The incidence, pathogenesis, and management of non-clear cell renal cell carcinoma.

Renal cell carcinoma (RCC) is the most common type of kidney cancer and is divided into two distinct subtypes, clear cell renal cell carcinoma (ccRCC) and non-clear cell renal cell carcinoma (nccRCC). Although many treatments exist for RCC, these are largely based on clinical trials performed in ccRCC and there are limited studies on the management of nccRCC. Non-clear cell RCC consists of multiple histological subtypes: papillary, chromophobe, translocation, medullary, collecting duct, unclassified, and other rare histologies. Due to variations in pathogenesis and therapeutic response, therapy should be tailored to specific variant histologies. For patients with localized nccRCC, surgical resection remains the gold standard. In the metastatic setting, the standard of care has yet to be clearly defined, and most guidelines recommend clinical trial participation. General therapeutic options include immunotherapy, either as monotherapy or in combination, targeted therapies such as vascular endothelial growth factor tyrosine kinase inhibitors and MET inhibitors, and chemotherapy in certain subtypes. Here we present a review of the incidence and pathogenesis of the various subtypes, as well as available clinical data to support therapeutic recommendations for these subtypes. We also highlight currently available clinical trials in nccRCC and future directions in investigating novel treatment modalities tailored to patients with variant histology.

Disparities in Lung Cancer Clinical Trial Discussion and Enrollment at a Safety Net Hospital.

BACKGROUND: In the United States, less than 5% of all adult cancer patients enroll in clinical trials. Few studies explore participation in cancer clinical trials at safety net hospitals, which disproportionately care for minoritized, low-income, uninsured, and underinsured populations. Our study aims to investigate disparities in clinical trial discussions and enrollment among lung cancer patients at Boston Medical Center, the largest safety net hospital in New England. METHODS: We included 1121 patients diagnosed with lung cancer between January 2015 and December 2020. Electronic Medical Records (EMR) were queried, and patients were categorized into three groups: (1) clinical trial discussed and the patient enrolled, (2) clinical trial discussed but the patient not enrolled, and (3) clinical trial not discussed. Sociodemographic variables such as age, gender, race, ethnicity, city, primary language, median household income, medical insurance type, and education level were also collected. Chi-squared,t test, and multivariate regression analysis was done using SPSS version 26.0. RESULTS: Of the 1121 patients, clinical trials were discussed in 141 patients (12.6%), of which 22 (15.6%) were enrolled. Clinical trial discussions were conducted more with younger patients (68.19 vs 71.37, p = .001), but on multivariate analysis there was no significant difference (OR = 1.023; 95% CI 0.998-1.048; p = .068). There was no significant difference in clinical trial discussion or enrollment between the other sociodemographic factors. CONCLUSION: Additional study of barriers to cancer clinical trial discussion and enrollment at safety net institutions can serve as a prerequisite to ameliorating racial disparities observed on a national scale.

Disparities in US Lung Cancer Clinical Trial Enrollment.

BACKGROUND: Disparities within clinical trial enrollment are well-documented, reducing the generalizability of results. Although nearly 30 years have passed since Congress passed the NIH Revitalization Act to encourage the participation of minoritized populations in clinical trials, these patients continue to be underrepresented. This study aimed to investigate lung cancer clinical trial enrollment disparities for race/ethnicity, sex, and age. METHODS: We queried the National Institutes of Health: US National Library of Medicine database of clinical trials for all US-based lung cancer clinical trials completed between 2004 and 2021 and collected data on race and ethnicity, gender, and age breakdown. This data was compared to Surveillance, Epidemiology, and End Results (SEER) database data. Independent sample t-tests and Kruskal-Wallis's approach were used to analyze the data. RESULTS: Of 311 eligible trials with exclusive US enrollment, 136 (44%) reported race and ethnicity breakdown for the patient cohort representing 9869 patients. Hispanic, Non-Hispanic American Indian/Alaska Native, Non-Hispanic Black, and Non-Hispanic Unreported participants were underrepresented (p = 0.001, p = 0.005, p = 0.014, p = 0.002, respectively). Non-Hispanic White participants were overrepresented (p = 0.018). Disparities worsened from 2017 to 2021 for Hispanic patients (p = 0.03). No significant differences were found for sex or age. CONCLUSIONS: Disparities for clinical lung cancer trial enrollment have not shown statistically significant improvement since 2004, and representation remains unequal, especially for racial and ethnic minorities.

Prior Admissions as a Risk Factor for Readmission in Patients Surgically Treated for Femur Fractures: Implications for a Potential Hip Fracture Bundle.

INTRODUCTION: Hip fractures are a significant economic burden to our healthcare system. As there have been efforts made to create an alternative payment model for hip fracture care, it will be imperative to risk-stratify reimbursement for these medically comorbid patients. We hypothesized that patients readmitted to the hospital within 90 days would be more likely to have a recent previous hospital admission, prior to their injury. Patients with a recent prior admission could therefore be considered higher risk for readmission and increased cost. METHODS: A retrospective chart review identified 598 patients who underwent surgical fixation of a hip or femur fracture. Data on readmissions within 90 days of surgical procedure and previous admissions in the year prior to injury resulting in surgical procedure were collected. Logistic regression analysis was used to determine if recent prior admission had increased risk of 90-day readmission. A subgroup analysis of geriatric hip fractures and of readmitted patients were also performed. RESULTS: Having a prior admission within one year was significantly associated (p < 0.0001) for 90-day readmission. Specifically, logistic regression analysis revealed that a prior admission was significantly associated with 90-day readmission with an odds ratio of 7.2 (95% CI: 4.8-10.9). DISCUSSION: This patient population has a high rate of prior hospital admissions, and these prior admissions were predictive of 90-day readmission. Alternative payment models that include penalties for readmissions or fail to apply robust risk stratification may unjustly penalize hospital systems which care for more medically complex patients. CONCLUSIONS: Hip fracture patients with a recent prior admission to the hospital are at an increased risk for 90-day readmission. This information should be considered as alternative payment models are developed for hip fracture care.