A novel nonparametric time-dependent precision-recall curve estimator for right-censored survival data.

In order to assess prognostic risk for individuals in precision health research, risk prediction models are increasingly used, in which statistical models are used to estimate the risk of future outcomes based on clinical and nonclinical characteristics. The predictive accuracy of a risk score must be assessed before it can be used in routine clinical decision making, where the receiver operator characteristic curves, precision-recall curves, and their corresponding area under the curves are commonly used metrics to evaluate the discriminatory ability of a continuous risk score. Among these the precision-recall curves have been shown to be more informative when dealing with unbalanced biomarker distribution between classes, which is common in rare event, even though except one, all existing methods are proposed for classic uncensored data. This paper is therefore to propose a novel nonparametric estimation approach for the time-dependent precision-recall curve and its associated area under the curve for right-censored data. A simulation is conducted to show the better finite sample property of the proposed estimator over the existing method and a real-world data from primary biliary cirrhosis trial is used to demonstrate the practical applicability of the proposed estimator.

Correlates of illness uncertainty in cancer survivors and family caregivers: a systematic review and meta-analysis.

PURPOSE: Illness uncertainty is widely recognized as a psychosocial stressor for cancer survivors and their family caregivers. This systematic review and meta-analysis aimed to identify the sociodemographic, physical, and psychosocial correlates that are associated with illness uncertainty in adult cancer survivors and their family caregivers. METHODS: Six scholarly databases were searched. Data synthesis was based on Mishel's Uncertainty in Illness Theory. Person's r was used as the effect size metric in the meta-analysis. Risk of bias was assessed using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. RESULTS: Of 1116 articles, 21 articles met the inclusion criteria. Of 21 reviewed studies, 18 focused on cancer survivors, one focused on family caregivers, and 2 included survivors and family caregivers. Findings identified distinct correlates for illness uncertainty in cancer survivors, including sociodemographic factors (e.g., age, gender, race), stimuli frame (e.g., symptom, family history of cancer), structure providers (e.g., education), coping, and adaptation. Notable effect sizes were observed in the correlations between illness uncertainty and social support, quality of life, depression, and anxiety. Caregivers' illness uncertainty was associated with their race, general health, perception of influence, social support, quality of life, and survivors' prostate-specific antigen levels. Insufficient data precluded examining effect size of correlates of illness uncertainty among family caregivers. CONCLUSION: This is the first systematic review and meta-analysis to summarize the literature on illness uncertainty among adult cancer survivors and family caregivers. Findings contribute to the growing literature on managing illness uncertainty among cancer survivors and family caregivers.

[Randomized Controlled Trial of the Effects of Repetitive Transcranial Magnetic Stimulation and Mirror Therapy on Phantom Limb Pain in Amputees].

Objective: To investigate the effect of repetitive transcranial magnetic stimulation (rTMS) on phantom limb pain (PLP) in amputees, and to compare the therapeutic effect with that of mirror therapy (MT). Methods: The study was designed as a randomized controlled trial. The evaluators were blinded, while the subjects and the therapists were unblinded. Subjects were randomly assigned to either the rTMS group or the MT group with a computer-generated random number table. From June 2018 to December 2020, from out of 45 amputee patients screened for the study, 30 who met the inclusion criteria were recruited for the study. All patients were recruited from the Rehabilitation Medicine Center, West China Hospital, Sichuan University. In the end, 4 patients withdrew from the study and 26 patients (12 in the rTMS group and 14 in the MT group) completed the prescribed treatment and evaluation. The rTMS group was given rTMS (1 Hz, 15 min, 5 d/week) for 2 weeks in addition to conventional rehabilitation therapy, while the MT group received MT (corresponding movements of limbs, 15 min, 5 d/week) for 2 weeks in addition to conventional rehabilitation therapy. PLP was evaluated by the Visual Analogue Scale (VAS) and Douleur Neuropathique 4 Questions (DN-4). Subjects were assessed before treatment ( t 0), immediately after the completion of the treatment ( t 1) and 3 months after the completion of the treatment ( t 2). Results: The mean age of the 26 patients was 39.73±12.64. There were 15 males and 11 females. According to the reported description of the characteristics of the PLP by the patients, the characteristics with the highest incidence were tingling, stabbing, numbing, electric shocks and burning in descending order. There was no significant difference in the incidence of PLP characteristics between the two groups ( P>0.05). The two groups had comparable baseline data, showing no significant difference in VAS and DN-4 between the two groups at t 0 ( P>0.05). At t 1 and t 2, the VAS and DN-4 scores were decreased from those of t 0, showing statistically significant difference in both groups ( P<0.01 for both scores). In the rTMS group, there was no significant difference between VAS and DN-4 scores at t 1 and those at t 2 ( P>0.05). In the MT group, the VAS and DN-4 scores at t 2 were significantly lower than those of t 1 ( P<0.05). There was no statistically significant difference between the rTMS group and MT group in the changes in pain measurements, i.e., VAS and DN-4 scores, before and after the intervention ( P>0.05). The 26 patients who completed the experiment showed no dizziness, headache, or other abnormalities during the study. Conclusion: The results of this study indicate that repetitive transcranial magnetic stimulation could improve PLP in amputees, and the improvement effect was comparable to that of mirror therapy.

