Understanding the microbiome as a mediator of bladder cancer progression and therapeutic response.

Bladder cancer (BCa) remains a significant source of morbidity and mortality. BCa is one of the most expensive tumors to treat, in part because of a lack of nonsurgical options. The recent advent of immunotherapy, alone or in combination with other compounds, has improved therapeutic options. Resistance to immunotherapy remains common, and many patients do not have durable response. Recent advances indicate immunotherapy efficacy may be tied in part to the endogenous bacteria present in our body, more commonly referred to as the microbiome. Laboratory and clinical data now support the idea that a healthy microbiome is critical to effective response to immunotherapy. At the same time, pathogenic interactions between the microbiome and immune cells can also serve to drive formation of tumors, increasing the complexity of these interactions. Given the rising importance of immunotherapy in BCa, understanding how we might be able to alter the microbiome to improve therapeutic efficacy offers a novel route to improved patient care. The goal of this review is to examine our current understanding of microbial interactions with the immune system and cancer with an emphasis on BCa. We will further attempt to define both current gaps in knowledge and future directions that may yield beneficial results to the field.

Correlation between visuo-cognitive tests and simulator performance of commercial drivers in the United States.

BACKGROUND: Driving commercial vehicles requires intact visuo-cognitive skills. Approximately 13% of all fatal motor vehicle crashes in the United States involve commercial drivers. The ability to accurately predict risk factors for unsafe commercial driving is essential for public safety. Accurate prediction tools will advance the field of commercial driver science, provide policy guidance for driver testing and assist healthcare providers during testing. Prior studies have correlated clinical tools to roadway safety; translating these results to commercial drivers has not yet been done. OBJECTIVE: This study aimed to identify specific demographic, driving history and visuo-cognitive test results that correlate with driving simulator performance. Using the Cumulative Simulator Score (CSS) as a surrogate for driving ability, the objective was to correlate both sets of data (self-reported and visuo-cognitive testing) with the CSS to identify screening tools for unsafe driving in commercial drivers. PRINCIPAL RESULTS: Baseline assessments of 120 variables were collected from October 2020 to January 2022. Of the 31 participants, 3 were female and 28 were male with a mean age of 53 years. Average BMI was 32, blood pressure 136/84, 32 years of CDL driving experience, 36,500 annual CDL mileage, 11,000 annual personal mileage, 14 years of education, average number of medications: 2, average number of medical conditions: 2, six participants with personal and/or commercial crashes or tickets in past five years, MOCA 27/30, Trails B time 66 s, UFOV Speed of Processing 15 ms, Stroke Disease Severity Assessment pass rate 94 %. The Cumulative Simulator Score (CSS), correlated significantly with education (r = 0.42; p = 0.02), commercial driving experience (r = 0.42; 0 = 0.02), and number of tickets as a commercial driver (Spearman rho = 0.40; p = 0.02). In a stepwise multivariable linear regression analysis, the number of tickets as a CDL driver in the past five years and years of education were retained as significant variables in the multivariable linear regression model, explaining 38 % of the variance of total scores on the CSS. MAJOR CONCLUSIONS: Descriptive and self-reported driving characteristics correlate better with the Cumulative Simulator Score in CDL drivers than visuo-cognitive tests. Since simulator performance has been shown to be a reliable surrogate for driving performance, the number of tickets as a CDL driver in the past five years and years of education can be considered as additions to annual physicals for policy makers and health care providers to help assess their on-the-road safety.

Predictive Value of Computed Tomography Following Neoadjuvant Chemotherapy for Muscle Invasive Bladder Cancer.

BACKGROUND: Neoadjuvant chemotherapy (NAC) prior to radical cystectomy (RC) remains standard treatment for select patients with muscle-invasive bladder cancer (MIBC). Although computed tomography (CT) is often obtained prior to RC, its ability to predict pathologic response is poorly characterized. OBJECTIVE: The purpose of this study is to evaluate the predictive value of CT in assessing disease burden after NAC. METHODS: Patients with MIBC having received NAC prior to RC were identified. Pre- and post-NAC CT scans were reviewed by an abdominal radiologist. The correlation between pathologic complete response (PCR) and radiologic complete response (RCR) was determined as the primary aim. As a secondary aim, the correlation between pathologic partial response (PPR) and radiologic partial response (RPR) was determined. Logistic regression analysis was utilized to determine the predictive value of CT in determining disease burden at RC. RESULTS: A total of 141 patients were identified for analysis. PCR and PPR was achieved in 34% and 16% of patients, respectively. The positive predictive value of post-NAC CT was 53.5% for PCR and 28.8% for PPR. The negative predictive value of post-NAC CT was 73.5% for PCR and 46.2% for PPR. There was no significant association between RCR and PCR (OR 1.13, p = 0.67). Similarly, there was no meaningful association between RPR and PPR, lymph node involvement, or presence of extravesical disease. CONCLUSIONS: CT findings correlate poorly with final pathology at RC and should not be used to evaluate local disease burden.