NONPARAMETRIC ESTIMATION OF BIVARIATE FAILURE TIME ASSOCIATIONS IN THE PRESENCE OF A COMPETING RISK

There has been much research on the study of associations among paired failure times. Most has either assumed time invariance of association or been based on complex measures or estimators. Little has accommodated failures arising amid competing risks. This paper targets the conditional cause specific hazard ratio, a recent modification of the conditional hazard ratio to accommodate competing risks data. Estimation is accomplished by an intuitive, nonparametric method that localizes Kendall’s tau. Time variance is accommodated through a partitioning of space into “bins” between which the strength of association may differ. Inferential procedures are researched, small sample performance evaluated, and methods applied to investigate familial association in dementia onset. The proposed methodology augments existing methodology with an approach that may be more readily applied and interpreted, thus facilitate dissemination of methodology addressing failure time associations into the substantive literatur

Multilevel Latent Class Models with Dirichlet Mixing Distribution

Latent class analysis (LCA) and latent class regression (LCR) are widely used for modeling multivariate categorical outcomes in social sciences and biomedical studies. Standard analyses assume data of different respondents to be mutually independent, excluding application of the methods to familial and other designs in which participants are clustered. In this paper, we develop multilevel latent class model, in which subpopulation mixing probabilities are treated as random effects that vary among clusters according to a common Dirichlet distribution. We apply the Expectation-Maximization (EM) algorithm for model fitting by maximum likelihood (ML). This approach works well, but is computationally intensive when either the number of classes or the cluster size is large. We propose a maximum pairwise likelihood (MPL) approach via a modified EM algorithm for this case. We also show that a simple latent class analysis, combined with robust standard errors, provides another consistent, robust, but less efficient inferential procedure. Simulation studies suggest that the three methods work well in finite samples, and that the MPL estimates often enjoy comparable precision as the ML estimates. We apply our methods to the analysis of comorbid symptoms in the Obsessive Compulsive Disorder study. Our models\u27 random effects structure has more straightforward interpretation than those of competing methods, thus should usefully augment tools available for latent class analysis of multilevel data

MODELING DIFFERENTIATED TREATMENT EFFECTS FOR MULTIPLE OUTCOMES DATA

Multiple outcomes data are commonly used to characterize treatment effects in medical research, for instance, multiple symptoms to characterize potential remission of a psychiatric disorder. Often either a global, i.e. symptom-invariant, treatment effect is evaluated. Such a treatment effect may over generalize the effect across the outcomes. On the other hand individual treatment effects, varying across all outcomes, are complicated to interpret, and their estimation may lose precision relative to a global summary. An effective compromise to summarize the treatment effect may be through patterns of the treatment effects, i.e. differentiated effects. In this paper we propose a two-category model to differentiate treatment effects into two groups. A model fitting algorithm and simulation study are presented, and several methods are developed to analyze heterogeneity presenting in the treatment effects. The method is illustrated using an analysis of schizophrenia symptom data

Relationship between continuity of care and adverse outcomes varies by number of chronic conditions among older adults with diabetes

Background: Continuity of care is a basic tenant of primary care practice. However, the evidence on the importance of continuity of care for older adults with complex conditions is mixed. Objective: To assess the relationship between measurement of continuity of care, number of chronic conditions, and health outcomes. Design: We analyzed data from a cohort of 1,600 US older adults with diabetes and ≥1 other chronic condition in a private Medicare health plan from July 2010 to December 2011. Multivariate regression models were used to examine the association of baseline continuity (the first 6 months) and the composite outcome of any emergency room use or inpatient hospitalization occurring in the following 12-month period. Results: After adjusting for baseline covariates, high known provider continuity (KPC) was associated with an 84% (adjusted odds ratio 0.16; 95% confidence interval 0.09–0.26) reduction in the risk of the composite outcome. High KPC was significantly associated with a lower risk of the composite outcome among individuals with ≥6 conditions. However, the usual provider of care and continuity of care indices were not significantly related with the composite outcome in the overall sample or in those with ≥6 conditions. Conclusion: The relationship between continuity of care and adverse outcomes depends on the measure of continuity of care employed. High morbidity patients are more likely to benefit from continuity of care interventions as measured by the KPC, which measures the proportion of a patient’s visits that are with the same providers over time. Journal of Comorbidity 2016;6(2):65–7

