Outcomes in gestational and non-gestational choriocarcinoma: A retrospective cohort study with nomograms and web tools

妊娠期和非妊娠期绒毛膜癌的预后:一项基于列线图和网络工具的回顾性队列研究

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Abstract

BACKGROUND: Choriocarcinoma (CC), a rare and aggressive form of cancer, is composed of cytotrophoblasts and syncytiotrophoblasts. It is present in two subtypes: gestational choriocarcinoma (GCC) and non-gestational choriocarcinoma (NGCC). Recognizing the disparities between GCC and NGCC is essential for the precise staging, prognosis, and determination of the primary treatment strategy. OBJECTIVE: This study aimed to differentiate clinical outcomes, treatment responses, and prognostic factors between GCC and NGCC and to introduce innovative tools for personalized treatment strategies. DESIGN: A retrospective cohort study with Survival Analysis and Nomogram Development. METHODS: We analyzed data from the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) database and identified female patients diagnosed with GCC and NGCC between 2000 and 2020. The clinicopathological features of each group were compared using the chi-square test. Kaplan-Meier curves, log-rank tests, and Cox proportional hazard regression were used to assess overall survival and cancer-specific survival and to determine risk factors. The 5-year survival predicting nomogram was constructed, evaluated, and validated. RESULTS: The study included 919 patients with 719 CC and 200 patients with NGCC. The NGCC group was characterized by older age, a higher proportion of married individuals, more advanced disease stages, larger tumor sizes, and a higher frequency of surgical interventions than the GCC group. NGCC was associated with worse survival rates than GCC patients. CONCLUSIONS: This study highlights the critical role of chemotherapy in improving the survival of patients with NGCC, in contrast to its limited effect on GCC. The negative prognosis associated with radiotherapy underscores the urgent need for further investigation to optimize its use. In addition, the introduction of the first web-based survival prediction tool and predictive nomogram marked a significant advancement in personalized treatment strategies, enabling improved clinical outcomes by tailoring therapy to individual patients.

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