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Background Frail elderly people experience elevated mortality. However, no consensus exists on the definition of frailty, and many frailty scores have been developed. The main aim of this study was to compare the association between 35 frailty scores and incident cardiovascular disease (CVD), incident cancer, and all-cause mortality. Also, we aimed to assess whether frailty scores added predictive value to basic and adjusted models for these outcomes. Methods and findings Through a structured literature search, we identified 35 frailty scores that could be calculated at wave 2 of the English Longitudinal Study of Ageing (ELSA), an observational cohort study. We analysed data from 5,294 participants, 44.9% men, aged 60 years and over. We studied the association between each of the scores and the incidence of CVD, cancer, and all-cause mortality during a 7-year follow-up using Cox proportional hazard models at progressive levels of adjustment. We also examined the added predictive performance of each score on top of basic models using Harrell's C statistic. Using age of the participant as a timescale, in sex-adjusted models, hazard ratios (HRs) (95% confidence intervals) for all-cause mortality ranged from 2.4 (95% CI: 1.7-3.3) to 26.2 (95% CI: 15.4-44.5). In further adjusted models including smoking status and alcohol consumption, HR ranged from 2.3 (95% CI: 1.6-3.1) to 20.2 (95% CI: 11.8-34.5). In fully adjusted models including lifestyle and comorbidity, HR ranged from 0.9 (95% CI: 0.5-1.7) to 8.4 (95% CI: 4.9-14.4). HRs for CVD and cancer incidence in sex-adjusted models ranged from 1.2 (95% CI: 0.5-3.2) to 16.5 (95% CI: 7.8-35.0) and from 0.7 (95% CI: 0.4-1.2) to 2.4 (95% CI: 1.0-5.7), respectively. In sex- and age-adjusted models, all frailty scores showed significant added predictive performance for all-cause mortality, increasing the C statistic by up to 3%. None of the scores significantly improved basic prediction models for CVD or cancer. A source of bias could be the differences in mortality follow-up time compared to CVD/cancer, because the existence of informative censoring cannot be excluded. Conclusion There is high variability in the strength of the association between frailty scores and 7-year all-cause mortality, incident CVD, and cancer. With regard to all-cause mortality, some scores give a modest improvement to the predictive ability. Our results show that certain scores clearly outperform others with regard to three important health outcomes in later life. Finally, we think that despite their limitations, the use of frailty scores to identify the elderly population at risk is still a useful measure, and the choice of a frailty score should balance feasibility with performance., Author(s): Gloria A. Aguayo 1,*, Michel T. Vaillant 2, Anne-Françoise Donneau 3, Anna Schritz 2, Saverio Stranges 4, Laurent Malisoux 1, Anna Chioti 1, Michèle Guillaume 3, Majon Muller 5, [...]

Perception of treatment effect (TE) in cosmetics is multifaceted and influenced by multiple parameters that need to be considered simultaneously when evaluating TE. Here we provide a global approach to predicting TE perception using Random Forest (RF) classifier. Data from three randomized double-blind clinical studies with a total of 50 subjects were used. Different products were applied to each facial cheek of subjects at each visit, and post-application photographs were taken. Nine primary endpoints relating to skin pores were assessed by a specific image analysis algorithm. Twenty judges evaluated the relative pore visibility in all possible pairs of cheek photographs. RF was used to construct a prediction model for TE perception based on the primary endpoints and judge's evaluation. Intra-study product ranking was done using the Bradley-Terry model on mean judges' predicted preference. RF demonstrated overall good accuracy in predicting TE perception. Applying RF technique not only addresses issues of multiplicity, nonlinearity and interactions between multiple criteria but also focuses decision-making on one discrete parameter thereby simplifying interpretability and allowing for more consumer-centered claim substantiation in clinical trials. Abbreviations: RF: Random Forest classifier; FDA: The US Food and Drug Agency; ID: Identifier; MCID: Minimal clinical important difference; Param: Parameter; PGIC: Patients' Global Impression of Change; TE: Treatment effect; TRT: Treatment [ABSTRACT FROM AUTHOR]

