Nomogram of Combining CT-Based Body Composition Analyses and Prognostic Inflammation Score: Prediction of Survival in Advanced Epithelial Ovarian Cancer Patients

• Published in: Academic radiology
• Main Authors: Wang, Xin, Zhang, Chao, Cao, Feng, Wang, Chuan-Bin, Dong, Jiang-Ning, Wang, Zhen-Huan
• Format: Journal Article
• Language: English
• Published: United States 01.09.2022
• Subjects: BMD bone mineral density; CT computer tomography; HE4 human epididymis protein 4; CI confidence intervals; Body composition; PMA area of paraspinal muscle; FIGO federation of gynecology and obstetrics; Ovarian cancer; PDS primary debulking surgery; Sarcopenia; PIS prognosis inflammation score; Computed tomography; Prognostic nomogram; Abbreviations: AEOC advanced epithelial ovarian cancer; AUC area under the curve; ROC receiver operating characteristic; CA 125 carbohydrate antigen 125; DFS disease free survival; BCC body composition changes; VFA visceral fat area; SFA subcutaneous fat area; C-index concordance index; HR hazard ratio; SMD skeletal muscle density; DCA decision curve analysis; QCT quantitative computed tomography; Systemic inflammation
• ISSN: 1878-4046
• DOI: 10.1016/j.acra.2021.11.011

To investigate the value of body composition changes measured by quantitative computer tomography (QCT) in evaluating the prognosis of advanced epithelial ovarian cancer (AEOC) patients who underwent primary debulking surgery (PDS) and adjuvant platinum-based chemotherapy, and constructed a nomogram model for predicting survival in combination with prognostic inflammation score (PIS). Fifty-seven patients with AEOC between 2012 and 2016 were retrospectively enrolled. Pre- and post-treatment CT images were used to analyze the body composition biomarkers. The subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), cross-sectional area of paraspinal skeletal muscle area (PMA), skeletal muscle density (SMD), body mineral density (BMD) were measured from two sets of CT images. In multivariate analyses, VFA gain, PMA loss, BMD loss, and PIS were independent risk factors of overall survival (OS) (HR = 3.7, 3.0, 2.8, 1.9, respectively, all p < 0.05). Receiver operating characteristic (ROC) curves showed that the prognostic model combining body composition changes (BCC) and PIS had the highest predictive performance (area under the curve = 0.890). The concordance index (C-index) of the prognostic nomogram was 0.779 (95% CI, 0.673-0.886). Decision curve analysis (DCA) demonstrated the prognostic nomogram had a great distinguishing performance. CT-based body composition analyses and PIS were associated with poor OS for AEOC patients who underwent PDS and adjuvant platinum-based chemotherapy. The prognostic nomogram with a combination of BCC and PIS was dependable in predicting survival for AEOC patients during treatment.