The prognostic effect of metastasis patterns on overall survival in patients with distant metastatic bladder cancer: a SEER population-based analysis

Development and validation of a nomogram for predicting suicide risk and prognostic factors in bladder cancer patients following diagnosis: A population-based retrospective study

This study sought to identify independent risk factors associated with suicide following a diagnosis of bladder cancer and to develop a predictive model with the potential to contribute to suicide rate reduction. Harnessing data from the Surveillance, Epidemiology, and End Results (SEER) database, we identified bladder cancer patients diagnosed between 2004 and 2015, randomly assigning them to training and validation cohorts. The Cox proportional hazard model was employed to identify relevant predictors, leading to the construction of prediction nomogram models. Validation of prognostic nomograms involved assessing the consistency index (C-index), receiver operating characteristic (ROC) curve, and calibration curve. A total of 109,961 eligible bladder cancer patients were enrolled, randomly divided into training and validation sets. Multivariate Cox regression analysis revealed that sex, marital status, tumor local status (T Stage), and lymph node metastatic conditions (N Stage) were independent predictors for suicide in bladder cancer patients. Evaluation of the nomogram's accuracy through the C-index and ROC curve demonstrated acceptable performance in both training and validation sets. Moreover, the calibration plot indicated moderate accuracy of the nomogram in both datasets. Overall, this study successfully identified risk factors for suicide among bladder cancer patients and developed a nomogram, offering individualized diagnosis, intervention, and risk assessment to mitigate the risk of suicide in this patient population.

Do Histology and Primary Tumor Location Influence Metastatic Patterns in Bladder Cancer?

Metastasis is the leading cause of death in patients with bladder cancer. This study utilized a statistical analysis of patient data from the Surveillance, Epidemiology, and End Results database to examine the influence of histological type and primary site on the metastatic behavior of bladder cancer. Significantly different metastatic patterns were observed among bladder cancer patients depending on their histological type. Patients with squamous cell carcinoma showed a significantly (p < 0.001) lower bone metastasis rate (27.2%) than patients with urothelial carcinoma (UC) (38.3%). Patients with neuroendocrine carcinoma showed a significantly (p < 0.001) higher liver metastasis rate (52.1%) and a significantly (p = 0.001) lower lung metastasis rate (25.7%) than patients with UC (22.6% and 33.5%, respectively). UC patients also demonstrated differences in metastatic behavior according to histological subtype. The sarcomatoid subtype showed a significantly (p < 0.001) higher lung metastasis rate (51.6%) and a significantly lower (p = 0.002) lymph node metastasis rate (22.6%) than the micropapillary subtype (12.1% and 54.1%, respectively). Significant differences in metastatic behavior were also observed among patients with conventional UCs originating from the bladder, ureter, and renal pelvis. This study highlights the impact of histological characteristics and primary site on metastatic tendencies in bladder cancer, highlighting the importance of tailoring treatment and surveillance strategies.

Biological differences underlying sex and gender disparities in bladder cancer: current synopsis and future directions

Sex and gender disparities in bladder cancer have long been a subject of interest to the cancer research community, wherein men have a 4 times higher incidence rate than women, and female patients often present with higher-grade disease and experience worse outcomes. Despite the known differences in disease incidence and clinical outcomes between male and female bladder cancer patients, clinical management remains the same. In this review, we critically analyze studies that report on the biological differences between men and women and evaluate how these differences contribute to sex and gender disparities in bladder cancer. Distinct characteristics of the male and female immune systems, differences in circulating hormone levels and hormone receptor expression, and different genetic and epigenetic alterations are major biological factors that all likely contribute to disparate incidence rates and outcomes for male and female bladder cancer patients. Future preclinical and clinical studies in this area should employ experimental approaches that account for and consider sex and gender disparities in bladder cancer, thereby facilitating the development of precision medicine for the effective treatment of bladder cancer in all patients.

Development and validation a model for predicting overall survival of bladder cancer with lung metastasis: a population-based study

BACKGROUND

Although the number of patients with bladder cancer and lung metastasis is increasing there is no accurate model for predicting survival in these patients.

METHODS

Patients enrolled in the Surveillance, Epidemiology, and End Results database between 2010 and 2015 were selected for the study. Univariate and multivariate Cox regression were used to determine independent prognostic factors, followed by development of a nomogram based on the multivariate Cox regression models. The consistency index, receiver operating characteristic curve, and calibration curve were used to validate the prognostic nomogram.

