OBJECTIVE: To develop a framework for estimating the long-term health and economic consequences of AD based on patient characteristics at a given point in time. METHODS: A pharmacoeconomic model (Assessment of Health Economics in Alzheimer's Disease, AHEAD) was developed based on equations that relate the probability of needing full-time care (FTC) over time to patient characteristics summarized in index scores. These equations were developed from published data on interquartile times until FTC is needed and until death, using nonlinear regressions of the resulting index-specific hazards. These equations were then incorporated into a hidden Markov framework that allows for calculation of expected time to FTC and to death, as well as of the economic consequences of disease progression. There are three major states in the model: not requiring FTC ("pre-FTC"), requiring FTC, and death. RESULTS: Outcomes for five sample patients are derived to illustrate application of the AHEAD model. The impact of altering disease markers in these patients is also considered. CONCLUSION: The need for a generally applicable tool to forecast long-term outcomes based on relatively short-term data is becoming increasingly acute with the advent of new therapies for AD. The AHEAD model provides a relatively simple framework for the prediction of time to FTC requirement based on short-term observed data such as those from clinical trials. Although subject to the uncertainties inherent in modeling, the model nevertheless provides a standard estimation technique that may facilitate comparisons between existing and emerging therapies.
OBJECTIVE: To develop a framework for estimating the long-term health and economic consequences of AD based on patient characteristics at a given point in time. METHODS: A pharmacoeconomic model (Assessment of Health Economics in Alzheimer's Disease, AHEAD) was developed based on equations that relate the probability of needing full-time care (FTC) over time to patient characteristics summarized in index scores. These equations were developed from published data on interquartile times until FTC is needed and until death, using nonlinear regressions of the resulting index-specific hazards. These equations were then incorporated into a hidden Markov framework that allows for calculation of expected time to FTC and to death, as well as of the economic consequences of disease progression. There are three major states in the model: not requiring FTC ("pre-FTC"), requiring FTC, and death. RESULTS: Outcomes for five sample patients are derived to illustrate application of the AHEAD model. The impact of altering disease markers in these patients is also considered. CONCLUSION: The need for a generally applicable tool to forecast long-term outcomes based on relatively short-term data is becoming increasingly acute with the advent of new therapies for AD. The AHEAD model provides a relatively simple framework for the prediction of time to FTC requirement based on short-term observed data such as those from clinical trials. Although subject to the uncertainties inherent in modeling, the model nevertheless provides a standard estimation technique that may facilitate comparisons between existing and emerging therapies.
Authors: Eric Stallard; Bruce Kinosian; Arthur S Zbrozek; Anatoliy I Yashin; Henry A Glick; Yaakov Stern Journal: Med Decis Making Date: 2010 Nov-Dec Impact factor: 2.583