Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 11 de 11
Filtrar
Más filtros










Base de datos
Intervalo de año de publicación
1.
Artículo en Inglés | MEDLINE | ID: mdl-32389555

RESUMEN

OBJECTIVE: To explore the implementation strategy of a recombinant zoster vaccine (RZV) clinical decision support (CDS) intervention in community pharmacy workflow to increase second-dose vaccination rates. SETTING: The level of analysis was the unit (e.g., pharmacy). The participants were selected from across approximately 2200 pharmacies in 37 states on the basis of criteria believed to affect implementation success (e.g., size, location) using a sampling matrix. PRACTICE DESCRIPTION: Large supermarket pharmacy chain. PRACTICE INNOVATION: Vaccine-based CDS intervention in community pharmacy workflow. EVALUATION: A mixed-methods contextual inquiry approach explored the implementation of a new RZV CDS workflow intervention. Data collection involved key informant, semistructured interviews and an electronic, Web-based survey. The survey was based on a validated instrument and was made available to all pharmacists nationwide within the study organization to assess views of the implementation's appropriateness, acceptability, and feasibility during early implementation. Afterward, a series of semistructured, in-depth interviews were conducted until a point of saturation was reached. The interview guide was based on selected constructs of the Consolidated Framework for Implementation Research. RESULTS: A total of 1128 survey responses were collected. Survey respondents agreed or strongly agreed that the implementation was acceptable (78.34%), appropriate (79.92%), and feasible (80.53%). Twelve pharmacist participants were interviewed via telephone. Five themes emerged from the interviews, revealing facilitators and barriers that affected implementation of the intervention: intervention characteristics, outer setting, inner setting, characteristics of individuals, and process. CONCLUSION: The implementation of the RZV CDS "nudge" intervention was welcomed, suitable, and operable in the community pharmacy setting to meet the needs of the organization, employees, and patients. The contextual factors identified during the implementation process of this CDS intervention in a community pharmacy setting may be used in scaling this and future CDS interventions for public health initiatives aimed at pharmacists in this setting.

3.
Addict Behav ; 102: 106190, 2020 03.
Artículo en Inglés | MEDLINE | ID: mdl-31704436

RESUMEN

Research indicates that increased cumulative exposure (duration of administration and strength of dose) is associated with long-term opioid use. Because dentists represent some of the highest opioid prescribing medical professionals in the US, dental practices offer a critical site for intervention. The current study used a randomized clinical trial design to examine the efficacy of an opioid misuse prevention program (OMPP), presented as a brief intervention immediately prior to dental extraction surgery. The OMPP provided educational counseling about risks and appropriate use of opioid medication, as well as 28 tablets of ibuprofen (200 mg) and 28 tablets of acetaminophen (500 mg) for weaning off opioid medication. This was compared with a Treatment as Usual (TAU) control condition. Participants were individuals presenting for surgery who were eligible for opioid medication (N = 76). Follow up assessment was conducted at 1 week following surgery, with 4 individuals refusing follow up or not prescribed opioid. Intent to treat analysis indicated a non-significant treatment group effect (N = 72, Beta = 0.16, p = .0835), such that the OMPP group self-reported less opioid use (in morphine milligram equivalents, MMEs) than the TAU group (37.94 vs. 47.79, effect size d = 0.42). Sensitivity analysis, excluding individuals with complications following surgery (n = 6) indicated a significant treatment group effect (N = 66, Beta = 0.24, p = .0259), such that the OMPP group self-reported significantly less MMEs than the TAU group (29.74 vs. 43.59, effect size d = 0.56). Results indicate that a 10-minute intervention and provision of non-narcotic pain medications may reduce the amount of self-administered opioid medication following dental surgery.

4.
Genet Epidemiol ; 43(8): 952-965, 2019 12.
Artículo en Inglés | MEDLINE | ID: mdl-31502722

RESUMEN

The importance to integrate survival analysis into genetics and genomics is widely recognized, but only a small number of statisticians have produced relevant work toward this study direction. For unrelated population data, functional regression (FR) models have been developed to test for association between a quantitative/dichotomous/survival trait and genetic variants in a gene region. In major gene association analysis, these models have higher power than sequence kernel association tests. In this paper, we extend this approach to analyze censored traits for family data or related samples using FR based mixed effect Cox models (FamCoxME). The FamCoxME model effect of major gene as fixed mean via functional data analysis techniques, the local gene or polygene variations or both as random, and the correlation of pedigree members by kinship coefficients or genetic relationship matrix or both. The association between the censored trait and the major gene is tested by likelihood ratio tests (FamCoxME FR LRT). Simulation results indicate that the LRT control the type I error rates accurately/conservatively and have good power levels when both local gene or polygene variations are modeled. The proposed methods were applied to analyze a breast cancer data set from the Consortium of Investigators of Modifiers of BRCA1 and BRCA2 (CIMBA). The FamCoxME provides a new tool for gene-based analysis of family-based studies or related samples.


