title: Is there an additional benefit of serial NT-proBNP measurements in patients with stable chronic heart failure receiving individually optimized therapy?
abstract: BACKGROUND
  The role of serial NT-proBNP measurements in patients suffering from chronic systolic heart failure (CHF) who already receive individually optimized pharmacotherapy is still unresolved.
  
  
  METHODS
  NT-proBNP was assessed at baseline and at 6 months follow-up in 504 stable CHF patients treated with individually optimized pharmacotherapy. After assessment of clinical stability at 6 months, patients were followed up for at least 1 year. The combined primary endpoint was defined as death, hospitalization due to cardiac reasons or heart transplantation in 1-year follow-up. We stratified our patients according to two principles: first, a percent change of value (CV) between the first and second measurement of NT-proBNP and secondly, the transformed logarithm of NT-proBNP measured at 6 months.
  
  
  RESULTS
  During the follow-up period of 1 year, 50 patients (9.9%) reached the combined primary endpoint. Stratification according to percentage CV was less accurate in predicting endpoint-free survival compared to a classification in categories of lnNT-proBNP measured at 6 months (ROC AUC = 0.615; 95% CI 0.525-0.70 vs. ROC AUC = 0.790; 95% CI 0.721-0.856, respectively). When entered into proportional hazard regression analysis, lnNT-proBNP measured at 6 months remained an independent predictor of the combined primary endpoint with an associated HR of 2.53 (95% CI 1.385-4.280).
  
  
  CONCLUSIONS
  To date, this is the largest analysis of serial NT-proBNP measurements in patients with CHF receiving individually optimized medical therapy. These data suggest that a single NT-proBNP measurement after 6 months in stable clinical conditions may have higher predictive value than stratification of change in serial measurements.
authors.affiliation: Department of Cardiology, University of Heidelberg, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany. Jennifer.Franke@med.uni-heidelberg.de
authors.forename: Jennifer
authors.initials: J
authors.lastname: Franke
authors.forename: Lutz
authors.initials: L
authors.lastname: Frankenstein
authors.forename: Dieter
authors.initials: D
authors.lastname: Schellberg
authors.forename: Amer
authors.initials: A
authors.lastname: Bajrovic
authors.forename: Jan Sebastian
authors.initials: JS
authors.lastname: Wolter
authors.forename: Philipp
authors.initials: P
authors.lastname: Ehlermann
authors.forename: Andreas O
authors.initials: AO
authors.lastname: Doesch
authors.forename: Manfred
authors.initials: M
authors.lastname: Nelles
authors.forename: Hugo A
authors.initials: HA
authors.lastname: Katus
authors.forename: Christian
authors.initials: C
authors.lastname: Zugck
mesh_terms: D000368:Aged; D015415:Biomarkers / Q000097:blood; D002317:Cardiovascular Agents / Q000627:therapeutic use*; D016009:Chi-Square Distribution; D002908:Chronic Disease; D005260:Female; D005858:Germany; D006333:Heart Failure / Q000097:blood / Q000175:diagnosis / Q000188:drug therapy* / Q000401:mortality; D006760:Hospitalization; D006801:Humans; D053208:Kaplan-Meier Estimate; D008297:Male; D008875:Middle Aged; D020097:Natriuretic Peptide, Brain / Q000097:blood*; D010446:Peptide Fragments / Q000097:blood*; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D011446:Prospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D016896:Treatment Outcome
chemical_list: D015415:Biomarkers; D002317:Cardiovascular Agents; D010446:Peptide Fragments; C109794:pro-brain natriuretic peptide (1-76); D020097:Natriuretic Peptide, Brain