To describe the novel technique of ventral inlay substitution urethroplasty for the management of male anterior urethral stricture disease. A 58-year-old gentleman with multifocal bulbar stricture disease measuring 7 cm in length was treated using a ventral inlay substitution urethroplasty. A dorsal urethrotomy was created, and the ventral urethral plated was incised. The edges of the urethral plate were mobilized without violation of the ventral corpus spongiosum. A buccal mucosa graft was harvested and affixed as a ventral inlay to augment the caliber of the urethra. The dorsal urethrotomy was closed over a foley catheter. No intraoperative or postoperative complications occurred. Postoperative imaging demonstrated a widely patent urethra. After three years of follow-up, the patient continues to do well with no voiding complaints and low postvoid residuals. Ventral inlay substitution urethroplasty appears to be a safe and feasible technique for the management of bulbar urethral strictures.
Buccal mucosa; Reconstructive surgical procedure; Urethral stricture
IL-17A has been implicated in severe forms of asthma. However, the factors that promote IL-17A production during the pathogenesis of severe asthma remain undefined. Diesel exhaust particles (DEP) are a major component of traffic related air pollution and are implicated in asthma pathogenesis and exacerbation.
To determine the mechanism by which DEP exposure impacts asthma severity using human and mouse studies.
Balb/c mice were challenged with DEP +/− house dust mite extract (HDM). Airway inflammation and function, BALF cytokine levels, and flow cytometry of lung T cells were assessed. The impact of DEP exposure on frequency of asthma symptoms and serum cytokine levels was determined in children with allergic asthma.
In mice, exposure to DEP alone did not induce asthma. DEP and HDM co-exposure markedly enhanced AHR compared to HDM alone and generated a mixed Th2 and Th17 response, including IL-13+IL-17A+ double producing T-cells. IL-17A neutralization prevented DEP-induced exacerbation of AHR. Among 235 high DEP-exposed children with allergic asthma, 32.2% had more frequent asthma symptoms over a 12 month period, compared to only 14.2% in the low DEP-exposed group (p=0.002). Additionally, high DEP-exposed children with allergic asthma had nearly six times higher serum IL-17A levels compared with low DEP-exposed children.
Expansion of Th17 cells contributes to DEP-mediated exacerbation of allergic asthma. Neutralization of IL-17A may be a useful potential therapeutic strategy to counteract the asthma promoting effects of traffic related air pollution especially in highly exposed severe allergic asthmatics.
allergic asthma; house dust mite; diesel exhaust particle; IL17A; Treg
Following a series of high-profile drug safety disasters in recent years, many countries are redoubling their efforts to ensure the safety of licensed medical products. Large-scale observational databases such as claims databases or electronic health record systems are attracting particular attention in this regard, but present significant methodological and computational concerns. In this paper we show how high-performance statistical computation, including graphics processing units, relatively inexpensive highly parallel computing devices, can enable complex methods in large databases. We focus on optimization and massive parallelization of cyclic coordinate descent approaches to fit a conditioned generalized linear model involving tens of millions of observations and thousands of predictors in a Bayesian context. We find orders-of-magnitude improvement in overall run-time. Coordinate descent approaches are ubiquitous in high-dimensional statistics and the algorithms we propose open up exciting new methodological possibilities with the potential to significantly improve drug safety.
The unique structure and coding of the Clinical Practice Research Datalink (CPRD) presents challenges for epidemiologic analysis and for comparisons with other databases. To address this limitation we sought to transform CPRD into the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM).
An extraction, transformation and loading process was developed, which detailed source code mappings, Read code domain classification, an imputation algorithm for drug duration and special handling of lifestyle/clinical data. Completeness and accuracy of the above elements were assessed. A final validation exercise involved replication of a published case–control study that examined use of nonsteroidal anti-inflammatory drugs (NSAIDs) and the risk of first-time acute myocardial infarction (AMI) in raw CPRD data and the CPRD CDM.
All elements of the CPRD CDM transformation were assessed to be of high quality. 99.9 % of database condition records and 89.7 % of database drug records were mapped (majority unmapped drugs were devices and over-the-counter products); 3.1 % of duration imputations were deemed possibly erroneous and prevalences for selected conditions and drugs across CPRD raw and CDM data were equivalent. Results between the replication raw data and CDM study agreed for conditions, demographics and lifestyle data with slight NSAID exposure data loss owing to unmapped drugs.
