title: Characterizing predictive models of mortality for older adults and their validation for use in clinical practice.
abstract: OBJECTIVE
  To systematically identify and characterize prognostic models of mortality for older adults, their reported potential use, and the actual level of their (external) validity.
  
  
  METHODS
  The Scopus database until January 2010 was searched for articles that developed and validated new models or validated existing prognostic models of mortality or survival in older adults.
  
  
  METHODS
  All domains of health care.
  
  
  METHODS
  Adults aged 50 and older.
  
  
  METHODS
  Study and model characteristics were summarized, including the model's development method and degree of validation, data types used, and outcomes.
  
  
  RESULTS
  One hundred three articles describing 193 models in 10 domains and mostly originating from the United States were included. These domains were mostly secondary or tertiary care settings (54%) such as intensive care (7%) or geriatric units (8%). Half of the studies (50%) were not disease specific. Heart failure-related diseases (9%) and pneumonia (9%) constituted the major disease-specific subgroups. Most studies (67%) reported support of clinical individual (treatment) decisions as use of prognostic models, but only 34% were externally validated, and only four models (2%) were validated in more than two studies. Most studies (68%) developed at least one new model, but they did not often go beyond addressing their apparent validation (49%).
  
  
  CONCLUSIONS
  Although prognostic models are regularly developed to support clinical individual decisions and could be useful for this purpose, their use is premature. Because clinical credibility and evidence of external validity build trust in prognostic models, both require much more consideration to enhance model acceptance in the future.
authors.affiliation: Department of Medical Informatics, Academic Medical Center, Amsterdam, the Netherlands. L.Minne@amc.uva.nl
authors.forename: Lilian
authors.initials: L
authors.lastname: Minne
authors.forename: Jeroen
authors.initials: J
authors.lastname: Ludikhuize
authors.forename: Sophia E J A
authors.initials: SE
authors.lastname: de Rooij
authors.forename: Ameen
authors.initials: A
authors.lastname: Abu-Hanna
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002908:Chronic Disease / Q000401:mortality*; D015897:Comorbidity; D003431:Cross-Cultural Comparison; D005260:Female; D015577:Geriatric Assessment / Q000706:statistics & numerical data*; D017052:Hospital Mortality; D006801:Humans; D015993:Life Tables; D008297:Male; D008875:Middle Aged; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data; D011379:Prognosis; D018570:Risk Assessment / Q000706:statistics & numerical data