RESULTS

506 eligible bladder cancer patients with lung metastasis were enrolled in the study and then divided randomly into training and validation sets (n = 356 vs. n = 150). Multivariate Cox regression analysis indicated that age at diagnosis, primary site, histological type, surgery of the primary site, chemotherapy, bone metastasis, and liver metastasis were prognostic factors for overall survival (OS) in patients with lung metastasis in the training set. The C-index of the nomogram OS was 0.699 and 0.747 in the training and validation sets, respectively. ROC curve estimation of the nomogram in the training and validation sets showed acceptable accuracy for classifying 1-year survival, with an area under the curve (AUC) of 0.766 and 0.717, respectively. More importantly, the calibration plot showed the nomogram had favorable predictive accuracy in both the training and validation sets.

CONCLUSIONS

The prognostic nomogram created in our study provides an individualized diagnosis, remedy, and risk evaluation for survival in patients with bladder cancer and lung metastasis. The nomogram would therefore enable clinicians to make more precise treatment decisions for patients with bladder cancer and lung metastasis.

Web-Based Nomograms for Overall Survival and Cancer-Specific Survival of Bladder Cancer Patients with Bone Metastasis: A Retrospective Cohort Study from SEER Database

BACKGROUND

Our study aimed to explore the prognostic factors of bladder cancer with bone metastasis (BCBM) and develop prediction models to predict the overall survival (OS) and cancer-specific survival (CSS) of BCBM patients.

METHODS

A total of 1438 patients with BCBM were obtained from the SEER database. Patients from 2010 to 2016 were randomly divided into training and validation datasets (7:3), while patients from 2017 were divided for external testing. Nomograms were established using prognostic factors identified through Cox regression analyses and validated internally and externally. The concordance index (C-index), calibration plots, and time-dependent receiver operating characteristic (ROC) curves were used to evaluate the discrimination and calibration of nomogram models, while decision curve analyses (DCA) and Kaplan-Meier (KM) curves were used to estimate the clinical applicability.

RESULTS

Marital status, tumor metastasis (brain, liver, and lung), primary site surgery, and chemotherapy were indicated as independent prognostic factors for OS and CSS. Calibration plots and the overall C-index showed a novel agreement between the observed and predicted outcomes. Nomograms revealed significant advantages in OS and CSS predictions. AUCs for internal and external validation were listed as follows: for OS, 3-month AUCs were 0.853 and 0.849; 6-month AUCs were 0.873 and 0.832; 12-month AUCs were 0.825 and 0.805; for CSS, 3-month AUCs were 0.849 and 0.847; 6-month AUCs were 0.870 and 0.824; 12-month AUCs were 0.815 and 0.797, respectively. DCA curves demonstrated good clinical benefit, and KM curves showed distinct stratification performance.

CONCLUSION

The nomograms as web-based tools were proved to be accurate, efficient, and clinically beneficial, which might help in patient management and clinical decision-making for BCBM patients.

Predictive nomograms for early death in metastatic bladder cancer

Background

Metastatic bladder cancer (MBC) is an incurable malignancy, which is prone to early death. We aimed to establish models to evaluating the risk of early death in patients with metastatic bladder cancer.

Methods

The data of 1,264 patients with MBC registered from 2010 to 2015 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. We utilized X-tile software to determine the optimal cut-off points of age and tumor size in diagnosis. Univariate and multivariate logistic regression analyses were used to identify significant independent risk factors for total early death and cancer-specific early death, then we construct two practical nomograms. In order to validate our prediction models, we performed calibration plots, receiver operating characteristics (ROCs) curves, decision curve analysis (DCA) and clinical impact curve (CIC).

Result

A total of 1,216 patients with MBC were included in this study. 463 patients died prematurely (≤3 months), and among them 424 patients died of cancer-specific early death. The nomogram of total premature death was created by surgery, chemotherapy, tumor size, histological type, liver metastases, and nomogram of cancer-specific early death was based on surgery, race, tumor size, histological type, chemotherapy, and metastases (liver, brain). Through the verify of calibration plots, receiver operating characteristics (ROCs) curves, decision curve analysis (DCA) and clinical impact curve (CIC), we concluded that nomogram were a valid tool with excellent clinical utility to help clinicians predict premature death in MBC patients.

Conclusions

The nomograms derived from the analysis of patients with MBC, which can provide refined prediction of premature death and furnish clinicians with useful ideas for patient-specific treatment options and follow-up scheduling.

