Severity of obstructive airways disease by age 2 years predicts asthma at 10 years of age

Three-year outcome of a very young severe uncontrolled preschool wheezers cohort, a real-life study

Preschool wheeze is a public health issue. Disease control can be difficult to obtain in this population, in which no biologic therapy is indicated. We studied the evolution of severe preschool wheezers in real-life and identified the factors leading to no-control. We conducted a retrospective study at our tertiary asthma center. Each child under 3 years of age with severe, uncontrolled preschool wheeze was admitted to a pediatric day hospital for further investigations. We collected the results of clinical, biological and radiological exams, and follow-up data at 1 (Y+1), 2 (Y+2) and 3 years (Y+3). We included 135 patients; 63 (47 %) were still being followed at Y+3; 53 % were discontinued due to disease control. The median age at inclusion was 12 months. 29 % of patients followed up still had severe uncontrolled wheezing at Y+3. Eosinophils greater than 0.23G/L (p = 0.03) and a first case of bronchiolitis before the age of 2 months (p = 0.01) were factors in uncontrolled wheezing at Y1. Tobacco exposure was a factor associated with uncontrolled wheezing at Y+2 (p < 0.001). A first case of bronchiolitis before the age of 2 months (p = 0.007), male sex (p < 0.001) and a familial history of atopy (p = 0.05) were factors in uncontrolled disease at Y+3. We report a real-life study, with a very young population and very severe wheezing. Our therapeutic approach is original, enabling us to study the evolution of "therapeutic pressure" in the early years of this frequent disease, the pathophysiology of which is still poorly understood.

Prediction of adult asthma risk in early childhood using novel adult asthma predictive risk scores

BACKGROUND

Numerous risk scores have been developed to predict childhood asthma. However, they may not predict asthma beyond childhood. We aim to create childhood risk scores that predict development and persistence of asthma up to young adult life.

METHODS

The Isle of Wight Birth Cohort (n = 1456) was prospectively assessed up to 26 years of age. Asthma predictive scores were developed based on factors during the first 4 years, using logistic regression and tested for sensitivity, specificity and area under the curve (AUC) for prediction of asthma at (i) 18 and (ii) 26 years, and persistent asthma (PA) (iii) at 10 and 18 years, and (iv) at 10, 18 and 26 years. Models were internally and externally validated.

RESULTS

Four models were generated for prediction of each asthma outcome. ASthma PredIctive Risk scorE (ASPIRE)-1: a 2-factor model (recurrent wheeze [RW] and positive skin prick test [+SPT] at 4 years) for asthma at 18 years (sensitivity: 0.49, specificity: 0.80, AUC: 0.65). ASPIRE-2: a 3-factor model (RW, +SPT and maternal rhinitis) for asthma at 26 years (sensitivity: 0.60, specificity: 0.79, AUC: 0.73). ASPIRE-3: a 3-factor model (RW, +SPT and eczema at 4 years) for PA-18 (sensitivity: 0.63, specificity: 0.87, AUC: 0.77). ASPIRE-4: a 3-factor model (RW, +SPT at 4 years and recurrent chest infection at 2 years) for PA-26 (sensitivity: 0.68, specificity: 0.87, AUC: 0.80). ASPIRE-1 and ASPIRE-3 scores were replicated externally. Further assessments indicated that ASPIRE-1 can be used in place of ASPIRE-2-4 with same predictive accuracy.

CONCLUSION

ASPIRE predicts persistent asthma up to young adult life.

Does machine learning have a role in the prediction of asthma in children?

Asthma is the most common chronic lung disease in childhood. There has been a significant worldwide effort to develop tools/methods to identify children's risk for asthma as early as possible for preventative and early management strategies. Unfortunately, most childhood asthma prediction tools using conventional statistical models have modest accuracy, sensitivity, and positive predictive value. Machine learning is an approach that may improve on conventional models by finding patterns and trends from large and complex datasets. Thus far, few studies have utilized machine learning to predict asthma in children. This review aims to critically assess these studies, describe their limitations, and discuss future directions to move from proof-of-concept to clinical application.

Early Life Wheeze and Risk Factors for Asthma-A Revisit at Age 7 in the GEWAC-Cohort

One third of all toddlers are in need of medical care because of acute wheeze and many of these children have persistent asthma at school age. Our aims were to assess risk factors for and the prevalence of asthma at age 7 in a cohort of children suffering from an acute wheezing episode as toddlers. A total of 113 children, included during an acute wheezing episode (cases), and 54 healthy controls were followed prospectively from early pre-school age to 7 years. The protocol included questionnaires, ACT, FeNO, nasopharyngeal virus samples, blood sampling for cell count, vitamin D levels, and IgE to food and airborne allergens. The prevalence of asthma at age 7 was 70.8% among cases and 1.9% among controls (p < 0.001). Acute wheeze caused by rhinovirus (RV) infection at inclusion was more common among cases with asthma at age 7 compared to cases without asthma (p = 0.011) and this association remained significant following adjustment for infection with other viruses (OR 3.8, 95% CI 1.4–10.5). Cases with asthma at age 7 had been admitted to hospital more often (p = 0.024) and spent more days admitted (p = 0.01) during the year following inclusion compared to cases without asthma. RV infection stands out as the main associated factor for wheeze evolving to persistent asthma. Cases who developed asthma also had an increased need of hospital time and care for wheeze during the year after inclusion.

Factors associated with wheezing among Lebanese children: Results of a cross-sectional study

BACKGROUND

In Lebanon, asthma is underdiagnosed due to low access to healthcare, particularly in rural areas, although asthma diagnosis in children is based mainly on clinical symptoms. Thus, wheezing might be more suggestive of undiagnosed respiratory diseases including asthma in Lebanese children. This study aimed to determine the factors associated with wheezing in Lebanese children without asthma diagnosis.

METHODS

This cross-sectional study was conducted between December 2015 and April 2016, enrolling a total of 1203 schoolchildren.

RESULTS

Out of 1500 prepared questionnaires, 1380 questionnaires were distributed in schools, and 1203 (87.17%) were collected back from the parents of children aged between 4-17 years old. The sample included 42 (3.5%) [95% CI 0.025-0.045] children with reported chronic wheezing. A multivariable analysis was performed taking the presence versus absence of wheezing in children as the dependent variable. The results showed that spraying pesticides at home (aOR=1.91), presence of humidity at home (aOR=2.21) and child reflux (aOR=2.60) were significantly associated with the presence of wheezing in children.

CONCLUSION

The findings of the study suggest that certain environmental factors, such as pesticides, humidity at home and reflux disease, might be associated with wheezing episodes in children. Those factors can be prevented through raising awareness by health care professionals.

Prediction models for childhood asthma: A systematic review

BACKGROUND

The inability to objectively diagnose childhood asthma before age five often results in both under-treatment and over-treatment of asthma in preschool children. Prediction tools for estimating a child's risk of developing asthma by school-age could assist physicians in early asthma care for preschool children. This review aimed to systematically identify and critically appraise studies which either developed novel or updated existing prediction models for predicting school-age asthma.

METHODS

Three databases (MEDLINE, Embase and Web of Science Core Collection) were searched up to July 2019 to identify studies utilizing information from children ≤5 years of age to predict asthma in school-age children (6-13 years). Validation studies were evaluated as a secondary objective.

