Early Peanut Introduction in Infants: Improving Guideline Adherence With EMR Standardization.

Clinical Decision Support Tools

554 Background: Primary care providers (PCPs) routinely address health screening during clinical encounters and are ideally positioned to promote awareness among patients who would benefit from lung cancer screening (LCS). Integrating clinical decision support (CDS) tools for LCS into the electronic health record (EHR) within primary care settings can potentially serve as a strategy for the implementation of LCS. This study aimed to (1) identify PCPs’ recommendations for LCS CDS tools and (2) develop LCS CDS tools and test their usability in primary care settings. Methods: User-centered design principles were used to gather information from 23 PCPs about their recommendations for LCS CDS tools. Qualitative research methods, including individual interviews and group meetings, were used to collect data on the desired components of LCS CDS tools that would be useful in primary care. Braun and Clarke’s thematic analysis was used to analyze the qualitative data. Member checking was conducted to validate the accuracy of the recommendations. A set of EHR-based CDS tools was developed based on the recommendations. The usability of the CDS tools was tested using a think-aloud methodology with five PCPs and five patients. Iterative changes were made until no further feedback was provided by the PCPs and patients who reviewed the CDS tools. Results: Four components for LCS CDS tools were identified as important: (1) streamline the assessment process to increase the accuracy of tobacco use data collection, (2) provide shared decision making educational resources for patients before the visit and integrate shared decision making tools into the best practice alerts for use by PCPs, (3) provide non-interruptive best practice advisory alerts that were easy to see within the EHR, and (4) streamline the process for ordering CT scans and enhance communication across departments about results and future testing. The CDS tools that were developed included: (1) a patient-reported tobacco use survey, (2) order set for tobacco treatment, (3) best practice alerts to notify PCPs about LCS eligibility based on the accuracy of information available from the tobacco use survey and the EHR, (4) shared decision-making educational materials, and (5) LCS CT order sets. PCPs provided positive feedback about the CDS tools except for the order set for tobacco treatment. PCPs indicated that the order set for tobacco treatment was difficult to use since it disrupted their workflow. Patients provided positive feedback about the educational resources and stressed the importance of having tobacco use questions framed in a way that minimized stigma associated with tobacco use. Conclusions: PCPs recommended four components for CDS tools to facilitate LCS, with a focus on strategies to streamline clinical workflows. Future testing of the CDS tools is needed to determine whether they facilitate implementation of LCS.

Through our work, we have demonstrated how clinical decision support (CDS) tools integrated into the electronic health record (EHR) assist providers in adopting evidence-based practices. This requires confronting technical challenges that result from relying on the EHR as the foundation for tool development; for example, the individual CDS tools need to be built independently for each different EHR. The objective of our research was to build and implement an EHR-agnostic platform for integrating CDS tools, which would remove the technical constraints inherent in relying on the EHR as the foundation and enable a single set of CDS tools that can work with any EHR. We developed EvidencePoint, a novel, cloud-based, EHR-agnostic CDS platform, and we will describe the development of EvidencePoint and the deployment of its initial CDS tools, which include EHR-integrated applications for clinical use cases such as prediction of hospitalization survival for patients with COVID-19, venous thromboembolism prophylaxis, and pulmonary embolism diagnosis. The results below highlight the adoption of the CDS tools, the International Medical Prevention Registry on Venous Thromboembolism-D-Dimer, the Wells' criteria, and the Northwell COVID-19 Survival (NOCOS), following development, usability testing, and implementation. The International Medical Prevention Registry on Venous Thromboembolism-D-Dimer CDS was used in 5249 patients at the 2 clinical intervention sites. The intervention group tool adoption was 77.8% (4083/5249 possible uses). For the NOCOS tool, which was designed to assist with triaging patients with COVID-19 for hospital admission in the event of constrained hospital resources, the worst-case resourcing scenario never materialized and triaging was never required. As a result, the NOCOS tool was not frequently used, though the EvidencePoint platform's flexibility and customizability enabled the tool to be developed and deployed rapidly under the emergency conditions of the pandemic. Adoption rates for the Wells' criteria tool will be reported in a future publication. The EvidencePoint system successfully demonstrated that a flexible, user-friendly platform for hosting CDS tools outside of a specific EHR is feasible. The forthcoming results of our outcomes analyses will demonstrate the adoption rate of EvidencePoint tools as well as the impact of behavioral economics "nudges" on the adoption rate. Due to the EHR-agnostic nature of EvidencePoint, the development process for additional forms of CDS will be simpler than traditional and cumbersome IT integration approaches and will benefit from the capabilities provided by the core system of EvidencePoint.

To develop and implement a clinical decision support (CDS) tool to improve antibiotic prescribing in neonatal intensive care units (NICUs) and to evaluate user acceptance of the CDS tool. Following sociotechnical analysis of NICU prescribing processes, a CDS tool for empiric and targeted antimicrobial therapy for healthcare-associated infections (HAIs) was developed and incorporated into a commercial electronic health record (EHR) in two NICUs. User logs were reviewed and NICU prescribers were surveyed for their perceptions of the CDS tool. The CDS tool aggregated selected laboratory results, including culture results, to make treatment recommendations for common clinical scenarios. From July 2010 to May 2012, 1,303 CDS activations for 452 patients occurred representing 22% of patients prescribed antibiotics during this period. While NICU clinicians viewed two culture results per tool activation, prescribing recommendations were viewed during only 15% of activations. Most (63%) survey respondents were aware of the CDS tool, but fewer (37%) used it during their most recent NICU rotation. Respondents considered the most useful features to be summarized culture results (43%) and antibiotic recommendations (48%). During the study period, the CDS tool functionality was hindered by EHR upgrades, implementation of a new laboratory information system, and changes to antimicrobial testing methodologies. Loss of functionality may have reduced viewing antibiotic recommendations. In contrast, viewing culture results was frequently performed, likely because this feature was perceived as useful and functionality was preserved. To improve CDS tool visibility and usefulness, we recommend early user and information technology team involvement which would facilitate use and mitigate implementation challenges.

