Competing risk nomogram predicting cause-specific mortality in older patients with testicular germ cell tumors.

Abstract

Testicular germ cell tumor (TGCT) is the most common type of malignancy in young men, but rarely in older adults. We aimed to construct a competing risk model to predict the prognosis for older patients with TGCT. We collected TGCT patients aged 50 years or older diagnosed between 2004 and 2015 from the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) database. We estimated the cumulative incidences of cause-specific death (CSD) and other causes of death and established a nomogram predicting cause-specific mortality in older patients with TGCT by Fine-Gray competing risk regression. The concordance index (C-index), calibration curves, area under the receiver operating characteristic curve (AUC), and decision analysis curves (DCA) were used to evaluate the differentiation, accuracy, and clinical significance of the nomogram. A total of 2,751 older TGCT patients were included in the study. The 3-, 5-, and 10-year cumulative incidences were 4.4, 5.0 and 6.1%, respectively, for cause-specific death, and 3.8, 6.2, 13.1%, respectively, for other causes of death. Predictors of cause-specific mortality in older TGCT included age, marital status, annual household income, histology, tumor size, stage and surgery. In the training and validation sets, the C-indexes were greater than 0.8, indicating that the nomogram had good discrimination. The AUC revealed the same result. The calibration curves showed good agreement between the predicted and observed results of the nomogram. DCA curves indicated that the nomogram had more clinical significance than the conventional American Joint Committee on Cancer (AJCC) staging. Based on the total nomogram score of each case, all patients were categorized into low-risk and high-risk groups, and risk categorization allowed the identification of cases with a high risk of death. We established a competing risk nomogram with good performance that may help clinicians accurately predict the prognosis of older TGCT patients.