Predicting time to nursing home care and death in individuals with Alzheimer disease

Yaakov Stern, Min Xing Tang, Marilyn Albert, Jason Brandt, Diane M. Jacobs, Karen Bell, Karen Marder, Mary Sano, Devangere Devanand, Steven M. Albert, Frederick Bylsma, Wei Yann Tsai

Research output: Contribution to journalArticle

Abstract

Objective.-To develop and validate an approach that uses clinical features that can be determined in a standard patient visit to estimate the length of time before an individual patient with Alzheimer disease (AD) requires care equivalent to nursing home placement or dies. Design.- Prospective cohort study of 236 patients, followed up semiannually for up to 7 years. A second validation cohort of 105 patients was also followed. Setting.-Three AD research centers. Patients.-All patients met National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) criteria for probable AD and had mild dementia at the initial visit. Intervention.- Predictive features, ascertained at the initial visit, were sex, duration of illness, age at onset, modified Mini-Mental State Examination (mMMS) score, and the presence or absence of extrapyramidal signs or psychotic features. Main Outcome Measures.-(1) Requiring the equivalent of nursing home placement and (2) death. Results.-Prediction algorithms were constructed for the 2 outcomes based on Cox proportional hazard models. For each algorithm, a predictor index is calculated based on the status of each predictive feature at the initial visit. A table that specifies the number of months in which 25%, 50%, and 75% of patients with any specific predictor index value are likely to reach the end point is then consulted. Survival curves for time to need for care equivalent to nursing home placement and for time to death derived from the algorithms for selected predictor indexes fell within the 95% confidence bands of actual survival curves for patients. When the predictor variables from the initial visit for the validation cohort patients were entered into the algorithm, the predicted survival curves for time to death fell within the 95% confidence bands of actual survival curves for the patients. Conclusions.-The prediction algorithms are a first but promising step toward providing specific prognoses to patients, families, and practitioners. This approach also has clear implications for the design and interpretation of clinical trials in patients with AD.

Original languageEnglish (US)
Pages (from-to)806-812
Number of pages7
JournalJournal of the American Medical Association
Volume277
Issue number10
StatePublished - Mar 12 1997

Fingerprint

Home Care Services
Nursing Care
Nursing Homes
Alzheimer Disease
Survival
National Institute of Neurological Disorders and Stroke
Communication Disorders
Age of Onset
Proportional Hazards Models
Dementia
Cohort Studies
Outcome Assessment (Health Care)
Clinical Trials
Prospective Studies

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Predicting time to nursing home care and death in individuals with Alzheimer disease. / Stern, Yaakov; Tang, Min Xing; Albert, Marilyn; Brandt, Jason; Jacobs, Diane M.; Bell, Karen; Marder, Karen; Sano, Mary; Devanand, Devangere; Albert, Steven M.; Bylsma, Frederick; Tsai, Wei Yann.

In: Journal of the American Medical Association, Vol. 277, No. 10, 12.03.1997, p. 806-812.

Research output: Contribution to journalArticle

Stern, Y, Tang, MX, Albert, M, Brandt, J, Jacobs, DM, Bell, K, Marder, K, Sano, M, Devanand, D, Albert, SM, Bylsma, F & Tsai, WY 1997, 'Predicting time to nursing home care and death in individuals with Alzheimer disease', Journal of the American Medical Association, vol. 277, no. 10, pp. 806-812.
Stern, Yaakov ; Tang, Min Xing ; Albert, Marilyn ; Brandt, Jason ; Jacobs, Diane M. ; Bell, Karen ; Marder, Karen ; Sano, Mary ; Devanand, Devangere ; Albert, Steven M. ; Bylsma, Frederick ; Tsai, Wei Yann. / Predicting time to nursing home care and death in individuals with Alzheimer disease. In: Journal of the American Medical Association. 1997 ; Vol. 277, No. 10. pp. 806-812.
@article{ae1563d360d3452baa99fc1b96fb3e26,
title = "Predicting time to nursing home care and death in individuals with Alzheimer disease",
abstract = "Objective.-To develop and validate an approach that uses clinical features that can be determined in a standard patient visit to estimate the length of time before an individual patient with Alzheimer disease (AD) requires care equivalent to nursing home placement or dies. Design.- Prospective cohort study of 236 patients, followed up semiannually for up to 7 years. A second validation cohort of 105 patients was also followed. Setting.-Three AD research centers. Patients.-All patients met National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) criteria for probable AD and had mild dementia at the initial visit. Intervention.- Predictive features, ascertained at the initial visit, were sex, duration of illness, age at onset, modified Mini-Mental State Examination (mMMS) score, and the presence or absence of extrapyramidal signs or psychotic features. Main Outcome Measures.-(1) Requiring the equivalent of nursing home placement and (2) death. Results.-Prediction algorithms were constructed for the 2 outcomes based on Cox proportional hazard models. For each algorithm, a predictor index is calculated based on the status of each predictive feature at the initial visit. A table that specifies the number of months in which 25{\%}, 50{\%}, and 75{\%} of patients with any specific predictor index value are likely to reach the end point is then consulted. Survival curves for time to need for care equivalent to nursing home placement and for time to death derived from the algorithms for selected predictor indexes fell within the 95{\%} confidence bands of actual survival curves for patients. When the predictor variables from the initial visit for the validation cohort patients were entered into the algorithm, the predicted survival curves for time to death fell within the 95{\%} confidence bands of actual survival curves for the patients. Conclusions.-The prediction algorithms are a first but promising step toward providing specific prognoses to patients, families, and practitioners. This approach also has clear implications for the design and interpretation of clinical trials in patients with AD.",
author = "Yaakov Stern and Tang, {Min Xing} and Marilyn Albert and Jason Brandt and Jacobs, {Diane M.} and Karen Bell and Karen Marder and Mary Sano and Devangere Devanand and Albert, {Steven M.} and Frederick Bylsma and Tsai, {Wei Yann}",
year = "1997",
month = "3",
day = "12",
language = "English (US)",
volume = "277",
pages = "806--812",
journal = "JAMA - Journal of the American Medical Association",
issn = "0098-7484",
publisher = "American Medical Association",
number = "10",