Electronic health record (EHR)-based clinical decision support (CDS) tools are rolled out with the urgency to meet federal requirements without time for usability testing and refinement of the user interface....

The effectiveness of an electronic clinical-decision support tool embedded into the patient medical record at the point of care to guide Mohs surgery utilization: A cohort study

Use of a Commercially Available Clinical Decision Support Tool to Expedite Prior Authorization in Partnership With a Private Payer.

BackgroundRetinal toxicity is a rare adverse event related to the use of hydroxychloroquine (HCQ). To address this, in 2016, the American Academy of Ophthalmology (AAO) issued guidelines recommending that HCQ not exceed 5 mg/kg/day. We analyzed HCQ prescribing habits at our institution, compared to these guidelines, and used surveys to determine the opinions on these guidelines. We then introduced, in a prospective and non-controlled study, a clinical decision support (CDS) tool into the electronic medical record (EMR) to study how this intervention might affect adherence with or opinions on these guidelines.MethodsData were collected pre-intervention (June 2017–January 2019) and post-intervention (March 2019–April 2020). In January 2019 we released our CDS tool. Results were analyzed using descriptive statistics for demographic data and Fisher’s exact tests for comparisons of proportions between groups.ResultsPre-intervention, we reviewed 1128 rheumatology charts and 282 dermatology charts. 31.0 and 39.7% respectively (32.8% combined) were prescribed HCQ > 5 .0 mg/kg/day. Post-intervention, we reviewed 1161 rheumatology charts and 110 dermatology charts. 23.0 and 25.5% respectively (23.2% combined) were prescribed HCQ > 5.0 mg/kg/day. Post-intervention, 9.6% fewer patients were prescribed HCQ > 5 mg/kg/day (P < .001). Pre-intervention, we compiled 18 rheumatology surveys and 12 dermatology surveys. Post-intervention, we compiled 16 rheumatology surveys and 12 dermatology surveys. Post-intervention, fewer rheumatologists incorrectly described the AAO weight-based guidelines. Combined, there was an overall reduction but not of statistical significance (P = .47). The majority of providers surveyed believed that the CDS tool was useful (72.2%).ConclusionsAt our academic institution, there remains unfamiliarity with and hesitation to comply with the 2016 AAO guidelines. Prescribed doses often exceed what is recommended in these guidelines. A CDS tool can improve adherence with these guidelines and might improve providers’ familiarity with these guidelines.

Provider Attitudes Toward the Implementation of Clinical Decision Support Tools in Dental Practice

BACKGROUND: Atrial fibrillation (AF) is a common arrhythmia that is often first diagnosed in the Emergency Department (ED). AF is associated with an increased risk of stroke that can be reduced by 64% if an oral anticoagulant (OAC) is prescribed appropriately. RESEARCH QUESTION: Will education and implementation of a clinical decision support (CDS) tool in the ED increase OAC prescription for appropriate candidates diagnosed with new-onset or paroxysmal AF (pAF)? METHODS: This is the first phase of a multi-stage multi-center stepped-wedge cluster-randomized clinical trial implementing a CDS tool into the electronic health record (EHR). Step one implements an external browser link to the CDS tool in the EHR with targeted provider education, whereas steps 2 and 3 will motivate provider engagement with triggers. Data were collected from an urban academic tertiary care center and a community hospital. Patients aged greater than 17 years were selected if they had a primary diagnosis of AF/pAF during ED visits from Jan 2020-Apr 2023. The academic and community sites transitioned from the retrospective phase to Step 1 in Jan 2022 and Apr 2022, respectively. Appropriate OAC prescription was determined based on elevated stroke risk and low-moderate bleed risk. A logistic GEE model was used to study the effect of the proposed intervention on OAC prescription. ED providers were treated as a random effect to capture clustering. The model includes the CDS intervention, site, and patient characteristics sex, race, ethnicity, and age. RESULTS: Of 2031 patients, 312 met inclusion criteria and 150 were selected as appropriate OAC candidates, with 72 (52% male, median age 74) in the retrospective step and 78 (52% male, median age 76) in Step 1. Below are odds ratio estimates with corresponding 95% CI’s: CDS intervention 3.12 [1.57, 6.21] and sex female vs male 2.04 [1.04, 4.00]. Non-significant variables site, race, ethnicity, and age were included as adjusting covariates. CONCLUSIONS: Limited CDS tool education and integration is associated with improved OAC prescribing for appropriate AF/pAF patients. Future studies should assess the impact of additional CDS integration on OAC prescribing and patient outcomes.

