Predicting persistence of wheezing: one algorithm does not fit all

Asthma and Allergy: Unravelling a Tangled Relationship with a Focus on New Biomarkers and Treatment

Asthma is a major driver of health care costs across ages. Despite widely disseminated asthma-treatment guidelines and a growing variety of effective therapeutic options, most patients still experience symptoms and/or refractoriness to standard of care treatments. As a result, most patients undergo a further intensification of therapy to optimize symptom control with a subsequent increased risk of side effects. Raising awareness about the relevance of evaluating aeroallergen sensitizations in asthmatic patients is a key step in better informing clinical practice while new molecular tools, such as the component resolved diagnosis, may be of help in refining the relationship between sensitization and therapeutic recommendations. In addition, patient care should benefit from reliable, easy-to-measure and clinically accessible biomarkers that are able to predict outcome and disease monitoring. To attain a personalized asthma management and to guide adequate treatment decisions, it is of paramount importance to expand clinicians' knowledge about the tangled relationship between asthma and allergy from a molecular perspective. Our review explores the relevance of allergen testing along the asthma patient's journey, with a special focus on recurrent wheezing children. Here, we also discuss the unresolved issues regarding currently available biomarkers and summarize the evidence supporting the eosinophil-derived neurotoxin as promising biomarker.

The Simple 10-Item Predicting Asthma Risk in Children Tool to Predict Childhood Asthma-An External Validation

BACKGROUND

External validation of prediction models is important to assess generalizability to other populations than the one used for model development. The Predicting Asthma Risk in Children (PARC) tool, developed in the Leicestershire Respiratory Cohort (LRC), uses information on preschool respiratory symptoms to predict asthma at school age.

OBJECTIVE

We performed an external validation of PARC using the Avon Longitudinal Study of Parents and Children (ALSPAC).

METHODS

We defined inclusion criteria, prediction score items at baseline and asthma at follow-up in ALSPAC to match those used in LRC using information from parent-reported questionnaires. We assessed performance of PARC by calculating sensitivity, specificity, predictive values, likelihood ratios, area under the curve (AUC), Brier score and Nagelkerke's R2. Sensitivity analyses varied inclusion criteria, scoring items, and outcomes.

RESULTS

The validation population included 2690 children with preschool respiratory symptoms of whom 373 (14%) had asthma at school age. Discriminative performance of PARC was similar in ALSPAC (AUC = 0.77, Brier score 0.13) as in LRC (0.78, 0.22). The score cutoff of 4 showed the highest sum of sensitivity (69%) and specificity (76%) and positive and negative likelihood ratios of 2.87 and 0.41, respectively. Changes to inclusion criteria, scoring items, or outcome definitions barely altered the prediction performance.

CONCLUSIONS

Performing equally well in the validation cohort as in the development cohort, PARC is a valid tool for predicting asthma in population-based cohorts. Its use in clinical practice is ready to be tested.

Report from the National Institute of Allergy and Infectious Diseases workshop on "Atopic dermatitis and the atopic march: Mechanisms and interventions"

Atopic dermatitis (AD) affects up to 20% of children worldwide and is an increasing public health problem, particularly in developed countries. Although AD in infants and young children can resolve, there is a well-recognized increased risk of sequential progression from AD to other atopic diseases, including food allergy (FA), allergic rhinitis, allergic asthma, and allergic rhinoconjunctivitis, a process referred to as the atopic march. The mechanisms underlying the development of AD and subsequent progression to other atopic comorbidities, particularly FA, are incompletely understood and the subject of intense investigation. Other major research objectives are the development of effective strategies to prevent AD and FA, as well as therapeutic interventions to inhibit the atopic march. In 2017, the Division of Allergy, Immunology, and Transplantation of the National Institute of Allergy and Infectious Diseases sponsored a workshop to discuss current understanding and important advances in these research areas and to identify gaps in knowledge and future research directions. International and national experts in the field were joined by representatives from several National Institutes of Health institutes. Summaries of workshop presentations, key conclusions, and recommendations are presented herein.

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.

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.

