Objective  To retrospectively analyze the causes of the dropping out in subjects in thy-roid-associated ophthalmopathy (TAO) clinical research, and to establish a predictive model of subject dropping out, to provide the basis for the subject management in TAO clinical trials.

Methods  Data of 384 subjects participating in the TAO clinical trial in the department of ophthalmology, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong Uni-versity School of Medicine, from November 2017 to April 2021 were collected. Lasso regression was used for variable screening and construting a logistic regression prediction model, and the differentiation and calibration of the receiver operator characteristic (ROC) curve and calibration curve validation model were drawn.

Results  A total of 384 sub-jects, of mean age (44.55±13.25) years, were 173 males (45.1%), 211 females (54.9%), and 53 subjects dropped out, with a dropping out rate of 13.8%. The main reasons for subject dropping out were untreated after enrollment, un-traced cause, refusal to follow-up, the impact of COVID-19, and unanswered phone calls. The results of multivariate Logistic regression analysis in the training set showed that treatment modality (OR=0.16, 95%CI 0.06 to 0.40, P<0.001), smoking (OR=0.19, 95%CI 0.03 to 0.78, P=0.04), diplopia score (OR=0.36, 95%CI 0.19 to 0.61, P<0.001), and source (OR=12.09, 95%CI 3.41 to 48.76, P<0.001) were independent predictors of subject dropping out. The area under curve (AUC) under the ROC curve in the validation set is 0.786, which indicates that the model built in the training set has good prediction ability, while the calibration curve shows good consistency in the validation set. Con-clusion  Applying the model established in this study to predict the dropping out of subjects in the upcoming TAO clinical reasearch, focusing on subjects with a probability of dropping out, providing warnings for problems that may lead to dropping out, and strengthening clinical research management training for researchers, can help reduce the subject dropping out rate and improve the quality of clinical research.

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