Digital clinical decision support (CDS) tools are of growing importance in supporting healthcare professionals in understanding complex clinical problems and arriving at decisions that improve patient outcomes. CDS tools are also increasingly used to improve antimicrobial stewardship (AMS) practices in healthcare settings. However, far fewer CDS tools are available in lowerand middle-income countries (LMICs) and in animal health settings, where their use in improving diagnostic and treatment decision-making is likely to have the greatest impact. The aim of this study was to evaluate digital CDS tools designed as a direct aid to support diagnosis and/or treatment decisionmaking, by reviewing their scope, functions, methodologies, and quality. Recommendations for the development of veterinary CDS tools in LMICs are then provided. The review considered studies and reports published between January 2017 and October 2023 in the English language in peer-reviewed and gray literature. A total of 41 studies and reports detailing CDS tools were included in the final review, with 35 CDS tools designed for human healthcare settings and six tools for animal healthcare settings. Of the tools reviewed, the majority were deployed in high-income countries (80.5%). Support for AMS programs was a feature in 12 (29.3%) of the tools, with 10 tools in human healthcare settings. The capabilities of the CDS tools varied when reviewed against the GUIDES checklist. We recommend a methodological approach for the development of veterinary CDS tools in LMICs predicated on securing sufficient and sustainable funding. Employing a multidisciplinary development team is an important first step. Developing standalone CDS tools using Bayesian algorithms based on local expert knowledge will provide users with rapid and reliable access to quality guidance on diagnoses and treatments. Such tools are likely to contribute to improved disease management on farms and reduce inappropriate antimicrobial use, thus supporting AMS practices in areas of high need.

Prevention of Peanut Allergy (PPA) guidelines were published in 2017 and recommended early introduction of peanut for prevention of peanut allergy. Despite this, there are still mixed practices on peanut introduction among caregivers. Caregiver beliefs, awareness of guidelines, and practices were explored in this survey study.Surveys were administered to a US general population-based sample of parents and caregivers of children between the ages of 7 months and 3.5 years (infants born after the 2017 PPA Guidelines were published). There were 3062 responses recorded.The survey included questions regarding peanut consumption practices and awareness of the PPA Guidelines, primary care physician (PCP) interactions, knowledge and belief assessments on early introduction of peanut, and outcomes of peanut introduction. Child and caregiver demographics, as well as comorbid atopic conditions and family history of allergy, were also noted.Overall, 47.7% of caregivers believed that early introduction prevented peanut allergy and 76.5% believed peanut consumption prevented peanut allergy. However, varying levels of adherence with PPA recommendations were reported. Overall, 17.2% offered peanut containing foods to their infant before 7 months, compared with 31% in guideline aware caregivers. Primary reasons for introduction of peanut after 7 months included fear of reaction (32.5%) and lack of importance (31.7%). PCP counseling was the most important facilitator for those that introduced peanut before 7 months. Awareness of PPA guidelines overall was 13.3%. Guideline aware individuals were more likely to be those who self-identified as white with higher income or education level and those with atopic conditions themselves or an index child with an atopic condition.Addressing concerns about potential reactions, outreach campaigns to make caregivers aware of guidelines, and greater support for PCPs to allow for conversations regarding early peanut introduction may increase adherence to PPA guidelines.Healthcare providers should address early introduction of peanut with patients at their visits to increase adherence and caregiver comfort and knowledge of PPA guidelines for prevention of peanut allergy. Disparities between guideline aware and unaware caregivers exist; providers should be proactive about having these conversations and discussing recommendations with all patients.

Pros and cons of pre-emptive screening programmes before peanut introduction in infancy

BackgroundSyncope evaluation and management is associated with testing overuse and unnecessary hospitalizations. The 2017 American College of Cardiology/American Heart Association (ACC/AHA) Syncope Guideline aims to standardize clinical practice and reduce unnecessary services. The use of clinical decision support (CDS) tools offers the potential to successfully implement evidence-based clinical guidelines. However, CDS tools that provide an evidence-based differential diagnosis (DDx) of syncope at the point of care are currently lacking.ObjectiveWith input from diverse health systems, we developed and demonstrated the viability of a mobile app, the Multilevel Implementation Strategy for Syncope optImal care thrOugh eNgagement (MISSION) Syncope, as a CDS tool for syncope diagnosis and prognosis.MethodsDevelopment of the app had three main goals: (1) reliable generation of an accurate DDx, (2) incorporation of an evidence-based clinical risk tool for prognosis, and (3) user-based design and technical development. To generate a DDx that incorporated assessment recommendations, we reviewed guidelines and the literature to determine clinical assessment questions (variables) and likelihood ratios (LHRs) for each variable in predicting etiology. The creation and validation of the app diagnosis occurred through an iterative clinician review and application to actual clinical cases. The review of available risk score calculators focused on identifying an easily applied and valid evidence-based clinical risk stratification tool. The review and decision-making factors included characteristics of the original study, clinical variables, and validation studies. App design and development relied on user-centered design principles. We used observations of the emergency department workflow, storyboard demonstration, multiple mock review sessions, and beta-testing to optimize functionality and usability.ResultsThe MISSION Syncope app is consistent with guideline recommendations on evidence-based practice (EBP), and its user interface (UI) reflects steps in a real-world patient evaluation: assessment, DDx, risk stratification, and recommendations. The app provides flexible clinical decision making, while emphasizing a care continuum; it generates recommendations for diagnosis and prognosis based on user input. The DDx in the app is deemed a pragmatic model that more closely aligns with real-world clinical practice and was validated using actual clinical cases. The beta-testing of the app demonstrated well-accepted functionality and usability of this syncope CDS tool.ConclusionsThe MISSION Syncope app development integrated the current literature and clinical expertise to provide an evidence-based DDx, a prognosis using a validated scoring system, and recommendations based on clinical guidelines. This app demonstrates the importance of using research literature in the development of a CDS tool and applying clinical experience to fill the gaps in available research. It is essential for a successful app to be deliberate in pursuing a practical clinical model instead of striving for a perfect mathematical model, given available published evidence. This hybrid methodology can be applied to similar CDS tool development.

