{"doi":"10.1093/clinchem/hvab260","title":"New Equations for Estimating Glomerular Filtration Rate","abstract":"The Chronic Kidney Disease Epidemiology (CKD-EPI) Collaboration has recently published new equations for calculating estimated glomerular filtration rate (eGFR) based on serum creatinine and cystatin C (1). Implementation of these new equations for routine reporting of eGFR in adults is strongly recommended (2). For approximately 15 years, US clinical laboratories have been encouraged to report eGFR with creatinine measurements in adults (3). This recommendation was based on the relatively high prevalence of chronic kidney disease, which affects approximately 14% of the US adult population, and which often goes undetected in its early stages. Changes in serum creatinine concentration may not appear significant (e.g., 0.80 mg/dL vs 1.00 mg/dL) and may even be within the typical population-based reference interval and therefore not flagged on laboratory reports. But that change represents a nearly 25% difference in eGFR (in a 65-year-old female, 78 vs 59 mL/min/1.73m2) using the current CKD-EPI creatinine eGFR equation. The first eGFR equation recommended for routine use in laboratory reports came from the Modification of Diet in Renal Disease (MDRD) study (3). At the time, calibration of creatinine measurement procedures was undergoing standardization. This was followed by the CKD-EPI equation, which had the advantage of being more accurate at values above 60 mL/min/1.73m2, and then by equations based on cystatin C, either alone or in combination with creatinine (4). A 2019 survey among 4,449 laboratories participating in the College of American Pathologists’ proficiency testing program showed that approximately 92% were reporting eGFR with creatinine measurements for adults, most doing so as a routine practice. Only 34% of labs were using the CKD-EPI equation for eGFR reporting; the majority were using an MDRD equation, often one that is not appropriate for creatinine assays that employ isotope-dilution mass-spectrometry-traceable calibration. In the data sets used for development of the MDRD equation and the 2009 CKD-EPI equations, the relationship between serum creatinine and measured GFR (mGFR) (measured using exogenous filtration markers) was found to vary by age, gender, and racial group (Black vs non-Black), with Black participants having higher mean serum creatinine concentrations relative to mGFR. Because information on a patient’s age and gender are usually available to the clinical laboratory, but less commonly a patient’s race, the recommended reporting format has been to routinely calculate and report 2 eGFRs, one for Black patients and one for non-Black patients (3). In recent years, there has been growing concern about the validity of using race designators in medicine, and the dual reporting of eGFR by race has been perceived by some to be an example of a flawed and inequitable practice (5). In the absence of authoritative recommendations, some laboratories have implemented different approaches to eliminate the race variable in eGFR calculations, including reporting values using the current equations without any adjustment for race, and reporting a range of values encompassing both Black and non-Black persons. The CKD-EPI Collaboration’s recommendation has now been published and provides an authoritative recommendation to clinical laboratories (1). κ = 0.7 if female or 0.9 if male; α = −0.241 if female or −0.302 if male. The new equations were derived using the same data sets that were used for development of the 2009 creatinine eGFR equation and the 2012 creatinine and cystatin C equation. These data sets included 32% and 40% Black participants, respectively. Pooling the earlier data sets without regard to race resulted in different values for some of the parameters in the new equations. New validation data sets were used that included both the 2012 external validation data set and several new validation data sets. In these validation data sets, the percentage of Black participants was 14%, which is similar to ","journal":"Clinical Chemistry","year":2021,"id":189592,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":15,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9497,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":20340,"name":"Gary L. Horowitz","orcid":null,"position":1,"is_corresponding":false},{"id":466008,"name":"Anthony A. Killeen","orcid":"0000-0003-1629-9468","position":0,"is_corresponding":true}],"reference_count":5,"raw_metadata":null,"created_at":"2026-07-18T23:49:18.604374Z","pmid":"35038742","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}