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Mortality Predictive Indexes for the Community-Dwelling Elderly US Population

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ABSTRACT

Background

Few predictive indexes for long-term mortality have been developed for community-dwelling elderly populations. Parsimonious predictive indexes are important decision-making tools for clinicians, policy makers, and epidemiologists.

Objective

To develop 1-, 5-, and 10-year mortality predictive indexes for nationally representative community-dwelling elderly people.

Design

Cohort study.

Setting

The Second Longitudinal Study of Aging (LSOA II).

Participants

Nationally representative civilian community-dwelling persons at least 70 years old. We randomly selected 60% of the sample for prediction development and used the remaining 40% for validation.

Main Measures

Sociodemographics, impairments, and medical diagnoses were collected from the LSOA II baseline interviews. Instrumental activities of daily living (IADLs) stages were derived to measure functional status. All-cause mortality was obtained from the LSOA II Linked Mortality Public-use File.

Results

The analyses included 7,373 sample persons with complete data, among which mortality rates were 3.7%, 23.3%, and 49.8% for 1, 5, and 10 years, respectively. Four, eight, and ten predictors were identified for 1-, 5-, and 10-year mortality, respectively, in multiple logistic regression models to create three predictive indexes. Age, sex, coronary artery disease, and IADL stages were the most essential predictors for all three indexes. C-statistics of the three indexes were 0.72, 0.74, and 0.75 in the development cohort and 0.72, 0.72, and 0.74 in the validation cohort for 1-, 5-, and 10-year mortality, respectively. Five risk groups were defined based on the scores.

Conclusions

The 1-, 5-, and 10-year mortality indexes include parsimonious predictor sets maximizing ease of mortality prediction in community settings. Thus, they may provide valuable information for prognosis of elderly patients and guide the comparison of alternative interventions. Including IADL stage as a predictor yields simplified mortality prediction when detailed disease information is not available.

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References

  1. Wasson JH, Sox HC, Neff RK, Goldman L. Clinical prediction rules. Applications and methodological standards. N Engl J Med. 1985;313(13):793–799.

    Article  PubMed  CAS  Google Scholar 

  2. Laupacis A, Sekar N, Stiell IG. Clinical prediction rules. A review and suggested modifications of methodological standards. JAMA. 1997;277(6):488–494. Feb 12.

    Article  PubMed  CAS  Google Scholar 

  3. McGinn TG, Guyatt GH, Wyer PC, Naylor CD, Stiell IG, Richardson WS. Users' guides to the medical literature: XXII: how to use articles about clinical decision rules. Evidence-Based Medicine Working Group. JAMA. 2000;284(1):79–84.

    Article  PubMed  CAS  Google Scholar 

  4. Ford MK, Beattie WS, Wijeysundera DN. Systematic review: prediction of perioperative cardiac complications and mortality by the revised cardiac risk index. Ann Intern Med. 2010;152(1):26–35.

    PubMed  Google Scholar 

  5. Mitchell SL, Miller SC, Teno JM, Kiely DK, Davis RB, Shaffer ML. Prediction of 6-month survival of nursing home residents with advanced dementia using ADEPT vs hospice eligibility guidelines. JAMA. 2010;304(17):1929–1935.

    Article  PubMed  CAS  Google Scholar 

  6. Levine SK, Sachs GA, Jin L, Meltzer D. A prognostic model for 1-year mortality in older adults after hospital discharge. Am J Med. 2007;120(5):455–460.

    Article  PubMed  Google Scholar 

  7. Lee SJ, Lindquist K, Segal MR, Covinsky KE. Development and validation of a prognostic index for 4-year mortality in older adults. JAMA. 2006;295(7):801–808.

    Article  PubMed  CAS  Google Scholar 

  8. Carey EC, Covinsky KE, Lui LY, Eng C, Sands LP, Walter LC. Prediction of mortality in community-living frail elderly people with long-term care needs. J Am Geriatr Soc. 2008;56(1):68–75.

    Article  PubMed  Google Scholar 

  9. Schonberg MA, Davis RB, McCarthy EP, Marcantonio ER. Index to predict 5-year mortality of community-dwelling adults aged 65 and older using data from the National Health Interview Survey. J Gen Intern Med. 2009;24(10):1115–1122.

    Article  PubMed  Google Scholar 

  10. Carey EC, Walter LC, Lindquist K, Covinsky KE. Development and validation of a functional morbidity index to predict mortality in community-dwelling elders. J Gen Intern Med. 2004;19(10):1027–1033.