SURROGATE SCREENING MODELS FOR THE LOW PHYSICAL ACTIVITY CRITERION OF FRAILTY

Background and Aims. Low physical activity, one of five criteria in a validated clinical phenotype of frailty, is assessed by a standardized questionnaire on up to 20 leisure time activities. Because of the time demanded to collect the interview data, it has been challenging to translate to studies other than the Cardiovascular Health Study (CHS), for which it was developed. Considering subsets of activities, we identified and evaluated streamlined surrogate assessment methods and compared them to one implemented in the Women’s Health and Aging Study (WHAS). Methods. Using data on men and women ages 65 and older from the CHS, we applied logistic regression models to rank activities by “relative influence” in predicting low physical activity. We considered subsets of the most influential activities as inputs to potential surrogate models (logistic regressions). We evaluated predictive accuracy and predictive validity using the area under receiver operating characteristic curves and assessed criterion validity using proportional hazards models relating frailty status (defined using the surrogate) to mortality. Results. Walking for exercise and moderately strenuous household chores were highly influential for both genders. Women required fewer activities than men for accurate classification. The WHAS model (8 CHS activities) was an effective surrogate, but a surrogate using 6 activities (walking, chores, gardening, general exercise, mowing and golfing) was also highly predictive. Conclusions. We recommend a 6 activity questionnaire to assess physical activity for men and women. If efficiency is essential and the study involves only women, fewer activities can be included

A prospective, population-based study of the role of visual impairment in motor vehicle crashes among older drivers: the SEE study.

PURPOSE: To determine the role of vision and visual attention factors in automobile crash involvement. METHODS: Drivers aged 65 to 84 years were identified during the baseline interview (1993-1995) of the Salisbury Eye Evaluation (SEE) Study. Crash involvement through December 1997 was determined from Maryland State motor vehicle records. Vision tests at baseline included distance acuity at normal and low luminance, contrast sensitivity, glare sensitivity, stereoacuity, and visual fields. Visual attention was evaluated with the Useful Field of View Test (UFOV; Visual Awareness, Chicago, IL). Survival analysis was used to determine the relative risk of a crash as a function of demographic variables, miles driven, vision, and visual attention. RESULTS: One hundred twenty (6.7%) of the 1801 drivers were involved in a crash during the observation interval. Glare sensitivity and binocular field loss were significant predictors of crash involvement (P < 0.05). For those with moderate or better vision (<3 letters for glare sensitivity and <20 points missed for binocular visual fields) increased glare sensitivity or reduced visual fields were, paradoxically, associated with a reduction in crash risk, whereas for those with poorer levels of vision, increased glare sensitivity or reduced visual fields were associated with increased crash risk. Worse UFOV score was associated with increased crash risk. CONCLUSIONS: Glare sensitivity, visual field loss, and UFOV were significant predictors of crash involvement. Acuity, contrast sensitivity, and stereoacuity were not associated with crashes. These results suggest that current vision screening for drivers' licensure, based primarily on visual acuity, may miss important aspects of visual impairment

Association of IGF-I Levels with Muscle Strength and Mobility in Older Women

The functional consequences of the age-associated decline in IGF-I are unknown. We hypothesized that low IGF-I levels in older women would be associated with poor muscle strength and mobility. We assessed this question in a population representative of the full spectrum of health in the community, obtaining serum IGF-I levels from women aged 70–79 yr, enrolled in the Women’s Health and Aging Study I or II. Cross-sectional analyses were performed using 617 women with IGF-I levels drawn within 90 d of measurement of outcomes. After adjustment for age, there was an association between IGF-I and knee extensor strength (P = 0.004), but not anthropometry or other strength measures. We found a positive relationship between IGF-I levels and walking speed for IGF-I levels below 50 μg/liter (P < 0.001), but no relationship above this threshold. A decline in IGF-I level was associated with self-reported difficulty in mobility tasks. All findings were attenuated after multivariate adjustment. In summary, in a study population including frail and healthy older women, low IGF-I levels were associated with poor knee extensor muscle strength, slow walking speed, and self-reported difficulty with mobility tasks. These findings suggest a role for IGF-I in disability as well as a potential target population for interventions to raise IGF-I levels

