Early detection of high disease activity in juvenile idiopathic arthritis by sequential monitoring of patients' health-related quality of life scores

Juvenile idiopathic arthritis (JIA) is a chronic disease. During its "high disease activity (HDA)" stage, JIA can cause severe pain, and thus could seriously affect patients' physical and psychological health. Early detection of the HDA stage of JIA can reduce the damage of the disease by treating it at an early stage and alleviating the painful experience of the patients. So far, no effective cure of JIA has been found, and one major goal of disease management is to improve patients' quality of life. To this end, patients' health-related quality of life (HRQOL) scores are routinely collected over time from JIA patients. In this paper, we demonstrate that a new statistical methodology called dynamic screening system (DySS) is effective for early detection of the HDA stage of JIA. By this approach, a patient's HRQOL scores are monitored sequentially, and a signal is given by DySS once the longitudinal pattern of the scores is found to be significantly different from the pattern of patients with low disease activity. Dimension reduction of the observed HRQOL scores and the corresponding impact on the performance of DySS are also discussed.