CPRD can be accurately transformed into the OMOP CDM with acceptable information loss across drugs, conditions and observations. We determined that for a particular use, case CDM structure was adequate and mappings could be improved but did not substantially change the results of our analysis.
Electronic supplementary material
The online version of this article (doi:10.1007/s40264-014-0214-3) contains supplementary material, which is available to authorized users.
Exhaled nitric oxide (eNO) is increasingly used as a non-invasive measure of airway inflammation. Despite this, little information exists regarding the potential effects of indoor microbial components on eNO. We determined the influence of microbial contaminants in house dust and other indoor environmental characteristics on eNO levels in seven-year-olds with and without a physician- diagnosis of asthma. The study included 158 children recruited from a birth cohort study, and 32 were physician-diagnosed as asthmatic. The relationship between eNO levels and exposures to home dust streptomycetes, endotoxin, and molds was investigated. Streptomycetes and endotoxin were analyzed both as loads and concentrations in separate models. Dog, cat, and dust mite allergens also were evaluated. In the multivariate exposure models high streptomycetes loads and concentrations were significantly associated with a decrease in eNO levels in asthmatic (p <0.001) but not in healthy children. The presence of dog allergen, however, was associated with increased levels of eNO (p = 0.001). Dust endotoxin was not significant. The relationship between eNO and indoor exposure to common outdoor molds was u-shaped. In non-asthmatic children, none of the exposure variables were significantly associated with eNO levels. To our knowledge, this is the first study demonstrating a significant association between microbial components in the indoor environment and eNO levels in asthmatic children. This study demonstrates the importance of simultaneously assessing multiple home exposures of asthmatic children to better understand opposing effects. Common components of the indoor Streptomyces community may beneficially influence airway inflammation.
streptomycetes; mold; allergens; asthma; exhaled nitric oxide; children
Clinical studies that use observational databases to evaluate the effects of medical products have become commonplace. Such studies begin by selecting a particular database, a decision that published papers invariably report but do not discuss. Studies of the same issue in different databases, however, can and do generate different results, sometimes with strikingly different clinical implications. In this paper, we systematically study heterogeneity among databases, holding other study methods constant, by exploring relative risk estimates for 53 drug-outcome pairs and 2 widely used study designs (cohort studies and self-controlled case series) across 10 observational databases. When holding the study design constant, our analysis shows that estimated relative risks range from a statistically significant decreased risk to a statistically significant increased risk in 11 of 53 (21%) of drug-outcome pairs that use a cohort design and 19 of 53 (36%) of drug-outcome pairs that use a self-controlled case series design. This exceeds the proportion of pairs that were consistent across databases in both direction and statistical significance, which was 9 of 53 (17%) for cohort studies and 5 of 53 (9%) for self-controlled case series. Our findings show that clinical studies that use observational databases can be sensitive to the choice of database. More attention is needed to consider how the choice of data source may be affecting results.
database; heterogeneity; methods; population characteristics; reproducibility of results; surveillance
The entire drug safety enterprise has a need to search, retrieve, evaluate, and synthesize scientific evidence more efficiently. This discovery and synthesis process would be greatly accelerated through access to a common framework that brings all relevant information sources together within a standardized structure. This presents an opportunity to establish an open-source community effort to develop a global knowledge base, one that brings together and standardizes all available information for all drugs and all health outcomes of interest (HOIs) from all electronic sources pertinent to drug safety. To make this vision a reality, we have established a workgroup within the Observational Health Data Sciences and Informatics (OHDSI, http://ohdsi.org) collaborative. The workgroup’s mission is to develop an open-source standardized knowledge base for the effects of medical products and an efficient procedure for maintaining and expanding it. The knowledge base will make it simpler for practitioners to access, retrieve, and synthesize evidence so that they can reach a rigorous and accurate assessment of causal relationships between a given drug and HOI. Development of the knowledge base will proceed with the measureable goal of supporting an efficient and thorough evidence-based assessment of the effects of 1,000 active ingredients across 100 HOIs. This non-trivial task will result in a high-quality and generally applicable drug safety knowledge base. It will also yield a reference standard of drug–HOI pairs that will enable more advanced methodological research that empirically evaluates the performance of drug safety analysis methods.
