Can the sensitization profile towards hazelnut, peanut and birch pollen be used to predict the severity of clinical symptoms of hazelnut allergy in both children and adults?

Can the sensitization profile towards hazelnut, peanut and birch pollen be used to predict the severity of clinical symptoms of hazelnut allergy in both children and adults? - Prediction model to predict the clinical severity of hazelnut allergy.

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

NL-OMON

Registry ID

NL-OMON35609

Enrollment

176

Registered

2009-09-29

Start date

2010-02-19

Completion date

Unknown

Last updated

2024-05-06

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

food allergy hazelnut allergy

Interventions

None listed

Eligibility

Age

2 Years to 99 Years

Inclusion criteria

Inclusion criteria: children and adults with a hazelnut sensitization

Exclusion criteria

Exclusion criteria: congenital/aqcuired immunodeficiency lymphoproliferative disease systemic immunosuppression insufficient knowledge of Dutch language children from 3-6 years will be excluded from genetic research

Design outcomes

Primary

Measure	Time frame
Based on literature and preliminary data, four determinants are identified, which we think are (most) predictive for the severity of the symptoms of hazelnut allergy. The determinants are: Cor a 1, Cor a 8, Cor a 9 and oleosin. First, the predictive value of each determinant will be assessed using univariate analysis. Second, a multivariable logistic regression model will be build starting with the strongest predictor (based on the relative risk obtained from univariate analysis). To make the prediction model applicable for clinical practice, a prediction rule will be made and for the different possible scores on the prediction rule (or categories of the score), we will present the probability of having severe symptoms of hazelnut allergy.	—

Measure

Time frame

Based on literature and preliminary data, four determinants are identified, which we think are (most) predictive for the severity of the symptoms of hazelnut allergy. The determinants are: Cor a 1, Cor a 8, Cor a 9 and oleosin. First, the predictive value of each determinant will be assessed using univariate analysis. Second, a multivariable logistic regression model will be build starting with the strongest predictor (based on the relative risk obtained from univariate analysis). To make the prediction model applicable for clinical practice, a prediction rule will be made and for the different possible scores on the prediction rule (or categories of the score), we will present the probability of having severe symptoms of hazelnut allergy.

—

Secondary

Measure	Time frame
The analysis of IgE and T cell cross-reactivity concerns a secondary analysis to define potential mechanisms responsible for the difference in clinical severity of symptoms. We determine whether there are genetic associations by analysing these polymorfisms.	—

Countries

Netherlands

Outcome results