Clinical endocrinology · 2020
Adrenal vein sampling: External validation of multinomial regression modelling and left adrenal vein-to-peripheral vein ratio to predict lateralization index without right adrenal vein sampling.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Bouchard-Bellavance Roxanne, Perrault Florence, Soulez Gilles, Chagnon Miguel, Kline Gregory A, Bourdeau Isabelle, Lacroix André, So Benny, Therasse Eric
Аннотация
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.
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.