.4 4.3
Specicity 100.0 62.5 66.7 100.0 100.0
PPV 100.0 94.1 96.3 100.0 100.0
NPV 22.7 45.5 15.8 3.8 8.3
2012 CKD-EPI creatinine-cystatin C
Sensitivity 28.6 27.4 65.3 72.2 68.0
Specicity 100.0 37.5 22.2 100.0 100.0
PPV 100.0 73.3 91.7 100.0 100.0
NPV 18.3 62.5 46.5 22.5 24.2
Cockcro-Gault
Sensitivity 72.2 63.0 92.7 91.9 69.6
Specicity 100.0 37.5 44.4 100.0 100.0
PPV 100.0 87.2 95.3 100.0 100.0
NPV 20.0 13.0 33.3 25.0 22.2
Janowitz & Williams
Sensitivity 55.6 98.2 92.7 91.9 30.4
Specicity 100.0 37.5 44.4 100.0 100.0
PPV 100.0 91.3 95.3 100.0 100.0
NPV 13.5 75.0 33.3 25.0 11.1
Table 5. e performances of published estimated glomerular ltration rate (GFR) models for chronic
kidney disease determination. Data are represented as percentages (%). CKD-EPI, Chronic Kidney Disease
Epidemiology Collaboration; MDRD, Modication of Diet in Renal Disease; PPV, positive predictive value;
NPV, negative predictive value.
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studied CKD patients of 68 mL/min/1.73 m2 and the mean BSA-unadjusted measured GFR of 75.9 mL/min.
Accordingly, the dierence of 7.9 mL/min was found aer reversing the BSA indexing process among their stud-
ied population. In the present study, the CKD-EPI equation showed greater performance over the Janowitz and
Williams equation, particularly in CKD with GFR < 30 mL/min, possibly due to (i) the ethnic dierence10, (ii) the
higher proportion of patients with low muscle mass (and BMI) in our study, iii) the dierence in reference eGFR
(99mTc-DTPA plasma clearance in the present study versus three dierent time points of chromium-51 EDTA
(51Cr-EDTA) administration in the other study) and iv) the inclusion criteria including both solid and hemato-
logic malignancy in the present study3.
ere were several limitations in our study. First, the gold standard renal inulin clearance was not included
in the present study. Although the 99mTc-DTPA method may overestimate GFR, particularly in patients with
lower BMI36, the comparable inulin method for CKD patients has been mentioned in a large study37. Second, the
performance status of most participants was good (ECOG 0–1) due to ethical restrictions. Patients with cachexia
might have displayed more deviations in GFR. ird, a small number of patients with paraproteinemia—a disease
with low SCr—were included in the present study. However, the exclusion criteria in this study ruled out most
of the potential cofounding factors inuencing the eGFR assessment. Fourth, the impacts of the dierent eGFR
equations on clinical outcomes, complications, and other aspects of renal dysfunction (i.e., albuminuria and
β2-microglobulin) and comparisons of the use of eGFR with the use of actual (reference) GFR were not explored.
Further studies are warranted.
Taken together, we propose that the BSA-unadjusted CKD-EPI formula is the most favorable eGFR equation
in patients with cancer, followed by the CKD-EPI and the Janowitz and Williams equations. Further validation
studies with pharmacokinetic exploration are of interest.
Received: 29 April 2019; Accepted: 2 December 2019;
Published: xx xx xxxx
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Acknowledgements
All of the funding supports during study period including the Development of New Faculty Sta fund and
Ratchadapiseksomphot Endowment Fund 2017 (76001-HR), Faculty of Medicine, Chulalongkorn University and
National Science and Technology Development Agency (NSTDA: P-13-00505)–Dr. Asada Leelahavanichkul. A.L.
is under the Translational Research in Inammation and Immunology Research Unit (TRIRU), Department of
Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok, ailand. e funders had no role in
study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Author contributions
W.C. acquisition and analysis of data, illustration, wrote the paper, revision for intellectual content. S.W.
acquisition and analysis of data, contributed essential reagents or tests. S.V. contributed to design of the work,
contributed essential reagents or tests; critical revision. S.E. design of the study, revision for intellectual content.
A.L. acquisition and analysis of data, contributions to design of the work, illustration, contributions to paper
writing.
Competing interests
e authors declare no competing interests.
Additional information
Correspondence and requests for materials should be addressed to W.C. or A.L.
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