Doppler‐based predictive model for methotrexate resistance in low‐risk gestational trophoblastic neoplasia with myometrial invasion: prospective study of 147 patients. (3rd May 2021)

• Record Type: Journal Article
• Authors: Qin, J.; Zhang, S.; Poon, L.; Pan, Z.; Luo, J.; Yu, N.; Wang, L.; Wu, X.; Cheng, X.; Xie, X.; Lu, Y.; LU, W.
• Is Part Of: Ultrasound in obstetrics & gynecology. Volume 57:Number 5(2021)
• Page Start: 829
• Page End: 839
• Publication Date: 2021-05-03
• Subjects: Doppler -- low‐risk gestational trophoblastic neoplasia -- methotrexate resistance -- predictive model -- time‐averaged mean velocity; Ultrasonics in obstetrics -- Periodicals; Generative organs, Female -- Diseases -- Diagnosis -- Periodicals; Diagnosis, Ultrasonic -- Periodicals; Genital Diseases, Female -- ultrasonography -- Periodicals; Ultrasonography, Prenatal -- Periodicals; 618.047543
• DOI: 10.1002/uog.22069
• Languages: English
• ISSNs: 0960-7692

Abstract

ABSTRACT: Objectives: This prospective clinical study aimed to evaluate the vascularization characteristics of low‐risk gestational trophoblastic neoplasia (GTN) using Doppler imaging and to develop a predictive model for resistance to methotrexate (MTX). Methods: Patients with low‐risk GTN receiving primary MTX treatment were enrolled from the Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China, from September 2012 to August 2018. The primary endpoint was to develop and internally validate a predictive model for resistance to MTX therapy in these patients. In the training set, clinical features and Doppler hemodynamic parameters before MTX therapy were analyzed using logistic regression to identify independent predictors of MTX resistance, which were integrated into the model. The predictive performance of the model was evaluated by leave‐one‐out cross‐validation in the training dataset and internal validation in an independent‐sample test dataset. Results: The entire imaging protocol was completed by 147 eligible patients, of which 110 comprised the training set and 37 the test set. In the training set, cases with myometrial invasion (81.8%; 90/110) showed vascular‐enriched areas in the myometrium and high velocity and low impedance ratios of the uterine artery (UtA) compared to cases without myometrial invasion (18.2%; 20/110). On multivariate logistic regression analysis, time‐averaged mean velocity in UtA (UtA‐TAmean) and the International Federation of Gynecology and Obstetrics (FIGO) score were identified as independent predictors ( P = 0.009 and P = 0.043, respectively) of MTX resistance. The Doppler‐based predictive model, developed based on the 90 cases with myometrial invasion, was y = −2.95332 + 0.41696 × FIGO score + 0.03551 × UtA‐TAmean. The model showed an area under the curve of 0.757 (95% CI, 0.653–0.862) and the optimal cut‐off value was 0.50622, which had 45.2% sensitivity and 96.6% specificity. The model stratified patients with low‐risk GTN into low (< 10%), intermediate (10–90%) and high (> 90%) probability of MTX resistance, based on the threshold values of −1.59544 and 0.10046. The model had an accuracy of 74.4% (95% CI, 64.5–82.3%) in the cross‐validation and 72.7% (95% CI, 55.8–84.9%) in the internal validation. Conclusions: The Doppler‐based predictive model, combining a non‐invasive marker of tumor vascularity with the FIGO scoring system, can differentiate cases with low from those with high probability of developing MTX resistance and therefore has the potential to guide treatment options in patients with low‐risk GTN and myometrial invasion. © 2020 Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.