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PubMed1999

Luteinizing hormone and different genetic variants, as indicators of frailty in healthy elderly men.

We investigated the possible clinical correlates between the serum LH concentration and characteristics of frailty and determined the presence and concentration of a genetic LH variant in an independently living population of elderly men. After exclusion of subjects with severe mobility problems and signs of dementia, 403 healthy men (aged 73-94 yr) were randomly selected from a population-based sample. Total testosterone (T), sex hormone-binding globulin (SHBG), and leptin were determined by RIA. Non-SHBG-bound T was calculated. LH and the presence of the genetic LH variant were measured using immunofluorometric assays. The characteristics of frailty were leg extensor strength using dynamometry, bone mineral density of total body and proximal femur, and body composition, including lean mass and fat mass, measured by dual energy x-ray absorptiometry. Disability was further assessed by the Modified Health Assessment Questionnaire and by a measure of physical performance. LH significantly increased with age and inversely correlated with T and non-SHBG-bound T. LH was inversely related to muscle strength and lean mass, and both relations were independent of T. LH was positively related to self-reported disability (Modified Health Assessment Questionnaire); 12.5% of the study population was heterozygous for the LH variant allele. T levels and the degree of frailty were not different in the wild-type LH group compared with the heterozygote LH variant group. A significant positive relation between LH and fat mass as well as leptin was only present in the heterozygote LH variant group. In conclusion, serum LH levels increases with age in independently living elderly men and correlates inversely with a variety of indicators of frailty. The observed relation between LH and frailty, independent of T, suggests that LH reflects serum androgen activity in a different way than T, possibly reflecting more closely the combined feedback effect of estrogen and androgen. A difference in biological response between the two LH forms is suggested, as a difference exists in the relation between LH and fat mass, respectively, and leptin in the heterozygote LH variant subjects vs. the wild-type LH subjects.

Aged↗

PubMedDate not supplied

[Cognitive state as a conditioner of frailty in the elderly. Perspective from a health centre].

AIM: To determine the influence of the cognitive state on the presence of different frailty factors in the elderly. METHODS: Study of an outpatient elderly population with chronic diseases (resident at home or institutionalised), the presence of different frailty risk factors and their relation to cognitive state (measured using the mini-mental state examination-MEC). RESULTS: Study of 147 elderly people with an average age of 71.4 years and a similar proportion of men (74; 50.3%) and women (73; 49.7%). Thirty-four subjects (23.1%) institutionalised in residences. The percentage of patients showing cognitive impairment (MEC<24 points) is 12.9% (19 cases). Presence of frailty risk factors: low social support: 7.5% (11); falls: 17% (25); urinary incontinence: 18.4% (27); depression: 13.6% (20); anxiety-insomnia: 29.9% (44); hospitalisation-readmissions: 21.8% (32); multiple medications (>3 medicines): 53.7% (79); pluripathology (> or =3 diseases): 36.1% (53). The frailty factors that have a significant relation in patients with cognitive impairment (MEC<24) are falls [OR=59.5 (CI 95%=14.7-240.6)] (p<0.0001), urinary incontinence [OR=31.2 (8.9-109.1)] (p<0.0001), hospitalisation-readmissions [OR=32.9 (8.6-125.8)] (p<0.0001) and depression [OR=7.8 (2.5-23.5)] (p<0.0001). With respect to scoring on the MEC by percentiles, the risk factors that showed a tendency of lineal appearance are falls (p<0.0001), urinary incontinence (p<0.0001), hospitalisation-readmissions (p<0.0001) and pluripathology (p=0.002). CONCLUSIONS: Cognitive impairment marks the appearance in a significant form of frailty factors in the elderly, such as falls, urinary incontinence, hospitalisation-readmissions and depression. This relation is not only appreciable in patients with an established cognitive impairment (MEC<24 points), but there is also a trend to appear as this impairment progresses, with a statistical relation for falls, urinary incontinence, hospitalisation-readmissions and pluripathology.

Age Factors↗

PubMed2005

Comorbidity, frailty, and evolution of pressure ulcers in geriatrics.

