Objective: An international multidisciplinary initiative, jointly supported by the American College of Rheumatology and European Alliance of Associations for Rheumatology, is underway to develop new rigorous classification criteria to identify patients with high likelihood of antiphospholipid syndrome (APS) for research purposes. The present study was undertaken to apply an evidence- and consensus-based approach to identify candidate criteria and develop a hierarchical organization of criteria within domains. Methods: During phase I, the APS classification criteria steering committee used systematic literature reviews and surveys of international APS physician scientists to generate a comprehensive list of items related to APS. In phase II, we reviewed the literature, administered surveys, formed domain subcommittees, and used Delphi exercises and nominal group technique to reduce potential APS candidate criteria. Candidate criteria were hierarchically organized into clinical and laboratory domains. Results: Phase I generated 152 candidate criteria, expanded to 261 items with the addition of subgroups and candidate criteria with potential negative weights. Using iterative item reduction techniques in phase II, we initially reduced these items to 64 potential candidate criteria organized into 10 clinical and laboratory domains. Subsequent item reduction methods resulted in 27 candidate criteria, hierarchically organized into 6 additive domains (laboratory, macrovascular, microvascular, obstetric, cardiac, and hematologic) for APS classification. Conclusion: Using data- and consensus-driven methodology, we identified 27 APS candidate criteria in 6 clinical or laboratory domains. In the next phase, the proposed candidate criteria will be used for real-world case collection and further refined, organized, and weighted to determine an aggregate score and threshold for APS classification.

Development of a New International Antiphospholipid Syndrome Classification Criteria Phase I/II Report: Generation and Reduction of Candidate Criteria

Sciascia S.;
2021-01-01

Abstract

Objective: An international multidisciplinary initiative, jointly supported by the American College of Rheumatology and European Alliance of Associations for Rheumatology, is underway to develop new rigorous classification criteria to identify patients with high likelihood of antiphospholipid syndrome (APS) for research purposes. The present study was undertaken to apply an evidence- and consensus-based approach to identify candidate criteria and develop a hierarchical organization of criteria within domains. Methods: During phase I, the APS classification criteria steering committee used systematic literature reviews and surveys of international APS physician scientists to generate a comprehensive list of items related to APS. In phase II, we reviewed the literature, administered surveys, formed domain subcommittees, and used Delphi exercises and nominal group technique to reduce potential APS candidate criteria. Candidate criteria were hierarchically organized into clinical and laboratory domains. Results: Phase I generated 152 candidate criteria, expanded to 261 items with the addition of subgroups and candidate criteria with potential negative weights. Using iterative item reduction techniques in phase II, we initially reduced these items to 64 potential candidate criteria organized into 10 clinical and laboratory domains. Subsequent item reduction methods resulted in 27 candidate criteria, hierarchically organized into 6 additive domains (laboratory, macrovascular, microvascular, obstetric, cardiac, and hematologic) for APS classification. Conclusion: Using data- and consensus-driven methodology, we identified 27 APS candidate criteria in 6 clinical or laboratory domains. In the next phase, the proposed candidate criteria will be used for real-world case collection and further refined, organized, and weighted to determine an aggregate score and threshold for APS classification.
2021
73
10
1490
1501
Antiphospholipid Syndrome; Consensus; Delphi Technique; Humans; Predictive Value of Tests; Rheumatology; Severity of Illness Index
Barbhaiya M.; Zuily S.; Ahmadzadeh Y.; Amigo M.-C.; Avcin T.; Bertolaccini M.; Branch D.W.; de Jesus G.; Devreese K.M.J.; Frances C.; Garcia D.; Guillemin F.; Levine S.R.; Levy R.A.; Lockshin M.D.; Ortel T.; Seshan S.V.; Tektonidou M.; Wahl D.; Willis R.; Naden R.; Costenbader K.; Erkan D.; Agmon-Levin N.; Aguilar C.; Alba P.; Alpan O.; Ambrozic A.; Amoura Z.; Andrade D.; Andrade L.; Appenzeller S.; Esen B.A.; Atsumi T.; Berkun Y.; Cabral A.; Canaud G.; Cervera R.; Chen P.; Chighizola C.; Cimaz R.; Cohen H.; Costedoat-Chalumeau N.; Crowther M.; Cuadrado M.J.; de Groot P.G.; de Moerloose P.; Derksen R.; Diz-Kucukkaya R.; Dorner T.; Fortin P.; Giannakopoulos B.; Gomez-Puerta J.A.; Gonzalez E.B.; Inanc M.; Kenet G.; Khamashta M.; Kriegel M.; Krilis S.; Laskin C.; Massicotte P.; McCarty G.; Meroni P.L.; Mikdashi J.; Myones B.; Pengo V.; Petri M.; Roubey R.; Sammaritano L.; Sanna G.; Sciascia S.; Signorelli F.; Soybilgic A.; Tincani A.; Woller S.; Yelnik C.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1829324
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