Can serum biomarkers predict the outcome of systemic immunosuppressive therapy in adult atopic dermatitis patients?. Issue 1 (7th January 2022)
- Record Type:
- Journal Article
- Title:
- Can serum biomarkers predict the outcome of systemic immunosuppressive therapy in adult atopic dermatitis patients?. Issue 1 (7th January 2022)
- Main Title:
- Can serum biomarkers predict the outcome of systemic immunosuppressive therapy in adult atopic dermatitis patients?
- Authors:
- Hurault, G.
Roekevisch, E.
Schram, M. E.
Szegedi, K.
Kezic, S.
Middelkamp‐Hup, M. A.
Spuls, P. I.
Tanaka, R. J. - Abstract:
- Abstract: Background: Atopic dermatitis (AD or eczema) is a most common chronic skin disease. Designing personalised treatment strategies for AD based on patient stratification is of high clinical relevance, given a considerable variation in the clinical phenotype and responses to treatments among patients. It has been hypothesised that the measurement of biomarkers could help predict therapeutic responses for individual patients. Objective: We aim to assess whether serum biomarkers can predict the outcome of systemic immunosuppressive therapy in adult AD patients. Methods: We developed a statistical machine learning model using the data of an already published longitudinal study of 42 patients who received azathioprine or methotrexate for over 24 weeks. The data contained 26 serum cytokines and chemokines measured before the therapy. The model described the dynamic evolution of the latent disease severity and measurement errors to predict AD severity scores (Eczema Area and Severity Index, (o)SCORing of AD and Patient Oriented Eczema Measure) two‐weeks ahead. We conducted feature selection to identify the most important biomarkers for the prediction of AD severity scores. Results: We validated our model in a forward chaining setting and confirmed that it outperformed standard time‐series forecasting models. Adding biomarkers did not improve predictive performance. Conclusions: In this study, biomarkers had a negligible and non‐significant effect for predicting the future ADAbstract: Background: Atopic dermatitis (AD or eczema) is a most common chronic skin disease. Designing personalised treatment strategies for AD based on patient stratification is of high clinical relevance, given a considerable variation in the clinical phenotype and responses to treatments among patients. It has been hypothesised that the measurement of biomarkers could help predict therapeutic responses for individual patients. Objective: We aim to assess whether serum biomarkers can predict the outcome of systemic immunosuppressive therapy in adult AD patients. Methods: We developed a statistical machine learning model using the data of an already published longitudinal study of 42 patients who received azathioprine or methotrexate for over 24 weeks. The data contained 26 serum cytokines and chemokines measured before the therapy. The model described the dynamic evolution of the latent disease severity and measurement errors to predict AD severity scores (Eczema Area and Severity Index, (o)SCORing of AD and Patient Oriented Eczema Measure) two‐weeks ahead. We conducted feature selection to identify the most important biomarkers for the prediction of AD severity scores. Results: We validated our model in a forward chaining setting and confirmed that it outperformed standard time‐series forecasting models. Adding biomarkers did not improve predictive performance. Conclusions: In this study, biomarkers had a negligible and non‐significant effect for predicting the future AD severity scores and the outcome of the systemic therapy. Abstract : … (more)
- Is Part Of:
- Skin health and disease. Volume 2:Issue 1(2022)
- Journal:
- Skin health and disease
- Issue:
- Volume 2:Issue 1(2022)
- Issue Display:
- Volume 2, Issue 1 (2022)
- Year:
- 2022
- Volume:
- 2
- Issue:
- 1
- Issue Sort Value:
- 2022-0002-0001-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2022-01-07
- Subjects:
- Skin -- Diseases -- Periodicals
Dermatology -- Periodicals
Dermatology
Skin -- Diseases
Skin Diseases
Dermatology
Periodicals
Periodical
616.5005 - Journal URLs:
- https://onlinelibrary.wiley.com/journal/2690442x ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/ski2.77 ↗
- Languages:
- English
- ISSNs:
- 2690-442X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21145.xml