    Article  PubMed  Google Scholar 

  11. Yourman LC, Lee SJ, Schonberg MA, Widera EW, Smith AK. Prognostic indices for older adults: a systematic review. JAMA. 2012;307(2):182–192.

    Article  PubMed  CAS  Google Scholar 

  12. National Center for Health Statistics. The Second Longitudinal Study on Aging, 1994-2000. 2002; http://www.cdc.gov/nchs/lsoa/lsoa2.htm. Accessed 2/9/12.

  13. National Center for Health Statistics. Data File Documentation, National Health Interview Survey on Disability, Phase I, Adult File 1994 Hayattsville, MD: National Center for Health Statistics; 1996

  14. National Center for Health Statistics: Data file Documentation. National Health Interview Survey on Disability, Phase II, Adult File 1995. Hayattsville, MD: Center for Disease Control and Prevention; 1998.

  15. Center for Disease Control and Prevention. Survey Instruments. 2009; http://www.cdc.gov/nchs/data/nhis/dfs_100_1994.pdf Accessed 2/9/12.

  16. National Center for Health Statistics. Office of Analysis and Epidemiology. Public-use Second Longitudinal Study of Aging (LSOA II) Linked Mortality File. 2010; http://www.cdc.gov/nchs/data_access/data_linkage/mortality/lsoaii_linkage_public_use.htm Accessed 2/9/12.

  17. Stineman MG, Henry-Sánchez JT, Kurichi JE, et al. Staging activity limitation and participation restriction in elderly community-dwelling persons according to difficulties in self-care and domestic life functioning. Am J Phys Med Rehabil. 2012;91:126–140.

    Article  PubMed  Google Scholar 

  18. Lawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist Autumn. 1969;9(3):179–186.

    Article  CAS  Google Scholar 

  19. Kempen GI, Myers AM, Powell LE. Hierarchical structure in ADL and IADL: analytical assumptions and applications for clinicians and researchers. J Clin Epidemiol. 1995;48(11):1299–1305.

    Article  PubMed  CAS  Google Scholar 

  20. Siu AL, Reuben DB, Hays RD. Hierarchical measures of physical function in ambulatory geriatrics. J Am Geriatr Soc. 1990;38(10):1113–1119.

    PubMed  CAS  Google Scholar 

  21. Ustun TB, Chatterji S, Bickenbach J, Kostanjsek N, Schneider M. The International Classification of Functioning, Disability and Health: a new tool for understanding disability and health. Disabil Rehabil. 2003;25(11-12):565–571. Jun 3-17.

    Article  PubMed  CAS  Google Scholar 

  22. Stineman M, Ross R, Maislin G. Functional status measures for integrating medical and social care. International Journal of Integrated Care. 2005;5:e07.

    PubMed  Google Scholar 

  23. Saliba D, Orlando M, Wenger NS, Hays RD, Rubenstein LZ. Identifying a short functional disability screen for older persons. J Gerontol A Biol Sci Med Sci. 2000;55(12):M750–M756.

    Article  PubMed  CAS  Google Scholar 

  24. Steyerberg EW, Harrell FE Jr, Borsboom GJ, Eijkemans MJ, Vergouwe Y, Habbema JD. Internal validation of predictive models: efficiency of some procedures for logistic regression analysis. J Clin Epidemiol. 2001;54(8):774–781.

    Article  PubMed  CAS  Google Scholar 

  25. Concato J, Feinstein AR, Holford TR. The risk of determining risk with multivariable models. Ann Intern Med. 1993;118(3):201–210.

    PubMed  CAS  Google Scholar 

  26. Toll DB, Janssen KJ, Vergouwe Y, Moons KG. Validation, updating and impact of clinical prediction rules: a review. J Clin Epidemiol. 2008;61(11):1085–1094.

    Article  PubMed  CAS  Google Scholar 

  27. Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology. 1982;143(1):29–36.

    PubMed  CAS  Google Scholar 

  28. Raghunathan, Solenberger, Hoewyk. IVEware: Imputation and Variance Estimation Software Users Guide. University of Michigan: Ann Arbor: Institute for Social Research; 2002.

    Google Scholar 

  29. Klijs B, Mackenbach JP, Kunst AE. Disability occurrence and proximity to death. Disabil Rehabil. 2010;32(21):1733–1741.

