There are several laboratory-based calculations that aid in the diagnosis of chronic kidney disease (CKD). The urine albumin to creatinine ratio (uACR) is a fundamental measurement in the diagnosis of CKD and is an early indicator of end-stage renal disease; the ratio has been incorporated into kidney failure risk predictions/algorithms(1). Despite its clinical utility in the evaluation of kidney function, reporting uACR results has been challenging for laboratories and the clinicians they serve(2). The uACR is calculated by dividing the urine albumin (uAlb) concentration, measured in mg/L, by the concentration of urine creatinine (uCr), measured in mg/dL; the end result reports the ratio as milligrams of urine albumin to grams of creatinine. The ratio allows for the adjustment of uAlb to the overall concentrate of urine, limiting the influence of water balance, urinary flow rate, and time of collection, on result interpretation. Increased renal permeability is associated with uACR ≥ 30 mg albumin/g creatinine, and even lower concentrations can be consequential(3). In individuals without increased renal permeability or kidney damage, elevated concentrations of albumin should not be present in the urinary filtrate and would fall below the manufacturer-defined limit of quantitation (LOQ). In cases where the uAlb concentration is less than the defined LOQ, the result is usually transmitted as “less than”, meaning that there is no numeric value provided to use as the numerator for the uACR equation. When this occurs, laboratories generally use one of two approaches:

  1. Report the uAlb result as <LOQ and the uCr as a numeric value, but result the ratio as “unable to calculate”
  2. Use the most conservative estimate for the numerator and divide this by the numeric result for uCr. The result is reported as a “less than” the calculated ratio.

The first approach is suboptimal because it implies there is no mechanism available to estimate uACR; the second is suboptimal because it can lead to an overestimation of risk. Of the two options, the latter is preferred because it provides an estimated value that may be used in risk equations and allows for some disease risk stratification(4). In the latter approach if the manufacturer defined LOQ was 12 mg/L any uAlb “less than” result would use 11.9 mg/L as the numerator in the uACR equation. For samples with a true uAlb concentration <11.9 mg/L, this approach artificially elevates the ratio. Given these limitations, we sought to investigate a third approach: challenge our uAlb assay at concentrations below the LOQ(5).

To illustrate, in a screening cohort of ~1200 uAlb results, 40% of individuals had a urine albumin concentration below the manufacturer defined LOQ of 12 mg/L (Figure 1). However, the limit of detection is 3 mg/L; the input of numeric value down to the LOD decreased abnormal flagging by 21%, and 105 people were provided with a quantitative result to be used for further risk evaluation, as applicable. Given the clinical relevance, the performance characteristics of a lower uAlb LOQ were evaluated. Linearity, precision, and method comparison experiments were completed, and the data confirmed that the analytical performance of values in this concentration range were similar to those at the manufacturer defined LOQ. Thus, validation of numeric reporting to the assay LOD provided additional potential to the uACR as a kidney function screening tool.

Laboratory assays aren’t perfect, and lack of standardization among assays can lead to disparate interpretation across platforms. Urine albumin is no exception and there is work underway to improve consistency between labs(6). However, lack of standardization limits consistent interpretation of all results, not just those near the LOQ(7). A holistic approach to improving result reporting requires creative solutions to their limitations. Lowering the LOQ for uAlb assays may improve CKD risk assessment and prediction of future risk for kidney failure.


  1. Tangri N, Grams ME, Levey AS, Coresh J, Appel LJ, Astor BC, et al. Multinational Assessment of Accuracy of Equations for Predicting Risk of Kidney Failure: A Meta-analysis. JAMA. 2016;315(2):164-74.

  2. Vassalotti JA, Boucree SC. Integrating CKD Into US Primary Care: Bridging the Knowledge and Implementation Gaps. Kidney Int Rep. 2022;7(3):389-96.

  3. Neuen BL, Weldegiorgis M, Herrington WG, Ohkuma T, Smith M, Woodward M. Changes in GFR and Albuminuria in Routine Clinical Practice and the Risk of Kidney Disease Progression. Am J Kidney Dis. 2021;78(3):350-60 e1.

  4. Miller WG, Bachmann LM, Fleming JK, Delanghe JR, Parsa A, Narva AS, et al. Recommendations for Reporting Low and High Values for Urine Albumin and Total Protein. Clin Chem. 2019;65(2):349-50.

  5. Greene DN, Marzinke MA, Carter C, Chen J, Hoenig MP, Rummel M. Decreasing the Lower Limit of Quantitation for Urine Albumin Improves Clinical Utility. J Appl Lab Med. 2022;7(5):1145-50.

  6. Miller WG, Seegmiller JC, Lieske JC, Narva AS, Bachmann LM. Standardization of Urine Albumin Measurements: Status and Performance Goals. J Appl Lab Med. 2017;2(3):423-9.

  7. Merrill AE, Khan J, Dickerson JA, Holmes DT, Harris NS, Greene DN. Method-to-method variability in urine albumin measurements. Clin Chim Acta. 2016;460:114-9.