Existing creatinine-based equations overestimate glomerular filtration rate in Indians

Glomerular filtration rate (GFR) is the most important determinant for identifying and classifying chronic kidney disease (CKD) [1]. Since measuring GFR is impractical, equations that rely upon the serum concentration of filtration markers (i.e., molecules generated in the body at a fixed rate and eliminated almost exclusively by glomerular filtration) have been developed for estimating GFR (eGFR). Creatinine is the best known of these markers, and was the basis for the development of Modification of Diet in Renal Disease (MDRD) GFR estimating equation [2]. Recognizing that serum creatinine concentration was dependent upon muscle mass, demographic parameters that acted as surrogates for muscle mass, i.e. age, gender and ethnicity, are included in the equation. The MDRD equation was found to be biased and imprecise for values above 60 ml/min, and has been superseded by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation, developed in more diverse populations [3]. The 2012 Kidney Disease Improving Global Outcomes (KDIGO) guidelines recommend the use of this equation for diagnosis and follow up of CKD, as well as for screening of populations with unknown kidney function, unless equations developed in local populations are available [1].

Based on the concern that the ethnicity coefficient did not address nonwhite, non-African-American groups, investigations in Chinese and Japanese populations led to development of correction factors of 1.23 and 0.81, respectively [4, 5]. This meant that the same value of serum creatinine represented a 23% higher and 19% lower GFR compared to the white population, respectively. Correction factors or new equations have also been developed in Thai, Korean and Pakistani populations [6‐8]. Since the largest differences are seen at higher GFR values, suggestions have been made to develop and validate ethnicity coefficients in populations where screening for CKD might occur.

Since muscle mass and dietary protein intake, in particular that of meat, are important determinants of serum creatinine concentration, it can be hypothesized that a correction factor, or a new eGFR equation may be necessary to accurately identify and classify individuals with CKD in the predominantly vegetarian Indian population, so that preventive and therapeutic strategies can be targeted appropriately. More recently, equations based on cystatin C (Cys), another filtration marker that is not dependent upon muscle mass and may be less susceptible to ethnic variations, have been developed [9]. Horio et al. showed that the CKD-EPI Cys (CKD-EPI_Cys) eGFR equation developed in white population performed equally well in the Japanese [10].

In this pilot study, we evaluated the performance of the existing eGFR equations for assessment of GFR in Indians to determine the need for a larger study to develop an ethnicity coefficient for GFR estimation in Indians.

A total of 200 participants with stable CKD and 85 prospective renal donors were screened between January 2014 and December 2015. 150 participants were excluded (on dialysis: 63; organ transplant recipient: 15; edema: 22; heart failure: 11; voiding dysfunction: 8, use of glucocorticoids: 12; refused consent: 19). Finally, 135 participants were studied. Data collection were incomplete in 5 participants and hence, 130 participants were included for final analyses. These included 63 apparently healthy prospective living renal donors and 67 patients with CKD. The causes of CKD in these 67 individuals are shown in Table 1. The demographic, biochemical characteristics and GFR in study population are shown in Table 2. Majority were males and 50% were strict vegetarian. Among meat-eaters, the average frequency of meat intake was 3.8 times every month. The average weight and 24-h urine volume in study participants were 63.2 kg (95% CI: 61.0 to 65.3 kg) and 2321 ml (95% CI: 2135 to 2508 ml), respectively. The average daily urine creatinine and urea nitrogen excretion were 0.87 g (95% CI: 0.80 to 0.93 g) and 5.4 g (95% CI: 5.0 to 5.8 g), respectively. The creatinine excretion were 14.7 mg/kg/day (95% CI: 13.5 to 15.9 mg/kg/day) and 12.4 mg/kg/day (95% CI: 11.2 to 13.6 mg/kg/day) in males and females, respectively. The average daily protein intake based on 24-h urea nitrogen excretion was 46.1 g/day (95% CI: 43.2 to 48.8 g/day), respectively.

The mean mGFR in the study population was 51.66 ± 31.68 ml/min/1.73m². A total of 54 participants had mGFR ≥60 ml/min/1.73m² whereas 76 had mGFR <60 ml/min/1.73m². Amongst apparently healthy participants (prospective renal donors), the mean mGFR was 79.44 ± 20.19 ml/min/1.73m² (range: 41.90–134.50 ml/min/1.73m²). All five eGFR equations overestimated GFR (Table 3, Fig. 1), with CKD-EPI_Cr being the poorest. The CKD-EPI_Cys exhibited the lowest bias. The results did not change after stratification by gender (data not shown) or mGFR categories (Additional file 1: Tables S2 and S3) or age (Additional file 1: Tables S4 and S5). eGFR by any of the creatinine based estimating equations was significantly different from mGFR. Overall, the accuracy was best for CKD-EPI_Cys equation [Table 3, Fig. 1]. When stratified by mGFR groups, the proportion of participants with eGFR by CKD-EPI_Cys within ±30% of mGFR were 81.5% and 69.7% for those with mGFR ≥60 ml/min/1.73m² and <60 ml/min/1.73m², respectively.

Serum creatinine values measured by the modified Jaffe method at PGIMER, India strongly correlated with those done at the Central Laboratory in Japan (Pearson’s correlation coefficient r = 0.965, p < 0.001, Additional file 2: Figure S1). The mean difference between the two methods was −0.037 ± 0.243 mg/dL (p = 0.096) with 95% limit of agreement as 0.439 to −0.513, and no potential proportional bias (linear regression analysis: unstandardized B = −0.023, p = 0.336). Sensitivity analysis using eGFR calculated using the Jaffe creatinine showed similar performance (Additional file 1: Table S6).

