GFR estimating equations, CKD prevalence and the public health

In 2002, the US National Kidney Foundation released clinical practice guidelines [the Kidney Disease Outcomes Quality Initiative (K / DOQI)] aimed at standardizing and simplifying the definition of chronic kidney disease (CKD). These guidelines classify CKD in part by glomerular filtration rate (GFR) estimated either by the Cockcroft–Gault or the Modification of Diet in Renal Disease (MDRD) study equations. The Cockcroft–Gault formula was derived from 249 mostly male Canadians [1] and the MDRD equation from 1628 mostly white study subjects with measured GFR by iothalamate of 22–55 mL min−1 1.73m−2 [2]. The wisdom of applying an equation derived within a population with moderate to advanced CKD to the general population is debatable, yet the MDRD equation nonetheless has become the ‘industry standard’ for estimating GFR, as evidenced by its widespread application in clinical research and its routine reporting in many laboratories. In the current issue of the Journal of Internal Medicine, Holzmann et al. [3] applied the abbreviated 4-variable MDRD equation in 571 353 adult outpatients undergoing a general health examination from the Swedish Apolipoprotein-related Mortality risk (AMORIS) cohort. Using a Cox proportional hazards regression model, the authors examined the relations among estimated GFR and risk of first myocardial infarction or death. In addition to using the MDRD equation, analyses were repeated using the so-called Mayo quadratic equation to estimate GFR, a formula derived in 2004 that included persons with CKD as well as healthy prospective kidney donors [4]. The Holzmann et al. study showed that for those individuals with an estimated GFR of 30–59 mL min−1 1.73 m−2 by either the MDRD or Mayo quadratic equation, adjusted hazard ratios for first myocardial infarction (MI) and all-cause mortality were significantly increased as compared with the referent group of those with normal to near-normal kidney function (estimated GFR >90 mL min−1 1.73 m−2). The group with advanced CKD (GFR 90 mL min−1 1.73m−2. In contrast, using the MDRD equation, the adjusted relative risk of death was actually decreased by 23% (21–25%) relative to persons with estimated GFR >90 mL min−1 1.73 m−2 and there was no difference in MI risk. Aside from differences in relative risk estimates, Holzmann et al. also showed strikingly different prevalence estimates of CKD depending on which GFR estimating equation was used. With the MDRD equation, only 37.4% of participants had normal kidney function versus 86.6% when the Mayo quadratic equation was used. As no gold standard was used to directly measure GFR, which estimate is closer to the truth? The monotonic increase in risk associated with lower estimated GFR using the Mayo quadratic equation is biologically plausible. It is difficult to explain why impaired kidney function would be associated with enhanced survival (as was seen with application of the MDRD equation), based on known correlates of CKD and the totality of evidence from experimental and epidemiological studies. A more likely explanation is that when applied to the general population on a single measurement, the MDRD equation misclassifies a large fraction of persons with normal or near normal kidney function as having mild (60–89 mL min−1 1.73 m−2) or moderate ‘CKD’ (30–59 mL min−1 1.73 m−2). After initial publication of the K/DOQI clinical practice guidelines, several studies have shown that the MDRD equation underestimates measured GFR around or above the upper levels at which the equation was derived [4,7, 8]. Misclassification of mild CKD has potentially enormous public health implications. If the prevalence estimates in this study were applied to the general adult population of the United States, the number of people affected / diagnosed / classified with mildly reduced GFR (estimated GFR 60–89 mL min−1 1.73 m−2) could differ by 4–5 fold depending on whether the Mayo quadratic or the MDRD equation were used. As the population attributable risk depends directly on the prevalence of disease, focusing efforts to modify cardiovascular risk factors on the largest of all groups with kidney disease would most likely have the largest impact on public health. On the other hand, targeting millions of people who may be erroneously categorized as having reduced GFR would be colossal waste of time, effort and money. It is therefore precisely in this population (i.e. CKD stage II and the upper range of CKD stage III), where the MDRD equation performs least well, that accurate identification and diagnosis of bona fide, clinically meaningful kidney disease is most imperative. Erroneously informing a patient that he or she has CKD could also lead to a host of adverse downstream consequences, including unnecessary office visits, blood tests, and interventions; difficulties obtaining health or life insurance; and undue anxiety, stress and worry. From the provider’s perspective, the time spent explaining misclassification of disease states by regression equations and / or reassuring a patient that he or she effectively does not have kidney disease is time that could otherwise be spent in more productive activities that could advance health and prevent disease and disability. Finally, misclassification of mild to moderate CKD could contribute to kidney transplant gridlock, as prospective living donors might be incorrectly deemed unsuitable based on falsely low MDRD GFR estimates. In summary, Holzmann et al. present an interesting and extremely important study that highlights both the calculated and real hazards inherent in applying a GFR estimating equation derived within a population with moderate to severe CKD to the general population. The major strengths of the study include its large well characterized cohort with relatively long follow-up time. The study also has several limitations. First, only a single serum creatinine determination was required for inclusion in the study. Within-person variation of serum creatinine concentrations can be substantial, and repeated measurements of serum creatinine would likely have reduced the magnitude of misclassification bias using both equations. Second, the serum creatinine, despite being measured at a single laboratory, was not calibrated. Calibration could significantly influence the performance of the MDRD equation, and calibration could have reduced misclassification error. One study found higher measured serum creatinine by 20.3 µmol L−1 when compared with assays of the same sample performed in the original MDRD laboratory [9]. Third, the study did not have information on, and therefore could not control for, several other risk factors for cardiovascular disease such as albuminuria, hypertension, smoking, and antihypertensive medication use. Most of these limitations were acknowledged by the authors. In our collective enthusiasm to arrive at a convenient method by which CKD can be recognized, diagnosed and staged, we (including these editorialists) have been led like lemmings off a cliff for the better part of a decade, unquestioningly applying the MDRD equation to anyone and everyone, without recalling (or conveniently forgetting) the population in which it was derived. Until additional studies have been conducted, a more thoughtful strategy would be to consider the application of alternative GFR estimating equations in different situations. For example, the MDRD equation can be used to estimate GFR in persons known to have moderate to advanced CKD while the Mayo quadratic equation may be better suited to the general population. Whether noncreatinine-based markers such as cystatin C will offer significant advantages over creatinine-based GFR estimating equations remains to be seen. Whatever the approach, before blindly applying the MDRD equation to a patient in an ambulatory practice or a cohort in an epidemiological study, it is worthwhile to take a moment to pause and ponder its appropriateness while considering its alternatives.