Predicting survival in patients with early Alzheimer's disease
J.J. Claus
Bok Engelsk 1998
| Utgitt | 1998
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| Omfang | Side 284- 293
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| Opplysninger | We investigated whether an index based on clinical features,electroencephalogram and computed tomography is useful to predictsurvival in early Alzheimer's disease. One hundred and sixty-threeconsecutively referred patients to an outpatient memory clinic andfirst diagnosed with Alzheimer's disease (105 'probable' and 58'possible', NINCDS-ADRDA criteria) were studied and outcome measurewas death. Cox proportional hazards regression analysis and Kaplan-Meier survival curves were used to investigate relations betweenbaseline parameters and survival. Eighty-four patients (51.5 %) diedduring the follow-up period that extended to 5.8 years, with a medianduration of survival after entry of 4.3 years. Baseline factors thatwere statistically significant and independently related to increasedrisk of mortality were high age, male sex, poor cognitive Function asmeasured with the CAMCOG; low alpha and beta power onelectroencephalogram, and temporoparietal atrophy on computedtomography scan. These results were independent of the diagnosisprobable or possible Alzheimer's disease. Based on the coefficientsfrom the regression equation, we computed a survival index for eachpatient and we constructed three groups according to tertiles of thisindex. After 5.2 years of follow-up, survival curves showed a lowmortality group with 81.7% patients alive (median survival at least5.7 years), an intermediate mortality group with 35.9% patients alive(median survival 3.8 years), and a high mortality group with nopatients alive (median survival 2.3 years). Log rank tests werestatistically significant for comparisons between all three groups.We conclude that an overall index combining demographic, cognitive,electroencephalogram and computed tomography features is a strongpredictor of survival in early Alzheimer's disease.
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