The association between serum testosterone level and congestive heart failure in US male adults: data from National Health and Nutrition Examination Survey (NHANES) 2011-2016.

BACKGROUND: This study aimed to investigate the relationship between serum testosterone levels and the risk of congestive heart failure (CHF) in adult males. Previous research has suggested a potential link between serum testosterone and cardiovascular health, but the findings have been inconclusive. METHODS: This study was cross-sectional, and the data were obtained from the 2011-2016 cycle of the National Health and Nutrition Examination Survey (NHANES), which included a sample of 6,841 male participants. Serum testosterone levels were measured using a standardized assay, and CHF status was assessed through self-reporting. Covariates such as age, ethnicity, lifestyle factors, and health conditions were considered in the analysis. RESULTS: Among the participants, 242 individuals had a documented history of CHF. We observed a linear correlation between serum testosterone levels and CHF occurrence, with higher serum testosterone levels associated with a decreased risk of CHF (Q4 vs. Q1, OR = 0.29, 95% CI: 0.19-0.47, P < 0.001). After adjusting for confounding variables, multivariate analysis revealed that high serum testosterone levels remained significantly associated with a lower risk of CHF (OR: 0.47, 95% CI: 0.27-0.80, P = 0.01). Subgroup analysis indicated a significant association between high serum testosterone levels and reduced CHF risk in individuals over 50 years old. CONCLUSION: Our findings suggest that the serum testosterone level was positively associated with CHF in adult males. This study highlights the potential role of serum testosterone in cardiovascular health, particularly in older individuals. Further research is needed to elucidate the underlying mechanisms and explore the clinical implications of these findings.

Trends in suicide mortality among prostate cancer survivors in the United States, 1975-2019.

BACKGROUND: Suicide was an important cause of death in prostate cancer. This study intended to investigate trends in suicide mortality among prostate cancer (PCa) survivors from 1975 to 2019 in the United States. METHOD: We identified PCa survivors from the Surveillance, Epidemiology, and End Results (SEER) program from January 1975 to December 2019. Standardized mortality rate (SMR) was calculated d to assess the relative risk of suicide in PCa survivors compared with the general men population. Poisson regression model was performed to test for trend of SMRs. The cumulative mortality rate of suicide was calculated to assess the clinical burden of suicide mortality. RESULTS: 7108 (0.2%) cases were death from suicide cause, and 2,308,923(65.04%%) cases recorded as dying from non-suicidal causes. Overall, a slightly higher suicide mortality rate among PCa survivors was observed compared with general male population (SMR: 1.15, 95%CI: 1.09-1.2). The suicide mortality rate declined significantly relative to the general population by the calendar year of diagnosis, from an SMR of 1.74(95%CI: 1.17-2.51) in 1975-1979 to 0.99(0.89-1.1) in 2015-2019 (Ptrend < 0.001). PCa survivors with aged over 84 years, black and other races, registered in registrations (including Utah, New Mexico, and Hawaii) failed to observe a decrease in suicide mortality (Ptrend > 0.05). The cumulative suicide mortality during 1975-1994 was distinctly higher than in 1995-2019(P < 0.001). CONCLUSION: The trend in suicide mortality declined significantly from 1975 to 2019 among PCa survivors compared with the general male population in the United States. Notably, part of PCa survivors had no improvement in suicide mortality, and additional studies in the future were needed to explore it.

U-shaped association between sleep duration and urgency urinary incontinence in women: a cross-sectional study.

BACKGROUND: To investigate the association between sleep duration and urgency urinary incontinence (UUI) among adult women. METHODS: Cross-sectional data were retrieved from the 2005-2014 National Health and Nutrition Examination Survey. To explore the association between sleep duration and urgency urinary incontinence, multivariable logistic regression and restricted cubic spline (RCS) regression analysis was carried out. RESULTS: Among 9204 adult women, the weighted urinary incontinence prevalence was  31% for urgency urinary incontinence (UUI). The fully adjusted multivariable model revealed that participants with short (< 7 h) or long (> 9 h) sleep duration were more likely to report UUI compared to participants with normal (7-9 h) sleep duration (OR 1.20, 95% CI 1.03-1.40, p = 0.02, OR 1.40, 95% CI 1.11-1.76, p = 0.005, respectively). Subgroup analysis showed no significant interaction. Furthermore, additional analysis demonstrated a U-shaped correlation between sleep duration and incident UUI. CONCLUSION: The non-linear association exists between sleep duration and urgency urinary incontinence. Compared with insufficient or excessive sleep, normal sleep duration is related to lower prevalence of urgency urinary incontinence. Future prospective longitudinal studies should be conducted to further investigate and determine the degree of the association between sleep time and urgent urinary incontinence.

