scholarly journals Lifetime cumulative incidence of dementia in a community-dwelling elderly population in Japan

Neurology ◽  
2020 ◽  
Vol 95 (5) ◽  
pp. e508-e518
Author(s):  
Daigo Yoshida ◽  
Tomoyuki Ohara ◽  
Jun Hata ◽  
Mao Shibata ◽  
Yoichiro Hirakawa ◽  
...  
Keyword(s):  
Cumulative Incidence ◽  
Elderly Population ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Survival Function ◽  
Community Dwelling ◽  
Lifetime Risk ◽  
Hazard Functions ◽  
Japanese Elderly ◽  
Incidence Of Dementia

ObjectiveTo estimate the lifetime cumulative incidence of dementia and its subtypes from a community-dwelling elderly population in Japan.MethodsA total of 1,193 community-dwelling Japanese individuals without dementia, aged 60 years or older, were followed up prospectively for 17 years. The cumulative incidence of dementia was estimated based on a death- and dementia-free survival function and the hazard functions of dementia at each year, which were computed by using a Weibull proportional hazards model. The lifetime risk of dementia was defined as the cumulative incidence of dementia at the point in time when the survival probability of the population was estimated to be less than 0.5%.ResultsDuring the follow-up, 350 participants experienced some type of dementia; among them, 191 participants developed Alzheimer disease (AD) and 117 developed vascular dementia (VaD). The lifetime risk of dementia was 55% (95% confidence interval, 49%–60%). Women had an approximately 1.5 times greater lifetime risk of dementia than men (65% [57%–72%] vs 41% [33%–49%]). The lifetime risks of developing AD and VaD were 42% (35%–50%) and 16% (12%–21%) in women vs 20% (7%–34%) and 18% (13%–23%) in men, respectively.ConclusionLifetime risk of all dementia for Japanese elderly was substantial at approximately 50% or higher. This study suggests that the lifetime burden attributable to dementia in contemporary Japanese communities is immense.

scholarly journals Traumatic Brain Injury and Dementia in Medicare Population: Differences in Risk Between Veterans and Non-Veterans

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 850-851
Author(s):  
Arseniy Yashkin
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Senile Dementia ◽  
Strong Predictor ◽  
Community Dwelling ◽  
Risk Scores ◽  
Increased Risk ◽  
Co Morbidity

Abstract The aim of this study was to assess differences in the effect of traumatic brain injury (TBI) on the onset of Alzheimer’s disease (AD) and other dementias between veteran and non-veteran respondents of the Health and Retirement Study as well as to measure the sensitivity of these differences to the introduction of controls for groups of demographic, medical co-morbidity and polygenic risk scores reflecting AD hallmarks. Using the Fine-Gray proportional hazards model we found that TBI was a strong predictor of dementia in community dwelling residents age 65+: for AD associated risk was 181% [Hazard Ratio (HR): 2.81; CI:2.05-3.86] sample-wide and 142% [HR: 2.42; CI:1.31-2.46] in veteran males. Effect magnitude decreased with the addition of risk-related control variables but remained associated with significantly increased risk. Large differences in risk were observed between veteran and non-veteran males for AD, vascular dementia, senile dementia, and dementia with Lewy Bodies

scholarly journals Cognitive, physical and disability trajectories in community-dwelling elderly people

2021 ◽  
Author(s):  
Ottavia Eleonora Ferraro ◽  
Antonio Guaita ◽  
Simona Villani
Keyword(s):  
Physical Function ◽  
Cumulative Incidence ◽  
Female Gender ◽  
Community Dwelling ◽  
Study Cohort ◽  
Carrier Status ◽  
Speed Test ◽  
Health Trajectories ◽  
Severe Group ◽  
Incidence Of Dementia