RESULTS

Twenty-four studies describing the development of 26 predictive models published between 2000 and 2019 were identified. Models were either regression-based (n = 21) or utilized machine learning approaches (n = 5). Nine studies conducted validations of six regression-based models. Fifteen (out of 21) models required additional clinical tests. Overall model performance, assessed by area under the receiver operating curve (AUC), ranged between 0.66 and 0.87. Models demonstrated moderate ability to either rule in or rule out asthma development, but not both. Where external validation was performed, models demonstrated modest generalizability (AUC range: 0.62-0.83).

CONCLUSION

Existing prediction models demonstrated moderate predictive performance, often with modest generalizability when independently validated. Limitations of traditional methods have shown to impair predictive accuracy and resolution. Exploration of novel methods such as machine learning approaches may address these limitations for future school-age asthma prediction.

Preschool Wheezing: Trajectories and Long-Term Treatment

Wheezing is very common in infancy affecting one in three children during the first 3 years of life. Several wheeze phenotypes have been identified and most rely on temporal pattern of symptoms. Assessing the risk of asthma development is difficult. Factors predisposing to onset and persistence of wheezing such as breastfeeding, atopy, indoor allergen exposure, environmental tobacco smoke and viral infections are analyzed. Inhaled corticosteroids are recommended as first choice of controller treatment in all preschool children irrespective of phenotype, but they are particularly beneficial in terms of fewer exacerbations in atopic children. Other therapeutic options include the addition of montelukast or the intermittent use of inhaled corticosteroids. Overuse of inhaled steroids must be avoided. Therefore, adherence to treatment and correct administration of the medications need to be checked at every visit.

Which Child with Asthma is a Candidate for Biological Therapies?

In asthmatic adults, monoclonals directed against Type 2 airway inflammation have led to major improvements in quality of life, reductions in asthma attacks and less need for oral corticosteroids. The paediatric evidence base has lagged behind. All monoclonals currently available for children are anti-eosinophilic, directed against the T helper (TH2) pathway. However, in children and in low and middle income settings, eosinophils may have important beneficial immunological actions. Furthermore, there is evidence that paediatric severe asthma may not be TH2 driven, phenotypes may be less stable than in adults, and adult biomarkers may be less useful. Children being evaluated for biologicals should undergo a protocolised assessment, because most paediatric asthma can be controlled with low dose inhaled corticosteroid if taken properly and regularly. For those with severe therapy resistant asthma, and refractory asthma which cannot be addressed, the two options if they have TH2 inflammation are omalizumab and mepolizumab. There is good evidence of efficacy for omalizumab, particularly in those with multiple asthma attacks, but only paediatric safety, not efficacy, data for mepolizumab. There is an urgent need for efficacy data in children, as well as data on biomarkers to guide therapy, if the right children are to be treated with these powerful new therapies.

Asthma predictive index as a useful diagnostic tool in preschool children: a cross-sectional study in Korea

BACKGROUND

It is challenging to diagnose asthma in preschool children. The asthma predictive index (API) has been used to predict asthma and decide whether to initiate treatment in preschool children.

PURPOSE

This study aimed to investigate the association between questionnaire-based current asthma with API, pulmonary function, airway hyperreactivity (AHR), fractional expiratory nitric oxide (FeNO), and atopic sensitization in preschool children.

METHODS

We performed a population-based cross-sectional study in 916 preschool children aged 4-6 years. We defined current asthma as the presence of both physician-diagnosed asthma and at least one wheezing episode within the previous 12 months using a modified International Study of Asthma and Allergies in Childhood questionnaire. Clinical and laboratory parameters were compared between groups according to the presence of current asthma.

RESULTS

The prevalence of current asthma was 3.9% in the study population. Children with current asthma showed a higher rate of positive bronchodilator response and loose and stringent API scores than children without current asthma. The stringent API was associated with current asthma with 72.2% sensitivity and 82.0% specificity. The diagnostic accuracy of the stringent API for current asthma was 0.771. However, no intergroup differences in spirometry results, methacholine provocation test results, FeNO level, or atopic sensitization rate were observed.

CONCLUSION

The questionnaire-based diagnosis of current asthma is associated with API, but not with spirometry, AHR, FeNO, or atopic sensitization in preschool children.

Special Considerations in Preschool Age

The diagnosis of asthma can be particularly difficult in young children, in whom wheezing is not always synonym with asthma. It is also difficult to predict which preschool children with wheeze will go on to be true asthmatics. In this chapter, we will characterize preschool wheezing and asthma and discuss early risk factors for the development of severe asthma. We will also review risk factors for severe acute wheezing in young children. Finally, we will describe the natural history and prognosis of wheezing and some of the attempts at early identification of children who will develop severe asthma.

Priorities for future research into asthma diagnostic tools: A PAN-EU consensus exercise from the European asthma research innovation partnership (EARIP)

The diagnosis of asthma is currently based on clinical history, physical examination and lung function, and to date, there are no accurate objective tests either to confirm the diagnosis or to discriminate between different types of asthma. This consensus exercise reviews the state of the art in asthma diagnosis to identify opportunities for future investment based on the likelihood of their successful development, potential for widespread adoption and their perceived impact on asthma patients. Using a two-stage e-Delphi process and a summarizing workshop, a group of European asthma experts including health professionals, researchers, people with asthma and industry representatives ranked the potential impact of research investment in each technique or tool for asthma diagnosis and monitoring. After a systematic review of the literature, 21 statements were extracted and were subject of the two-stage Delphi process. Eleven statements were scored 3 or more and were further discussed and ranked in a face-to-face workshop. The three most important diagnostic/predictive tools ranked were as follows: "New biological markers of asthma (eg genomics, proteomics and metabolomics) as a tool for diagnosis and/or monitoring," "Prediction of future asthma in preschool children with reasonable accuracy" and "Tools to measure volatile organic compounds (VOCs) in exhaled breath."

Transition for Adolescents and Young Adults With Asthma

Asthma is a complex, heterogenous medical condition which is very common in children and adults. The transition process from pediatric to adult health care services can be a challenge for young people with chronic medical conditions. The significant changes in physical and mental health during this time, as well as the many unique developmental and psychosocial challenges that occur during adolescence can complicate and impede transition if not adequately addressed and managed. The transition period can also be a challenging time for health professionals to assess readiness for transition and manage some of the complications which are particularly common during this time, including poor adherence to therapy, smoking, drug use, and emerging mental health conditions. The natural history, presentation, symptoms, and management of asthma is often significantly different when comparing pediatric and adult practice. In addition, management in infants, toddlers, school aged children, and adolescents differs significantly, offering an additional challenge to pediatric physicians managing asthmatic children and young people. Despite these challenges, if the transition process for young people with asthma is planned and performed in a formalized manner, many of these issues can be addressed, allowing the transition to occur smoothly despite changes that may occur in medical and psychosocial domains.

Validation of childhood asthma predictive tools: A systematic review

BACKGROUND

There is uncertainty about the clinical usefulness of currently available asthma predictive tools. Validation of predictive tools in different populations and clinical settings is an essential requirement for the assessment of their predictive performance, reproducibility and generalizability. We aimed to critically appraise asthma predictive tools which have been validated in external studies.

METHODS

We searched MEDLINE and EMBASE (1946-2017) for all available childhood asthma prediction models and focused on externally validated predictive tools alongside the studies in which they were originally developed. We excluded non-English and non-original studies. PROSPERO registration number is CRD42016035727.