Recently, our research team found a strong and significant association between loss-of-function (LOF) mutations in filaggrin (FLG), a gene that encodes a skin barrier protein, in European and Canadian individuals with peanut allergy (PA).1Brown S.J. Asai Y. Cordell H.J. Campbell L.E. Zhao Y. Liao H. et al.Loss-of-function variants in the filaggrin gene are a significant risk factor for peanut allergy.J Allergy Clin Immunol. 2011; 127: 661-667Abstract Full Text Full Text PDF PubMed Scopus (326) Google Scholar These mutations result in a barrier defect and have been associated with atopic dermatitis, asthma, and allergic rhinitis.2Irvine A.D. McLean W.H. Leung D.Y. Filaggrin mutations associated with skin and allergic diseases.N Engl J Med. 2011; 365: 1315-1327Crossref PubMed Scopus (812) Google Scholar This finding represents the strongest genetic risk factor found to date for PA, a highly heritable disease,3Sicherer S.H. Furlong T.J. Maes H.H. Desnick R.J. Sampson H.A. Gelb B.D. Genetics of peanut allergy: a twin study.J Allergy Clin Immunol. 2000; 106: 53-56Abstract Full Text Full Text PDF PubMed Scopus (229) Google Scholar with an estimated odds ratio (OR) between 1.9 (Canadian) and 5.3 (English, Dutch, and Irish combined).1Brown S.J. Asai Y. Cordell H.J. Campbell L.E. Zhao Y. Liao H. et al.Loss-of-function variants in the filaggrin gene are a significant risk factor for peanut allergy.J Allergy Clin Immunol. 2011; 127: 661-667Abstract Full Text Full Text PDF PubMed Scopus (326) Google Scholar Because there is no uniformly accepted definition of PA short of oral food challenge, it is worthwhile to examine whether the association between the FLG LOF mutations and PA varies with the diagnostic criteria for PA. Furthermore, the frequent coexistence of PA with other atopic conditions may mean that the association between PA and FLG LOF mutations is confounded. Although we controlled for eczema in the European populations in our previous work, data on eczema were not available for the Canadian control group; however, data on asthma were available. Asthma is a potential confounder, as it has known relationships with both PA4Liu A.H. Jaramillo R. Sicherer S.H. Wood R.A. Bock S.A. Burks A.W. et al.National prevalence and risk factors for food allergy and relationship to asthma: results from the National Health and Nutrition Examination Survey 2005-2006.J Allergy Clin Immunol. 2010; 126: 798-806.e13Abstract Full Text Full Text PDF PubMed Scopus (379) Google Scholar and FLG mutations.5Palmer C.N. Ismail T. Lee S.P. Terron-Kwiatkowski A. Zhao Y. Liao H. et al.Filaggrin null mutations are associated with increased asthma severity in children and young adults.J Allergy Clin Immunol. 2007; 120: 64-68Abstract Full Text Full Text PDF PubMed Scopus (174) Google Scholar By using statistical sensitivity analyses, we examined the effect of PA diagnostic criteria and asthma on the relationship between PA and FLG LOF mutations in a Canadian PA case group. Because the PA case group was composed of both English- and French-speaking individuals, we also investigated whether the difference in OR between the Canadian and European populations could be due to some common French-Canadian mutations not yet identified in FLG.Caucasian subjects from a well-described Canadian pediatric PA case group were recruited (n = 679), and DNA was isolated from salivary samples.1Brown S.J. Asai Y. Cordell H.J. Campbell L.E. Zhao Y. Liao H. et al.Loss-of-function variants in the filaggrin gene are a significant risk factor for peanut allergy.J Allergy Clin Immunol. 2011; 127: 661-667Abstract Full Text Full Text PDF PubMed Scopus (326) Google Scholar One control group consisted of adult Caucasians recruited from the general population of Ontario, Canada; DNA was provided by the Ontario Population Genomics Platform at The Centre for Applied Genomics (Toronto) (n = 894). A second control group of newborn babies from Quebec City was sampled on the basis of French-Canadian surname (stored blood; n = 268).6Girouard J. Giguere Y. Delage R. Rousseau F. Prevalence of HFE gene C282Y and H63D mutations in a French-Canadian population of neonates and in referred patients.Hum Mol Genet. 2002; 11: 185-189Crossref PubMed Scopus (18) Google Scholar All samples were genotyped in Dundee, Scotland, for the 4 most common FLG LOF mutations found in Caucasians (R501X, 2282del4, R2447X, and S3247X). rs and accession numbers for mutations are available in the Online Repository at www.jacionline.org (see Table E1)."Mutation carriers" were defined as those with heterozygous, homozygous, or compound heterozygous mutations. Those individuals with none of the 4 FLG mutations were classified as "nonmutation carriers." The association between mutation status and PA was compared with the Ontario control group, the Quebec control group, and the combined control group. To evaluate whether the association between PA and mutation status changed with case definition, a continuum of PA case definitions was constructed and the resulting OR trends with case definition were examined by using the combined control groups. The methodology and rationale for these definitions are given in the Online Repository available at www.jacionline.org (see Tables E2 and E3). To increase power, case definitions were transformed into an ordered variable and the association between PA and FLG mutations was examined by using regression modeling through increasingly stringent definitions of PA to see whether the OR changed significantly.We also examined the effect of asthma on FLG mutation status and PA. Logistic regression using the Ontario control group was conducted with PA status, age, sex, asthma, and interaction terms for PA and age, PA and sex, and PA and asthma. Because there may be interaction between mutation status, asthma, and smoking,7Berg N.D. Husemoen L.L. Thuesen B.H. Hersoug L.G. Elberling J. Thyssen J.P. et al.Interaction between filaggrin null mutations and tobacco smoking in relation to asthma.J Allergy Clin Immunol. 