Scoring the Risk of Having Systemic Mastocytosis in Adult Patients with Mastocytosis in the Skin

David Fuchs*, Alex Kilbertus, Karin Kofler, Nikolas von Bubnoff, Khalid Shoumariyeh, Roberta Zanotti, Patrizia Bonadonna, Luigi Scaffidi, Michael Doubek, Hanneke Oude Elberink, Lambert F.R. Span, Olivier Hermine, Chiara Elena, Pietro Benvenuti, Akif Selim Yavuz, Knut Brockow, Alexander Zink, Elisabeth Aberer, Aleksandra Gorska, Jan RomantowskiEmir Hadzijusufovic, Anna Belloni Fortina, Francesca Caroppo, Cecelia Perkins, Anja Illerhaus, Jens Panse, Vladan Vucinic, Mohamad Jawhar, Vito Sabato, Massimo Triggiani, Roberta Parente, Anna Bergström, Christine Breynaert, Jason Gotlib, Andreas Reiter, Karin Hartmann, Marek Niedoszytko, Michel Arock, Hanneke C. Kluin-Nelemans, Wolfgang R. Sperr, Rosemarie Greul, Peter Valent

*Korrespondierende/r Autor/-in für diese Arbeit

Abstract

Background: Mastocytosis in adults often presents with skin lesions. A bone marrow biopsy is necessary to confirm or exclude the presence of systemic mastocytosis (SM) in these cases. When a bone marrow biopsy is not performed, the provisional diagnosis is mastocytosis in the skin (MIS). No generally accepted scoring system has been established to estimate the risk of SM in these patients. Objective: To develop a risk score to predict SM in adults with MIS. Methods: We examined 1145 patients with MIS from the European Competence Network on Mastocytosis Registry who underwent a bone marrow biopsy. A total of 944 patients had SM and 201 patients had cutaneous mastocytosis; 63.7% were female, and 36.3% were male. Median age was 44 ± 13.3 years. The median serum tryptase level amounted to 29.3 ± 81.9 ng/mL. We established a multivariate regression model using the whole population of patients as a training and validation set (bootstrapping). A risk score was developed and validated with receiver-operating curves. Results: In the multivariate model, the tryptase level (P <.001), constitutional/cardiovascular symptoms (P =.014), and bone symptoms/osteoporosis (P <.001) were independent predictors of SM (P <.001; sensitivity, 90.7%; specificity, 69.1%). A 6-point risk score was established (risk, 10.7%-98.0%) and validated. Conclusions: Using a large data set of the European Competence Network on Mastocytosis Registry, we created a risk score to predict the presence of SM in patients with MIS. Although the score will need further validation in independent cohorts, our score seems to discriminate safely between patients with SM and with pure cutaneous mastocytosis.

OriginalspracheEnglisch
ZeitschriftJournal of Allergy and Clinical Immunology: In Practice
Jahrgang9
Ausgabenummer4
Seiten (von - bis)1705-1712.e4
ISSN2213-2198
DOIs
PublikationsstatusVeröffentlicht - 04.2021

Fördermittel

This work was supported by Deutsche Forschungsgemeinschaft (DFG; grant no. RA 2838 to A.I.) and by the Koeln Fortune Program, Faculty of Medicine , University of Cologne (grant no. 216/2016 to A.I.). P.V. and his team were supported by the Austrian Science Fund (Fonds zur Förderung der wissenschaftlichen Forschung; grant nos. F4704-B20 and P32470-B). V.S. is a senior clinical researcher of the Research Foundation Flanders/Fonds Wetenschappelijk Onderzoek (FWO: 1804518N). Conflicts of interest: D. Fuchs received honoraria from Novartis, outside the submitted work. N. von Bubnoff received honoraria from Amgen, Astra Zeneca, BMS, and Novartis, and research funding from Novartis . J. Panse reports personal fees from Alexion, BMS, Boehringer Ingelheim, Grünenthal, MSD, Novartis, Pfizer, Chugai, Roche, Apellis, and Blueprint medicines, all outside the submitted work. M. Triggiani received fee for Advisory Board from Novartis, Deciphera, and Blueprint Medicines. H. C. Kluin-Nelemans received financial support from Novartis . W. R. Sperr received honoraria from Novartis, Pfizer, AbbVie, Daiichi Sankyo, Amgen, Thermo Fisher, Deciphera, Incyte, Celgene, and Jazz. Valent received honoraria from Deciphera, Blueprint, Celgene, Novartis, Pfizer, and Incyte, all outside the submitted work.

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

  1. SDG 3 – Gesundheit und Wohlergehen
    SDG 3 – Gesundheit und Wohlergehen

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