Skip to main content
Download PDF

Establishment and validation of a nomogram for predicting overall survival of upper-tract urothelial carcinoma with bone metastasis: a population-based study

BMC Urology volume 24, Article number: 100 (2024) Cite this article

Abstract

Background

Bone metastasis (BM) carries a poor prognosis for patients with upper-tract urothelial carcinoma (UTUC). This study aims to identify survival predictors and develop a prognostic nomogram for overall survival (OS) in UTUC patients with BM.

Methods

The Surveillance, Epidemiology, and End Results database was used to select patients with UTUC between 2010 and 2019. The chi-square test was used to assess the baseline differences between the groups. Kaplan–Meier analysis was employed to assess OS. Univariate and multivariate analyses were conducted to identify prognostic factors for nomogram establishment. An independent cohort was used for external validation of the nomogram. The discrimination and calibration of the nomogram were evaluated using concordance index (C-index), area under receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA). All statistical analyses were performed using SPSS 23.0 and R software 4.2.2.

Results

The mean OS for UTUC patients with BM was 10 months (95% CI: 8.17 to 11.84), with 6-month OS, 1-year OS, and 3-year OS rates of 41%, 21%, and 3%, respectively. Multi-organ metastases (HR = 2.21, 95% CI: 1.66 to 2.95, P < 0.001), surgery (HR = 0.72, 95% CI: 0.56 to 0.91, P = 0.007), and chemotherapy (HR = 0.37, 95% CI: 0.3 to 0.46, P < 0.001) were identified as independent prognostic factors. The C-index was 0.725 for the training cohort and 0.854 for the validation cohort, and all AUC values were > 0.679. The calibration curve and DCA curve showed the accuracy and practicality of the nomogram.

Conclusions

The OS of UTUC patients with BM was poor. Multi-organ metastases was a risk factor for OS, while surgery and chemotherapy were protective factors. Our nomogram was developed and validated to assist clinicians in evaluating the OS of UTUC patients with BM.

Peer Review reports

Background

Upper-tract urothelial carcinoma (UTUC), specifically affecting the renal pelvis and ureter, represents a small proportion (5%-10%) of all urothelial carcinomas [1]. This carcinoma carries a poor prognosis, as approximately 60% of patients are diagnosed with invasive disease. A correlation has been observed between a higher T stage and a reduced 5-year survival rate [2]. Additionally, around 7% of individuals with UTUC present with distant metastasis, commonly in the lungs, liver, and bones, which significantly impacts cancer-related mortality [3]. Notably, bone metastasis (BM) in UTUC patients is associated with an unfavorable prognosis [4]. Therefore, thoroughly evaluating therapeutic strategies and prognostic factors is crucial to improving survival outcomes. Unfortunately, the literature on this topic is notably limited, with only a few retrospective studies available, all of which have small sample sizes.

Standard treatments for UTUC include radical nephroureterectomy, chemotherapy, and radiotherapy [5, 6]. However, there is a lack of research on the management of UTUC patients with BM. Recent studies suggest that surgery and chemotherapy are optimal approaches, but further investigation is necessary to validate these findings [7].

The Surveillance, Epidemiology, and End Results (SEER) Program, conducted by the National Cancer Institute (NCI), offers a comprehensive and widely accessible cancer database, regarded as one of the most extensive worldwide [8]. In tumor-related studies, the nomogram is a commonly used model that utilizes multivariate regression analysis to estimate a patient's likelihood of clinical events [9]. Currently, there is no prognostic model specifically developed for overall survival (OS) in UTUC patients with BM.

To address this gap, we utilized clinical data from the SEER database to characterize UTUC patients initially diagnosed with BM, identifying relevant prognostic factors systematically. Consequently, we developed a prognostic prediction model to assess the impact of each factor on the prognosis of UTUC patients with BM and predict OS.