Non-Catalytic Subunits Facilitate Quaternary Organization of Plastidic Acetyl-CoA Carboxylase.

Arabidopsis (Arabidopsis thaliana), like most dicotyledonous plants, expresses a multicomponent, heteromeric acetyl-CoA carboxylase (htACCase), which catalyzes the generation of the malonyl-CoA precursor of de novo fatty acid biosynthesis. This enzyme consists of four catalytic subunits: biotin carboxylase (BC), carboxyltransferase (CT)-α, CT-ß, and biotin carboxyl carrier protein (BCCP1 or BCCP2). By coexpressing combinations of components in a bacterial expression system, we demonstrate noncatalytic BADCs facilitate the assembly and activation of BCCP-BADC-BC subcomplexes catalyzing the bicarbonate-dependent hydrolysis of ATP, which is the first half-reaction catalyzed by the htACCase enzyme. Although BADC proteins do not directly impact formation of the CT-αß subcomplex, the BADC-facilitated BCCP-BADC-BC subcomplex can more readily interact with the CT-αß subcomplex to facilitate the generation of malonyl-CoA. The Arabidopsis genome encodes three BADC isoforms (BADC1, BADC2, and BADC3), and BADC2 and BADC3 (rather than BADC1), in combination with BCCP1, best support this quaternary-structural organization and catalytic activation of the htACCase enzyme. Physiological genetic studies validate these attributes as Arabidopsis double mutants singularly expressing BADC2, BADC3, or BADC1 present increasingly greater deleterious impacts on morphological and biochemical phenotypes. Specifically, plants expressing only BADC2 develop normally, plants only expressing BADC3 suffer a stunted root-growth phenotype, and plants expressing only BADC1 are embryo-lethal. The latter phenotype may also be associated with the distinct suborganelle localization of BADC1 in plastids as compared to the localization of the other two BADC homologs. These finding can inspire novel strategies to improve the biological sources of fats and oils for dietary and industrial applications.

Influencing Factors of Inflammatory Bowel Disease-Fatigue: A Path Analysis Model.

BACKGROUND: Fatigue is a common symptom in adults with inflammatory bowel disease (IBD) and is influenced by many physiological, psychological, and situational factors. However, the influencing factors of fatigue associated with IBD have not been evaluated. OBJECTIVE: This study aims to examine factors associated with fatigue during IBD and develop a parsimonious model that describes the influencing factors of fatigue. METHODS: The study was a secondary analysis of cross-sectional data obtained from IBD Partners, an online cohort of adults with the disease, including 12,053 eligible participants. Data were collected using the Patient-Reported Outcomes Measurement Information System short-form scales measuring fatigue, sleep disturbances, pain interference, anxiety, depression, and satisfaction with social roles. Physical activity was measured using a single question. Demographic and clinical variables were collected. Path analysis was computed to identify the direct and indirect effects of situational, physiological, and psychological factors on IBD-fatigue based on the middle range theory of unpleasant symptoms' conceptual framework. RESULTS: Most of the participants were White females. The data best fit a model with situational factors (physical activity and satisfaction with social roles as the mediators). The direct effect of IBD activity, age, sleep disturbances, pain interference, anxiety, and depression on IBD-fatigue was significant. Significant indirect effects were noted on IBD-fatigue from sleep disturbances, pain interference, and depression via physical activity and satisfaction with social roles. DISCUSSION: The study identified two important intervening variables from the tested model. In addition, other symptoms such as sleep, pain, anxiety, and depression are essential and also influence IBD-fatigue.

