Dataset Information

Indicators of "healthy aging" in older women (65-69 years of age). A data-mining approach based on prediction of long-term survival.

ABSTRACT:

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 ConclusionsThe 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.

SUBMITTER: Swindell WR

PROVIDER: S-EPMC2936300 | biostudies-literature | 2010 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Indicators of "healthy aging" in older women (65-69 years of age). A data-mining approach based on prediction of long-term survival.

Swindell William R WR Ensrud Kristine E KE Cawthon Peggy M PM Cauley Jane A JA Cummings Steve R SR Miller Richard A RA

BMC geriatrics 20100817

<h4>Background</h4>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).<h4>Methods</h4>We considered only the youngest subjects (n = 4,097) enrolled in the SOF cohort (65 to 69 years of age) and excluded older SOF s ...[more]

PMID: 20716351

Similar Datasets

Project description:ImportanceTo our knowledge, the role of overall diet quality in successful aging has not been conclusively demonstrated.ObjectiveTo prospectively examine the association between diet quality and longevity and successful aging in a population-based cohort of older adults.Design, setting, and participantsParticipants in "Mabat Zahav" (the Israeli National Health and Nutrition Survey of Older Adults), an older adult cohort (aged ≥65 years) consisting of a random sample of 1770 individuals, were recruited from July 2005 to December 2006 (time 1 [T1]). Survivors of T1 were again contacted and asked to participate in a second interview. From May 2017 to June 2019 (time 2 [T2]), an extensive face-to-face interview and a functional assessment were conducted in each participant's home in a subsample of 604 participants from T1, representing 72.7% of 820 surviving individuals who were able to complete interviews and assessments.ExposuresA 24-hour dietary recall, assessed at T1, was used to calculate scores from the 2015 version of the Healthy Eating Index (HEI-2015) (scores range from 0 [worst diet] to 100 [best diet]).Main outcomes and measuresTime to death, with follow-up lasting through June 2019, and successful aging. The latter, based on T2 assessment, was defined as (objectively measured) preserved physical and cognitive function and (subjective) mental well-being and favorable self-rated health. Inverse probability weighting was used in the analysis to minimize attrition bias.ResultsAt T1, the study included 1770 participants (mean [SD] age, 74.6 [6.2] years; 943 women [53%]). On average, participants with higher HEI-2015 scores had healthier lifestyles and higher socioeconomic status at T1. During a median follow-up duration of 12.6 years (IQR, 7.6-13.2 years), 893 deaths occurred. Among the 596 T2 participants analyzed (mean [SD] age, 84.1 [4.4] years; 334 [56%] women), 242 (40%) met successful aging criteria. After adjustment for sociodemographic and lifestyle risk factors, a higher HEI-2015 score was inversely associated with mortality (hazard ratios, 0.85; 95% CI, 0.72-0.99 in the upper tertile and 0.83; 95% CI, 0.71-0.98 in the middle tertile vs the lower tertile; P = .04 for trend) and was positively associated with successful aging (odds ratios, 1.73; 95% CI, 1.10-2.72 in the upper tertile and 1.30; 95% CI, 0.83-2.03 in the middle tertile vs the lower tertile; P = .03 for trend).Conclusions and relevanceIn this cohort study of older adults in Israel, improved diet quality was associated with increased longevity and successful aging in a dose-dependent manner. These data contribute to the body of literature that suggests diet quality is associated with aging in the older age group.

Project description:To conduct post-hoc analysis of National CT Colonography Trial data and compare the sensitivity and specificity of computed tomographic (CT) colonography in participants younger than 65 years with those in participants aged 65 years and older.Of 2600 asymptomatic participants recruited at 15 centers for the trial, 497 were 65 years of age or older. Approval of this HIPAA-compliant study was obtained from the institutional review board of each site, and informed consent was obtained from each subject. Radiologists certified in CT colonography reported lesions 5 mm in diameter or larger. Screening detection of large (≥10-mm) histologically confirmed colorectal neoplasia was the primary end point; screening detection of smaller (6-9-mm) colorectal neoplasia was a secondary end point. The differences in sensitivity and specificity of CT colonography in the two age cohorts (age < 65 years and age ≥ 65 years) were estimated with bootstrap confidence intervals (CIs).Complete data were available for 477 participants 65 years of age or older (among 2531 evaluable participants). Prevalence of adenomas 1 cm or larger for the older participants versus the younger participants was 6.9% (33 of 477) versus 3.7% (76 of 2054) (P < .004). For large neoplasms, mean estimates for CT colonography sensitivity and specificity among the older cohort were 0.82 (95% CI: 0.644, 0.944) and 0.83 (95% CI: 0.779, 0.883), respectively. For large neoplasms in the younger group, CT colonography sensitivity and specificity were 0.92 (95% CI: 0.837, 0.967) and 0.86 (95% CI: 0.816, 0.899), respectively. Per-polyp sensitivity for large neoplasms for the older and younger populations was 0.75 (95% CI: 0.578, 0.869) and 0.84 (95% CI: 0.717, 0.924), respectively. For the older and younger groups, per-participant sensitivity was 0.72 (95% CI: 0.565, 0.854) and 0.81 (95% CI: 0.745, 0.882) for detecting adenomas 6 mm in diameter or larger.For most measures of diagnostic performance and in most subsets, the difference between senior-aged participants and those younger than 65 years was not statistically significant.