Increased Burden of Second Bladder Cancer and Rectal Cancer in Prostate Cancer Treated With Radiotherapy: Results From Surveillance, Epidemiology, and End Results.

BACKGROUND: Previous studies have confirmed the higher risk of bladder cancer (BC) and rectal cancer (RC) development among prostate cancer (PCa) patients receiving radiotherapy. In this study, we intend to explore the long-term trend in second BC and RC incidence among PCa patients undergoing radiotherapy. METHOD: We identified first primary PCa patients diagnosed between 1975 and 2014 from the Surveillance, Epidemiology, and End Results (SEER)-9 cancer registries. Standardized incidence ratios (SIRs) were calculated by calendar year of diagnosis among PCa patients receiving radiotherapy and not. P trends were evaluated using Poisson regression. 10-year cumulative incidence of BC and RC was calculated utilizing competing risk regression model. RESULT: Of PCa patients treated with radiotherapy, SIRs of BC increased from .82 (95% CI: .35- 1.61) in 1980-1984 to 1.58 (95% CI: 1.48-1.68) in 2010-2014 (Ptrend=.003). SIRs of RC increased from 1.01 (95% CI: .27-2.58) in 1980-1984 to 1.54 (95% CI: 1.31-1.81) in 2010-2014 (Ptrend=.025). No statistically significant change in both BC and RC incidence was observed. The 10-year cumulative incidence of BC increased from 1975-1984 (.04%) to 2005-2014 (.15%) among PCa treated with radiotherapy. Simultaneously, the 10-year cumulative incidence of RC was demonstrated to range from 1975-1984 (.02%) to 2005-2014 (.11%). CONCLUSION: we have observed an increasing trend in second BC and RC incidence in PCa patients receiving radiotherapy. There was no significant change in the incidence of second BC and RC in PCa without radiotherapy. These results reflect the increasing clinical burden of second malignant tumors in PCa patients undergoing radiotherapy.

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.

Trends in cause of death among patients with renal cell carcinoma in the United States: a SEER-based study.

BACKGROUND: Renal cell carcinoma (RCC) survival has improved due to recent developments in RCC treatment. Therefore, other co-morbid conditions may have a more critical role. This study aims to explore the common causes of death in patients with RCC to improve the management and survival of RCC. METHOD: We used the Surveillance, Epidemiology, and End Results (SEER) (1992-2018) database to get patients with RCC. We calculated the percentage of total deaths of six kinds of the cause of death (COD) and the cumulative incidence of death for each selected cause over survival time. The joinpoint regression was utilized to present the trend of mortality rate by COD. RESULTS: We enrolled 107,683 cases with RCC. RCC was the leading cause of death in patients with RCC [25376(48.3%)], followed by cardiovascular diseases [9023(17.2%)], other cancers [8003 (15.2%)], other non-cancer diseases [4195 (8%)], non-disease cause [4023 (7.7%)], and respiratory diseases [1934 (3.6%)]. The proportion of patients who died of RCC decreased gradually over survival time, and this value decreased from 69.71% in 1992-1996 to 38.96% in 2012-2018. The non-RCC cause mortality rate showed an increasing trend, whereas a slight decrease was observed in RCC specific mortality rate. The distribution of such conditions varied across different patient populations. CONCLUSION: RCC was still the primary COD of patients with RCC. However, non-RCC cause death was increasingly important among RCC patients in recent two decades. Cardiovascular disease and other cancers were crucial co-morbidities that required significant attention in the management of RCC patients.

Trends in the cause of death among patients with bladder cancer in the US SEER population, 1992-2018.

