Xiaohong Lyu1,2, Dingyue Zhang2, Hui Pan1, Huijuan Zhu1, Shi Chen3, Lin Lu4. 1. Key Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 100730, Beijing, China. 2. Eight-year Program of Clinical Medicine, Peking Union Medical College, 100730, Beijing, China. 3. Key Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 100730, Beijing, China. chenshi@pumch.cn. 4. Key Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 100730, Beijing, China. lulin@pumch.cn.
Abstract
OBJECTIVES: The differential diagnosis of ACTH-dependent Cushing's disease (CS) is challenging. The gold standard approach bilateral inferior petrosal sinus sampling (BIPSS) is expensive and invasive, while other noninvasive tests, like the high-dose dexamethasone suppression test (HDDST), provide unsatisfactory diagnostic accuracy. This study aimed to find a new noninvasive practical approach with higher diagnostic accuracy to differently diagnose ACTH-dependent CS, which can be used in centers where BIPSS cannot be applied. METHODS: 264 Cushing's disease (CD) patients and 47 ectopic ACTH secretion syndrome (EAS) patients were analyzed in this single-center retrospective study (2011-2021). The multivariate logistic model was used to construct the scoring model. RESULTS: Female (adjusted OR 3.030, 95%CI 1.229-7.471), hypokalemia (0.209, 0.076-0.576), ACTH (0.988, 0.982-0.994), MRI pituitary lesion positive (8.671, 3.521-21.352), and HDDST positive (2.768, 1.139-6.726) have a strong association with the differential diagnosis of ACTH-dependent CS and were included in the final multivariable logistic regression model. A -14-to-14-point noninvasive scoring model was built on the model. The AUC of the noninvasive scoring model was 0.915 (95% CI 0.869-0.960), significantly higher than the AUC of HDDST (0.756, 95% CI 0.685-0.825, P = 0.004). The optimal cutoff of the model was ≥0 to diagnose CD. The sensitivity of the noninvasive scoring model was 91.3% (95% CI 87.3%-94.1%), and the specificity was 80.9% (95% CI 67.5%-89.6%). When the model's sensitivity was 100.0%, the cutoff was ≥ -10 with a specificity of 19.2%; when the model's specificity was 100.0%, the cutoff was ≥ 13 with a sensitivity of 22.7%. CONCLUSIONS: We developed a noninvasive scoring model to distinguish CD and EAS in ACTH-dependent CS patients with higher diagnostic utility than HDDST in the same cohort. The noninvasive scoring model might be applied in areas where BIPSS is unavailable, the CRH is hard to obtain, or the desmopressin stimulation is not widely applied. It also provided a triage tool for selecting patients that might benefit the most from a further BIPSS test.
OBJECTIVES: The differential diagnosis of ACTH-dependent Cushing's disease (CS) is challenging. The gold standard approach bilateral inferior petrosal sinus sampling (BIPSS) is expensive and invasive, while other noninvasive tests, like the high-dose dexamethasone suppression test (HDDST), provide unsatisfactory diagnostic accuracy. This study aimed to find a new noninvasive practical approach with higher diagnostic accuracy to differently diagnose ACTH-dependent CS, which can be used in centers where BIPSS cannot be applied. METHODS: 264 Cushing's disease (CD) patients and 47 ectopic ACTH secretion syndrome (EAS) patients were analyzed in this single-center retrospective study (2011-2021). The multivariate logistic model was used to construct the scoring model. RESULTS: Female (adjusted OR 3.030, 95%CI 1.229-7.471), hypokalemia (0.209, 0.076-0.576), ACTH (0.988, 0.982-0.994), MRI pituitary lesion positive (8.671, 3.521-21.352), and HDDST positive (2.768, 1.139-6.726) have a strong association with the differential diagnosis of ACTH-dependent CS and were included in the final multivariable logistic regression model. A -14-to-14-point noninvasive scoring model was built on the model. The AUC of the noninvasive scoring model was 0.915 (95% CI 0.869-0.960), significantly higher than the AUC of HDDST (0.756, 95% CI 0.685-0.825, P = 0.004). The optimal cutoff of the model was ≥0 to diagnose CD. The sensitivity of the noninvasive scoring model was 91.3% (95% CI 87.3%-94.1%), and the specificity was 80.9% (95% CI 67.5%-89.6%). When the model's sensitivity was 100.0%, the cutoff was ≥ -10 with a specificity of 19.2%; when the model's specificity was 100.0%, the cutoff was ≥ 13 with a sensitivity of 22.7%. CONCLUSIONS: We developed a noninvasive scoring model to distinguish CD and EAS in ACTH-dependent CS patients with higher diagnostic utility than HDDST in the same cohort. The noninvasive scoring model might be applied in areas where BIPSS is unavailable, the CRH is hard to obtain, or the desmopressin stimulation is not widely applied. It also provided a triage tool for selecting patients that might benefit the most from a further BIPSS test.
Authors: G Dickstein; C R DeBold; D Gaitan; G S DeCherney; R V Jackson; W R Sheldon; W E Nicholson; D N Orth Journal: J Clin Endocrinol Metab Date: 1996-08 Impact factor: 5.958