RESULTS

From 946 screened papers, eight were included in the review. Statistical approaches for creation of prediction tools included chi-square tests, logistic regression models and the least absolute shrinkage and selection operator. Predictive models were developed and validated in general and high-risk populations. Only three prediction tools were externally validated: the Asthma Predictive Index, the PIAMA and the Leicester asthma prediction tool. A variety of predictors has been tested, but no studies examined the same combination. There was heterogeneity in definition of the primary outcome among development and validation studies, and no objective measurements were used for asthma diagnosis. The performance of tools varied at different ages of outcome assessment. We observed a discrepancy between the development and validation studies in the tools' predictive performance in terms of sensitivity and positive predictive values.

CONCLUSIONS

Validated asthma predictive tools, reviewed in this paper, provided poor predictive accuracy with performance variation in sensitivity and positive predictive value.

Development of an asthma risk factors scale (ARFS) for risk assessment asthma screening in children

BACKGROUND

The study objective was to create asthma risk factors scale (ARFS) score that would be correlated with the increased risk of asthma in Lebanese children. This scale would eventually be used both to identify children at risk and assess early diagnosis of asthma.

METHODS

A case-control study (study 1) of 1276 children (976 controls and 300 cases) and a cross-sectional study (study 2) of 1000 children were conducted using a parental questionnaire. Children aged between 3 and 16 years were screened for possible enrollment. The ARFS was created by combining the following risk factors: child's exposure to pesticides, detergent mixing, alcohol, smoking and drug intake during pregnancy and breastfeeding, the actual paternal and maternal smoking status and history of asthma, and the types of food the child consumes.

RESULTS

There was a significant increase in the risk assessment screening for asthma per 15 points increments of ARFS (p < 0.001 for trend). The score category 0-14.99 best-represented control individuals (88.8% controls), while a score higher than 45 represented asthmatic children best (98.4% asthmatics). The positive predictive value (disease positive/all positive by scale) came out as 94.02%, whereas the negative predictive value (disease negative/all negative by scale) was found to be 90.47%. These results were confirmed in the second study sample.

CONCLUSION

The ARFS is a simple and easy-to-use tool, composed of 15 questions, for the clinician risk assessment of asthma in children, taking into account the environmental exposure, parental history of asthma and dietary habits of the child. Its value for asthma diagnosis remains to be confirmed in future prospective studies, especially in children with chronic respiratory symptoms.

Individual risk assessment tool for school-age asthma prediction in UK birth cohort

Background

Current published asthma predictive tools have moderate positive likelihood ratios (+LR) but high negative likelihood ratios (−LR) based on their recommended cut‐offs, which limit their clinical usefulness.

Objective

To develop a simple clinically applicable asthma prediction tool within a population‐based birth cohort.

Method

Children from the Manchester Asthma and Allergy Study (MAAS) attended follow‐up at ages 3, 8 and 11 years. Data on preschool wheeze were extracted from primary‐care records. Parents completed validated respiratory questionnaires. Children were skin prick tested (SPT). Asthma at 8/11 years (school‐age) was defined as parentally reported (a) physician‐diagnosed asthma and wheeze in the previous 12 months or (b) ≥3 wheeze attacks in the previous 12 months. An asthma prediction tool (MAAS APT) was developed using logistic regression of characteristics at age 3 years to predict school‐age asthma.

Results

Of 336 children with physician‐confirmed wheeze by age 3 years, 117(35%) had school‐age asthma. Logistic regression selected 5 significant risk factors which formed the basis of the MAAS APT: wheeze after exercise; wheeze causing breathlessness; cough on exertion; current eczema and SPT sensitisation(maximum score 5). A total of 281(84%) children had complete data at age 3 years and were used to test the MAAS APT. Children scoring ≥3 were at high risk of having asthma at school‐age (PPV > 75%; +LR 6.3, −LR 0.6), whereas children who had a score of 0 had very low risk(PPV 9.3%; LR 0.2).

Conclusion

MAAS APT is a simple asthma prediction tool which could easily be applied in clinical and research settings.

Pathophysiological Mechanisms of Asthma

The recent Lancet commission has highlighted that "asthma" should be used to describe a clinical syndrome of wheeze, breathlessness, chest tightness, and sometimes cough. The next step is to deconstruct the airway into components of fixed and variable airflow obstruction, inflammation, infection and altered cough reflex, setting the airway disease in the context of extra-pulmonary co-morbidities and social and environmental factors. The emphasis is always on delineating treatable traits, including variable airflow obstruction caused by airway smooth muscle constriction (treated with short- and long-acting β-2 agonists), eosinophilic airway inflammation (treated with inhaled corticosteroids) and chronic bacterial infection (treated with antibiotics with benefit if it is driving the disease). It is also important not to over-treat the untreatable, such as fixed airflow obstruction. These can all be determined using simple, non-invasive tests such as spirometry before and after acute administration of a bronchodilator (reversible airflow obstruction); peripheral blood eosinophil count, induced sputum, exhaled nitric oxide (airway eosinophilia); and sputum or cough swab culture (bacterial infection). Additionally, the pathophysiology of risk domains must be considered: these are risk of an asthma attack, risk of poor airway growth, and in pre-school children, risk of progression to eosinophilic school age asthma. Phenotyping the airway will allow more precise diagnosis and targeted treatment, but it is important to move to endotypes, especially in the era of increasing numbers of biologicals. Advances in -omics technology allow delineation of pathways, which will be particularly important in TH2 low eosinophilic asthma, and also pauci-inflammatory disease. It is very important to appreciate the difficulties of cluster analysis; a patient may have eosinophilic airway disease because of a steroid resistant endotype, because of non-adherence to basic treatment, and a surge in environmental allergen burden. Sophisticated -omics approaches will be reviewed in this manuscript, but currently they are not being used in clinical practice. However, even while they are being evaluated, management of the asthmas can and should be improved by considering the pathophysiologies of the different airway diseases lumped under that umbrella term, using simple, non-invasive tests which are readily available, and treating accordingly.

Predicting Asthma Using Clinical Indexes

Asthma is no longer considered a single disease, but a common label for a set of heterogeneous conditions with shared clinical symptoms but associated with different cellular and molecular mechanisms. Several wheezing phenotypes coexist at preschool age but not all preschoolers with recurrent wheezing develop asthma at school-age; and since at the present no accurate single screening test using genetic or biochemical markers has been developed to determine which preschooler with recurrent wheezing will have asthma at school age, the asthma diagnosis still needs to be based on clinical predicted models or scores. The purpose of this review is to summarize the existing and most frequently used asthma predicting models, to discuss their advantages/disadvantages, and their accomplishment on all the necessary consecutive steps for any predictive model. Seven most popular asthma predictive models were reviewed (original API, Isle of Wight, PIAMA, modified API, ucAPI, APT Leicestersher, and ademAPI). Among these, the original API has a good positive LR~7.4 (increases the probability of a prediction of asthma by 2-7 times), and it is also simple: it only requires four clinical parameters and a peripheral blood sample for eosinophil count. It is thus an easy model to use in any rural or urban health care system. However, because its negative LR is not good, it cannot be used to rule out the development of asthma.

Life Cycle of Childhood Asthma: Prenatal, Infancy and Preschool, Childhood, and Adolescence

Asthma is a heterogeneous developmental disorder influenced by complex interactions between genetic susceptibility and exposures. Wheezing in infancy and early childhood is highly prevalent, with a substantial minority of children progressing to established asthma by school age, most of whom are atopic. Adolescence is a time of remission of symptoms with persistent lung function deficits. The transition to asthma in adulthood is not well understood.

