Pulmonary metastasis risk and overall survival score in choriocarcinoma: a novel nomogram-based risk assessment system.

BACKGROUND

At present, the risk of developing pulmonary metastasis and prognostic factors for choriocarcinoma (CC) remain unclear. This study aimed to investigate the independent risk factors and prognostic factors for pulmonary metastasis of CC and to construct a prognostic prediction model.

METHODS

We retrieved data on patients diagnosed with CC between 2010 and 2019 from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate logistic regressions were used to identify independent risk factors for developing pulmonary metastases in CC. Then, univariate and multivariate COX regression analyses were used to identify independent risk factors affecting the prognosis of patients with CC. Finally, we constructed a predictive nomogram and assessed the efficacy of the nomogram by receiver operating characteristic (ROC) curves, calibration curves, and decision analysis curves (DCAs).

RESULTS

Independent risk factors for developing pulmonary metastases in CC patients were gender and tissue type. Independent risk factors for the prognosis of CC patients were age, marriage, primary location, liver metastases, lung metastases, and surgical intervention. The results of ROC curves, calibration curves, and DCA in the training and validation groups confirmed that the nomogram could accurately predict the prognosis of CC patients.

CONCLUSIONS

Patients with CC are more likely to be young, have a more primary male genital system, have a poor prognosis, and are most likely to be complicated by pulmonary metastasis at initial diagnosis. A novel prediction model to predict the prognosis of CC patients has been constructed to personalize and guide clinical decision-making.