BACKGROUND: Bladder cancer (BC) survival has shown no significant improvement. This study investigated the trends in the common causes of death among patients with BC to improve the management and survival of BC. METHOD: The Surveillance, Epidemiology, and End Results (SEER) (1992-2018) database was utilized to get the data of BC patients. We presented the proportion of six common causes of death in BC patients. We calculated the annual incidence of death due to the six most common causes and analyzed temporal trends in mortality rates using joinpoint regression. The competitive risk model was utilized to analyze the risk factors for death of BC and other causes. RESULTS: 198037 BC patients were enrolled. BC was the most common cause of death (30.62%), followed by other cancers (22.22%), circulatory diseases (20.28%), non-disease causes (11.58%), other non-cancer diseases (8.29%), and respiratory diseases (7.01%). However, the proportion of cases dying from BC gradually decreased from 44.87% in 1992-1996 to 26.74% in 2012-2018. The proportion of deaths due to BC decreased gradually with survival time from diagnosis. Age-standardized temporal trends present an initial increase in BC-specific and other-cause mortality rates. Advanced stage and older age were the most influential risk factors for BC-specific and other-cause death, respectively. CONCLUSION: Although BC was still the leading cause of death, other causes, especially other cancers and circulatory diseases, gradually became more critical. The management of other comorbid conditions will be a crucial part of the treatment for BC patients, especially for those with prolonged survival and NMIBC tumors.

Causal role of immune cells in prostate cancer: a bidirectional Mendelian-randomization analyses.

BACKGROUND: Immune cell signatures have been implicated in cancer progression and response to treatment. However, the causal relationship between immune cell signatures and prostate cancer (PCa) is still unclear. This study aimed to investigate the potential causal associations between immune cell signatures and PCa using Mendelian randomization (MR). METHOD: This study utilized genome-wide association studies (GWAS) summary statistics for PCa and immune cell signatures from publicly available datasets. MR analyses, including IVW, MR-Egger, and weighted median methods, were performed to evaluate the causal associations between immune cell signatures and PCa. Multiple sensitivity analysis methods have been adopted to test the robustness of our results. RESULTS: After FDR correction, our findings suggested that specific immune cell signatures, such as HLA DR on CD33+ HLA DR+ CD14dim (odds ratio [OR] = 1.47, 95% confidence interval [CI] = 1.12-1.92, p = 0.006), HLA DR on CD33+ HLA DR+ CD14- (OR = 1.32, 95% CI = 1.05-1.67, p = 0.018), and HLA DR on monocyte (OR = 1.23, 95% CI = 1.03-1.47, p = 0.021), were significantly associated with PCa. PCa had no statistically significant effect on immunophenotypes. These results remained robust in sensitivity analyses, supporting the validity of the causal associations. CONCLUSIONS: This study provides evidence of a potential causal relationship between certain immune cell signatures and PCa. We observed that immune cell signatures involving HLA DR expression on specific cell types are associated with an increased risk of PCa.

Trends in suicide mortality among cancer survivors in the US, 1975-2020.

BACKGROUND: Suicide in cancer survivors is a major public health concern, but its trends and risk factors are not well understood. This study aimed to investigate the standardized mortality rate (SMR) and trends in suicide among cancer survivors in the United States. METHODS: Using data from the SEER-9 database and US Mortality data, we identified 3,684,040 cancer survivors diagnosed between 1975 and 2020. The SMR of suicide among cancer survivors was calculated, and Poisson regression analysis was used to evaluate trends in suicide risk. Subgroup analyses were performed based on age, gender, race, tumor site, and stage. A competing risk model was used to calculate the 10-year cumulative incidence of suicide. RESULTS: Among cancer survivors, the overall SMR of suicide was 1.49 (95%CI: 1.46-1.53) times higher than that of the general population in the US. The risk of suicide varied significantly by cancer site, with the highest risk found in patients with malignant respiratory system cancer. Overall, we observed a significant downward trend in the suicide mortality rate among cancer patients. The cumulative incidence of suicide mortality among cancer survivors across four study periods exhibited significant statistical differences (P<0.001). CONCLUSIONS: Our study highlights the need for targeted suicide prevention efforts for cancer survivors, particularly those diagnosed with respiratory system cancer. The trend of declining suicide mortality rates among cancer survivors is promising, but continued efforts are needed to understand and address the underlying risk factors.

