Nomogram for predicting overall survival of patients with bladder cancer: A population-based study

Development of a predictive nomogram for postembolization syndrome after transcatheter arterial chemoembolization of hepatocellular carcinoma

Post-embolization syndrome (PES) is a frequent complication after receiving transcatheter arterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC), but only a few studies have focused on the factors influencing PES in those patients. In this study, the impact factors of PES were explored and a nomogram was constructed to predict the occurrence of PES in HCC patients with TACE. This was a retrospective cohort study of HCC patients who underwent TACE obtained from the third affiliated Hospital of Kunming Medical University between January 1, 2020, and September 1, 2022. T‑test and Chi‑square test were used to search for factors influencing PES occurrence, and then the nomogram was further established based on multivariable logistic regression analysis. Validation of the predictive nomogram was also evaluated by calibration curve, concordance index (C-index), and receiver operating characteristic (ROC) curves. The enrolled patients (n = 258) were randomly assigned to the primary cohort (n = 180) and validation cohort (n = 78) in a 7:3 ratio. Among 180 patients in the primary cohort, 106 (58.89%) experienced PES. TACE types (P = 0.015), embolization degree (P = 0.008), and tumor number (P = 0.026) were identified as predictors by the logistic regression analysis and were used to develop the predictive nomogram. The internally validated and externally validated C-indexes were 0.713 and 0.703, respectively. The calibration curves presented good consistency between actual and predictive survival. Types of embolic agents, embolization degree, and tumor number were found to be the predictors of PES after TACE. The nomogram could reliably predict PES in HCC patients with TACE. This predictive model might be considered for clinical practice.

Assessing the prognostic impact of prostatic urethra involvement and developing a nomogram for T1 stage bladder cancer

PURPOSE

To investigate prognostic values of prostatic urethra involvement (PUI) and construct a prognostic model that estimates the probability of cancer-specific survival for T1 bladder cancer patients.

METHOD AND MATERIALS

We investigated the national Surveillance, Epidemiology, and End Results (SEER) database (2004-2015) to get patients diagnosed with T1 bladder cancer. An external validation cohort was obtained from the First Affiliated Hospital of Nanchang University. The Kaplan-Meier method with the log-rank test was applied to assess cancer-specific survival (CSS) and overall survival (OS). Moreover, the propensity score matching (PSM) and multivariable Cox proportional hazard model were performed. All patients were randomly divided into the development cohort and validation group at the ratio of 7:3. The performance of the model was internally validated by calibration curves and the concordance index (C-index).

RESULTS

The PUI group had a lower survival rate of both CSS and overall survival OS before and after PSM when compared to non-involved patients (All P < 0.05). Multivariate analysis revealed a poor prognosis in the PUI group for cancer-specific mortality (CSM) and all-cause mortality (ACM) analyses before and after PSM (All P < 0.05). Seven variables, including age, surgery, radiotherapy, tumour size, PUI, and marital status, were incorporated in the final nomogram. The C-index in the development cohort was 0.715 (0.711-0.719), while it was 0.672 (0.667-0.677) in the validation group. Calibration plots for 3- and 5-year cancer-specific survival showed good concordance in the development and validation cohorts.

CONCLUSIONS

PUI was an independent risk factor of ACM and CSM in T1 bladder cancer patients. In addition, a highly discriminative and precise nomogram that predicted the individualized probability of cancer-specific survival for patients with T1 bladder cancer was constructed.

The Impact of the Initial Clinical Presentation of Bladder Cancer on Histopathological and Morphological Tumor Characteristics

This study investigated the impact of the initial clinical presentation of bladder cancer on tumor characteristics. A cross-sectional, retrospective study was performed, and it involved 515 patients who underwent transurethral bladder cancer resection at the University Hospital Center Split between April 2019 and April 2023, excluding recurrent cases. The association between symptomatic versus asymptomatic presentation and bladder cancer characteristics was analyzed. A subgroup analysis compared tumor characteristics between patients with gross and microscopic hematuria. Multiple regression analyses revealed a significant association between symptomatic presentation and the detection of high-grade bladder cancer (OR 3.43, 95% CI 2.22-5.29, p < 0.001), concomitant CIS (OR 3.41, 95% CI 1.31-8.88, p = 0.012), T2 stage bladder cancer (OR 5.79, 95% CI 2.45-13.71, p < 0.001), a higher number of tumors (IRR 1.24, 95% CI 1.07-1.45, p = 0.005), and larger tumor size (B 1.68, 95% CI 1.19-2.18, p < 0.001). In the subgroup analysis, gross hematuria was associated with the detection of high-grade bladder cancer (OR 2.07, 95% CI 1.12-3.84, p = 0.020), T2 stage bladder cancer (OR 6.03, 95% CI 1.42-25.49, p = 0.015), and larger tumor size (B 1.8, 95% CI 0.99-2.6, p < 0.001). The identified associations between symptomatic presentation and unfavorable bladder cancer characteristics, likely attributed to early detection in asymptomatic cases, underscore the importance of additional research in the development of bladder cancer screening strategies.

