The following is a summary of “A Diagnostic Prediction Model for Separating Juvenile Idiopathic Arthritis and Chronic Musculoskeletal Pain Syndrome,” published in the December 2022 issue of Pediatrics by Straalen, et al.
For a study, researchers sought to create and verify a diagnostic prediction model that, using patient-reported outcomes, could discriminate between juvenile idiopathic arthritis (JIA) and chronic musculoskeletal pain syndrome (CMPS).
The Juvenile Arthritis Multidimensional Assessment Report’s (JAMAR) ability to identify JIA from CMPS was examined in the retrospective cohort research. They looked at the JAMARs that 287 children filled out during their initial appointments with the pediatric rheumatology specialists at Wilhelmina Children’s Hospital in Utrecht, the Netherlands. In a penalized multivariable model appropriate for clinical use, pertinent JAMAR items for predicting a diagnosis of JIA were chosen. New data from the same center was used to validate the model later.
The validation data included 91 JAMARs (48 JIA, 43 CMPS), whereas the model development data included a total of 196 JAMARs (97 JIA, 99 CMPS). Asymmetric pain and swelling in the shoulder (OR, 2.34), trouble with self-care (OR, 2.41), skin rash (OR, 2.07), and asymmetric pain and swelling in the knee (OR, 2.29) were the factors in the prediction model that was most strongly related with a diagnosis of JIA as opposed to CMPS. The model performed well when applied to the validation data in calibration and discrimination (area under the receiver operating characteristic curve, 0.83; 95% CI, 0.74-0.92).
In individuals with comparable symptoms, a number of JAMAR questionnaire items might help to identify JIA from CMPS. By using patient-reported outcomes, they provided a simple, modified, and validated model to distinguish between the 2 diagnoses early in the presenting process to allow appropriate referral and treatment.