Measuring Alzheimer's disease progression with transition probabilities - Estimates from CERAD

Objectives: To estimate annual transition probabilities (i.e., the likeliho od that a patient will move from one disease stage to another in a given ti me period) for AD progression. Transition probabilities are estimated by di sease stages (mild, moderate, severe) and settings of care (community, nurs ing home), accounting for differences in age, gender, and behavioral sympto ms as well as the length of time a patient has been in a disease stage. Met hods: Using data from the Consortium to Establish a Registry for Alzheimer' s Disease (CERAD), the authors employed a modified survival analysis to est imate stage-to-stage and stage-to-nursing home transition probabilities. To account for individual variability, a Cox proportional hazards model was f it to the CERAD data to estimate hazard ratios for gender, age (50 to 64, 6 5 to 74, and more than 75 years), and level of behavioral symptoms (low/hig h, according to responses to the Behavioral Rating Scale for Dementia) for each of the key stage-to-stage and stage-to-nursing home transitions. Resul ts: The transition probabilities underscore the rapid progression of patien ts into more severe disease stages and into nursing homes and the differenc es among population subgroups. In general, male gender, age under 65, and h igh level of behavioral symptoms were associated with higher transition pro babilities to more severe disease stages. Disease progression is roughly co nstant as a function of the time a patient has spent in a particular stage. Conclusions: Transition probabilities provide a useful means of characteri zing AD progression. Economic models of interventions for AD should conside r the varied course of progression for different population subgroups, part icularly those defined by high levels of behavioral symptoms.