Constructing and validating nomograms to predict risk and prognostic factors of distant metastasis in urothelial bladder cancer patients: a population-based retrospective study

BACKGROUND

Urothelial carcinoma is the most common type of bladder cancer worldwide and it has a poor prognosis for patients with distant metastasis. Nomograms are frequently used in clinical research, but no research has evaluated the diagnostic and prognostic factors of distant metastasis in urothelial bladder cancer (UBC).

METHODS

The Surveillance, Epidemiology, and End Results database was used to analyze all patients diagnosed with UBC between 2000 and 2017. Lasso regression was used to identify the potential risk predictive factors for distant metastasis in UBC. Univariate and multivariate Cox proportional hazard regression analyses were performed to determine independent prognostic factors for distant metastasis urothelial bladder cancer (DMUBC). Subsequently, two nomograms were constructed based on the above models. The receiver operating characteristic (ROC), and calibration curves were performed to evaluate the two nomograms.

RESULTS

The study included 73,264 patients with UBC, with 2,129 (2.9%) having distant metastasis at the time of diagnosis. In the diagnostic model, tumor size, histologic type, and stage N and T were all important risk predictive factors for distant metastasis of UBC. In the prognostic model, age, tumor size, surgery, and chemotherapy were independent factors affecting the prognosis of DMUBC. DCA, ROC, calibration, and Kaplan-Meier (K-M) survival curves reveal that the two nomograms can effectively predict the diagnosis and prognosis of DMUBC.

CONCLUSION

The developed nomograms are practical methods for predicting the occurrence risk and prognosis of distant metastasis urothelial bladder cancer patients, which may benefit the clinical decision-making process.

Effects of Different Organ Metastases on the Prognosis of Stage IV Urothelial Carcinoma of the Bladder

Objective

To assess the prognosis of stage IV metastatic urinary bladder urothelial carcinoma (UBUC) at initial diagnosis and determine prognostic factors based on distant organ metastasis.

Methods

A retrospective cohort analysis of UBUC was conducted based on the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression analyses were used to determine the variables associated with overall survival (OS). Kaplan–Meier curves were used to compare survival curves among different groups.

Results

A total of 3103 patients with stage IV UBUC were selected for analysis. The number of distant organ metastatic sites independently predicted the OS. The OS was not different in other metastatic sites when bone metastasis was used as a reference (P > 0.05). However, the OS was shorter for a single metastatic site (P < 0.001) and multiple metastatic sites when metastasis was not used as a reference (P < 0.001). Multivariable Cox regression analysis indicated that low survivorship was independently associated with no surgery for the entire cohort and patients with only one metastatic organ. Sex (P = 0.019) and grade (P = 0.046) were the independent risk factors for patients with only one metastatic organ.

Conclusions

These results show that the prognosis of stage IV metastatic UBUC is not different between any single metastatic organ. The prognosis of stage IV metastatic UBUC depends on the number of distant organ metastasis. This study determined some predictors of survival and thus may help therapists to choose appropriate treatment strategies for metastatic UBUC.

Prognostic Significance of Organ-Specific Metastases in Patients with Metastatic Upper Tract Urothelial Carcinoma

Background: Existing data on metastatic upper tract urothelial carcinoma (mUTUC) are limited. In this study, we investigated the prognostic value of site-specific metastases in patients with mUTUC and its association with survival outcomes. Methods: We retrospectively collected data from the Surveillance, Epidemiology and End Results (SEER) database between 2004 and 2016. Kaplan−Meier analysis with a log-rank test was used for survival comparisons. Multivariate Cox regression was employed to predict overall survival (OS) and cancer-specific survival (CSS). Results: 633 patients were selected in this study cohort. The median follow-up was 6 months (IQR 2−13) and a total of 584 (92.3%) deaths were recorded. Within the population presenting with a single metastatic organ site, the most common metastatic sites were distant lymph nodes, accounting for 36%, followed by lung, bone and liver metastases, accounting for 26%, 22.8% and 16.2%, respectively. In patients with a single metastatic organ site, the Kaplan−Meier curves showed significantly worse OS for patients with liver metastases vs. patients presenting with metastases in a distant lymph node (p < 0.001), bone (p = 0.023) or lung (p = 0.026). When analyzing CSS, statistically significant differences were detectable only between patients presenting with liver metastases vs. distant lymph node metastases (p < 0.001). Multivariate analyses showed that the presence of liver (OS: HR = 1.732, 95% CI = 1.234−2.430, p < 0.001; CSS: HR = 1.531, 95% CI = 1.062−2.207, p = 0.022) or multiple metastatic organ sites (OS: HR = 1.425, 95% CI = 1.159−1.753, p < 0.001; CSS: HR = 1.417, 95% CI = 1.141−1.760, p = 0.002) was an independent predictor of poor survival. Additionally, survival benefits were found in patients undergoing radical nephroureterectomy (RNU) (OS: HR = 0.675, 95% CI = 0.514−0.886, p = 0.005; CSS: HR = 0.671, 95% CI = 0.505−0.891, p = 0.006) and chemotherapy (CHT) (OS: HR = 0.405, 95% CI = 0.313−0.523, p < 0.001; CSS: HR = 0.435, 95% CI = 0.333−0.570, p < 0.001). Conclusions: A distant lymph node was the most common site of single-organ metastases for mUTUC. Patients with liver metastases and patients with multiple organ metastases exhibited worse survival outcomes. Lastly, CHT administration and RNU were revealed to be predictors of better survival outcomes in the mUTUC cohort.

