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Background Methods Results Conclusion Amidst the rise of frailty among a globally aging population, olfactory decline has emerged as a harbinger of frailty and mortality in population‐level studies. However, the relationships between frailty and the olfactory subdomains of identification (OI), discrimination (OD), and threshold (OT) remain unexplored. This study prospectively examined the association between olfactory subdomains and the physical frailty phenotype (PFP) to investigate olfactory evaluation as a means of frailty screening.A case‒control study of 45 frail and 45 non‐frail individuals matched by age and sex. OT, OD, OI (range 0‒16), and composite sum (threshold, discrimination, and identification scores [TDI], range 0‒48) were measured with Sniffin’ Sticks. PFP was defined by presence of three or more criteria: physical inactivity, self‐reported exhaustion, muscle weakness, slow gait, and unintentional weight loss. Conditional logistic regression evaluated associations between olfactory subdomains and frailty.Ninety individuals with mean age of 83.1 ± 4.9 years, 60% female (n = 54), and 87.8% white (n = 79) were included. Olfactory scores were significantly lower in the frail group for OI (9.2 vs. 12.1, p < 0.001), OD (8.1 vs. 11.6, p < 0.001), OT (4.4 vs. 8.5, p < 0.001), and TDI (21.7 vs. 32.2, p < 0.001) than in the non‐frail group. A single‐point decrease in olfactory score was associated with increased odds of frailty in OT (odds ratio [OR]: 2.21, 95% confidence interval: [1.22, 3.98]), OD (OR: 2.19, 95% CI: [1.32, 3.65]), OI (OR: 2.29, 95% CI: [1.19, 4.39]), and TDI (OR: 1.54, 95% CI: [1.14, 2.08]).The robust association between olfactory subdomain scores and frailty suggests that olfaction may be an accessible signifier of frailty. Future studies should investigate this relationship longitudinally to assess predictive relationships. [ABSTRACT FROM AUTHOR]

Unobserved individual heterogeneity is a common challenge in population cancer survival studies. This heterogeneity is usually associated with the combination of model misspecification and the failure to record truly relevant variables. We investigate the effects of unobserved individual heterogeneity in the context of excess hazard models, one of the main tools in cancer epidemiology. We propose an individual excess hazard frailty model to account for individual heterogeneity. This represents an extension of frailty modeling to the relative survival framework. In order to facilitate the inference on the parameters of the proposed model, we select frailty distributions which produce closed‐form expressions of the marginal hazard and survival functions. The resulting model allows for an intuitive interpretation, in which the frailties induce a selection of the healthier individuals among survivors. We model the excess hazard using a flexible parametric model with a general hazard structure which facilitates the inclusion of time‐dependent effects. We illustrate the performance of the proposed methodology through a simulation study. We present a real‐data example using data from lung cancer patients diagnosed in England, and discuss the impact of not accounting for unobserved heterogeneity on the estimation of net survival. The methodology is implemented in the R package IFNS. [ABSTRACT FROM AUTHOR]

Political longevity in young democracies has attracted the attention of scholars and practitioners alike due to several particular characteristics of such democracies, such as a low level of trust, a low level of credibility, corruption, economic difficulties, a less well‐established rule of law and an increased bureaucracy. In such a context, we studied the tenure duration of Romanian ministers since 1989, as well as their accumulated political longevity in ministerial offices. Using proportional hazards regression, we observed some peculiarities in the young Romanian democracy in comparison with more established regimes. We observed that left‐wing majorities tend to increase the probability of seat changes and thus diminish tenure longevity. We also observed that good economic conditions may lead to the substitution of certain types of ministries, while higher inflation rates tend to shorten tenure longevity for Romanian ministers. Moreover, our estimations support the finding that Romanian ministers tend to have shorter tenures as the number of past ministerial functions increases and that the burden of simultaneously managing various ministries significantly contributes to the shorter political longevity of a given minister. Finally, recent ministers have had longer tenures than those in the first years after the fall of communism in Eastern Europe in 1989. [ABSTRACT FROM AUTHOR]

Survival models which incorporate frailties are common in time-to-event data collected over distinct spatial regions. While incomplete data are unavoidable and a common complication in statistical analysis of spatial survival research, most researchers still ignore the missing data problem. In this paper, we propose a geostatistical modeling approach for incomplete spatially correlated survival data. We achieve this by exploring missingness in outcome, covariates, and spatial locations. In the process, we analyze incomplete spatially-referenced survival data using a Weibull model for the baseline hazard function and correlated log-Gaussian frailties to model spatial correlation. We illustrate the proposed method with simulated data and an application to geo-referenced COVID-19 data from Ghana. There are several disagreements between parameter estimates and credible intervals widths obtained using our proposed approach and complete case analysis. Based on these findings, we argue that our approach provides more reliable parameter estimates and has higher predictive accuracy. [ABSTRACT FROM AUTHOR]

