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

Abstract

Purpose: 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).

Method: 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.

Results: 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.

Conclusion: 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.

Keywords: AUC area under the curve; Abbreviations: AEOC advanced epithelial ovarian cancer; BCC body composition changes; BMD bone mineral density; Body composition; C-index concordance index; CA 125 carbohydrate antigen 125; CI confidence intervals; CT computer tomography; Computed tomography; DCA decision curve analysis; DFS disease free survival; FIGO federation of gynecology and obstetrics; HE4 human epididymis protein 4; HR hazard ratio; Ovarian cancer; PDS primary debulking surgery; PIS prognosis inflammation score; PMA area of paraspinal muscle; Prognostic nomogram; QCT quantitative computed tomography; ROC receiver operating characteristic; SFA subcutaneous fat area; SMD skeletal muscle density; Sarcopenia; Systemic inflammation; VFA visceral fat area.