Previously, we demonstrated that infants residing in homes with higher Environmental Relative Moldiness Index were at greater risk for developing asthma by age seven. The purpose of this analysis was to identify the family and home characteristics associated with higher moldiness index values in infants' homes at age one. Univariate linear regression of each characteristic determined that family factors associated with moldiness index were race and income. Home characteristics associated with the moldiness index values were: air conditioning, carpet, age of the home, season of home assessment, and house dust mite allergen. Parental history of asthma, use of dehumidifier, visible mold, dog and cat allergen levels were not associated with moldiness index. Results of multiple linear regression showed that older homes had 2.9 units higher moldiness index (95% confidence interval [CI] = 0.4, 5.4), whereas homes with central air conditioning had 2.5 units lower moldiness index (95% CI = -4.7, -0.4). In addition, higher dust mite allergen levels and carpeting were positively and negatively associated with higher moldiness index, respectively. Because older homes and lack of air conditioning were also correlated with race and lower income, whereas carpeting was associated with newer homes, the multivariate analyses suggests that lower overall socioeconomic position is associated with higher moldiness index values. This may lead to increased asthma risk in homes inhabited by susceptible, vulnerable population subgroups. Further, age of the home was a surrogate of income, race and carpeting in our population; thus the use of these factors should carefully be evaluated in future studies.
mold; environmental relative moldiness index; air conditioning; age of the home; socioeconomic position
Signal detection algorithms (SDAs) are recognized as vital tools in pharmacovigilance. However, their performance characteristics are generally unknown. By leveraging a unique gold standard recently made public by the Observational Medical Outcomes Partnership and by conducting a unique systematic evaluation, we provide new insights into the diagnostic potential and characteristics of SDAs routinely applied to FDAs adverse event reporting system. We find that SDAs can attain reasonable predictive accuracy in signaling adverse events. Two performance classes emerge, indicating that the class of approaches addressing confounding and masking effects benefits safety surveillance. Our study shows that not all events are equally detectable, suggesting that specific events might be monitored more effectively through other sources. We provide performance guidelines for several operating scenarios to inform the trade-off between sensitivity and specificity for specific use cases. We also propose an approach and apply it to identify optimal signaling thresholds given specific misclassification tolerances.
drug safety; pharmacovigilance; adverse event reporting system; signal detection algorithms
Critical illness is a well-recognized cause of neuromuscular weakness and impaired physical functioning. Physical therapy (PT) has been demonstrated to be safe and effective for critically ill patients. The impact of such an intervention on patients receiving extracorporeal membrane oxygenation (ECMO) has not been well characterized. We describe the feasibility and impact of active PT on ECMO patients.
We performed a retrospective cohort study of 100 consecutive patients receiving ECMO in the medical intensive care unit of a university hospital.
Of the 100 patients receiving ECMO, 35 (35%) participated in active PT; 19 as bridge to transplant and 16 as bridge to recovery. Duration of ECMO was 14.3 ± 10.9 days. Patients received 7.2 ± 6.5 PT sessions while on ECMO. During PT sessions, 18 patients (51%) ambulated (median distance 175 feet, range 4 to 2,800) and 9 patients were on vasopressors. Whilst receiving ECMO, 23 patients were liberated from invasive mechanical ventilation. Of the 16 bridge to recovery patients, 14 (88%) survived to discharge; 10 bridge to transplant patients (53%) survived to transplantation, with 9 (90%) surviving to discharge. Of the 23 survivors, 13 (57%) went directly home, 8 (35%) went to acute rehabilitation, and 2 (9%) went to subacute rehabilitation. There were no PT-related complications.
Active PT, including ambulation, can be achieved safely and reliably in ECMO patients when an experienced, multidisciplinary team is utilized. More research is needed to define the barriers to PT and the impact on survival and long-term functional, neurocognitive outcomes in this population.
A recent Canadian case–control study reported a 4.5-fold increased risk of retinal detachment (RD) during oral fluoroquinolone use. Of the fluoroquinolone-exposed cases, 83 % were exposed to ciprofloxacin. We sought to replicate this finding, and assess whether it applied to all fluoroquinolones.