Causal relationship between prostate cancer and 12 types of cancers: multivariable and bidirectional Mendelian randomization analyses.

BACKGROUND: Previous observational studies have shown an association between certain cancers and the subsequent risk of prostate cancer (PCa). However, the causal relationship between these cancers and PCa is still unclear. This study aimed to investigate the causal relationship between 12 common cancers and the risk of PCa. METHODS: We employed genome-wide association studies (GWAS) to perform forward and reverse Mendelian randomization (MR) within two-sample frameworks. Furthermore, we conducted multivariable MR analyses to investigate the relationships between different types of cancer. In addition, multiple sensitivity analysis methods were employed to assess the robustness of our findings. RESULTS: Our univariable MR analysis showed that genetically predicted hematological cancer was associated with a reduced risk of PCa (OR: 0.911, 95% CI 0.89-0.922, P = 0.03). Furthermore, MR analysis demonstrates that genetically predicted occurrence of thyroid gland and endocrine gland cancer also raised the risk of PCa (all P < 0.05). Multivariable analysis showed that thyroid gland cancer exhibited a higher incidence of PCa (OR: 1.12, 95% CI: 1.08-1.16, P = 0.008). In the reverse MR analysis, we found no significant inverse causal associations between PCa and 12 types of cancers. CONCLUSION: In summary, this study provided insights into the causal relationships between various types of cancer and PCa. Hematological cancer was suggested to associate with a lower risk of PCa, while thyroid gland cancer and endocrine gland cancer might increase the risk. These findings contribute to the understanding of genetic factors related to PCa and its potential associations with other cancers.

Machine Learning-based Nomograms for Predicting Clinical Stages of Initial Prostate Cancer: A Multicenter Retrospective Study.

OBJECTIVE: To construct and externally validate machine learning-based nomograms for predicting progression stages of initial prostate cancer (PCa) using biomarkers and clinicopathologic features. METHODS: Three hundred sixty-two inpatients diagnosed with PCa at the First Affiliated Hospital were randomly assigned to training and testing sets in a 3:7 ratio, while 136 PCa patients from People's Hospital formed the external validation set. Imaging and clinicopathologic information were collected. Optimal features distinguishing advanced prostate cancer (APC) and metastatic PCa (mPCa) were identified through logistic regression (LR). ML algorithms were employed to build and compare ML models. The best-performing algorithm established models for PCa progression stage. Models performance was evaluated using metrics, ROC curves, calibration, and decision curve analysis (DCA) in training, testing, and external validation sets. RESULTS: Following LR analyses, PSA (P = .001), maximum tumor diameter (P = .026), Gleason score (P <.001), and RNF41 (P <.001) were optimal features for predicting APC, while ALP (P <.001), PSA (P <.001), and GS score (P = .024) were for mPCa. Among ML models, the LR models exhibited superior performance. Consequently, the LR algorithm was used for the APC-risk-nomogram and mPCa-risk-nomogram construction, with AUC values of 0.848, 0.814, 0.810, and 0.940, 0.913, 0.910, in the training, testing, and external validation sets, respectively. Calibration and DCA curves affirmed nomograms' consistency and net benefits for clinical decision-making. CONCLUSION: In summary, ML-based APC-risk-nomogram and mPCa-risk-nomogram exhibit outstanding predictive performance for PCa progression stages. These nomograms can assist clinicians in finely categorizing newly diagnosed PCa patients, facilitating personalized treatment plans and prognosis assessment.

Machine learning-based CT radiomics enhances bladder cancer staging predictions: A comparative study of clinical, radiomics, and combined models.