Methods

Data source and patient selection

We utilized the case-listing session of SEER*Stat version 8.3.9 software (https://seer.cancer.gov/seerstat/) to extract clinical data from the SEER database for patients diagnosed with UTUC between 2010 and 2019. This time frame was chosen as sites of metastases were not recorded before 2010. The primary tumor sites of UTUC were selected using the International Classification of Diseases for Oncology, 3rd edition (ICD-O-3) codes "C65.9-Renal pelvis" and "C66.9-Ureter." The patients with BM were identified by designating "YES" in the column for "SEER Combined Mets at DX-bone (2010 +)". Patients with a confirmed pathological diagnosis and complete records of metastasis sites were included. All types of BM were taken into account, including solitary BM and BM combined with other metastatic sites. The distant metastasis events were recorded at the initial diagnosis of UTUC, and patients received treatment after diagnosis. Patients who meet any of the following criteria are excluded: aged under 18 years, unknown distant metastasis, prior malignancy, incomplete survival data, and unknown cause of death. We initially included all UTUC patients to investigate OS, but ultimately only patients with BM were selected for the construction and validation of the predictive model.

We established a validation cohort using electronic and/or papery medical records of UTUC patients with BM from The First Affiliated Hospital of Ningbo University diagnosed between April 1, 2003, and May 31, 2022. The criteria used to select the validation cohort are consistent with those applied to the training cohort. The study was approved by the licensing committee of The First Affiliated Hospital of Ningbo University (Approval NO.: 2023-163RS). Informed consent was waived by the Institutional Review Board of The First Affiliated Hospital of Ningbo University. All methods employed in this study adhered to relevant guidelines and regulations.

Data collection and endpoint

We collected patients' clinical data, including age at diagnosis, sex, race, marital status, primary site, the total number of in situ/malignant tumors, laterality, histological type, T stage, N stage, tumor size, other metastases, surgery, radiotherapy, and chemotherapy. The primary endpoint was OS, defined as the time from diagnosis to death from any cause.

Statistical analysis

The categorical variables were presented as frequency (percentage), and the chi-square test was used to assess the baseline differences between the groups. The mean and 95% confidence intervals (CIs) were used to describe the OS time. The OS was assessed using Kaplan–Meier analysis, and the survival curves were compared using the log-rank test.

Univariate and multivariate Cox regression models were employed to determine hazard ratios (HRs) and 95% CIs to identify independent prognostic factors. Baseline variables deemed clinically relevant or demonstrating a univariate relationship with the outcome were incorporated into the multivariate Cox proportional-hazards regression model. Variables for inclusion were carefully chosen, given the number of events available, to ensure parsimony of the final model [10]. Therefore, candidate variables with a P value less than 0.2 on univariate analysis were included in multivariable model [11].

Multivariable time-to-event analysis was performed using Cox proportional hazards regression models to develop a nomogram using weighted estimators corresponding to each covariate derived from fitted Cox regression coefficients and estimates of variance. Validation of the nomogram was evaluated by discrimination and calibration using the Harrell concordance index (C-index), area under receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA) curve.

All statistical analyses and chart creation were conducted using SPSS 23.0 (IBM, Armonk, NY) and R software 4.2.2 (https://www.r-project.org/). A P-value less than 0.05 was considered statistically significant.

Results

Baseline characteristics

Based on the defined criteria, we initially identified 1,055 patients with distant metastasis and 7,770 patients without distant metastasis from the SEER database. Ultimately, a total of 468 patients with BM were included in the training cohort (Fig. 1). These comprised 212 patients (45.3%) with solitary BM, 5 patients (1.1%) with BM and brain metastasis, 78 patients (16.7%) with BM and liver metastasis, 96 patients (20.5%) with BM and lung metastasis, and 77 patients (16.5%) who had multiple metastases. In addition, 57 patients from The First Affiliated Hospital of Ningbo University were included in the validation cohort. The baseline characteristics of the patients from the two cohorts were compared in Table 1. Significant differences were observed in age (P = 0.035), race (P < 0.001), marital status (P < 0.001), tumor site (P < 0.001), TNT (P = 0.001), tumor laterality (P < 0.001), histological type (P < 0.001), T stage (P < 0.001), N stage (P < 0.001), tumor size (P < 0.001), surgery (P < 0.001), radiotherapy (P < 0.001), and chemotherapy (P = 0.039) between the training and validation sets.

Fig. 1
figure 1

Flow chart of patient identification and selection from SEER

Full size image
Table 1 Baseline characteristics of UTUC patients with BM in the training cohort and validation cohort
Full size table

Overall survival

The OS of 468 UTUC patients with BM was compared to that of 7,770 patients without distant metastasis. The mean OS for BM patients was 10 months (95%CI: 8.17 to 11.84 months), which was significantly shorter than 59 months (95%CI: 57.73 to 60.18 months) observed in patients without distant metastasis (Fig. 2A; P < 0.001). The 6-month OS, 1-year OS, and 3-year OS for BM patients were 41% (190/468), 21% (96/468), and 3% (15/468), respectively (Fig. 2A).

Fig. 2
figure 2

Kaplan–Meier survival curve of UTUC patients (A comparison of the OS between patients with BM and without distant metastasis; B comparison of the OS between patients with solitary BM and other types of solitary metastasis; C comparison of the OS between patients with solitary BM and multiple metastases)

Full size image

We conducted a subsequent analysis to compare the OS of UTUC patients with metastasis limited to a single site. Significant differences in OS were observed between patients with single metastasis in different sites (Fig. 2B; P < 0.001). Specifically, the OS of patients with BM (6-month OS: 50%, 1-year OS: 26%) was observed to be superior to those with liver metastasis (6-month OS: 34%, 1-year OS: 13%).

In addition, we compared the OS of UTUC patients with BM presenting in different metastasis patterns. A statistically significant difference in OS was observed among these patients with varied metastasis patterns (Fig. 2C; P < 0.001). The 6-month OS of patients with solitary BM was better than that of patients with both BM and other metastases.

Prognostic factors for UTUC patients with BM

As shown in Table 2, the univariate analysis revealed that several factors were significantly associated with patients' OS. These candidate variables included age (P < 0.001), marital status (P = 0.07), TNT (P = 0.1), laterality (P = 0.1), presence of other metastases (P < 0.001), surgery (P = 0.001), radiotherapy (P = 0.1), and chemotherapy (P < 0.001). Multivariate Cox regression analysis identified the following factors as significantly associated with OS in BM patients: presence of multi-organ metastases (HR = 2.21, 95% CI: 1.66 to 2.95, P < 0.001), surgery performed (HR = 0.72, 95% CI: 0.56 to 0.91, P = 0.007), and chemotherapy performed (HR = 0.37, 95% CI: 0.3 to 0.46, P < 0.001).

Table 2 Univariate and multivariate Cox regression analysis of included variables for OS in training cohort
Full size table

Construction of nomogram

The nomogram was developed based on the results of the multivariate Cox regression analysis to predict the OS of UTUC patients with BM (Fig. 3). Each subgroup of the variables was assigned a score ranging from 0 to 100 on the top scale. By summing up the total score and locating it on the bottom scale, the estimated probability of survival at each time point (6 months, 1 year, and 3 years) can be easily determined by drawing a vertical line. The nomogram illustrated that chemotherapy had the most substantial contribution to the prognosis, followed by the presence of other metastases and surgery.

Fig. 3
figure 3

Nomogram for predicting OS of UTUC patients with BM

Full size image

Validation of nomogram

The C-index was 0.725 for the training cohort and 0.854 for the validation cohort. All AUC values were > 0.679 (Fig. 4). The calibration curve of the training cohort for 6-month, 1- and 3-year OS displayed an excellent fitting degree between the nomogram prediction and actual observation (Fig. 5A). Similarly, the calibration curve of the 6-month, 1- and 3-year OS were well calibrated in the validation cohort (Fig. 5B). The DCA curve graphically showed that the nomogram achieved the highest net benefit over a wide range (about 0.2 to 0.8) of reasonable threshold probabilities (Fig. 6).

Fig. 4
figure 4

ROC curves of the prognostic nomogram (A-C training cohort; D-F validation cohort)

Full size image
Fig. 5
figure 5

Calibration curve of the prognostic nomogram (A training cohort; B validation cohort)

Full size image
Fig. 6
figure 6

DCA curve of the prognostic nomogram

Full size image

Discussion

UTUC with BM is a relatively rare subtype of urothelial carcinoma [12]. These patients have a poor prognosis, as shown by the survival curve in Fig. 2A, which demonstrates a more rapid decline compared to patients without distant metastasis over the next three years. Despite its rarity, the incidence of UTUC with BM has been increasing over the past few decades, highlighting the importance of exploring independent predictors of survival [13]. In this study, we conducted a comprehensive analysis of factors influencing the OS of UTUC patients with BM using the SEER database. Additionally, we developed a nomogram to assist clinicians and patients in making informed treatment decisions.

BM is a frequently observed site of metastasis in genitourinary cancer and has been the subject of extensive research. BM leads to skeletal-related events (SREs) such as pathological fractures, spinal cord compression, and hypercalcemia [14]. These events have a negative impact on the quality of life, increase healthcare burdens, and contribute to higher mortality rates. Early administration of bone-modifying agents to prevent SREs is recommended [15]. Owari et al. developed a scoring system specific to genitourinary cancer to predict survival rates in patients with BM, highlighting its clinical significance [16]. However, the limited set of predictors and a validation cohort with a lower proportion of patients undergoing surgery or radiotherapy make it challenging to draw definitive conclusions regarding treatment strategies.

Our study identified metastasis patterns, surgical interventions, and chemotherapy as key factors associated with OS in UTUC patients with BM, as determined by multivariate Cox regression analysis. Among these factors, chemotherapy had the most significant impact, followed by other metastases and surgery. Platinum-based chemotherapy (PBC) remains a crucial component of first-line treatment for metastatic urothelial carcinoma, extending median OS by three months [17]. Consistent with our findings, Alqaisi et al. reported improved OS in patients with BM after chemotherapy [18]. Additionally, chemotherapy facilitates the downstaging of UTUC, enabling surgical interventions [2, 19]. The combination of radical nephroureterectomy (RNU) and systemic chemotherapy for metastatic UTUC was found to be associated with an OS benefit compared to chemotherapy alone [20]. Furthermore, a retrospective study based on the National Cancer Database from the United States has demonstrated the high-intensity local treatments extended OS by 5 months in metastatic patients with stage IV UTUC [21]. Radiotherapy, as a routine treatment, can alleviate localized pain and improve SRE management [14, 22]. Maing et al. supported a radiation dose of ≥ 20 Gy as a factor in enhancing the prognosis of metastatic uroepithelial carcinoma [23]. However, Huang et al. found no significant survival benefit with radiotherapy in UTUC patients [24]. Therefore, we recommend an integrated approach involving surgery and chemotherapy as the optimal strategy for improving the prognosis of UTUC patients with BM.

The standard treatment for high-grade UTUC typically involves RNU and excision of the ipsilateral bladder cuff [25]. However, the significant rates of recurrence and cancer-specific mortality following surgery underscore the need for systemic treatments in the perioperative period to improve early-stage cancer management and patient survival [26]. Immunotherapy presents an opportunity to treat patients prior to RNU-related decline in renal function, potentially expanding the pool of patients eligible for PBC treatment by 30% [27]. In addition, for patients ineligible for chemotherapy, immunotherapy could represent a viable treatment option for metastatic UTUC [28]. Nonetheless, current data on the use of immunotherapy in managing metastatic UTUC is limited [25]. Considering the significance of chemotherapy in determining patient prognosis, immunotherapy may hold similar importance for patients who are ineligible for chemotherapy. Therefore, immunotherapy not only has the potential to enhance the effectiveness of chemotherapy and surgery but also holds promise as a novel alternative therapy.

Simultaneous metastases to other sites were common in UTUC patients with BM and significantly reduced their survival rates [7, 29]. Liu et al. suggested that the prognosis of stage IV metastatic uroepithelial carcinoma depends on the number of metastases from other organs, with no difference in OS compared to other metastatic sites when using bone metastasis as a reference [30]. Importantly, our findings contrast with those of Zhou et al. [7], who reported that lung metastasis was identified as a risk factor for OS in UTUC patients with BM. This discrepancy could be attributed to the fact that their study did not further stratify cases based on the presence of multiple metastases. It is plausible that the presence of metastasis in other regions along with lung metastasis contributes to a poorer OS, rather than lung metastasis alone being the sole causative factor. In addition, their study did not develop a nomogram to facilitate clinical decision-making [7]. Our research addresses these gaps and indicates that multi-organ metastases are independent risk factors.

To the best of our knowledge, this is the first nomogram developed to predict the survival of UTUC patients with BM based on a large database with long-term follow-up. Importantly, we reviewed hospitalization medical records from a single center over the past 20 years to collect patients and establish an external validation set. However, several limitations of our study should be taken into account. Firstly, it is important to acknowledge that our study is retrospective in nature, which may introduce selection bias. This bias arises from the fact that patients who received more aggressive therapies may have inherently better chances of survival. Patients who did not receive chemotherapy were likely individuals with a notably unfavorable prognosis, potentially due to the presence of comorbidities. Secondly, the database lacked some potential prognostic parameters, such as smoking status, performance status, comorbidities, and time to metastasis. Thirdly, the database did not provide specific details on surgical modalities, radiotherapy regimens, chemotherapy protocols, and systemic treatments. Fourthly, the patients who develop new tumors after being diagnosed with BM were not excluded. Fifthly, surgery information recorded in the SEER database typically focuses on the primary site, and not all patients undergo surgery for metastatic sites. Additionally, the number of cases involving relevant treatments like radiotherapy was minimal. Lastly, it should be noted that our single-center external dataset lacks representativeness, as there is a substantial difference in population characteristics compared to the training group.

Conclusions

In conclusion, the OS of UTUC patients with BM is worse than that of patients without distant metastases. The OS of patients with solitary BM is better than that of patients with solitary liver metastasis. Multi-organ metastases are independent risk factors for OS in patients with BM, while surgery and chemotherapy are protective factors. Our nomogram, which incorporates metastasis patterns, surgery, and chemotherapy, is expected to serve as an individualized tool for clinicians to estimate the OS of UTUC patients with BM.

Availability of data and materials

The datasets generated and/or analyzed during the current study are available in the SEER database, https://seer.cancer.gov/. Other datasets are available from the corresponding author on reasonable request.

Abbreviations

BM:

Bone metastasis

UTUC:

Upper-tract urothelial carcinoma

OS:

Overall survival

AUC:

Area under receiver operating characteristic curve

DCA:

Decision curve analysis

SEER:

Surveillance, Epidemiology, and End Results

NCI:

National Cancer Institute

HR:

Hazard ratio

CI:

Confidence interval

SRE:

Skeletal-related event

PBC:

Platinum-based chemotherapy

RNU:

Radical nephroureterectomy

References

  1. Miyazaki J, Nishiyama H. Epidemiology of urothelial carcinoma. Int J Urol. 2017;24(10):730–4.

    Article  PubMed  Google Scholar 

  2. Kim DK, Cho KS. Neoadjuvant chemotherapy for upper tract urothelial carcinoma. Transl Cancer Res. 2020;9(10):6576–82.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Raman JD, Messer J, Sielatycki JA, Hollenbeak CS. Incidence and survival of patients with carcinoma of the ureter and renal pelvis in the USA, 1973–2005. BJU Int. 2011;107(7):1059–64.

    Article  PubMed  Google Scholar 

  4. Cheaib JG, Claus LE, Patel HD, Kates MR, Matoso A, Hahn NM, et al. Site of metastatic recurrence impacts prognosis in patients with high-grade upper tract urothelial carcinoma. Urol Oncol. 2021;39(1):74.e9-.e16.

    Article  PubMed  Google Scholar 

  5. Zalay O, Yan M, Sigurdson S, Malone S, Vera-Badillo FE, Mahmud A. Adjuvant Radiotherapy for Upper Tract Urothelial Carcinoma: Systematic Review and Meta-Analysis. Curr Oncol. 2022;30(1):19–36.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Leow JJ, Orsola A, Chang SL, Bellmunt J. A contemporary review of management and prognostic factors of upper tract urothelial carcinoma. Cancer Treat Rev. 2015;41(4):310–9.

    Article  PubMed  Google Scholar 

  7. Zhou M, Zhang J, Chen X, Wang Z, Liang W. Clinical features and prognostic indicators in upper-tract urothelial carcinoma with bone metastasis. Front Surg. 2022;9: 928294.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Liang W, He J, Shen Y, Shen J, He Q, Zhang J, et al. Impact of Examined Lymph Node Count on Precise Staging and Long-Term Survival of Resected Non-Small-Cell Lung Cancer: A Population Study of the US SEER Database and a Chinese Multi-Institutional Registry. J Clin Oncol. 2017;35(11):1162–70.

    Article  PubMed  Google Scholar 

  9. Wu J, Zhang H, Li L, Hu M, Chen L, Xu B, et al. A nomogram for predicting overall survival in patients with low-grade endometrial stromal sarcoma: A population-based analysis. Cancer Commun (Lond). 2020;40(7):301–12.

    Article  PubMed  Google Scholar 

  10. Stone GW, Maehara A, Lansky AJ, de Bruyne B, Cristea E, Mintz GS, et al. A prospective natural-history study of coronary atherosclerosis. N Engl J Med. 2011;364(3):226–35.

    Article  CAS  PubMed  Google Scholar 

  11. Kang SJ, Cho YR, Park GM, Ahn JM, Han SB, Lee JY, et al. Predictors for functionally significant in-stent restenosis: an integrated analysis using coronary angiography, IVUS, and myocardial perfusion imaging. JACC Cardiovasc Imaging. 2013;6(11):1183–90.

    Article  PubMed  Google Scholar 

  12. Zhang X, Wang P, Qi K, Qiao Q, Jiang Y. The role of surgery on primary site in metastatic upper urinary tract urothelial carcinoma and a nomogram for predicting the survival of patients with metastatic upper urinary tract urothelial carcinoma. Cancer Med. 2021;10(22):8079–90.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Leow JJ, Chong KT, Chang SL, Bellmunt J. Upper tract urothelial carcinoma: a different disease entity in terms of management. ESMO open. 2016;1(6):e000126.

    Article  PubMed  Google Scholar 

  14. Tsuda Y, Nakagawa T, Shinoda Y, Kanatani A, Kawai T, Taguchi S, et al. Skeletal-related events and prognosis in urothelial cancer patients with bone metastasis. Int J Clin Oncol. 2017;22(3):548–53.

    Article  PubMed  Google Scholar 

  15. Owari T, Miyake M, Nakai Y, Morizawa Y, Itami Y, Hori S, et al. Clinical Features and Risk Factors of Skeletal-Related Events in Genitourinary Cancer Patients with Bone Metastasis: A Retrospective Analysis of Prostate Cancer, Renal Cell Carcinoma, and Urothelial Carcinoma. Oncology. 2018;95(3):170–8.

    Article  PubMed  Google Scholar 

  16. Owari T, Miyake M, Nakai Y, Tanaka N, Itami Y, Hirao S, et al. External validation of a genitourinary cancer-specific prognostic scoring system to predict survival for patients with bone metastasis (modified B-FOM scoring model): Comparison with other scoring models in terms of accuracy. J Bone Oncol. 2021;26:100344.

    Article  PubMed  Google Scholar 

  17. Galsky MD, Chen GJ, Oh WK, Bellmunt J, Roth BJ, Petrioli R, et al. Comparative effectiveness of cisplatin-based and carboplatin-based chemotherapy for treatment of advanced urothelial carcinoma. Ann Oncol. 2012;23(2):406–10.

    Article  CAS  PubMed  Google Scholar 

  18. Alqaisi HA, Stecca C, Veitch ZW, Riromar J, Kaiser J, Fallah-Rad N, et al. The prognostic impact of bone metastasis in patients with metastatic urothelial carcinoma treated with first-line platinum-based chemotherapy. Ther Adv Med Oncol. 2022;14:17588359221094880.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Leow JJ, Chong YL, Chang SL, Valderrama BP, Powles T, Bellmunt J. Neoadjuvant and Adjuvant Chemotherapy for Upper Tract Urothelial Carcinoma: A 2020 Systematic Review and Meta-analysis, and Future Perspectives on Systemic Therapy. Eur Urol. 2021;79(5):635–54.

    Article  CAS  PubMed  Google Scholar 

  20. Seisen T, Jindal T, Karabon P, Sood A, Bellmunt J, Rouprêt M, et al. Efficacy of Systemic Chemotherapy Plus Radical Nephroureterectomy for Metastatic Upper Tract Urothelial Carcinoma. Eur Urol. 2017;71(5):714–8.

    Article  PubMed  Google Scholar 

  21. Paciotti M, Nguyen DD, Modonutti D, Haeuser L, Lipsitz S, Mossanen M, et al. Impact of high-intensity local treatment on overall survival in stage IV upper tract urothelial carcinoma. Urol Oncol. 2021;39(7):436.e1-436.e10.

    Article  PubMed  Google Scholar 

  22. Sprave T, Verma V, Förster R, Schlampp I, Hees K, Bruckner T, et al. Bone density and pain response following intensity-modulated radiotherapy versus three-dimensional conformal radiotherapy for vertebral metastases - secondary results of a randomized trial. Radiat Oncol. 2018;13(1):212.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Manig L, Käsmann L, Janssen S, Rades D. Predicting Survival After Irradiation of Metastases from Transitional Carcinoma of the Bladder. Anticancer Res. 2016;36(12):6663–5.

    Article  PubMed  Google Scholar 

  24. Huang YC, Chang YH, Chiu KH, Shindel AW, Lai CH. Adjuvant radiotherapy for locally advanced upper tract urothelial carcinoma. Sci Rep. 2016;6:38175.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Kolawa A, D’Souza A, Tulpule V. Overview, Diagnosis, and Perioperative Systemic Therapy of Upper Tract Urothelial Carcinoma. Cancers (Basel). 2023;15(19):4813.

    Article  CAS  PubMed  Google Scholar 

  26. Rouprêt M, Seisen T, Birtle AJ, Capoun O, Compérat EM, Dominguez-Escrig JL, et al. European Association of Urology Guidelines on Upper Urinary Tract Urothelial Carcinoma: 2023 Update. Eur Urol. 2023;84(1):49–64.

    Article  PubMed  Google Scholar 

  27. Kaag MG, O’Malley RL, O’Malley P, Godoy G, Chen M, Smaldone MC, et al. Changes in renal function following nephroureterectomy may affect the use of perioperative chemotherapy. Eur Urol. 2010;58(4):581–7.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Ni K, Yu C, Wang H, Zhu S, Yu S, Li G. Immunotherapy with or without targeted therapy for metastatic upper tract urothelial carcinoma: case report and literature review. Heliyon. 2023;9(5):e15813.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Wang Z, Cheng Y, Chen S, Shao H, Chen X, Wang Z, et al. Novel prognostic nomograms for female patients with breast cancer and bone metastasis at presentation. Ann Transl Med. 2020;8(5):197.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Liu L, Yuan H, Wang Q, Li C. Effects of Different Organ Metastases on the Prognosis of Stage IV Urothelial Carcinoma of the Bladder. J Oncol. 2022;2022:8594022.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors would like to express their gratitude to the Surveillance, Epidemiology, and End Results (SEER) database, for the data provided in this study.

Funding

This study was funded by the Ningbo Top Medical and Health Research Program (No. 2022020203) and Medical scientific research projects of Zhejiang Province (No. 2024KY306).

Author information

Authors and Affiliations

  1. Department of Urology, The First Affiliated Hospital of Ningbo University, Ningbo, China

    Jiasheng Hu, Haowen Gu, Dongxu Zhang, Min Wen, Zejun Yan & Baiyang Song

  2. Ningbo Clinical Research Center for Urological Disease, Ningbo, China

    Jiasheng Hu, Dongxu Zhang, Min Wen & Zejun Yan

  3. Shandong First Medical University, Jinan, 250021, China

    Chengxin Xie

  4. Department of Orthopedics, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, China

    Chengxin Xie

Authors
  1. Jiasheng Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Haowen Gu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dongxu Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Min Wen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Zejun Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Baiyang Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Chengxin Xie
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

(I) Conception and design: CXX, BYS; (II) Administrative support: BYS, ZJY; (III) Provision of study materials or patients: BYS, JSH; (IV) Collection and assembly of data: JSH, HWG, DXZ; (V) Data analysis and interpretation: CXX, JSH, HWG, MW; (VI) Manuscript writing: JSH, BYS, CXX; (VII) Final approval of manuscript: All authors.

Corresponding authors

Correspondence to Baiyang Song or Chengxin Xie.

Ethics declarations

Ethics approval and consent to participate

This study was approved from the Institutional Review Board of The First Affiliated Hospital of Ningbo University (Approval NO.: 2023-163RS). Informed consent was waived by the Institutional Review Board of The First Affiliated Hospital of Ningbo University, as this retrospective study did not involve patient biological samples or any information that could potentially lead to participant identification. The present study adhered to the 1964 Helsinki Declaration and its subsequent amendments or comparable ethical standards.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hu, J., Gu, H., Zhang, D. et al. Establishment and validation of a nomogram for predicting overall survival of upper-tract urothelial carcinoma with bone metastasis: a population-based study. BMC Urol 24, 100 (2024). https://0-doi-org.brum.beds.ac.uk/10.1186/s12894-024-01488-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://0-doi-org.brum.beds.ac.uk/10.1186/s12894-024-01488-7

Keywords

BMC Urology

ISSN: 1471-2490

Contact us