Abstract Backgrounds and aims Health trajectories in aging, rather than single time-point assessments, could be early indicators of the onset of conditions such as dementia. The aim of this study was to identify different aging trajectories and to investigate their influence on the cumulative incidence of dementia. Methods We evaluated data referring to 993 elders from the InveCe.Ab study cohort. All subjects were free from dementia at baseline and re-assessed on at least one other occasion thereafter. Cognitive function was assessed using the Mini-Mental State Examination (MMSE), physical function using the Walking Speed Test (WST), and disability on the basis of the Activities of Daily Living (ADL) score. To describe the different courses of the three outcomes combined, the Group-Based Trajectory Model (GBTM) method was applied. We looked for differences in age, gender, education, ApoE-e4 carrier status and obesity, and then investigated the influence of the observed trajectories on the incidence of dementia. Results Three trajectories were identified: a “good” scenario was observed in 703 (70.2%) individuals, who showed substantially stable cognitive and physical function and no disability; an “intermediate” scenario in 248 subjects (25.5%), who recorded a longer walking time, lower MMSE score, and a one-point higher ADL score; and a “severe” scenario in 42 elders (4.3%), who recorded declines in all the outcomes. Female gender, obesity and low education were most represented in the “severe” group. ApoE-e4 carrier status showed no difference between groups. The estimated cumulative incidence of dementia was higher in the “severe” (37%) than in the “intermediate” (7%) and “good” (< 1%) scenarios. Conclusions Using simple measurements, we built different aging trajectories, and observed that the worst performers had the highest incidence of dementia. Better knowledge of trajectories of aging would be useful for preventive interventions aimed at promoting healthier aging.

scholarly journals Circulating Inflammatory and Hemostatic Biomarkers are Associated with All-Cause Death and Cancer Death in a Population of Community-Dwelling Japanese: The Tanushimaru Study

2014 ◽  
Vol 8s3 ◽  
pp. CMC.S17065
Author(s):  
Mika Enomoto ◽  
Hisashi Adachi ◽  
Ako Fukami ◽  
Ayako Yoshimura ◽  
Aya Obuchi ◽  
...  
Keyword(s):  
Cardiovascular Diseases ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Inflammatory Diseases ◽  
Cox Proportional Hazards ◽  
Predictive Markers ◽  
Community Dwelling ◽  
Cox Proportional Hazards Model ◽  
Cancer Death ◽  
Hazards Model

Background In patients with cardiovascular diseases, inflammatory and hemostatic biomarkers are significant indicators of prognosis. We investigated whether circulating inflammatory and hemostatic biomarkers were predictive markers for all-cause death and cancer death in a population of community-dwelling Japanese. Methods We studied 1,920 healthy Japanese adults who underwent health examinations in 1999. Those who reported a history of inflammatory diseases and malignancy on a baseline questionnaire were excluded. Inflammatory and hemostatic biomarkers were measured in the remaining 1,862 participants, who were followed up periodically for 10 years. Multivariate proportional hazards regression analysis was used to estimate all-cause and cancer mortality. Results A total of 258 participants died during follow-up: 87 from cancer, 38 from cerebro-cardiovascular diseases, and 133 from other diseases. Mean C-reactive protein (CRP) levels at baseline were significantly higher in decedents than in survivors. Mean von Willebrand factor (vWF) levels at baseline were significantly higher in decedents than in survivors. The Cox proportional hazards model after adjustments for age and sex showed that CRP (hazard ratio [HR], 1.26; 95% confidence interval [CI], 1.06-1.51) and vWF (HR, 1.01; 95% CI, 1.00-1.01) were independent predictors of all-cause death. CRP (HR, 1.40; 95% CI, 1.06-1.86) and vWF (HR, 1.01; 95% CI, 1.00-1.02) were also independent predictive markers for cancer death. Conclusions Serum CRP and vWF were predictors of all-cause death and cancer death in the population of community dwelling Japanese.

