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Adrenal vein sampling: External validation of multinomial regression modelling and left adrenal vein-to-peripheral
Roxanne Bouchard-Bellavance1, Florence Perrault1, Gilles Soulez1,2
1Department of Radiology, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada.
Background:
Adrenal vein sampling (AVS) failure is mainly due to right adrenal vein unavailability. Multinomial regression modelling (MRM) and left adrenal vein-to-peripheral vein ratio (LAV/PV) were proposed to predict the lateralization index without the right AVS.
Objective:
To assess external validity of MRM and LAV/PV to predict lateralization index when right adrenal vein sampling is missing.
Design:
Diagnostic retrospective study.
Patients:
Development and validation cohorts included AVS of 174 and 122 patients, respectively, from 2 different centres.
Measurements:
Development and validation cohort data were used, respectively, for calibration and for validation of MRM and LAV/PV to predict the lateralization index without the right adrenal vein sampling. Sensitivity and specificity of MRM and LAV/PV were compared between both centres at different pre-established specificity thresholds based on receiver operating characteristic curves generated from the development cohort data.
Results:
At a specificity threshold of 95% set in the development cohort, specificity values exceeded 90% (range, 90.6%-98.8%) for all verified MRM and LAV/PV models in the validation cohort. Corresponding sensitivities for MRM and LAV/PV, respectively, range from 54.1% to 83.7% and 32.8% to 88.4% for the development cohort compared to 33.3%-87.5% and 2.8%-79.2% for the validation cohort. Overall, diagnostic accuracy of both methods was higher to detect right (82.8%-93.5%) than left (70.2%-80.6%) lateralization index status in both centres.
Conclusions:
Minimal changes in specificity from development to validation cohorts validate the use of MRM and LAV/PV to predict the lateralization index when the right AVS is missing. Both methods had better accuracy for right than left lateralization detection.
