Smoking cessation and relapse among Black and White patients referred for lung cancer screening

Background: Tobacco quit rates in the adult U.S. population range from 4% to 8% annually. Lung cancer screening (LCS) provides an opportunity for discussion of smoking cessation. Outside of LCS, Blacks have been shown to make more quit attempts and have higher readiness to quit, but have lower quit rates among current smokers and higher relapse rates among former smokers. In this study, we determined quit and relapse rates after a provider referral for LCS in Black and White patients. Methods: We conducted an observational study within an integrated health system that has both a LCS program and an independent smoking cessation program. Patients, aged 55-77 years who received at least one provider referral (order) for LCS between September 2016 and April 2022 and a second order within 9-36 months, were included in this study. Smoking status was captured in LCS orders. Demographic variables, completion of a low-dose screening CT (LDSCT), smoking cessation counseling referral and medication prescription were captured from the electronic medical record. Pearson Chi-squared test and multivariable logistic regression were used to determine group differences and important predictors of tobacco quit and relapse. Results: During the study period, 6,096 patients (21% Black) received a referral to LCS and 75% of these patients completed an LDSCT between orders. Among current smokers (N=3715) the quit rate was 14% and relapse occurred in 10% of former smokers (N=2381), overall. Rates of quit (12.0% LDSCT no vs. 14.6% LDSCT yes, p=0.048) and relapse (13.7% LDSCT no vs. 9.4% LDSCT yes, p=0.006) were worse for those who did not complete the LDSCT between orders. Black patients had lower quit (11% vs. 14%, p=0.003) and higher relapse (13.6% vs. 9.7%, p=0.03) rates than Whites. Among Black former smokers who did not complete the LDSCT, the relapse rate was nearly 20% and these patients received referrals to counseling and prescriptions for cessation medications at higher rates than White former smokers. In multivariable models, older age, receiving a prescription for a cessation medication, and completing the LDSCT were associated with smoking cessation, while Black race and receiving a referral for counseling were associated with lower odds of quitting. Black race and longer duration between orders were associated with greater likelihood of relapse, while older age and completing the LDSCT were associated with lower likelihood of relapse. Discussion: Rates of smoking cessation appear higher in patients referred for LCS than in the general population. In the context of LCS, Black patients still have lower quit and higher relapse rates than White patients. Relapse is particularly high in Black former smokers who do not complete LDSCT after a referral for screening. Lung screening and smoking cessation programs will need to work together to find culturally appropriate resources and ways to reach out to patients referred for screening, especially those who do not complete the LDSCT, to encourage quitting and provide equitable cessation support

Oral Microbiome Community Composition in Head and Neck Squamous Cell Carcinoma

The impact of the oral microbiome on head and neck cancer pathogenesis and outcomes requires further study. 16s rRNA was isolated and amplified from pre-treatment oral wash samples for 52 cases and 102 controls. The sequences were binned into operational taxonomic units (OTUs) at the genus level. Diversity metrics and significant associations between OTUs and case status were assessed. The samples were binned into community types using Dirichlet multinomial models, and survival outcomes were assessed by community type. Twelve OTUs from the phyla Firmicutes, Proteobacteria, and Acinetobacter were found to differ significantly between the cases and the controls. Beta-diversity was significantly higher between the cases than between the controls (p p p p < 0.01). Significant differences between the cases and the controls in community type, beta-diversity, and OTUs indicate that the oral microbiome may play a role in HNSCC

Application of the Denovo Discrete Ordinates Radiation Transport Code to Large-Scale Fusion Neutronics

Fusion energy systems pose unique challenges to the modeling and simulation community. These challenges must be met to ensure the success of the ITER experimental fusion reactor. ITER's complex systems require detailed modeling that goes beyond the scale of comparable simulations to date. In this work, the Denovo radiation transport code was used to calculate neutron fluence and kerma for the JET streaming benchmark. This work was performed on the Titan supercomputer at the Oak Ridge Leadership Computing Facility. Denovo is a novel three-dimensional discrete ordinates transport code designed to be highly scalable. Sensitivity studies have been completed to examine the impact of several deterministic parameters. Results were compared against experiment as well as the MCNP and Shift Monte Carlo codes