Asunto(s)
Estudios de Asociación Genética , Modelos Genéticos , Análisis de Supervivencia , Simulación por Computador , Variación Genética , Humanos , Linaje , Fenotipo , Modelos de Riesgos Proporcionales , Análisis de Regresión
5.
Ophthalmology ; 126(11): 1541-1548, 2019 11.
Artículo en Inglés | MEDLINE | ID: mdl-31358387

RESUMEN

PURPOSE: To assess whether genotypes at 2 major loci associated with age-related macular degeneration (AMD), complement factor H (CFH), or age-related maculopathy susceptibility 2 (ARMS2), modify the response to oral nutrients for the treatment of AMD in the Age-Related Eye Disease Study 2 (AREDS2). DESIGN: Post hoc analysis of a randomized trial. PARTICIPANTS: White AREDS2 participants. METHODS: AREDS2 participants (n = 4203) with bilateral large drusen or late AMD in 1 eye were assigned randomly to lutein and zeaxanthin, omega-3 fatty acids, both, or placebo, and most also received the AREDS supplements. A secondary randomization assessed modified AREDS supplements in 4 treatment arms: lower zinc dosage, omission of ß-carotene, both, or no modification. To evaluate the progression to late AMD, fundus photographs were obtained at baseline and annual study visits, and history of treatment for late AMD was obtained at study visits and 6-month interim telephone calls. Participants were genotyped for the single-nucleotide polymorphisms rs1061170 in CFH and rs10490924 in ARMS2. Bivariate frailty models using both eyes were conducted, including a gene-supplement interaction term and adjusting for age, gender, level of education, and smoking status. The main treatment effects, as well as the direct comparison between lutein plus zeaxanthin and ß-carotene, were assessed for genotype interaction. MAIN OUTCOME MEASURES: The interaction between genotype and the response to AREDS2 supplements regarding progression to late AMD, any geographic atrophy (GA), and neovascular AMD. RESULTS: Complete data were available for 2775 eyes without baseline late AMD (1684 participants). The participants (mean age ± standard deviation, 72.1±7.7 years; 58.5% female) were followed up for a median of 5 years. The ARMS2 risk allele was associated significantly with progression to late AMD and neovascular AMD (P = 2.40 × 10-5 and P = 0.002, respectively), but not any GA (P = 0.097). The CFH risk allele was not associated with AMD progression. Genotype did not modify significantly the response to any of the AREDS2 supplements. CONCLUSIONS: CFH and ARMS2 risk alleles do not modify the response to the AREDS2 nutrient supplements with respect to the progression to late AMD (GA and neovascular AMD).


Asunto(s)
Carotenoides/administración & dosificación , Ácidos Grasos Omega-3/administración & dosificación , Degeneración Macular/tratamiento farmacológico , Degeneración Macular/genética , Proteínas/genética , Compuestos de Zinc/administración & dosificación , Anciano , Anciano de 80 o más Años , Factor H de Complemento/genética , Suplementos Dietéticos , Progresión de la Enfermedad , Método Doble Ciego , Combinación de Medicamentos , Femenino , Estudios de Asociación Genética , Estudio de Asociación del Genoma Completo , Técnicas de Genotipaje , Humanos , Luteína/administración & dosificación , Degeneración Macular/diagnóstico , Masculino , Reacción en Cadena de la Polimerasa , Polimorfismo de Nucleótido Simple , Agudeza Visual/fisiología , Zeaxantinas/administración & dosificación , beta Caroteno/administración & dosificación
6.
Genet Epidemiol ; 43(2): 189-206, 2019 03.
Artículo en Inglés | MEDLINE | ID: mdl-30537345

RESUMEN

We develop linear mixed models (LMMs) and functional linear mixed models (FLMMs) for gene-based tests of association between a quantitative trait and genetic variants on pedigrees. The effects of a major gene are modeled as a fixed effect, the contributions of polygenes are modeled as a random effect, and the correlations of pedigree members are modeled via inbreeding/kinship coefficients. F -statistics and χ 2 likelihood ratio test (LRT) statistics based on the LMMs and FLMMs are constructed to test for association. We show empirically that the F -distributed statistics provide a good control of the type I error rate. The F -test statistics of the LMMs have similar or higher power than the FLMMs, kernel-based famSKAT (family-based sequence kernel association test), and burden test famBT (family-based burden test). The F -statistics of the FLMMs perform well when analyzing a combination of rare and common variants. For small samples, the LRT statistics of the FLMMs control the type I error rate well at the nominal levels α = 0.01 and 0.05 . For moderate/large samples, the LRT statistics of the FLMMs control the type I error rates well. The LRT statistics of the LMMs can lead to inflated type I error rates. The proposed models are useful in whole genome and whole exome association studies of complex traits.