This pilot study shows that the existing creatinine based eGFR equations significantly overestimate GFR in the predominantly vegetarian Indian population. Better performance of CKD-EPI_cys equation and lower creatinine excretion suggest that this overestimation is likely linked to the lower muscle mass. These findings support the need of an appropriately powered study to develop either a correction factor or a new equation for accurate assessment of kidney function in the Indian population.

In stable individuals, age, sex and race are important non-GFR determinants that affect creatinine generation and have been factored in creatinine based eGFR equations [18]. Most Indians are vegetarian because of cultural and religious beliefs. Even those who count themselves as non-vegetarians eat meat only infrequently. Also, the body habitus of individuals of Indian ethnicity is different from other Western and Asian populations. Indian individuals are comparatively short, have less muscle mass, and exhibit truncal obesity [19‐22]. The measured daily creatinine excretion rates of 14.7 and 12.4 mg/kg/day in Indian males and females are lower than what has been reported for Japanese participants (20.2 and 16.7 mg/kg/day respectively) [5]. These important physiologic non-GFR determinants of serum creatinine have not been factored in the available serum creatinine based eGFR equations [18], and could account for poor performance of these equations in our study population, as shown by low P₃₀ values.

This hypothesis was also supported by the better performance of cystatin-based equation. Notably, the eGFR by CKD-EPI_Cys and mGFR did not differ significantly in overall study population and GFR subgroups. Cys is produced by all nucleated cells and is less affected by age and sex [23‐25]. Its generation is not dependent on muscle mass and dietary protein intake. In a study of 170 healthy individuals, serum creatinine and 24-h urinary creatinine excretion significantly correlated with lean body mass whereas serum Cys levels did not, even after adjustment for dietary protein/meat intake and level of physical activity [26]. This observation is important, as use of equations that use both serum creatinine and cystatin has been recommended to offset errors by equations that rely on individual parameters [27]. Similar finding has been reported amongst the Japanese, where the CKD-EPI_Cys accurately predicted mGFR, but addition of creatinine to the formula worsened the bias [10].

Another important finding was the relatively low mGFR in apparently healthy participants who were being worked up as kidney donors. This finding is consistent with earlier reports from India. In a selected population of 122 apparently healthy prospective renal donors, GFR measured by plasma clearance of technetium 99 m diethyltriaminepentaacetic acid was 83.42 ± 13.4 (range 61–130) ml/min/1.73m² [28]. In another study of 101 healthy Indian adults, mGFR was 82.4 ± 12.7 ml/min/1.73m² (95% CI: 80.0 to 84.8 ml/min/1.73m²) [29]. In a multiethnic study of 103 healthy volunteers from Singapore, participants with Indian ethnicity had lower measured GFR compared with other Asian populations (Chinese, Malay and others) [30]. This is comparable to mean mGFR of 79.44 ± 20.19 ml/min/1.73m² seen in apparently healthy prospective renal donors in our population. The mGFR was <60 ml/min/1.73m² in 9 participants. According to the 2012 KDIGO classification scheme, people with GFR <60 ml/min/1.73m² would be deemed to have stage 3 CKD [1]. Low protein intake on account of largely vegetarian diet could be one of the reasons for comparatively low GFR in Indian population. Previous studies, however, have shown an acute rise in GFR with protein loading, indicating preserved renal functional reserve [29, 31]. An important question that needs to be answered is whether this low GFR in otherwise healthy individuals has long term adverse health consequences. Several meta-analyses have shown the adverse impact of low GFR on mortality and ESRD risk [32]. These meta-analyses, however, have not included any cohorts from India. The KDIGO classification [1] emphasizes that individuals should be labelled as having CKD only when the abnormality has implications for health. It remains unknown, however, whether having a low GFR in apparently healthy individuals in this population is physiological or carries an adverse prognosis as described in individuals with comparable eGFR levels elsewhere. Therefore, longitudinal studies that measure GFR and carefully and accurately define prognosis in this population are needed to inform the definition and staging of CKD. The Indian government has launched a scheme for a population wide non-communicable disease survey that includes assessment for CKD (http://​timesofindia.​indiatimes.​com/​india/​Soon-door-to-door-screening-of-diseases/​articleshow/​53471865.​cms). In the absence of an accurate equation, misclassification of healthy individuals as CKD could overwhelm the implementation of preventive and therapeutic strategies, and impair the credibility of the discipline [33]. This information is also important for selecting living kidney donors. Currently, only a minority of centers in India measure GFR, relying upon eGFR for donor selection. Reliance on equations that overestimate GFR could lead to inappropriate selection of donors with low true GFR, or inappropriate exclusion of healthy individuals who may not have any consequence from donation despite having a low GFR. This study is the first attempt at robust assessment of accuracy of currently recommended eGFR equations in Indian population. We have measured GFR by the gold standard method - urinary inulin clearance.

Our study has some limitations, including small sample size, limited regional representation (mainly North Indian population) and no formal measurement of muscle mass.

Our findings support the need for developing either a correction factor or a new equation for the Indian population. Such a study should be adequately powered, and should include participants from all geographies so that an equation that performs well across full spectrum of clinical characteristics in the population could be developed. Longitudinal studies are also needed for accurately estimating future risk of kidney failure, cardiovascular disease or mortality in populations who have had a baseline GFR measurement to validate the existing eGFR based diagnosis and classification system.

In conclusion, our study shows that the existing creatinine-based GFR estimating equations significantly overestimate mGFR in the Indian population, which could be linked to the low muscle mass and vegetarian diet.