Illness uncertainty, coping, and quality of life among patients with prostate cancer.

OBJECTIVE: Illness uncertainty is a significant source of psychological distress that affects cancer patients' quality of life (QOL). Mishel's uncertainty in illness theory (UIT) proposes that illness uncertainty influences an individual's use of coping strategies, and directly and indirectly influences their QOL. This study tested the relationships depicted in the adapted UIT in cancer patients. METHODS: This cross-sectional study is a secondary analysis of the baseline data from a randomized clinical trial (N = 263 prostate cancer patients). Patients were diagnosed with localized (64.6%), biochemical recurrent (12.6%), or advanced (22.8%) prostate cancer. Uncertainty, coping (avoidant and active coping strategies), and QOL (physical and mental well-being) were measured using the Mishel's uncertainty of illness scale, Brief COPE, and the Medical Outcomes Study 12-item short form (SF-12), respectively. We used path analysis to achieve the research aim. RESULTS: Patients' illness uncertainty directly, negatively influenced their physical well-being (P < .001) and mental well-being (P < .05). Patients' illness uncertainty was positively related to their avoidant coping strategies (P < .001). Patients' active and avoidant coping strategies influenced their mental well-being (P < .001). Uncertainty also negatively influenced mental well-being through avoidant coping strategies. The model had excellent fit to the data. CONCLUSIONS: Our findings have indicated the potential of improving QOL by decreasing illness uncertainty and reducing avoidant coping strategies. Future research is needed to better understand the complex relationships between illness uncertainty, coping strategies, and domains of QOL among patients with different types of cancer using longitudinal research.

Relative efficiency of using summary versus individual data in random-effects meta-analysis.

Meta-analysis is a statistical methodology for combining information from diverse sources so that a more reliable and efficient conclusion can be reached. It can be conducted by either synthesizing study-level summary statistics or drawing inference from an overarching model for individual participant data (IPD) if available. The latter is often viewed as the "gold standard." For random-effects models, however, it remains not fully understood whether the use of IPD indeed gains efficiency over summary statistics. In this paper, we examine the relative efficiency of the two methods under a general likelihood inference setting. We show theoretically and numerically that summary-statistics-based analysis is at most as efficient as IPD analysis, provided that the random effects follow the Gaussian distribution, and maximum likelihood estimation is used to obtain summary statistics. More specifically, (i) the two methods are equivalent in an asymptotic sense; and (ii) summary-statistics-based inference can incur an appreciable loss of efficiency if the sample sizes are not sufficiently large. Our results are established under the assumption that the between-study heterogeneity parameter remains constant regardless of the sample sizes, which is different from a previous study. Our findings are confirmed by the analyses of simulated data sets and a real-world study of alcohol interventions.

A robust Bayesian mixed effects approach for zero inflated and highly skewed longitudinal count data emanating from the zero inflated discrete Weibull distribution.

This article proposes a Bayesian mixed effects zero inflated discrete Weibull (ZIDW) regression model for zero inflated and highly skewed longitudinal count data, as an alternative to mixed effects regression models that are based on the negative binomial, zero inflated negative binomial, and conventional discrete Weibull (DW) distributions. The mixed effects ZIDW regression model is an extension of a recently introduced model based on the DW distribution and uses the log-link function to specify the relationship between the linear predictors and the median counts. The ZIDW approach offers a more robust characteristic of central tendency, compared to the mean count, when there is skewness in the data. A matrix generalized half-t (MGH-t) prior distribution is specified for the random effects covariance matrix as an alternative to the widely used Wishart prior distribution. The methodology is applied to a longitudinal dataset from an epilepsy clinical trial. In a data contamination simulation study, we show that the mixed effect ZIDW regression model is more robust than the competing mixed effects regression models when the data contain excess zeros or outliers. The performance of the ZIDW regression model is also assessed in a simulation study under the specification of, respectively, the MGH-t and Wishart prior distributions for the random effects covariance matrix. It turns out that the highest posterior density intervals under the MGH-t prior for the fixed effects maintain nominal coverage when the true variability between random slopes over time is small, whereas those under the Wishart prior are generally conservative.

