OBJECTIVES: To systematically identify and characterize prognostic models of mortality for older adults, their reported potential use, and the actual level of their (external) validity. DESIGN: 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. SETTING: All domains of health care. PARTICIPANTS: Adults aged 50 and older. MEASUREMENTS: 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%). CONCLUSION: 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.
OBJECTIVES: To systematically identify and characterize prognostic models of mortality for older adults, their reported potential use, and the actual level of their (external) validity. DESIGN: 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. SETTING: All domains of health care. PARTICIPANTS: Adults aged 50 and older. MEASUREMENTS: 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%). CONCLUSION: 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: Jerome L Fleg; Daniel E Forman; Kathy Berra; Vera Bittner; James A Blumenthal; Michael A Chen; Susan Cheng; Dalane W Kitzman; Mathew S Maurer; Michael W Rich; Win-Kuang Shen; Mark A Williams; Susan J Zieman Journal: Circulation Date: 2013-10-28 Impact factor: 29.690
Authors: Douglas A Wolf; Vicki A Freedman; Jan I Ondrich; Christopher L Seplaki; Brenda C Spillman Journal: J Gerontol B Psychol Sci Soc Sci Date: 2015-03-03 Impact factor: 4.077
Authors: Marco Falcone; Salvatore Corrao; Giuseppe Licata; Pietro Serra; Mario Venditti Journal: Intern Emerg Med Date: 2012-06-12 Impact factor: 3.397
Authors: Hugo A J M de Wit; Bjorn Winkens; Carlota Mestres Gonzalvo; Kim P G M Hurkens; Wubbo J Mulder; Rob Janknegt; Frans R Verhey; Paul-Hugo M van der Kuy; Jos M G A Schols Journal: Int J Clin Pharm Date: 2016-05-13
Authors: Supriya G Mohile; William Dale; Mark R Somerfield; Mara A Schonberg; Cynthia M Boyd; Peggy S Burhenn; Beverly Canin; Harvey Jay Cohen; Holly M Holmes; Judith O Hopkins; Michelle C Janelsins; Alok A Khorana; Heidi D Klepin; Stuart M Lichtman; Karen M Mustian; William P Tew; Arti Hurria Journal: J Clin Oncol Date: 2018-05-21 Impact factor: 44.544
Authors: Jason L Sanders; Robert M Boudreau; Brenda W Penninx; Eleanor M Simonsick; Stephen B Kritchevsky; Suzanne Satterfield; Tamara B Harris; Douglas C Bauer; Anne B Newman Journal: J Gerontol A Biol Sci Med Sci Date: 2012-04-30 Impact factor: 6.053