Testicular cancer is a cancer of the reproductive system that is common in young males and is the 29th most common new type of cancer in the world.[2] There are approximately 9,300 new testicular cancer patients in the US each year, making it the 18th most common new cancer for male patients.[4] Testicular cancers mostly consist of germ cell tumors, which often have a serious impact on health.[21,22] Therefore, early detection and treatment are of great importance in improving therapeutic effects and prolonging survival of patients with testicular cancer.[23] At present, the AJCC staging system is the most common tool used by clinicians in predicting the survival of cancer patients. It cannot predict the survival of the individual as it only contains the relevant characteristics of the tumor.[24] Therefore, the development of a new method that individualizes survival predictions is of great importance for testicular cancer patients.
Due to the limitations of the AJCC staging system, nomograms have become a new method for predicting the overall survival of cancer patients in recent years.[19] A nomogram is a predictive model that includes a variety of predictors, such as tumor and demographic characteristics, and types of therapy.[25–27] It displays the predicted survival of patients in a graphical manner based on a complex mathematical formula. Using the nomogram, we can calculate the score of each predictor variable and its cumulative score that matches with the results list to predict the survival of each patient.[28,29] Given that nomograms can contain diverse predictors and provide accurate predictions, they have been widely used to predict the survival of many other cancers, such as lung, breast, liver, stomach, and prostate cancer.[30–33]
The present study constructed a nomogram for predicting the survival of testicular cancer patients. We first extracted data on 25,468 testicular cancer patients from the SEER database, and analyzed the risk factors that affect their survival using multivariable COX regression analysis. We identified the seven predictors most relevant to survival (P<0.05) based on the AIC criteria, which were AJCC stage, race, SEER historic stage A, age at diagnosis, surgery status, marital status, and origin. We next clarified the impact of these factors on the long-term survival of testicular cancer patients using multivariable COX regression analysis. Therefore, we decided to include these in the final forecast nomogram. We then constructed a nomogram for the training cohort based on the filtered predictors. The nomogram for the training cohort has a higher C index (0.898) than the AJCC staging system (0.834). The nomogram has a higher AUC than the AJCC staging system for 3, 5, and 10 years after diagnosis. According to the results of the calibration curve of the training cohort at 3, 5, and 10 years after diagnosis, we found that the nomogram’s predictions on testicular cancer survival are very close to the actual survival. This indicates that the nomogram is more accurate in predicting the survival of testicular cancer patients than the AJCC staging system.
We used the validation cohort to validate the nomogram for testicular cancer patient survival. The C index of the nomogram for the validation cohort (0.872) was similar to that for the training cohort, but higher than that of the AJCC staging system (0.797). The AUC values of the validation cohort for 3, 5, and 10 years after diagnosis are similar to the nomogram of the training cohort. This indicates that the nomogram for the validation cohort has similar testicular cancer survival predictions to the nomogram of the training cohort. Meanwhile, we constructed calibration curves for the validation cohort at 3, 5, and 10 years after diagnosis, which confirmed this conclusion. We then evaluated the clinical significance of the nomogram for predicting the survival of testicular cancer patients. We found that the nomogram had higher NRI and IDI values for 3, 5, and 10 years after diagnosis than the AJCC staging system. This indicates that the nomogram has more accurate predictions for the overall survival of testicular cancer patients. DCA is often considered to be useful for verifying the benefits and clinical validity of a model.[19,34,35] In our research, the nomogram had better DCA results than the AJCC staging system at 3, 5, and 10 years after diagnosis. This indicates that, compared to the AJCC staging system, the nomogram is more clinically effective and accurate in predicting the survival of testicular cancer patients. In summary, the nomogram we constructed is better than the AJCC staging system at predicting the survival of testicular cancer patients, and provides a reference for patient treatment strategies.
Our study had several limitations. First, the research data comes from the SEER database which lacks some information, such as basic disease status, education level, drug treatments, religious beliefs, and family history, which may have an impact on the survival of testicular cancer patients. Second, cohort studies have inherent limitations, such as possible selection and information bias. Third, there are inherent limitations for any nomogram, such as the assumption that the data collected and analyzed are static in time, and there are no recognized reporting standards for performance.[19] In addition, our study only included testicular cancer patients in some regions of the US, therefore external data verification needs to be added for it to be applied to other regions. Future studies should include testicular cancer patients from other countries or regions to further verify the nomogram.