2012; 129 (e1-2): 374-380Abstract Full Text Full Text PDF PubMed Scopus (30) Google Scholar and self-identified asthmatic patients may have significant misclassification, analyses controlled for smoking history in the controls and misclassification in the asthma variable in both controls and cases. A constructed atopic asthma variable was used to control for the effect of smoking with 4 assumptions: (1) Those individuals who have atopic asthma in childhood are less likely to smoke as adults. (2) Those adults who have asthma and have never smoked are more likely to have atopic asthma. (3) If a patient reports bronchial emphysema, he or she does not have atopic asthma. (4) Asthma reported in the case group is atopic. To examine the possibility of error due to self-report of asthma, we completed a sensitivity analysis taking into account data from the PA registry that found that 6% had "forgotten" previously noted atopic history, while 12% more reported atopic history on the current questionnaire than at baseline registry recruitment. Random sampling and subsequent logistic regression modeling was completed 100 times to see the overall effect of error in asthma reporting on the relationship of PA and FLG LOF mutations using these parameters.Finally, a similar sensitivity analysis of PA status was conducted, as PA status could be affected by the age disparity between the Ontario control group and the cases, because it is estimated that up to 20% of individuals with PA may have resolution of their allergy.8Skolnick H.S. Conover-Walker M.K. Koerner C.B. Sampson H.A. Burks W. Wood R.A. The natural history of peanut allergy.J Allergy Clin Immunol. 2001; 107: 367-374Abstract Full Text Full Text PDF PubMed Scopus (467) Google Scholar This sensitivity analysis also took into account the 1% prevalence of PA in the general population.9Ben-Shoshan M. Harrington D.W. Soller L. Fragapane J. Joseph L. St Pierre Y. et al.A population-based study on peanut, tree nut, fish, shellfish, and sesame allergy prevalence in Canada.J Allergy Clin Immunol. 2010; 125: 1327-1335Abstract Full Text Full Text PDF PubMed Scopus (174) Google ScholarOf the 679 cases eligible to participate, 99.3% had good quality DNA. Demographic information is presented in Table I. The 674 cases had approximately twice as many mutations as the controls (20% vs 11%), and the OR for PA and FLG mutation status was similar in the Ontario and Quebec control groups (Table II). The genotype frequencies in cases and controls are shown in the Online Repository available at www.jacionline.org (see Table E4). Among the 13 case definitions, there was no significant difference in the OR for the relationship between PA and FLG mutation status. Seven representative case definitions are shown in Table III. Logistic regression of the ordered case definition criteria variable produced similar results.Table IDemographics: PA cases and controlsCharacteristicPA casesOntario controlsQuebec controlsNo. of subjects674894268Age (y)∗Age on January 1, 2009. Mean ± SD9.3 ± 4.065.5 ± 10.29.7 ± 0.5 Range0-2133-847-10 No. with missing data020Sex No. of males416281157 Proportion of males (CI)0.617 (0.580-0.654)0.315 (0.284-0.346)0.586 (0.526-0.645)∗ Age on January 1, 2009. Open table in a new tab Table IIFLG genotypes and statistical tests of PA cases compared with control groupsPA casesOntario controlsQuebec controlsCombined controlsNo. of analyzed subjects∗Genotyping failures occurred in 11 PA cases, 5 of the Ontario controls, and 1 of the Quebec controls.6638892671156No. of FLG heterozygotes†One FLG mutation detected.1129429123No. of FLG homozygotes/compound heterozygotes‡Two of the same (FLG homozygote) or 2 different (compound heterozygote) FLG mutations detected.18415Total no. with 1 or 2 FLG mutations1309830128Proportion with 1 or 2 FLG mutations0.1960.1100.1120.110ORNA1.971.931.9695% CINA1.47-2.651.24-3.061.49-2.58χ2 test (P value)NA22.33 (2.30 × 10−6)9.37 (2.21 × 10−3)25.22 (5.12 × 10−7)NA, Not applicable.∗ Genotyping failures occurred in 11 PA cases, 5 of the Ontario controls, and 1 of the Quebec controls.† One FLG mutation detected.‡ Two of the same (FLG homozygote) or 2 different (compound heterozygote) FLG mutations detected. Open table in a new tab Table IIIPA case definition analysis (PA cases compared with the combined control group)No. of subjectsOR95% CIMinimum criteria to be considered for inclusion:a.Convincing history of PA∗A convincing history was defined as a minimum of 2 mild symptoms/signs or either 1 moderate or 1 severe symptom/sign occurring within 120 min after peanut contact or ingestion. (1) Mild: pruritus, urticaria, flushing, and/or rhinoconjunctivitis. (2) Moderate: angioedema, throat tightness, change in voice, coughing, difficulty breathing (other than wheeze), nausea and/or vomiting, and/or abdominal pain. (3) Severe: wheezing, stridor, cyanosis, and/or circulatory collapse. and (i) SPT ≥3 mm or (ii) psIgE ≥ 0.35 kU/L orb.No history of peanut ingestion/uncertain history of allergy and (i) SPT ≥3 mm and (ii) psIgE ≥15 kU/L orc.Any history suggestive of an IgE-mediated reaction not compatible with anaphylaxis and (i) SPT ≥8 mm or (ii) SPT ≥4 mm if <2 y old or (iii) psIgE ≥15 kU/L ord.Positive OFC6741.961.49-2.58psIgE ≥15 kU/L or SPT ≥8 mm, or positive OFC†The definition used in our previous work1 required a history of anaphylaxis or a history suggestive of type I hypersensitivity to peanut along with SPT ≥8 mm and psIgE ≥15 kU/L.5261.971.47-2.65psIgE ≥57 kU/L or SPT ≥8 mm, or positive OFC4862.071.53-2.78psIgE ≥57 kU/L or SPT ≥15 mm, or positive OFC2672.071.42-2.96psIgE ≥15 kU/L, or SPT ≥8 mm AND anaphylaxis, or positive OFC2662.091.44-3.00psIgE ≥57 kU/L, or SPT ≥8 mm AND anaphylaxis, or positive OFC2532.211.52-3.18psIgE ≥57 kU/L, or SPT ≥15 mm AND anaphylaxis, or positive OFC1222.281.38-3.69OFC, Oral food challenge; psIgE, peanut-specific immunoglobulin E; SPT, skin prick test.∗ A convincing history was defined as a minimum of 2 mild symptoms/signs or either 1 moderate or 1 severe symptom/sign occurring within 120 min after peanut contact or ingestion. (1) Mild: pruritus, urticaria, flushing, and/or rhinoconjunctivitis. (2) Moderate: angioedema, throat tightness, change in voice, coughing, difficulty breathing (other than wheeze), nausea and/or vomiting, and/or abdominal pain. (3) Severe: wheezing, stridor, cyanosis, and/or circulatory collapse.† The definition used in our previous work1 required a history of anaphylaxis or a history suggestive of type I hypersensitivity to peanut along with SPT ≥8 mm and psIgE ≥15 kU/L. Open table in a new tab The self-reported prevalence of asthma was 11% in the Ontario controls, compared with 65% in the PA cases (see Table E5 in this article's Online Repository at www.jacionline.org). Univariate analysis found PA status to be the strongest predictor of a mutation, followed by asthma. Neither age nor gender had an appreciable relationship with the presence of FLG mutations on univariate or multivariate analysis and were not included in the final model. Multivariate logistic regression found no evidence for an effect of asthma (OR, 1.12; 95% CI, 0.79-1.59) on the relationship between PA (OR, 1.81; 95% CI, 1.29-2.55) and FLG LOF mutations. The proportion of mutations was similar in those PA cases with and without asthma. Peanut-allergic individuals with asthma had at least 1 mutation in 19.8% of the cases (95% CI, 0.159-0.236), while 18.7% (95% CI, 0.136-0.238) of the PA cases without asthma had at least 1 mutation.An additional analysis using a constructed atopic asthma variable to control for the effect of smoking yielded similar results. PA status remained significant (OR, 1.88; 95% CI, 1.27-2.80), while history of atopic asthma was not (OR, 1.44; 95% CI, 0.59-3.53). Results were also unchanged after the sensitivity analysis of the self-reported asthma variable, with only PA status remaining significant in the multivariate analysis. The sensitivity analysis on PA status similarly had little effect on the findings. While 20% resolution in cases alone finds that both PA and asthma status are nonsignificant, modeling 20% resolution of cases with 1% prevalence in the general population finds that only PA status remains significant in the multivariate model.This study substantiates the relationship between PA and FLG LOF mutations, and moreover this relationship appears independent of diagnostic criteria of PA and history of asthma, although residual confounding is always possible. All sets of diagnostic criteria used in this study were intended to define individuals with clinical allergy, although it is possible that some individuals who were merely sensitized could have been included in the less stringent definitions of PA. Despite this possibility, the association between the FLG LOF mutations and PA does not appear to vary with the diagnostic criteria for PA. Although the point estimates for the OR increase as the PA definition becomes more stringent, the sample size decreases and the CIs overlap; thus, the differences are not statistically significant.The similarity of the OR in the 2 control groups provides indirect evidence that it is unlikely that there are common FLG mutations not yet identified in French-Canadians, under the assumption of similar prevalence of PA. If unidentified common French-Canadian FLG variants exist, one would expect the observed OR to be higher when the PA cases were compared with the Quebec controls, due to a lower detection of mutations in the control group. However, further evidence such as the sequencing of FLG in French-Canadians would be of interest.Limitations of this study include the inability to verify ethnicity by using genetic markers of ethnicity, which were not available for either the cases or controls. However, of the 47 identified FLG mutations, those examined here are shared in many European populations2Irvine A.D. McLean W.H. Leung D.Y. Filaggrin mutations associated with skin and allergic diseases.N Engl J Med. 2011; 365: 1315-1327Crossref PubMed Scopus (812) Google Scholar (see Table E6 in this article's Online Repository at www.jacionline.org), including the expected ancestries of our case and control groups, giving us confidence that population stratification is not the cause of the difference in mutation frequency in the cases and controls. The rate of mutations in the control groups is comparable to the number seen in other Caucasian general populations (Table E6), which also leads us to believe that we have not overestimated the association. This study was also impeded by the inability to confirm asthma status by diagnostic means and that the only control group for which we had asthma and smoking history was a group of adults. While genotype will not change with age, the age difference could have affected ethnicity (eg, through different times of immigration) and PA status because of generational lifestyle, dietary, or environmental differences. Asthma status could also be affected by this age difference, because of smoking history, failure to remember a history of childhood asthma, as well as the possibility that cases have not yet developed asthma, although there is already a large proportion of PA cases who