Individual frailty excess hazard models in cancer epidemiology.

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.

Transcending human frailties with technological enhancements and replacements: Transhumanist perspective in nursing and healthcare.

As human beings age, they become weak, fragile, and feeble. It is a slowly progressing yet complex syndrome in which old age or some disabilities are not prerequisites; neither does loss of human parts lead to frailty among the physically fit older persons. This paper aims to describe the influences of transhumanist perspectives on human-technology enhancements and replacements in the transcendence of human frailties, including those of older persons, in which technology is projected to deliver solutions toward transcending these frailties. Through technologies including genetic screening and other technological manipulations, intelligent machines and augmented humans improve, maintain, and remedy human-linked susceptibilities. Furthermore, other technologies replace parts fabricated through inorganic-mechanical processes such as 3D-printing. Advancing technologies are reaching the summit of technological sophistication contributing to the transhumanist views of being human in a technological world. Technologies enhance the transcendence of human frailties as essential expressions of the symbiosis between human beings and technology in a transcendental world.

Centre characteristics and procedure-related factors have an impact on outcomes of allogeneic transplantation for patients with CLL: a retrospective analysis from the European Society for Blood and Marrow Transplantation (EBMT).

The best approach for allogeneic haematopoietic stem cell transplantations (alloHCT) 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 alloHCT 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 alloHCTs (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.

Dynamic frailty models based on compound birth-death processes.

Frailty models are used in survival analysis to model unobserved heterogeneity. They accommodate such heterogeneity by the inclusion of a random term, the frailty, which is assumed to multiply the hazard of a subject (individual frailty) or the hazards of all subjects in a cluster (shared frailty). Typically, the frailty term is assumed to be constant over time. This is a restrictive assumption and extensions to allow for time-varying or dynamic frailties are of interest. In this paper, we extend the auto-correlated frailty models of Henderson and Shimakura and of Fiocco, Putter and van Houwelingen, developed for longitudinal count data and discrete survival data, to continuous survival data. We present a rigorous construction of the frailty processes in continuous time based on compound birth-death processes. When the frailty processes are used as mixtures in models for survival data, we derive the marginal hazards and survival functions and the marginal bivariate survival functions and cross-ratio function. We derive distributional properties of the processes, conditional on observed data, and show how to obtain the maximum likelihood estimators of the parameters of the model using a (stochastic) expectation-maximization algorithm. The methods are applied to a publicly available data set.

The association between olfactory subdomains and frailty: A prospective case‒control study investigation.

BACKGROUND: 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. METHODS: 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. RESULTS: 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]). CONCLUSION: 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.

Modeling geostatistical incomplete spatially correlated survival data with applications to COVID-19 mortality in Ghana.

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.

Modelling time varying heterogeneity in recurrent infection processes: an application to serological data.

Frailty models are often used in survival analysis to model multivariate time-to-event data. In infectious disease epidemiology, frailty models have been proposed to model heterogeneity in the acquisition of infection and to accommodate association in the occurrence of multiple types of infection. Although traditional frailty models rely on the assumption of lifelong immunity after recovery, refinements have been made to account for reinfections with the same pathogen. Recently, Abrams and Hens quantified the effect of misspecifying the underlying infection process on the basic and effective reproduction number in the context of bivariate current status data on parvovirus B19 and varicella zoster virus. Furthermore, Farrington, Unkel and their co-workers introduced and applied time varying shared frailty models to paired bivariate serological data. In this paper, we consider an extension of the proposed frailty methodology by Abrams and Hens to account for age-dependence in individual heterogeneity through the use of age-dependent shared and correlated gamma frailty models. The methodology is illustrated by using two data applications.