A disease model for wheezing disorders in preschool children based on clinicians' perceptions

Abstract

Background: Wheezing disorders in childhood vary widely in clinical presentation and disease course. During the last years, several ways to classify wheezing children into different disease phenotypes have been proposed and are increasingly used for clinical guidance, but validation of these hypothetical entities is difficult.

Methodology/principal findings: The aim of this study was to develop a testable disease model which reflects the full spectrum of wheezing illness in preschool children. We performed a qualitative study among a panel of 7 experienced clinicians from 4 European countries working in primary, secondary and tertiary paediatric care. In a series of questionnaire surveys and structured discussions, we found a general consensus that preschool wheezing disorders consist of several phenotypes, with a great heterogeneity of specific disease concepts between clinicians. Initially, 24 disease entities were described among the 7 physicians. In structured discussions, these could be narrowed down to three entities which were linked to proposed mechanisms: a) allergic wheeze, b) non-allergic wheeze due to structural airway narrowing and c) non-allergic wheeze due to increased immune response to viral infections. This disease model will serve to create an artificial dataset that allows the validation of data-driven multidimensional methods, such as cluster analysis, which have been proposed for identification of wheezing phenotypes in children.

Conclusions/significance: While there appears to be wide agreement among clinicians that wheezing disorders consist of several diseases, there is less agreement regarding their number and nature. A great diversity of disease concepts exist but a unified phenotype classification reflecting underlying disease mechanisms is lacking. We propose a disease model which may help guide future research so that proposed mechanisms are measured at the right time and their role in disease heterogeneity can be studied.

Figure 1. Graphical display of disease entities initially suggested by panel members.

The figure shows the position of disease entities initially suggested by panel members along the two main axes of variability identified by multiple correspondence analysis. The position of each entity is determined by its feature profile (features used by the panel member to describe the entity) such that entities with similar features lie close together. The numbering follows that used in table 1 and entities suggested by the same panel member are coloured with the same colour. The ellipses indicate groups of entities which have similar label names but were suggested independently by different panel members. The fact that entities within the same ellipse lie close to each other indicates that when different panel members suggested similar labels they also gave a similar description of the corresponding entities. The initial disease model consisted of 4 entities representing the 4 ellipses.