Machine learning-derived asthma and allergy trajectories in children : a systematic review and meta-analysis
(2025) In European Respiratory Review 34(175). p.1-14- Abstract
INTRODUCTION: Numerous studies have characterised trajectories of asthma and allergy in children using machine learning, but with different techniques and mixed findings. The present work aimed to summarise the evidence and critically appraise the methodology.
METHODS: 10 databases were searched. Screening, data extraction and quality assessment were performed in pairs. Trajectory characteristics were tabulated and visualised. Associated risk factor and outcome estimates were pooled using a random-effects meta-analysis.
RESULTS: 89 studies were included. Early-onset (infancy) persistent, mid-onset (∼2-5 years) persistent, early-onset early-resolving (within ∼2 years) and early-onset mid-resolving (by ∼3-6 years) wheezing and... (More)
INTRODUCTION: Numerous studies have characterised trajectories of asthma and allergy in children using machine learning, but with different techniques and mixed findings. The present work aimed to summarise the evidence and critically appraise the methodology.
METHODS: 10 databases were searched. Screening, data extraction and quality assessment were performed in pairs. Trajectory characteristics were tabulated and visualised. Associated risk factor and outcome estimates were pooled using a random-effects meta-analysis.
RESULTS: 89 studies were included. Early-onset (infancy) persistent, mid-onset (∼2-5 years) persistent, early-onset early-resolving (within ∼2 years) and early-onset mid-resolving (by ∼3-6 years) wheezing and eczema, respectively, were the most commonly identified disease trajectories. Intermediate/transient trajectories were rare. Male sex was associated with a higher risk of most wheezing trajectories and possibly with early-resolving eczema, while being slightly protective against mid-onset persistent eczema. Parental disease/genetic markers were associated with persistent trajectories of wheezing and eczema, respectively. Prenatal (and less so postnatal) tobacco smoke exposure was associated with most wheezing trajectories, as were lower respiratory tract infections in infancy (particularly with the early-onset resolving patterns). Most studies (69%) were of low methodological quality (particularly in modelling approaches and reporting). Few studies investigated allergic multimorbidity, allergic rhinitis and food allergy.
CONCLUSIONS: Childhood asthma/wheezing and eczema can be characterised by a few relatively consistent trajectories, with some actionable risk factors such as pre-/postnatal smoke exposure. Improved computational methodology is warranted to better assess generalisability and elucidate the validity of intermediate/transient trajectories. Likewise, allergic multimorbidity and trajectories of allergic rhinitis and food allergy need to be further elucidated.
(Less)
- author
- Lisik, Daniil
; Özuygur Ermis, Saliha Selin
; Milani, Gregorio Paolo
; Spolidoro, Giulia Carla Immacolata
; Ercan, Selin
; Salisu, Michael
; Odetola, Faozyat
; Ghiglioni, Daniele Giovanni
; Pylov, Danylo
; Goksör, Emma
; Basna, Rani
LU
; Wennergren, Göran
; Kankaanranta, Hannu
and Nwaru, Bright I
(Less) - organization
- publishing date
- 2025-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Adolescent, Child, Child, Preschool, Female, Humans, Infant, Male, Age Factors, Age of Onset, Epidemiology, Diagnosis, Computer-Assisted, Disease Progression, Eczema/epidemiology, Hypersensitivity/epidemiology, Machine Learning, Predictive Value of Tests, Prognosis, Respiratory Sounds/physiopathology, Risk Assessment, Risk Factors, Artifical Intelligence, statistical analysis
- in
- European Respiratory Review
- volume
- 34
- issue
- 175
- article number
- 240160
- pages
- 1 - 14
- publisher
- European Respiratory Society
- external identifiers
-
- pmid:39778923
- scopus:85215113282
- ISSN
- 0905-9180
- DOI
- 10.1183/16000617.0160-2024
- language
- English
- LU publication?
- yes
- additional info
- Copyright ©The authors 2025.
- id
- 7981fe18-0bdb-4b98-b973-e3cebc2fc25c
- date added to LUP
- 2025-01-16 12:31:16
- date last changed
- 2025-06-05 12:14:40
@article{7981fe18-0bdb-4b98-b973-e3cebc2fc25c,
abstract = {{<p>INTRODUCTION: Numerous studies have characterised trajectories of asthma and allergy in children using machine learning, but with different techniques and mixed findings. The present work aimed to summarise the evidence and critically appraise the methodology.</p><p>METHODS: 10 databases were searched. Screening, data extraction and quality assessment were performed in pairs. Trajectory characteristics were tabulated and visualised. Associated risk factor and outcome estimates were pooled using a random-effects meta-analysis.</p><p>RESULTS: 89 studies were included. Early-onset (infancy) persistent, mid-onset (∼2-5 years) persistent, early-onset early-resolving (within ∼2 years) and early-onset mid-resolving (by ∼3-6 years) wheezing and eczema, respectively, were the most commonly identified disease trajectories. Intermediate/transient trajectories were rare. Male sex was associated with a higher risk of most wheezing trajectories and possibly with early-resolving eczema, while being slightly protective against mid-onset persistent eczema. Parental disease/genetic markers were associated with persistent trajectories of wheezing and eczema, respectively. Prenatal (and less so postnatal) tobacco smoke exposure was associated with most wheezing trajectories, as were lower respiratory tract infections in infancy (particularly with the early-onset resolving patterns). Most studies (69%) were of low methodological quality (particularly in modelling approaches and reporting). Few studies investigated allergic multimorbidity, allergic rhinitis and food allergy.</p><p>CONCLUSIONS: Childhood asthma/wheezing and eczema can be characterised by a few relatively consistent trajectories, with some actionable risk factors such as pre-/postnatal smoke exposure. Improved computational methodology is warranted to better assess generalisability and elucidate the validity of intermediate/transient trajectories. Likewise, allergic multimorbidity and trajectories of allergic rhinitis and food allergy need to be further elucidated.</p>}},
author = {{Lisik, Daniil and Özuygur Ermis, Saliha Selin and Milani, Gregorio Paolo and Spolidoro, Giulia Carla Immacolata and Ercan, Selin and Salisu, Michael and Odetola, Faozyat and Ghiglioni, Daniele Giovanni and Pylov, Danylo and Goksör, Emma and Basna, Rani and Wennergren, Göran and Kankaanranta, Hannu and Nwaru, Bright I}},
issn = {{0905-9180}},
keywords = {{Adolescent; Child; Child, Preschool; Female; Humans; Infant; Male; Age Factors; Age of Onset; Epidemiology; Diagnosis, Computer-Assisted; Disease Progression; Eczema/epidemiology; Hypersensitivity/epidemiology; Machine Learning; Predictive Value of Tests; Prognosis; Respiratory Sounds/physiopathology; Risk Assessment; Risk Factors; Artifical Intelligence; statistical analysis}},
language = {{eng}},
number = {{175}},
pages = {{1--14}},
publisher = {{European Respiratory Society}},
series = {{European Respiratory Review}},
title = {{Machine learning-derived asthma and allergy trajectories in children : a systematic review and meta-analysis}},
url = {{http://dx.doi.org/10.1183/16000617.0160-2024}},
doi = {{10.1183/16000617.0160-2024}},
volume = {{34}},
year = {{2025}},
}