BACKGROUND: The prevalence of pressure ulcers (PUs) ranges from 1 to 18% of in-patients and from 3 to 28% in long-term settings. The aim of our study was to verify how comorbidity and frailty influenced the course of PUs in a population of elderly subjects hospitalized in a long-term care setting. MATERIAL/METHODS: The charts of 125 patients with pressure ulcers were evaluated retrospectively. For each subject we took note of PU characteristics (stage, ulcer surface, evolution), and clinical characteristics (comorbidity, adverse clinical events, and cognitive, functional, and nutritional status). Frailty was defined considering age, cognitive functions, and functional and nutritional status. RESULTS: In 58 patients (46.4%) there was overall resolution of the lesions, while in 39 patients (31.2%) we had "improvement" of PUs. The course of PU was not significantly influenced by the patient's physiological characteristics, cognitive status, or the initial characteristics of PU. We noticed a significant difference in the course of PUs as a function of autonomy level and clinical and nutritional status. During the observation period we found significant differences in the frailty scores: 87.2% of those who showed an improvement in the score had resolution or improvement in PUs, while this occurred in only 27.3% of those who had a worsening in the level of frailty. CONCLUSIONS: We maintain that integration of multidimensional assessment, with special attention to comorbidity status and to frailty (particularly autonomy level and nutritional status), and the different approaches may allow optimal healing of PUs.

Aged↗

PubMed2006

Recurrence in breast cancer. Analysis with frailty model.

OBJECTIVE: To determine the value of known prognostic factors for metastasis in breast cancer by accounting for patient-specific effect of patients who received surgical treatment followed by adjuvant treatment using the frailty model. METHODS: One hundred seventeen women with breast cancer who underwent surgery followed by adjuvant therapy at 3 hospitals in Tehran, Iran between 1995 and 2003 were enrolled in this study. Women with defined breast cancer with no distant metastases at time of diagnosis that have undergone modified radical mastectomy or breast-conserving surgery were enrolled. Tumors were classified according to the Tumor, Node, Metastasis (TNM) system of the American Joint Committee on cancer. Grading was performed according to Scarff-Bloom-Richardson method. Estrogen receptor (ER) was measured by immunohistochemistry method. The patients have been followed regularly by routine clinical laboratory profile, serologic markers (CEA, CA15-3) and para-clinical examinations; furthermore, we have followed missing materials by other access ways such as calling. RESULTS: Median follow up time for patients was 26 months after surgery. During the follow up time 44 (38%) patients developed metastasis and 20 (45%) of these 44 patients experienced the second metastasis. The median disease-free survival for patients in the study was 49.6 month. The median time to experience second metastasis after the first one was 22.5 months. Risk of occurrence of a metastasis in the first year after surgery was 12%. Risk of experience a metastasis up to the second year was 32% and up to fifth years was 69%. Result of fitting a frailty model to data showed that size of tumor, number of positive lymph nodes and histologic grade had a significant effect on the risk of metastasis (p<0.05). Patients with tumor size larger than 5 cm were in higher risk of metastasis compared with others. Increase in the number of positive lymph nodes to more than 10, increased risk of metastasis. Patients with moderate or undifferentiated histologic grade were in higher risk of metastasis to well differentiated patients. Age, family history, lymph node stage, and ER had no significant effect. It was found that there was heterogeneity between patients after adjusting for other covariates because variance of frailty was 0.315. It means that based on the variance of the distribution of frailty, the relative risk of high-risk patients to low-risk patients was 7.2, wherein high-risk group is defined as a cluster at the 95th percentile and low-risk to a cluster of 5th percentile of the frailty distribution. CONCLUSION: Known risk factors describe the risk of metastasis partly and other unknown or unmeasured factors, such as genetics or environmental factors are important to describe the risk of metastasis in breast cancer.

Adult↗

PubMed1988

Inherited frailty and longevity.

The life spans of parents and children appear only weakly related, even though parents affect their children's longevity through both genetic and environmental influences. These influences can be summarized as a correlation between parents' and children's frailty. It is shown that even if children perfectly inherit their frailty from their parents, parents' life spans explain little of the variance in children's life spans, because the variance in life expectancies among people with different frailties is small compared with the variance in life spans among people at the same level of frailty. By interpreting frailty as a relative risk in a proportional-hazard model, longevity as a duration or waiting time, and inheritance as an invariance in relative risk over time, one can extend this result to repeatable events involving fertility, migration, marriage, unemployment, and so forth.