In two large US healthcare databases, we performed three case–control analyses: one replicating the recent study; one addressing additional potential confounders; and one that increased sample size by dropping the Canadian study’s requirement for a prior ophthalmologist visit. We also performed a self-controlled case-series (SCCS) analysis in which each subject served as his or her own comparator.
In the replication case–control analyses, the adjusted odds ratios (ORs) for any exposure to fluoroquinolones or ciprofloxacin were approximately 1.2 in both databases, and were statistically significant, and the ORs for current exposure were modestly above 1 in one database, modestly below 1 in the other, and not statistically significant. In the other case–control analyses, the ORs were close to 1. In a post hoc age-stratified case–control analysis, we observed an association of RD with fluoroquinolone exposure among older subjects in one of the two databases. All estimates from the SCCS analyses were below 1.2 and none was statistically significant.
The present study does not confirm the recent Canadian study’s finding of a strong relationship between RD and current exposure to fluoroquinolones. Instead, it found a modest association between RD and current or any exposure to fluoroquinolones in the case–control analyses, and no association in the SCCS analyses.
DNA methylation; respiratory hypersensitivity; saliva; pyrosequencing; wheezing; traffic-related air pollution
Antisocial behavior is a product of multiple interacting sociohereditary variables, yet there is increasing evidence that metal exposure, particularly, manganese and lead, play a role in its epigenesis. Other metals, such as arsenic, cadmium, chromium, and mercury, and exposure to traffic-related air pollution, such as fine particulate matter (≤2.5 μm) have been associated with neurological deficits, yet largely unexplored with respect to their relationship with delinquent behavior. The purpose of this study is to evaluate the ecological relationship between county-wide reported airborne emissions of air metals, particulate matter, and youth adjudicated for criminal activity.
Metal exposure data were collected from the Environmental Protection Agency AirData. Population statistics were obtained from the United States Census 2000 and adjudication data was obtained from the Courts of Common Pleases from each Ohio County.
Simple correlations were calculated with the percentage of adjudications, all covariates, and estimated metal air emissions. Separate negative binomial regression models for each pollutant were used to provide an estimated risk ratio of pollutant emissions on the risk of adjudication for all Ohio counties adjusting for urban–rural residence, percentage of African Americans, median family income, percentage of family below poverty, percentage of high school graduation in 25 years and older populations, and population density.
Metal emissions and PM in 1999 were all correlated with adjudication rate (2003–2005 average). Metal emissions were associated with slightly higher risk of adjudication, with about 3–4% increased risk per natural log unit of metal emission except chromium. The associations achieved statistical significance for manganese and mercury. The particulate matter ≤2.5 and ≤10 μm emissions had a higher risk estimate, with 12% and 19% increase per natural log unit emission, respectively, and also achieved statistical significance.
In summary, airborne exposure to manganese, mercury, and particulate matter are associated with increased risk of adjudication. Causality cannot be proven in observational studies such as this one, but the association warrants further examination in other research studies. Comprehensive epidemiologic investigations of metal exposure in pediatric populations should include social health outcomes, including measures of delinquent or criminal activity. Furthermore, the influence of metals on the neurotoxic pathway leading to delinquent activity should be further explored.
Manganese; Lead; Particulate matter; Mercury; Air pollution; Ecological study
Mental disorders account for six of the 20 leading causes of disability worldwide with a very high prevalence of psychiatric morbidity in youth aged 15–24 years. However, healthcare professionals are faced with many challenges in the identification and treatment of mental and substance use disorders in young people (e.g. young people’s unwillingness to seek help from healthcare professionals, lack of training, limited resources etc.) The challenge of youth mental health for primary care is especially evident in urban deprived areas, where rates of and risk factors for mental health problems are especially common. There is an emerging consensus that primary care is well placed to address mental and substance use disorders in young people especially in deprived urban areas. This study aims to describe healthcare professionals’ experience and attitudes towards screening and early intervention for mental and substance use disorders among young people (16–25 years) in primary care in deprived urban settings in Ireland.
The chosen method for this qualitative study was inductive thematic analysis which involved semi-structured interviews with 37 healthcare professionals from primary care, secondary care and community agencies at two deprived urban centres.