A Pediatric Asthma Risk Score to better predict asthma development in young children

BACKGROUND

Asthma phenotypes are currently not amenable to primary prevention or early intervention because their natural history cannot be reliably predicted. Clinicians remain reliant on poorly predictive asthma outcome tools because of a lack of better alternatives.

OBJECTIVE

We sought to develop a quantitative personalized tool to predict asthma development in young children.

METHODS

Data from the Cincinnati Childhood Allergy and Air Pollution Study (n = 762) birth cohort were used to identify factors that predicted asthma development. The Pediatric Asthma Risk Score (PARS) was constructed by integrating demographic and clinical data. The sensitivity and specificity of PARS were compared with those of the Asthma Predictive Index (API) and replicated in the Isle of Wight birth cohort.

RESULTS

PARS reliably predicted asthma development in the Cincinnati Childhood Allergy and Air Pollution Study (sensitivity = 0.68, specificity = 0.77). Although both the PARS and API predicted asthma in high-risk children, the PARS had improved ability to predict asthma in children with mild-to-moderate asthma risk. In addition to parental asthma, eczema, and wheezing apart from colds, variables that predicted asthma in the PARS included early wheezing (odds ratio [OR], 2.88; 95% CI, 1.52-5.37), sensitization to 2 or more food allergens and/or aeroallergens (OR, 2.44; 95% CI, 1.49-4.05), and African American race (OR, 2.04; 95% CI, 1.19-3.47). The PARS was replicated in the Isle of Wight birth cohort (sensitivity = 0.67, specificity = 0.79), demonstrating that it is a robust, valid, and generalizable asthma predictive tool.

CONCLUSIONS

The PARS performed better than the API in children with mild-to-moderate asthma. This is significant because these children are the most common and most difficult to predict and might be the most amenable to prevention strategies.

Translating Asthma: Dissecting the Role of Metabolomics, Genomics and Personalized Medicine

The management of asthma has largely stagnated over the last 25 years, but we are at the dawning of a new age wherein -omics technology can help us manage the disease objectively and rationally. Even in this new scientific age, getting the basics of asthma management right remains essential. The new technologies which can be applied to multiple biological samples include genomics (study of the genome), transcriptomics (gene transcription), lipidomics, proteomics and metabolomics (lipids, proteins and metabolites, respectively) and breathomics, using exhaled breath as a source of biomarkers, which is of particular interest in view of its non-invasive nature in pediatrics. Important applications will include the diagnosis of airways disease, including its components; the pathways driving airway pathology; monitoring the response to treatment; and measuring future risk (asthma attacks, poor lung growth trajectory). With the advent of a wide range of novel biologicals to treat asthma, -omics technology to personalize therapy will be especially important. The U-BIOPRED (Europe) and SARP (USA) groups have been most active in this field, especially using bronchoscopically obtained samples to perform cluster analyses to define new asthma endotypes. However, stability over time and consistency between investigators is imperfect. This is perhaps unsurprising; results of biomarker studies in asthma will be a composite of the underlying disease, the (variable) effects of adverse drivers such as allergen exposure and pollution, the effects of treatment, and the effects of adherence or otherwise to treatment. Ultimately, the aim should be an exhaled breath based tool with a rapid result that can be used as a routine in the clinic. However, at the moment, there are as yet no clinical applications in children of -omics technology.

Prenatal exposure to perfluoralkyl substances (PFASs) associated with respiratory tract infections but not allergy- and asthma-related health outcomes in childhood

BACKGROUND

Prenatal exposure to perfluoralkyl substances (PFASs) has been reported to be associated with immunosuppression in early childhood, but with contradictory findings related to atopic and lung diseases.

AIM

We aimed to determine if prenatal exposure to PFASs is associated with asthma or other allergic diseases or respiratory tract infections in childhood.

METHODS

Nineteen PFASs were measured in cord blood available from 641 infants in the Environment and Childhood Asthma (ECA) prospective birth cohort study. The six most abundant PFASs were perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorooctanesulfonamide (PFOSA), perfluorohexane sulfonic acid (PFHxS), perfluorononanoic acid (PFNA), and perfluoroundecanoic acid (PFUnDA). Health outcomes were assessed at two and ten years of age, and included reported obstructive airways disease (wheeze by 10 years; asthma by 2 and 10 years; reduced lung function at birth; allergic rhinitis by 10 years), atopic dermatitis (AD) by 2 and 10 years, allergic sensitization by 10 years, and episodes of common respiratory tract infections (common cold by 2 years, lower respiratory tract infections (LRTI) by 10 years). The associations between exposure and health outcomes were examined using logistic and Poisson regression.

RESULTS

The number of reported airways infections were significantly associated with cord blood concentrations of PFAS; common colds by two years with PFUnDA (β = 0.11 (0.08-0.14)) and LRTIs from 0 to 10 years of age with PFOS (β = 0.50 (0.42-0.57)), PFOA (β = 0.28 (0.22-0.35)), PFOSA (β = 0.10 (0.06-0.14)), PFNA (β = 0.09 (0.03-0.14)) and PFUnDA (β = 0.18 (0.13-0.23)) concentrations. Neither reduced lung function at birth, asthma, allergic rhinitis, AD nor allergic sensitization were significantly associated with any of the PFASs.

CONCLUSION

Although prenatal exposure to PFASs was not associated with atopic or lung manifestations by 10 years of age, several PFASs were associated with an increased number of respiratory tract infections in the first 10 years of life, suggesting immunosuppressive effects of PFASs.

Stability and predictiveness of multiple trigger and episodic viral wheeze in preschoolers

BACKGROUND

In 2008, the European Respiratory Society Task Force proposed the terms multiple-trigger wheeze (MTW) and episodic (viral) wheeze (EVW) for children with wheezing episodes. We determined MTW and EVW prevalence, their 24-month stability and predictiveness for asthma.

METHODS

In total, 565 preschoolers (1-, 2- and 3-year-olds) in primary care with respiratory symptoms were followed until the age of 6 years when asthma was diagnosed. MTW status and EVW status were determined using questionnaire data collected at baseline and after one and 2 years. We distinguished 3 phenotypes and determined their 24-month stability, also accounting for treatment with inhaled corticosteroids (ICS). Logistic regression was used to analyse the phenotypes' associations with asthma.

RESULTS

Two hundred and eighty-one children had complete information. MTW and EVW were stable in 10 of 281 (3.6%) and 24 of 281 (8.5%), respectively. The odds of developing asthma for children with stable MTW and stable EVW were 14.4 (1.7-119) and 3.6 (1.2-11.3) times greater than those for children free of wheeze (for at least 1 year). ICS was associated with increased stability of MTW and EVW.

CONCLUSIONS

Stable multiple-trigger and stable episodic viral wheeze are relatively uncommon. However, 1- to 3-year-olds with stable MTW are at much increased risk of asthma.

Official American Thoracic Society Clinical Practice Guidelines: Diagnostic Evaluation of Infants with Recurrent or Persistent Wheezing

BACKGROUND

Infantile wheezing is a common problem, but there are no guidelines for the evaluation of infants with recurrent or persistent wheezing that is not relieved or prevented by standard therapies.

METHODS

An American Thoracic Society-sanctioned guideline development committee selected clinical questions related to uncertainties or controversies in the diagnostic evaluation of wheezing infants. Members of the committee conducted pragmatic evidence syntheses, which followed the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach. The evidence syntheses were used to inform the formulation and grading of recommendations.