Asunto(s)
Estudios de Asociación Genética , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Modelos Genéticos , Carácter Cuantitativo Heredable , Simulación por Computador , Familia , Humanos , Modelos Lineales , Miopía/genética
7.
Am J Clin Nutr ; 107(3): 345-354, 2018 03 01.
Artículo en Inglés | MEDLINE | ID: mdl-29566195

RESUMEN

Background: Formate is an important metabolite that serves as a donor of one-carbon groups to the intracellular tetrahydrofolate pool. However, little is known of its circulating concentrations or of their determinants. Objective: This study aimed to define formate concentrations and their determinants in a healthy young population. Design: Serum formate was measured in 1701 participants from the Trinity Student Study. The participants were men and women, aged 18 to 28 y, enrolled at Trinity College, Dublin. Formate concentrations were compared with other one-carbon metabolites, vitamin status, potential formate precursors, genetic polymorphisms, and lifestyle factors. Results: Serum formate concentrations ranged from 8.7 to 96.5 µM, with a mean of 25.9 µM. Formate concentrations were significantly higher in women than in men; oral contraceptive use did not further affect them. There was no effect of smoking or of alcohol ingestion, but the TT genotype of the methylenetetrahydrofolate reductase (MTHFR) 677C→T (rs1801133) polymorphism was associated with a significantly decreased formate concentration. Formate was positively associated with potential metabolic precursors (serine, methionine, tryptophan, choline) but not with glycine. Formate concentrations were positively related to serum folate and negatively related to serum vitamin B-12. Conclusions: Formate concentrations were sensitive to the concentrations of metabolic precursors. In view of the increased susceptibility of women with the TT genotype of MTHFR to give birth to infants with neural tube defects as well as the effectiveness of formate supplementation in decreasing the incidence of folate-resistant neural tube defects in susceptible mice, it will be important to understand how this genotype decreases the serum formate concentration. This trial was registered at www.clinicaltrials.gov as NCT03305900.


Asunto(s)
Formiatos/sangre , Estilo de Vida , Metilenotetrahidrofolato Reductasa (NADPH2)/genética , Adolescente , Adulto , Colina/sangre , Estudios Transversales , Femenino , Técnicas de Genotipaje , Humanos , Incidencia , Masculino , Metionina/sangre , Polimorfismo de Nucleótido Simple , Serina/sangre , Triptófano/sangre , Adulto Joven
8.
Eur J Hum Genet ; 25(3): 350-359, 2017 02.
Artículo en Inglés | MEDLINE | ID: mdl-28000696

RESUMEN

To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data.


Asunto(s)
Pleiotropía Genética , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Modelos Genéticos , Análisis de Secuencia de ADN/métodos , Reacciones Falso Positivas , Humanos , Modelos Lineales , Análisis Multivariante , Carácter Cuantitativo Heredable
9.
Genet Epidemiol ; 41(1): 18-34, 2017 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-27917525

RESUMEN

In this paper, extensive simulations are performed to compare two statistical methods to analyze multiple correlated quantitative phenotypes: (1) approximate F-distributed tests of multivariate functional linear models (MFLM) and additive models of multivariate analysis of variance (MANOVA), and (2) Gene Association with Multiple Traits (GAMuT) for association testing of high-dimensional genotype data. It is shown that approximate F-distributed tests of MFLM and MANOVA have higher power and are more appropriate for major gene association analysis (i.e., scenarios in which some genetic variants have relatively large effects on the phenotypes); GAMuT has higher power and is more appropriate for analyzing polygenic effects (i.e., effects from a large number of genetic variants each of which contributes a small amount to the phenotypes). MFLM and MANOVA are very flexible and can be used to perform association analysis for (i) rare variants, (ii) common variants, and (iii) a combination of rare and common variants. Although GAMuT was designed to analyze rare variants, it can be applied to analyze a combination of rare and common variants and it performs well when (1) the number of genetic variants is large and (2) each variant contributes a small amount to the phenotypes (i.e., polygenes). MFLM and MANOVA are fixed effect models that perform well for major gene association analysis. GAMuT can be viewed as an extension of sequence kernel association tests (SKAT). Both GAMuT and SKAT are more appropriate for analyzing polygenic effects and they perform well not only in the rare variant case, but also in the case of a combination of rare and common variants. Data analyses of European cohorts and the Trinity Students Study are presented to compare the performance of the two methods.