    Article  PubMed  Google Scholar 

  30. Gill TM, Gahbauer EA, Han L, Allore HG. Trajectories of disability in the last year of life. N Engl J Med. 2010;362(13):1173–1180.

    Article  PubMed  CAS  Google Scholar 

  31. Volpato S, Cavalieri M, Sioulis F, et al. Predictive value of the Short Physical Performance Battery following hospitalization in older patients. J Gerontol A Biol Sci Med Sci. 2011;66(1):89–96.

    Article  PubMed  Google Scholar 

  32. Turvey CL, Schultz SK, Beglinger L, Klein DM. A longitudinal community-based study of chronic illness, cognitive and physical function, and depression. Am J Geriatr Psychiatry. 2009;17(8):632–641.

    Article  PubMed  Google Scholar 

  33. Landi F, Liperoti R, Russo A, et al. Disability, more than multimorbidity, was predictive of mortality among older persons aged 80years and older. J Clin Epidemiol. 2010;63(7):752–759.

    Article  PubMed  Google Scholar 

  34. Min L, Yoon W, Mariano J, et al. The vulnerable elders-13 survey predicts 5-year functional decline and mortality outcomes in older ambulatory care patients. J Am Geriatr Soc. 2009;57(11):2070–2076.

    Article  PubMed  Google Scholar 

  35. Keeler E, Guralnik JM, Tian H, Wallace RB, Reuben DB. The impact of functional status on life expectancy in older persons. J Gerontol A Biol Sci Med Sci. 2010;65(7):727–733.

    Article  PubMed  Google Scholar 

  36. Hardy SE, Kang Y, Studenski SA, Degenholtz HB. Ability to walk 1/4 mile predicts subsequent disability, mortality, and health care costs. J Gen Intern Med. 2011;26(2):130–135.

    Article  PubMed  Google Scholar 

  37. Ng TP, Niti M, Chiam PC, Kua EH. Physical and cognitive domains of the Instrumental Activities of Daily Living: validation in a multiethnic population of Asian older adults. J Gerontol A Biol Sci Med Sci. 2006;61(7):726–735.

    Article  PubMed  Google Scholar 

  38. Wang CY, Hu MH, Chen HY, Li RH. Self-Reported Mobility and Instrumental Activities of Daily Living Disability Status in Community-Dwelling Older Asian Adults: Test-Retest Reliability and Criterion Validity. J Aging Phys Act. Oct 19 2011.

  39. Barberger-Gateau P, Commenges D, Gagnon M, Letenneur L, Sauvel C, Dartigues JF. Instrumental activities of daily living as a screening tool for cognitive impairment and dementia in elderly community dwellers. J Am Geriatr Soc. 1992;40(11):1129–1134.

    PubMed  CAS  Google Scholar 

  40. Inouye SK, Peduzzi PN, Robison JT, Hughes JS, Horwitz RI, Concato J. Importance of functional measures in predicting mortality among older hospitalized patients. JAMA. 1998;279(15):1187–1193.

    Article  PubMed  CAS  Google Scholar 

  41. Mitchell SL, Kiely DK, Hamel MB, Park PS, Morris JN, Fries BE. Estimating prognosis for nursing home residents with advanced dementia. JAMA. 2004;291(22):2734–2740.

    Article  PubMed  CAS  Google Scholar 

  42. Heron M, Tejada-Vera B. Deaths: leading causes for 2005. Natl Vital Stat Rep. 2009;58(8):1–97.

    PubMed  Google Scholar 

  43. Zhou H, Isaman DJ, Messinger S, et al. A computer simulation model of diabetes progression, quality of life, and cost. Diabetes Care. 2005;28(12):2856–2863.

    Article  PubMed  Google Scholar 

  44. Emond M, Mock MB, Davis KB, et al. Long-term survival of medically treated patients in the Coronary Artery Surgery Study (CASS) Registry. Circulation. 1994;90(6):2645–2657.

    Article  PubMed  CAS  Google Scholar 

  45. National Cancer Institute. Cancer survival statistics. http://surveillance.cancer.gov/statistics/types/survival.html Accessed 2/9/12.

  46. Sloan FA, Ostermann J, Brown DS, Lee PP. Effects of changes in self-reported vision on cognitive, affective, and functional status and living arrangements among the elderly. Am J Ophthalmol. 2005;140(4):618–627.

