PREDICTING TIME TO NURSING-HOME CARE AND DEATH IN INDIVIDUALS WITH ALZHEIMER-DISEASE

Objective.-To develop and validate an approach that uses clinical feat ures that can be determined in a standard patient visit to estimate th e 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 f or up to 7 years, A second validation cohort of 105 patients was also followed. Setting.-Three AD research centers. Patients.-All patients m et National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer's Disease and Related Disorders Association (NINCDS-A DRDA) criteria for probable AD and had mild dementia at the initial vi sit. Intervention.-Predictive features, ascertained at the initial vis it, were sex, duration of illness, age at onset, modified Mini-Mental State Examination (mMMS) score, and the presence or absence of extrapy ramidal signs or psychotic features. Main Outcome Measures.-(1) Requir ing the equivalent of nursing home placement and (2) death. Results.-P rediction algorithms were constructed for the 2 outcomes based on Cox proportional hazard models, For each algorithm, a predictor index is c alculated based on the status of each predictive feature at the initia l visit, A table that specifies the number of months in which 25%, 50% , and 75% of patients with any specific predictor index value are like ly 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 validati on cohort patients were entered into the algorithm, the predicted surv ival curves for time to death fell within the 95% confidence bands of actual survival curves for the patients. Conclusions.-The prediction a lgorithms are a first but promising step toward providing specific pro gnoses to patients, families, and practitioners, This approach also ha s clear implications for the design and interpretation of clinical tri als in patients with AD.