Asunto(s)
Estudios de Asociación Genética , Marcadores Genéticos/genética , Variación Genética/genética , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Lípidos/genética , Modelos Genéticos , Herencia Multifactorial/genética , Análisis de Varianza , Genoma Humano , Genotipo , Humanos , Lípidos/análisis , Fenotipo , Sitios de Carácter Cuantitativo
10.
Genet Epidemiol ; 40(8): 702-721, 2016 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-27374056

RESUMEN

In association studies of complex traits, fixed-effect regression models are usually used to test for association between traits and major gene loci. In recent years, variance-component tests based on mixed models were developed for region-based genetic variant association tests. In the mixed models, the association is tested by a null hypothesis of zero variance via a sequence kernel association test (SKAT), its optimal unified test (SKAT-O), and a combined sum test of rare and common variant effect (SKAT-C). Although there are some comparison studies to evaluate the performance of mixed and fixed models, there is no systematic analysis to determine when the mixed models perform better and when the fixed models perform better. Here we evaluated, based on extensive simulations, the performance of the fixed and mixed model statistics, using genetic variants located in 3, 6, 9, 12, and 15 kb simulated regions. We compared the performance of three models: (i) mixed models that lead to SKAT, SKAT-O, and SKAT-C, (ii) traditional fixed-effect additive models, and (iii) fixed-effect functional regression models. To evaluate the type I error rates of the tests of fixed models, we generated genotype data by two methods: (i) using all variants, (ii) using only rare variants. We found that the fixed-effect tests accurately control or have low false positive rates. We performed simulation analyses to compare power for two scenarios: (i) all causal variants are rare, (ii) some causal variants are rare and some are common. Either one or both of the fixed-effect models performed better than or similar to the mixed models except when (1) the region sizes are 12 and 15 kb and (2) effect sizes are small. Therefore, the assumption of mixed models could be satisfied and SKAT/SKAT-O/SKAT-C could perform better if the number of causal variants is large and each causal variant contributes a small amount to the traits (i.e., polygenes). In major gene association studies, we argue that the fixed-effect models perform better or similarly to mixed models in most cases because some variants should affect the traits relatively large. In practice, it makes sense to perform analysis by both the fixed and mixed effect models and to make a comparison, and this can be readily done using our R codes and the SKAT packages.


Asunto(s)
Simulación por Computador , Estudios de Asociación Genética , Marcadores Genéticos/genética , Variación Genética/genética , Modelos Estadísticos , Herencia Multifactorial/genética , Sitios de Carácter Cuantitativo/genética , Genotipo , Enfermedad de Hirschsprung/genética , Humanos , Trastornos del Metabolismo de los Lípidos/genética , Modelos Genéticos , Defectos del Tubo Neural/genética , Fenotipo
11.
Genetics ; 202(2): 457-70, 2016 Feb.
Artículo en Inglés | MEDLINE | ID: mdl-26715663

RESUMEN

We developed generalized functional linear models (GFLMs) to perform a meta-analysis of multiple case-control studies to evaluate the relationship of genetic data to dichotomous traits adjusting for covariates. Unlike the previously developed meta-analysis for sequence kernel association tests (MetaSKATs), which are based on mixed-effect models to make the contributions of major gene loci random, GFLMs are fixed models; i.e., genetic effects of multiple genetic variants are fixed. Based on GFLMs, we developed chi-squared-distributed Rao's efficient score test and likelihood-ratio test (LRT) statistics to test for an association between a complex dichotomous trait and multiple genetic variants. We then performed extensive simulations to evaluate the empirical type I error rates and power performance of the proposed tests. The Rao's efficient score test statistics of GFLMs are very conservative and have higher power than MetaSKATs when some causal variants are rare and some are common. When the causal variants are all rare [i.e., minor allele frequencies (MAF) < 0.03], the Rao's efficient score test statistics have similar or slightly lower power than MetaSKATs. The LRT statistics generate accurate type I error rates for homogeneous genetic-effect models and may inflate type I error rates for heterogeneous genetic-effect models owing to the large numbers of degrees of freedom and have similar or slightly higher power than the Rao's efficient score test statistics. GFLMs were applied to analyze genetic data of 22 gene regions of type 2 diabetes data from a meta-analysis of eight European studies and detected significant association for 18 genes (P < 3.10 × 10(-6)), tentative association for 2 genes (HHEX and HMGA2; P ≈ 10(-5)), and no association for 2 genes, while MetaSKATs detected none. In addition, the traditional additive-effect model detects association at gene HHEX. GFLMs and related tests can analyze rare or common variants or a combination of the two and can be useful in whole-genome and whole-exome association studies.


Asunto(s)
Estudios de Asociación Genética , Predisposición Genética a la Enfermedad , Modelos Lineales , Modelos Genéticos , Herencia Multifactorial , Algoritmos , Estudios de Casos y Controles , Mapeo Cromosómico , Estudios de Cohortes , Simulación por Computador , Diabetes Mellitus Tipo 2/genética , Europa (Continente) , Variación Genética , Humanos , Modelos Estadísticos
SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA