Model estimates of hospitalization discharge rates for norovirus gastroenteritis in Europe, 2004-2015.

BACKGROUND: Norovirus is an important cause of acute gastroenteritis globally. However, norovirus is rarely laboratory confirmed or recorded explicitly as a cause of hospitalization. In recent years, there has been an interest in using medical databases and indirect modelling methods to estimate the incidence of norovirus gastroenteritis. The objective of this study was to estimate the incidence of hospitalizations for norovirus gastroenteritis in Europe (2004-2015) using nationwide in-patient discharge records from different European countries. METHODS: National hospital discharge registers in all 28 European Union countries (at that time) and all 4 European Free Trade Association countries were contacted and invited to participate in the study. Discharges with ICD9/ICD10 codes for acute gastroenteritis (AGE) as first-listed (principal) diagnosis were extracted to assess hospitalization rates for AGE and norovirus gastroenteritis (NGE), overall, by age group, country, month, and seasonal year. The number of cause-unspecified episodes was regressed against pathogen-specific AGE episodes: Rotavirus, Clostridium difficile, Other Bacterial, Other Viral and Parasitic separately. NGE hospital discharges were estimated for each month by calculating the difference between observed cause-unspecified and model-predicted counts, assuming that any remaining seasonality not otherwise captured in the model was due to norovirus, and adding those to the coded NGE episodes to get the total number of norovirus-associated episodes. RESULTS: Data were available from 15 countries, representing 68% of the total population in Europe. Only 24.4% of all AGE discharges were coded as cause-specified. We estimated that between 2004 and 2015, the overall rate of NGE hospital discharges in Europe was 3.9 per 10,000 person-years, ranging from 1.2 (Portugal) to 10.7 (Lithuania). Norovirus was predicted to be responsible for 17% of all AGE hospital discharges in Europe in this period. Norovirus affects individuals of all ages, but NGE discharge rates were highest in children < 5 years (24.8 per 10,000 person-years), and adults aged ≥80 years (10.7 per 10,000 person-years). CONCLUSION: We estimated that 1 in 400 hospitalizations in Europe can be attributed to Norovirus. In the absence of routine norovirus testing and recording in hospital settings, modelling methods are useful resources to estimate the incidence of norovirus gastroenteritis.

The Brussels Infant and Toddler Stool Scale: A Study on Interobserver Reliability.

OBJECTIVES: The Bristol Stool Form Scale (BSFS) is inadequate for non-toilet trained children. The Brussels Infant and Toddler Stool Scale (BITSS) was developed, consisting of 7 photographs of diapers containing stools of infants and toddlers. We aimed to evaluate interobserver reliability of stool consistency assessment among parents, nurses, and medical doctors (MDs) using the BITSS. METHODS: In this multicenter cross-sectional study (2016-2017), BITSS photographs were rated according to the BSFS. The reliability of the BITSS was evaluated using the overall proportion of perfect agreement and the linearly weighted κ statistic. RESULTS: A total of 2462 observers participated: 1181 parents (48.0%), 624 nurses (25.3%), and 657 MDs (26.7%). The best-performing BITSS photographs corresponded with BSFS type 7 (87.5%) and type 4 (87.6%), followed by the BITSS photographs representing BSFS type 6 (75.0%), BSFS type 5 (68.0%), BSFS type 1 (64.8%), and BSFS type 3 (64.6%). The weakest performing BITSS photograph corresponded with BSFS type 2 (49.7%). The overall weighted κ-value was 0.72 (95% CI 0.59-0.85; good agreement). Based on these results, photographs were categorized per stool group as hard (BSFS type 1-3), formed (BSFS type 4), loose (BSFS types 5 and 6), or watery (BSFS type 7) stools. According to this new categorization system, correct allocation for each photograph ranged from 83 to 96% (average: 90%). The overall proportion of correct allocations was 72.8%. CONCLUSIONS: BITSS showed good agreement with BSFS. Using the newly categorized BITSS photographs, the BITSS is reliable for the assessment of stools of non-toilet trained children in clinical practice and research. A multilanguage translated version of the BITSS can be downloaded at https://bitss-stoolscale.com/.

Estimating the Burden of Medically Attended Norovirus Gastroenteritis: Modeling Linked Primary Care and Hospitalization Datasets.

Background: Norovirus is the leading cause of community-acquired and nosocomial acute gastroenteritis. Routine testing for norovirus is seldom undertaken, and diagnosis is mainly based on presenting symptoms. This makes understanding the burden of medically attended norovirus-attributable gastroenteritis (MA-NGE) and targeting care and prevention strategies challenging. Methods: We used linked population-based healthcare datasets (Clinical Practice Research Datalink General Practice OnLine Database linked with Hospital Episode Statistics Admitted Patient Care) to model the incidence of MA-NGE associated with primary care consultations or hospitalizations according to age groups in England in the period July 2007-June 2013. Results: Mean annual incidence rates of MA-NGE were 4.9/1000 person-years and 0.7/1000 person-years for episodes involving primary care or hospitalizations, respectively. Incidence rates were highest in children aged <5 years: 34.0 consultations/1000 person-years and 3.3 hospitalizations/1000 person-years. Medically attended norovirus-attributable gastroenteritis hospitalization rates were second highest in adults aged >65 years (1.7/1000 person-years). Conclusions: In this particular study, the burden of MA-NGE estimated from healthcare datasets was higher than previously estimated in small cohort studies in England. Routinely collected primary care and hospitalization datasets are useful resources to estimate and monitor the burden of MA-NGE in a population over time.

Withdrawal of immunomodulators after co-treatment does not reduce trough level of infliximab in patients with Crohn's disease.

BACKGROUND & AIMS: The addition of immunomodulators increases the efficacy of maintenance therapy with infliximab for up to 1 year in patients with Crohn's disease who have not been previously treated with immunomodulators. However, there are questions about the effect of withdrawing immunomodulator therapy from these patients. We studied the effects of treatment with infliximab and immunomodulators (co-treatment) and then immunomodulator withdrawal on long-term outcomes of patients, as well as trough levels of infliximab and formation of anti-infliximab antibodies (ATI). METHODS: In a retrospective study with the median follow-up period of 34 months (interquartile range, 19-58 months), we analyzed data from 223 patients treated for Crohn's disease between May 1999 and December 2010 at the University Hospitals, Leuven, Belgium (65 received infliximab monotherapy, 158 received infliximab and an immunomodulator). Trough levels of infliximab and levels of ATI were measured in blood samples collected from 117 patients throughout co-treatment, as well as the time of immunomodulator withdrawal and after withdrawal. RESULTS: Patients receiving co-treatment had higher trough levels of infliximab (adjusted mean increase, 1.44-fold) than those receiving infliximab monotherapy (95% confidence interval [CI], 1.07-1.92; P = .02). A smaller percentage of patients receiving co-treatment developed ATI (35 of 158, 22%) than those receiving infliximab monotherapy (25 of 65, 38%; P = .01). Among co-treated patients, levels of infliximab remained stable after immunomodulators were withdrawn (before: 3.2 µg/mL; 95% CI, 1.6-5.8 µg/mL and after: 3.7 µg/mL; 95% CI, 1.3-6.3 µg/mL; P = .70). After withdrawal of immunomodulators, 45 of 117 patients (38%) required increasing doses of infliximab, and 21 of 117 (18%) discontinued infliximab. At the time of immunomodulator withdrawal, trough levels of infliximab and C-reactive protein were most strongly associated with response to infliximab thereafter. CONCLUSIONS: In a retrospective analysis, we confirmed that withdrawal of immunomodulators after at least 6 months (median, 13 months) of co-treatment with infliximab does not reduce the trough levels of infliximab in patients with Crohn's disease. Detectable trough levels of infliximab at the time of immunomodulator withdrawal are associated with long-term response.

Specific IgE against Staphylococcus aureus enterotoxins: an independent risk factor for asthma.

BACKGROUND: The role of IgE in patients with severe asthma is not fully understood. OBJECTIVE: We sought to investigate whether IgE to Staphylococcus aureus enterotoxins might be relevant to disease severity in adult asthmatic patients. METHODS: Specific IgE antibody concentrations in serum against enterotoxins, grass pollen (GP), and house dust mite allergens and total IgE levels were measured in adult cohorts of 69 control subjects, 152 patients with nonsevere asthma, and 166 patients with severe asthma. Severe asthma was defined as inadequately controlled disease despite high-dose inhaled corticosteroids plus at least 2 other controller therapies, including oral steroids. RESULTS: Enterotoxin IgE positivity was significantly greater in patients with severe asthma (59.6%) than in healthy control subjects (13%, P< .001). Twenty-one percent of patients with severe asthma with enterotoxin IgE were considered nonatopic. Logistic regression analyses demonstrated significantly increased risks for enterotoxin IgE-positive subjects to have any asthma (OR, 7.25; 95% CI, 2.7-19.1) or severe asthma (OR, 11.09; 95% CI, 4.1-29.6) versus enterotoxin IgE-negative subjects. The presence of GP or house dust mite IgE antibodies was not associated with either significantly increased risk for asthma or severity. Oral steroid use and hospitalizations were significantly increased in patients with enterotoxin IgE and nonatopic asthma. GP IgE was associated with a higher FEV(1) percent predicted value, and enterotoxin IgE was associated with a lower FEV(1) percent predicted value. CONCLUSIONS: Staphylococcal enterotoxin IgE antibodies, but not IgE against inhalant allergens, are risk factors for asthma severity. We hypothesize that the presence of enterotoxin IgE in serum indicates the involvement of staphylococcal superantigens in the pathophysiology of patients with severe asthma.

Mepolizumab, a humanized anti-IL-5 mAb, as a treatment option for severe nasal polyposis.

BACKGROUND: Approximately 85% of nasal polyps (NPs) in white subjects are characterized by prominent eosinophilia. IL-5 is the key driver of eosinophilic differentiation and survival. OBJECTIVE: We sought to investigate the therapeutic potential of inhibiting IL-5 with a humanized mAb as treatment for severe nasal polyposis. METHODS: Thirty patients with severe nasal polyposis (grade 3 or 4 or recurrent after surgery) refractory to corticosteroid therapy were randomized in a double-blind fashion to receive either 2 single intravenous injections (28 days apart) of 750 mg of mepolizumab (n = 20) or placebo (n = 10). Change from baseline in NP score was assessed monthly until 1 month after the last dose (week 8). Computed tomographic scans were also performed at week 8. RESULTS: Twelve of 20 patients receiving mepolizumab had a significantly improved NP score and computed tomographic scan score compared with 1 of 10 patients receiving placebo at week 8 versus baseline. CONCLUSION: Mepolizumab achieved a statistically significant reduction in NP size for at least 1 month after dosing in 12 of 20 patients. IL-5 inhibition is a potential novel therapeutic approach in patients with severe eosinophilic nasal polyposis.

Model-based multifactor dimensionality reduction for detecting epistasis in case-control data in the presence of noise.

Analyzing the combined effects of genes and/or environmental factors on the development of complex diseases is a great challenge from both the statistical and computational perspective, even using a relatively small number of genetic and nongenetic exposures. Several data-mining methods have been proposed for interaction analysis, among them, the Multifactor Dimensionality Reduction Method (MDR) has proven its utility in a variety of theoretical and practical settings. Model-Based Multifactor Dimensionality Reduction (MB-MDR), a relatively new MDR-based technique that is able to unify the best of both nonparametric and parametric worlds, was developed to address some of the remaining concerns that go along with an MDR analysis. These include the restriction to univariate, dichotomous traits, the absence of flexible ways to adjust for lower order effects and important confounders, and the difficulty in highlighting epistatic effects when too many multilocus genotype cells are pooled into two new genotype groups. We investigate the empirical power of MB-MDR to detect gene-gene interactions in the absence of any noise and in the presence of genotyping error, missing data, phenocopy, and genetic heterogeneity. Power is generally higher for MB-MDR than for MDR, in particular in the presence of genetic heterogeneity, phenocopy, or low minor allele frequencies.

Estimation of Risk of Death Attributable to Acute Gastroenteritis Not Caused by Clostridioides difficile Infection Among Hospitalized Adults in England.

INTRODUCTION: The role of an infectious agent may be unclear as the primary cause of death. Furthermore, many infections go undiagnosed, particularly if identification does not affect treatment. To circumvent the limitations of individual death attribution, a population-level assessment of the role of infectious acute gastroenteritis (AGE) was performed. METHODS: Using the Clinical Practice Research Datalink and the Office for National Statistics - Mortality Statistics, covering 16 million patients in the UK, we conducted a matched case-control study to estimate the odds of having AGE not due to Clostridioides difficile infection (CDI) diagnosed in the month before death among hospitalized adults in England. To estimate the number of deaths, we first estimated the attributable fraction (AF). The population attributable fraction (PAF) was then derived by multiplying AF with the proportion of AGE hospitalizations among all hospitalizations. Finally, by multiplying the PAF with the number of deaths, the number of deaths attributable to AGE not caused by CDI among hospitalized patients was estimated. RESULTS: The odds of having AGE not caused by CDI was 4.6 times higher among fatal compared to non-fatal hospitalizations. The overall PAF was 1.7% for AGE not caused by CDI. The overall number of deaths attributable to AGE not caused by CDI among adults in England is estimated to be 5000 annually. DISCUSSION: Approximately 5000 of the 276,000 deaths that occur annually among hospitalized adults in England can be attributed to AGE not caused by CDI, which is higher than previously estimated.

Hepatitis B virus infection and the risk of liver disease progression in type 2 diabetic patients with potential nonalcoholic fatty liver disease: a retrospective, observational, cohort study in the United Kingdom Clinical Practice Research Datalink.

OBJECTIVE: Assess the risk of progression to cirrhosis and hepatocellular carcinoma (HCC) due to hepatitis B virus (HBV)-infection in patients with nonalcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus (T2DM). METHODS: Retrospective cohort study in the UK Clinical Practice Research Datalink with three cohorts: subjects with T2DM and HBV infection (T2DM+HBV cohort; N = 297), with T2DM without HBV-infection (T2DM cohort; N = 261 865), and with HBV-infection without T2DM (HBV cohort; N = 3630). Primary analyses were performed on the three cohorts and secondary analyses on subcohorts including patients with NAFLD diagnosis code (N = 6599). Case/outcome definitions were formulated with International Classification of Diseases/Read codes/laboratory results and classified using validated algorithms. Adjusted incidence rate ratios (IRR) were estimated with a Poisson regression model. RESULTS: When comparing the T2DM+HBV and T2DM cohorts, adjusted IRRs were 14.06 (95% confidence interval: 4.47-44.19) for cirrhosis and 2.83 (1.06-7.55) for HCC. When comparing the T2DM+HBV and HBV cohorts, adjusted IRRs were 0.68 (0.21-2.27) for cirrhosis and 1.39 (0.46-4.20) for HCC. No cirrhosis cases were identified in T2DM+NAFLD+HBV patients; IRs were 16.92/10 000 person-years (12.97-21.69) and 85.24/10 000 person-years (10.32-307.91) in the T2DM+NAFLD and NAFLD+HBV cohorts. CONCLUSION: HBV-infection increased significantly the risk for cirrhosis among T2DM patients, however, not beyond the expected incremental risk among infected non-T2DM subjects. Our approach to evaluate the role of T2DM/NAFLD and HBV-infection in liver disease progression could be applied to other settings with higher HBV prevalence.

Lower-order effects adjustment in quantitative traits model-based multifactor dimensionality reduction.

Identifying gene-gene interactions or gene-environment interactions in studies of human complex diseases remains a big challenge in genetic epidemiology. An additional challenge, often forgotten, is to account for important lower-order genetic effects. These may hamper the identification of genuine epistasis. If lower-order genetic effects contribute to the genetic variance of a trait, identified statistical interactions may simply be due to a signal boost of these effects. In this study, we restrict attention to quantitative traits and bi-allelic SNPs as genetic markers. Moreover, our interaction study focuses on 2-way SNP-SNP interactions. Via simulations, we assess the performance of different corrective measures for lower-order genetic effects in Model-Based Multifactor Dimensionality Reduction epistasis detection, using additive and co-dominant coding schemes. Performance is evaluated in terms of power and familywise error rate. Our simulations indicate that empirical power estimates are reduced with correction of lower-order effects, likewise familywise error rates. Easy-to-use automatic SNP selection procedures, SNP selection based on "top" findings, or SNP selection based on p-value criterion for interesting main effects result in reduced power but also almost zero false positive rates. Always accounting for main effects in the SNP-SNP pair under investigation during Model-Based Multifactor Dimensionality Reduction analysis adequately controls false positive epistasis findings. This is particularly true when adopting a co-dominant corrective coding scheme. In conclusion, automatic search procedures to identify lower-order effects to correct for during epistasis screening should be avoided. The same is true for procedures that adjust for lower-order effects prior to Model-Based Multifactor Dimensionality Reduction and involve using residuals as the new trait. We advocate using "on-the-fly" lower-order effects adjusting when screening for SNP-SNP interactions using Model-Based Multifactor Dimensionality Reduction analysis.

Comparison of genetic association strategies in the presence of rare alleles.

In the quest for the missing heritability of most complex diseases, rare variants have received increased attention. Advances in large-scale sequencing have led to a shift from the common disease/common variant hypothesis to the common disease/rare variant hypothesis or have at least reopened the debate about the relevance and importance of rare variants for gene discoveries. The investigation of modeling and testing approaches to identify significant disease/rare variant associations is in full motion. New methods to better deal with parameter estimation instabilities, convergence problems, or multiple testing corrections in the presence of rare variants or effect modifiers of rare variants are in their infancy. Using a recently developed semiparametric strategy to detect causal variants, we investigate the performance of the model-based multifactor dimensionality reduction (MB-MDR) technique in terms of power and family-wise error rate (FWER) control in the presence of rare variants, using population-based and family-based data (FAM-MDR). We compare family-based results obtained from MB-MDR analyses to screening findings from a quantitative trait Pedigree-based association test (PBAT). Population-based data were further examined using penalized regression models. We restrict attention to all available single-nucleotide polymorphisms on chromosome 4 and consider Q1 as the outcome of interest. The considered family-based methods identified marker C4S4935 in the VEGFC gene with estimated power not exceeding 0.35 (FAM-MDR), when FWER was kept under control. The considered population-based methods gave rise to highly inflated FWERs (up to 90% for PBAT screening).

FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals.

We propose a novel multifactor dimensionality reduction method for epistasis detection in small or extended pedigrees, FAM-MDR. It combines features of the Genome-wide Rapid Association using Mixed Model And Regression approach (GRAMMAR) with Model-Based MDR (MB-MDR). We focus on continuous traits, although the method is general and can be used for outcomes of any type, including binary and censored traits. When comparing FAM-MDR with Pedigree-based Generalized MDR (PGMDR), which is a generalization of Multifactor Dimensionality Reduction (MDR) to continuous traits and related individuals, FAM-MDR was found to outperform PGMDR in terms of power, in most of the considered simulated scenarios. Additional simulations revealed that PGMDR does not appropriately deal with multiple testing and consequently gives rise to overly optimistic results. FAM-MDR adequately deals with multiple testing in epistasis screens and is in contrast rather conservative, by construction. Furthermore, simulations show that correcting for lower order (main) effects is of utmost importance when claiming epistasis. As Type 2 Diabetes Mellitus (T2DM) is a complex phenotype likely influenced by gene-gene interactions, we applied FAM-MDR to examine data on glucose area-under-the-curve (GAUC), an endophenotype of T2DM for which multiple independent genetic associations have been observed, in the Amish Family Diabetes Study (AFDS). This application reveals that FAM-MDR makes more efficient use of the available data than PGMDR and can deal with multi-generational pedigrees more easily. In conclusion, we have validated FAM-MDR and compared it to PGMDR, the current state-of-the-art MDR method for family data, using both simulations and a practical dataset. FAM-MDR is found to outperform PGMDR in that it handles the multiple testing issue more correctly, has increased power, and efficiently uses all available information.