RESULTS

The pragmatic evidence syntheses identified few studies that addressed the clinical questions. The studies that were identified constituted very low-quality evidence, consisting almost exclusively of case series with risk of selection bias, indirect patient populations, and imprecise estimates. The committee made conditional recommendations to perform bronchoscopic airway survey, bronchoalveolar lavage, esophageal pH monitoring, and a swallowing study. It also made conditional recommendations against empiric food avoidance, upper gastrointestinal radiography, and gastrointestinal scintigraphy. Finally, the committee recommended additional research about the roles of infant pulmonary function testing and food avoidance or dietary changes, based on allergy testing.

CONCLUSIONS

Although infantile wheezing is common, there is a paucity of evidence to guide clinicians in selecting diagnostic tests for recurrent or persistent wheezing. Our committee made several conditional recommendations to guide clinicians; however, additional research that measures clinical outcomes is needed to improve our confidence in the effects of various diagnostic interventions and to allow advice to be provided with greater confidence.

Corticosteroid Therapy During Acute Bronchiolitis in Patients Who Later Develop Asthma

BACKGROUND AND OBJECTIVE

Meta-analyses show that corticosteroids are not effective in patients with bronchiolitis. However, risk factors for asthma such as eczema or familial atopy prompt some practitioners to prescribe corticosteroids for bronchiolitis. We assessed if corticosteroid prescription is associated with shorter hospitalization for bronchiolitis among patients who later develop asthma.

METHODS

The Pediatric Health Information System database was interrogated for patients with bronchiolitis aged <2 years hospitalized between 2006 and 2015. Only patients who also later had a hospitalization for asthma and prescription of inhaled corticosteroids were included. For the initial bronchiolitis admission, use of mechanical ventilation defined "severe illness," and ICU admission without mechanical ventilation defined "moderate illness"; all other patients were deemed to have "mild illness." Variables associated (P < .10) with length of stay (LOS) in bivariate analysis were included in linear regression analysis.

RESULTS

During the bronchiolitis admission of 2479 children who were later hospitalized for asthma, corticosteroid prescription (n = 857) was associated with longer LOS in bivariate analysis (3 [2-4] vs 2 [2-4] days; P < .01) but not the multivariate model (P = .18) that included age, sex, comorbid conditions, bacterial pneumonia, and illness severity. Corticosteroid prescription was associated with shorter LOS among previously healthy children with moderate illness (4 [2-6] vs 5 [3-7] days; P = .02) but not those with mild or severe illness.

CONCLUSIONS

Corticosteroids were not associated with improved outcome in patients with bronchiolitis who were later hospitalized with asthma. Moderately ill patients with no comorbidities may warrant further study.

Risk factors for recurrent wheezing in the first year of life in the city of Córdoba, Argentina

BACKGROUND

Wheezing is a very common respiratory symptom in infants. The prevalence of wheezing in infants, conducted in developed countries shows prevalence rates ranging between 20% and 30%. However, we do not know the risk factors in our population of wheezing infants.

METHODS

A standardised written questionnaire (WQ-P1-EISL) in infants between 12 and 18 months of age residing in the city of Cordoba was used; population/sample included 1031 infants. Recurrent wheezing (RW) was defined as three or more episodes of wheezing reported by the parents during the first 12 months of life. Data obtained were coded in Epi-Info™ (version 7) and statistically analysed with SPSS (version 17.5) software in Spanish. Parametric tests (one-way ANOVA) were performed for identifying significantly associated variables.

RESULTS

The prevalence of wheezing infants was 39.7%; recurrent wheezing 33%; and severe wheezing 14.7%; 13.7% had pneumonia before the first year and of these 6.3% were hospitalised, multiple variables as risk factors for wheezing were found such as: >6 high airway infections and bronchiolitis in the first three months of life, smokers who smoke in the home among other risk factors and protective factors in those who have an elevated socioeconomic status.

CONCLUSION

It is known that persistent respiratory problems in children due to low socioeconomic status is a risk factor for wheezing, pneumonia and could be a determining factor in the prevalence and severity of RW in infants. Research suggests that there are areas for improvement in the implementation of new educational strategies.

Factors predicting persistence of early wheezing through childhood and adolescence: a systematic review of the literature

Background

For the early identification of persistent asthma symptoms among young children with recurrent wheezing, it would be helpful to identify all available studies that have identified at least one factor for predicting the persistence of early wheezing. The objective of the present study was to perform a systematic review of all studies that have identified factors that predict the persistence of symptoms among young patients with recurring wheezing.

Methods

A systematic review of relevant studies was conducted through searching in MEDLINE, EMBASE, CINHAL, and SCOPUS databases up to June 2016. Studies that identified predictors of persistence of wheezing illness among young children with recurrent wheezing were retrieved. Two independent reviewers screened the literature and extracted relevant data.

Results

The literature search returned 649 references, 619 of which were excluded due to their irrelevance. Five additional studies were identified from reference lists, and 35 studies were finally included in the review. Among all the identified predictors, the most frequently identified ones were the following: family asthma or atopy; personal history of atopic diseases; allergic sensitization early in life; and frequency, clinical pattern, or severity of wheezing/symptoms.

Conclusion

Parental asthma (especially maternal), parental allergy, eczema, allergic rhinitis, persistent wheezing, wheeze without colds, exercise-induced wheeze, severe wheezing episodes, allergic sensitization (especially polysensitization), eosinophils (blood or eosinophil cationic protein in nasal sample), and fraction of exhaled nitric oxide were risk factors predicting persistence of early wheezing through school age. All of them are included in conventional algorithms, for example, Asthma Predictive Index and its modifications, for predicting future asthma.

The Role of Sensitization to Allergen in Asthma Prediction and Prevention

The burden of asthma in childhood is considerable worldwide, although some populations are much more affected than others. Many attempts have been made by different investigators to identify the factors that could predict asthma development or persistence in childhood. In this review, the relation between atopic sensitization as an indicator of allergy and asthma in childhood will be discussed. Cross sectional studies, carried out in different countries, failed to show any firm correlation between asthma and atopic sensitization. Birth cohort mainly of infants at high risk for asthma and case-control studies showed that atopic sensitization was a risk factor for current asthma in children older than 6 years. In general, clear relations are observed mostly in affluent Western countries, whereas in less affluent countries, the picture is more heterogeneous. For the prediction of asthma development or persistence in school age children, other prerequisites should also be fulfilled such as family history of asthma and wheezing episodes at preschool age. Despite the conductance of different studies regarding the potential role of allergen avoidance for the primary prevention of childhood asthma, it does not seem that this approach is of benefit for primary prevention purposes. However, the identification of children at risk for asthma is of benefit as these subjects could be provided with the best management practices and with the appropriate secondary prevention measures.

Asthma phenotypes in children and stratified pharmacological treatment regimens

INTRODUCTION

Asthma is the most common inflammatory disease in childhood. The interaction of genetic, environmental and host factors may contribute to the development of childhood asthma and defines its progress, including persistence and severity. Until now, various classifications of childhood asthma phenotypes have been suggested based on patient's age during onset of symptoms, type of inflammatory cells, response to treatment and disease severity. Many efforts have been carried out to identify childhood asthma phenotypes and to clarify which are the risk factors that define asthma prediction and the response to therapy. The identification of asthma phenotypes has not only prognostic but also therapeutic role. However, the classification of asthma phenotypes is complex due to the heterogeneity of the disease. Areas covered: The current childhood asthma phenotypes and the new therapeutic strategies for each phenotype are reviewed. Expert commentary: There are multiple phenotypes in childhood asthma and it is crucial to define them before the initiation of personalized treatment. Both the therapeutic strategy and monitoring should follow the recent guidelines.