report asthma. In an effort to address these issues, sensitivity analyses of both PA and smoking status were undertaken, which found no appreciable effects on the findings of this study.The results of this study lend credence to the hypothesis that sensitization in allergic in at least some patients may through the J. J. I. R. to peanut oral and allergic PubMed Scopus Google Scholar peanut is a risk factor for the of H. peanut as a risk factor for the of peanut allergy.J Allergy Clin Immunol. Full Text Full Text PDF PubMed Scopus Google Scholar and may be a for the of peanut for a young to peanut may be to to such as that with peanut R. M. The prevalence of peanut sensitization in childhood is due to to 2011; PubMed Scopus Google Scholar filaggrin is not the to these through the skin or could result in to If the to either barrier or may allergic research in barrier and environmental is to further of the of atopic Recently, our research team found a strong and significant association between loss-of-function (LOF) mutations in filaggrin (FLG), a gene that encodes a skin barrier protein, in European and Canadian individuals with peanut allergy (PA).1Brown S.J. Asai Y. Cordell H.J. Campbell L.E. Zhao Y. Liao H. et al.Loss-of-function variants in the filaggrin gene are a significant risk factor for peanut allergy.J Allergy Clin Immunol. 2011; 127: 661-667Abstract Full Text Full Text PDF PubMed Scopus (326) Google Scholar These mutations result in a barrier defect and have been associated with atopic dermatitis, asthma, and allergic rhinitis.2Irvine A.D. McLean W.H. Leung D.Y. Filaggrin mutations associated with skin and allergic diseases.N Engl J Med. 2011; 365: 1315-1327Crossref PubMed Scopus (812) Google Scholar This finding represents the strongest genetic risk factor found to date for PA, a highly heritable disease,3Sicherer S.H. Furlong T.J. Maes H.H. Desnick R.J. Sampson H.A. Gelb B.D. Genetics of peanut allergy: a twin study.J Allergy Clin Immunol. 2000; 106: 53-56Abstract Full Text Full Text PDF PubMed Scopus (229) Google Scholar with an estimated odds ratio (OR) between 1.9 (Canadian) and 5.3 (English, Dutch, and Irish combined).1Brown S.J. Asai Y. Cordell H.J. Campbell L.E. Zhao Y. Liao H. et al.Loss-of-function variants in the filaggrin gene are a significant risk factor for peanut allergy.J Allergy Clin Immunol. 2011; 127: 661-667Abstract Full Text Full Text PDF PubMed Scopus (326) Google Scholar Because there is no uniformly accepted definition of PA short of oral food challenge, it is worthwhile to examine whether the association between the FLG LOF mutations and PA varies with the diagnostic criteria for PA. Furthermore, the frequent coexistence of PA with other atopic conditions may mean that the association between PA and FLG LOF mutations is confounded. Although we controlled for eczema in the European populations in our previous work, data on eczema were not available for the Canadian control group; however, data on asthma were available. Asthma is a potential confounder, as it has known relationships with both PA4Liu A.H. Jaramillo R. Sicherer S.H. Wood R.A. Bock S.A. Burks A.W. et al.National prevalence and risk factors for food allergy and relationship to asthma: results from the National Health and Nutrition Examination Survey 2005-2006.J Allergy Clin Immunol. 2010; 126: 798-806.e13Abstract Full Text Full Text PDF PubMed Scopus (379) Google Scholar and FLG mutations.5Palmer C.N. Ismail T. Lee S.P. Terron-Kwiatkowski A. Zhao Y. Liao H. et al.Filaggrin null mutations are associated with increased asthma severity in children and young adults.J Allergy Clin Immunol. 2007; 120: 64-68Abstract Full Text Full Text PDF PubMed Scopus (174) Google Scholar By using statistical sensitivity analyses, we examined the effect of PA diagnostic criteria and asthma on the relationship between PA and FLG LOF mutations in a Canadian PA case group. Because the PA case group was composed of both English- and French-speaking individuals, we also investigated whether the difference in OR between the Canadian and European populations could be due to some common French-Canadian mutations not yet identified in Caucasian subjects from a well-described Canadian pediatric PA case group were recruited (n = 679), and DNA was isolated from salivary samples.1Brown S.J. Asai Y. Cordell H.J. Campbell L.E. Zhao Y. Liao H. et al.Loss-of-function variants in the filaggrin gene are a significant risk factor for peanut allergy.J Allergy Clin Immunol. 2011; 127: 661-667Abstract Full Text Full Text PDF PubMed Scopus (326) Google Scholar One control group consisted of adult Caucasians recruited from the general population of Ontario, Canada; DNA was provided by the Ontario Population Genomics Platform at The Centre for Applied Genomics (Toronto) (n = 894). A second control group of newborn babies from Quebec City was sampled on the basis of French-Canadian surname (stored blood; n = 268).6Girouard J. Giguere Y. Delage R. Rousseau F. Prevalence of HFE gene C282Y and H63D mutations in a French-Canadian population of neonates and in referred patients.Hum Mol Genet. 