A generalized Bayesian nonlinear mixed-effects regression model for zero-inflated longitudinal count data in tuberculosis trials.

In this paper, we investigate Bayesian generalized nonlinear mixed-effects (NLME) regression models for zero-inflated longitudinal count data. The methodology is motivated by and applied to colony forming unit (CFU) counts in extended bactericidal activity tuberculosis (TB) trials. Furthermore, for model comparisons, we present a generalized method for calculating the marginal likelihoods required to determine Bayes factors. A simulation study shows that the proposed zero-inflated negative binomial regression model has good accuracy, precision, and credibility interval coverage. In contrast, conventional normal NLME regression models applied to log-transformed count data, which handle zero counts as left censored values, may yield credibility intervals that undercover the true bactericidal activity of anti-TB drugs. We therefore recommend that zero-inflated NLME regression models should be fitted to CFU count on the original scale, as an alternative to conventional normal NLME regression models on the logarithmic scale.

Nonlinear Dynamics of Binge Drinking among U.S. High School Students in Grade 12: Cusp Catastrophe Modeling of National Survey Data.

Findings from cusp catastrophe modeling of binge drinking among college students in the United States (U.S.) and high school students in other countries (i.e., Japan) have advanced our understanding of alcohol abuse. No reported study has used the same method to investigate binge drinking among U.S. high school students, a high-risk population for alcohol abuse. In this study, we analyzed data for 12th graders (n = 1122) from the 2015 Monitoring the Future (MFT) Study with cusp catastrophe models. Guided by Kahneman's dual-system theory that integrates the theories of reasoned action and planned behavior, perceived alcohol harm (0-3, larger indicating less harm) was modeled as asymmetry variable (knowledge and beliefs), and drinking in social settings (contextual factors, 0 = no and 4 = always) as bifurcation variable to predict binge drinking in the past two weeks (0, 1, 2, 3 or more times). Analytical results indicated that a cusp model, depending on the method for parameter estimation could explain 36-88% of the variance in binge drinking while a linear model only explained up to 14%. Results from the indirect cusp modeling methods indicated that perceived alcohol harm and drinking in social settings both significantly predicted binge drinking. However, the estimated cusp point varied depending on the method for parameter estimation. In conclusion, the dynamics of binge drinking among U.S. high school students are nonlinear and discrete. Knowledge-based interventions to prevent binge drinking need to emphasize social and contextual factors that may trigger sudden behavior change to achieve greater intervention effect. To advance cusp catastrophe modeling, further research is needed to improve the method for parameter estimation.

Quantum changes in self-efficacy and condom-use intention among youth: A chained cusp catastrophe model.

INTRODUCTION: The complex relationships among HIV knowledge, condom-use skills, self-efficacy, peer influence and intention to use condoms have been rigorously investigated. However, studies guided by a linear behavior change model often explain only a limited amount of variances. This study aims to advance our understanding of the relationships through a nonlinear quantum change paradigm. METHODS: Data (n = 1970, 40.61% male, mean age 16.94 ±â€¯0.74) from a behavioral intervention program among high school students in the Bahamas were analyzed with a chained cusp catastrophe model in two steps. In the first step, self-efficacy was analyzed as the outcome with HIV knowledge/condom-use skills as asymmetry variables and peer influence as bifurcation variable. In the second step, condom-use intention was analyzed as the outcome while self-efficacy (outcome in the first step) was used as bifurcation variable allowing peer influence as bifurcation, and HIV knowledge/condom-use skills were included as asymmetry. Cusp modeling analysis was conducted along with equivalent linear models. RESULTS: The cusp model performed better than the linear and logistic models. Cusp modeling analyses revealed that peer influence significantly bifurcated the relationships between HIV knowledge/condom-use skills and self-efficacy; while both self-efficacy and peer influence significantly bifurcated the relationship between HIV knowledge/condom-use skills and condom-use intention. CONCLUSION: Our findings support the central role of self-efficacy and peer influence as two chains in bridging the complex quantum relationships between HIV knowledge/condom-use skills and condom-use intention among adolescents. The nonlinear cusp catastrophe modeling provided a new method to advance HIV behavioral research.