Asthma phenotypes in childhood

INTRODUCTION

Asthma is no longer thought of as a single disease, but rather a collection of varying symptoms expressing different disease patterns. One of the ongoing challenges is understanding the underlying pathophysiological mechanisms that may be responsible for the varying responses to treatment. Areas Covered: This review provides an overview of our current understanding of the asthma phenotype concept in childhood and describes key findings from both conventional and data-driven methods. Expert Commentary: With the vast amounts of data generated from cohorts, there is hope that we can elucidate distinct pathophysiological mechanisms, or endotypes. In return, this would lead to better patient stratification and disease management, thereby providing true personalised medicine.

Evaluating early-life asthma definitions as a marker for subsequent asthma in an electronic medical record setting

BACKGROUND

Case definitions for asthma incidence in early life vary between studies using medical records to define disease. This study assessed the impact of different approaches to using medical records on estimates of asthma incidence by age 3 and determined the validity of early-life asthma case definitions in predicting school-age asthma.

METHODS

Asthma diagnoses and medications by age 3 were used to classify 7103 children enrolled in Kaiser Permanente Georgia according to 14 definitions of asthma. School-age asthma was defined as an asthma diagnosis between ages 5 and 8. Sensitivity (probability of asthma by age 3 given school-age asthma), specificity (probability of no asthma by age 3 given no school-age asthma), positive and negative predictive values (probability of (no) school-age asthma given (no) asthma by age 3), and likelihood ratios (combining sensitivity and specificity) were used to determine predictive ability.

RESULTS

9.0-35.2% of children were classified as asthmatic by age 3 depending on asthma case definition. Early-life asthma classifications were more specific than sensitive and were better at identifying children who would not have school-age asthma (negative predictive values: 80.7-86.6%) than at predicting children who would have school-age asthma (positive predictive values: 43.5-71.5%).

CONCLUSIONS

Choice of case definition had a large impact on the estimate of asthma incidence. While ability to predict school-age asthma was limited, several case definitions performed similarly to clinical asthma prediction tools used in previous asthma research (e.g., the Asthma Predictive Index).

Monitoring asthma in childhood

The goal of asthma treatment is to obtain clinical control and reduce future risks to the patient. However, to date there is limited evidence on how to monitor patients with asthma. Childhood asthma introduces specific challenges in terms of deciding what, when, how often, by whom and in whom different assessments of asthma should be performed. The age of the child, the fluctuating course of asthma severity, variability in clinical presentation, exacerbations, comorbidities, socioeconomic and psychosocial factors, and environmental exposures may all influence disease activity and, hence, monitoring strategies. These factors will be addressed in herein.

We identified large knowledge gaps in the effects of different monitoring strategies in children with asthma. Studies into monitoring strategies are urgently needed, preferably in collaborative paediatric studies across countries and healthcare systems.

Monitoring asthma in children is essential for disease control and should reflect age, triggers and disease activityhttp://ow.ly/J0k7f

A systematic review of predictive models for asthma development in children

BACKGROUND

Asthma is the most common pediatric chronic disease affecting 9.6 % of American children. Delay in asthma diagnosis is prevalent, resulting in suboptimal asthma management. To help avoid delay in asthma diagnosis and advance asthma prevention research, researchers have proposed various models to predict asthma development in children. This paper reviews these models.

METHODS

A systematic review was conducted through searching in PubMed, EMBASE, CINAHL, Scopus, the Cochrane Library, the ACM Digital Library, IEEE Xplore, and OpenGrey up to June 3, 2015. The literature on predictive models for asthma development in children was retrieved, with search results limited to human subjects and children (birth to 18 years). Two independent reviewers screened the literature, performed data extraction, and assessed article quality.

RESULTS

The literature search returned 13,101 references in total. After manual review, 32 of these references were determined to be relevant and are discussed in the paper. We identify several limitations of existing predictive models for asthma development in children, and provide preliminary thoughts on how to address these limitations.

CONCLUSIONS

Existing predictive models for asthma development in children have inadequate accuracy. Efforts to improve these models' performance are needed, but are limited by a lack of a gold standard for asthma development in children.

Childhood asthma prediction models: a systematic review

Early identification of children at risk of developing asthma at school age is crucial, but the usefulness of childhood asthma prediction models in clinical practice is still unclear. We systematically reviewed all existing prediction models to identify preschool children with asthma-like symptoms at risk of developing asthma at school age. Studies were included if they developed a new prediction model or updated an existing model in children aged 4 years or younger with asthma-like symptoms, with assessment of asthma done between 6 and 12 years of age. 12 prediction models were identified in four types of cohorts of preschool children: those with health-care visits, those with parent-reported symptoms, those at high risk of asthma, or children in the general population. Four basic models included non-invasive, easy-to-obtain predictors only, notably family history, allergic disease comorbidities or precursors of asthma, and severity of early symptoms. Eight extended models included additional clinical tests, mostly specific IgE determination. Some models could better predict asthma development and other models could better rule out asthma development, but the predictive performance of no single model stood out in both aspects simultaneously. This finding suggests that there is a large proportion of preschool children with wheeze for which prediction of asthma development is difficult.

Gender differences in the relationship between body mass index (BMI) changes and the prevalence and severity of wheezing and asthma in the first year of life

BACKGROUND

Rapid weight gain has been recently associated with asthma at school age, but its influence in respiratory symptoms during infancy is still unknown.

METHODS

Answers from 6541 parents living in six different cities of Brazil to the International Study of Wheezing in Infants (EISL) questionnaire were analysed. Data from reported weight and height at birth and at one year were used to calculate BMI. Rapid body mass index (BMI) gain was defined by the difference in BMI superior to 1.0z and excessive by the difference superior to 2.0z.

RESULTS

Rapid BMI gain was found in 45.8% infants and excessive in 24.4%. Boys showed a significantly higher BMI gain than girls. Girls with rapid BMI gain showed a significantly higher prevalence of hospitalisation for wheezing (8.8% vs. 6.4%; aOR: 1.4, 95%CI: 1.1-1.8), severe wheezing (18.1% vs. 15.0%; aOR: 1.3, 95%CI: 1.0-1.5) and medical diagnosis of asthma (7.5% vs. 5.7%; aOR: 1.3, 95%CI: 1.0-1.7). Girls with excessive BMI gain also had a significantly higher prevalence of hospitalisation for wheezing (9.8% vs. 6.7%; aOR: 1.5, 95%CI: 1.1-2.0) and severe wheezing (18.9% vs. 15.5%; aOR: 1.3, 95%CI: 1.0-1.6). No significant association was found among boys.

CONCLUSIONS

The majority of the evaluated infants showed BMI gain above expected in the first year of life. Although more commonly found in boys, rapid and excessive BMI gain in the first year of life was significantly related to more severe patterns of wheezing in infancy among girls.

Early risk factors for pubertal asthma

BACKGROUND

Early life risk factors are previously described for childhood asthma, but less is known related to asthma in adolescence. We aimed to investigate early risk factors (before 2 years) for pubertal asthma and secondarily for pubertal asthma phenotypes based upon allergic comorbidities.