We identified three themes in respect of interventions to increase screening and treatment: (1) Identification is optimised by a range of strategies, including raising awareness, training, more systematic and formalised assessment, and youth-friendly practices (e.g. communication skills, ensuring confidentiality); (2) Treatment is enhanced by closer inter-agency collaboration and training for all healthcare professionals working in primary care; (3) Ongoing engagement is enhanced by motivational work with young people, setting achievable treatment goals, supporting transition between child and adult mental health services and recognising primary care’s longitudinal nature as a key asset in promoting treatment engagement.
Especially in deprived areas, primary care is central to early intervention for youth mental health. Identification, treatment and continuing engagement are likely to be enhanced by a range of strategies with young people, healthcare professionals and systems. Further research on youth mental health and primary care, including qualitative accounts of young people’s experience and developing complex interventions that promote early intervention are priorities. (350 words)
Young people; Urban deprivation; Mental health; Substance use; Primary care; General practice
Small proline rich protein 2B (SPRR2B) is a skin and lung epithelial protein associated with allergic inflammation in mice that has not been evaluated in human atopic diseases.
To determine whether single-nucleotide polymorphisms (SNPs) in SPRR2B are associated with childhood eczema and with the phenotype of childhood eczema combined with asthma.
Genotyping for SPRR2B and filaggrin (FLG) was performed in 2 independent populations: the Cincinnati Childhood Allergy & Air Pollution Study (CCAAPS; N = 762; birth-age, 4 years) and the Greater Cincinnati Pediatric Clinical Repository (GCPCR;N = 1152; ages 5–10 years). Eczema and eczema plus asthma were clinical outcomes based on parental report and clinician’s diagnosis. Genetic analyses were restricted to whites and adjusted for sex in both cohorts and adjusted for environmental covariates in CCAAPS.
Variants in SPRR2B were not significantly associated with eczema in either cohort after Bonferroni adjustment. Children from both cohorts with the CC genotype of the SPRR2B rs6693927 SNP were at 4 times the risk for eczema plus asthma (adjusted odds ratio, 4.1; 95% confidence interval, 1.5– 10.9; P = .005 in CCAAPS; and adjusted odds ratio, 4.0; 95% confidence interval, 1.8 –9.1; P <.001 in the GCPCR), however. SNPs in SPRR2B were not in strong linkage disequilibrium with the R501X and del2282 FLG mutations, and these findings were independent of FLG.
An SNP in SPRR2B was predictive of asthma among white children with eczema from 2 independent populations. SPRR2B polymorphisms may serve as important predictive markers for the combined eczema plus asthma phenotype.
The specific cause(s) of asthma development must be identified in order to prevent this disease.
Our hypothesis was that specific mold exposures are associated with childhood asthma development.
Infants were identified from birth certificates. Dust samples were collected from 289 homes when the infants were age eight months. Samples were analyzed for concentrations of 36 molds that comprise the Environmental Relative Moldiness Index (ERMI) and endotoxin, house dust mite, cat, dog, and cockroach allergens. Children were evaluated at age seven for asthma based on reported symptoms and objective measures of lung function. Host, environmental exposures and home characteristics evaluated included history of parental asthma, race, gender, upper and lower respiratory symptoms, season of birth, family income, cigarette smoke exposure, air conditioning, dehumidifier, carpeting, age of home, and visible mold at age one and child positive skin prick test (SPT) to aeroallergens and molds at age seven.
Asthma was diagnosed in 24% of the children at age seven. A statistically significant increase in asthma risk at age seven was associated with high ERMI levels in the child’s home in infancy (adjusted risk ratio (aRR) for a 10-unit increase in ERMI = 1.8, 95% CI=1.5, 2.2). The summation of levels of three mold species, Aspergillus ochraceus, Aspergillus unguis, and Penicillium variabile was significantly associated with asthma (aRR = 2.2, 95% CI=1.8, 2.7).
In this birth cohort study, exposure during infancy to three mold species common to water-damaged buildings was associated with childhood asthma at age seven.
Asthma; molds; speciation; infants; Environmental Relative Moldiness Index
Discovery of new adverse drug events (ADEs) in the post-approval period is an important goal of the health system. Data mining methods that can transform data into meaningful knowledge to inform patient safety have proven to be essential. New opportunities have emerged to harness data sources that have not been used within the traditional framework. This article provides an overview of recent methodological innovations and data sources used in support of ADE discovery and analysis.