Adolescent↗

PubMed1995

Frailty: constructing a common meaning, definition, and conceptual framework.

The term frailty has been used for many years, both in everyday and academic language. It is a term that appears, on the surface, to be simple enough in its meaning, yet it has been used in a variety of ways to describe both people and a condition that applies to people. Moreover, little conceptual thought has gone into the nature of frailty and the factors that might affect it. This paper presents a definition of frailty: frailty occurs when there is diminished ability to carry out the important practical and social activities of daily living. It also presents a conceptualization of frailty that specifies its basic components, the categories of factors that contribute to it, and its relationship to closely related concepts.

Activities of Daily Living↗

PubMed2025

Gut metagenome and plasma metabolome profiles in older adults suggest pyruvate metabolism as a link between sleep quality and frailty.

Poor sleep quality is associated with increased frailty in older adults, but the role of the gut microbiome in this relationship remains unclear. Here, gut metagenome and plasma metabolome were profiled in 1,225 individuals aged 62-96 years. Poor sleep quality was associated with reduced abundances of potential probiotics such as Faecalibacterium prausnitzii and elevated abundances of pathobionts. A gut microbiome sleep quality index (GMSI) was developed to quantify microbial balance related to better sleep quality; higher GMSI scores were inversely associated with frailty and related clinical traits. Pyruvate metabolism emerged as a key microbial pathway linking sleep quality to frailty, with features such as F. prausnitzii abundance and microbial pyridoxal 5'-phosphate biosynthesis implicated in this connection. These findings deepen our understanding of microbiome-metabolome pathways related to sleep quality and frailty in aging and provide a valuable resource for future longitudinal and interventional studies.

Humans↗

PubMed1998

ML and REML estimation in survival analysis with time dependent correlated frailty.

In the study of multiple failure times for the same subjects, for example, recurrent infections for patients with a given disease, there are often subject effects, that is, subjects have different risks that cannot be explained by known covariates. Standard methods, which ignore subject effects, lead to overestimation of precision. The frailty model for subject effects is better, but can be insufficient, because it assumes that subject effects are constant over time. Experience has shown that the dependence between different time periods often decreases with distance in time. Such a model is presented here, assuming that the frailty is no longer constant, but time varying, with one value for each spell. The main example is a first-order autoregressive process. This is applied to a data set of 128 patients with chronic granulomatous disease (CGD), participating in a placebo controlled randomized trial of gamma interferon (gamma-IFN), suffering between 0 and 7 infections. It is shown that the time varying frailty model gives a significantly better fit than the constant frailty model.

Adrenal Cortex Hormones↗

PubMed1999

A frailty approach for modelling diseases with variable age of onset in families: the NHLBI Family Heart Study.

We use frailty models to analyse the effect of latent genetic and environmental risk factors on hazard functions in nuclear families. The approach expresses latent risk factors (frailties) as functions of the effects of a single major gene and shared familial risk. The latter may result from shared polygenes and/or a common environment. Genetic frailties are modelled using a two-point distribution, and residual frailties (shared environment, polygenes) using a gamma distribution. The two-point distribution follows the laws of Mendelian transmission, under either dominant or recessive gene action. We describe a robust EM approach for the joint estimation of the magnitude of genetic, covariate, gene by covariate interaction effects while allowing residual familial correlation. We illustrate the method on coronary heart disease data from the National Heart, Lung, and Blood Institute Family Heart Study. In addition, a simulation study shows that ignoring possible residual correlation in disease status due to a shared familial environment leads to an overestimate of the relative risk associated with a latent genotype.

Age of Onset↗

PubMed2003

Three-state frailty model for age at onset of dementia and death in Swedish twins.

