Development of the 2023 ACR/EULAR Antiphospholipid Syndrome Classification Criteria, Phase III-D Report: Multi Criteria Decision Analysis.
Journal
Arthritis care & research
ISSN: 2151-4658
Titre abrégé: Arthritis Care Res (Hoboken)
Pays: United States
ID NLM: 101518086
Informations de publication
Date de publication:
12 Aug 2024
12 Aug 2024
Historique:
revised:
19
07
2024
received:
20
03
2024
accepted:
08
08
2024
medline:
13
8
2024
pubmed:
13
8
2024
entrez:
13
8
2024
Statut:
aheadofprint
Résumé
The 2023 ACR/EULAR Antiphospholipid Syndrome (APS) Classification Criteria development, aiming to identify patients with high likelihood of APS for research, employed a four-phase methodology. Phase I and II resulted in 27 proposed candidate criteria, organized into laboratory and clinical domains. Here, we summarize the last stage of Phase III efforts employing a consensus-based multi-criteria decision analysis (MCDA) to weigh candidate criteria and identify an APS classification threshold score. We evaluated 192 unique, international real-world cases referred for "suspected APS" with a wide range of APS manifestations. Using proposed candidate criteria, subcommittee members rank-ordered 20 representative cases from highly unlikely to highly likely APS. During an in-person meeting, the subcommittee refined definitions and participated in an MCDA exercise to identify relative weights of candidate criteria. Using consensus decisions and pairwise criteria comparisons, 1000Minds™ software assigned criteria weights, and we rank ordered 192 cases by their additive scores. A consensus-based threshold score for APS classification was set. Pre-meeting evaluation of 20 representative cases demonstrated variability in APS assessment. MCDA resolved 81 pairwise decisions; relative weights identified domain item hierarchy. After assessing 192 cases by weights and additive scores, the Steering Committee reached consensus that APS classification should require separate clinical and laboratory scores, rather than a single aggregate score, to ensure high specificity. Using MCDA, candidate criteria preliminary weights were determined. Unlike other disease classification systems using a single aggregate threshold score, separate clinical and laboratory domain thresholds were incorporated into the new APS classification criteria.
Sections du résumé
BACKGROUND
BACKGROUND
The 2023 ACR/EULAR Antiphospholipid Syndrome (APS) Classification Criteria development, aiming to identify patients with high likelihood of APS for research, employed a four-phase methodology. Phase I and II resulted in 27 proposed candidate criteria, organized into laboratory and clinical domains. Here, we summarize the last stage of Phase III efforts employing a consensus-based multi-criteria decision analysis (MCDA) to weigh candidate criteria and identify an APS classification threshold score.
METHODS
METHODS
We evaluated 192 unique, international real-world cases referred for "suspected APS" with a wide range of APS manifestations. Using proposed candidate criteria, subcommittee members rank-ordered 20 representative cases from highly unlikely to highly likely APS. During an in-person meeting, the subcommittee refined definitions and participated in an MCDA exercise to identify relative weights of candidate criteria. Using consensus decisions and pairwise criteria comparisons, 1000Minds™ software assigned criteria weights, and we rank ordered 192 cases by their additive scores. A consensus-based threshold score for APS classification was set.
RESULTS
RESULTS
Pre-meeting evaluation of 20 representative cases demonstrated variability in APS assessment. MCDA resolved 81 pairwise decisions; relative weights identified domain item hierarchy. After assessing 192 cases by weights and additive scores, the Steering Committee reached consensus that APS classification should require separate clinical and laboratory scores, rather than a single aggregate score, to ensure high specificity.
CONCLUSION
CONCLUSIONS
Using MCDA, candidate criteria preliminary weights were determined. Unlike other disease classification systems using a single aggregate threshold score, separate clinical and laboratory domain thresholds were incorporated into the new APS classification criteria.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Investigateurs
Nancy Agmon-Levin
(N)
Cassyanne Aguilar
(C)
Paula Alba
(P)
Oral Alpan
(O)
Ales Ambrozic
(A)
Luis Andrade
(L)
Simone Appenzeller
(S)
Yackov Berkun
(Y)
Antonio Cabral
(A)
Guillame Canaud
(G)
Pojen Chen
(P)
Cecilia Chighizola
(C)
Rolando Cimaz
(R)
Maria Jose Cuadrado
(MJ)
Philip G de Groot
(PG)
Philippe de Moerloose
(P)
Ronald Derksen
(R)
Thomas Dörner
(T)
Paul Fortin
(P)
Bill Giannakopoulos
(B)
Emilio B Gonzalez
(EB)
Murat Inanc
(M)
Gili Kenet
(G)
Munther Khamashta
(M)
Martin Kriegel
(M)
Steven Krilis
(S)
Danyal Ladha
(D)
Florian Manneville
(F)
Patti Massicotte
(P)
Gale McCarty
(G)
Jamal Mikdashi
(J)
Barry Myones
(B)
Lisa Sammaritano
(L)
Flavio Signorelli
(F)
Arzu Soybilgic
(A)
Scott Woller
(S)
Ray Zuo
(R)
Informations de copyright
This article is protected by copyright. All rights reserved.