Pharmacovigilance; Adverse Drug Events; Data Mining
Background: There is increasing concern about the potential effects of traffic-related air pollution (TRAP) on the developing brain. The impact of TRAP exposure on childhood behavior is not fully understood because of limited epidemiologic studies.
Objective: We explored the association between early-life exposure to TRAP using a surrogate, elemental carbon attributed to traffic (ECAT), and attention deficit/hyperactivity disorder (ADHD) symptoms at 7 years of age.
Methods: From the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS) birth cohort we collected data on exposure to ECAT during infancy and behavioral scores at 7 years of age. Children enrolled in CCAAPS had at least one atopic parent and a birth residence either < 400 m or > 1,500 m from a major highway. Children were followed from infancy through 7 years of age. ECAT exposure during the first year of life was estimated based on measurements from 27 air sampling sites and land use regression modeling. Parents completed the Behavioral Assessment System for Children, 2nd Edition, when the child was 7 years of age. ADHD-related symptoms were assessed using the Hyperactivity, Attention Problems, Aggression, Conduct Problems, and Atypicality subscales.
Results: Exposure to the highest tertile of ECAT during the child’s first year of life was significantly associated with Hyperactivity T-scores in the “at risk” range at 7 years of age, after adjustment [adjusted odds ratio (aOR) = 1.7; 95% CI: 1.0, 2.7]. Stratification by maternal education revealed a stronger association in children whose mothers had higher education (aOR = 2.3; 95% CI: 1.3, 4.1).
Conclusions: ECAT exposure during infancy was associated with higher Hyperactivity scores in children; this association was limited to children whose mothers had more than a high school education.
attention deficit/hyperactivity disorder; child behavior; epidemiology; land use regression; traffic-related air pollution
Clinical studies that use observational databases, such as administrative claims and electronic health records, to evaluate the effects of medical products have become commonplace. These studies begin by selecting a particular study design, such as a case control, cohort, or self-controlled design, and different authors can and do choose different designs for the same clinical question. Furthermore, published papers invariably report the study design but do not discuss the rationale for the specific choice. Studies of the same clinical question with different designs, however, can generate different results, sometimes with strikingly different implications. Even within a specific study design, authors make many different analytic choices and these too can profoundly impact results. In this paper, we systematically study heterogeneity due to the type of study design and due to analytic choices within study design.
Methods and findings:
We conducted our analysis in 10 observational healthcare databases but mostly present our results in the context of the GE Centricity EMR database, an electronic health record database containing data for 11.2 million lives. We considered the impact of three different study design choices on estimates of associations between bisphosphonates and four particular health outcomes for which there is no evidence of an association. We show that applying alternative study designs can yield discrepant results, in terms of direction and significance of association. We also highlight that while traditional univariate sensitivity analysis may not show substantial variation, systematic assessment of all analytical choices within a study design can yield inconsistent results ranging from statistically significant decreased risk to statistically significant increased risk. Our findings show that clinical studies using observational databases can be sensitive both to study design choices and to specific analytic choices within study design.
More attention is needed to consider how design choices may be impacting results and, when possible, investigators should examine a wide array of possible choices to confirm that significant findings are consistently identified.
