Clinical Outcomes and Prognosis Analysis of Younger Bladder Cancer Patients

Abudurexiti, Mierxiati; Ma, Jie; Li, Yao; Hu, Chuanyi; Cai, Zhixiang; Wang, Zhong; Jiang, Ning

doi:10.3390/curroncol29020052

Cited by 4 publications

(3 citation statements)

References 17 publications

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“…In light of these results, we caution against the excessive use of radiotherapy in UCB patients. Furthermore, our nomogram underscored the detrimental prognosis linked to larger tumor sizes in UCB cases, a nding echoed in various studies (33).…”

Section: Discussionsupporting

confidence: 69%

Development and External Validation of a Nomogram to Predict Prognosis of Patients With Urothelial Carcinoma of Bladder

Wei,

Chen

et al. 2024

Preprint

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Background This research aimed to create and validate nomogram predicting overall survival (OS) for urothelial carcinoma of the bladder (UCB) patients. Methods We sourced 15,606 UCB patients diagnosed between 2004 and 2015 from the Surveillance, Epidemiology, and End Results database. The patients were randomized into training (70%) and internal validation (30%) cohorts. In addition, 122 patients from Minzu Hospital of Guangxi Zhuang Autonomous Region between 2012 and 2022 were selected as the external validation cohort. Utilizing univariate and multivariate Cox regression analyses, we devised nomograms forecasting 1-, 3-, and 5-year OS. Several metrics, including the consistency index (C-index), calibration plots, area under the receiver operator characteristics (ROC) curve, and decision curve analysis (DCA) were used to validate the validity and clinical utility of the model. Patients were categorized into high- and low-risk profiles, and their survival outcomes were contrasted using the Kaplan-Meier method and the log-rank test. Results Age, marriage, AJCC stage, tumor size, surgery, and chemotherapy were identified as predictors of OS. In the training cohort, internal validation cohort and external validation cohort, the nomogram for predicting OS achieved C-index values of 0.718 (95% CI: 0.712–0.724), 0.714 (95% CI: 0.704–0.724), and 0.725 (95% CI: 0.641–0.809), respectively. In all cohorts, the calibration plots revealed high consistency between actual and predicted values. The nomogram depicted by ROC and DCA showcased superior stability, predictive value, and clinical applicability for 1, 3-, and 5-year OS. The risk stratification delineated patients into low- and high-risk brackets, revealing significant prognostic distinctions (P < 0.05). Conclusions Based on the SEER database and Chinese data, we developed a reliable nomogram forecasting 1-, 3-, and 5-year OS for UCB patients. The model can identifie high-risk patients, aiding clinicians in personalised treatment and prognostic evaluations.

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Section: Discussionsupporting

confidence: 69%

Development and External Validation of a Nomogram to Predict Prognosis of Patients With Urothelial Carcinoma of Bladder

Wei,

Chen

et al. 2024

Preprint

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“…Furthermore, the nomogram also illustrated that an increase in cancer size resulted in a poorer prognosis in bladder cancer patients. Other studies have further confirmed the influence of cancer size on bladder cancer-specific prognosis [ 30 ]. Moreover, the number of cancers is also related to the prognosis of bladder cancer.…”

Section: Discussionmentioning

confidence: 74%

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

Xue

Wang

et al. 2022

Journal of Oncology

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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.

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“…The primary tumor distinguishability on PET and CT was associated with mortality in patients with BC in univariate analysis. It is known that the size of the primary tumor in BC is a prognostic factor ( 20 , 21 ). Patients with larger primary tumors might have more distinguishable tumors on PET and/or CT; therefore, their prognosis might be poorer than others.…”

Section: Discussionmentioning

confidence: 99%

The Added-value of Staging <sup>18</sup>F-FDG PET/CT in the Prediction of Overall Survival in the Patients with Bladder Cancer

Ateş,

Demirel,

Başar

et al. 2024

Mirt

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Objectives: This retrospective study aimed to evaluate the prognostic importance of 18 F-fluorodeoxyglucose ( 18 F-FDG)-positive pelvic lymph nodes (LNs) and extra-pelvic disease on staging 18 F-FDG positron emission tomography/computed tomography (PET/CT) in patients with bladder cancer. Methods: Bladder cancer patients who underwent staging 18 F-FDG PET/CT were included in the study. Histopathologic features of tumors, therapy histories, presence of distinguishable tumors on CT and PET images, sizes and maximum standardized uptake value (SUV max ) of primary tumors, total numbers, sizes, and SUV max of 18 F-FDG-positive pelvic and extra-pelvic LNs, and total numbers and SUV max of distant metastases (M1a/1b) were recorded. Patients were followed up until death or the last medical visit. Factors predicting overall survival were determined using Cox regression analysis. Results: Fifty-five patients [median age: 70 (53-84), 48 (87.3%) male, 7 (12.7%) female] with bladder cancer were included in this study. Twenty-nine (52.7%) patients had 18 F-FDG positive pelvic LNs, while 24 (43.7%) patients had 18 F-FDG positive extra-pelvic disease. Patients with 18 F-FDGpositive pelvic LNs had a higher rate of extra-pelvic disease (p=0.003). The median follow-up duration was 13.5 months. The median overall survival was 16.3 months [95% confidence interval (CI) 8.9-23.7]. The primary tumor distinguishability on PET (p=0.011) and CT (p=0.009) images, the presence of 18 F-FDG-positive pelvic LNs (p<0.001) and 18 F-FDG-positive extra-pelvic disease/distant metastases (M1a/M1b) (p<0.001), and the number of distant metastases (p=0.034) were associated with mortality. The 18 F-FDG-positive extra-pelvic disease/distant metastases [p=0.029, odds ratio: 4.15 (95% CI 1.16-14.86)] was found to be an independent predictor of mortality in patients with bladder cancer. Conclusion: The presence of 18 F-FDG-positive extra-pelvic disease in pretreatment 18 F-FDG PET/CT is an important prognostic factor in bladder cancer patients.

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Clinical Outcomes and Prognosis Analysis of Younger Bladder Cancer Patients

Cited by 4 publications

References 17 publications

Development and External Validation of a Nomogram to Predict Prognosis of Patients With Urothelial Carcinoma of Bladder

Development and External Validation of a Nomogram to Predict Prognosis of Patients With Urothelial Carcinoma of Bladder

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

The Added-value of Staging <sup>18</sup>F-FDG PET/CT in the Prediction of Overall Survival in the Patients with Bladder Cancer

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