We present a frailty model to estimate the relative importance of genetic and environmental factors on age at onset of dementia in a twin design. We use modern survival methodology to define a model that accounts simultaneously for longitudinal aspects, e.g., left truncation and right censoring in data, and the multivariate nature of twin data. Additionally, we present a novel three-state frailty model, with nondemented, demented, and dead states, describing variation in the onset of disease and mortality simultaneously in one model, while accounting for possible dependence for the two competing events. The frailty structure, i.e., the latent random effects structure, mimics the traditional twin model for continuous variables used in quantitative genetics, and as such describes within-pair dependence. This in turn leads to estimates for intrapair correlations, as well as for additive genetic, and shared and nonshared environmental components of variance. A hierarchical Bayesian model formulation and Gibbs sampling are used to estimate posterior distributions of the parameters. The models are applied to Swedish Twin Registry data on the onset of dementia in elderly twins. Based on the three-state frailty model, we estimate the intrapair correlations for dementia to be 0.87 [90% credible interval: 0.61,0.98] and 0.68[0.18,0.91] for MZ and DZ twins, respectively. Based on our model, we estimate that genetic effects account for about one third, and shared environmental effects for almost a half, of the variation in dementia hazards between individuals. More data, however, are needed to gain precision in these estimates.

Age of Onset↗

PubMed1995

Modelling frailty in area mortality.

This paper investigates the impact on area life tables of the specification of unobserved frailty. Frailty specification may affect both the regression effects of area and individual level covariates, and lead to changes in the value of summary mortality parameters, such as life expectancy. The paper also investigates how frailty affects life tables for specific causes of death, especially lung cancer and heart disease. Implications for choice between different model specifications, both in terms of age dependence and frailty, are discussed. The focus is on registered deaths recorded by age, birthplace and by small area within a borough of Greater London.

Adult↗

PubMed2001

Analysis of childhood brain tumour data in New York City using frailty models.

This paper uses frailty models to analyse overall survival and progression-free survival times for children with a brain tumour. We are interested in how surgery resection affects survival times. We are also interested in how strong a child's progression-free survival correlates with his/her overall survival and if the association differs with age. Traditionally the frailty is modelled parametrically and a maximum likelihood approach is used to estimate the parameters of interest. However, the result is sensitive to the misspecification of the frailty distribution and the currently developed algorithms for the maximum likelihood approach do not allow the association parameter to depend on covariates. Xue formulates a Poisson regression model and applies an estimating equation approach to obtain a consistent estimate of the covariate effect on survival. This paper extends that approach to obtain consistent and efficient estimates of the association parameter as well as the covariate effect and to allow the association parameter to depend on the covariates. The approach does not require the specification of the frailty distribution. The performance of the method is evaluated through simulation studies. We apply this method to a childhood brain tumour data set in New York City.

Age Factors↗

PubMed1996

Bivariate frailty model for the analysis of multivariate survival time.

Because of limitations of the univariate frailty model in analysis of multivariate survival data, a bivariate frailty model is introduced for the analysis of bivariate survival data. This provides tremendous flexibility especially in allowing negative associations between subjects within the same cluster. The approach involves incorporating into the model two possibly correlated frailties for each cluster. The bivariate lognormal distribution is used as the frailty distribution. The model is then generalized to multivariate survival data with two distinguished groups and also to alternating process data. A modified EM algorithm is developed with no requirement of specification of the baseline hazards. The estimators are generalized maximum likelihood estimators with subject-specific interpretation. The model is applied to a mental health study on evaluation of health policy effects for inpatient psychiatric care.

Algorithms↗

PubMed1995

Frailty models for survival data.

A frailty model is a random effects model for time variables, where the random effect (the frailty) has a multiplicative effect on the hazard. It can be used for univariate (independent) failure times, i.e. to describe the influence of unobserved covariates in a proportional hazards model. More interesting, however, is to consider multivariate (dependent) failure times generated as conditionally independent times given the frailty. This approach can be used both for survival times for individuals, like twins or family members, and for repeated events for the same individual. The standard assumption is to use a gamma distribution for the frailty, but this is a restriction that implies that the dependence is most important for late events. More generally, the distribution can be stable, inverse Gaussian, or follow a power variance function exponential family. Theoretically, large differences are seen between the choices. In practice, using the largest model makes it possible to allow for more general dependence structures, without making the formulas too complicated.