Competitive Risk Model for Specific Mortality Prediction in Patients with Bladder Cancer: A Population-Based Cohort Study with Machine Learning

Background

Noncancer death accounts for a high proportion of all patients with bladder cancer, while these patients are often excluded from the survival analysis, which increases the selection bias of the study subjects in the prediction model.

Methods

Clinicopathological information of bladder cancer patients was retrieved from the Surveillance, Epidemiology, and End Results (SEER) database, and the patients were categorized at random into the training and validation cohorts. The random forest method was used to calculate the importance of clinical variables in the training cohort. Multivariate and univariate analyses were undertaken to assess the risk indicators, and the prediction nomogram based on the competitive risk model was constructed. The model's performance was evaluated utilizing the calibration curve, consistency index (C index), and the area under the receiver operator characteristic curve (AUC).

Results

In total, we enrolled 39285 bladder cancer patients in the study (27500 patients were allotted to the training cohort, whereas 11785 were allotted to the validation cohort). A competitive risk model was constructed to predict bladder cancer-specific mortality. The overall C index of patients in the training cohort was 0.876, and the AUC values were 0.891, 0.871, and 0.853, correspondingly, for 1-, 3-, and 5-year cancer-specific mortality. On the other hand, the overall C index of patients in the validation cohort was 0.877, and the AUC values were 0.894, 0.870, and 0.847 for 1-, 3-, and 5-year correspondingly, suggesting a remarkable predictive performance of the model.

Conclusions

The competitive risk model proved to be of great accuracy and reliability and could help clinical decision-makers improve their management and approaches for managing bladder cancer patients.

Distant metastasis without regional progression in non-muscle invasive bladder cancer: case report and pooled analysis of literature

Background

Non-muscle invasive bladder cancer (NMIBC) represents the majority of bladder neoplasms. It is unusual for NMIBC metastasizing distantly without regional progression, namely metastatic NMIBC (mNMIBC), which is still poorly understood and easily omitted based on current management policies. So far, description of mNMIBC is limited to a few case reports.

Methods

We reported a 70-year-old man with NMIBC who suffered from cervical metastasis without pelvic recurrence at 41 months after initial diagnosis. Then we performed a collective analysis of this case together with published mNMIBC cases searched from PubMed, Embase, and Web of Science, aiming to illustrate baseline clinicopathologic parameters, metastatic patterns, and treatment outcomes of these patients and analyze associated influencing factors.

Results

After scrupulous review, 45 cases previous reported and the one from our center were incorporated into the aggregated cohort of mNMIBC, including 34 males and 12 females. Primary tumors from 46.7% of patients were high-grade (HG) or grade 3 (G3) and 65.1% had T1 lesions. Aberrant biomarker expression was found in tumors of some cases. Most (40/46) metastases of mNMIBC occurred at a single site, mainly in lung, bone and lymph nodes. Apart from three cases of de novo mNMIBC, the mean metastasis-free survival (MFS) interval of metachronous mNMIBC was 42.5 months, which was obviously longer than conventional metastatic bladder cancer. Shortened MFS interval was associated with old age, T1 or HG/G3 primary tumors, and non-lung metastases. Systemic chemotherapy and metastasectomy or radiotherapy for oligometastatic lesion were main therapeutic approaches of mNMIBC, and immunotherapy was adopted for the case from our center. Lung and bone metastases correlated with relatively favorable and unfavorable survival outcomes, respectively. Compared with monotherapy, chemotherapy, or immunotherapy combined with local cytoreduction got more favorable outcomes.

