Descriptive analysis of postmarket surveillance data for hip implants

Purpose: Recent safety issues involving medical devices have highlighted the need for better postmarket surveillance (PMS) evaluation. This article aims to describe and to assess the quality of the PMS data for a medical device and, finally, to provide recommendations to improve the data gathering process. Methods: A descriptive analysis of medical device reports (MDRs) on the use of MRA, a specific type of hip implant replacement submitted to the Food and Drug Administration Manufacturer and User Facility Device Experience database from 1 January 2008 to 31 December 2017. The number of reports was described as the number of MDRs per unique MDR number and stratified by different variables. The quality was assessed by the level of completeness of the collected PMS data. Results: The total number of reports related to MRA was 2377, and the number of MDRs per year ranged between 84 in 2009 and 452 in 2017. Most of the reports were reported by manufacturer Depuy Johnson & Johnson and were reported by a physician. In 44.9% of the reports, the device problem was reported as “Unknown.” When the device problem was known, in the majority of cases, it was related to an implant fracture. The quality of the collected data was assessed as low due to missing information. Conclusion: The underlying data should meet high quality standards to generate more evidence and to ensure a timely signal generation. This case study shows that the completeness and quality of the MDRs can be improved. The authors propose the development of tools to ensure a more dynamic complaint data collection to contribute to this enhancement

Evaluating the Safety Profile of Non-Active Implantable Medical Devices Compared with Medicines

Recent safety issues involving non-active implantable medical devices (NAIMDs) have highlighted the need for better pre-market and post-market evaluation. Some stakeholders have argued that certain features of medicine safety evaluation should also be applied to medical devices. Our objectives were to compare the current processes and methodologies for the assessment of NAIMD safety profiles with those for medicines, identify potential gaps, and make recommendations for the adoption of new methodologies for the ongoing benefit–risk monitoring of these devices throughout their entire life cycle. A literature review served to examine the current tools for the safety evaluation of NAIMDs and those for medicines. We searched MEDLINE using these two categories. We supplemented this search with Google searches using the same key terms used in the MEDLINE search. Using a comparative approach, we summarized the new product design, development cycle (preclinical and clinical phases), and post-market phases for NAIMDs and drugs. We also evaluated and compared the respective processes to integrate and assess safety data during the life cycle of the products, including signal detection, signal management, and subsequent potential regulatory actions. The search identified a gap in NAIMD safety signal generation: no global program exists that collects and analyzes adverse events and product quality issues. Data sources in real-world settings, such as electronic health records, need to be effectively identified and explored as additional sources of safety information, particularly in some areas such as the EU and USA where there are plans to implement the unique device identifier (UDI). The UDI and other initiatives will enable more robust follow-up and assessment of long-term patient outcomes. The safety evaluation system for NAIMDs differs in many ways from those for drugs, but both systems face analogous challenges with respect to monitoring real-world usage. Certain features of the drug safety evaluation process could, if adopted and adapted for NAIMDs, lead to better and more systematic evaluations of the latter

Genetic and environmental influences on Type A Behavior Pattern: Evidence from twins and their parents in the Netherlands Twin Register

OBJECTIVE: There is a dose-response positive relationship between type A behavior (TABP) and cardiovascular disease-related symptoms. Estimates of heritability for TABP from previous studies vary; this might be explained by limitations in the sizes and compositions of the samples. METHODS: This study combines a large sample size, twin and parental, data from males and females, two generations of young adults and older adults, and the use of structural equation modeling (SEM) and full information maximum likelihood (FIML) estimation. To assess TABP, the Jenkins Activity Survey (JAS) was collected from MZ and DZ twins and their parents (n = 1670 twin families). Structural equation modeling is used to evaluate and estimate the effects of additive and nonadditive genetic effects, nonshared environmental effects, and competitive sibling interaction. RESULTS: Forty-five percent of the variance in TABP was the result of genetic factors (28% were additive and 17% were nonadditive). The remaining 55% of the variance was explained by environmental factors not shared by the members of the same family. Competitive sibling interaction effects were not significant. There was no evidence of sex differences either in variances or means. CONCLUSION: Understanding the sources of variance on TABP is important for therapy and prevention. According to the present results, the relevant environmental factors for the development of TABP are not shared by the members of the same family. The genetic portion of the variance is also worth considering for therapeutic purposes. Although the genetic code cannot be altered, its effects on behavior may be modifiable through the treatment of the biological mediators. Copyright © 2006 by the American Psychosomatic Society