Surveillance of prognostic risk factors in patients with SCCB using artificial intelligence: a retrospective study

Small cell carcinoma of the bladder (SCCB) is a rare urological tumor. The prognosis of SCCB is abysmal. Therefore, this study aimed to construct nomograms that predict overall survival (OS) and cancer-specific survival (CSS) in SCCB patients. Information on patients diagnosed with SCCB during 2004-2018 was obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression models analyzed Independent risk factors affecting patients' OS and CSS. Nomograms predicting the OS and CSS were constructed based on the multivariate Cox regression model results. The calibration curve verified the accuracy and reliability of the nomograms, the concordance index (C-index), and the area under the curve (AUC). Decision curve analysis (DCA) assessed the potential clinical value. 975 patients were included in the training set (N = 687) and the validation set (N = 288). Multivariate COX regression models showed that age, marital status, AJCC stage, T stage, M stage, surgical approach, chemotherapy, tumor size, and lung metastasis were independent risk factors affecting the patients' OS. However, distant lymph node metastasis instead AJCC stage is the independent risk factor affecting the CSS in the patients. We successfully constructed nomograms that predict the OS and CSS for SCCB patients. The C index of the training set and the validation set of the OS were 0.747 (95% CI 0.725-0.769) and 0.765 (95% CI 0.736-0.794), respectively. The C index of the CSS were 0.749 (95% CI 0.710-0.773) and 0.786 (95% CI 0.755-0.817), respectively, indicating that the predictive models of the nomograms have excellent discriminative power. The calibration curve and the AUC also show good accuracy and discrimination of the nomograms. To sum up, We established nomograms to predict the OS and CSS of SCCB patients. The nomograms have undergone internal cross-validation and show good accuracy and reliability. The DCA shows that the nomograms have an excellent clinical value that can help doctors make clinical-assisted decision-making.

Development of a predictive model to identify patients most likely to benefit from surgery in metastatic breast cancer

Primary tumor resection for metastatic breast cancer (MBC) has demonstrated a survival advantage, however, not all patients with MBC benefit from surgery. The purpose of this study was to develop a predictive model to select patients with MBC who are most likely to benefit from surgery at the primary site. Data from patients with MBC were obtained from the Surveillance, Epidemiology and End Results (SEER) cohort and patients treated at the Yunnan Cancer Hospital. The patients from the SEER database were divided into surgery and non-surgery groups and a 1:1 propensity score matching (PSM) was used to balance baseline characteristics. We hypothesized that patients who underwent local resection of primary tumors had improved overall survival (OS) compared to those who did not undergo surgery. Based on the median OS time of the non-surgery group, patients from the surgery group were further categorized into beneficial and non-beneficial groups. Logistic regression analysis was performed to identify independent factors associated with improved survival in the surgery group and a nomogram was established using the most significant predictive factors. Finally, internal and external validation of the prognostic nomogram was also evaluated by concordance index (C-index) and using a calibration curve. A total of 7759 eligible patients with MBC were identified in the SEER cohort and 92 with MBC patients who underwent surgery at the Yunnan Cancer Hospital. Amongst the SEER cohort, 3199 (41.23%) patients received surgery of the primary tumor. After PSM, the OS between the surgery and non-surgery group was significantly different based on Kaplan-Meier survival analysis (46 vs. 31 months, P < 0.001), In the surgery group, 562 (55.20%) patients survived for longer than 31 months and were classified in the beneficial group. Significant differences were observed in patient characteristics between the beneficial and non-beneficial groups including age, grade, tumor size, liver metastasis, breast cancer subtype and marital status. These factors were used as independent predictors to create a nomogram. The internally and externally validated C-indices of the nomogram were 0.703 and 0.733, respectively, indicating strong consistency between the actual and predicted survival. A nomogram was developed and used to identify MBC patients who are most likely to benefit from primary tumor resection. This predictive model has the potential to improve clinical decision-making and should be considered routine clinical practice.

