ReviewPredicting persistence of asthma in preschool wheezers: crystal balls or muddy waters?
Section snippets
Background
Preschool wheezing is the common expression of several heterogeneous disorders with variable course and prognosis.1 During the first years of life, approximately one third of children will have at least one episode of wheeze, and in half of these children the symptoms will be recurrent.2 However, although these episodes resemble asthma exacerbations in older children, approximately two-thirds of preschool wheezers cease to wheeze by the age of 6 years.2 Therefore, identification of symptomatic
Currently available asthma predictive models
API. The API was developed in 2000 by Castro-Rodríguez et al.25 The investigators used data from 1,246 children in the Tuscon Children's Respiratory Study cohort to identify clinical and laboratory parameters in recurrent wheezers during the first 3 years of life, which could predict asthma persistence beyond the age of 6 years. In combination with the number of wheezing episodes, these parameters (named “criteria”) were used to create two predictive indices: a loose and a stringent API. These
General principles
As a basic rule in clinical epidemiology, a predictive rule developed in any given population should be applied in practice only after it has been validated in a different cohort; this is termed “broad” or “level 2” validation.43 Conversely, “narrow” validation refers to the evaluation of the model either within the sample it was derived from (“level 4” validation) or in a different cohort with similar characteristics (“level 3” validation).43 This preliminary “narrow” validation process
Limitations
Besides their poor performance in validation studies (if at all available), asthma predictive models also present important limitations related to their development methodology and clinical applicability.
In the case of API, it remains unclear exactly how the cut-off point between loose and stringent API (< 3 or > 3 wheezing episodes) was derived. In the original study, parents rated the frequency of wheezing using a Likert-type scale from 1 (“very rarely”) to 5 (“on most days”),25 but it was
Discussion
Successful introduction of a predictive rule in clinical practice is dependent on its simplicity, performance characteristics, and clinical and prognostic implications. Moreover, the clinical usefulness of a predictive tool depends strongly on the aim of the prediction per se. In general paediatric practice, for example, clinicians caring for wheezing preschoolers seek to identify children at risk for later asthma and to decide with sufficient certainty whether they should intervene. In
Conclusions
The available asthma predictive models suffer important intrinsic and practical limitations, precluding their useful clinical applicability. Although these tools are generally simple and easy to apply, they have been insufficiently validated, and they have limited predictive value in terms of confirming or ruling out persistence of asthma symptoms among preschool wheezers. The stringent API in particular performs poorly in high-risk populations in which early identification of children at risk
Educational aims
After reading this article the reader will be able to:
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Describe the currently available asthma predictive models (such as the asthma predictive index, API) and understand the rationale for their development.
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Describe the methodological and practical limitations of the available asthma predictive models.
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Understand the poor ability of the available asthma predictive models to predict the long-term outcome of preschool wheeze.
Future directions
Future research on asthma predictive models should include:
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Proper validation in independent populations and clinical settings.
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Assessment of their performance by longitudinal follow-up of high-risk cohorts.
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Assessment of their true clinical impact.
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Development of more accurate models by identifying and incorporating new predictive variables
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Which Wheezing Preschoolers Should be Treated for Asthma?
2021, Journal of Allergy and Clinical Immunology: In PracticeChronic obstructive pulmonary diseases in children
2015, Jornal de PediatriaCitation Excerpt :Some authors have mentioned methodological and practical limitations of APIs, suggesting that they have low capacity and poor sensitivity to predict asthma at school age,45,46 and that although they are simple and easy-to-apply tools, they have not been sufficiently validated. According to these authors, predicting asthma using simple clinical models is virtually impossible.45,46 Although most of the scientific community is favorable to the use of APIs,47,48 the search for clinical and/or laboratory markers for the diagnosis of asthma in RWI and children younger than 5 years remains a rich area for future studies.
Childhood asthma prediction models: A systematic review
2015, The Lancet Respiratory MedicineCitation Excerpt :The existing models can be updated to one optimal, generic model or to several specific models for different definitions of outcome or ages at outcome. External validation may also clarify some concerns.2–8 If the external study population is sufficiently large and is composed of different cultures, exposures,38 and ethnic groups, the validation will shed light on the generalisability of the models.
Utility of the asthma predictive index in predicting childhood asthma and identifying disease-modifying interventions
2014, Annals of Allergy, Asthma and ImmunologyChildhood Asthma-Predictive Phenotype
2014, Journal of Allergy and Clinical Immunology: In PracticeCitation Excerpt :Children with a positive API at age 3 years had an 8-fold increased risk of asthma in the school years, similar to that found in the Tucson study.73,82 As is typical with these risk models, the overall predictive performance was low.83,84 The API, however, also has a high negative predictive value when the API is negative, which enables the identification of children who are at low risk of developing asthma later.85,86
Optimum Predictors of Childhood Asthma: Persistent Wheeze or the Asthma Predictive Index?
2014, Journal of Allergy and Clinical Immunology: In PracticeCitation Excerpt :LRs best reflect the diagnostic accuracy of a test. The LR+ of the stringent API in the Tucson study ranged from 3.0 to 7.4 for asthma between ages 6 to 8, whereas the LR–ranged from 0.5 to 0.8.23 The LR+ of 7.5 and LR–of 0.6 reported for the ucAPI are comparable with that of the API in the Tucson study and suggest that a positive ucAPI could have a significant effect on the posttest probability.