The simple 10-item PARC tool to predict childhood asthma - an external validation.

Pedersen, Eva S L; Spycher, Ben D; de Jong, Carmen; Halbeisen, Florian; Ramette, Alban; Gaillard, Erol A; Granell, Raquel; Henderson, A John; Kuehni, Claudia E (2019). The simple 10-item PARC tool to predict childhood asthma - an external validation. The Journal of allergy and clinical immunology, 7(3), 943-953.e4. Elsevier 10.1016/j.jaip.2018.09.032

[img]
Preview
Text
Pedersen JAllergyClinImmunolPract 2018_manuscript.pdf - Accepted Version
Available under License Creative Commons: Attribution-Noncommercial-No Derivative Works (CC-BY-NC-ND).

Download (523kB) | Preview

BACKGROUND External validation of prediction models is important to assess generalisability 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 R-squared. Sensitivity analyses varied inclusion criteria, scoring items and outcomes. RESULTS The validation population included 2690 children with preschool respiratory symptoms of which 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 cut-off 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. CONCLUSION 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.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Social and Preventive Medicine
04 Faculty of Medicine > Service Sector > Institute for Infectious Diseases

Graduate School:

Graduate School for Cellular and Biomedical Sciences (GCB)
Graduate School for Health Sciences (GHS)

UniBE Contributor:

Pedersen, Eva Sophie Lunde; Spycher, Ben; de Jong, Carmen Cornelia Maria; Halbeisen, Florian; Ramette, Alban Nicolas and Kühni, Claudia

Subjects:

600 Technology > 610 Medicine & health
300 Social sciences, sociology & anthropology > 360 Social problems & social services
500 Science > 570 Life sciences; biology

ISSN:

1097-6825

Publisher:

Elsevier

Language:

English

Submitter:

Tanya Karrer

Date Deposited:

24 Oct 2018 15:40

Last Modified:

10 Oct 2019 02:30

Publisher DOI:

10.1016/j.jaip.2018.09.032

PubMed ID:

30312804

Uncontrolled Keywords:

ALSPAC Asthma External Validation Leicestershire Respiratory Cohorts PARC Prediction Wheeze

BORIS DOI:

10.7892/boris.120546

URI:

https://boris.unibe.ch/id/eprint/120546

Actions (login required)

Edit item Edit item
Provide Feedback