Familial Resemblance for Loneliness

Social isolation and loneliness in humans have been associated with physical and psychological morbidity, as well as mortality. This study aimed to assess the etiology of individual differences in feelings of loneliness. The genetic architecture of loneliness was explored in an extended twin-family design including 8,683 twins, siblings and parents from 3,911 families. In addition, 917 spouses of twins participated. The presence of assortative mating, genetic non-additivity, vertical cultural transmission, genotype–environment (GE) correlation and interaction was modeled. GE interaction was considered for several demographic characteristics. Results showed non-random mating for loneliness. We confirmed that loneliness is moderately heritable, with a significant contribution of non-additive genetic variation. There were no effects of vertical cultural transmission. With respect to demographic characteristics, results indicated that marriage, having offspring, more years of education, and a higher number of siblings are associated with lower levels of loneliness. Interestingly, these effects tended to be stronger for men than women. There was little evidence of changes in genetic architecture as a function of these characteristics. We conclude that the genetic architecture of loneliness points to non-additive genetic influences, suggesting it may be a trait that was not neutral to selection in our evolutionary past. Sociodemographic factors that influence the prevalence of loneliness do not affect its genetic architecture

Exercise Participation in Adolescents and Their Parents: Evidence for Genetic and Generation Specific Environmental Effects

Individual differences in adolescent exercise behavior are to a large extent explained by shared environmental factors. The aim of this study was to explore to what extent this shared environment represents effects of cultural transmission of parents to their offspring, generation specific environmental effects or assortative mating. Survey data on leisure-time exercise behavior were available from 3,525 adolescent twins and their siblings (13-18 years) and 3,138 parents from 1,736 families registered at the Netherlands Twin Registry. Data were also available from 5,471 adult twins, their siblings and spouses similar in age to the parents. Exercise participation (No/Yes, using a cut-off criterion of 4 metabolic equivalents and 60 min weekly) was based on questions on type, frequency and duration of exercise. A model to analyze dichotomous data from twins, siblings and parents including differences in variance decomposition across sex and generation was developed. Data from adult twins and their spouses were used to investigate the causes of assortative mating (correlation between spouses = 0.41, due to phenotypic assortment). The heritability of exercise in the adult generation was estimated at 42%. The shared environment for exercise behavior in adolescents mainly represents generation specific shared environmental influences that seem somewhat more important in explaining familial clustering in girls than in boys (52 versus 41%). A small effect of vertical cultural transmission was found for boys only (3%). The remaining familial clustering for exercise behavior was explained by additive genetic factors (42% in boys and 36% in girls). Future studies on adolescent exercise behavior should focus on identification of the generation specific environmental factors. © 2010 Springer Science+Business Media, LLC

Genetic and Environmental Influences on Type A Behavior Pattern: Evidence From Twins and Their Parents in The Netherlands Twin Register

Objective: There is a dose–response positive relationship between type A behavior (TABP) and cardiovascular disease-related symptoms. Estimates of heritability for TABP from previous studies vary; this might be explained by limitations in the sizes and compositions of the samples. Methods: This study combines a large sample size, twin and parental, data from males and females, two generations of young adults and older adults, and the use of structural equation modeling (SEM) and full information maximum likelihood (FIML) estimation. To assess TABP, the Jenkins Activity Survey (JAS) was collected from MZ and DZ twins and their parents (n � 1670 twin families). Structural equation modeling is used to evaluate and estimate the effects of additive and nonadditive genetic effects, nonshared environmental effects, and competitive sibling interaction. Results: Forty-five percent of the variance in TABP was the result of genetic factors (28 % were additive and 17 % were nonadditive). The remaining 55 % of the variance was explained by environmental factors not shared by the members of the same family. Competitive sibling interaction effects were not significant. There was no evidence of sex differences either in variances or means. Conclusion: Understanding the sources of variance on TABP is important for therapy and prevention. According to the present results, the relevant environmental factors for the development of TABP are not shared by the members of the same family. The genetic portion of the variance is also worth considering for therapeutic purposes. Although the genetic code cannot be altered, its effects on behavior may be modifiable through the treatment of the biological mediators. Key words: type A behavior pattern, risk of CHD, JAS, sibling interaction, twin studies, parents–offspring

Genetic Analysis of Anger: Genetic Dominance or Competitive Sibling Interaction

Anger is defined by Spielberger et al. (1983) as an emotional state that consists of feelings of variable intensity, from mild irritation or annoyance to intense fury and rage. The study of the sources o