The aim of this study was to (1) evaluate the ability of F-18 fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) parameters to predict suboptimal cytoreduction and (2) to create a risk model for predicting suboptimal cytoreduction in advanced ovarian cancer. From 2011 to 2015, 51 patients underwent primary cytoreductive surgery for advanced ovarian cancer were enrolled. A residual disease with maximal diameter > 1 cm was considered a suboptimal surgical result. The SUVmax values for nine abdominal regions, the sum of 9 regional SUVmax (WB1SUVmax) and WB2SUVmax (WB1SUVmax plus SUVmax of lymph nodes) were used for PET parameter. Multiple logistic regression analysis was used to determine the predictive value of PET and clinical parameters for risk model. In addition, assessments of disease-free survival (DFS) and overall survival (OS) were performed. Seventeen of the 51 patients (33.3%) underwent suboptimal cytoreduction. The ECOG status (OR, 4.091), SUVmax of central (OR, 5.250), right upper (OR, 4.148), left upper (OR, 5.921) and WB2SUVmax (OR, 4.148) were associated with suboptimal cytoreduction. The risk model can divide the risk groups of suboptimal cytoreduction (area under the curve (AUC), 0.775; p = 0.0001). The DFS and OS in the high-risk group were significantly worse than those in the low-risk group (p = 0.0379 for DFS; p = 0.0211 for OS). The presence of hypermetabolic lesions in the central, right upper, and left upper regions showed predictive value for suboptimal cytoreduction. Our risk model may be helpful for selecting patients who may show suboptimal cytoreduction.

This study aimed to develop a prognosis-predicting model based on [¹⁸F]fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) and clinicopathologic factors in locally advanced cervical cancer patients treated with concurrent chemoradiotherapy (CCRT). The medical records of 270 locally advanced cervical cancer patients who were treated with CCRT were collected from three institutions and reviewed retrospectively. A nomogram was used for predicting 2-year disease-free survival (DFS) and 5-year overall survival (OS) based on Cox proportional hazards regression. Predictor variables included nodal maximum standardized uptake value (SUVmax), primary tumor SUVmax, age, tumor size, stage, serum squamous cell carcinoma antigen level, and human papillomavirus status. Internal nomogram validation was performed. A nomogram for predicting the 2-year DFS and 5-year OS was constructed using six and seven parameters, respectively. With a focus on 2-year DFS, our model found nodal SUVmax to be the highest weighted negative prognostic factor. With a focus on 5-year OS, young age was the highest weighted negative prognostic factor. The concordance index was 0.75 and 0.78 for the 2-year DFS and 5-year OS, respectively. This nomogram is a predictive tool that can be used to counsel patients for predicting survival outcomes. Moreover, our prognosis-predicting model may make it possible to personalize treatment.