Project description:BackgroundThere is little consensus, and minimal evidence, regarding the age at which to stop cervical screening. We studied the association between screening at age 50-64 y and cervical cancer at age 65-83 y.Methods and findingsCases were women (n = 1,341) diagnosed with cervical cancer at age 65-83 y between 1 April 2007 and 31 March 2012 in England and Wales; age-matched controls (n = 2,646) were randomly selected from population registers. Screening details from 1988 onwards were extracted from national databases. We calculated the odds ratios (OR) for different screening histories and subsequent cervical cancer. Women with adequate negative screening at age 65 y (288 cases, 1,395 controls) were at lowest risk of cervical cancer (20-y risk: 8 cancers per 10,000 women) compared with those (532 cases, 429 controls) not screened at age 50-64 y (20-y risk: 49 cancers per 10,000 women, with OR = 0.16, 95% CI 0.13-0.19). ORs depended on the age mix of women because of the weakening association with time since last screen: OR = 0.11, 95% CI 0.08-0.14 at 2.5 to 7.5 y since last screen; OR = 0.27, 95% CI 0.20-0.36 at 12.5 to 17.5 y since last screen. Screening at least every 5.5 y between the ages 50 and 64 y was associated with a 75% lower risk of cervical cancer between the ages 65 and 79 y (OR = 0.25, 95% CI 0.21-0.30), and the attributable risk was such that in the absence of screening, cervical cancer rates in women aged 65+ would have been 2.4 (95% CI 2.1-2.7) times higher. In women aged 80-83 y the association was weaker (OR = 0.49, 95% CI 0.28-0.83) than in those aged 65-69 y (OR = 0.12, 95% CI 0.09-0.17). This study was limited by an absence of data on confounding factors; additionally, findings based on cytology may not generalise to human papillomavirus testing.ConclusionsWomen with adequate negative screening at age 50-64 y had one-sixth of the risk of cervical cancer at age 65-83 y compared with women who were not screened. Stopping screening between ages 60 and 69 y in women with adequate negative screening seems sensible, but further screening may be justifiable as life expectancy increases.

Project description:Background Survival prediction for cervical cancer is usually based on its stage at diagnosis or a multivariate nomogram. However, few studies cared whether long-term survival improved after they survived for several years. Meanwhile, traditional survival analysis could not calculate this dynamic outcome. We aimed to assess the improvement of survival over time using conditional survival (CS) analysis and developed a novel conditional survival nomogram (CS-nomogram) to provide individualized and real-time prognostic information. Methods Cervical cancer patients were collected from the Surveillance, Epidemiology, and End Results (SEER) database. The Kaplan–Meier method estimated cancer-specific survival (CSS) and calculated the conditional CSS (C-CSS) at year y+x after giving x years of survival based on the formula C-CSS(y|x) =CSS(y+x)/CSS(x). y indicated the number of years of further survival under the condition that the patient was determined to have survived for x years. The study identified predictors by the least absolute shrinkage and selection operator (LASSO) regression and used multivariate Cox regression to demonstrate these predictors’ effect on CSS and to develop a nomogram. Finally, the CSS possibilities predicted by the nomogram were brought into the C-CSS formula to create the CS-nomogram. Results A total of 18,511 patients aged <65 years with cervical cancer from 2004 to 2019 were included in this study. CS analysis revealed that the 15-year CSS increased year by year from the initial 72.6% to 77.8%, 84.5%, 88.8%, 91.5%, 93.5%, 94.8%, 95.7%, 96.4%, 97.3%, 98.0%, 98.5%, 99.1%, and 99.4% (after surviving for 1-13 years, respectively), and found that when survival exceeded 5-6 years, the risk of death from cervical cancer would be less than 5% in 10-15 years. The CS-nomogram constructed using tumor size, lymph node status, distant metastasis status, and histological grade showed strong predictive performance with a concordance index (C-index) of 0.805 and a stable area under the curve (AUC) between 0.795 and 0.816 over 15 years. Conclusions CS analysis in this study revealed the gradual improvement of CSS over time in long-term survived cervical cancer patients. We applied CS to the nomogram and developed a CS-nomogram successfully predicting individualized and real-time prognosis.

Dataset Information

Indicators of "healthy aging" in older women (65-69 years of age). A data-mining approach based on prediction of long-term survival.

Background

Methods

Results

Publications

Indicators of "healthy aging" in older women (65-69 years of age). A data-mining approach based on prediction of long-term survival.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets