A prognostic nomogram for the cancer-specific survival of patients with upper-tract urothelial carcinoma based on the Surveillance, Epidemiology, and End Results Database

Urothelial carcinoma is a type of urinary tumor that can occur in the upper urinary tract (renal pelvis and ureter) or the lower urinary tract (bladder and urethra). Although urothelial carcinoma is the fourth most common type of tumor [1], upper-tract urothelial carcinoma (UTUC) is a rare malignancy of the urinary system that accounts for about 10% of all renal tumors and 5% of all urothelial tumors [2]. UTUC includes carcinoma of the renal pelvis and ureter, and ureteral tumors are less common than renal pelvis tumors [3]. Most of the few studies that have investigated UTUC have combined UTUC with kidney cancer. However, since the incidence and mortality rates of UTUC have increased in recent years [3‐5], the present study focused on analyzing UTUC alone.

Age at diagnosis and being male are known risk factors for UTUC [3]. Surgery is the preferred approach for treating UTUC, and nephroureterectomy with bladder cuff excision has been the mainstay treatment [6]. The roles of chemotherapy and radiotherapy in advanced disease have not been clearly demonstrated, but some studies have found chemotherapy to be beneficial [7]. UTUC has a more-aggressive clinical course and a worse prognosis than bladder cancer [8], and the currently available prognostic models of UTUC are inadequate.

The traditional American Joint Committee on Cancer (AJCC) staging system provides clinically significant prognoses of UTUC and is currently the main reference standard for the prognosis of clinical treatment [9]. However, the AJCC staging system does not incorporate the entire pathological nature of the tumor, excluding potentially important factors when predicting the prognosis such as demographic characteristics, tumor size, tumor location, and the treatment applied [10‐12]. A nomogram is based on a prognostic model and it can clearly and concisely show how various prognostic factors influence certain outcome variables. A nomogram can be used to calculate the survival probability of individual patients, making it of great value in clinical practice [13].

The Surveillance, Epidemiology, and End Results (SEER) database has not previously been used to construct a prognostic nomogram for UTUC. Therefore, the purpose of this study was to establish a comprehensive nomogram that includes both demographic factors and clinicopathological features. The new prediction model was compared with the traditional AJCC staging system in order to determine its reliability. The developed nomogram has considerable clinical value in helping clinical staff to predict the 3-, 5-, and 8-year cancer-specific survival (CSS) probability of UTUC patients more comprehensively and on an individual basis.

Previous studies of UTUC have been inadequate, with many clinical studies combining UTUC with renal or bladder cancer, which is not consistent with UTUC have its own unique pathological features [23]. The recent increases in the incidence and mortality rates of UTUC mean that the importance of determining the clinical prognosis of UTUC is also increasing [24]. The prognosis of UTUC is poor, and there is a lack of comprehensive and simple support research for this disease.

The special clinical characteristics of UTUC make it necessary to develop a UTUC-specific nomogram for providing more-accurate prediction models for use by clinical staff. In this study we successfully constructed a prognostic nomogram for UTUC patients using case data obtained from the SEER database. Nomograms are widely used in oncology and medicine to predict prognoses and meet the needs of clinical staff to provide patients with individualized treatments, and they are easier to understand than the traditional AJCC staging system [25]. The multivariable Cox regression analysis performed in the present study revealed that age at diagnosis, sex, race, marital status, histological grade, tumor size, AJCC stage, surgery status, radiotherapy status, and chemotherapy status are associated with the prognosis of UTUC.

One of the prognostic factors included in the new model, age, has long been considered a risk factor for UTUC [26]. In contrast, whether sex is a risk factor for UTUC had not been determined previously [27], but the present study found that being female is a risk factor for survival (HR = 1.142, p < 0.01). Moreover, our study found for the first time that being unmarried is a risk factor of CSS affecting the prognosis of UTUC. A study showed that unmarried patients are at significantly higher risk of presentation with metastatic cancer, undertreatment, and death resulting from their cancer [28]. The relationship between marriage and cancer prognosis may be due to the following reasons. First of all, married patients may be higher than unmarried in terms of economic level and education level. Married persons also have better adherence to treatment, which may lead to differences in the prognosis of different marital status [29]. Second, a study showed that married patients were less likely to present with metastatic disease than those who were unmarried [28]. Finally, a review confirmed that marriage positively influences the likelihood of early diagnosis for all types of cancer. Correspondingly, if an unmarried person is diagnosed with cancer, the risk of developing advanced disease is greater, and the life expectancy is usually shorter [30]. In short, the prognosis of unmarried patients in this study is poor, and more reminders should be given to unmarried patients in this regard.

