TY - JOUR
T1 - Prediction of inactive disease in juvenile idiopathic arthritis
T2 - a multicentre observational cohort study
AU - van Dijkhuizen, Evert H Pieter
AU - Aidonopoulos, Orfeas
AU - Ter Haar, Nienke M
AU - Pires Marafon, Denise
AU - Magni-Manzoni, Silvia
AU - Ioannidis, Yannis E
AU - Putignani, Lorenza
AU - Vastert, Sebastiaan J
AU - Malattia, Clara
AU - De Benedetti, Fabrizio
AU - Martini, Alberto
PY - 2018/10/1
Y1 - 2018/10/1
N2 - Objectives: To predict the occurrence of inactive disease in JIA in the first 2 years of disease.Methods: An inception cohort of 152 treatment-naïve JIA patients with disease duration <6 months was analysed. Potential predictors were baseline clinical variables, joint US, gut microbiota composition and a panel of inflammation-related compounds in blood plasma. Various algorithms were employed to predict inactive disease according to Wallace criteria at 6-month intervals in the first 2 years. Performance of the models was evaluated using the split-cohort technique. The cohort was analysed in its entirety, and separate models were developed for oligoarticular patients, polyarticular RF negative patients and ANA positive patients.Results: All models analysing the cohort as a whole showed poor performance in test data [area under the curve (AUC): <0.65]. The subgroup models performed better. Inactive disease was predicted by lower baseline juvenile arthritis DAS (JADAS)-71 and lower relative abundance of the operational taxonomic unit Mogibacteriaceae for oligoarticular patients (AUC in test data: 0.69); shorter duration of morning stiffness, higher haemoglobin and lower CXCL-9 levels at baseline for polyarticular RF negative patients (AUC in test data: 0.69); and shorter duration of morning stiffness and higher baseline haemoglobin for ANA positive patients (AUC in test data: 0.72).Conclusion: Inactive disease could not be predicted with satisfactory accuracy in the whole cohort, likely due to disease heterogeneity. Interesting predictors were found in more homogeneous subgroups. These need to be validated in future studies.
AB - Objectives: To predict the occurrence of inactive disease in JIA in the first 2 years of disease.Methods: An inception cohort of 152 treatment-naïve JIA patients with disease duration <6 months was analysed. Potential predictors were baseline clinical variables, joint US, gut microbiota composition and a panel of inflammation-related compounds in blood plasma. Various algorithms were employed to predict inactive disease according to Wallace criteria at 6-month intervals in the first 2 years. Performance of the models was evaluated using the split-cohort technique. The cohort was analysed in its entirety, and separate models were developed for oligoarticular patients, polyarticular RF negative patients and ANA positive patients.Results: All models analysing the cohort as a whole showed poor performance in test data [area under the curve (AUC): <0.65]. The subgroup models performed better. Inactive disease was predicted by lower baseline juvenile arthritis DAS (JADAS)-71 and lower relative abundance of the operational taxonomic unit Mogibacteriaceae for oligoarticular patients (AUC in test data: 0.69); shorter duration of morning stiffness, higher haemoglobin and lower CXCL-9 levels at baseline for polyarticular RF negative patients (AUC in test data: 0.69); and shorter duration of morning stiffness and higher baseline haemoglobin for ANA positive patients (AUC in test data: 0.72).Conclusion: Inactive disease could not be predicted with satisfactory accuracy in the whole cohort, likely due to disease heterogeneity. Interesting predictors were found in more homogeneous subgroups. These need to be validated in future studies.
KW - Algorithms
KW - Arthritis, Juvenile/pathology
KW - Child
KW - Child, Preschool
KW - Female
KW - Humans
KW - Male
KW - Predictive Value of Tests
KW - Prognosis
KW - Prospective Studies
KW - Severity of Illness Index
U2 - 10.1093/rheumatology/key148
DO - 10.1093/rheumatology/key148
M3 - Article
C2 - 29931340
VL - 57
SP - 1752
EP - 1760
JO - Rheumatology
JF - Rheumatology
SN - 1462-0324
IS - 10
ER -