Systems-based analysis of patient compliance in allergen-specific immunotherapy

OData support
Supervisor:
Dr. Antal Péter
Department of Measurement and Information Systems

During my studies, I investigated systems-based statistical data analytic methods to explore mechanisms of the immune system, especially its functions and disorders in allergy. Allergy is very common disase, which is related to a hypersensitivity of the immune system.

Allergy can be cured in many ways, but the most effective is the allergen-specific immunotherapy. This therapy not only eases the symptoms but also cure causes of the allergy.

However, this therapy requires a longer period to cure the patient: it can last three to five years. Because of its long period many patients end the therapy before it would be successful. A proper and timely doctor-patient interaction could help to achieve better patient compliance.

In this research, we use many data about patient’s genetics, personality, genomics, immune system, clinical data, daily medication, symptoms, adverse effects, pollen data, meteorology data, and air pollution data.

I have analyzed data from the Department of Genetics, Cell- and Immunobiology at the Semmelweis University. I applied systems-based methods to explore these data sets in R using different statistical models. I have got acquainted with efficacy, effectiveness, efficiency. I analyzed the robustness of the used statistical models, and I formulated suggestions to improve the cost-effectiveness of the therapy.

Downloads

Please sign in to download the files of this thesis.