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Prediction models for early-onset atopic dermatitis in infancy: a prospective cohort study

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  • Published: 28 September 2026
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Prediction models for early-onset atopic dermatitis in infancy: a prospective cohort study
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  • Eakchalerm Eakpanit1,
  • Kamolwish Laoprasopwattan1,
  • Pasuree Sangsupawanich1,
  • Nattaporn Tassanakijpanich1,
  • Kemmapon Chumchuen2 &
  • …
  • Vanlaya Koosakulchai1 
  • 18 Accesses

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We’re sharing this article early to provide faster access to peer-reviewed, accepted research. It is citable and carries a permanent DOI. This version is subject to further edits and will be replaced automatically by the final Version of Record. All legal disclaimers apply.

Abstract

Background

Atopic dermatitis (AD) is the most common chronic inflammatory skin disease in childhood. Early identification of infants at high risk for AD may support preventive interventions and reduce the subsequent burden of allergic diseases. This study aimed to develop and evaluate prediction models for early-onset AD during the first two years of life.

Methods

Prediction models were developed using data from a prospective cohort study of healthy infants aged 42–90 days enrolled at Songklanagarind Hospital between August 2020 and October 2021. Demographic and clinical characteristics were collected at baseline. AD was assessed at 12 and 24 months of age using the Hanifin and Rajka diagnostic criteria. Multivariable logistic regression models were constructed, with variable selection performed using stepwise and least absolute shrinkage and selection operator (LASSO) methods. Model performance was evaluated using sensitivity, specificity, area under the receiver operating characteristic curve (AUC), F1 score, and calibration plots.

Results

Among 671 infants included in the analysis, 55 (8.2%) developed AD within the first two years of life. Higher household income and a family history of allergy were significantly associated with increased AD risk, whereas regular moisturizer use was significantly associated with reduced AD risk. The stepwise-selected model demonstrated lower sensitivity than the LASSO-selected model (68% vs. 74%) but higher specificity (75% vs. 66%) and AUC (74% vs. 67%). Both models were similar in F1 score (26%) and calibration.

Conclusions

Prediction models based on early-life clinical factors demonstrated promising performance in identifying infants at risk of atopic dermatitis. These models may support early risk stratification and prevention-oriented counseling in infancy.

Trial registration The present study is a secondary analysis of data derived from participants enrolled in the V114-032 (PNEU-ERA) clinical trial, which was prospectively registered at ClinicalTrials.gov (NCT04193215). The current cohort analysis evaluating prediction models for atopic dermatitis did not involve a separate interventional protocol.

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Abbreviations

AD:

Atopic dermatitis

AUC:

Area under the receiver operating characteristic curve

CI:

Confidence interval

IQR:

Interquartile range

LASSO:

Least absolute shrinkage and selection operator

LR+:

Positive likelihood ratio

NPV:

Negative predictive value

OR:

Odds ratio

PPV:

Positive predictive value

ROC:

Receiver operating characteristic

Acknowledgements

Not applicable.

Funding

Permission to use data from participants enrolled in the V114-032 (PNEU-ERA) study at Site 0005 (ClinicalTrials.gov identifier: NCT04193215) was obtained from Merck Sharp & Dohme LLC. The present analysis of early-onset atopic dermatitis was investigator-initiated and did not receive separate funding. The sponsor had no role in the design of this study, data analysis, interpretation of the results, manuscript preparation, or decision to submit the manuscript for publication.

Author information

Authors and Affiliations

  1. Department of Pediatrics, Faculty of Medicine, Prince of Songkla University, Hat Yai, 90110, Songkhla, Thailand

    Eakchalerm Eakpanit, Kamolwish Laoprasopwattan, Pasuree Sangsupawanich, Nattaporn Tassanakijpanich & Vanlaya Koosakulchai

  2. Department of Clinical Research and Medical Data Science, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, Thailand

    Kemmapon Chumchuen

Authors
  1. Eakchalerm Eakpanit
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  2. Kamolwish Laoprasopwattan
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  3. Pasuree Sangsupawanich
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  4. Nattaporn Tassanakijpanich
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  5. Kemmapon Chumchuen
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  6. Vanlaya Koosakulchai
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Corresponding author

Correspondence to Vanlaya Koosakulchai.

Ethics declarations

Ethics approval and consent to participate

This study was approved by the Human Research Ethics Committee of the Faculty of Medicine, Prince of Songkla University, Thailand (REC 65-189-1-1). Written informed consent was obtained from the parents or legal guardians of all participants prior to enrollment. The present study represents a secondary cohort analysis of participants enrolled in the V114-032 (PNEU-ERA) study.

Consent for publication

Not applicable.

Competing interests

The present study used follow-up data from participants enrolled in the V114-032 (PNEU-ERA) study, which was funded by Merck Sharp & Dohme LLC. The current analysis on early-onset atopic dermatitis was investigator-initiated and did not receive separate funding. The sponsor had no role in the study design, data analysis, data interpretation, manuscript preparation, or the decision to submit the manuscript for publication. KL received research funding from Merck Sharp & Dohme LLC for the V114-032/PNEU-ERA study at site 0005. All other authors declare no competing interests.

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Cite this article

Eakpanit, E., Laoprasopwattan, K., Sangsupawanich, P. et al. Prediction models for early-onset atopic dermatitis in infancy: a prospective cohort study. Allergy Asthma Clin Immunol (2026). https://doi.org/10.1186/s13223-026-01068-4

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  • Received: 17 February 2026

  • Accepted: 23 September 2026

  • Published: 28 September 2026

  • DOI: https://doi.org/10.1186/s13223-026-01068-4

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Keywords

  • Atopic dermatitis
  • Infancy
  • Risk prediction
  • Prevention

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