Extensive clinical experience: Hypothalamic-pituitary-adrenal axis recovery after adrenalectomy for corticotropin-independent cortisol excess

Objective To identify predictors of hypothalamic-pituitary-adrenal (HPA) axis recovery interval and severity of glucocorticoid withdrawal symptoms (GWS) in patients undergoing adrenalectomy for corticotropin-independent cortisol excess. Design This is a retrospective study of patients with mild autonomous cortisol excess (MACE), moderate and severe Cushing syndrome (CS) who developed adrenal insufficiency after unilateral adrenalectomy between 1998 and 2017. Results Adrenalectomy was performed in 81 patients (79% women, median age 52 years [IQR 42-62]). HPA axis recovery occurred at a median of 4.3 months (IQR 1.6-11.4) after adrenalectomy (severe CS vs moderate CS vs MACE: median 11.4 vs 2.8 vs 2.1 months, P < 0.01). Main predictors of HPA axis recovery interval included: preoperative serum cortisol concentration after 1-mg overnight dexamethasone suppression test >10 mu g/dL or >276 nmol/L (9.7 vs 1.3 months if cortisol <= 10 mu g/dL or <= 276 nmol/L, P < 0.01); body mass index (for every 3 kg/m(2) decrease, glucocorticoid taper increased by 1 month, P < 0.05); age <45 (11.4 vs 2.3 months if >= 45 years, P < 0.05); duration of symptoms prior to diagnosis >1 year (11.4 vs 2.8 months if <= 1 year); moon facies (11.4 vs 2.2 months if no rounding of the face); and myopathy (13.1 vs 2.7 months if no myopathy, P < 0.05). Patients with severe CS had a higher incidence of GWS compared to patients with MACE (66.7% vs 40.0%, P < 0.05) with a median of 1 and 0 events/patient, respectively. Conclusions The HPA axis recovery interval was the longest for patients with severe CS. Surprisingly, patients with moderate CS recovered their HPA axis as quickly as those with MACE. Glucocorticoid withdrawal symptoms were observed in all groups, with more events in patients with severe CS. This study emphasizes the need to counsel patients on expectations for HPA axis recovery and address intervention for GWS based on individual preoperative parameters.