Publications by authors named "Doan Tu Tran"
Objective: This study compares the diagnostic performance of the early-stage ovarian malignancy (EOM) score against other risk prediction models for identifying early-stage ovarian cancer.
Methods: This prospective cohort study involved 925 cases from the obstetrics and gynecology departments of two tertiary hospitals from May 2018 to December 2023. The data included gynecologic examination and/or ultrasound findings, menopausal status, ultrasonography features, serum CA125, and HE4 values, which were used to calculate the EOM score and compare it with other algorithms.
Article Synopsis
- - This study evaluated the effectiveness of three diagnostic tools—Risk of Ovarian Malignancy Algorithm (ROMA), Copenhagen Index (CPH-I), and Ovarian Adnexal Reporting and Data System (O-RADS)—for predicting ovarian cancer in patients with ovarian tumors.
- - Conducted on 462 patients between May 2020 and December 2022, the research found that O-RADS combined with cancer markers like CA125 provided the most accurate predictions, demonstrating high sensitivity and specificity.
- - The results indicated that while all models showed good predictive values, the combination of O-RADS with CA125 yielded the highest predictive accuracy for ovarian cancer detection.
Objectives: This study aimed to evaluate the diagnostic performances of the Copenhagen Index (CPH-I) and Risk of Ovarian Malignancy Algorithm (ROMA) in the preoperative prediction of ovarian cancer.
Methods: In a prospective cohort study, data were collected from 475 patients with ovarian masses diagnosed by gynecologic examination / ultrasound who were hospitalized at the Departments of Obstetrics and Gynecology, Hue University of Medicine and Pharmacy Hospital and Hue Central Hospital, Vietnam, between January 2018 and June 2020. ROMA and CPH-I were calculated based on measurements of serum carbohydrate antigen (CA-125) and human epididymis protein (HE4).