Conclusion

Although rare, mNMIBC occurs more in tumors with high-risk features. Usually, mNMIBC metastasizes later than conventional metastatic bladder cancer and manifests as solitary lesion. Outcomes of mNMIBC would be influenced by metastatic site and post-metastatic treatment. Systemic treatment combined with local cytoreduction may render survival benefit in selected patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02664-5.

[Liver metastases-Non-colorectal, non-endocrine]

In contrast to colorectal and neuroendocrine liver metastases, liver surgery has not yet gained the same status for non-colorectal non-endocrine (NCNE) liver metastases. The main explanation is a different tumor biology but is also due to the lack of effective systemic treatment options for some tumor entities in the past. Even selected chemotherapy-naive patients with NCNE liver metastases can benefit from liver resection. Due to the sometimes dramatic improvements in systemic treatment in recent years, multimodality treatment concepts should be increasingly considered for several diseases in which modern liver surgery will become an integral part.

Prediction of Metastatic Patterns in Bladder Cancer: Spatiotemporal Progression and Development of a Novel, Web-based Platform for Clinical Utility

Background

Bladder cancer (BCa), the sixth commonest cancer in the USA, is highly lethal when metastatic. Spatial and temporal patterns of patient-specific metastatic spread are deemed random and unpredictable. Whether BCa metastatic patterns can be quantified and predicted more accurately is unknown.

Objective

To develop a web-based calculator for forecasting metastatic progression in individual BCa patients.

Design setting and participants

We used a prospectively collected longitudinal dataset of 3503 BCa patients who underwent a radical cystectomy following diagnosis and were enrolled continuously. We subdivided patients by their pathologic subgroup stages of organ confined (OC), extravesical (EV), and node positive (N+). We illustrated metastatic pathway progression using color-coded, circular, tree ring diagrams. We created a dynamical, data-visualization, web-based platform that displays temporal, spatial, and Markov modeling figures with predictive capability.

Outcome measurements and statistical analysis

Patients underwent history and physical examination, serum studies, and liver function tests. Surveillance follow-up included computed tomography scans, chest x-rays, and radiographic evaluation of the reservoir and upper tracts, with bone scans performed only if clinically indicated. Outcomes were measured by time to clinical recurrence and overall or progression-free survival.

Results and limitations

Metastases developed in 29% of patients (n = 812; median follow-up 15.3 yr), with 5-yr overall survival of 20.2%, compared with 78.6% in those without metastases (n = 1983; median follow-up 10.9 yr). The three commonest sites of spread at the time of first progression were bone (n = 214; 26.4%), pelvis (n = 194; 23.9%), and lung (n = 194; 23.9%). The order and frequency of these sites vary when divided by pathologic subgroup stages of OC (lung [n = 65; 25.1%], urethra [n = 45; 17.4%], and bone [n = 29; 11.2%]), EV (pelvis [n = 63; 33.0%], bone [n = 45; 23.6%], and lung [n = 29; 15.2%]), and N+ (bone [n = 111; 30.7%], retroperitoneum [n = 70; 19.3%], and pelvis [n = 60; 16.6%]). Markov chain modeling indicated a higher probability of spread from bladder to bone (15.5%), pelvis (14.7%), and lung (14.2%).

Conclusions

Our web-based calculator allows real-time analyses in the clinic based on individual patient-specific demographic and cancer data elements. For contrasting subgroups, the models indicated differences in Markov transition probabilities. Spatiotemporal patterns of BCa metastasis and sites of spread indicated underlying organotropic mechanisms in the prediction of response. This recognition opens the possibility of organ site-specific therapeutic targeting in the oligometastatic BCa setting. In the precision medicine era, visualization of complex, time-resolved clinical data will enhance management of postoperative metastatic BCa patients.

Patient summary

We developed a web-based calculator to forecast metastatic progression for individual bladder cancer (BCa) patients, based on the clinical and demographic information obtained at diagnosis. This can help in predicting disease status and survival, and improving management in postoperative metastatic BCa patients.

Take  Home Message

Future pathways of metastatic progression for individual bladder cancer patients can be determined based on currently available clinical and demographic information obtained at diagnosis. In focused subgroups of patients, these metastatic spread patterns can also portend disease status and survival.