Robust Bayesian nonlinear mixed-effects modeling of time to positivity in tuberculosis trials.

Early phase 2 tuberculosis (TB) trials are conducted to characterize the early bactericidal activity (EBA) of anti-TB drugs. The EBA of anti-TB drugs has conventionally been calculated as the rate of decline in colony forming unit (CFU) count during the first 14 days of treatment. The measurement of CFU count, however, is expensive and prone to contamination. Alternatively to CFU count, time to positivity (TTP), which is a potential biomarker for long-term efficacy of anti-TB drugs, can be used to characterize EBA. The current Bayesian nonlinear mixed-effects (NLME) regression model for TTP data, however, lacks robustness to gross outliers that often are present in the data. The conventional way of handling such outliers involves their identification by visual inspection and subsequent exclusion from the analysis. However, this process can be questioned because of its subjective nature. For this reason, we fitted robust versions of the Bayesian nonlinear mixed-effects regression model to a wide range of TTP datasets. The performance of the explored models was assessed through model comparison statistics and a simulation study. We conclude that fitting a robust model to TTP data obviates the need for explicit identification and subsequent "deletion" of outliers but ensures that gross outliers exert no undue influence on model fits. We recommend that the current practice of fitting conventional normal theory models be abandoned in favor of fitting robust models to TTP data.

Probabilistic Discrete Event Systems Modeling of Nonlinear Transitions between Electronic and Combustible Cigarette Smoking with the 2014 National Youth Tobacco Survey Data.

A growing number of young people smoke electronic (e-) cigarettes, presenting an emerging challenge to tobacco control. Analyses are needed to better understand the dynamics of mutual transitions between e-cigarette and conventional combustible (c-) cigarette smoking to advance evidence-based tobacco control. In this study we modeled the nonlinear dynamics of c- and e-cigarette smoking behavior transitions using the 2014 National Youth Tobacco Survey (NYTS) data. A model with five Markov-Chain transition stages linked by 21 transitional paths/probabilities was constructed, guided by the probabilistic discrete event systems (PDES) theory. The Moore-Penrose generalized inverse matrix was used to solve the proposed model that was under-determined. The estimated transitional probabilities indicate that each year, 7-8% of middle school students and 11% of high school students initiated smoking. E-cigarettes were more attractive then c-cigarettes but the behavior of smoking c-cigarettes was more stable than that of smoking e-cigarettes. Female students were more likely to remain as quitters or ex-smokers while male students were more likely to relapse and smoke again. Findings of this nonlinear dynamics modelling indicate potential increases in both e- and c-cigarette smoking among U.S. middle and high school students if no further measures are taken. The PDES-based approach is effective to investigate the nonlinear dynamics of mutual transitions of two risk behaviors in adolescents with one wave cross-sectional data.

Perceptions about interpersonal relationships and school environment among middle school students with asthma.

OBJECTIVES: To examine interpersonal relationships involving peers and teachers and perceptions about school environment among middle school students with asthma in comparison to their healthy counterparts. The study also assesses asthma prevalence in a large sample of middle school students representing different geographic locations. METHODS: Cross-sectional data were collected from 1059 middle school students in grades 6-8 enrolled in schools in a northeastern region of the United States. Students reported their chronic health conditions including asthma and completed questionnaires measuring perceptions about their relationships with peers and teachers as well as school environment. Analyses of covariance (ANCOVAs) were used to compare students with asthma and their healthy counterparts in the study variables. RESULTS: Asthma was reported by 16.5% of the sample (n = 169). The rate was higher among minority students (23%) than their white counterparts (15%). Greater proportion of urban students (28%) reported asthma than rural (18%) and suburban (14%) students. Students with asthma reported significantly poorer relationships with peers (B = -1.74, p <.001) and teachers (B = -1.41, p =.009), and their perceptions about overall school environment (B = -1.30, p =.009) were also lower than their healthy counterparts. Race showed no significant effects on school factors. CONCLUSION: Overall asthma prevalence was substantially higher than the national average of adolescent asthma, particularly those residing in the urban area. Poor perceptions of interpersonal relationships with peers and teachers among students with asthma may indicate compromised quality of life. Suboptimal interpersonal relationships and school environment need to be identified and adequately addressed, given their implications for asthma management at the school setting among middle school students.