There has been increasing interest in recent years in the possibility of increasing the efficiency of clinical trials by using historical controls. There has been a general recognition that in replacing concurrent by historical controls, the potential for bias is serious and requires some down-weighting to the apparent amount of historical information available. However, such approaches have generally assumed that what is required is some modification to the standard inferential model offered by the parallel group trial. In our opinion, the correct starting point that requires modification is a trial in which treatments are allocated to clusters. This immediately shows that the amount of information available is governed not just by the number of historical patients but also by the number of centres and of historical studies. Furthermore, once one accepts that external patients may be used as controls, this raises the issue as to which patients should be used. Thus, abandoning concurrent control has implications for many aspects of design and analysis of trials, including (a) identification, pre-specification and agreement on a suitable historical dataset; (b) an agreed, enforceable and checkable plan for recruiting the experimental arm; (c) a finalised analysis plan prior to beginning the trial and (d) use of a hierarchical model with sufficient complexity. We discuss these issues and suggest approaches to design and analysis making extensive reference to the partially randomised Therapeutic Arthritis Research and Gastrointestinal Event Trial study. We also compare some Bayesian and frequentist approaches and provide some important regulatory considerations. We conclude that effective use of historical data will require considerable circumspection and discipline. [ABSTRACT FROM AUTHOR]

Objective: Frailty is a dynamic state of vulnerability in the elderly. We examined whether individuals with overt diabetes or higher levels of HbA1c or fasting plasma glucose (FG) experience different frailty trajectories with aging.Research Design and Methods: Diabetes, HbA1c, and FG were assessed at baseline, and frailty status was evaluated with a 36-item frailty index every 2 years during a 10-year follow-up among participants from the English Longitudinal Study of Ageing (ELSA). Mixed-effects models with age as time scale were used to assess whether age trajectories of frailty differed as a function of diabetes, HbA1c, and FG.Results: Among 5,377 participants (median age [interquartile range] 70 [65, 77] years, 45% men), 35% were frail at baseline. In a model adjusted for sex, participants with baseline diabetes had an increased frailty index over aging compared with those without diabetes. Similar findings were observed with higher levels of HbA1c, while FG was not associated with frailty. In a model additionally adjusted for income, social class, smoking, alcohol, and hemoglobin, only diabetes was associated with an increased frailty index. Among nonfrail participants at baseline, both diabetes and HbA1c level were associated with a higher increased frailty index over time.Conclusions: People with diabetes or higher HbA1c levels at baseline had a higher frailty level throughout later life. Nonfrail participants with diabetes or higher HbA1c also experienced more rapid deterioration of frailty level with aging. This observation could reflect a role of diabetes complications in frailty trajectories or earlier shared determinants that contribute to diabetes and frailty risk in later life. [ABSTRACT FROM AUTHOR]

Introduction: Frailty is a state of vulnerability in elderly people linked to higher mortality risk. Cardiovascular disease (CVD) is highly prevalent in aged populations and associated with frailty. Thus, frailty state could predict higher risk of CVD. Many frailty scores (FS) have been developed, but none of them is considered the gold standard. We aimed to compare predictive and discriminative ability of an extensive list of FS with regard to incidence of CVD in a sample of the general elderly population in England. We assessed the hypothesis that some FS will have better predictive ability than others, depending on their characteristics. Methods: We performed a prospective analysis of the association between 35 FS in participants free of CVD at baseline wave 2 of the English Longitudinal Study of Ageing (2004-2005), and incident CVD assessed until February 2012. The sample consisted of 4,177 participants (43.0% men). Hazard ratios (HR) and 95% confidence intervals (95% CI) were calculated for each FS using Cox proportional hazards model, adjusted for demographic, lifestyle and comorbidity variables. FS were analyzed on a continuous scale and using original cutoffs. The added predictive ability of FS beyond a basic model consisting of sex and age was studied using Harrel's C statistic (the higher the better). Results: The median follow-up was 5.8 years, the incidence rate of CVD events was 301.2 /10,000 person-years and CVD represented 28% of the total cause of death. The mean age was 70.5 (SD: ±7.8) years. In fully-adjusted models with demographics, lifestyles and comorbidity, HRs ranged from: 1.0 (0.7; 1.6) to 12.7 (5.5; 29.3). Using cutoffs, HRs ranged from 0.7 (0.2; 1.9) to 1.8 (1.3; 2.5). Adjusted for sex and age, delta Harrel's C statistic ranged from -0.8 (-3.4; 1.8) to 3.0 (-0.4; 6.4). The best CVD predictive ability was found for the Frailty Index with 70 variables and the Comprehensive Geriatric Assessment screening FS for continuous and cutoff analyses respectively. In conclusion, there is high variability in the association between different published FS and incident CVD. FS have better predictive ability used as continuous variable. Although most of the analyzed FS have good predictive ability with regard to incident CVD, they do not significantly improve on the discriminative capacity of a basic model. Our results will help to guide clinicians, researchers and public health practitioners in choosing the most informative frailty assessment tool. [ABSTRACT FROM AUTHOR]

