TY - JOUR
T1 - Development of a consensus core dataset in juvenile dermatomyositis for clinical use to inform research
AU - McCann, Liza J.
AU - Pilkington, Clarissa A.
AU - Huber, Adam M.
AU - Ravelli, Angelo
AU - Appelbe, Duncan
AU - Kirkham, Jamie J.
AU - Williamson, Paula R.
AU - Aggarwal, Amita
AU - Christopher-Stine, Lisa
AU - Constantin, Tamas
AU - Feldman, Brian M.
AU - Lundberg, Ingrid
AU - Maillard, Sue
AU - Mathiesen, Pernille
AU - Murphy, Ruth
AU - Pachman, Lauren M.
AU - Reed, Ann M.
AU - Rider, Lisa G.
AU - Van Royen-Kerkof, Annet
AU - Russo, Ricardo
AU - Spinty, Stefan
AU - Wedderburn, Lucy R.
AU - Beresford, Michael W.
N1 - Publisher Copyright:
© 2018 Article author(s).
PY - 2018/2
Y1 - 2018/2
N2 - Objectives: This study aimed to develop consensus on an internationally agreed dataset for juvenile dermatomyositis (JDM), designed for clinical use, to enhance collaborative research and allow integration of data between centres. Methods: A prototype dataset was developed through a formal process that included analysing items within existing databases of patients with idiopathic inflammatory myopathies. This template was used to aid a structured multistage consensus process. Exploiting Delphi methodology, two web-based questionnaires were distributed to healthcare professionals caring for patients with JDM identified through email distribution lists of international paediatric rheumatology and myositis research groups. A separate questionnaire was sent to parents of children with JDM and patients with JDM, identified through established research networks and patient support groups. The results of these parallel processes informed a face-to-face nominal group consensus meeting of international myositis experts, tasked with defining the content of the dataset. This developed dataset was tested in routine clinical practice before review and finalisation. Results: A dataset containing 123 items was formulated with an accompanying glossary. Demographic and diagnostic data are contained within form A collected at baseline visit only, disease activity measures are included within form B collected at every visit and disease damage items within form C collected at baseline and annual visits thereafter. Conclusions: Through a robust international process, a consensus dataset for JDM has been formulated that can capture disease activity and damage over time. This dataset can be incorporated into national and international collaborative efforts, including existing clinical research databases.
AB - Objectives: This study aimed to develop consensus on an internationally agreed dataset for juvenile dermatomyositis (JDM), designed for clinical use, to enhance collaborative research and allow integration of data between centres. Methods: A prototype dataset was developed through a formal process that included analysing items within existing databases of patients with idiopathic inflammatory myopathies. This template was used to aid a structured multistage consensus process. Exploiting Delphi methodology, two web-based questionnaires were distributed to healthcare professionals caring for patients with JDM identified through email distribution lists of international paediatric rheumatology and myositis research groups. A separate questionnaire was sent to parents of children with JDM and patients with JDM, identified through established research networks and patient support groups. The results of these parallel processes informed a face-to-face nominal group consensus meeting of international myositis experts, tasked with defining the content of the dataset. This developed dataset was tested in routine clinical practice before review and finalisation. Results: A dataset containing 123 items was formulated with an accompanying glossary. Demographic and diagnostic data are contained within form A collected at baseline visit only, disease activity measures are included within form B collected at every visit and disease damage items within form C collected at baseline and annual visits thereafter. Conclusions: Through a robust international process, a consensus dataset for JDM has been formulated that can capture disease activity and damage over time. This dataset can be incorporated into national and international collaborative efforts, including existing clinical research databases.
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U2 - 10.1136/annrheumdis-2017-212141
DO - 10.1136/annrheumdis-2017-212141
M3 - Article
AN - SCOPUS:85041537394
SN - 0003-4967
VL - 77
SP - 241
EP - 250
JO - Annals of the rheumatic diseases
JF - Annals of the rheumatic diseases
IS - 2
ER -