MLBCD: a machine learning tool for big clinical data

Background

Predictive modeling is fundamental for extracting value from large clinical data sets, or “big clinical data,” advancing clinical research, and improving healthcare. Machine learning is a powerful approach to predictive modeling. Two factors make machine learning challenging for healthcare researchers. First, before training a machine learning model, the values of one or more model parameters called hyper-parameters must typically be specified. Due to their inexperience with machine learning, it is hard for healthcare researchers to choose an appropriate algorithm and hyper-parameter values. Second, many clinical data are stored in a special format. These data must be iteratively transformed into the relational table format before conducting predictive modeling. This transformation is time-consuming and requires computing expertise.

Methods

This paper presents our vision for and design of MLBCD (Machine Learning for Big Clinical Data), a new software system aiming to address these challenges and facilitate building machine learning predictive models using big clinical data.

Results

The paper describes MLBCD’s design in detail.

Conclusions

By making machine learning accessible to healthcare researchers, MLBCD will open the use of big clinical data and increase the ability to foster biomedical discovery and improve care.

What lessons can be learned about asthma phenotypes in children from cohort studies?

'Phenotyping' asthma by multivariate analyses and more recently by unsupervised analysis has been performed in children cohorts. We describe the key findings that have emerged from these cohorts. It would appear that there are three wheeze phenotypes in children of preschool age: the mild episodic viral wheeze phenotype; the multitrigger atopic wheeze; and, less often encountered, the severe non-atopic wheeze. Early onset of allergy in asthma (more prevalent in boys) is associated with poor prognosis unlike the severe non-atopic wheeze phenotype which has a female predominance. The prognosis of the severe non-atopic wheeze depends on time of onset (early or late) of allergic expression. At school age, the risk of severe asthmatic exacerbations is associated with eosinophil predominant inflammation frequently related to allergic asthma, whereas neutrophil inflammation is associated with moderate-to-severe asthma with poorer lung function. Nevertheless, allergic asthma is also a heterogeneous disease with a severe allergic phenotype strongly associated with atopic dermatitis and very high eosinophil-driven inflammatory markers. Further studies are required to find non-invasive biological markers in very young children to better define wheezing phenotypes associated with an elevated risk of developing severe asthma with a view to personalizing treatment.

The novel 10-item asthma prediction tool: external validation in the German MAS birth cohort

Background

A novel non-invasive asthma prediction tool from the Leicester Cohort, UK, forecasts asthma at age 8 years based on 10 predictors assessed in early childhood, including current respiratory symptoms, eczema, and parental history of asthma.

Objective

We aimed to externally validate the proposed asthma prediction method in a German birth cohort.

Methods

The MAS-90 study (Multicentre Allergy Study) recorded details on allergic diseases prospectively in about yearly follow-up assessments up to age 20 years in a cohort of 1,314 children born 1990. We replicated the scoring method from the Leicester cohort and assessed prediction, performance and discrimination. The primary outcome was defined as the combination of parent-reported wheeze and asthma drugs (both in last 12 months) at age 8. Sensitivity analyses assessed model performance for outcomes related to asthma up to age 20 years.

Results

For 140 children parents reported current wheeze or cough at age 3 years. Score distribution and frequencies of later asthma resembled the Leicester cohort: 9% vs. 16% (MAS-90 vs. Leicester) of children at low risk at 3 years had asthma at 8 years, at medium risk 45% vs. 48%. Performance of the asthma prediction tool in the MAS-90 cohort was similar (Brier score 0.22 vs. 0.23) and discrimination slightly better than in the original cohort (area under the curve, AUC 0.83 vs. 0.78). Prediction and discrimination were robust against changes of inclusion criteria, scoring and outcome definitions. The secondary outcome ‘physicians’ diagnosed asthma at 20 years' showed the highest discrimination (AUC 0.89).

Conclusion

The novel asthma prediction tool from the Leicester cohort, UK, performed well in another population, a German birth cohort, supporting its use and further development as a simple aid to predict asthma risk in clinical settings.

