Study of the bivariate survival data using frailty models based on Lévy processes

Frailty models allow us to take into account the non-observable inhomogeneity of individual hazard functions. Although models with time-independent frailty have been intensively studied over the last decades and a wide range of applications in survival analysis have been found, the studies based on the models with time-dependent frailty are relatively rare. In this paper, we formulate and prove two propositions related to the identifiability of the bivariate survival models with frailty given by a nonnegative bivariate Lévy process. We discuss parametric and semiparametric procedures for estimating unknown parameters and baseline hazard functions. Numerical experiments with simulated and real data illustrate these procedures. The statements of the propositions can be easily extended to the multivariate case

A frailty model for (interval) censored family survival data, applied to the age at onset of non-physical problems

Family survival data can be used to estimate the degree of genetic and environmental contributions to the age at onset of a disease or of a specific event in life. The data can be modeled with a correlated frailty model in which the frailty variable accounts for the degree of kinship within the family. The heritability (degree of heredity) of the age at a specific event in life (or the onset of a disease) is usually defined as the proportion of variance of the survival age that is associated with genetic effects. If the survival age is (interval) censored, heritability as usually defined cannot be estimated. Instead, it is defined as the proportion of variance of the frailty associated with genetic effects. In this paper we describe a correlated frailty model to estimate the heritability and the degree of environmental effects on the age at which individuals contact a social worker for the first time and to test whether there is a difference between the survival functions of this age for twins and non-twins. © 2009 The Author(s)

Homeostatic dysregulation proceeds in parallel in multiple physiological systems

Abstract: An increasing number of aging researchers believes that multisystem physiological dysregulation may be a key biological mechanism of aging, but evidence of this has been sparse. Here, we used biomarker data on nearly 33 000 individuals from four large datasets to test for the presence of multi-system dysregulation. We grouped 37 biomarkers into six a priori groupings representing physiological systems (lipids, immune, oxygen transport, liver function, vitamins, and electrolytes), then calculated dysregulation scores for each system in each individual using statistical distance. Correlations among dysregulation levels across systems were generally weak but significant. Comparison of these results to dysregulation in arbitrary ‘systems’ generated by random grouping of biomarkers showed that a priori knowledge effectively distinguished the true systems in which dysregulation proceeds most independently. In other words, correlations among dysregulation levels were higher using arbitrary systems, indicating that only a priori systems identified distinct dysregulation processes. Additionally, dysregulation of most systems increased with age and significantly predicted multiple health outcomes including mortality, frailty, diabetes, heart disease, and number of chronic diseases. The six systems differed in how well their dysregulation scores predicted health outcomes and age. These findings present the first unequivocal demonstration of integrated multi-system physiological dysregulation during aging, demonstrating that physiological dysregulation proceeds neither as a single global process nor as a completely independent process in different systems, but rather as a set of system-specific processes likely linked through weak feedback effects. These processes – probably many more than the six measured here – are implicated in aging

A polymorphic variant of the insulin-like growth factor 1 (IGF-1) receptor correlates with male longevity in the Italian population: a genetic study and evaluation of circulating IGF-1 from the "Treviso Longeva (TRELONG)" study

<p>Abstract</p> <p>Background</p> <p>An attenuation of the insulin-like growth factor 1 (IGF-1) signaling has been associated with elongation of the lifespan in simple metazoan organisms and in rodents. In humans, IGF-1 level has an age-related modulation with a lower concentration in the elderly, depending on hormonal and genetic factors affecting the IGF-1 receptor gene (<it>IGF-1R</it>).</p> <p>Methods</p> <p>In an elderly population from North-eastern Italy (<it>n </it>= 668 subjects, age range 70–106 years) we investigated the <it>IGF-1R </it>polymorphism G3174A (<it>rs2229765</it>) and the plasma concentration of free IGF-1. Frequency distributions were compared using χ²-test "Goodness of Fit" test, and means were compared by one-way analysis of variance (ANOVA); multiple regression analysis was performed using JMP7 for SAS software (SAS Institute, USA). The limit of significance for genetic and biochemical comparison was set at α = 0.05.</p> <p>Results</p> <p>Males showed an age-related increase in the A-allele of <it>rs2229765 </it>and a change in the plasma level of IGF-1, which dropped significantly after 85 years of age (85+ group). In the male 85+ group, A/A homozygous subjects had the lowest plasma IGF-1 level. We found no clear correlation between <it>rs2229765 </it>genotype and IGF-1 in the females.</p> <p>Conclusion</p> <p>These findings confirm the importance of the <it>rs2229765 </it>minor allele as a genetic predisposing factor for longevity in Italy where a sex-specific pattern for IGF-1 attenuation with ageing was found.</p

Midlife muscle strength and human longevity up to age 100 years: a 44-year prospective study among a decedent cohort

We studied prospectively the midlife handgrip strength, living habits, and parents’ longevity as predictors of length of life up to becoming a centenarian. The participants were 2,239 men from the Honolulu Heart Program/Honolulu–Asia Aging Study who were born before the end of June 1909 and who took part in baseline physical assessment in 1965–1968, when they were 56–68 years old. Deaths were followed until the end of June 2009 for 44 years with complete ascertainment. Longevity was categorized as centenarian (≥100 years, n = 47), nonagenarian (90–99 years, n = 545), octogenarian (80–89 years, n = 847), and ≤79 years (n = 801, reference). The average survival after baseline was 20.8 years (SD = 9.62). Compared with people who died at the age of ≤79 years, centenarians belonged 2.5 times (odds ratio (OR) = 2.52, 95% confidence interval (CI) = 1.23–5.10) more often to the highest third of grip strength in midlife, were never smokers (OR = 5.75 95% CI = 3.06–10.80), had participated in physical activity outside work (OR = 1.13 per daily hour, 95% CI = 1.02–1.25), and had a long-lived mother (≥80 vs. ≤60 years, OR = 2.3, 95% CI = 1.06–5.01). Associations for nonagenarians and octogenarians were parallel, but weaker. Multivariate modeling showed that mother’s longevity and offspring’s grip strength operated through the same or overlapping pathway to longevity. High midlife grip strength and long-lived mother may indicate resilience to aging, which, combined with healthy lifestyle, increases the probability of extreme longevity

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

<p>Abstract</p> <p>Background</p> <p>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).</p> <p>Methods</p> <p>We considered only the youngest subjects (<it>n </it>= 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.</p> <p>Results</p> <p>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 ≥ 0.879 or RH ≤ 1.131; P < 0.001). We evaluated this model and show that it predicts long-term survival among subjects assigned differing causes of death (e.g., cancer, cardiovascular disease; P < 0.01). For an average follow-up time of 20 years, output from the model was associated with multiple outcomes among survivors, such as tests of cognitive function, geriatric depression, number of daily living impairments and grip strength (P < 0.03).</p> <p>Conclusions</p> <p>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.</p