METHODS

Based on data from 550 adolescents in the prospective birth cohort 'Environment and Childhood Asthma' study, subjects were categorized by recurrent bronchial obstruction (rBO) 0-2 years, asthma 2-10 years, and pubertal asthma from 10 to 16 years including incident asthma in puberty and asthma in remission from 10 to 16 years or as never rBO/asthma 0-16 years. Asthma in puberty was further classified based on the comorbidities atopic dermatitis and allergic rhinitis (AR) from 10 to 16 years. Twenty-three common asthma risk factors identified by 2 years of age, including frequency and persistence of bronchial obstruction (severity score), were analysed by weighted logistic regression for each phenotype.

RESULTS

In adjusted models, the risk of pubertal asthma increased significantly with higher severity score, parental rhinitis, being the firstborn child, and familial stress around birth. Pubertal asthma in remission was significantly associated with severity score and number of lower respiratory tract infections and inversely associated with breastfeeding beyond 4 months. Pubertal incident asthma was more common among firstborn children. All asthma phenotypes with allergic diseases were significantly associated with severity score, whereas familial perinatal stress increased the risk of asthma only. Asthma combined with AR was associated with parental asthma and being firstborn, whereas the risk of asthma with both atopic dermatitis and AR increased with higher paternal education, atopic dermatitis, being firstborn, and familial perinatal stress.

CONCLUSION AND CLINICAL RELEVANCE

Important early risk factors for pubertal asthma were early airways obstruction, parental rhinitis, being the firstborn child, and perinatal familial stress.

Allergic diseases and the effect of inhaled epinephrine in children with acute bronchiolitis: follow-up from the randomised, controlled, double-blind, Bronchiolitis ALL trial

BACKGROUND

Although use of inhaled bronchodilators in infants with acute bronchiolitis is not supported by evidence-based guidelines, it is often justified by the belief in a subgroup effect in individuals developing atopic disease. We aimed to assess if inhaled epinephrine during acute bronchiolitis in infancy would benefit patients with later recurrent bronchial obstruction, atopic eczema, or allergic sensitisation.

METHODS

In the randomised, double-blind, multicentre Bronchiolitis ALL trial, 404 infants with moderate-to-severe acute bronchiolitis were recruited from eight hospitals in Norway to receive either inhaled epinephrine or saline up to every second hour throughout the hospital stay. Randomisation was done centrally, and the two study medications (20 mg/mL racemic epinephrine or 0.9% saline) were prepared in identical bottles. The dose given depended on the infant's weight: 0.10 mL, less than 5 kg; 0.15 mL, 5-6.9 kg; 0.2 mL, 7-9.9 kg; and 0.25 mL, 10 kg or more; all dissolved in 2 mL of 0.9% saline before nebulisation. The primary outcome was the length of hospital stay. In this follow-up study, 294 children were reinvestigated at 2 years of age with an interview, a clinical examination, and a skin prick test for 17 allergens, determining bronchial obstruction, atopic eczema, and allergic sensitisation, on which subgroup analyses were done. Analyses were done by intention to treat. The trial has been completed and is registered at ClinicalTrials.gov (number NCT00817466) and EUDRACT (number 2009-012667-34).

FINDINGS

Length of stay did not differ between patients who received inhaled epinephrine versus saline in the subgroup of infants who developed recurrent bronchial obstruction by age 2 years (143 [48.6%] of 294 patients; p(interaction)=0.40). However, the presence of atopic eczema or allergic sensitisation by the age of 2 years (n=77) significantly interacted with the treatment effect of inhaled epinephrine (p(interaction)=0.02); the length of stay (mean 80.3 h, 95% CI 72.8-87.9) was significantly shorter in patients receiving inhaled epinephrine versus saline in patients without allergic sensitisation or atopic eczema by 2 years (-19.9 h, -33.1 to -6.3; p=0.003). No significant differences were found in length of hospital stay in response to epinephrine or saline in children with atopic eczema or allergic sensitisation by 2 years (+16.2 h, -11.0 to 43.3; p=0.24).

INTERPRETATION

Contrary to our hypothesis, hospital length of stay for bronchiolitis was not reduced by administration of inhaled epinephrine in infants who subsequently developed atopic eczema, allergic sensitisation, or recurrent bronchial obstruction. The present study does not support an individual trial of inhaled epinephrine in acute bronchiolitis in children with increased risk of allergic diseases.

FUNDING

Medicines for Children Network, Norway.

Predicting asthma in preschool children at high risk presenting in primary care: development of a clinical asthma prediction score

BACKGROUND

A setting-specific asthma prediction score for preschool children with wheezing and/or dyspnoea presenting in primary healthcare is needed since existing indices are mainly based on general populations.

AIMS

To find an optimally informative yet practical set of predictors for the prediction of asthma in preschool children at high risk who present in primary healthcare.

METHODS

A total of 771 Dutch preschool children at high risk of asthma were followed prospectively until the age of six years. Data on asthma symptoms and environmental conditions were obtained using validated questionnaires and specific IgE was measured. At the age of six years the presence of asthma was assessed based on asthma symptoms, medication, and bronchial hyper-responsiveness. A clinical asthma prediction score (CAPS) was developed using bootstrapped multivariable regression methods.

RESULTS

In all, 438 children (56.8%) completed the study; the asthma prevalence at six years was 42.7%. Five parameters optimally predicted asthma: age, family history of asthma or allergy, wheezing-induced sleep disturbances, wheezing in the absence of common colds, and specific IgE. CAPS scores range from 0 to 11 points; scores <3 signified a negative predictive value of 78.4% while scores of >7 signified a positive predictive value of 74.3%.

CONCLUSIONS

We have developed an easy-to-use CAPS for preschool children with symptoms suggesting asthma who present in primary healthcare. After suitable validation, the CAPS may assist in guiding shared decision-making to tailor the need for medical or non-medical interventions. External validation of the CAPS is needed.

Childhood asthma-predictive phenotype

Wheezing is a fairly common symptom in early childhood, but only some of these toddlers will experience continued wheezing symptoms in later childhood. The definition of the asthma-predictive phenotype is in children with frequent, recurrent wheezing in early life who have risk factors associated with the continuation of asthma symptoms in later life. Several asthma-predictive phenotypes were developed retrospectively based on large, longitudinal cohort studies; however, it can be difficult to differentiate these phenotypes clinically as the expression of symptoms, and risk factors can change with time. Genetic, environmental, developmental, and host factors and their interactions may contribute to the development, severity, and persistence of the asthma phenotype over time. Key characteristics that distinguish the childhood asthma-predictive phenotype include the following: male sex; a history of wheezing, with lower respiratory tract infections; history of parental asthma; history of atopic dermatitis; eosinophilia; early sensitization to food or aeroallergens; or lower lung function in early life.

A new index to identify risk of multi-trigger wheezing in infants with first episode of wheezing

OBJECTIVE

Identification of young children who are likely to have multi-trigger wheezing is very important for early diagnosis and treatment of asthma. We investigate an index for predicting multi-trigger wheezing in infants with first episode of wheezing.

METHODS

One-hundred twenty-eight infants (2-20 months) with first episode of wheezing were followed for two years. Personal and family history of atopic diseases was recorded. Wheezing severity was evaluated using the Preschool Respiratory Assessment Measure. Sputum samples were collected from patients, stained with hematoxylin and eosin and studied by optical microscopy. The largest Creola body in sputum was located and the number of shed exfoliated airway epithelial cells (EAECs) counted. Recurrent wheezing was observed and classified as multi-trigger wheezing or non-multi-trigger wheezing. The predictive value of EAECs, family or personal history of atopic disease and the severity of wheezing for subsequent development of multi-trigger wheezing was analyzed.