    Article  PubMed  Google Scholar 

  47. Dalton DS, Cruickshanks KJ, Klein BE, Klein R, Wiley TL, Nondahl DM. The impact of hearing loss on quality of life in older adults. Gerontologist. 2003;43(5):661–668.

    Article  PubMed  Google Scholar 

  48. Shyu YI, Chen MC, Liang J, Wu CC, Su JY. Predictors of functional recovery for hip fractured elders during 12months following hospital discharge: a prospective study on a Taiwanese sample. Osteoporos Int. 2004;15(6):475–482.

    Article  PubMed  Google Scholar 

  49. Overcash J. Prediction of falls in older adults with cancer: a preliminary study. Oncol Nurs Forum. 2007;34(2):341–346.

    Article  PubMed  Google Scholar 

  50. Heistaro S, Jousilahti P, Lahelma E, Vartiainen E, Puska P. Self rated health and mortality: a long term prospective study in eastern Finland. J Epidemiol Community Health. 2001;55(4):227–232.

    Article  PubMed  CAS  Google Scholar 

  51. Gander J, Lee DC, Sui X, Hebert JR, Hooker SP, Blair SN. Self-rated health status and cardiorespiratory fitness as predictors of mortality in men. Br J Sports Med. 45:1095–1100.

  52. Katz S. Assessing self-maintenance: activities of daily living, mobility, and instrumental activities of daily living. J Am Geriatr Soc. 1983;31(12):721–727.

    PubMed  CAS  Google Scholar 

  53. Banerjee D, Perry M, Tran D, Arafat R. Self-reported health, functional status and chronic disease in community dwelling older adults: untangling the role of demographics. J Community Health. 2010;35(2):135–141.

    Article  PubMed  Google Scholar 

  54. Fan VS, Au D, Heagerty P, Deyo RA, McDonell MB, Fihn SD. Validation of case-mix measures derived from self-reports of diagnoses and health. J Clin Epidemiol. 2002;55(4):371–380.

    Article  PubMed  Google Scholar 

  55. Hornbrook MC, Goodman MJ. Chronic disease, functional health status, and demographics: a multi-dimensional approach to risk adjustment. Health Serv Res. 1996;31(3):283–307.

    PubMed  CAS  Google Scholar 

  56. Tatemichi TK, Desmond DW, Stern Y, Paik M, Sano M, Bagiella E. Cognitive impairment after stroke: frequency, patterns, and relationship to functional abilities. J Neurol Neurosurg Psychiatry. 1994;57(2):202–207.

    Article  PubMed  CAS  Google Scholar 

  57. Mok VC, Wong A, Lam WW, et al. Cognitive impairment and functional outcome after stroke associated with small vessel disease. J Neurol Neurosurg Psychiatry. 2004;75(4):560–566.

    Article  PubMed  CAS  Google Scholar 

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ACKNOWLEDGEMENTS

Funders:

The research for this manuscript was supported by the National Institutes of Health (AG032420-01A1). There are no personal conflicts of interest of any of the authors, and no authors reported disclosures beyond the funding source. The opinions and conclusions of the authors are not necessarily those of the sponsoring agency or of the NCHS who is responsible only for provision of the data.

Prior Presentations:

None.

Conflict of Interest:

There are no personal conflicts of interest of any of the authors, and no authors reported disclosures beyond the funding source. The opinions and conclusions of the authors are not necessarily those of the sponsoring agencies.

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Authors and Affiliations

  1. Department of Biostatistics and Epidemiology, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, 904 Blockley Hall, 423 Guardian Drive, Philadelphia, Pennsylvania, 19104, USA

    Zi Zhang MD, Dawei Xie PhD, Jibby E. Kurichi MPH & Margaret G. Stineman MD

  2. Geriatric Psychiatry Section, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania and VISN 4 Mental Illness Research Education and Clinical Center, Philadelphia Veterans Affairs Medical Center, Philadelphia, Pennsylvania, USA

    Joel Streim MD

  3. Department of Epidemiology and Biostatistics, University of Maryland, College Park, Maryland, USA

    Guangyu Zhang PhD

  4. Department of Physical Medicine and Rehabilitation, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    Margaret G. Stineman MD

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  1. Zi Zhang MD
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Correspondence to Margaret G. Stineman MD.

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Zhang, Z., Xie, D., Kurichi, J.E. et al. Mortality Predictive Indexes for the Community-Dwelling Elderly US Population. J GEN INTERN MED 27, 901–910 (2012). https://doi.org/10.1007/s11606-012-2027-3

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