Linking cognition and frailty in middle and old age: metabolic syndrome matters.

OBJECTIVES: This study examined whether metabolic syndrome (MetS) would moderate the association of cognition with frailty in middle and old age. METHODS: A cross-sectional design was used. Six hundred and ninety participants (age ≥ 50 years) from an on-going national survey were included in the study. Confirmatory factor analysis was applied to determine latent variables of executive function (EF), episodic memory (EM), and MetS based on relevant measurements. Frailty was defined using a modified form of Fried's criteria. RESULTS: Applying structural equation modeling, having MetS significantly increased the likelihood of being frail. Better performance on EM tasks, but not EF, was significantly associated with lower likelihood of MetS. Worse performance on EF, but not EM, significantly increased the likelihood of being frail. There was a significant interacting effect between MetS and EF, but not EM, on frailty. Further contrast analysis indicated that having MetS strengthened the negative association between EF and frailty. CONCLUSION: Metabolic syndrome moderates the relationship between EF and frailty. A prospecitve study is needed to validate such relationships before developing interventions targeting the prevention or treatment of EF and frailty in individuals with MetS.

Self-management intervention for long-term indwelling urinary catheter users: randomized clinical trial.

BACKGROUND: People using long-term indwelling urinary catheters experience multiple recurrent catheter problems. Self-management approaches are needed to avoid catheter-related problems. OBJECTIVES: The aim was to determine effectiveness of a self-management intervention in prevention of adverse outcomes (catheter-related urinary tract infection, blockage, and accidental dislodgement). Healthcare treatment associated with the adverse outcomes and catheter-related quality of life was also studied. METHODS: A randomized clinical trial was conducted. The intervention involved learning catheter-related self-monitoring and self-management skills during home visits by a study nurse (twice during the first month and at 4 months-with a phone call at 2 months). The control group received usual care. Data were collected during an initial face-to-face home interview followed by bimonthly phone interviews. A total of 202 adult long-term urinary catheter users participated. Participants were randomized to treatment or control groups following collection of baseline data. Generalized estimating equations were used for the analysis of treatment effect. RESULTS: In the intervention group, there was a significant decrease in reported blockage in the first 6 months (p = .02), but the effect did not persist. There were no significant effects for catheter-related urinary tract infection or dislodgment. Comparison of baseline rates of adverse outcomes with subsequent periods suggested that both groups improved over 12 months. DISCUSSION: A simple-to-use catheter problems calendar and the bimonthly interviews might have functioned as a modest self-monitoring intervention for persons in both groups. A simplified intervention using a self-monitoring calendar is suggested-with optimal and consistent fluid intake likely to add value.

Frequency of mentally stimulating activities modifies the relationship between cardiovascular reactivity and executive function in old age.

OBJECTIVES: Recent evidence suggests that younger and middle-age adults who show greater cardiovascular reactivity (CVR) to acute mental stress demonstrate better reasoning and memory skills. The purpose of this study was to examine whether older adults would exhibit a similar positive association between CVR and executive function and whether regular engagement in mentally stimulating activities (MSA) would moderate this association. DESIGN: Secondary cross-sectional analysis. SETTING: Three clinical research centers in the Midwest and on the West Coast and East Coast. PARTICIPANTS: A total of 487 older adults participating in an ongoing national survey. MEASUREMENTS: Heart rate (HR) and low-frequency (LF) and high-frequency (HF) domains of heart rate variability (HRV) were measured at baseline and in response to standard mental stress tasks (Stroop color word task and mental arithmetic). Executive function was measured separately from the stress tasks by using five neuropsychological tests. MSA was measured by self-reported frequency of six common MSA. RESULTS: Higher HR reactivity was associated with better executive function after controlling for demographic and health characteristics and baseline HR, and the interaction between HR reactivity and MSA was significant for executive function. Higher LF-HRV reactivity was also associated with executive function, but subsequent analyses indicated that frequency of MSA was the strongest predictor of executive function in models that included LF-HRV or HF-HRV. CONCLUSIONS: Higher HR reactivity to acute psychological stress is related to better executive function in older adults. For those with lower HR reactivity, engaging frequently in MSA produced compensatory benefits for executive function.

