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Full-Text Articles in Physical Sciences and Mathematics
Projections Of Alzheimer's Disease In The United States And The Public Health Impact Of Delaying Disease Onset., Ron Brookmeyer, Sarah Gray, Claudia Kawas
Projections Of Alzheimer's Disease In The United States And The Public Health Impact Of Delaying Disease Onset., Ron Brookmeyer, Sarah Gray, Claudia Kawas
Ron Brookmeyer
OBJECTIVES: The goal of this study was to project the future prevalence and incidence of Alzheimer's disease in the United States and the potential impact of interventions to delay disease onset.
METHODS: The numbers of individuals in the United States with Alzheimer's disease and the numbers of newly diagnosed cases that can be expected over the next 50 years were estimated from a model that used age-specific incidence rates summarized from several epidemiological studies, US mortality rates, and US Bureau of the Census projections.
RESULTS: in 1997, the prevalence of Alzheimer's disease in the United States was 2.32 million (range: …
Predicting Future Years Of Healthy Life For Older Adults, Paula Diehr
Predicting Future Years Of Healthy Life For Older Adults, Paula Diehr
Paula Diehr
Cost-effectiveness studies often need to compare the cost of a program to the lifetime benefits of the program, but estimates of lifetime benefits are not routinely available, especially for older adults. We used data from two large longitudinal studies of older adults (ages 65-100) to estimate transition probabilities from one health state to another, and used those probabilities to estimate the mean additional years of healthy life that an older adult of specified age, sex, and health status would experience. We found, for example, that 65-year-old women in excellent health can expect 16.8 years of healthy life in the future, …
Intracellular Coexpression Of Epidermal Growth Factor Receptor, Her-2/Neu, And P21ras In Human Breast Cancers: Evidence For The Existence Of Distinctive Patterns Of Genetic Evolution That Are Common To Tumors From Different Patients, Stanley E. Shackney, Agnese A. Pollice, Charles A. Smith, Laura E. Janocko, Lillian Sweeney, Kathryn A. Brown, Sarita G. Singh, Lingping Gu, Robert Yakulis, Joseph F. Lucke
Intracellular Coexpression Of Epidermal Growth Factor Receptor, Her-2/Neu, And P21ras In Human Breast Cancers: Evidence For The Existence Of Distinctive Patterns Of Genetic Evolution That Are Common To Tumors From Different Patients, Stanley E. Shackney, Agnese A. Pollice, Charles A. Smith, Laura E. Janocko, Lillian Sweeney, Kathryn A. Brown, Sarita G. Singh, Lingping Gu, Robert Yakulis, Joseph F. Lucke
Joseph Lucke
Multiparameter flow cytometry studies were performed on cells from the primary tumors of 94 patients with breast cancer. Correlated cellular measurements of cell DNA content, Her-2/neu, epidermal growth factor receptor (EGFR), and p21ras levels were performed on each of 5,000 to 100,000 cells from each tumor. When criteria for positivity were matched with those in common use for immunohistochemical studies, 28 of 94 (30\%) breast cancers were classified as positive for Her-2/neu overexpression. When similar criteria were applied to the EGFR measurements, 23 of 94 (24\%) cases were classified as positive for EGFR overexpression. Similarly, 23 of 94 (24\%) cases …
Additive Nonparametric Regression With Autocorrelated Errors, Michael S. Smith, C Wong, Robert Kohn
Additive Nonparametric Regression With Autocorrelated Errors, Michael S. Smith, C Wong, Robert Kohn
Michael Stanley Smith
A Bayesian approach is presented for nonparametric estimation of an additive regression model with autocorrelated errors. Each of the potentially nonlinear components is modelled as a regression spline using many knots, while the errors are modelled by a high order stationary autoregressive process parameterised in terms of its autocorrelations. The distribution of significant knots and partial autocorrelations is accounted for using subset selection. Our approach also allows the selection of a suitable transformation of the dependent variable. All aspects of the model are estimated simultaneously using Markov chain Monte Carlo. It is shown empirically that the proposed approach works well …