Modelling the Results of the Phadiatop Test Using the Logistic and Ordinal Regression

Part of the Studies in Computational Intelligence book series (SCI, volume 606)


This study was based on examination Phadiatop onerous test at the Clinic of Occupational and Preventive Medicine in order to save money and not make unnecessary testing. The aim of this study was to assess the outcome of the test Phadiatop only under close personal or family history of each patient. This estimation was used statistical methods specifically logistic and ordinal regression. The most important findings are that Phadiatop test result does not imply eczema; it is a different immune response and the disease is not relevant in personal or family anamnesis. The patient was based on a family and personal anamnesis, in assigning only two groups (healthy or sick) correctly classified with a probability of 75 %. The test sensitivity is about 77 % and the diseases influencing the results are asthma and allergic rhinitis. The success rate of classifying each patient into one of the five Phadiatop test groups according to the seriousness of diseases was about 68 %. Also a testing based on age groups of the patients was done using this database. The presence of the positive Phadiatop test was the most common for people born between 1972 and 1981, where the genetic predispositions for a positive Phadiatop test results are about 39 %.


Logistic Regression Positive Predictive Value Negative Predictive Value Allergic Rhinitis Genetic Predisposition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This paper was done thanks to cooperation with The University Hospital of Ostrava, the Department of Clinic of Occupation and Preventive medicine. This work was supported by the International Visegrad Fund’s Standard Grant No. 21320401.


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© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Mathematical Methods in EconomicsVŠB—Technical University of OstravaOstravaCzech Republic

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