title: Time-dependent Cox regression: serial measurement of the cardiovascular biomarker proadrenomedullin improves survival prediction in patients with lower respiratory tract infection.
abstract: BACKGROUND
  The aim of this study was to determine the prognostic utility of serial measurement of the cardiovascular biomarker midregion proadrenomedullin (MR-proADM) in patients admitted with lower respiratory tract infection. In a previous trial in dyspneic patients (BACH trial) we could show that serial measurement of MR-proADM proves useful for risk assessment and patient monitoring. Models designed to evaluate serial biomarker measurements usually fail to answer two fundamental questions necessary to judge their clinical relevance: whether serial measurements provide additional information on top of the first measurement, and, if yes, at which time point a re-evaluation may be clinically useful.
  
  
  METHODS
  We apply an adapted time-dependent Cox model to data from the ProHosp trial, a prospective trial, which was observational in regards to application of prognostic biomarkers, where blood draws for biomarker evaluation were collected at day of patient inclusion, days 3, 5 and 7. In this trial, the cardiovascular biomarker MR-proADM was evaluated for its ability to predict survival in comparison to clinical risk scores.
  
  
  RESULTS
  With the adapted time-dependent Cox model, we could demonstrate a significant added value of the follow up measurements on top of that obtained on admission. Despite a high correlation between serial measurements, the gain can be observed as early as 3 days after inclusion. We illustrate the added prognostic value and clinical relevance of re-evaluation via Kaplan-Meier plots.
  
  
  CONCLUSIONS
  We could demonstrate that the prognostic biomarker MR-proADM can potentially serve as a outcome monitoring marker in patients admitted with lower respiratory tract infections.
authors.affiliation: Clinical Diagnostics Division, Thermo Fisher Scientific/BRAHMS GmbH, Hennigsdorf, Germany.
authors.forename: Oliver
authors.initials: O
authors.lastname: Hartmann
authors.forename: Philipp
authors.initials: P
authors.lastname: Schuetz
authors.forename: Werner C
authors.initials: WC
authors.lastname: Albrich
authors.forename: Stefan D
authors.initials: SD
authors.lastname: Anker
authors.forename: Beat
authors.initials: B
authors.lastname: Mueller
authors.forename: Thorsten
authors.initials: T
authors.lastname: Schmidt
mesh_terms: D053607:Adrenomedullin / Q000097:blood*; D000368:Aged; D000369:Aged, 80 and over; D015415:Biomarkers / Q000097:blood; D002318:Cardiovascular Diseases / Q000097:blood* / Q000175:diagnosis* / Q000401:mortality; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011446:Prospective Studies; D011498:Protein Precursors / Q000097:blood*; D012044:Regression Analysis; D012141:Respiratory Tract Infections / Q000097:blood* / Q000175:diagnosis* / Q000401:mortality; D015996:Survival Rate / Q000639:trends; D013997:Time Factors
chemical_list: D015415:Biomarkers; D011498:Protein Precursors; C088633:proadrenomedullin; D053607:Adrenomedullin