BACKGROUND: Predicting the accurate preoperative staging of bladder cancer (BLCA), which markedly affects treatment decisions and patient outcomes, using traditional clinical parameters is challenging. Nevertheless, emerging studies in radiomics, especially machine learning-based computed tomography (CT) image-based radiomics, hold promise in improving stage prediction accuracy in various tumors. However, the comparative performance and clinical utility of models for BLCA are under investigation. PURPOSE: We aimed to investigate the application value of machine learning-based CT radiomics in preoperative staging prediction by comparing the performance of clinical, radiomics, and clinical-radiomics combined models. METHODS: A retrospective cohort of 105 patients with initial BLCA was randomized into training (70%) and testing (30%) cohorts. Radiomics features were extracted from CT images using the optimal feature filter, followed by the application of the least absolute shrinkage and selection operator algorithm for optimum feature selection. Furthermore, machine learning algorithms were used to establish a radiomics model within the training cohort. Independent risk factors for muscle-invasive BLCA (MIBC) obtained by multivariate logistic regression (LR) analysis were separately used to construct a clinical model. For a clinical-radiomics fusion model, radiomics features were combined with clinical parameters. Performance was evaluated based on receiver operating characteristic curves, calibration curves, decision curve analysis (DCA), and standard performance metrics. RESULTS: Patients exhibited a significantly higher age (p = 0.029), larger tumor size (p = 0.01), and an increased neutrophil-to-lymphocyte ratio (NLR; p = 0.045) in the MIBC group than in the NMIBC group. LR analysis revealed age (p = 0.026), tumor size (p = 0.007), and NLR (p = 0.019) as significant predictors for constructing the clinical model. In the testing cohort, the radiomics model, which used an Support Vector Machine classifier, achieved the highest area under the curve (AUC) value of 0.857. The clinical-radiomics model outperformed the remaining two models, with AUC values of 0.958 and 0.893 in the training and testing cohorts, respectively. DeLong's test indicated significant differences between the three models. Calibration curves showed good agreement, and DCA confirmed the superior clinical utility of the clinical-radiomics model. CONCLUSIONS: Machine learning-based CT radiomics combined with clinical parameters was a promising approach in staging BLCA accurately, which outperformed the individual models. Integrating radiomics features with clinical information holds the potential to improve personalized treatment planning and patient outcomes in BLCA.

Higher systemic immune-inflammation index is associated with increased risk of erectile dysfunction: Result from NHANES 2001-2004.

This study utilized data from the National Health and Nutrition Examination Survey (NHANES) to investigate the association between the systemic immune-inflammation index (SII) and erectile dysfunction (ED) in adult males. The SII is a novel index derived from the counts of neutrophils, lymphocytes, and platelets in the peripheral blood and serves as a comprehensive indicator of the immune response and inflammation levels. The study included 3601 participants from the NHANES 2001-2004 cycle. Covariates such as age, race, marital status, education, smoking, alcohol consumption, BMI, hypertension, and diabetes were taken into account. Weighted analysis and logistic regression models were applied to assess the relationship between SII and ED, adjusting for potential confounding factors. The prevalence of ED was found to be 6.28%. Overall, there is a linear correlation between SII (nonlinear P > .05) and ED. After adjusting for various confounding factors, a significant association was observed between high levels of the SII and ED. The odds ratio (OR) for ED in individuals with high SII levels was 1.45 (95% CI: 1.01-2.17, P = .045). Subgroup analysis further identified specific participant subgroups with a significant association between SII and ED. Our findings suggest that higher levels of the SII are independently associated with an increased risk of ED in adult males. The SII may serve as a valuable biomarker for identifying individuals at higher risk of ED and may aid in the development of tailored treatment approaches. Further research is needed to explore the underlying mechanisms and potential therapeutic implications.

Incidence, mortality and survival of transitional cell carcinoma in the urinary system: A population-based analysis.

The goal of this study is exploring the disparity of incidence, mortality and survival outcome among transitional cell carcinomas (TCCs) in the 4 parts of urinary system. This study comprehensively evaluates these disparities using the Surveillance, Epidemiology, and End Results (SEER) (2000-2018) database. According to the SEER database, the urinary tract is divided into 4 parts: urinary bladder, renal pelvis, ureter, and urethra. The joinpoint regression was used to analyze the secular trend of incidence and incidence-based mortality (IBM). The Kaplan-Meier method with the log-rank test is performed to evaluate survival outcomes. The bladder TCC has the highest age-adjusted incidence and mortality rate compared with TCC in other 3 locations. A slight decrease in incidence is shown in the both bladder and urethra TCCs during 2000-2018. The age-adjusted mortality rate similarly presents an initial increase among 4 locations TCCs at the beginning of study period. The survival curves demonstrate that patients with bladder TCCs have better overall survival (OS) and cancer-specific survival (CSS), whereas those with renal pelvis TCCs have the worse OS and CSS. In addition, patients with bladder TCC have the highest 1-year, 3-year, 5-year relative survival rate, and those with renal pelvis TCC have the lowest. These disparities are especially essential when we explore tumor characteristics and treatment, extrapolated from the literature on bladder TCC for upper tract urothelial carcinoma (UTUC). Notably, patients with bladder TCC especially for localized stage have better survival outcomes than those with UTUC.

