Evidence map›Paper›PMID 40740762›Full record

ArticleFrontiers in immunology2025

Development and implementation of Phleos, a web-based tool for the data collection on Hypereosinophilic syndrome: the Italian Network on HES (INHES) study protocol.

Stefania Nicola, Marco Caminati, Richard Borrelli, Luca Lo Sardo, Federica Corradi, Iuliana Badiu, Angelo Vacca, Palma Carlucci, Amato De Paulis, Ilaria Mormile and 8 more

Abstract read
In one paragraph

Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Stefania Nicola *Immunology and Allergy Unit - AO Ordine Mauriziano di Torino, Turin, Italy.
Marco Caminati *Department of Medicine, University of Verona, Verona, Italy.
Richard BorrelliDepartment of Medical Sciences, University of Turin, Turin, Italy.
Luca Lo SardoImmunology and Allergy Unit - AO Ordine Mauriziano di Torino, Turin, Italy.
Federica CorradiImmunology and Allergy Unit - AO Ordine Mauriziano di Torino, Turin, Italy.
Iuliana BadiuImmunology and Allergy Unit - AO Ordine Mauriziano di Torino, Turin, Italy.
Angelo VaccaInternal Medicine Guido Baccelli, University of Bari Aldo Moro Medical School, Bari, Italy.
Palma CarlucciInternal Medicine Guido Baccelli, University of Bari Aldo Moro Medical School, Bari, Italy.
Amato De PaulisDepartment of Translational Medical Sciences, Federico II University, Naples, Italy.
Ilaria MormileDepartment of Translational Medical Sciences, Federico II University, Naples, Italy.
Marco ZurloDepartment of Medicine, University of Verona, Verona, Italy.
Mario Di GioacchinoInstitute for Clinical Immunotherapy and Advanced Biological Treatments, Pescara, Italy.
Vincenzo PatellaDepartment of Internal Medicine asl Salerno, "Santa maria della Speranza" Hospital, Salerno, Italy.
Stefano Del GiaccoDepartment of Medical Science and Public Health, University of Cagliari, Monserrato, Italy.
Giulia CostanzoDepartment of Medical Science and Public Health, University of Cagliari, Monserrato, Italy.
Simone NegriniImmunology and Allergy Unit - AO Ordine Mauriziano di Torino, Turin, Italy.
Giovanni RollaDepartment of Medical Sciences, University of Turin, Turin, Italy.
Luisa BrussinoDepartment of Medical Sciences, University of Turin, Turin, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hypereosinophilic syndrome (HES) is a heterogeneous group of disorders characterised by persistent hypereosinophilia associated with organ damage. Due to its rarity and heterogeneity in its clinical presentation, HES remains underdiagnosed or misdiagnosed, often leading to delayed diagnosis and irreversible organ damage. The complexity of HES diagnosis is even more complicated due to the absence of standardised criteria. Moreover, the lack of structured referral pathways among specialists, including allergists, clinical immunologists, haematologists, and rheumatologists, further hinders optimal patient care. To address these challenges, the Italian National Hypereosinophilic Syndrome (INHES) Network aimed to enhance the diagnosis, management, and research of HES. INHES objectives also include connecting specialised centres, facilitating data collection on HES and eosinophilic-associated conditions, and improving healthcare standards through consensus guidelines. To do this, INHES has created a web-based platform called "Phleos" to develop a comprehensive referral map, ensuring timely and appropriate patient access to expert care. Phleos is a web-based datasheet, per GDPR regulations, to systematically collect anonymised clinical data, including absolute eosinophil counts, organ involvement, laboratory parameters, instrumental assessments, and treatments. A structured classification system enables differentiation among idiopathic, lymphocytic, myeloid, familial, reactive, and overlap forms of HES. Moreover, the platform integrates standardised diagnostic pathways and treatment protocols to harmonise patient care across participating centres. The INHES Network aims to mitigate diagnostic delays, optimise therapeutic decision-making, and advance research in eosinophilic disorders by fostering interdisciplinary collaboration and establishing a unified framework. This initiative represents a crucial step toward a cohesive national strategy, ultimately improving clinical outcomes for HES patients in Italy.

Indexed as

Data CollectionHypereosinophilic SyndromeInternetHumansItalyeosinophilic-related disorderseosinophilsHEShypereosinophilic syndrome (HES)INHESPhleosweb-based tool

Identifiers

PMID40740762
PMCPMC12307140

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.