RESULTS

Better predictive performance was achieved by considering the three measures together than by considering each separately. Receiver operator characteristic analysis showed that an index combining wheezing severity score of 9495 sputum EAECs and a family or personal history of atopic disease had a sensitivity of 95.1%, specificity of 74.2%, a positive predictive value of 58.6% and a negative predictive value of 93.6% for prediction of multi-trigger wheezing.

CONCLUSION

For infants with first episode of wheezing, wheezing severity score, family or personal history of atopic disease and number of EAECs in sputum can predict future multi-trigger wheezing.

Evaluation of the modified asthma predictive index in high-risk preschool children

BACKGROUND

Prediction of subsequent school-age asthma during the preschool years has proven challenging.

OBJECTIVE

To confirm in a post hoc analysis the predictive ability of the modified Asthma Predictive Index (mAPI) ina high-risk cohort and a theoretical unselected population. We also tested a potential mAPI modification with a 2-wheezing episode requirement (m2API) in the same populations.

METHODS

Subjects (n [ 289) with a family history of allergy and/or asthma were used to predict asthma at age 6, 8, and 11 years with the use of characteristics collected during the first 3 years of life. The mAPI and the m2API were tested for predictive value.

RESULTS

For the mAPI and m2API, school-age asthma prediction improved from 1 to 3 years of age. The mAPI had high predictive value after a positive test (positive likelihood ratio ranging from 4.9 to 55) for asthma development at years 6,8, and 11. Lowering the number of wheezing episodes to 2(m2API) lowered the predictive value after a positive test(positive likelihood ratio ranging from 1.91 to 13.1) without meaningfully improving the predictive value of a negative test.Posttest probabilities for a positive mAPI reached 72% and 90%in unselected and high-risk populations, respectively.

CONCLUSIONS

In a high-risk cohort, a positive mAPI greatly increased future asthma probability (eg, 30% pretest probability to 90% posttest probability) and is a preferred predictive test to them 2API. With its more favorable positive posttest probability,the mAPI can aid clinical decision making in assessing future asthma risk for preschool-age children.

Diagnosis, management, and prognosis of preschool wheeze

Preschool children (ie, those aged 5 years or younger) with wheeze consume a disproportionately high amount of health-care resources compared with older children and adults with wheeze or asthma, representing a diagnostic challenge. Although several phenotype classifications have been described, none have been validated to identify individuals responding to specific therapeutic approaches. Several risk factors related to genetic, prenatal, and postnatal environment are associated with preschool wheezing. Findings from several cohort studies have shown that preschool children with wheeze have deficits in lung function at 6 years of age that persisted until early and middle adulthood, suggesting increased susceptibility in the first years of life that might lead to persistent sequelae. Daily inhaled corticosteroids seem to be the most effective therapy for recurrent wheezing in trials of children with interim symptoms or atopy; intermittent high-dose inhaled corticosteroids are effective in moderate-to-severe viral-induced wheezing without interim symptoms. The role of leukotriene receptor antagonist is less clear. Interventions to modify the short-term and long-term outcomes of preschool wheeze should be a research priority.

The potential to predict the course of childhood asthma

Many children experience pre-school or early childhood wheezing. In a significant proportion symptoms disappear as the child grows, but others have persistent and troublesome asthma which can be life-long. Tools to predict course of disease in young children are a priority for families and clinicians. This review summarizes evidence from several longitudinal population-based birth-cohort studies that have identified risk factors for persistence and remission of childhood asthma. These factors include clinical characteristics, environmental and other exposures, familial factors, biomarkers of allergic inflammation, measurements of lung function and airway responsiveness, and genetic variants. This review also introduces the concept of polygenic risk and genetic risk scores, and describes results from a recent study that suggests promise for the use of genetic information in predicting the course of childhood asthma. We conclude with a discussion of implications and future directions.

Role of infections in the induction and development of asthma: genetic and inflammatory drivers

Genetic and environmental factors interact to initiate and even maintain the course of asthma. As one of the highly risky environmental factors, infections in predisposed individuals can promote asthma development and exacerbations and/or prolong symptoms. This review will describe our current understanding of the genetic markers of innate immunity in the induction and development of asthma, the diverse roles of infections in modulating allergic inflammation, host susceptibility to infections and subsequent acute exacerbations in an allergic setting, and the therapeutic or preventive implications of existing knowledge. Current challenges and future directions in basic and clinical research of asthma are also discussed.

A simple asthma prediction tool for preschool children with wheeze or cough

BACKGROUND

Many preschool children have wheeze or cough, but only some have asthma later. Existing prediction tools are difficult to apply in clinical practice or exhibit methodological weaknesses.

OBJECTIVE

We sought to develop a simple and robust tool for predicting asthma at school age in preschool children with wheeze or cough.

METHODS

From a population-based cohort in Leicestershire, United Kingdom, we included 1- to 3-year-old subjects seeing a doctor for wheeze or cough and assessed the prevalence of asthma 5 years later. We considered only noninvasive predictors that are easy to assess in primary care: demographic and perinatal data, eczema, upper and lower respiratory tract symptoms, and family history of atopy. We developed a model using logistic regression, avoided overfitting with the least absolute shrinkage and selection operator penalty, and then simplified it to a practical tool. We performed internal validation and assessed its predictive performance using the scaled Brier score and the area under the receiver operating characteristic curve.

RESULTS

Of 1226 symptomatic children with follow-up information, 345 (28%) had asthma 5 years later. The tool consists of 10 predictors yielding a total score between 0 and 15: sex, age, wheeze without colds, wheeze frequency, activity disturbance, shortness of breath, exercise-related and aeroallergen-related wheeze/cough, eczema, and parental history of asthma/bronchitis. The scaled Brier scores for the internally validated model and tool were 0.20 and 0.16, and the areas under the receiver operating characteristic curves were 0.76 and 0.74, respectively.

CONCLUSION

This tool represents a simple, low-cost, and noninvasive method to predict the risk of later asthma in symptomatic preschool children, which is ready to be tested in other populations.

Severe bronchiolitis in infancy: can asthma in adolescence be predicted?

Bronchiolitis in infancy is a risk factor for development of asthma in the first decades of life, although the majority may be asymptomatic at school age. Respiratory symptoms are common in early life, and prediction of later asthma may be challenging. We aimed to study if simple clinical variables assessed at 2 years of age could predict asthma at 11 years of age and thereby provide a basis for follow-up and treatment after bronchiolitis in infancy. The study included 105 children hospitalized for bronchiolitis during their first year of life. Of these, 101 (96.2%) participated in the first follow-up at 2 years of age and 93 (88.6%) in the second follow-up at age 11. The overall prevalence of asthma at 11 years of age was 22.6%. Among the risk factors assessed at 2 years of age, recurrent wheeze appeared most important (odds ratio for later asthma: 7.2; 95% confidence interval: 1.3, 41.6; P = 0.015). Tested separately, recurrent wheeze had high sensitivity (90.5%), but low specificity (58.3%), low negative likelihood ratio (LR) (0.2) and low negative post-test probability (4.5%); indicating that absence of recurrent wheeze was better suited to exclude than to predict asthma at 11 years of age. Combining recurrent wheeze with either parental atopy, parental asthma or atopic dermatitis improved the specificity (>80), positive LR (>3) and positive post-test probability (∼50%), rendering the combinations more appropriate for the prediction of later asthma. In conclusion, after bronchiolitis in infancy, simple clinical non-invasive variables assessed at 2 years of age could predict asthma at 11 years of age with reasonable accuracy. However, the data were better suited to exclude than to predict later asthma.