- Course: MBChB
- Authors: Fergus Caskey
- Contact details: fergus.caskey@bristol.ac.uk
The issue that we identified
Kidney function was historically assessed using the blood level of serum creatinine, but this had limitations as creatinine in the blood comes from muscle and is therefore determined by more than just kidney function. Two people with the same kidney function will therefore have different creatinine levels in their blood if they have different muscle mass. Factors associated with muscle mass include age, sex, and weight.
Since 1976, equations have been developed to estimate kidney function using blood (serum) creatinine alongside other information about the patient, such as age, sex, body weight. One formula, the MDRD equation developed in 1999 in the United States of America, included African American race as one of its variable, because inclusion of this variable improved the model that estimated kidney function. Later United States and then global guideline bodies then recommended using this equation (and a later adaptation, the CKD-EPI equation) to diagnose chronic kidney disease (CKD) and determine staging.
Initially this use of an African American variable was not challenged, as it is fairly common place in epidemiology to build models using variables that select themselves on the basis of what the add to model performance. However, in 2020 people starting probing into the evidence for its inclusion and questioning a number of assumptions:
- The patients included in the studies that were used to develop the MDRD and CKD-EPI equations were from the United States, and Black people in those studies were predominantly from very low socio-economic backgrounds. This raised the possibility that it was not being African American that affected your creatinine generations, but your poverty and perhaps the effect that has on your diet.
- There was very little research establishing the link between African American status and creatinine generations
- New research in Africa showed that the inclusion of the African American coefficient in the kidney function equations did not improve their accuracy in African populations (and indeed had the opposite effect)
- The African American coefficient assumes that all African American are the same (and that all non-African Americans are the same).
By assuming that African American’s generated more creatinine, adjusting for this meant that for the same serum creatinine an African American was estimated to have better kidney function than non-African American with the same serum creatinine. This created a dilemma:
- If this assumption was incorrect, it was argued that African Americans would be being systematically disadvantaged in terms of timeliness of referral for dialysis or kidney transplantation.
- If this assumption was correct, however, dropping the African American coefficient would lead to African Americans being labelled with more severe CKD than they actually had, and this might affect access to certain drugs and or insurance.
Actions
In 2021, kidney doctor associations in the United States recommended dropping the African American coefficient from equations estimating kidney function
Shortly after this, researchers in the United States (who had developed the MDRD and CKD-EPI equations) developed a new equation that did not include an African American coefficient.
In the UK, NICE revised its CKD guidance and advised dropping the African American coefficient. Instead, it emphasises the role of clinicians in considering the individual (and their muscle mass) when interpreting serum creatinine and estimated glomerular filtration rate. NICE has not yet advised on use of the new equation.
Impacts
The impact of this change needs to be formally evaluated in research, in particular does it lead to reductions or increases in kidney health inequalities. Efforts are now increasingly going into finding new biomarkers that better estimate kidney function, independent of muscle mass.
What we have learned
The case highlights how a whole global community can accept a research finding and associated guidance without challenging the underlying empirical evidence and assumptions. It also highlights how difficult it can be to know what the right thing to do is, when dropping a race indicator could lead to worsening of kidney health inequalities.