Glucose Metabolism Reprogramming in Bladder Cancer: Hexokinase 2 (HK2) as Prognostic Biomarker and Target for Bladder Cancer Therapy

Proliferating cancer cells are able to reprogram their energy metabolism, favouring glycolysis even in the presence of oxygen and fully functioning mitochondria. Research is needed to validate the glycolysis-related proteins as prognostic/predictive biomarkers in urothelial bladder carcinoma (UBC), a malignancy tagged by high recurrence rates and poor response to chemotherapy. Here, we assessed GLUT1, HK2, PFKL, PKM2, phospho-PDH, and LDHA immunoexpression in 76 UBC samples, differentiating among urothelial, fibroblast, and endothelial cells and among normoxic versus hypoxic areas. We additionally studied the functional effects of the HK2 inhibitor 2-deoxy-D-glucose (2DG) in "in vitro" and "in vivo" preclinical UBC models. We showed that the expression of the glycolysis-related proteins is associated with UBC aggressiveness and poor prognosis. HK2 remained as an independent prognostic factor for disease-free and overall survival. 2DG decreased the UBC cell's viability, proliferation, migration, and invasion; the inhibition of cell cycle progression and apoptosis occurrence was also verified. A significant reduction in tumour growth and blood vessel formation upon 2DG treatment was observed in the chick chorioallantoic membrane assay. 2DG potentiated the cisplatin-induced inhibition of cell viability in a cisplatin-resistant subline. This study highlights HK2 as a prognostic biomarker for UBC patients and demonstrates the potential benefits of using 2DG as a glycolysis inhibitor. Future studies should focus on integrating 2DG into chemotherapy design, as an attempt to overcome cisplatin resistance.

Holistic Assessment of Quality of Life Predicts Survival in Older Patients with Bladder Cancer

OBJECTIVE

To determine if clustering methods can use a holistic assessment of health-related quality-of-life after bladder cancer diagnosis to predict survival outcomes independent of clinical characteristics. In the United States, an estimated 81,180 cases of bladder cancer will be diagnosed in 2022. We aim to help address the knowledge gap concerning the impact of patient functional status on outcomes.

MATERIALS AND METHODS

This is a cross-sectional, retrospective cohort study of patients in the End Results-Medicare Health Outcomes Survey Registry. Age and 36-Item Short Form Survey (SF-36) responses were used as K-means inputs to identify homogenous clusters of older patients with bladder cancer. We analyzed the association between the identified clusters, patient and disease characteristics, and outcomes. We used Cox proportional hazard regression to compare overall survival.

RESULTS

We identified 5 homogenous clusters that exhibited differences in patient characteristics and survival. There was no significant difference in cancer stage or surgery type among the clusters. The Cox proportional hazard regression demonstrated significant associations of cluster with gender, age, education, marital status, smoking status, type of surgery, and cancer stage on overall survival. Cluster independently predicted overall survival.

CONCLUSION

Using unsupervised machine learning, we identified clusters of patients with bladder cancer who had similar mental and physical function scores. Cluster grouping suggests that patients' mental and physical function may not be based on disease or treatment. There are significant survival differences between all clusters, demonstrating that a holistic assessment of patient-reported health-related quality-of-life has the potential to predict survival and possible modifiable risk factors in older patients with bladder cancer.

Construction and validation of a prognostic nomogram in metastatic breast cancer patients of childbearing age: A study based on the SEER database and a Chinese cohort

Introduction

Cancer in patients of childbearing age continues to become increasingly common. The purpose of this study was to explore the impact of metastatic breast cancer (MBC) on overall survival (OS) and cancer-specifific survival (CSS) in patients of childbearing age and to construct prognostic nomograms to predict OS and CSS.

Methods

Data from MBC patients of childbearing age were obtained from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015, and the patients were randomly assigned into the training and validation cohorts. Univariate and multivariate Cox analyses were used to search for independent prognostic factors impacting OS and CSS, and these data were used to construct nomograms. The concordance index (C-index), area under the curve (AUC), and calibration curves were used to determine the predictive accuracy and discriminative ability of the nomograms. Additional data were obtained from patients at the Yunnan Cancer Hospital to further verify the accuracy of the nomograms.

