Comparison of glomerular filtration rate estimated by plasma clearance method with modification of diet in renal disease prediction equation and Gates method

Introduction

Glomerular filtration rate (GFR) is considered to be the best parameter to assess the overall kidney function.[1] GFR can be measured by calculating the plasma clearance of various glomerular filtration markers like inulin, ethylene-diamine-tetra-acetic-acid, diethylene-triamine-penta-acetic acid (DTPA), iothalamate and iohexol.[2] Although, the plasma clearance methods give accurate GFR measurement but these methods are time consuming and require timed blood sampling.[34] However, the the modification of diet in renal disease (MDRD) equation, a serum creatinine based equations for GFR prediction is widely used to estimate GFR, but the intrinsic limitations of serum creatinine in estimation of GFR is well known.[1] As an alternative to these equations, techniques using radioisotopes have also been developed for instant assessment of GFR. These methods do not require urine or blood collection and results can be obtained within few minutes. The method introduced by Gates is the most commonly used method.[5] There is paucity of study to show the relative superiority of Gates method and MDRD equation for estimation of GFR. Therefore, we undertook this study to compare the Gates method and MDRD equation in a sizeable patient population with wide range of renal function to evaluate their clinical utility.

Materials and Methods

Results

The patient characteristics and indications for estimating GFR are shown in Table 1. The mean age, gender ratio, height, weight, serum creatinine, GFR estimated by Gates and MDRD equation are shown in Table 2, with all subjects divided in to 4 different levels of GFR (0-30, 31-60, 61-90, >90 ml) measured by clearance method.

Table 1 Patient characteristics

Table 2 Clinical and biochemical parameter in each study group

The comparative differences of correlation coefficient and precision of GFR estimated by all three methods are shown in Table 3. Analysis of correlation between clearance method and Gates method indicated 56% correlation with the measured GFR for the GFR range of 0-30 ml, and correlation went down to 39% in the GFR range of 31-60 ml, 40% in the GFR range of 61-90 ml, 26.4% in the GFR range of >90 ml. Analysis of correlation between clearance method and MDRD equation indicated the correlation of 47.9% with the measured GFR for the GFR range of 0-30 ml, and correlation went down to 31.1% in the GFR range of 31-60 ml, 17.6% in the GFR range of 61-90 ml, 16.1% in the GFR range of >90 ml. Overall, there was significant correlation between measured GFR and GFR estimated by gates method (r=0.73, P=0.001) [Figure 1] and the correlation was also significant between measured GFR and GFR estimated by MDRD equation (r=0.62, P=0.001) [Figure 2].

Table 3 Comparison of Gates GFR with MDRD GFR for various range of renal function

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Figure 1

Correlation between Gates GFR and measured GFR

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Figure 2

Correlation between MDRD-GFR and measured GFR

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On linear regression analysis with depended variable GFR estimated by clearance method and predictable variable GFR by Gates method, the precision of the Gates method was 0.315 for GFR 0-30 ml, 0.152 for GFR 31-60 ml, 0.167 for 61-90 ml and 0.07 for GFR >90 ml. The precision of the MDRD equation was 0.230 for GFR 0-30 ml, 0.097 for GFR 31-60 ml, 0.031 for 61-90 ml and 0.026 for GFR >90 ml, respectively. Regression analysis showed that both Gates method and MDRD equation overestimated GFR at lower range of renal function and underestimated at higher range of renal function.

Discussion

The main finding of this study is the better correlation of Gates GFR with ‘measured GFR’ compared to MDRD GFR for all level of renal function. Our results also indicate that both Gates method and MDRD equation overestimates GFR at lower level of renal function and underestimates at higher level of kidney function. This current study revealed few important differences with the existing literature.[89] First, our study shows precision of Gates method decreases with increase in level of GFR which means Gates method will produce more reliable result at lower level of renal function i.e., lower GFR. Similar trend was observed for MDRD equation, where the obtained correlation was 0.479 for GFR range of 0-30 ml as against 0.161 for >90 ml range. MDRD equation was derived from patients of chronic kidney disease and is known to perform better at lower level of renal function.