Objective: Frailty is a dynamic state of vulnerability in the elderly. We examined whether individuals with overt diabetes or higher levels of HbA 1c or fasting plasma glucose (FG) experience different frailty trajectories with aging., Research Design and Methods: Diabetes, HbA 1c , and FG were assessed at baseline, and frailty status was evaluated with a 36-item frailty index every 2 years during a 10-year follow-up among participants from the English Longitudinal Study of Ageing (ELSA). Mixed-effects models with age as time scale were used to assess whether age trajectories of frailty differed as a function of diabetes, HbA 1c , and FG., Results: Among 5,377 participants (median age [interquartile range] 70 [65, 77] years, 45% men), 35% were frail at baseline. In a model adjusted for sex, participants with baseline diabetes had an increased frailty index over aging compared with those without diabetes. Similar findings were observed with higher levels of HbA 1c , while FG was not associated with frailty. In a model additionally adjusted for income, social class, smoking, alcohol, and hemoglobin, only diabetes was associated with an increased frailty index. Among nonfrail participants at baseline, both diabetes and HbA 1c level were associated with a higher increased frailty index over time., Conclusions: People with diabetes or higher HbA 1c levels at baseline had a higher frailty level throughout later life. Nonfrail participants with diabetes or higher HbA 1c also experienced more rapid deterioration of frailty level with aging. This observation could reflect a role of diabetes complications in frailty trajectories or earlier shared determinants that contribute to diabetes and frailty risk in later life., (© 2019 by the American Diabetes Association.)

Rationale . The value of microRNAs (miRNAs) as biomarkers has been addressed in various clinical contexts. Initial studies suggested that miRNAs, such as the brain-enriched miR-124-3p, might improve outcome prediction after out-of-hospital cardiac arrest. The aim of this study is to determine the prognostic value of miR-122-5p in a large cohort of comatose survivors of out-of-hospital cardiac arrest. Methods . We analyzed 590 patients from the Targeted Temperature Management trial (TTM-trial). Circulating levels of miR-122-5p were measured in serum samples obtained 48 hours after return of spontaneous circulation. The primary end-point was poor neurological outcome at 6 months evaluated by the cerebral performance category score. The secondary end-point was survival at the end of the trial. Results. Forty-eight percent of patients had a poor neurological outcome at 6 months and 43% were dead at the end of the trial. Levels of miR-122-5p were lower in patients with poor neurological outcome compared to patients with good neurological outcome (p<0.001), independently of targeted temperature management regimen. Levels of miR-122-5p were significant univariate predictors of neurological outcome (odds ratios (OR), 95% confidence intervals (CI): 0.71 [0.57-0.88]). In multivariable analyses, miR-122-5p was an independent predictor of neurological outcome and improved the predictive value of a clinical model including miR-124-3p (integrated discrimination improvement of 0.03 [0.02-0.04]). In Cox proportional hazards models, miR-122-5p was a significant predictor of survival at the end of the trial. Conclusion. Circulating levels of miR-122-5p improve the prediction of outcome after out-of-hospital cardiac arrest., Competing Interests: Competing Interests: The authors have declared that no competing interest exists.

Background: In Germany a growing number of community-based support services for people with dementia (PwD) and their caregivers are organized in dementia care networks (DCN), which provide a single point of entry to social facilities and offer personal care and support., Objective: The aim of this study was to describe the health, functional and social characteristics of PwDs enrolled in DCNs throughout Germany because no data are currently available on this aspect., Material and Methods: As part of the multi-center, multi-professional 12-month follow-up study DemNet-D, data on functional and psychological health, sociodemographic and dementia-specific factors and social inclusion were collected in standardized interviews with PwDs living at home., Results: A total of 560 PwDs with an average age of 80 years were enrolled in the study. Of the participants approximately 50 % had Alzheimer's dementia and more than 75 % demonstrated at least a challenging form of behavior. More than half of the participants lived together with a partner or relative. Instrumental activities of daily living (IADLs) were very limited; nevertheless, one in five PwDs showed no long-term care-dependency level. The participants reported having a relatively low feeling of loneliness and a high feeling of social inclusion, depending on the severity of dementia., Conclusion: This is one of the very first studies generating data on PwDs who receive domiciliary care within DCNs in Germany. The results suggest that the regional DCNs make a successful contribution to overcoming the interface problem and can, therefore, contribute to a more stable care situation and better social integration of PwDs.