}

TY - JOUR

T1 - Predicting time to nursing home care and death in individuals with Alzheimer disease

AU - Stern, Yaakov

AU - Tang, Min Xing

AU - Albert, Marilyn

AU - Brandt, Jason

AU - Jacobs, Diane M.

AU - Bell, Karen

AU - Marder, Karen

AU - Sano, Mary

AU - Devanand, Devangere

AU - Albert, Steven M.

AU - Bylsma, Frederick

AU - Tsai, Wei Yann

PY - 1997/3/12

Y1 - 1997/3/12

N2 - Objective.-To develop and validate an approach that uses clinical features that can be determined in a standard patient visit to estimate the length of time before an individual patient with Alzheimer disease (AD) requires care equivalent to nursing home placement or dies. Design.- Prospective cohort study of 236 patients, followed up semiannually for up to 7 years. A second validation cohort of 105 patients was also followed. Setting.-Three AD research centers. Patients.-All patients met National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) criteria for probable AD and had mild dementia at the initial visit. Intervention.- Predictive features, ascertained at the initial visit, were sex, duration of illness, age at onset, modified Mini-Mental State Examination (mMMS) score, and the presence or absence of extrapyramidal signs or psychotic features. Main Outcome Measures.-(1) Requiring the equivalent of nursing home placement and (2) death. Results.-Prediction algorithms were constructed for the 2 outcomes based on Cox proportional hazard models. For each algorithm, a predictor index is calculated based on the status of each predictive feature at the initial visit. A table that specifies the number of months in which 25%, 50%, and 75% of patients with any specific predictor index value are likely to reach the end point is then consulted. Survival curves for time to need for care equivalent to nursing home placement and for time to death derived from the algorithms for selected predictor indexes fell within the 95% confidence bands of actual survival curves for patients. When the predictor variables from the initial visit for the validation cohort patients were entered into the algorithm, the predicted survival curves for time to death fell within the 95% confidence bands of actual survival curves for the patients. Conclusions.-The prediction algorithms are a first but promising step toward providing specific prognoses to patients, families, and practitioners. This approach also has clear implications for the design and interpretation of clinical trials in patients with AD.

AB - Objective.-To develop and validate an approach that uses clinical features that can be determined in a standard patient visit to estimate the length of time before an individual patient with Alzheimer disease (AD) requires care equivalent to nursing home placement or dies. Design.- Prospective cohort study of 236 patients, followed up semiannually for up to 7 years. A second validation cohort of 105 patients was also followed. Setting.-Three AD research centers. Patients.-All patients met National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) criteria for probable AD and had mild dementia at the initial visit. Intervention.- Predictive features, ascertained at the initial visit, were sex, duration of illness, age at onset, modified Mini-Mental State Examination (mMMS) score, and the presence or absence of extrapyramidal signs or psychotic features. Main Outcome Measures.-(1) Requiring the equivalent of nursing home placement and (2) death. Results.-Prediction algorithms were constructed for the 2 outcomes based on Cox proportional hazard models. For each algorithm, a predictor index is calculated based on the status of each predictive feature at the initial visit. A table that specifies the number of months in which 25%, 50%, and 75% of patients with any specific predictor index value are likely to reach the end point is then consulted. Survival curves for time to need for care equivalent to nursing home placement and for time to death derived from the algorithms for selected predictor indexes fell within the 95% confidence bands of actual survival curves for patients. When the predictor variables from the initial visit for the validation cohort patients were entered into the algorithm, the predicted survival curves for time to death fell within the 95% confidence bands of actual survival curves for the patients. Conclusions.-The prediction algorithms are a first but promising step toward providing specific prognoses to patients, families, and practitioners. This approach also has clear implications for the design and interpretation of clinical trials in patients with AD.

UR - http://www.scopus.com/inward/record.url?scp=8044242205&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=8044242205&partnerID=8YFLogxK

M3 - Article

VL - 277

SP - 806

EP - 812

JO - JAMA - Journal of the American Medical Association

JF - JAMA - Journal of the American Medical Association

SN - 0098-7484

IS - 10

ER -