Evidence map›Paper›PMID 34736505›Full record

ArticleOrphanet journal of rare diseases2021

The Italian National Registry for FSHD: an enhanced data integration and an analytics framework towards Smart Health Care and Precision Medicine for a rare disease.

Cinzia Bettio, Valentina Salsi, Mirko Orsini, Enrico Calanchi, Luca Magnotta, Luca Gagliardelli, June Kinoshita, Sonia Bergamaschi, Rossella Tupler

Open access · goldAbstract read
In one paragraph

Article in Orphanet journal of rare diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.5field-weighted citation impact, top 11% of its field
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

10 citing papers in PubMed, 31 citations in OpenAlex.

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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

9 authors at 1 institution in 2 countries.

Cinzia BettioDepartment of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy.
Valentina SalsiDepartment of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy.
Mirko OrsiniDataRiver Srl, Modena, Italy.
Enrico CalanchiDataRiver Srl, Modena, Italy.
Luca MagnottaDataRiver Srl, Modena, Italy.
Luca GagliardelliDepartment of Engineering "Enzo Ferrari", University of Modena and Reggio Emilia, Modena, Italy.
June KinoshitaFSHD Society, Reading, MA, USA.
Sonia BergamaschiDepartment of Engineering "Enzo Ferrari", University of Modena and Reggio Emilia, Modena, Italy.
Rossella TuplerDepartment of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy. rossella.tupler@unimore.it.ORCID 0000-0002-3797-1789
University of Modena and Reggio Emilia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Italian Clinical network for FSHD (ICNF) has established the Italian National Registry for FSHD (INRF), collecting data from patients affected by Facioscapulohumeral dystrophy (FSHD) and their relatives. The INRF has gathered data from molecular analysis, clinical evaluation, anamnestic information, and family history from more than 3500 participants.

methodsA data management framework, called Mediator Environment for Multiple Information Sources (MOMIS) FSHD Web Platform, has been developed to provide charts, maps and search tools customized for specific needs. Patients' samples and their clinical information derives from the Italian Clinical network for FSHD (ICNF), a consortium consisting of fourteen neuromuscular clinics distributed across Italy. The tools used to collect, integrate, and visualize clinical, molecular and natural history information about patients affected by FSHD and their relatives are described.

resultsThe INRF collected the molecular data regarding FSHD diagnosis conducted on 7197 subjects and identified 3362 individuals carrying a D4Z4 Reduced Allele (DRA): 1634 were unrelated index cases. In 1032 cases the molecular testing has been extended to 3747 relatives, 1728 carrying a DRA. Since 2009 molecular analysis has been accompanied by clinical evaluation based standardized evaluation protocols. In the period 2009-2020, 3577 clinical forms have been collected, 2059 follow the Comprehensive Clinical Evaluation form (CCEF). The integration of standardized clinical information and molecular data has made possible to demonstrate the wide phenotypic variability of FSHD. The MOMIS (Mediator Environment for Multiple Information Sources) data integration framework allowed performing genotype-phenotype correlation studies, and generated information of medical importance either for clinical practice or genetic counseling.

conclusionThe platform implemented for the FSHD Registry data collection based on OpenClinica meets the requirement to integrate patient/disease information, as well as the need to adapt dynamically to security and privacy concerns. Our results indicate that the quality of data collection in a multi-integrated approach is fundamental for clinical and epidemiological research in a rare disease and may have great value in allowing us to redefine diagnostic criteria and disease markers for FSHD. By extending the use of the MOMIS data integration framework to other countries and the longitudinal systematic collection of standardized clinical data will facilitate the understanding of disease natural history and offer valuable inputs towards trial readiness. This approach is of high significance to FSHD medical community and also to rare disease research in general.

Indexed as

Muscular Dystrophy, FacioscapulohumeralRegistriesDelivery of Health CareHumansItalyPrecision MedicineRare DiseasesData collectionData integrationFSHDRare disease registryRare diseases

Identifiers

PMID34736505
PMCPMC8567605
OpenAlexW3159971904

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.