title: Prediction of mortality risk in the elderly.
abstract: OBJECTIVE
  Ways to predict the risk of cardiovascular (CV) events or all-cause mortality have largely been derived from populations in which old and very old subjects were underrepresented. We set out to estimate the incremental prognostic utility of inflammation and atherosclerosis markers in the prediction of all-cause and CV mortality in elderly men.
  
  
  METHODS
  In a prospective population-based cohort study, conventional CV risk factors were documented in 403 independently living elderly men. C-reactive protein (CRP) and interleukin (IL)-6 levels were measured. Carotid plaques were assessed by ultrasound. Analyses were performed with proportional hazards analyses, and bootstrapping was used for internal validation. Main outcome was CV and all-cause mortality occurring during 4 years of follow-up.
  
  
  RESULTS
  Increasing tertiles of CRP, IL-6, and number of plaques were independently associated with all-cause and CV mortality. With information on age, carotid plaques, IL-6, and CRP yielded good discriminatory power for all-cause and CV mortality: area under the receiver operating characteristic curve (95% confidence interval), 0.76 (0.70-0.82) and 0.74 (0.68-0.80), respectively. Combined use of only IL-6 and plaque burden allowed identification of subjects with low and high mortality risk. The Framingham PROCAM and a Dutch Risk Function poorly predicted mortality risk, similar or worse than a model using age alone.
  
  
  CONCLUSIONS
  In the old and very old, IL-6 and number of carotid plaques are powerful predictors of mortality risk in the years to come. Conventional risk scores seem to perform unsatisfactorily.
authors.affiliation: Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
authors.forename: Stefan
authors.initials: S
authors.lastname: Störk
authors.forename: Richard A
authors.initials: RA
authors.lastname: Feelders
authors.forename: Annewieke W
authors.initials: AW
authors.lastname: van den Beld
authors.forename: Ewout W
authors.initials: EW
authors.lastname: Steyerberg
authors.forename: Huub F J
authors.initials: HF
authors.lastname: Savelkoul
authors.forename: Steven W J
authors.initials: SW
authors.lastname: Lamberts
authors.forename: Diederick E
authors.initials: DE
authors.lastname: Grobbee
authors.forename: Michiel L
authors.initials: ML
authors.lastname: Bots
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D015415:Biomarkers / Q000097:blood; D002097:C-Reactive Protein / Q000378:metabolism*; D002318:Cardiovascular Diseases / Q000097:blood / Q000209:etiology* / Q000401:mortality* / Q000473:pathology; D016893:Carotid Stenosis / Q000097:blood / Q000000981:diagnostic imaging / Q000473:pathology*; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007249:Inflammation / Q000097:blood*; D015850:Interleukin-6 / Q000097:blood*; D008297:Male; D016017:Odds Ratio; D011237:Predictive Value of Tests; D011379:Prognosis; D011446:Prospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D014463:Ultrasonography
chemical_list: D015415:Biomarkers; D015850:Interleukin-6; D002097:C-Reactive Protein