BACKGROUND AND OBJECTIVES: The Italian Gruppo di Studio delle Piastrine recently developed a diagnostic algorithm to assist clinicians in the diagnosis of inherited thrombocytopenias. This algorithm is based on the simplest possible diagnostic investigations and can also be used in centers that are not highly specialized. The aim of the present study was to validate this diagnostic algorithm by applying it to a case series of genetic thrombocytopenias. DESIGN AND METHODS: The diagnostic algorithm was applied retrospectively to 46 consecutive patients observed during the last five years at a single institution. Twenty-eight were affected by defined illnesses or their variants, while 18 had a disorder that did not fit the criteria for any known genetic thrombocytopenia. The study was based on the evaluation of clinical records and laboratory tests. RESULTS: The diagnostic algorithm recognized: 4 homozygous and 4 heterozygous Bernard-Soulier syndromes, 11 MYH9-related diseases, one von WillebrandOs disease type 2B, one gray platelet syndrome and one X-linked thrombocytopenia with thalassemia. Moreover, it identified 4 patients with the clinical and laboratory features of heterozygous Bernard-Soulier syndrome not caused by mutations in the coding region of the GPIbalpha, GPIbbeta, GPIX or GPV genes, and two patients with the clinical phenotype of MYH9-related disease but without MYH9 mutations. Since the diagnostic flow chart did not allow prompt recognition of two subjects with MYH9-related disease, we introduced a small change to the previously proposed flow chart to obviate this defect. INTERPRETATION AND CONCLUSIONS: The diagnostic algorithm correctly diagnosed 26 of 28 patients with known disorders or phenotypic variants of known disorders. By a simple modification of the investigation sequence, its sensitivity reached 100%. The algorithm also identified 18 patients with new, as yet uncharacterized forms of genetic thrombocytopenia.
BACKGROUND AND OBJECTIVES: The Italian Gruppo di Studio delle Piastrine recently developed a diagnostic algorithm to assist clinicians in the diagnosis of inherited thrombocytopenias. This algorithm is based on the simplest possible diagnostic investigations and can also be used in centers that are not highly specialized. The aim of the present study was to validate this diagnostic algorithm by applying it to a case series of genetic thrombocytopenias. DESIGN AND METHODS: The diagnostic algorithm was applied retrospectively to 46 consecutive patients observed during the last five years at a single institution. Twenty-eight were affected by defined illnesses or their variants, while 18 had a disorder that did not fit the criteria for any known genetic thrombocytopenia. The study was based on the evaluation of clinical records and laboratory tests. RESULTS: The diagnostic algorithm recognized: 4 homozygous and 4 heterozygous Bernard-Soulier syndromes, 11 MYH9-related diseases, one von WillebrandOs disease type 2B, one gray platelet syndrome and one X-linked thrombocytopenia with thalassemia. Moreover, it identified 4 patients with the clinical and laboratory features of heterozygous Bernard-Soulier syndrome not caused by mutations in the coding region of the GPIbalpha, GPIbbeta, GPIX or GPV genes, and two patients with the clinical phenotype of MYH9-related disease but without MYH9 mutations. Since the diagnostic flow chart did not allow prompt recognition of two subjects with MYH9-related disease, we introduced a small change to the previously proposed flow chart to obviate this defect. INTERPRETATION AND CONCLUSIONS: The diagnostic algorithm correctly diagnosed 26 of 28 patients with known disorders or phenotypic variants of known disorders. By a simple modification of the investigation sequence, its sensitivity reached 100%. The algorithm also identified 18 patients with new, as yet uncharacterized forms of genetic thrombocytopenia.
Authors: Hamilton C Tsang; James B Bussel; Susan Mathew; Yen-Chun Liu; Allison A Imahiyerobo; Attilio Orazi; Julia T Geyer Journal: Mod Pathol Date: 2017-01-06 Impact factor: 7.842
Authors: Paolo Gresele; Emanuela Falcinelli; Silvia Giannini; Pio D'Adamo; Angela D'Eustacchio; Teresa Corazzi; Anna Maria Mezzasoma; Filomena Di Bari; Giuseppe Guglielmini; Luca Cecchetti; Patrizia Noris; Carlo L Balduini; Anna Savoia Journal: Haematologica Date: 2009-03-31 Impact factor: 9.941