Grace Shu Hui Chiang1, Ma Shwe Zin Nyunt2, Qi Gao3, Shiou Liang Wee4, Keng Bee Yap5, Boon Yeow Tan1,3, Tze Pin Ng6,7. 1. Department of Medicine, St Luke's Hospital, Singapore, Singapore. 2. Singapore Eye Research Institute, Singapore, Singapore. 3. Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. 4. Geriatric Education and Research Institute, Singapore, Singapore. 5. Department of Geriatric Medicine, Ng Teng Fong Hospital, Singapore, Singapore. 6. Geriatric Education and Research Institute, Singapore, Singapore. pcmngtp@nus.edu.sg. 7. Gerontology Research Programme, Department of Psychological Medicine, National University of Singapore, Singapore, Singapore. pcmngtp@nus.edu.sg.
Abstract
BACKGROUND: Healthcare providers use a life expectancy of at least 5 to 10 years in shared clinical decision-making with older adults about cancer screening, major surgeries, and disease prevention interventions. At present, few prognostic indexes predict long-term mortality beyond 10 years or are suited for use in primary care settings. OBJECTIVE: We developed and validated an 8-item multidimensional index predicting 11-year mortality for use in primary care. DESIGN, SETTING, AND PARTICIPANTS: Using data from the Singapore Longitudinal Ageing Studies (SLAS), we developed a Primary Care Prognostic (PCP) Index for predicting 11-year mortality risk in a development cohort (n = 1550) and validated it in a geographically different cohort (n = 928). MAIN MEASURES: The PCP Index was derived from eight indicators (body mass loss, weakness, slow gait, comorbidity, polypharmacy, IADL/BADL dependency, low albumin, low total cholesterol, out of 25 candidate indicators) using stepwise Cox proportional hazard models. KEY RESULTS: In the developmental cohort, the mortality hazard ratio increased by 53% per PCP point score increase, independent of age and sex. Across risk categories, absolute risks of mortality increased from 5% (score 0) to 67.9% (scores 7-9), with area under curve (AUC = 0.77 (95% CI 0.73-0.80)). The PCP Index also predicted mortality in the validation cohort, with AUC = 0.70 (95% CI 0.64-0.75). CONCLUSIONS: The PCP Index using simple clinical assessments and point scoring is a potentially useful prognostic tool for predicting long-term mortality and is well suited for risk stratification and shared clinical decision-making with older adults in primary care.
BACKGROUND: Healthcare providers use a life expectancy of at least 5 to 10 years in shared clinical decision-making with older adults about cancer screening, major surgeries, and disease prevention interventions. At present, few prognostic indexes predict long-term mortality beyond 10 years or are suited for use in primary care settings. OBJECTIVE: We developed and validated an 8-item multidimensional index predicting 11-year mortality for use in primary care. DESIGN, SETTING, AND PARTICIPANTS: Using data from the Singapore Longitudinal Ageing Studies (SLAS), we developed a Primary Care Prognostic (PCP) Index for predicting 11-year mortality risk in a development cohort (n = 1550) and validated it in a geographically different cohort (n = 928). MAIN MEASURES: The PCP Index was derived from eight indicators (body mass loss, weakness, slow gait, comorbidity, polypharmacy, IADL/BADL dependency, low albumin, low total cholesterol, out of 25 candidate indicators) using stepwise Cox proportional hazard models. KEY RESULTS: In the developmental cohort, the mortality hazard ratio increased by 53% per PCP point score increase, independent of age and sex. Across risk categories, absolute risks of mortality increased from 5% (score 0) to 67.9% (scores 7-9), with area under curve (AUC = 0.77 (95% CI 0.73-0.80)). The PCP Index also predicted mortality in the validation cohort, with AUC = 0.70 (95% CI 0.64-0.75). CONCLUSIONS: The PCP Index using simple clinical assessments and point scoring is a potentially useful prognostic tool for predicting long-term mortality and is well suited for risk stratification and shared clinical decision-making with older adults in primary care.
Authors: Linda P Fried; Luigi Ferrucci; Jonathan Darer; Jeff D Williamson; Gerard Anderson Journal: J Gerontol A Biol Sci Med Sci Date: 2004-03 Impact factor: 6.053
Authors: L C Walter; R J Brand; S R Counsell; R M Palmer; C S Landefeld; R H Fortinsky; K E Covinsky Journal: JAMA Date: 2001-06-20 Impact factor: 56.272
Authors: Hanne Nybo; Hans Chr Petersen; David Gaist; Bernard Jeune; Kjeld Andersen; Matt McGue; James W Vaupel; Kaare Christensen Journal: J Am Geriatr Soc Date: 2003-10 Impact factor: 5.562