Preoperative prognostic nomogram for prophylactic steroid treatment of patients with subclinical Cushing’s syndrome

BACKGROUND: Subclinical Cushing’s syndrome (SCS) is incidentally detected in a growing number of patients by advanced imaging technology. However, there is no consensus on the clinical management of SCS, especially in terms of whether prophylactic steroid treatment is necessary following adrenalectomy. In this study we developed a model based on preoperative indices for predicting postoperative adrenal insufficiency (AI) that can guide therapeutic decision-making. METHODS: A total of 27 patients with SCS who underwent adrenalectomy between August 2016 and August 2019 were enrolled and divided into AI and non-AI groups. Cox proportional hazards regression and least absolute shrinkage and selection operator analyses were performed to select relevant clinical parameters. The predictive performance of our model was evaluated by time-dependent receiver operating characteristic (ROC) curve and calibration curve analyses. RESULTS: Five clinical parameters (apolipoprotein A1, neutrophil–lymphocyte ratio, total cholesterol, platelet count, and homocysteine) were identified as the best predictors of replacement therapy (RT). The areas under the ROC curve for our prognostic model were 0.833, 0.945, and 0.967 for 3-, 4-, and 5-day non-(N)RT, respectively. The calibration curve of the 5 independent RT-related markers showed a good fit between nomogram-predicted probability of NRT and actual NRT, suggesting that our model has good predictive value. CONCLUSIONS: Our prognostic nomogram can help clinicians identify patients with AI who would benefit from RT so that timely treatment can be initiated. KEYWORDS: Subclinical Cushing’s syndrome (SCS); Replacement therapy (RT); Adrenal insufficiency (AI); Nomogram; Receiver operating characteristic (ROC)