Characterizing wheeze phenotypes to identify endotypes of childhood asthma, and the implications for future management

It is now a commonly held view that asthma is not a single disease, but rather a set of heterogeneous diseases sharing common symptoms. One of the major challenges in treating asthma is understanding these different asthma phenotypes and their underlying biological mechanisms. This review gives an epidemiological perspective of our current understanding of the different phenotypes that develop from birth to childhood that come under the umbrella term 'asthma'. The review focuses mainly on publications from longitudinal birth cohort studies where the natural history of asthma symptoms is observed over time in the whole population. Identifying distinct pathophysiological mechanisms for these different phenotypes will potentially elucidate different asthma endotypes, ultimately leading to more effective treatment and management strategies.

Wheeze phenotypes in young children have different courses during the preschool period

BACKGROUND

Rules for predicting the course of asthma in wheezy infants have low specificity.

OBJECTIVE

To determine if the novel phenotypes-mild early viral wheeze (EVW), atopic multiple-trigger wheeze (MTW), and nonatopic uncontrolled wheeze (NAUW)-have different courses during the preschool period.

METHODS

Part of the prospectively followed Trousseau Asthma Program cohort was phenotyped using cluster analysis with 12 parameters (sex, asthma severity and control with inhaled corticosteroid [ICS], parental asthma, allergic rhinitis, eczema, food allergy, EVW or MTW, and allergen exposure trigger). Wheezing trajectories were assessed by crossing the original phenotypes with the phenotypes obtained at 5 years.

RESULTS

Four clusters were identified at 5 years of age: asymptomatic children (n = 47) with no wheezing (98%), children with mild EVW (n = 40, 87% with EVW, 50% with EVW controlled with low-dose ICS), those with atopic MTW (n = 30, 100% with MTW, only 17% with MTW controlled with low-dose ICS, more significant for pollen asthmatic trigger), and those with atopic severe UW (n = 33, 63% with UW uncontrolled despite high doses of ICS, more significant for allergic rhinitis and dust as asthmatic trigger). Those with mild EVW became asymptomatic or remained with mild EVW. Those with atopic MTW remained with atopic MTW and those with NAUW developed severe UW in most cases.

CONCLUSION

These results show that remission is most frequently observed in mild EVW and that no remission is observed in atopic MTW.

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.

Episodic viral wheeze and multiple trigger wheeze in preschool children: a useful distinction for clinicians?

Accumulating evidence suggest that splitting preschool recurrent wheezing disorders into Episodic (Viral) Wheeze (EVW) and Multiple Trigger Wheeze (MTW) is an oversimplification. There is little evidence that the EVW and MTW phenotypes are related to the longitudinal patterns of wheeze, or to different underlying pathological processes. As the clinical response to inhaled corticosteroids and montelukast varies considerably between individual children with EVW, and between individual patients with MTW, the clinical usefulness of the EVW-MTW approach is doubtful. Based on the currently available evidence, we propose to describe preschool wheeze symptoms not only in terms of temporal pattern, but also in terms of frequency and severity, and age of onset. Relevant associated clinical parameters like atopy and eczema should be described with recognition of age of onset, pattern, and severity. Comparing these data to biomarkers and histopathology may help to improve our understanding of preschool wheezing disorders in the future. Until phenotypes can be described that are associated with different pathobiological process, are related to different longitudinal outcomes, or are clearly different in terms of response to therapy, clinicians are encouraged to take a trial and error approach of different therapeutic agents in preschool children with troublesome recurrent wheeze.

Diagnosis of allergy and asthma in childhood

Childhood asthma is a widespread health problem because of its epidemic prevalence, as asthma affects more than 300 million people worldwide. Results from cross-sectional and cohort studies show that asthma starts in childhood in a large proportion of cases. A proper diagnosis is easier to make in adults and school-age children, as permanent changes in lung development, the strong impact of environmental factors on the airways, the immunologic maturity process, and the use of some diagnostic tools make asthma more difficult to diagnose in preschool children. This period of a child's life is an interesting challenge for pediatricians and specialists. The aim of the present review is to analyze the current knowledge regarding making an early and accurate asthma diagnosis and therefore deciding on the correct treatment to gain control over asthma symptoms and minimize health risks.