A review of literature yielded limited number of studies in English, which have compared Gates method with a creatinine-based GFR prediction equation. De Santo et al.[8] evaluated GFR in 65 individual (15 healthy controls and 50 patients with renal disease) by Tc99m-DTPA renogram (Gates method), creatinine clearance (measured and predicted by Cockroft and Gault, CG) and by inulin clearance. They concluded that Gates method for GFR assessment is less precise than measured and predicted creatinine clearance. Itoh et al.[9] studied 133 patients (69 males and 64 females; age range 24-84 years) with a wide range of renal function and determined GFR simultaneously by γ-camera uptake method (Gates method), predicted creatinine clearance method (Cockcroft-Gault, CG) and single or two-plasma sample and concluded that Gates method is even less precise than the Cockcroft-Gault prediction equation. Both of our above findings are in contrast with the study of De Santo et al. and Itoh et al.[89] However, in both these studies Cockcroft-Gault equation was used to predict GFR rather that MDRD equation, which is presently, favored over Cockcroft-Gault equation as per recent National Kidney Foundation guidelines.[1] Aydin et al. compared measured GFR by single plasma sample methods (SPSMs), γ-camera Gates, 24-h endogenous creatinine clearance, and prediction equations [Cockcroft-Gault and MDRD] with the two plasma sample method (TPSM) considered as the reference in 115 potential kidney donors with normal renal function. They concluded that Gates method, creatinine clearance, Cockcroft-Gault prediction equation and MDRD prediction equation overestimated GFR (bias 5.76, 15.49, 13.24 and 6.72, respectively). The correlation coefficients were 0.49, 0.27, 0.48 and 0.43 for Gates method, creatinine clearance, Cockcroft-Gault prediction equation and MDRD prediction equation respectively.[10] Another recent multicentric study by Virga et al. has evaluated the performance of 12 different creatinine (Cr)-based equations commonly used to estimate GFR in predicting total Cr clearance (totCrCL) in 355 peritoneal dialysis patient and concluded that the Gates, Virga and 4-MDRD equations showed the best global performance.[11]

Apart from the difference in the prediction equation used, there are other issues involved with method of creatinine measurement. In the present study and the study by Itoh et al. creatinine measurement was done using an autoanalyzer; however, the method of creatinine measurement has not been mentioned in the study of De Santo et al.[89] It is well known that autoanalyzer produces more accurate measurement of creatinine than the conventional alkaline-picrate method.[1] Moreover, all these three studies were performed in three entirely different racial population. The study of De Santo et al. was performed in Caucasian population whereas the study of Itoh et al. was performed in Japanese population and the present study was done exclusively in Indian population. This also raises the issue of suitability of one GFR prediction equation for all racial groups. Number of subjects recruited in these two studies was also relatively small of 65 and 133, respectively. The study by De Santo et al. utilized inulin clearance as measured GFR, where as Itoh et al. used single sample Tc99m-DTPA clearance in 116 of 133 subjects recruited and the two-sample Tc99m-DTPA clearance was used only in 17 patients. In the present study, GFR was measured by two-sample Tc99m-DTPA clearance method in all subjects. The differences in study design might have influenced the results.

Serum creatinine concentration is the most widely used biochemical parameter to assess renal function. However, it is not an ideal marker of GFR, because apart from excretion by glomerular filtration, a significant portion is secreted by the renal tubules.[1213] Moreover, there is a small fraction of extra renal elimination of creatinine, which can become the major route of elimination in advanced renal insufficiency. Hence, an isolated serum creatinine measurement will overestimate GFR and this degree of overestimation is unpredictable.[1415] A concern with GFR prediction equations has been the bias from a lack of standard calibration in serum creatinine assays across laboratories.[1617] Presently there is no standard calibration for serum creatinine measurement for laboratories in India much like in the rest of the world. The implication was that a constant calibration bias caused greater inaccuracies in estimated GFR for persons with a normal serum creatinine level than that for persons with an elevated serum creatinine level.[1819] Other potential sources of measurement error include intraindividual variability in serum creatinine, racial and intraindividual variability in GFR, and intra-assay variability in creatinine and GFR measurement.

The clearance of Tc99m-DTPA in timed plasma collections is a very accurate method to measure the GFR and correlates very closely with inulin.[18–20] However, these methods are lengthy and time-consuming. The estimation of GFR by the Tc99m-DTPA renogram is proposed as an answer to the need of the simplicity without losing the precision.[521] Several sources of errors in the estimation of GFR by scintigraphy are recognized: Background correction, decay statistics, attenuation correction, and estimation of arterial plasma activity, system dead time, volume measurements and radiopharmaceutical quality. Of these, the bias for overestimation for GFR by the gates may be attributable to insufficient background correction.[22]

Conclusions

Gates method provides better estimate of GFR at all levels of renal function compared to MDRD equation. However, poor correlation exhibited by both this method with reference radionuclide clearance method makes them suboptimal for clinical use.