Hamdah Hanifa

Survival rates and predictors in gestational choriocarcinoma: Is chemotherapy always the answer?

Gestational choriocarcinoma is a highly malignant form of gestational trophoblastic neoplasia characterized by early vascular invasion and a strong tendency for widespread metastasis. To date, there is no consensus in the FIGO recommendations regarding when chemotherapy should be initiated following diagnosis. This study aimed to evaluate the impact of chemotherapy on survival and develop machine learning (ML) prognostic models for patients with gestational choriocarcinoma. We analyzed data from the SEER database [2000–2020]. Patients with histologically confirmed GC arising from the placenta were included, while those with other malignancies or missing key data were excluded. We conducted a Cox regression analysis for prognostic factors and developed ML models (using 5 algorithms) to predict 5-year survival rates. A validation method incorporating the area under the curve of the receiver operating characteristic curve was used to validate the accuracy and reliability of the ML models. We also investigated the role of multiple therapeutic options using the Kaplan–Meier survival analysis. This study included 732 patients with a median age of 32 years (54.5% ≥30 years); most were White (66.4%), and 44.3% had metastatic disease at diagnosis. Of these, 283 received chemotherapy, 116 underwent surgery alone, and 333 underwent both surgery and chemotherapy. Survival analysis showed no significant differences in survival between the treatment modalities. Multivariate Cox regression analysis identified older age, metastasis, and marital status as significant prognostic factors. Among the ML models, Random Forest Classifier achieved the highest performance. Feature importance analysis identified age, marital status, and metastasis as the most influential survival factors. The study suggests that chemotherapy may not have benefit for survival. Further multicenter prospective studies are needed to evaluate the importance of chemotherapy initiation.

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

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.