title: [Useful tests to assess the clinical usefulness of new prognostic markers: the example of heart failure].
abstract: BACKGROUND
  Identification of risk factors is one of the most frequent questions in medical research currently. Several reports showed "significant" and "independent" prognostic factors in a variety of human conditions, however, those were not tested about predictive information in addition to standard risk markers. Recently novel statistical approaches (reclassification) have been developed to test the performance and usefulness of new risk factors and prognostic markers. There are several established methods to test the prognostic models.
  
  
  OBJECTIVE
  The aim of this work was to present the application of these novel statistical approaches by re-analyzing previously reported results of the authors.
  
  
  METHODS
  The authors analyzed the prognostic role of two markers: red cell distribution width and heat shock protein 70 in patients with heart failure. Using Cox regression analyses the authors have reported previously that both markers are independent predictors. In the present study they re-analyzed the role of red cell distribution width and heat shock protein 70 by reclassification tests.
  
  
  RESULTS
  Incorporating red cell distribution width to the reference model the authors found a significant improvement in discrimination . However, the reclassification analysis provided ambiguous results with heat shock protein 70.
  
  
  CONCLUSIONS
  Interpretation of results on new prognostic factors has to be done carefully, and appropriate reclassification approaches may help to confirm clinical usefulness only.
authors: Semmelweis Egyetem, Általános Orvostudományi Kar III. Belgyógyászati Klinika, Kutatólaboratórium Budapest Kútvölgyi út 4. 1125.
authors: Zsigmond Máté
authors: ZM
authors: Jenei
authors: Zoltán
authors: Z
authors: Prohászka
mesh_terms: D019540:Area Under Curve; D015415:Biomarkers / Q000097:blood*; D002097:C-Reactive Protein / Q000378:metabolism; D004912:Erythrocytes / Q000473:pathology*; D005260:Female; D018840:HSP70 Heat-Shock Proteins / Q000097:blood; D006333:Heart Failure / Q000097:blood / Q000175:diagnosis* / Q000401:mortality / Q000473:pathology; D006801:Humans; D008297:Male; D008875:Middle Aged; D020097:Natriuretic Peptide, Brain / Q000097:blood; D010446:Peptide Fragments / Q000097:blood; D011379:Prognosis; D016016:Proportional Hazards Models; D012372:ROC Curve; D018570:Risk Assessment; D012307:Risk Factors; D012680:Sensitivity and Specificity; D016019:Survival Analysis
chemical_list: D015415:Biomarkers; D018840:HSP70 Heat-Shock Proteins; D010446:Peptide Fragments; C109794:pro-brain natriuretic peptide (1-76); D020097:Natriuretic Peptide, Brain; D002097:C-Reactive Protein