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Prospective validation of the diagnostic score for molecular analysis of hereditary autoinflammatory syndromes in Italian children with periodic fever


Aim of the study was to verify in a prospective study the sensitivity and specificity of a recently elaborated diagnostic score for the prediction of the presence of mutation of genes associated with periodic fever [1].

Patients and methods

Detailed clinical information of 100 Italian patients with a clinical history of periodic fever was collected since June 2007. For each patient the Diagnostic score ( was calculated. According to previous experiences a cut-off > 1.32 was chosen to define those patients at high risk to carry relevant mutations. All patients were screened for mutations of MVK, TNFRSF1A and MEFV genes.


Ten patients displayed relevant (homozygous or compound heterozygous) mutations for MVK and MEFV genes. No structural mutations of TNFRSF1A gene were found. 10 patients dysplayed low-penetrance mutations of the TNFRSF1A gene (R92Q) or a single mutation of the MEFV gene. 80 patients were negative to all the three genes.

The Diagnostic score revealed high sensitivity (90%) and specificity (65%) in discriminating positive and negative patients. The regression tree analysis [1] was able to provide the correct identification of the affected gene in 7 out of the 9 positive identified by the diagnostic score.


This study confirm the validity of the Diagnostic score as a useful tool for the identification of children at higher risk to carry relevant mutations of genes associated with periodic fever.


  1. 1.

    Gattorno M: A diagnostic score for molecular analysis of hereditary autoinflammatory syndromes with periodic fever in children. Arthritis Rheum. 2008, 58: 1823-1832. 10.1002/art.23474.

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Author information

Correspondence to S Federici.

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Open Access This article is published under license to BioMed Central Ltd. This is an Open Access article is distributed under the terms of the Creative Commons Attribution 2.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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  • Regression Tree
  • Tree Analysis
  • Single Mutation
  • Correct Identification
  • Negative Patient