analysis; healthcare database; health outcomes; study design
The panel addresses the urgent need to ensure that comparative effectiveness research (CER) findings derived from diverse and distributed data sources are based on credible, high-quality data; and that the methods used to assess and report data quality are consistent, comprehensive, and available to data consumers. The panel consists of representatives from four teams leveraging electronic clinical data for CER, patient centered outcomes research (PCOR), and quality improvement (QI) and seeks to change the current paradigm where data quality assessment (DQA) is performed “behind the scenes” using one-off project specific methods. The panelists will present their process of harmonizing existing models for describing and measuring clinical data quality and will describe a comprehensive integrated framework for assessing and reporting DQA findings. The collaborative project is supported by the Electronic Data Methods (EDM) Forum, a three-year grant from the Agency for Healthcare Research and Quality (AHRQ) to facilitate learning and foster collaboration across a set of CER, PCOR, and QI projects designed to build infrastructure and methods for collecting and analyzing prospective data from electronic clinical data
When defining allergic outcomes in epidemiology studies results of the skin prick test (SPT) panel is often dichotomized as positive/negative or categorized based on the number of positive responses. Item Response Theory (IRT) models, however, may prove to be a better alternative with the ability to generate scores that account for both type and number of positive SPTs. IRT was applied to SPT responses administered to 537 children at age two in order to determine predictability of allergic disease at age four. The children received SPTs to 15 aeroallergens and two foods. Atopy predisposition scores were obtained from the IRT model using the posterior distribution of the latent trait, atopy. These scores were used to predict persistent wheeze, rhino-conjunctivitis, and eczema at age four. Results were compared to the dichotomized and categorical (positive to ≥ 2, positive to one, versus negative to all allergens) SPT variables. At age two, 39% of children had at least one positive SPT. All three allergic disease outcomes were significantly associated with IRT atopy scores: persistent wheeze odds ratio (OR)=1.7 (95% confidence interval (CI): 1.2, 2.3); rhino-conjunctivitis OR=1.7 (95% CI:1.2, 2.3); eczema OR=1.6 (95% CI: 1.2, 2.3). In contrast, rhino-conjunctivitis was the only outcome significantly associated with the dichotomized SPT variable with an OR=1.9 (95% CI:1.2, 3.0). For the categorical SPT variable, all three allergic symptoms were significantly associated with positive to ≥ 2 allergens compared to negative to all, but no difference was observed between those with positive to one compared to negative to all. The IRT model proved to be an informative methodology to assess the predictability of early SPT responses and identify the allergens most associated with atopy predisposition.
Item Response Theory; Skin Prick Test; Allergy; Atopy; Asthma; Wheeze; Rhino-conjunctivitis; Eczema; Predicting allergies
Systematic analysis of observational medical databases for active safety surveillance is hindered by the variation in data models and coding systems. Data analysts often find robust clinical data models difficult to understand and ill suited to support their analytic approaches. Further, some models do not facilitate the computations required for systematic analysis across many interventions and outcomes for large datasets. Translating the data from these idiosyncratic data models to a common data model (CDM) could facilitate both the analysts' understanding and the suitability for large-scale systematic analysis. In addition to facilitating analysis, a suitable CDM has to faithfully represent the source observational database. Before beginning to use the Observational Medical Outcomes Partnership (OMOP) CDM and a related dictionary of standardized terminologies for a study of large-scale systematic active safety surveillance, the authors validated the model's suitability for this use by example.
Validation by example
To validate the OMOP CDM, the model was instantiated into a relational database, data from 10 different observational healthcare databases were loaded into separate instances, a comprehensive array of analytic methods that operate on the data model was created, and these methods were executed against the databases to measure performance.
There was acceptable representation of the data from 10 observational databases in the OMOP CDM using the standardized terminologies selected, and a range of analytic methods was developed and executed with sufficient performance to be useful for active safety surveillance.
Developing/using computerized provider order entry; Systems to support and improve diagnostic accuracy; other specific EHR applications (results review); medication administration; disease progression and image managem; data exchange; communication and integration across care settings (inter- and intraenterprise); measuring/improving patient safety and reducing medical errors; improving healthcare workflow and process efficiency
Observational healthcare databases represent a valuable resource for health economics, outcomes research, quality of care, drug safety, epidemiology and comparative effectiveness research. The methods used to identify a population for study in an observational healthcare database with the desired drug exposures of interest are complex and not consistent nor apparent in the published literature. Our research evaluates three drug classification systems and their impact on prevalence in the analysis of observational healthcare databases using opioids as a case in point. The standard terminologies compiled in the Observational Medical Outcomes Partnership’s Common Data Model vocabulary were used to facilitate the identification of populations with opioid exposures. This study analyzed three distinct observational healthcare databases and identified patients with at least one exposure to an opioid as defined by drug codes derived through the application of three classification systems. Opioid code sets were created for each of the three classification systems and the number of identified codes was summarized. We estimated the prevalence of opioid exposure in three observational healthcare databases using the three defined code sets. In addition we compared the number of drug codes and distinct ingredients that were identified using these classification systems. We found substantial variation in the prevalence of opioid exposure identified using an individual classification system versus a composite method using multiple classification systems. To ensure transparent and reproducible research publications should include a description of the process used to develop code sets and the complete code set used in studies.
Observational databases; Classification systems; Coding standards; Drug exposures; OMOP