Development and validation of a prediction model for depression in adolescents with polycystic ovary syndrome: A study protocol - Ding, Rui; Zhou, Heng; Yan, Xin; Liu, Ying; Guo, Yunmei; Tan, Huiwen; Wang, Xueting; Wang, Yousha; Wang, Lianhong (Frontiers in Psychiatry, 2022)
Background: The high prevalence and severity of depression in adolescents with polycystic ovary syndrome (PCOS) is a critical health threat that must be taken seriously. It is necessary to use an early warning model to identify high-risk groups for depression with PCOS in adolescents. In this study, we will develop and validate a warning model for depression in adolescents with PCOS by collecting relevant influencing factors. Methods: Model development and validation will be conducted using a retrospective study. The study will involve adolescents with PCOS as potential participants. We will collect not only general factors such as individual susceptibility factors, biological factors, and psychosocial environmental factors of depression in adolescence, but will also examine the pathological factors, illness perception factors, diagnosis and treatment factors, and symptom-related factors of PCOS, as well as the outcome of depression. LASSO will be used to fit a multivariate early warning model of depression risk. Data collected between January 2022 and August 2022 will be used to develop and validate the model internally, and data collected between September 2022 and December 2022 will be used for external validation. We will use the C statistic to measure the model's discrimination, the calibration plot to measure the model's risk prediction ability for depression, and the nomogram to visualize the model. Discussion: The ability to calculate the absolute risk of depression outcomes in adolescents with PCOS would allow preventative and therapeutic interventions to be delivered to adolescents at high risk, which would have significant implications for halting the progression of the disease and improving its prognosis.