Clinical, Cosmetic and Investigational Dermatology (Mar 2021)

A Priori Estimation of the Narrow-Band UVB Phototherapy Outcome for Moderate-to-Severe Psoriasis Based on the Patients’ Questionnaire and Blood Tests Using Random Forest Classifier

  • Narbutt J,
  • Krzyścin J,
  • Sobolewski P,
  • Skibińska M,
  • Noweta M,
  • Owczarek W,
  • Rajewska-Więch B,
  • Lesiak A

Journal volume & issue
Vol. Volume 14
pp. 253 – 259

Abstract

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Joanna Narbutt,1 Janusz Krzyścin,2 Piotr Sobolewski,2 Małgorzata Skibińska,1 Marcin Noweta,1 Witold Owczarek,3 Bonawentura Rajewska-Więch,2 Aleksandra Lesiak1 1Department of Dermatology, Pediatric Dermatology and Oncology, Medical University of Łódź, Łódź, Poland; 2Institute of Geophysics, Polish Academy of Sciences, Warsaw, Poland; 3Department of Dermatology, Military Institute of Medicine, Warsaw, PolandCorrespondence: Janusz KrzyścinInstitute of Geophysics, Polish Academy of Sciences, Warsaw, 01-452, PolandTel +48-2269-15950Email [email protected]: Nowadays, patients with moderate-to-severe psoriasis are treated with conventional immunosuppressants or with new biological agents. Phototherapy is the first-line treatment for patients in whom topical therapy is insufficient. Although numerous studies have been carried out, it is still difficult to predict the outcome of phototherapy in individual patients.Methods: Prior to standard narrow band (NB) ultraviolet B (UVB) phototherapy, the patients filled out a questionnaire about personal life and health status. Several standard blood tests, including selected cytokine levels, were performed before and after a course of 20 NB-UVB treatments. The questionnaire answers, results of the blood tests, and treatment outcomes were analyzed using an artificial intelligence approach—the random forest (RF) classification tool.Results: A total of 82 participants with moderate-to-severe psoriasis were enrolled. Prior to starting phototherapy, the patients with expected good outcome from the phototherapy, shorter remission, and quitting a possible second course of the NB-UVB treatment could be identified by the RF classifier with sensitivity over 84%, and accuracy of 75%, 85%, and 79%, respectively. The inclusion of cytokine data did not improve the performance of the RF classifier.Conclusion: This approach offers help in making clinical decisions by identifying psoriatic patients in whom phototherapy will significantly improve their skin, or those in whom other therapies should be recommended beforehand.Keywords: psoriasis, phototherapy, outcome prediction, artificial intelligence

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