Role of senescence marker p16INK4a measured in peripheral blood T-lymphocytes in predicting length of hospital stay after coronary artery bypass surgery in older adults

Adults older than 65 years undergo more than 120,000 coronary artery bypass (CAB) procedures each year in the United States. Chronological age alone, though commonly used in prediction models of outcomes after CAB, does not alone reflect variability in aging process; thus, the risk of complications in older adults. We performed a prospective study to evaluate a relationship between senescence marker p16INK4a expression in peripheral blood T-lymphocytes (p16 levels in PBTLs) with aging and with perioperative outcomes in older CAB patients. We included 55 patients age 55 and older, who underwent CAB in Johns Hopkins Hospital between September 1st, 2010 and March 25th, 2013. Demographic, clinical and laboratory data following outline of the Society of Thoracic Surgeons data collection form was collected, and p16 mRNA levels in PBTLs were measured using Taqman® qRT-PCR. Associations between p16 mRNA levels in PBTLs with length of hospital stay, frailty status, p16 protein levels in the aortic and left internal mammary artery tissue, cerebral oxygen saturation, and augmentation index as a measure of vascular stiffness were measured using regression analyses. Length of hospital stay was the primary outcome of interest, and major organ morbidity, mortality, and discharge to a skilled nursing facility were secondary outcomes. In secondary analysis, we evaluated associations between p16 mRNA levels in PBTLs and interleukin-6 levels using regression analyses. Median age of enrolled patients was 63.5 years (range 56-81 years), they were predominantly male (74.55%), of Caucasian descent (85.45%). Median log2(p16 levels in PBTLs) were 4.71 (range 1.10-6.82). P16 levels in PBTLs were significantly associated with chronological age (mean difference 0.06 for each year increase in age, 95% CI 0.01-0.11) and interleukin 6 levels (mean difference 0.09 for each pg/ml increase in IL-6 levels, 95% CI 0.01-0.18). There were no significant associations with frailty status, augmentation index, cerebral oxygenation and p16 protein levels in blood vessels. Increasing p16 levels in PBTLs did not predict length of stay in the hospital (HR 1.10, 95% CI 0.87-1.40) or intensive care unit (HR 1.02, 95% CI 0.79-1.32). Additional evaluation of p16 levels in PBTLs as predictor of perioperative outcomes is required and should include additional markers of immune system aging as well as different outcomes after CAB in addition to length of hospital stay

Operationalizing Frailty in the Atherosclerosis Risk in Communities Study Cohort

Background: Factors that may contribute to the development of frailty in late life have not been widely investigated. The Atherosclerosis Risk in Communities (ARIC) Study cohort presents an opportunity to examine relationships of midlife risk factors with frailty in late life. However, we first present findings on the validation of an established frailty phenotype in this predominantly biracial population of older adults. Methods: Among 6,080 participants, we defined frailty based upon the Cardiovascular Health Study (CHS) criteria incorporating measures of weight loss, exhaustion, slow walking speed, low physical activity, and low grip strength. Criterion and predictive validity of the frailty phenotype were estimated from associations between frailty status and participants' physical and mental health status, physiologic markers, and incident clinical outcomes. Results: A total of 393 (6.5%) participants were classified as frail and 50.4% pre-frail, similar to CHS (6.9% frail, 46.6% pre-frail). In age-adjusted analyses, frailty was concurrently associated with depressive symptoms, low self-rated health, low medication adherence, and clinical biomarker levels (ie, cholesterol, hemoglobin A1c, white blood cell count, C-reactive protein, and hemoglobin). During 1-year follow-up, frailty was associated with falls, low physical ability, fatigue, and mortality. Conclusions: These findings support the validity of the CHS frailty phenotype in the ARIC Study cohort. Future studies in ARIC may elucidate early-life exposures that contribute to late-life frailty