Results

A total of 1,700 MBC patients of childbearing age were identifified from the SEER database, and an additional 92 eligible patients were enrolled at the Yunnan Cancer Hospital. Multivariate Cox analyses identifified 10 prognostic factors for OS and CSS that were used to construct the nomograms. The calibration curve for the probabilities of OS and CSS showed good agreement between nomogram prediction and clinical observations. The C-index of the nomogram for OS was 0.735 (95% CI = 0.725-0.744); the AUC at 3 years was 0.806 and 0.794 at 5 years.The nomogram predicted that the C-index of the CSS was 0.740 (95% CI = 0.730- 0.750); the AUC at 3 years was 0.811 and 0.789 at 5 years. The same results were observed in the validation cohort. Kaplan- Meier curves comparing the low-,medium-, and high-risk groups showed strong prediction results for the prognostic nomogram.

Conclusion

We identifified several independent prognostic factors and constructed nomograms to predict the OS and CSS for MBC patients of childbearing age.These prognostic models should be considered in clinical practice to individualize treatments for this group of patients.

Development and Internal Validation of a Nomogram Predicting Overall Survival Based on Log ODDS of Positive Lymph-Nodes for Post Radical Cystectomy Patients in Muscle Invasive Carcinoma of Bladder

BACKGROUND

To develop and validate a nomogram based on LODDS (Log ODDS of positive lymph-nodes) for prediction of overall survival (OS) in post radical cystectomy (RC) patients of muscle invasive bladder cancer (MIBC).

MATERIALS AND METHODS

Data was retrospectively collected from 282 cases of MIBC that underwent RC from 2011 to 2017 at our institute. Significant independent predictors were identified using Cox regression model and incorporated into a nomogram to predict 1, 2, and 4-year OS.

RESULTS

Multivariate analysis showed that Neo-Adjuvant Chemo-Therapy (NACT) (P< .001), LODDS (P< .001), T-stage (Pi = .001), CCI (Charlson Comorbidity Index) (P = .034) and grade (P = .003) were independent predictors of OS. The C-index of nomogram (0.740) was higher than that of the American Joint Committee on Cancer (AJCC) staging system (0.614). The bias-corrected calibration plots showed that the predicted risks were in excellent accordance with the actual risks. The results of NRI, IDI, and DCA exhibited superior predictive capability and higher clinical use of the nomogram.

CONCLUSION

A simple, easy to use nomogram to predict OS in cases of MIBC has been constructed. To best of our knowledge, LODDS has been incorporated for the first time. It has superior predictive ability and higher clinical use than AJCC system. It would help the clinicians for better patient counselling, planning follow-up strategies and designing a clinical trial for newer adjuvant therapy (eg immunotherapy) in post radical cystectomy patients of MIBC.

Mortality prediction models after radical cystectomy for bladder tumour: A systematic review and critical appraisal

INTRODUCTION

To identify risk-predictive models for bladder-specific cancer mortality in patients undergoing radical cystectomy and assess their clinical utility and risk of bias.

METHODS

Systematic review (CRD42021224626:PROSPERO) in Medline and EMBASE (from their creation until 31/10/2021) was screened to include articles focused on the development and internal validation of a predictive model of specific cancer mortality in patients undergoing radical cystectomy. CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS) and Prediction model Risk Of Bias ASsessment Tool (PROBAST) were applied.

RESULTS

Nineteen observational studies were included. The main predictors were sociodemographic variables, such as age (18 studies, 94.7%) and sex (17, 89.5% studies), tumour characteristics (TNM stage (18 studies, 94.7%), histological subtype/grade (15 studies, 78.9%), lymphovascular invasion (10 studies, 52.6%) and treatment with chemotherapy (13 studies, 68.4%). C-index values were presented in 14 studies. The overall risk of bias assessed using PROBAST led to 100% of studies being classified as high risk (the analysis domain was rated to be at high risk of bias in all the studies), and 52.6% showed low applicability. Only 5 studies (26.3%) included an external validation and 2 (10.5%) included a prospective study design.

