Literature DB >> 26992008

Comparison of six disease severity scores for allergic rhinitis against pollen counts a prospective analysis at population and individual level.

Jakob Florack1, Maria Antonia Brighetti2, Serena Perna1,3, Antonio Pizzulli1,4, Antje Pizzulli4, Salvatore Tripodi5,6, Corrado Costa7, Alessandro Travaglini2, Simone Pelosi6, Annamaria Bianchi8, Olympia Tsilochristou1, Francesca Gabrielli9, Paolo Maria Matricardi1.   

Abstract

BACKGROUND: Many different symptom (medication) scores are nowadays used as measures of allergic rhinoconjunctivitis severity in individual patients and in clinical trials. Their differences contribute to the heterogeneity of the primary end-point in meta-analyses, so that calls for symptom (medication) score harmonization have been launched.
OBJECTIVE: To prospectively compare six different severity scores for allergic rhinitis (AR) against pollen counts at both population and individual levels.
METHODS: Two groups of children with seasonal AR and grass pollen sensitization were recruited in Ascoli, Italy (n = 76) and Berlin, Germany (n = 29). Symptoms and drug intake were monitored daily for 40 and 30 days of the grass pollen season in 2011 (Ascoli) and 2013 (Berlin), respectively, through an Internet-based platform (AllergyMonitor(™) , TPS Production srl, Rome, Italy). From the gathered data, the informatics platform automatically generated one symptom score (RTSS) and five symptom-medication scores (RC-ACS(©) , ACS, RTSS[LOCF], RTSS[WC] and AdSS). Values were then statistically normalized for reciprocal comparison and matched against the daily variations of local grass pollen counts (Spearman's rank correlation).
RESULTS: The grass pollen counts were higher in Ascoli than in Berlin (peak values 194 vs. 59 grains/m(3) ). At population level, the trajectories of the normalized average values of the six scores differed only slightly in both studies and correlated well with the pollen counts (ranges r(2) : 0.38-0.50 in Ascoli, 0.41-0.56 in Berlin). By contrast, in individual patients, trajectories of different scores were often quite heterogeneous. The RTSS[WC] had a very low discriminatory power and generated in many patients long, flat horizontal segments.
CONCLUSIONS: Disease severity scores for seasonal AR, as evaluated via an Internet-based platform, tend to provide similar results at population level but can often produce heterogeneous slopes in individual patients. The choice of the disease severity score might have only a low impact on the outcome of a very large clinical trial, but it may be crucial in the management of individual patients.
© 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  allergic rhinitis; e-Health; grass pollen; hay fever; symptom-medication score

Mesh:

Substances:

Year:  2016        PMID: 26992008     DOI: 10.1111/pai.12562

Source DB:  PubMed          Journal:  Pediatr Allergy Immunol        ISSN: 0905-6157            Impact factor:   6.377


  6 in total

1.  Validation Parameters of Patient-Generated Data for Digitally Recorded Allergic Rhinitis Symptom and Medication Scores in the @IT.2020 Project: Exploratory Study.

Authors:  Stephanie Dramburg; Serena Perna; Marco Di Fraia; Salvatore Tripodi; Stefania Arasi; Sveva Castelli; Danilo Villalta; Francesca Buzzulini; Ifigenia Sfika; Valeria Villella; Ekaterina Potapova; Maria Antonia Brighetti; Alessandro Travaglini; Pierluigi Verardo; Simone Pelosi; Paolo Maria Matricardi
Journal:  JMIR Mhealth Uhealth       Date:  2022-06-03       Impact factor: 4.947

Review 2.  How the Smartphone Is Changing Allergy Diagnostics.

Authors:  Ana Margarida Pereira; Cristina Jácome; Rute Almeida; João Almeida Fonseca
Journal:  Curr Allergy Asthma Rep       Date:  2018-10-25       Impact factor: 4.806

Review 3.  Digital technologies for an improved management of respiratory allergic diseases: 10 years of clinical studies using an online platform for patients and physicians.

Authors:  Salvatore Tripodi; Andrea Giannone; Ifigenia Sfika; Simone Pelosi; Stephanie Dramburg; Annamaria Bianchi; Antonio Pizzulli; Jakob Florack; Valeria Villella; Ekaterina Potapova; Paolo Maria Matricardi
Journal:  Ital J Pediatr       Date:  2020-07-25       Impact factor: 2.638

Review 4.  mHealth and telemedicine utility in the monitoring of allergic diseases.

Authors:  Violeta Kvedarienė; Paulina Burzdikaitė; Inga Česnavičiūtė
Journal:  Front Allergy       Date:  2022-09-02

5.  A study of longitudinal mobile health data through fuzzy clustering methods for functional data: The case of allergic rhinoconjunctivitis in childhood.

Authors:  Paolo Giordani; Serena Perna; Annamaria Bianchi; Antonio Pizzulli; Salvatore Tripodi; Paolo Maria Matricardi
Journal:  PLoS One       Date:  2020-11-17       Impact factor: 3.240

6.  Heterogeneous validity of daily data on symptoms of seasonal allergic rhinitis recorded by patients using the e-diary AllergyMonitor®.

Authors:  Stephanie Dramburg; Serena Perna; Marco Di Fraia; Salvatore Tripodi; Stefania Arasi; Sveva Castelli; Danilo Villalta; Francesca Buzzulini; Ifigenia Sfika; Valeria Villella; Ekaterina Potapova; Maria Antonia Brighetti; Alessandro Travaglini; Pier Luigi Verardo; Simone Pelosi; Paolo Maria Matricardi
Journal:  Clin Transl Allergy       Date:  2021-12-15       Impact factor: 5.871

  6 in total

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