Frontiers in Public Health (Oct 2022)

Develop and validate nomogram to predict cancer-specific survival for patients with testicular yolk sac tumors

  • Maoxian Li,
  • Maoxian Li,
  • Jinkui Wang,
  • Jinfeng Li,
  • Yongbo Zhang,
  • Xing Zhao,
  • Yang Lin,
  • Changkai Deng,
  • Fulin Li,
  • Qiang Peng

DOI
https://doi.org/10.3389/fpubh.2022.1038502
Journal volume & issue
Vol. 10

Abstract

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PurposeTesticular yolk sac tumor (TYST) is a rare malignant germ cell tumor that mainly occurs in young men. Due to the low incidence of yolk sac tumors, there is a lack of prospective cohort studies with large samples. We aimed to develop a nomogram to predict cancer-specific survival (CSS) in patients with TYST.Materials and methodsPatient information was downloaded from the Surveillance, Epidemiology and End Results (SEER) database. We enrolled all patients with TYST from 2000 to 2018, and all patients were randomly divided into a training set and a validation set. Univariate and multivariate Cox proportional hazards regression models were used to identify independent risk factors for patients. We constructed a nomogram based on the multivariate Cox regression model to predict 1-, 3-, and 5-year CSS in patients with TYST. We used a series of validation methods to test the accuracy and reliability of the model, including the concordance index (C-index), calibration curve and the area under the receiver operating characteristic curve (AUC).Results619 patients with TYST were enrolled in the study. Univariate and multivariate Cox regression analysis showed that age, T stage, M stage and chemotherapy were independent risk factors for CSS. A nomogram was constructed to predict the patient's CSS. The C-index of the training set and the validation set were 0.901 (95%CI: 0.859–0.847) and 0.855 (95%CI: 0.865–0.845), respectively, indicating that the model had excellent discrimination. The AUC showed the same results. The calibration curve also indicated that the model had good accuracy.ConclusionsIn this study, we constructed the nomogram for the first time to predict the CSS of patients with TYST, which has good accuracy and reliability and can help doctors and patients make clinical decisions.

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