Predicted visceral adiposity index in relation to risk of coronary heart disease and all-cause mortality: insights from NHANES.

Background and aims: The Visceral Adiposity Index (VAI) is a straightforward and gender-specific marker that combines anthropometric measurements with lipid profiles. The objective of this study was to evaluate the relationship between VAI and coronary heart disease (CHD). Methods and results: The study examined data collected from adults during the NHANES 1999-2018 cycle. The analyses were weighted, and multivariable logistic regression models were employed to investigate the association between VAI and CHD. Additionally, subgroup analyses stratified by age were conducted. To evaluate the impact of VAI levels on survival outcomes, the study utilized the Kaplan-Meier method and performed the log-rank test to evaluate the survival outcome of participants with different VAI levels. The study findings revealed a significant association between VAI and CHD, indicating a non-linear relationship where an increase in VAI was associated with an elevated risk of CHD. High levels of VAI were linked to an increased prevalence of CHD (Q4 vs Q1, OR 1.50, 95% CI 1.12-2.01, P=0.01). Additionally, higher levels of VAI were associated with a poorer overall prognosis in terms of survival outcomes. There were no statistically significant differences in survival outcomes among the population with CHD. Conclusion: The results of this study highlighted a significant association between VAI and CHD, with a non-linear relationship observed. High VAI levels were associated with an increased risk of CHD and poor survival outcomes, emphasizing the importance of understanding and managing this risk factor, particularly in older age groups.

For small (1-3cm) nonfunctional adrenal incidentaloma (NFAI), which option is more appropriate for conservative treatment or surgery?

Objective: To compare the efficacy and safety between conservative treatment and surgery for the patients with small (1-3cm) nonfunctional adrenal incidentaloma (NFAI). Methods: The patients with small (1-3cm) NFAI who received conservative treatment or surgery in our hospital from November 2018 to December 2019 were retrospectively collected. A total of 83 patients were included in this study. They were divided into two groups according to the treatment methods: the surgery group (n=51) and the conservative treatment group (n=32).Then patients' demographics, tumor characteristics, functional indicators and complications were compared. Statistical analysis was performed using t-test for continuous variables and Pearson chi-square test or Fisher's exact test for categorical variables. Results: At the time of diagnosis, after 3 months, after 6 months, after 12 months, and after 24 months, we found that there was no significant difference between the two groups in systolic blood pressure, diastolic blood pressure, serum potassium levels, and hormone levels. 51 patients chose to have surgery, of which 41 patients chose RLA and 10 patients chose RARLA. RARLA group patients had the highest total cost and conservative treatment group patients had the lowest cost, and the difference was significant (P < 0.001). There was no significant difference in tumor size in the conservative treatment group between at the time of diagnosis and after 24 months (P = 0.305). Conclusion: Surgical treatment is more effective for 1-3cm NFAI, but conservative treatment is safer and more economical. Follow-up after conservative or surgical treatment is necessary.

Advances in the bladder cancer research using 3D culture models.

