IMPORTANCEThere is concern that African American men with low-risk prostate cancer may harbor more aggressive disease than non-Hispanic White men. Therefore, it is unclear whether active surveillance is a safe option for African American men.OBJECTIVE To compare clinical outcomes of African American and non-Hispanic White men with low-risk prostate cancer managed with active surveillance.

Chemokines and their receptors are involved in oncogenesis and in tumor progression, invasion, and metastasis. Various chemokines also promote cell proliferation and resistance to apoptosis of stressed cells. The chemokine CXCL8, also known as interleukin-8 (IL-8), is a proinflammatory molecule that has functions within the tumor microenvironment. Deregulation of IL-8 signaling is shown to play pivotal roles in tumorigenesis and progression. Mallory-Denk Bodies (MDBs) are prevalent in various liver diseases including alcoholic hepatitis (AH) and are formed in mice livers by feeding DDC. By comparing AH livers where MDBs had formed with normal livers, there were significant changes of IL-8 signaling by RNA sequencing (RNA-Seq) analyses. Real-time PCR analysis of CXCR2 further shows a 6-fold up regulation in AH livers and a 26-fold up regulation in the livers of DDC re-fed mice. IL-8 mRNA was also significantly up regulated in AH livers and DDC re-fed mice livers. This indicates that CXCR2 and IL-8 may be crucial for liver MDB formation. MDB containing balloon hepatocytes in AH livers had increased intensity of staining of the cytoplasm for both CXCR2 and IL-8. Over expression of IL-8 leads to an increase of the mitogen activated protein kinase (MAPK) cascade and exacerbates the inflammatory cycle. These observations constitute a demonstration of the altered regulation of IL-8 signaling in the livers of AH and mice fed DDC where MDBs formed, providing further insight into the mechanism of MDB formation mediated by IL-8 signaling in AH.

PURPOSE: Minority race and lower socioeconomic status are associated with lower rates of opioid prescription and undertreatment of pain in multiple noncancer healthcare settings. It is not known whether these differences in opioid prescribing exist among patients undergoing cancer treatment. METHODS AND MATERIALS: This observational cohort study involved 33,872 opioid-naive patients of age > 65 years undergoing definitive cancer treatment. We compared rates of new opioid prescriptions by race or ethnicity and socioeconomic status controlling for differences in baseline patient, cancer, and treatment factors. To evaluate downstream impacts of opioid prescribing and pain management, we also compared rates of persistent opioid use and pain-related emergency department (ED) visits. RESULTS: Compared with non-Hispanic White patients, the covariate-adjusted odds of receiving an opioid prescription were 24.9% (95% CI, 16.0 to 33.9, P < .001) lower for non-Hispanic Blacks, 115.0% (84.7 to 150.3, P < .001) higher for Asian–Pacific Islanders, and not statistically different for Hispanics (−1.0 to 14.0, P = .06). There was no significant association between race or ethnicity and persistent opioid use or pain-related ED visits. Patients living in a high-poverty area had higher odds (53.9% [25.4 to 88.8, P < .001]) of developing persistent use and having a pain-related ED visit (39.4% [16.4 to 66.9, P < .001]). CONCLUSION: For older patients with cancer, rates of opioid prescriptions and pain-related outcomes significantly differed by race and area-level poverty. Non-Hispanic Black patients were associated with a significantly decreased likelihood of receiving an opioid prescription. Patients from high-poverty areas were more likely to develop persistent opioid use and have a pain-related ED visit.

Background This study was done to determine the representation of minorities, women, and the elderly in National Cancer Institute (NCI) clinical trials. Methods This is an analysis in the NCI Clinical Data Update System. Patients were evaluated in breast, colorectal, lung, and prostate cancer trials from 2000 to 2019. Representation in a trial was determined by race/ethnicity, sex, and age. Secondarily, the change in trial participation by multivariable analysis by comparing years 2000 through 2004 to 2015 through 2019 was evaluated. Results The cohort included 242,720 participants: 197,320 Non‐Hispanic White (81.3%), 21,190 Black (8.7%), 11,587 Hispanic (4.8%), and 6880 Asian/Pacific Islander (2.8%). Black and Hispanic patients were underrepresented for colorectal (odds ratio [OR], 0.58; 95% confidence interval [CI], 0.50‐0.67; P < .001 and OR, 0.74; 95% CI, 0.64‐0.87; P < .001, respectively), lung (OR, 0.83; 95% CI, 0.76‐0.91; P < .001 and 0.66; 95% CI, 0.57‐0.77; P < .001, respectively), and prostate cancer trials (OR, 0.85; 95% CI, 0.79‐0.92; P < .001 and OR, 0.58; 95% CI, 0.51‐0.66; P < .001) between 2015 and 2019. The odds of participation in 2015 to 2019 increased among Black patients in breast (OR, 2.19; 95% CI, 2.07‐%2.32; P < .001), lung (OR, 1.54; 95% CI, 1.38‐1.73; P < .001), and prostate cancer trials (OR, 1.14; 95% CI, 1.04‐1.26; P < .001). The odds of participation in a trial among Hispanic patients increased for breast (OR, 3.32; 95% CI, 3.09‐3.56; P < .001), colorectal (OR, 2.46; 95% CI, 2.04‐2.96; P < .001), lung (OR, 3.88; 95% CI, 3.20‐4.69; P < .001), and prostate cancer (OR, 1.70; 95% CI, 1.42‐2.04; P = .005). Conclusions This study identified that Black and Hispanic patients remain underrepresented in trials, but in recent years, participation has increased. These findings indicate that minority participation has increased over time, but further efforts are needed.

