Xijuan Wang1, Xiurong Ke2, Junxia Min3. 1. Cancer Institute (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education, Key Laboratory of Molecular Biology in Medical Sciences), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. 2. Department of Orthopedic Surgery, The Third Hospital Affiliated to Wenzhou Medical University, Rui'an, China. 3. Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, The First Affiliated Hospital, Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou, China.
Abstract
BACKGROUND: Primary ovarian signet-ring cell carcinoma (POSRCC) is a rare subtype of ovarian carcinoma that is characterized by abundant mucin accumulation. POSRCC is aggressive, and the prognostic factors associated with its clinical outcome remain poorly defined. This study aimed to elucidate the clinical characteristics and survival of patients with POSRCC, and to establish an effective prognostic nomogram and risk stratification model to predict the risks associated with patient outcomes. METHODS: Data of patients with POSRCC from the period 1975 to 2016 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Univariable and multivariable analyses of demographic factors, clinicopathological characteristics, and treatments were conducted to identify significant prognostic parameters. The identified independent variables were integrated to develop a nomogram and risk stratification model. The discrimination and calibration of the nomogram were assessed with the concordance index (C-index), receiver operating characteristic (ROC) curves, and calibration curves. RESULTS: A total of 172 patients were identified as being eligible to participate in this study. The median overall survival (OS) time was 7 months [95% confidence interval (CI), 4.6-9.4 months]. The 1-, 3-, and 5-year OS rates were 35.5%, 15.3%, and 6%, respectively. A multivariable analysis of the primary patients identified the independent predictors for survival as age at diagnosis, race, marital status, T (primary tumor size) stage, and chemotherapy, which were all incorporated into the nomogram. The C-index was 0.70 (95% CI, 0.66-0.75), which was statistically higher than that of the International Federation of Gynecology and Obstetrics (FIGO) staging system (0.58; 95% CI, 0.53-0.63). ROC curve analysis also showed that the nomogram had good discrimination, with an area under the curve (AUC) of 0.74, 0.62, and 0.71 for 1-, 3-, and 5-year survival, respectively. The calibration curves showed good agreement between the prediction by the nomogram and actual observations. A risk stratification model was further used to classify patients into a low-risk or high-risk group. The median OS time for the low- and high-risk groups was 13.0 months (95% CI, 9.33-16.67) and 2.0 months (95% CI, 1.12-2.89), respectively. Surgery did not significantly prolong survival in either group [low-risk group: hazard ratio (HR), 0.69; 95% CI, 0.45-1.07; P=0.09; high-risk group: HR, 0.55; 95% CI, 0.46-0.67; P=0.18]. CONCLUSIONS: The proposed nomogram and risk stratification model showed accurate prognostic prediction for POSRCC. These methods could improve individualized evaluations of survival and therapeutic decisions for patients with POSRCC. 2021 Annals of Translational Medicine. All rights reserved.
BACKGROUND: Primary ovarian signet-ring cell carcinoma (POSRCC) is a rare subtype of ovarian carcinoma that is characterized by abundant mucin accumulation. POSRCC is aggressive, and the prognostic factors associated with its clinical outcome remain poorly defined. This study aimed to elucidate the clinical characteristics and survival of patients with POSRCC, and to establish an effective prognostic nomogram and risk stratification model to predict the risks associated with patient outcomes. METHODS: Data of patients with POSRCC from the period 1975 to 2016 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Univariable and multivariable analyses of demographic factors, clinicopathological characteristics, and treatments were conducted to identify significant prognostic parameters. The identified independent variables were integrated to develop a nomogram and risk stratification model. The discrimination and calibration of the nomogram were assessed with the concordance index (C-index), receiver operating characteristic (ROC) curves, and calibration curves. RESULTS: A total of 172 patients were identified as being eligible to participate in this study. The median overall survival (OS) time was 7 months [95% confidence interval (CI), 4.6-9.4 months]. The 1-, 3-, and 5-year OS rates were 35.5%, 15.3%, and 6%, respectively. A multivariable analysis of the primary patients identified the independent predictors for survival as age at diagnosis, race, marital status, T (primary tumor size) stage, and chemotherapy, which were all incorporated into the nomogram. The C-index was 0.70 (95% CI, 0.66-0.75), which was statistically higher than that of the International Federation of Gynecology and Obstetrics (FIGO) staging system (0.58; 95% CI, 0.53-0.63). ROC curve analysis also showed that the nomogram had good discrimination, with an area under the curve (AUC) of 0.74, 0.62, and 0.71 for 1-, 3-, and 5-year survival, respectively. The calibration curves showed good agreement between the prediction by the nomogram and actual observations. A risk stratification model was further used to classify patients into a low-risk or high-risk group. The median OS time for the low- and high-risk groups was 13.0 months (95% CI, 9.33-16.67) and 2.0 months (95% CI, 1.12-2.89), respectively. Surgery did not significantly prolong survival in either group [low-risk group: hazard ratio (HR), 0.69; 95% CI, 0.45-1.07; P=0.09; high-risk group: HR, 0.55; 95% CI, 0.46-0.67; P=0.18]. CONCLUSIONS: The proposed nomogram and risk stratification model showed accurate prognostic prediction for POSRCC. These methods could improve individualized evaluations of survival and therapeutic decisions for patients with POSRCC. 2021 Annals of Translational Medicine. All rights reserved.
Entities:
Keywords:
Chemotherapy; Surveillance, Epidemiology, and End Results database (SEER database); nomogram; ovarian cancer; survival
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