CONCLUSIONS

Using clinical predictors to assess the risk of bladder-specific cancer mortality is a feasibility alternative. However, the studies showed a high risk of bias and their applicability is uncertain. Studies should improve the conducting and reporting, and subsequent external validation studies should be developed.

A Prognostic Nomogram Based on Log Odds of Positive Lymph Nodes to Predict Overall Survival for Non-Metastatic Bladder Cancer Patients after Radical Cystectomy

(1) Purpose: The purpose of this study was to evaluate the prognostic capacity of the pathological N status (pN), lymph node ratio (LNR), and the log odds of positive lymph nodes (LODDS), and to build a prognostic nomogram to predict overall survival (OS) for bladder cancer patients treated by radical cystectomy. (2) Methods: The clinical and pathological characteristics of 10,938 patients with bladder cancer were identified from the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2017. The predictive capacity was assessed by univariate and multivariate Cox regression analyses, the area under the receiver operating characteristic curve (AUC), and C-index. Calibration curves, decision curve analysis (DCA), and risk-grouping were utilized to evaluate the predictive accuracy and discriminative ability of the nomogram. (3) Results: LODDS was an independent risk factor for bladder cancer (all p < 0.001) and demonstrated the highest values of C-index and AUC. The values of AUCs in the training cohort were 0.747, 0.743, and 0.735 for predicting 1-, 3-, and 5-year OS, respectively. Calibration curves and DCA curves suggested the excellent clinical application value of our nomogram. (4) Conclusions: LODDS is a better predictive indicator for bladder cancer patients compared to pN and LNR. The LODDS-incorporated nomogram has excellent accuracy and promising clinical application value for non-metastatic bladder cancer after radical cystectomy.

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.

Beta-blocker use and urothelial bladder cancer survival: a Swedish register-based cohort study

BACKGROUND

Recent observational studies linked β-adrenergic receptor blocker use with improved survival in patients with several cancer types, but there is no information on the potential effects of β-blockers in patients with bladder cancer. Literature from pre-clinical studies is also limited, but urothelial cancer can exhibit significant overexpression of β-adrenergic receptors relative to normal urothelial tissue, suggesting that urothelial cancer may benefit from β-blockade therapy. We thus aimed to explore the possible association between β-blocker use and bladder cancer-specific mortality (BCSM) among patients with urothelial bladder cancer.

MATERIAL AND METHODS

Patients diagnosed during 2006-2014 and identified from the Swedish Cancer Register (n = 16,669) were followed until 31 December 2015. Cox regression was used to evaluate the association of β-blockers dispensed within 90 days prior to cancer diagnosis with BCSM (primary outcome) and all-cause mortality, while controlling for socio-demographic factors, tumor characteristics, comorbidity, other medications and surgical procedures. Hazard ratios (HR) with 95% confidence intervals (CI) were reported.

RESULTS

Overall, β-blocker use was associated with lower BCSM [HR 0.88 (95%CI 0.81-0.96)]. Especially use of nonselective β-blockers showed a clear inverse association in comparison with both nonuse [0.66 (0.50-0.86)] and use of other antihypertensive medications [0.72 (0.54-0.95)]. The inverse association was most pronounced among patients with locally advanced/metastatic disease: [0.35 (0.18-0.68)]. A lower-magnitude inverse association was observed for selective β-blocker use [0.91 (0.83-0.99)]. Largely similar inverse associations were observed for hydrophilic [0.82 (0.70-0.95)] and lipophilic [0.91 (0.83-1.00)] β-blocker use.

CONCLUSION

β-blocker use, particularly of the nonselective type, was associated with lower BCSM, especially in patients with locally advanced/metastatic urothelial bladder cancer.

Development of a prognostic nomogram for metastatic pancreatic ductal adenocarcinoma integrating marital status

