Cost of illness of Alzheimer's disease: how useful are current estimates?

PURPOSE: The goal of this literature review was to determine the validity and policy relevance of recent estimates from many countries of Alzheimer's disease (AD) costs. DESIGN AND METHODS: We searched Medline and other databases for English-language peer-reviewed journals on total, direct, indirect, and per case cost of AD that used 1985-2000 data. We adjusted costs of U.S. studies for inflation. We adjusted non-U.S. studies by that country's medical cost inflation rate and purchasing power parity (PPP). RESULTS: Of 71 studies identified, 21 met all criteria for inclusion. Annual inflation adjusted U.S. total costs of AD varied from $5.6 billion to $88.3 billion. AD total per case (direct and indirect) costs varied from $1,500 to $91,000; indirect/family costs varied from $3,700 to $21,000. Among non-U.S. studies, AD annual adjusted per case costs varied from PPP $2,300 to PPP $30,000. Cost variation was due to diverse study methods, data sources, services included, and lack of clear differentiation between cost of AD and cost of caring for people with AD. IMPLICATIONS: The cost of AD is high, although reliable estimates are not available. Costs are likely to rise given expected demographic shifts in all countries. The widely variable cost estimates call into question the real costs of Alzheimer's disease and their applicability to policy initiatives.

Classic or Bayesian research design and analysis. Does it make a difference?

OBJECTIVE: The role of classical and Bayesian statistical approaches remains in dispute in health services research and policy. The goal of this study was to determine if results differ when both analytic techniques are used with the same data set. DESIGN: We searched MEDLINE and related databases for English-language articles published January 1, 1978 through August 31, 1999. We combined Bayesian and classical statistics search terms and their variants with randomized control trials (RCTs) and meta-analyses. RESULTS: Searches found 18 studies in 14 publications that met all review criteria--nine RCTs, eight meta-analyses, and one epidemiologic estimate. Statistical analyses using both methods agreed in five RCTs, four meta-analyses, and for the epidemiologic estimates. For four RCTs where results disagreed, classical analysis found the experimental intervention was efficacious compared with the control, and Bayesian reanalysis concluded the intervention was not proven efficacious. Classical meta-analyses of the four studies where results disagreed concluded the experimental intervention was not better than the control; Bayesian reanalysis concluded it was efficacious. CONCLUSION: Classical and Bayesian methods in this review exhibited important divergence of results. Disagreement on many fundamental beliefs between classical and Bayesian statistics means continuing debate. One way to resolve this debate is for proponents of each technique to decide together the circumstances for use of each method and analytic framework. If the experts do not agree on the methodologic requirements, other decision makers likely will force their own views.