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Screening and diagnostic clinical algorithm for paroxysmal nocturnal hemoglobinuria: Expert consensus
Author(s) -
Röth Alexander,
Maciejewski Jaroslaw,
Nishimura JunIchi,
Jain Deepak,
Weitz Jeffrey I.
Publication year - 2018
Publication title -
european journal of haematology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.904
H-Index - 84
eISSN - 1600-0609
pISSN - 0902-4441
DOI - 10.1111/ejh.13059
Subject(s) - paroxysmal nocturnal hemoglobinuria , medicine , differential diagnosis , delphi method , consensus conference , pediatrics , case finding , algorithm , family medicine , intensive care medicine , pathology , artificial intelligence , computer science , tuberculosis
Objective Paroxysmal nocturnal hemoglobinuria ( PNH ) is a severe, life‐threatening disorder for which early diagnosis is essential. However, given the rarity of the disease and non‐specificity of symptoms, correct diagnosis may be delayed or missed. While various hematologic guidelines note common signs and symptoms associated with PNH , international expert consensus based on real‐world clinical experience and an actionable algorithm for non‐specialists to facilitate screening and diagnosis are lacking. The objective of the study is to develop a clinically relevant, consensus‐driven screening and diagnostic algorithm on PNH for non‐specialist clinicians. Methods An expert advisory committee of PNH experts from North America, Europe, and Japan was convened, and a modified Delphi methodology was employed to develop an algorithm to assist non‐specialist clinicians in identifying signs/symptoms of PNH and conducting appropriate differential diagnosis. Twelve globally representative Delphi panelists with clinical expertise in PNH were identified and recruited. Panelists provided their differential diagnosis for 5 blinded case studies via 2 rounds of online questionnaires. Responses mentioned by >50% of panelists in the first round were included in the second‐round questionnaire, at which point consensus was attained if >80% of panelists agreed on an approach. Results Consensus was reached for 95% of screening and diagnostic decision points and 90% of tests required at decision points. Conclusion These results facilitated development of a consensus‐based, clinically relevant algorithm, providing non‐specialist clinicians with actionable guidance on PNH screening and diagnosis.