Histological grade, AJCC stage, surgery status, radiotherapy status, and chemotherapy status were also found to affect the survival probability. However, it is worth noting that the survival probability decreased in UTUC patients who received radiotherapy, which is consistent with the findings of Leow et al. [7] However, it should be noted that the gold standard treatment for UTUC is still surgery. Radiation therapy is usually performed in patients who have progressed to the point where surgery cannot be performed [31]. The experimental research on radiotherapy alone is very limited, which is worthy of further research in UTUC. On the other hand, this is a retrospective study and there are selection biases that are difficult to adjust. Therefore, the exact relationship between radiotherapy and UTUC prognosis needs further prospective experiments to confirm. In addition, like some previous studies [32, 33], tumor size was included in our model as a risk factor. However, the tumor site was not included in the model, meaning that this does not affect the prognosis of UTUC. Figure 2 clearly shows the relevant factors and their effects on the 3-, 5-, and 8-year CSS probabilities in UTUC patients. The total score can be obtained by adding the individual scores for each of the above factors, and clinical staff can use this score to predict the CSS probability of individual patients and thereby make decisions that are more likely to improve their prognosis.

After constructing the nomogram and analyzing related prognostic factors, it was compared with traditional the AJCC model using a training cohort and an internal validation cohort in order to evaluate the model underlying the nomogram. We used the C-index and AUC to evaluate the discrimination performance, and found that both of these parameters were higher for the nomogram than for the AJCC staging system in both the training and validation cohorts (Fig. 3). When adding a new parameter to a model and then performing a comparison to see whether the predictive power of the model has improved, the increase in the AUC is sometimes not obvious. Instead, the NRI is often used to compare the prediction powers of two models, while the IDI can be used to reflect the overall model improvement [34, 35]. The NRI of the prediction model showed that after adding the new index, the proportion of correct classifications for the 3-, 5-, and 8-year survival probabilities increased by 21.9, 24.7, and 25.9%, respectively, in the training cohort, and by 25.9, 27.2, and 26.5% in the validation cohort (p < 0.001). The IDI revealed that the new model improved the predictive abilities for the 3-, 5-, and 8-year survival probabilities compared with the old model by 2.9, 2.8, and 2.6%, respectively, in the training cohort, and by 3.1, 2.6, and 2.5% in the validation cohort (p < 0.001).

We used calibration curves to evaluate the calibration performance of the model. The 45-degree line in Fig. 4 is the standard line [36]. The broken lines in the figure are very close to the standard line and the predicted points are evenly distributed, which indicates that the nomogram exhibited good discrimination and calibration abilities both in the training and validation cohorts.

DCA is a method to evaluate prediction models by calculating the clinical net benefit. Figure 5 shows that the DCA curves of the nomogram for the 3-, 5-, and 8-year survival probabilities were almost all above those for the traditional AJCC model, which means that the new model has better clinical effectiveness.

This study was subject to several limitations. The first limitation is that the study had a retrospective design and obtained data from the SEER database, which inevitably resulted in the presence of selection bias and information bias; for example, it is improper to integrate “no” and “unknown” into one category in the SEER database. The second limitation was that some potentially important factors were not included in the study, making it insufficiently comprehensive, such as certain biological indicators and behavioral habits. Finally, external validation of the nomogram was not performed, and the use of only internal validation may lead to overfitting of the new model. In the future we plan to incorporate more predictors and validate the effect of the model with external cohorts in order to obtain more-accurate results.

This study is the first to establish a comprehensive UTUC nomogram based on the SEER database and evaluate it using a series of indicators. A particularly interesting finding was of the marital status being a prognostic factor for UTUC. The tumor size also significantly affected the prognosis, will the primary site of UTUC did not. Our novel nomogram can be used a tool to help clinical staff to predict the 3-, 5-, and 8-year CSS probabilities of UTUC patients more accurately than using the AJCC staging system.