An improved model for the French genetic evaluation of dairy bulls on length of productive life of their daughters

2005 ◽  
Vol 80 (3) ◽  
pp. 249-256 ◽  
Author(s):  
V. Ducrocq
Keyword(s):  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Analysis Model ◽  
Genetic Trend ◽  
Hazard Functions ◽  
Stage Of Lactation ◽  
Dairy Bulls ◽  
Estimated Breeding Values ◽  
Improved Model ◽  
Efficiency Of Selection

AbstractFunctional longevity of dairy cows has been routinely evaluated in France since 1997 using a survival analysis model. Recently, we proposed a genetic trend validation test that could be used before including national data in an international evaluation of bulls on longevity of their daughters. Its application to the French Holstein data revealed a large overestimation of the genetic trend. It was found that the bias is the result of a change in the baseline hazard rate over time. A new proportional hazards model is proposed which accounts for this change. In the new model, the baseline is described as a stratified, piecewise Weibull hazard function within lactation, i.e. a function of the number of days since the most recent calving. Stratification is within year and parity. Different Weibull hazard functions are used over four periods: 0 to 270 days, 271 to 380 days, 381 days to day when dried, dry period until the next calving. The non-genetic effects included in the model were slightly different from the previous one. In particular the interaction effects between the within herd-year class of production and lactation number × stage of lactation on the one hand and year-season were accounted for. The estimated genetic variance was smaller than with the old model. The new genetic trend is almost flat. An illustration of the efficiency of selection on the estimated breeding values for longevity is presented.

scholarly journals Competing risks’ analysis in cardiovascular disease epidemiology; – Τhe case of ATTICA study (2002-2012)

2020 ◽  
pp. 19-25
Author(s):  
Thomas Tsiampalis ◽  
Demosthenes Panagiotakos
Keyword(s):  
Cardiovascular Disease ◽  
Competing Risks ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Model ◽  
Survival Function ◽  
Gray Model ◽  
Disease Epidemiology ◽  
Hazards Model ◽  
One To One

Background: In studies of all-cause mortality, a one-to-one relation connects the hazard with the survival and as a consequence the regression models which focus on the hazard, such as the proportional hazards model, immediately dictate how the covariates relate to the survival function, as well. However, these two concepts and their one-to-one relation are totally different in the context of competing risks, where the terms of cause-specific hazard and cumulative incidence function appear. Objective: The aim of the present work was to present two of the most popular methods (cause-specific hazard model and Fine & Gray model) through an application on cardiovascular disease epidemiology (CVD), as well as, to narratively review more recent publications, based on either the frequentist, or the Bayesian approach to inference. Methods: A narrative review of the most widely used methods in the competing risks setting was conducted, extended to more recent publications. For the application, our interest lied in modeling the risk of Coronary Heart Disease in the presence of vascular stroke, by using the cause-specific hazard and the Fine & Gray models, two of most commonly encountered approaches. Results-Conclusions: After the implementation of these two approaches in the context of competing risks in CVD epidemiology, it is noted that while the use of the Fine & Gray model includes information about the existence of a competing risk, the interpretation of the results is not as easy as in the case of the cause-specific risk Cox model.

scholarly journals Predictors for depressive symptoms by four types of disability

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sun Wook Jung ◽  
Jin-Ha Yoon ◽  
Wanhyung Lee
Keyword(s):  
Depressive Symptoms ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Depressive Symptomatology ◽  
Cox Proportional Hazards ◽  
Community Dwelling ◽  
Cox Proportional Hazards Model ◽  
Mental Disability ◽  
Multivariate Logistic Regression Model ◽  
Industrial Disaster

AbstractThis study aimed to examine the longitudinal relationship between disability and depressive symptoms, by comparing four types of disability in community-dwelling individuals with disabilities in South Korea. A total of 3347 South Koreans with disabilities from the second wave of the Panel Survey of Employment for the Disabled was utilized. Depressive symptomatology was assessed by whether the participant had experienced depressive symptoms for more than two weeks during the past year. A multivariate logistic regression model was used to calculate the odds ratio (OR) for depressive symptoms, and a Cox proportional hazards model to calculate the hazard ratio (HR) for two-year survival analysis. Persons who acquired mental disability from accident or industrial disaster and persons with congenital physical-internal disability were at higher risk for depressive symptoms. Maintaining employment was found to be an effective way to decrease the risk of depressive symptoms in persons with physical-external disability, sensory/speech disability, or mental disability. In contrast, in physical-internal disability, retaining normal ability to work seemed to be the key to reduce the risk of depressive symptoms. Predictors of depressive symptoms were found to differ depending on the type of disability. Such differences should be reflected in clinical and policy-level interventions to address the specific psychiatric needs of persons with different disabilities.

