A Decade After the KDOQI CKD Guidelines: Impact on CKD Guidelines

Abstract

Treatments for individuals with kidney diseases are understudied, as shown by the relatively small number of trials in nephrology compared with other specialties.1Strippoli G.F. Craig J.C. Schena F.P. The number, quality, and coverage of randomized controlled trials in nephrology.J Am Soc Nephrol. 2004; 15: 411-419Crossref PubMed Scopus (266) Google Scholar Nevertheless, even in a small field like nephrology, the rate at which new research is published is too fast for individual clinicians to keep abreast of important developments. Guidelines are tools to overcome the problem of information overload and help inform practitioner and patient decisions. Guideline recommendations build on systematic reviews of best available evidence that summarize risks and benefits of different strategies. The starting point for a systematic review is the “PICO” question, which defines Population of Interest, Intervention, Comparator, and Outcomes. The specification of the disease and the inclusion and exclusion criteria for the population are critical for refining this question and guiding the review process. Without a clear definition of the population, question formulation, searching, screening of literature, and synthesis cannot proceed purposefully. Before the 2002 KDOQI (Kidney Disease Outcomes Quality Initiative) chronic kidney disease (CKD) guidelines,2National Kidney FoundationK/DOQI Clinical Practice Guidelines for Chronic Kidney Disease: evaluation, classification, and stratification.Am J Kidney Dis. 2002; 39: S1-S266PubMed Google Scholar the terminology for CKD consisted of a confusing array of terms. The creation of a unifying approach for defining and staging CKD is a major achievement of the KDOQI guidelines.2National Kidney FoundationK/DOQI Clinical Practice Guidelines for Chronic Kidney Disease: evaluation, classification, and stratification.Am J Kidney Dis. 2002; 39: S1-S266PubMed Google Scholar The definition was based predominantly on face validity and expert consensus: if peak glomerular filtration rate (GFR) during young adulthood is ∼120 mL/min/1.73 m2, a persistent 50% reduction, in other words, ≤60 mL/min/1.73 m2, constituted CKD. Supporting evidence showed an increasing rate of CKD complications in individuals starting at GFR <60 mL/min/1.73 m2. As another independent criterion, the definition included a marker for chronic kidney damage, which in most cases is proteinuria. The KDOQI CKD guidelines stratified stages of CKD based on GFR ranges that were linked to a specific action plan. Extensive research subsequently has validated the prognostic importance of decreased GFR and has shown graded risk relationships according to CKD stages for kidney failure, cardiovascular disease, and mortality.3Go A.S. Chertow G.M. Fan D. et al.Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization.N Engl J Med. 2004; 351: 1296-1305Crossref PubMed Scopus (8722) Google Scholar The CKD definition and staging system have served as a point of reference for describing populations in subsequent interventional CKD guidelines. For example, the KDOQI hypertension guidelines reviewed trials when the study population or a subgroup met the definition of CKD regardless of pathologic diagnosis.4National Kidney FoundationK/DOQI Clinical Practice Guidelines on Hypertension and Antihypertensive Agents in Chronic Kidney Disease.Am J Kidney Dis. 2004; 43: S1-S290PubMed Google Scholar The literature strategy for the hypertension guidelines included a Boolean combination of the terms for proteinuria and hypertension because at the time, individuals with hypertension and proteinuria were not necessarily identified as having kidney disease. The guidelines further used proteinuria to stratify recommendations for blood pressure targets and choice of antihypertensive agents. Clinical research studies are now using CKD stages for inclusion and exclusion criteria in patient recruitment (eg,5Cardiff UniversityRisk Factors for Foot Ulceration in the CKD Population.http://clinicaltrials.gov/ct2/show/NCT01089829Google Scholar), which will further help standardize the grouping of trials in systematic reviews. Furthermore, KDIGO (Kidney Disease: Improving Global Outcomes) treatment guidelines6Kidney Disease: Improving Global Outcomes (KDIGO) Anemia Work GroupKDIGO Clinical Practice Guideline for Anemia in Chronic Kidney Disease.Kidney Int Suppl. 2012; 2: 279-335Crossref Scopus (625) Google Scholar now use a refined CKD nomenclature to specify the target CKD population in each recommendation (Table 1).Table 1Nomenclature for CKDReproduced from KDIGO anemia guidelines6Kidney Disease: Improving Global Outcomes (KDIGO) Anemia Work GroupKDIGO Clinical Practice Guideline for Anemia in Chronic Kidney Disease.Kidney Int Suppl. 