title: A new tool for predicting the probability of chronic kidney disease from a specific value of estimated GFR.
abstract: OBJECTIVE
  To demonstrate how patients' probability of having chronic kidney disease (CKD) stage 3-5 (measured GFR <60 mL/min/1.73 m(2)) can be predicted from a specific value of estimated glomerular filtration rate (eGFR).
  
  
  METHODS
  The probability of CKD stage 3-5 was predicted from a logistic regression model (n = 850) using three different eGFR prediction equations: Lund-Malmö, MDRD and CKD-EPI. Population weighting was used to illustrate how this probability varies in three different populations: original sample (55% true prevalence of CKD stage 3-5), a screening (6.7% prevalence) and a CKD population (84% prevalence).
  
  
  RESULTS
  All three eGFR-equations had high classification ability (area under the receiver-operating-characteristic curve = 97%). The probability of CKD stage 3-5 increased with decreasing eGFR, varied substantially among the populations studied and to some extent between the eGFR-equations. Using the Lund-Malmö equation as illustration, the probability of CKD stage 3-5 is > 90% only when eGFR is <38 mL/min/1.73 m(2) in a screening population, whereas it is > 90% already when eGFR is <51 mL/min/1.73 m(2) in a CKD population. Conversely, the probability of CKD stage 3-5 is <10% if eGFR > 59 mL/min/1.73 m(2) in a screening population, whereas it is <10% only when eGFR is > 88 mL/min/1.73 m(2) in a CKD population.
  
  
  CONCLUSIONS
  Instead of reporting diagnostic accuracy as sensitivity, specificity, and predictive values, actual eGFR supplemented with the probability that it represents a true GFR <60 mL/min/1.73 m(2) may be more valuable for physicians. Clinical (pre-test) probability in the population must be considered when predicting this probability.
authors.affiliation: Competence Centre for Clinical Research, Lund University Hospital, Lund, Sweden.
authors.forename: Jonas
authors.initials: J
authors.lastname: Björk
authors.forename: Anders
authors.initials: A
authors.lastname: Grubb
authors.forename: Gunnar
authors.initials: G
authors.lastname: Sterner
authors.forename: Ulf
authors.initials: U
authors.lastname: Nyman
mesh_terms: D000328:Adult; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D007472:Iohexol; D007676:Kidney Failure, Chronic / Q000175:diagnosis* / Q000453:epidemiology; D016015:Logistic Models; D008297:Male; D015995:Prevalence; D011336:Probability; D051436:Renal Insufficiency, Chronic / Q000175:diagnosis* / Q000453:epidemiology; D013548:Sweden / Q000453:epidemiology
chemical_list: D007472:Iohexol