The best approach for allogeneic haematopoietic stem cell transplantations (allo HCT) in patients with chronic lymphocytic leukaemia ( CLL) is unknown. We therefore analysed the impact of procedure- and centre-related factors on 5-year event-free survival ( EFS) in a large retrospective study. Data of 684 CLL patients who received a first allo HCT between 2000 and 2011 were analysed by multivariable Cox proportional hazards models with a frailty component to investigate unexplained centre heterogeneity. Five-year EFS of the whole cohort was 37% (95% confidence interval [ CI], 34-42%). Larger numbers of CLL allo HCTs (hazard ratio [ HR] 0·96, P = 0·002), certification of quality management ( HR 0·7, P = 0·045) and a higher gross national income per capita ( HR 0·4, P = 0·04) improved EFS. In vivo T-cell depletion ( TCD) with alemtuzumab compared to no TCD ( HR 1·5, P = 0·03), and a female donor compared to a male donor for a male patient ( HR 1·4, P = 0·02) had a negative impact on EFS, but not non-myeloablative versus more intensive conditioning. After correcting for patient-, procedure- and centre-characteristics, significant variation in centre outcomes persisted. In conclusion, further research on the impact of centre and procedural characteristics is warranted. Non-myeloablative conditioning appears to be the preferable approach for patients with CLL. [ABSTRACT FROM AUTHOR]

[Purpose] The aim of this study was to examine the relationships between physical functions and psychological factors in community-dwelling frail elderly. [Subjects] Subjects were 170 elderly persons who participated in an exercise program for frailties. [Methods] Walking abilities, balance functions, and muscle functions of the lower and upper extremities were assessed. We evaluated relationships between physical functions and psychological factors such as Health-related Quality of Life (HR-QOL), falls self-efficacy and so on by partial correlation coefficient analysis. [Results] Some physical functions showed significant relationships with psychological factors, but those relations were moderate or weak. [Conclusion] Although we supposed that there were some relations between physical and psychological functions, a more multiphasic evaluation might be needed to produce more conclusive evidence. [ABSTRACT FROM AUTHOR]

We study job durations using a multivariate hazard model allowing for worker-specific and firm-specific unobserved determinants. The latter are captured by unobserved heterogeneity terms or random effects, one at the firm level and another at the worker level. This enables us to decompose the variation in job durations into the relative contribution of the worker and the firm. We also allow the unobserved terms to be correlated in a model that is primarily relevant for markets with small firms. For the empirical analysis, we use a Portuguese longitudinal matched employer–employee dataset. The model is estimated with a Bayesian Markov chain Monte Carlo (MCMC) estimation method. The results imply that unobserved firm characteristics explain almost 40% of the systematic variation in log job durations. In addition, we find a positive correlation between unobserved worker and firm characteristics. [ABSTRACT FROM AUTHOR]

Bayesian Poisson log-linear multilevel models scalable to epidemiological studies are proposed to investigate population variability in sleep state transition rates. Hierarchical random effects are used to account for pairings of subjects and repeated measures within those subjects, as comparing diseased with non-diseased subjects while minimizing bias is of importance. Essentially, non-parametric piecewise constant hazards are estimated and smoothed, allowing for time-varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming exponentially distributed survival times. Such re-derivation allows synthesis of two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear generalized estimating equations (GEE) models for transition counts. An example data set from the Sleep Heart Health Study is analyzed. Supplementary material includes the analyzed data set as well as the code for a reproducible analysis. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A general formulation of mixed proportional hazard models with K random effects is provided. It enables to account for a population stratified at K different levels. I then show how to approximate the partial maximum likelihood estimator using an EM algorithm. In a Monte Carlo study, the behavior of the estimator is assessed and I provide an application to the ratification of ILO conventions. Compared to other procedures, the results indicate an important decrease in computing time, as well as improved convergence and stability. [ABSTRACT FROM AUTHOR]

Multi-state models provide a unified framework for the description of the evolution of discrete phenomena in continuous time. One particular example is Markov processes which can be characterised by a set of time-constant transition intensities between the states. In this paper, we will extend such parametric approaches to semiparametric models with flexible transition intensities based on Bayesian versions of penalised splines. The transition intensities will be modelled as smooth functions of time and can further be related to parametric as well as nonparametric covariate effects. Covariates with time-varying effects and frailty terms can be included in addition. Inference will be conducted either fully Bayesian (using Markov chain Monte Carlo simulation techniques) or empirically Bayesian (based on a mixed model representation). A counting process representation of semiparametric multi-state models provides the likelihood formula and also forms the basis for model validation via martingale residual processes. As an application, we will consider human sleep data with a discrete set of sleep states such as REM and non-REM phases. In this case, simple parametric approaches are inappropriate since the dynamics underlying human sleep are strongly varying throughout the night and individual-specific variation has to be accounted for using covariate information and frailty terms. [ABSTRACT FROM AUTHOR]

Abstract: In a society experiencing an accelerating increase in the middle- and old-age population, there is an urgent need to address age-dependent frailties by a paradigm shift, i.e. a new medical strategy to combat middle-age decline at the stage before incipient old-age problems develop into full-blown diseases. We suggest that a decline in cellular health status occurs at mid-life, and that this decline may involve a universal or system-specific programmatic shift of signaling control. This decline, although sub-clinical and asymptomatic, may precipitate increased risk of late-life diseases. The putative control for this mid-life cellular decline may be governed by a recently discovered group of molecular species, the microRNAs, small RNAs of ∼22 nucleotide bases. In general microRNAs, while themselves not coding for any protein product, negatively regulate the expression of target genes by either degrading their message or inhibiting translation by binding to their 3′-untranslated region (UTR). Thus, possible derailment of these negative regulators for gene expression in mid-life may be the putative force inducing molecular frailty in individual cell signaling, and in time leading to tissue-wide dysfunction. A challenge for future research is then to identify these dysfunctional microRNAs, in order to develop advance diagnosis and therapy to combat mid-life decline, a preventive medicine approach to block, delay or reduce the risk of old-age diseases. [Copyright &y& Elsevier]