التفاصيل البيبلوغرافية
| العنوان: |
Indicators of "healthy aging" in older women (65-69 years of age). A data-mining approach based on prediction of long-term survival. |
| المؤلفون: |
Swindell WR, Ensrud KE, Cawthon PM, Cauley JA, Cummings SR, Miller RA, Study Of Osteoporotic Fractures Research Group, Swindell, William R, Ensrud, Kristine E, Cawthon, Peggy M, Cauley, Jane A, Cummings, Steve R, Miller, Richard A |
| المصدر: |
BMC Geriatrics; 2010, Vol. 10, p55-55, 1p |
| مستخلص: |
Background: Prediction of long-term survival in healthy adults requires recognition of features that serve as early indicators of successful aging. The aims of this study were to identify predictors of long-term survival in older women and to develop a multivariable model based upon longitudinal data from the Study of Osteoporotic Fractures (SOF).Methods: We considered only the youngest subjects (n = 4,097) enrolled in the SOF cohort (65 to 69 years of age) and excluded older SOF subjects more likely to exhibit a "frail" phenotype. A total of 377 phenotypic measures were screened to determine which were of most value for prediction of long-term (19-year) survival. Prognostic capacity of individual predictors, and combinations of predictors, was evaluated using a cross-validation criterion with prediction accuracy assessed according to time-specific AUC statistics.Results: Visual contrast sensitivity score was among the top 5 individual predictors relative to all 377 variables evaluated (mean AUC = 0.570). A 13-variable model with strong predictive performance was generated using a forward search strategy (mean AUC = 0.673). Variables within this model included a measure of physical function, smoking and diabetes status, self-reported health, contrast sensitivity, and functional status indices reflecting cumulative number of daily living impairments (HR >or= 0.879 or RH Conclusions: The multivariate model we developed characterizes a "healthy aging" phenotype based upon an integration of measures that together reflect multiple dimensions of an aging adult (65-69 years of age). Age-sensitive components of this model may be of value as biomarkers in human studies that evaluate anti-aging interventions. Our methodology could be applied to data from other longitudinal cohorts to generalize these findings, identify additional predictors of long-term survival, and to further develop the "healthy aging" concept. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
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