2002; 11: 185-189Crossref PubMed Scopus (18) Google Scholar All samples were genotyped in Dundee, Scotland, for the 4 most common FLG LOF mutations found in Caucasians (R501X, 2282del4, R2447X, and S3247X). rs and accession numbers for mutations are available in the Online Repository at www.jacionline.org (see Table carriers" were defined as those with heterozygous, homozygous, or compound heterozygous mutations. Those individuals with none of the 4 FLG mutations were classified as "nonmutation carriers." The association between mutation status and PA was compared with the Ontario control group, the Quebec control group, and the combined control group. To evaluate whether the association between PA and mutation status changed with case definition, a continuum of PA case definitions was constructed and the resulting OR trends with case definition were examined by using the combined control groups. The methodology and rationale for these definitions are given in the Online Repository available at www.jacionline.org (see Tables E2 and E3). To increase power, case definitions were transformed into an ordered variable and the association between PA and FLG mutations was examined by using regression modeling through increasingly stringent definitions of PA to see whether the OR changed also examined the effect of asthma on FLG mutation status and PA. Logistic regression using the Ontario control group was conducted with PA status, age, sex, asthma, and interaction terms for PA and age, PA and sex, and PA and asthma. Because there may be interaction between mutation status, asthma, and smoking,7Berg N.D. Husemoen L.L. Thuesen B.H. Hersoug L.G. Elberling J. Thyssen J.P. et al.Interaction between filaggrin null mutations and tobacco smoking in relation to asthma.J Allergy Clin Immunol. 2012; 129 (e1-2): 374-380Abstract Full Text Full Text PDF PubMed Scopus (30) Google Scholar and self-identified asthmatic patients may have significant misclassification, analyses controlled for smoking history in the controls and misclassification in the asthma variable in both controls and cases. A constructed atopic asthma variable was used to control for the effect of smoking with 4 assumptions: (1) Those individuals who have atopic asthma in childhood are less likely to smoke as adults. (2) Those adults who have asthma and have never smoked are more likely to have atopic asthma. (3) If a patient reports bronchial emphysema, he or she does not have atopic asthma. (4) Asthma reported in the case group is atopic. To examine the possibility of error due to self-report of asthma, we completed a sensitivity analysis taking into account data from the PA registry that found that 6% had "forgotten" previously noted atopic history, while 12% more reported atopic history on the current questionnaire than at baseline registry recruitment. Random sampling and subsequent logistic regression modeling was completed 100 times to see the overall effect of error in asthma reporting on the relationship of PA and FLG LOF mutations using these a similar sensitivity analysis of PA status was conducted, as PA status could be affected by the age disparity between the Ontario control group and the cases, because it is estimated that up to 20% of individuals with PA may have resolution of their allergy.8Skolnick H.S. Conover-Walker M.K. Koerner C.B. Sampson H.A. Burks W. Wood R.A. The natural history of peanut allergy.J Allergy Clin Immunol. 2001; 107: 367-374Abstract Full Text Full Text PDF PubMed Scopus (467) Google Scholar This sensitivity analysis also took into account the 1% prevalence of PA in the general population.9Ben-Shoshan M. Harrington D.W. Soller L. Fragapane J. Joseph L. St Pierre Y. et al.A population-based study on peanut, tree nut, fish, shellfish, and sesame allergy prevalence in Canada.J Allergy Clin Immunol. 2010; 125: 1327-1335Abstract Full Text Full Text PDF PubMed Scopus (174) Google Scholar the 679 cases eligible to participate, 99.3% had good quality DNA. Demographic information is presented in Table I. The 674 cases had approximately twice as many mutations as the controls (20% vs 11%), and the OR for PA and FLG mutation status was similar in the Ontario and Quebec control groups (Table II). The genotype frequencies in cases and controls are shown in the Online Repository available at www.jacionline.org (see Table E4). Among the 13 case definitions, there was no significant difference in the OR for the relationship between PA and FLG mutation status. Seven representative case definitions are shown in Table III. Logistic regression of the ordered case definition criteria variable produced similar results. Not Oral food challenge; psIgE, peanut-specific immunoglobulin E; SPT, skin prick The self-reported prevalence of asthma was 11% in the Ontario controls, compared with 65% in the PA cases (see Table E5 in this article's Online Repository at www.jacionline.org). Univariate analysis found PA status to be the strongest predictor of a mutation, followed by asthma. Neither age nor gender had an appreciable relationship with the presence of FLG mutations on univariate or multivariate analysis and were not included in the final model. Multivariate logistic regression found no evidence for an effect of asthma (OR, 1.12; 95% CI, 0.79-1.59) on the relationship between PA (OR, 1.81; 95% CI, 1.29-2.55) and FLG LOF mutations. The proportion of mutations was similar in those PA cases with and without asthma. Peanut-allergic individuals with asthma had at least 1 mutation in 19.8% of the cases (95% CI, 0.159-0.236), while 18.7% (95% CI, 0.136-0.238) of the PA cases without asthma had at least 1 additional analysis using a constructed atopic asthma variable to control for the effect of smoking yielded similar results. PA status remained significant (OR, 1.88; 95% CI, 1.27-2.80), while history of atopic asthma was not (OR, 1.44; 95% CI, 0.59-3.53). Results were also unchanged after the sensitivity analysis of the self-reported asthma variable, with only PA status remaining significant in the multivariate analysis. The sensitivity analysis on PA status similarly had little effect on the findings. While 20% resolution in cases alone finds that both PA and asthma status are nonsignificant, modeling 20% resolution of cases with 1% prevalence in the general population finds that only PA status remains significant in the multivariate