# The importance of using the oral glucose tolerance test when assessing the glycemic profile in patients with adrenal incidentaloma

## TL;DR

This study shows that the oral glucose tolerance test is important for accurately identifying dysglycemia in patients with adrenal incidentaloma.

## Contribution

The study demonstrates the added value of OGTT in diagnosing dysglycemia in adrenal incidentaloma patients compared to controls.

## Key findings

- MACS patients had the highest AUC >290mg.h/dL (75%) compared to NFAI and controls.
- The OGTT changed dysglycemia classification in 27% of MACS and 23% of NFAI patients.
- Patients with AI had 9.5 times higher odds of benefiting from OGTT for accurate classification.

## Abstract

There are limited data regarding the role of oral glucose tolerance test (OGTT) in classifying glycemic alterations in patients with adrenal incidentaloma (AI). This study aims to compare the frequency of dysglycemia [pre-diabetes mellitus (DM) and DM] among patients with non-functioning adrenal incidentalomas (NFAI), mild autonomous cortisol secretion (MACS), and controls; and to assess the area under the curve (AUC) in the OGTT and determine whether the OGTT was decisive in diagnosing dysglycemia in each population.

A cross-sectional study was conducted on 65 NFAI (1mg-dexamethasone suppression test [DST] ≤1.8μg/dL), 45 MACS (1mg-DST ≥1.9μg/dL), and 56 controls. The control group was selected based on normal adrenal imaging. Patients were classified as normoglycemic or dysglycemic based on fasting glucose, glycated hemoglobin, and OGTT.

AUC >290mg.h/dL was found in 75% of MACS, 55% of NFAI, and 22% of controls (p=0.008). The presence of AI was determinant for this result. Glucose levels ≥155 mg/dL at the 1-hour during the OGTT were observed in 75% of MACS, 65% of NFAI, and 28% of controls (p=0.01). Dysglycemia frequency was higher in MACS and NFAI than controls (91.1 vs. 90.8 vs. 73.2%; p=0.01). The OGTT changed the classification in 27% of MACS, 23% of NFAI, and 3% of controls (p=0.03). Presence of AI increased the odds ratio for benefiting from OGTT to obtain a more accurate dysglycemia classification by 9.5 times.

Patients with AI had a higher dysglycemia frequency, and a significant number of these patients benefited from OGTT in classifying glycemic alterations.