Adolescent↗

PubMed1995

Frailty models of manufacturing effects.

The median service lifetime of respiratory safety devices produced by different manufacturers is determined using frailty models to account for unobserved differences in manufacturing processes and raw materials. The gamma and positive stable frailty distributions are used to obtain survival distribution estimates when the baseline hazard is assumed to be Weibull. Frailty distributions are compared using laboratory test data of the failure times for 104 respirator cartridges produced by 10 different manufacturers tested with three different challenge agents. Likelihood ratio tests indicate that both frailty models provide a significant improvement over a Weibull model assuming independence. Results are compared to fixed effects approaches for analysis of this data.

Equipment Failure↗

PubMed2006

Frailty modelling of colorectal cancer incidence in Norway: indications that individual heterogeneity in risk is related to birth cohort.

Some cancer types level off or decrease in incidence at older age groups, not following the Weibull hazard rate. This stagnation can be explained by the frailty model, which describes the population effect of mixing individuals who are susceptible, with high risk of cancer, with those that are "non-susceptible", with a low risk of cancer even in the oldest age groups. The aim of the study was to apply a frailty model on colorectal cancer incidence data for the Norwegian population aged 40-99 years, diagnosed 1956-2000. The model provided an acceptable fit to the data. The estimated proportion of susceptibles increased from about 5% to about 24% from the first cohort (1851-1855) to the last cohort (1946-1950), in line with the rise in incidence of the disease during this period. According to the frailty modelling, the estimated number of genetic events necessary for a malignant lesion to develop in the colorectum is seven to eight, which accords with the present knowledge regarding colorectal carcinogenesis. The frailty phenomenon may thus be present in this cancer form. The findings indicate that it is possible to model the development of colorectal cancer in the population based on large heterogeneity in risk between individuals, in such a manner that a small group of individuals are susceptible to develop the disease, whereas the remaining majority have a low susceptibility.

Adult↗

PubMed2005

A distribution for multivariate frailty based on the compound Poisson distribution with random scale.

Frailty models are often used to model heterogeneity in survival analysis. The most common frailty model has an individual intensity which is a product of a random factor and a basic intensity common to all individuals. This paper uses the compound Poisson distribution as the random factor. It allows some individuals to be non-susceptible, which can be useful in many settings. In some diseases, one may suppose that a number of families have an increased susceptibility due to genetic circumstances. Then, it is logical to use a frailty model where the individuals within each family have some shared factor, while individuals between families have different factors. This can be attained by randomizing the Poisson parameter in the compound Poisson distribution. To our knowledge, this is a new distribution. The power variance function distributions are used for the Poisson parameter. The subsequent appearing distributions are studied in some detail, both regarding appearance and various statistical properties. An application to infant mortality data from the Medical Birth Registry of Norway is included, where the model is compared to more traditional shared frailty models.

Humans↗

PubMed2006

Association between level of frailty and bone mineral density in community-dwelling men.

The goal of this study is to determine the associations between the components of a frailty definition and bone mineral density (BMD) in older men. A total of 392 community dwelling men (age range: 58-95 yr) with a mean age of 73+/-8 yr were evaluated. Femoral neck BMD T-scores ranged from -5.78 to +2.50, with 48.7% who had T-scores between -1 and -2.5 (low bone mass) and 8.7% who had T scores < or = -2.5 (osteoporosis). Participants were characterized as normal (39%), intermediate (55%), or frail (6%). Hand grip strength was 31.5+/-9.1 kg in those with normal BMD compared with 26.5+/-7.9 kg in those with osteoporotic BMD (p=0.0026). Walk speed (8 ft) was 2.32+/-0.49 s in those with normal BMD compared with 2.87+/-1.30 s with osteoporotic BMD (p=0.0015). Femoral neck T-score declined significantly with increasing level of frailty (p=0.014), but significance of decline was lost when corrected for age. Increasing frailty was associated with lower femoral neck BMD, although the association was not independent of age. Two components of the frailty model (i.e., hand grip strength and walking speed) were independently associated with lower femoral neck BMD, a finding that has not previously been reported in men.

Absorptiometry, Photon↗