Fatigability disrupts cognitive processes' regulation of inflammatory reactivity in old age.

OBJECTIVE: High fatigability, a dysfunctional adaption to fatigue, may lead to difficulties performing otherwise regularly encountered cognitive activities and may be related to pro-inflammatory reactivity. The purpose of the study was to investigate the effect of fatigability on cognitive processes and inflammatory response after an acute cognitive stress task in older adults. METHODS: In an observational stress reactivity study conducted in a light- and temperature-controlled laboratory, we measured IL-6, self-reported acute fatigue, and frontally oriented cognitive processes in 55 community-dwelling individuals aged 75 years or older as part of a demanding set of cognitive tasks intended to induce stress. RESULTS: Subjects were classified into groups of low and high fatigability based on cluster analysis of their self-report acute fatigue before and after the cognitive tasks. The two clusters were comparable on levels of baseline IL-6 and cognitive processes; however, the high fatigability cluster had significantly higher levels of IL-6 response than the low fatigability cluster. After controlling for multiple covariates, fatigability moderated the relationship between speed of processing and IL-6 reactivity. Further exploratory analyses indicated significant adverse associations between speed of processing and attention and IL-6 reactivity in the group with low but not high fatigability. CONCLUSION: Although observational, these data are consistent with the notion that pro-inflammatory states in older adults might be reduced by improvements in cognitive processes. Because fatigability was associated with increased acute inflammatory response and disrupted the normal stress regulation provided by the cognitive processes, future randomized studies might examine whether fatigability alleviation reduces IL-6.

Cusp catastrophe model: a nonlinear model for health outcomes in nursing research.

BACKGROUND: Although health outcomes may have fundamentally nonlinear relationships with relevant behavioral, psychological, cognitively, or biological predictors, most analytical models assume a linear relationship. Furthermore, some health outcomes may have multimodal distributions, but most statistical models in common use assume a unimodal, normal distribution. Suitable nonlinear models should be developed to explain health outcomes. OBJECTIVE: The aim of this study is to provide an overview of a cusp catastrophe model for examining health outcomes and to present an example using grip strength as an indicator of a physical functioning outcome to illustrate how the technique may be used. Results using linear regression, nonlinear logistic model, and the cusp catastrophe model were compared. METHODS: Data from 935 participants from the Survey of Midlife Development in the United States (MIDUS) were analyzed. The outcome was grip strength; executive function and the inflammatory cytokine interleukin-6 were predictor variables. RESULTS: Grip strength was bimodally distributed. On the basis of fit and model selection criteria, the cusp model was superior to the linear model and the nonlinear logistic regression model. The cusp catastrophe model identified interleukin-6 as a significant asymmetry factor and executive function as a significant bifurcation factor. CONCLUSION: The cusp catastrophe model is a useful alternative for explaining the nonlinear relationships commonly seen between health outcome and its predictors. Considerations for the use of cusp catastrophe model in nursing research are discussed and recommended.

Time-dependent receiver operating characteristic curve estimator for correlated right-censored time-to-event data.

In clinical trials, evaluating the accuracy of risk scores (markers) derived from prognostic models for prediction of survival outcomes is of major concern. The time-dependent receiver operating characteristic curve and the corresponding area under the receiver operating characteristic curve are appealing measures to evaluate the predictive accuracy. Several estimation methods have been proposed in the context of classical right-censored data which assumes the event time of individuals are independent. In many applications, however, this may not hold true if, for example, individuals belong to clusters or experience recurrent events. Estimates may be biased if this correlated nature is not taken into account. This paper is then aimed to fill this knowledge gap to introduce a time-dependent receiver operating characteristic curve and the corresponding area under the receiver operating characteristic curve estimation method for right-censored data that take the correlated nature into account. In the proposed method, the unknown status of censored subjects is imputed using conditional survival functions given the marker and frailty of the subjects. An extensive simulation study is conducted to evaluate and demonstrate the finite sample performance of the proposed method. Finally, the proposed method is illustrated using two real-world examples of lung cancer and kidney disease.