Previous studies have shown that marital status can affect the overall survival (OS) of cancer patients yet its role in metastatic pancreatic ductal adenocarcinoma (mPDAC) remains unclear. This study aimed to explore the impact of marital status on the OS of mPDAC patients and to construct a prognostic nomogram to predict OS outcomes. Data from patients diagnosed with mPDAC were obtained from the Surveillance, Epidemiology, and End Results database between 1973 and 2015. The patients were randomized into primary and validation cohorts. Kaplan-Meier survival analysis was performed to compare differences in survival depending on marital status. Univariate and multivariate analyses were conducted to identify independent prognostic factors and a nomogram was established based using Cox regression analyses. Validation of the prognostic nomogram was evaluated with a calibration curve and concordance index (C-index). Our data showed significant differences in the OS of mPDAC patients with different marital status by Kaplan-Meier analysis (P < 0.05). Univariate and multivariate analyses confirmed that marital status was an independent OS-related factor in mPDAC patients. Based on the multivariate models of the primary cohort, a nomogram was developed that combined marital status, age, grade, tumor size, surgery of primary site, surgery of lymph node and metastatic. The nomogram showed that marital status had a moderate influence on predicting the OS of mPDAC patients. Moreover, the internally and externally validated C-indexes were 0.633 and 0.619, respectively. A calibration curve confirmed favorable consistency between the observed and predicted outcomes. Marital status was identified as an independent prognostic factor for OS of mPDAC patients and is a reliable and valid parameter to predict the survival of patients with mPDAC. This prognostic model has value and may be integrated as a tool to inform decision-making in the clinic.

Construction and validation of prognostic nomograms for elderly patients with metastatic non-small cell lung cancer

BACKGROUND

Metastatic non-small cell lung cancer (NSCLC) is mostly seen in older patients and is associated with poor prognosis. There is no reliable method to predict the prognosis of elderly patients (≥60 years old) with metastatic NSCLC. The aim of our study was to develop and validate nomograms which accurately predict survival in this group of patients.

METHODS

NSCLC patients diagnosed between 2010 and 2015 were all identified from the Surveillance, Epidemiology, and End Results (SEER) database. Nomograms were constructed by significant clinicopathological variables (p < 0.05) selected in multivariate Cox analysis regression.

RESULTS

A total of 9584 patients met the inclusion criteria and were randomly allocated in the training (n = 6712) and validation (n = 2872) cohorts. In training cohort, independent prognostic factors included age, gender, race, grade, tumor site, pathology, T stage, N stage, radiotherapy, surgery, chemotherapy, and metastatic site (p < 0.05) for lung cancer-specific survival (LCSS) and overall survival (OS) were identified by the Cox regression. Nomograms for predicting 1-, 2-, and 3-years LCSS and OS were established and showed excellent predictive performance with a higher C-index than that of the 7th TNM staging system (LCSS: training cohort: 0.712 vs. 0.534; p < 0.001; validation cohort: 0.707 vs. 0.528; p < 0.001; OS: training cohort: 0.713 vs. 0.531; p < 0.001; validation cohort: 0.710 vs. 0.528; p < 0.001). The calibration plots showed good consistency from the predicted to actual survival probabilities both in training cohort and validation cohort. Moreover, the decision curve analysis (DCA) achieved better net clinical benefit compared with TNM staging models.

CONCLUSIONS

We established and validated novel nomograms for predicting LCSS and OS in elderly patients with metastatic NSCLC with desirable discrimination and calibration ability. These nomograms could provide personalized risk assessment for these patients and assist in clinical decision.

Development and Validation of a Prognostic Nomogram for Predicting Overall Survival for T1 High-Grade Patients After Radical Cystectomy: A Study Based on SEER

Objective

To construct a prognostic model that estimates the probability of overall survival for T1 high-grade bladder cancer patients after radical cystectomy.

Patients and Methods

We enrolled 801 patients diagnosed with T1 high grade and received radical cystectomy from the Surveillance, Epidemiology, and End Results (SEER) database (2004–2015). All patients were randomly divided into the development group (n = 561) and validation group (n = 240) with the ratio of 7:3. Cox proportional hazards regression analyses were used to filter variables and the Kaplan–Meier method to evaluate survival outcomes. The results of sensitivity analysis determined the variables in the final model. The performance of the model was internally validated by calibration curves, the receiver operating characteristic (ROC) curves, and the concordance index (C-index).

Results

The mean survival months were 56.086 in the development group and 58.21 in the validation group. Six variables including age, marital status, tumour size, tumour sites, region nodes examined, and N stage were incorporated in the final nomogram. The accuracy of the nomogram for prediction of overall survival was estimated by C-index (0.732; 0.712–0.752) and AUC (0.771 for 3-year; 0.766 for 5-year) in the development group. In the validation group, the C-index of the nomogram was 0.752 (0.723–0.781), and AUC was 0.761 for 3-year as well as 0.793 for 5-year. These results all showed better performance than the AJCC stage. Calibration plots for 3- and 5-year overall survival presented good concordance in both the development and validation group.