scholarly journals Aspirin and Risk of Dementia in Patients with Late-Onset Depression: A Population-Based Cohort Study

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Ya-Hsu Yang ◽  
Chih-Chiang Chiu ◽  
Hao-Wei Teng ◽  
Chun-Teng Huang ◽  
Chun-Yu Liu ◽  
...  
Keyword(s):  
Cumulative Incidence ◽  
Propensity Scores ◽  
Nearest Neighbor ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Late Onset ◽  
Population Based ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Incident Dementia

Background. Late onset depression (LOD) often occurs in the context of vascular disease and may be associated with risk of dementia. Aspirin is widely used to reduce the risk of cardiovascular disease and stroke. However, its role in patients with LOD and risk of dementia remains inconclusive. Materials and Methods. A population-based study was conducted using data from National Health Insurance of Taiwan during 1996–2009. Patients fulfil diagnostic criteria for LOD with or without subsequent dementia (incident dementia) and among whom users of aspirin (75 mg daily for at least 6 months) were identified. The time-dependent Cox proportional hazards model was applied for multivariate analyses. Propensity scores with the one-to-one nearest-neighbor matching model were used to select matching patients. Cumulative incidence of incident dementia after diagnosis of LOD was calculated by Kaplan–Meier Method. Results. A total of 6028 (13.4%) and 40,411 (86.6%) patients were defined as, with and without diagnosis of LOD, among whom 2,424 (41.9%) were aspirin users. Patients with LOD had more comorbidities such as cardiovascular diseases, diabetes, and hypertension comparing to those without LOD. Among patients with LOD, aspirin users had lower incidence of subsequent incident dementia than non-users (Hazard Ratio = 0.734, 95% CI 0.641–0.841, p<0.001). After matching aspirin users with non-users by propensity scores-matching method, the cumulative incidence of incident dementia was significantly lower in aspirin users of LOD patients (p=0.022). Conclusions. Aspirin may be associated with a lower risk of incident dementia in patients with LOD. This beneficial effect of aspirin in LOD patients needs validation in prospective clinical trials and our results should be interpreted with caution.

scholarly journals Prognostic Factors in Patients with Rhabdomyosarcoma Using Competing-Risks Analysis: A Study of Cases in the SEER Database

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Didi Han ◽  
Chengzhuo Li ◽  
Xiang Li ◽  
Qiao Huang ◽  
Fengshuo Xu ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Competing Risks ◽  
Cumulative Incidence ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Treatment Strategies ◽  
Incidence Rates ◽  
Seer Database ◽  
Competing Risks Analysis ◽  
Using Data

Background. Rhabdomyosarcoma (RMS) is a rare malignant soft-tissue sarcoma characterized by a poor outcome and unclear prognostic factors. This study applied a competing-risks analysis using data from the Surveillance, Epidemiology, and End Results (SEER) database to RMS patients, with the aim of identifying more accurate prognostic factors. Methods. Data of all patients with RMS during 1986–2015 were extracted from the SEER database. We used the competing-risks approach to calculate the cumulative incidence function (CIF) for death due to rhabdomyosarcoma (DTR) and death from other causes (DOC) at each time point. The Fine–Gray subdistribution proportional-hazards model was then applied in univariate and multivariate analyses to determine how the CIF differs between groups and to identify independent prognostic factors. The potential prognostic factors were analyzed using the competing-risks analysis methods in SAS and R statistical software. Results. This study included 3399 patients with RMS. The 5-year cumulative incidence rates of DTR and DOC after an RMS diagnosis were 39.9% and 8.7%, respectively. The multivariate analysis indicated that age, year of diagnosis, race, primary site, historic stage, tumor size, histology subtype, and surgery status significantly affected the probability of DTR and were independent prognostic factors in patients with RMS. A nomogram model was constructed based on multivariate models for DTR and DOC. The performances of the two models were validated by calibration and discrimination, with C-index values of 0.758 and 0.670, respectively. Conclusions. A prognostic nomogram model based on the competing-risks model has been established for predicting the probability of death in patients with RMS. This validated prognostic model may be useful when choosing treatment strategies and for predicting survival.

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