2012; 2: 279-335Crossref Scopus (625) Google Scholar with permission of KDIGO.CKD CategoriesDefinition CKD CKD of any stage (1-5), with or without a kidney transplant, including both non–dialysis-dependent CKD (CKD 1-5ND) and dialysis-dependent CKD (CKD 5D) CKD ND Non–dialysis-dependent CKD of any stage (1-5), with or without a kidney transplant (ie, CKD excluding CKD 5D) CKD T Non–dialysis-dependent CKD of any stage (1-5) with a kidney transplantSpecific CKD stagesDefinition CKD 1, 2, 3, 4 Specific stages of CKD, CKD ND, or CKD T CKD 3-4, etc Range of specific stages (eg, both CKD 3 and CKD 4) CKD 5D Dialysis-dependent CKD 5 CKD 5HD Hemodialysis-dependent CKD 5 CKD 5PD Peritoneal dialysis–dependent CKD 5Abbreviations: CKD, chronic kidney disease; D, dialysis; HD, hemodialysis; ND, non-dialysis; PD, peritoneal dialysis; T, transplant. Open table in a new tab Abbreviations: CKD, chronic kidney disease; D, dialysis; HD, hemodialysis; ND, non-dialysis; PD, peritoneal dialysis; T, transplant. New evidence may necessitate re-evaluation or modification of a disease system. The KDOQI CKD guidelines have stirred public debate about the clinical meaning of early CKD stage 3.7Eckardt K.U. Berns J.S. Rocco M.V. et al.Definition and classification of CKD: the debate should be about patient prognosis—a position statement from KDOQI and KDIGO.Am J Kidney Dis. 2009; 53: 915-920Abstract Full Text Full Text PDF PubMed Scopus (177) Google Scholar Emerging data from the CKD Prognosis Consortium show that while the risk increases at GFR <60 mL/min/1.73 m2, there is a steep increase at GFR <45 mL/min/1.73 m2.8Levey A.S. de Jong P.E. Coresh J. et al.The definition, classification, and prognosis of chronic kidney disease: a KDIGO Controversies Conference report.Kidney Int. 2011; 80: 17-28Crossref PubMed Scopus (1428) Google Scholar Further, the consortium analyses showed that proteinuria stages are as powerful as predictors for cardiovascular disease and mortality as GFR stages.8Levey A.S. de Jong P.E. Coresh J. et al.The definition, classification, and prognosis of chronic kidney disease: a KDIGO Controversies Conference report.Kidney Int. 2011; 80: 17-28Crossref PubMed Scopus (1428) Google Scholar In light of these findings, a KDIGO CKD guideline work group was charged to re-evaluate the KDOQI CKD classification. The work group had to consider that changes to the classification may have major implications for comparability of trials, clinical cohorts, and consistency across guidelines. Giving preference to maintaining compatibility and allowing integration of prior and new staging approaches, the KDIGO CKD guideline authors have adopted a conservative approach that preserves the KDOQI definition and GFR stages. However, the upcoming KDIGO recommendations propose a subdivision of GFR stage 3 into GFR stage 3a and stage 3b. Also, they expand the CKD risk states in a 2-dimensional grid with proteinuria categories on the horizontal axes and GFR categories on the vertical axes. They further propose an approach that harmonizes across different proteinuria and albuminuria measurements and metrics, establishing 3 discrete categories of albuminuria/proteinuria. This harmonization and categorization of proteinuria again should provide a point of reference for consistent characterization of proteinuria in CKD studies and facilitate combining studies in systematic reviews. Although the unifying notion of CKD undoubtedly has been a major step in facilitating evidence synthesis, CKD describes a heterogeneous syndrome rather than a uniform disease entity. The clinical meaning of a certain level of GFR or albuminuria depends on various patient and disease factors. Obviously, the cause of kidney disease is of particular relevance. Combining information about diagnosis, GFR, and albuminuria categories is likely to outperform the predictive value of the latter 2 measurements alone. Thus, the upcoming KDIGO CKD guideline proposes to include type of kidney disease in the characterization of patients with CKD, which is analogous to combining tumor type with TNM staging in oncology. Splitting the CKD syndrome into defined subsets of individuals with similar pathophysiology, clinical characteristics, and prognosis will greatly facilitate the development and testing of new treatments. More nuanced stratification is possible with the use of sophisticated modeling that incorporates additional variables.9Tangri N. Stevens L.A. Griffith J. et al.A predictive model for progression of chronic kidney disease to kidney failure.JAMA. 2011; 305: 1553-1559Crossref PubMed Scopus (666) Google Scholar Expanded panels of risk factors and biomarkers are candidates for exploration.10Fassett R.G. Venuthurupalli S.K. Gobe G.C. et al.Biomarkers in chronic kidney disease: a review.Kidney Int. 2011; 80: 806-821Crossref PubMed Scopus (310) Google Scholar However, the ultimate goal should be to develop parsimonious models that include easily measured and widely available variables and to agree on using the same discrete risk categories.11Brotman D.J. Walker E. Lauer M.S. O'Brien R.G. In search of fewer independent risk factors.Arch Intern Med. 2005; 165: 138-145Crossref PubMed Scopus (112) Google Scholar As the success story of the KDOQI CKD classification has shown, a concerted effort that culminated in a harmonized CKD disease classification allowed comparison across clinical cohorts. This was critical for systematic evidence review and guideline development, which in turn accelerated the generation and translation of new knowledge. Dr Uhlig served as the Director of Guideline Development for KDOQI and KDIGO guidelines, and Dr Eckardt served as a KDIGO Chair. Financial Disclosure: Dr Eckardt has served on the boards of Amgen (ARO Initiative), Sandoz-Hexal (Data and Safety Monitoring Board), Johnson & Johnson (Scientific Advisory Board), and Roche (Data and Safety Monitoring Board). He also has consulted for Amgen, Fresenius, Glaxo SmithKline, Sanofi-Aventis, Bayer, Johnson & Johnson, Roche, and Abbott and received lecture fees from Amgen, Genzyme, Fresenius, and Roche. Dr Uhlig declares that she has no relevant financial interests.