Conclusion

We have established a prognostic nomogram that provides a more accurate and relevant individualized probability of overall survival for patients with T1HG bladder transitional cell carcinoma after radical cystectomy. It can contribute to improving patient counselling and treatment selection.

Clinical Outcomes and Prognosis Analysis of Younger Bladder Cancer Patients

Background: Generally, little is known about prognostic factors in bladder cancer patients under 40 years of age. We therefore performed a retrospective study to identify prognostic factors in these younger bladder cancer patients. Methods: We collected clinicopathological data on bladder cancer patients ≤40 years old diagnosed between 1975 and 2018 from the Surveillance, Epidemiology, and End Results (SEER) database. Survival curves were generated using the Kaplan–Meier method, and the differences between groups were analyzed using the log-rank test. Univariate and multivariate Cox hazards regression analyses were performed to define hazard ratios (HRs) for cancer-specific survival (CSS). Results: There were statistical differences in race, histological type, cancer stage, tumor size, and surgery treatment groups between overall survival and CSS. Only tumor size and cancer stage were significant independent prognostic risk factors in younger bladder cancer patients for the prediction of CSS. Conclusion: Tumors greater than 30 mm in size and a more advanced stage of bladder cancer were indicative of a poor prognosis in bladder cancer patients ≤40 years old, and long-term follow-up is suggested.

Study Progress of Noninvasive Imaging and Radiomics for Decoding the Phenotypes and Recurrence Risk of Bladder Cancer

Urinary bladder cancer (BCa) is a highly prevalent disease among aged males. Precise diagnosis of tumor phenotypes and recurrence risk is of vital importance in the clinical management of BCa. Although imaging modalities such as CT and multiparametric MRI have played an essential role in the noninvasive diagnosis and prognosis of BCa, radiomics has also shown great potential in the precise diagnosis of BCa and preoperative prediction of the recurrence risk. Radiomics-empowered image interpretation can amplify the differences in tumor heterogeneity between different phenotypes, i.e., high-grade vs. low-grade, early-stage vs. advanced-stage, and nonmuscle-invasive vs. muscle-invasive. With a multimodal radiomics strategy, the recurrence risk of BCa can be preoperatively predicted, providing critical information for the clinical decision making. We thus reviewed the rapid progress in the field of medical imaging empowered by the radiomics for decoding the phenotype and recurrence risk of BCa during the past 20 years, summarizing the entire pipeline of the radiomics strategy for the definition of BCa phenotype and recurrence risk including region of interest definition, radiomics feature extraction, tumor phenotype prediction and recurrence risk stratification. We particularly focus on current pitfalls, challenges and opportunities to promote massive clinical applications of radiomics pipeline in the near future.

Marital Status and Prognostic Nomogram for Bladder Cancer With Distant Metastasis: A SEER-Based Study

Background

To investigate the impact of marital status on overall survival (OS) and create a prognostic nomogram predicting OS in distant-metastatic bladder cancer (DMBC) patients.

Methods

The Surveillance, Epidemiology, and End Results (SEER) database was explored to recruit DMBC patients from 2010 to 2015. Kaplan–Meier survival analysis was used to compare survival differences among different marital status. Univariate and multivariate analyses were used to screen for prognostic factors and then constructed the nomogram based on Cox proportional hazard regression models. Calibration plot diagrams and concordance index (C-index) were used to verify the prognostic nomogram.

Results

Kaplan–Meier curves suggested the significant differences of OS among different marital status existed in total (P < 0.001), female (P = 0.011) and male (P = 0.001) DMBC patients, respectively. Multivariate analysis indicated marital status was an independent prognostic factor for OS of DMBC patients. Nomogram showed the contribution of marital status to predicting OS was small. Other independent prognostic factors included age, grade, histology type, surgery of primary site, chemotherapy, and metastasis pattern. By combining seven factors, we constructed a prognostic nomogram for DMBC patients. The C-index of this nomogram for OS prediction was 0.722 (95% CI 0.712–0.732). The calibration curves showed perfect consistency between observed and predictive survival.

Conclusions

Marital status was an independent prognostic factor for OS of DMBC patients, but its contribution to predicting OS was small. The prognostic nomogram will provide an individualized evaluation of OS and guidance for suitable treatments in DMBC patients.