Bladder cancer represents the most common malignancy of the urinary system, posing a significant threat to patients' life. Animal models and two-dimensional (2D) cell cultures, among other traditional models, have been used for years to study various aspects of bladder cancer. However, these methods are subject to various limitations when mimicking the tumor microenvironment in vivo, thus hindering the further improvement of bladder cancer treatments. Recently, three-dimensional (3D) culture models have attracted extensive attention since they overcome the shortcomings of their traditional counterparts. Most importantly, 3D culture models more accurately reproduce the tumor microenvironment in the human body because they can recapitulate the cell-cell and cell-extracellular matrix interactions. 3D culture models can thereby help us gain deeper insight into the bladder cancer. The 3D culture models of tumor cells can extend the culture duration and allow for co-culturing with different cell types. Study of patient-specific bladder cancer mutations and subtypes is made possible by the ability to preserve cells isolated from particular patients in 3D culture models. It will be feasible to develop customized treatments that target relevant signaling pathways or biomarkers. This article reviews the development, application, advantages, and limitations of traditional modeling systems and 3D culture models used in the study of bladder cancer and discusses the potential application of 3D culture models.

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.

Get insight into the cause of death distribution and epidemiology of penile squamous cell carcinoma: A population-based study.

BACKGROUND: Penile squamous cell carcinoma (PSCC) survival had no significant improvement since 1990 in the United States. This study aims to get insight into the changing trend and distribution of death causes of PSCC. The epidemiology of PSCC is also investigated. METHODS: The Surveillance, Epidemiology, and End Results (SEER) (1992-2018) database is utilized to get patients diagnosed with penile squamous cell carcinoma. The trend of incidence, distribution of age, changing trend and distribution of death cause, and survival outcome are analyzed for all PSCC patients and each race. RESULTS: Three thousand four hundred and twenty-three male patients with PSCC are enrolled in our study. The age-adjusted incidence rate of the white has a slight increase (Annual percent change [APC] = 0.647%). American Indian/Alaska Native men have the highest average annual incidence, while Asian /Pacific Islander men have the lowest. PSCC patients aged 70-80 are the most common, and patients over 80 years have the highest 3-year (50%) and 5-year (63.93%) mortality rate. Non-cancer disease, especially circulatory system disease, is the most common cause of death, whereas the proportion of patients who died of PSCC significantly increased from 21.17% (1992-2001) to 41.3% (2012-2017) in PSCC patients (p < 0.001). These results have not changed significantly when we only focus on primary PSCC without previous malignant tumors. Hispanics are shown better overall survival than non-Hispanic White and non- Hispanic Black men. (p < 0.001) No statistical differences in cancer-specific survival are observed (p = 0.15). CONCLUSION: The current study provides essential initial data regarding the presentation and clinical outcomes of PSCC patients. Notably, non-cancer disease, especially circulatory system disease, is the more common cause of death than PSCC. However, the proportion of patients who died of penile squamous cell carcinoma has a relatively significant increase in recent years. The increasing trends in the advanced stage of PSCC patients might account for this change.

High cardiovascular disease mortality after penile squamous cell carcinomas diagnosis: Results from the United States SEER population, 2005-2016.

Background: Cancer survivorship care is an emerging and necessary component of oncology management. To explore cardiovascular disease (CVD)-specific mortality and prognostic factors among patients with penile squamous cell carcinomas (PSCC). These results aid clinicians in furtherly understand this disease's prognosis. Method: We analyzed Surveillance, Epidemiology and End Results Program data for 2668 PSCC cases diagnosed between 2005 to 2016. We calculated standardized mortality ratios (SMRs) of CVD and all-cause mortality, comparing PSCC patients with general population men. A cumulative mortality curve and competitive risk regression model were utilized to evaluate the prognostic factors of CVD-specific death. Results: Death distribution is as follows: PSCC (42.4%), other causes (21.3%) CVD (19%), and other cancers (17.3%). PSCC patients are more like to die from CVD (SMR=3.2, 95%CI: 3.1-3.3) and all-cause death compared with the general population. Meanwhile, patients undergoing surgery show a relatively higher CVD-specific mortality than the general population (SMR=2.7, 95%CI: 2.4-3.2). In the competitive risk model, higher CVD mortality is associated with age, region, year of diagnosis, stage, and marital status (all P<0.05). Patients with the localized stage show a higher risk of CVD-specific death than those with regional or distant stage. Conclusion: Our study mainly reveals that cardiovascular disease was the important cause of death and higher CVD-specific mortality among PSCC patients. Several associated factors related to CVD-specific death are also identified. In the future, more work in educating health care professionals on the components of survivorship care is needed to meet the long-term and late effects cancer patients experience.