Background: Radiomics has been applied to predict recurrence in several disease sites, but current approaches are typically restricted to analyzing tumor features, neglecting non-tumor information in the rest of the body. The purpose of this work was to develop and validate a model incorporating non-tumor radiomics, including whole body features, to predict treatment outcomes in patients with previously untreated locoregionally advanced cervical cancer. Methods:We analyzed 127 cervical cancer patients treated definitively with chemoradiotherapy and intracavitary brachytherapy. All patients underwent pretreatment whole body 18 F-FDG PET/CT. To quantify effects due to the tumor itself, the gross tumor volume (GTV) was directly contoured on the PET/CT. Meanwhile, to quantify effects arising from the rest of the body, the planning target volume (PTV) was deformably registered from each planning CT to the PET/CT, and a semi-automated approach combining seed-growing and manual contour review generated whole body muscle, bone, and fat segmentations on each PET/CT. A total of 965 radiomic features were extracted for GTV, PTV, muscle, bone, and fat. 95 patients were used to train a Cox model of disease recurrence including both radiomic and clinical features (age, stage, tumor grade, histology, and baseline complete blood cell counts), using bagging and split-sample-validation for feature reduction and model selection. To further avoid overfitting, the resulting models were tested for generalization on the remaining 32 patients, by calculating a risk score based on Cox regression and evaluating the c-index (c-index > 0.5 indicates predictive power). Results: Optimal performance was seen in a Cox model including one clinical biomarker (whether or not a tumor was stage III-IVA), two GTV radiomic biomarkers (PET gray-level size-zone matrix small area low gray level emphasis and zone entropy), one PTV radiomic biomarker (major axis length) and one whole body radiomic biomarker (CT Bone root mean square). In particular, stratification into high-and lowrisk groups, based on the linear risk score from this Cox model, resulted in a hazard ratio [95% CI] of 0.019 [0.004, 0.082], an improvement over stratification based on clinical stage alone, which had a hazard ratio of 0.36 [0.16, 0.83]. Conclusions: Incorporating non-tumor radiomic biomarkers can improve the performance of prognostic models compared to using only clinical and tumor radiomic biomarkers. Future work should look to further test these models in larger, multiinstitutional cohorts.

Background Despite higher risks associated with prostate cancer, young African American men are poorly represented in prostate-specific antigen (PSA) trials, which limits proper evidence-based guidance. We evaluated the impact of PSA screening, alongside primary care provider utilization, on prostate cancer outcomes for these patients. Methods We identified African American men aged 40–55, diagnosed with prostate cancer between 2004–2017 within the Veterans Health Administration. Inverse probability of treatment weighted propensity scores were utilized in multivariable models to assess PSA screening on PSA &gt; 20, Gleason score ≥ 8, and metastatic disease at diagnosis. Lead-time adjusted Fine-Gray regression evaluated PSA screening on PCSM, with non-cancer death as competing events. All statistical tests were 2-sided. Results The cohort included 4,726 patients. Mean age was 51.8 years, with 84-month median follow-up. There were 1,057 (22.4%) with no PSA screening prior to diagnosis. Compared to no screening, PSA screening was associated with statistically significantly reduced odds of PSA &gt; 20 (odds ratio [OR] = 0.56, 95% confidence interval [CI] = 0.49–0.63, P &lt; .001), Gleason score ≥ 8 (OR = 0.78, 95% CI = 0.69–0.88, P &lt; .001), and metastatic disease at diagnosis (OR = 0.50, 95% CI = 0.39–0.64, P &lt; .001), and decreased PCSM (subdistribution hazard ratio = 0.52, 95% CI = 0.36–0.76, P &lt; .001). Primary care provider visits displayed similar effects. Conclusions Among young African American men diagnosed with prostate cancer, PSA screening was associated with statistically significantly lower risk of PSA &gt; 20, Gleason score ≥ 8, and metastatic disease at diagnosis and statistically significantly reduced risk of PCSM. However, the retrospective design limits precise estimation of screening effects. Prospective studies are needed to validate these findings.

Purpose: Cancer treatments can paradoxically appear to reduce the risk of noncancer mortality in observational studies, due to residual confounding. Here we introduce a method, Bias Reduction through Analysis of Competing Events (BRACE), to reduce bias in the presence of residual confounding. Experimental Design: BRACE is a novel method for adjusting for bias from residual confounding in proportional hazards models. Using standard simulation methods, we compared BRACE with Cox proportional hazards regression in the presence of an unmeasured confounder. We examined estimator distributions, bias, mean squared error (MSE), and coverage probability. We then estimated treatment effects of high versus low intensity treatments in 36,630 prostate cancer, 4,069 lung cancer, and 7,117 head/neck cancer patients, using the Veterans Affairs database. We analyzed treatment effects on cancer-specific mortality (CSM), noncancer mortality (NCM), and overall survival (OS), using conventional multivariable Cox and propensity score (adjusted using inverse probability weighting) models, versus BRACE-adjusted estimates. Results: In simulations with residual confounding, BRACE uniformly reduced both bias and MSE. In the absence of bias, BRACE introduced bias toward the null, albeit with lower MSE. BRACE markedly improved coverage probability, but with a tendency toward overcorrection for effective but nontoxic treatments. For each clinical cohort, more intensive treatments were associated with significantly reduced hazards for CSM, NCM, and OS. BRACE attenuated OS estimates, yielding results more consistent with findings from randomized trials and meta-analyses. Conclusions: BRACE reduces bias and MSE when residual confounding is present and represents a novel approach to improve treatment effect estimation in nonrandomized studies.

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