Extract
We have known for a long time that asthma-like symptoms in the first years of life predict later asthma poorly. Many preschool wheezers become asymptomatic by school age. A few will develop classic atopic asthma, which is likely to persist into later childhood and even adulthood, but the large majority of preschool children with asthma-like symptoms are difficult place into clear-cut categories. The clinical picture varies from child to child, and remissions and relapses are common. During past decades, many attempts have been made to define asthma phenotypes. Initial attempts were simple and based on a combination of expert opinion and observations made in early cohort studies [1]. More recently, researchers have used statistical clustering techniques, which should provide a more objective classification because they obtain phenotypes from observed data according to a predefined method. Most of us would agree that letting the data speak is a good idea. We want a classification that reflects true patterns of disease as they occur in the population. However, in spite of their promises, these methods are not entirely objective. They require investigators to make certain choices such as which variables to include or which age intervals to consider, and these choices matter.
Abstract
The potential of latent transition analysis of asthma phenotypes will be seen larger cohort studies http://ow.ly/VUzAH
Footnotes
Support statement: B.D. Spycher was supported by a Swiss National Science Foundation fellowship (grant number PZ00P3_147987). Funding information for this article has been deposited with FundRef.
Conflict of interest: Disclosures can be found alongside the online version of this article at erj.ersjournals.com
- Received December 1, 2015.
- Accepted December 3, 2015.
- Copyright ©ERS 2016