Racial disparities in conditional survival of patients with bladder cancer: a population-based study

Racial differences in carcinoma-in-situ and non-muscle-invasive bladder cancer mortality: Accounting for insurance status, black segregation, and neighborhood poverty

BACKGROUND

Few Bladder Cancer (BC) studies have examined the role of area-level variables. The purpose of this study was to examine racial differences in BC survival to elucidate if insurance status and contextual covariates could explain Black disadvantage in survival.

METHOD

Using the Fine-Gray subdistribution hazard models (sHR), five-year survival time was calculated from the date of diagnosis until the last day of follow-up or the date of death due to BC in Florida 2000-2014 (n = 32,321). Non-BC deaths were considered a competing risk. In all models, individual-level clinical and demographic variables were adjusted for and we included the exposures of interest for Carcinoma-in-Situ (CIS) and Non-Muscle-Invasive BC(NMIBC), separately.

RESULTS

In CIS-Patients, living in neighborhoods with higher levels of segregation was associated with 50 % to 2-fold increase in sHR (medium level segregation sHR= 1.50, 95 % CI: 1.06-2.13; high level segregation sHR= 2.07, 95 % CI: 1.25-3.43). Uninsured CIS patients had more than 2-fold increased sHR compared to those with private insurance (sHR=2.34, 95 % CI: 1.05-5.24). In NMIBC patients, living in areas with level of poverty resulted in 10 % the hazard of death increased when compared to low poverty (high poverty sHR=1.11, 95 % CI: 1.01-1.21). Uninsured and Medicaid covered NMIBC patients had an increased sHR (uninsured sHR=2.05, 95 % CI: 1.62-2.59; Medicaid sHR=1.36, 95 % CI: 1.11-1.67). For both CIS and NMIBC patients, the Black/White survival gap decreased when insurance and contextual variables were included.

CONCLUSION

This study identified BC survival rates were different for Black and White patients in Florida and found that those observed gaps were, to some extent, linked to broader social factors. We recommend that future cancer studies examining racial disparities incorporate area-level variables to offer a more nuanced understanding of these complex disparities.

Examining Patient Characteristics in Bladder Cancer Clinical Trials Involving Immunotherapy

Background/Objectives: Comprehending the patient composition of bladder cancer (BC) clinical trials is crucial for effectively designing clinical trials and contextualizing the generated science. In this study, we reviewed publicly available data and explored the demographic information of BC studies administering immune checkpoint inhibitors (ICIs). Methods: Trial eligibility was irrespective of government or private sponsorship, and trial activation dates were limited to between 2013 and 2023. The main inclusion criteria were use of ICIs and trials reporting endpoints that include progression-free survival (PFS), overall survival (OS), disease-free survival (DFS), and event-free survival (EFS). The key exclusion terms were review articles and meta-analysis. Results: We identified a total of 109 clinical trials with an aggregate total of 8936 enrolled patients. Ninety-six percent identified as Caucasian or White European, and 23% identified as female. Further analyses revealed that 65% of the patients were aged 65 years or older. One-third of the trials listed similar comorbidities, such as cardiovascular disease and diabetes, that were exhibited by approximately 30 percent of the patients. Conclusions: Our data suggest that recruitment strategies should be mindful of comorbidities that may interfere with ICI treatments. Additionally, our results are consistent with findings from other reviews that indicate that certain patient groups may be under-represented in BC trials.

Conditional survival analysis and dynamic prediction of long-term survival in Merkel cell carcinoma patients

Background

Merkel cell carcinoma (MCC) is a rare type of invasive neuroendocrine skin malignancy with high mortality. However, with years of follow-up, what is the actual survival rate and how can we continually assess an individual's prognosis? The purpose of this study was to estimate conditional survival (CS) for MCC patients and establish a novel CS-based nomogram model.

Methods

This study collected MCC patients from the Surveillance, Epidemiology, and End Results (SEER) database and divided these patients into training and validation groups at the ratio of 7:3. CS refers to the probability of survival for a specific timeframe (y years), based on the patient's survival after the initial diagnosis (x years). Then, we attempted to describe the CS pattern of MCCs. The Least absolute shrinkage and selection operator (LASSO) regression was employed to screen predictive factors. The Multivariate Cox regression analysis was applied to demonstrate these predictors' effect on overall survival and establish a novel CS-based nomogram.

Results

A total of 3,843 MCC patients were extracted from the SEER database. Analysis of the CS revealed that the 7-year survival rate of MCC patients progressively increased with each subsequent year of survival. The rates progressed from an initial 41-50%, 61, 70, 78, 85%, and finally to 93%. And the improvement of survival rate was nonlinear. The LASSO regression identified five predictors including patient age, sex, AJCC stage, surgery and radiotherapy as predictors for CS-nomogram development. And this novel survival prediction model was successfully validated with good predictive performance.

Conclusion

CS of MCC patients was dynamic and increased with time since the initial diagnosis. Our newly established CS-based nomogram can provide a dynamic estimate of survival, which has implications for follow-up guidelines and survivorship planning, enabling clinicians to guide treatment for these patients better.