Estimation of Creatinine Clearance in Morbidly Obese Patients

Jasmina A. Demirovic; Amy Barton Pai; Manjunath P. Pai


Am J Health Syst Pharm. 2009;66(7):642-648. 

In This Article


The prevalence of obesity in the United States has reached epidemic proportions. According to the National Health and Nutrition Examination Survey III, approximately half of the U.S. population over age 20 years are overweight or obese.[1] Obese patients are classified into three groups based on a body mass index (BMI) of 30.0-34.9, 35.0-39.9, and ≥40.0 kg/m2.[2] This last group is often referred to as morbidly obese and constitutes 5% of the U.S. population.[1] Many studies have demonstrated that obesity predisposes patients to an increased risk for diseases such as hypertension, cardiovascular disease, and type 2 diabetes mellitus.[3] While the guidelines on evaluation and treatment of obesity address the effect of obesity on blood pressure control, glucose regulation, and cardiovascular health, more research is necessary to better understand its effect on renal function.[3] Chagnac and colleagues[4] found that overweight patients have an increased glomerular filtration rate (GFR) and increased renal plasma flow. Renal hyperfiltration occurs through renal vasodilation in a compensatory response to overcome the increased tubular reabsorption of sodium. However, vasodilation of afferent arterioles increases the hydrostatic pressure in the glomerulus, which can lead to hypertrophy over time and renal disease, even in patients without diabetes.[3] In addition, hyperlipidemia, leptin, and adipocyte-derived hormones contribute to the development of glomerular sclerosis. Thus, the results of these studies indicate that obesity independently affects the filtering capacity of the kidneys over time.[3]

As a result, a better assessment of renal function and dosage adjustment of drugs eliminated by the kidneys is needed in obese patients. The GFR is considered to be the best indicator of the filtering capacity of the kidneys and overall measure of renal function.[5] The most commonly used equations to estimate GFR are based on serum creatinine concentration (SCr). These equations provide practical and inexpensive methods for estimating GFR through the surrogate measure of CLcr. However, their accuracy and precision are affected by factors such as age, muscle mass, diet, and proximal tubule secretion of creatinine.[5] Most of the equations currently published for estimating CLcr have not been validated for use with obese patients. The exception is the Salazar-Corcoran[6] equation, developed using an obese rat model and then validated using data from obese patients from a study conducted by Dionne and colleagues.[7] Several studies have evaluated the accuracy and precision of currently published equations that estimate GFR in obese patients.[8,9,10] All methods produced CLcr estimates that significantly differed from the measured CLcr. On the other hand, two retrospective studies found the Salazar-Corcoran method to be the only unbiased and most precise equation for estimating CLcr in obese patients.[9,10] Aside from the Salazar-Corcoran method, there are no other valid equations for estimating CLcr in obese patients.

Recently, the Modification of Diet in Renal Disease (MDRD) Study Group developed a four-variable equation (MDRD4) to estimate the GFR using SCr, age, sex, and race.[11] The equation was evaluated in 1628 patients with a mean total body weight (TBW) of 79.6 kg. The MDRD4 equation does not include weight as a variable and thus avoids potential weight-related bias when used for obese patients. However, the equation has not been studied extensively with obese patients or patients with normal SCr values. In addition, the estimated GFR is expressed in milliliters per minute per 1.73 m2, necessitating the use of body surface area (BSA) equations to obtain GFR estimates in milliliters per minute. Since BSA equations have never been validated in obese patients, their use may contribute to biased results for this population.[12] Currently, the National Kidney Disease Education Program (NKDEP) advocates the use of the MDRD4 equation only for staging chronic kidney disease.[5] It does not recommend basing adjustments in drug dosing on CLcr estimates using the MDRD4 equation.

One of the most commonly used methods for estimating GFR is through the surrogate CLcr using the Cockcroft-Gault equation.[13] All Food and Drug Administration (FDA)-approved package inserts provide dosing adjustments based on CLcr estimated using the Cockcroft-Gault equation.[5] In addition, most pharmacokinetic studies in patients with chronic kidney disease have relied on the Cockcroft-Gault equation to stratify patients' disease severity. As a result, the Cockcroft-Gault equation has become a gold standard for estimating CLcr to adjust dosing regimens. However, CLcr is known to increase in a linear manner with lean body weight (LBW), and surrogates of this parameter have evolved to improve estimated CLcr by the Cockcroft-Gault method. Ideal body weight (IBW) as a substitute for LBW underestimates CLcr when using the Cockcroft-Gault equation.[14] This underestimation is expected, as obese patients have a greater total LBW than do normal-weight individuals of equal height, which is not accounted for by IBW equations. Adjusted body weight (ABW), which includes an adjustment factor of 0.3 (ABW0.3) or 0.4 (ABW0.4) to represent gain in LBW between TBW and IBW, was developed as a possible solution.[8,15] However, the validity of this approach in morbidly obese individuals has not been evaluated.

Han and colleagues[16] suggested that the use of LBW provides a more accurate estimate of CLcr. They used an LBW equation derived by Janmahasatian and colleagues[17] to reanalyze renal clearance data from another study that included normal-weight and obese patients. The results revealed that drug clearance for patients with different heights and weights is the same after adjusting for body composition. Consequently, the authors proposed that pharmacokinetic studies should use LBW to relate clearance and body composition.[17] They also recommended estimating LBW using derived equations or standard methods such as dual-energy x-ray absorptiometry (DXA) or bioelectric impedance analysis (BIA).

The Cockcroft-Gault equation is the most widely used clinical method for estimating CLcr to adjust drug dosages. We conducted a prospective study to evaluate whether the use of different body-size descriptors could improve CLcr estimates using the Cockcroft-Gault equation. We hypothesized that use of fat-free weight (FFW) estimated using BIA in the Cockcroft-Gault equation would provide better estimates of CLcr. In addition, we compared the Cockcroft-Gault using TBW, IBW, FFW, and LBW with the MDRD4 and Salazar-Corcoran equations for estimating CLcr in obese patients. We enrolled only morbidly obese patients (BMI of ≥40.0 kg/m2), since this population has been consistently underrepresented in previous trials.


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