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FDG PET/CT parameters and CA-125 levels to predict optimal cytoreduction at primary cytoreductive surgery for advanced ovarian cancer (149)

医学 阶段(地层学) 卵巢癌 接收机工作特性 浆液性液体 曲线下面积 放射科 肾静脉 核医学 癌症 泌尿科 内科学 古生物学 生物
作者
Junhwan Kim,Maria Lee,Se Ik Kim,Joonhyung Gil,Jae‐Weon Kim,Gi Jeong Cheon
出处
期刊:Gynecologic Oncology [Elsevier BV]
卷期号:166: S91-S91
标识
DOI:10.1016/s0090-8258(22)01376-2
摘要

Objectives: To develop models predicting optimal cytoreduction in primary cytoreductive surgery (CRS) using clinical-pathologic characteristics and FDG PET/CT-derived parameters in advanced ovarian cancer. Methods: We retrospectively identified patients with stage III-IV ovarian cancer who underwent primary CRS between June 2013 and February 2020 at our center. We calculated the following 18 parameters: maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG), visual grade, and the number of lesions in three divided areas of the abdominal cavity. Optimal cytoreduction was defined as grossly no residual tumor after CRS. We constructed various predictive models for optimal cytoreduction by combining clinical-pathologic characteristics and FDG PET/CT-derived parameters. The predictive performance of each model was assessed based on the area under the receiver operating characteristic curve (AUC). Results: In total, 159 patients were included in the study. The median age was 55 years. The most common histologic subtype was serous (74.2%). Stage III and stage IV were 73.6% and 26.4%, respectively. Optimal cytoreduction was achieved in 104 patients (65.4%). The median CA-125 was 764 IU/ml. As a single variable, MTV, TLG, number of lesions above the renal vein showed high AUC for optimal cytoreduction, at 0.749, 0.748, and 0.748, respectively. The best predictive multivariable model consisted of CA-125 (<750 or ≥750 IU/ml), the number of lesions above the renal vein (<2 or ≥2), and MTV above the renal vein with an AUC of 0.770 for optimal cytoreduction. Conclusions: We successfully developed FDG PET/CT-based predictive model for optimal cytoreduction. This result may help determine patients’ treatment plans. Objectives: To develop models predicting optimal cytoreduction in primary cytoreductive surgery (CRS) using clinical-pathologic characteristics and FDG PET/CT-derived parameters in advanced ovarian cancer. Methods: We retrospectively identified patients with stage III-IV ovarian cancer who underwent primary CRS between June 2013 and February 2020 at our center. We calculated the following 18 parameters: maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG), visual grade, and the number of lesions in three divided areas of the abdominal cavity. Optimal cytoreduction was defined as grossly no residual tumor after CRS. We constructed various predictive models for optimal cytoreduction by combining clinical-pathologic characteristics and FDG PET/CT-derived parameters. The predictive performance of each model was assessed based on the area under the receiver operating characteristic curve (AUC). Results: In total, 159 patients were included in the study. The median age was 55 years. The most common histologic subtype was serous (74.2%). Stage III and stage IV were 73.6% and 26.4%, respectively. Optimal cytoreduction was achieved in 104 patients (65.4%). The median CA-125 was 764 IU/ml. As a single variable, MTV, TLG, number of lesions above the renal vein showed high AUC for optimal cytoreduction, at 0.749, 0.748, and 0.748, respectively. The best predictive multivariable model consisted of CA-125 (<750 or ≥750 IU/ml), the number of lesions above the renal vein (<2 or ≥2), and MTV above the renal vein with an AUC of 0.770 for optimal cytoreduction. Conclusions: We successfully developed FDG PET/CT-based predictive model for optimal cytoreduction. This result may help determine patients’ treatment plans.
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