Faculty Bibliography

OBJECTIVE:To assess urologists' perceptions and practices related to smoking and smoking cessation. MATERIALS AND METHODS/METHODS:Six survey questions were designed to assess beliefs, practices, and determinants related to tobacco use assessment and treatment (TUAT) in outpatient urology clinics. These questions were included in an annual census survey (2021) offered to all practicing urologists. Responses were weighted to represent the practicing US population of nonpediatric urologists (N=12,852). The primary outcome was affirmative responses to the question, "Do you agree it is important for urologists to screen for and provide smoking cessation treatment to patients in the outpatient clinic?" Practice patterns, perceptions, and opinions of optimal care delivery were assessed. RESULTS:In total, 98% of urologists agreed (27%) or strongly agreed (71%) that cigarette smoking is a significant contributor to urologic disease. However, only 58% agreed that TUAT is important in urology clinics. Most urologists (61%) advise patients who smoke to quit but do not provide additional cessation counseling or medications or arrange follow-up. The most frequently identified barriers to TUAT were lack of time (70%), perceptions that patients are unwilling to quit (44%), and lack of comfort prescribing cessation medications (42%). Additionally, 72% of respondents stated that urologists should provide a recommendation to quit and refer patients for cessation support. CONCLUSIONS:TUAT does not routinely occur in an evidence-based fashion in outpatient urology clinics. Addressing established barriers and facilitating these practices with multilevel implementation strategies can promote tobacco treatment and improve outcomes for patients with urologic disease.

BACKGROUND:To identify gaps in urologic oncology quality and evidence-based smoking cessation care by assessing how often smoking cessation pharmacotherapy (SCP) is given in the inpatient setting following cystectomy. METHODS:The Premier Healthcare Database (PHD), a deidentified all-payer dataset, was used to generate nationally representative estimates of SCP receipt during hospitalization following cystectomy for patients with bladder cancer who smoke. Regressions were used to model associations between SCP receipt and patient- and hospital-level factors. RESULTS:Of the 21,624 patients who underwent cystectomy for bladder cancer, 3,676 patients (17.0%) were identified as current smokers, representing a weighted estimate of 16,063 admissions. Among these admissions, 27.9% of patients received SCP, the vast majority of which (91.5%) received exclusively nicotine replacement therapy. Rates of SCP receipt varied substantially across hospitals (median: 25.0%, IQR: 20.0-33.3, range: 0.0-60.0). Older age and black race (aOR = 0.59, 95% CI: 0.42-0.82) were associated with lower odds of SCP receipt. Increased patient comorbidity score was associated with higher odds of SCP receipt (aOR = 1.02, 95% CI: 1.01-1.03); specifically, chronic pulmonary disease, alcohol abuse, and depression were independently associated with SCP receipt. Hospital teaching status, bed capacity, and mean annual cystectomy volume were not associated with SCP receipt. SCP receipt was not associated with hospital length of stay nor 90-day readmission or mortality following cystectomy. CONCLUSIONS:SCP is infrequently given to patients who smoke during their hospitalization following cystectomy for bladder cancer, representing a gap in quality urologic oncology care and a missed opportunity to effectively intervene with evidence-based treatment.

PURPOSE:Quitting smoking improves patients' clinical outcomes, yet smoking is not commonly addressed as part of cancer care. The Cancer Center Cessation Initiative (C3I) supports National Cancer Institute-designated cancer centers to integrate tobacco treatment programs (TTPs) into routine cancer care. C3I centers vary in size, implementation strategies used, and treatment approaches. We examined associations of these contextual factors with treatment reach and smoking cessation effectiveness. METHODS:This cross-sectional study used survey data from 28 C3I centers that reported tobacco treatment data during the first 6 months of 2021. Primary outcomes of interest were treatment reach (reach)-the proportion of patients identified as currently smoking who received at least one evidence-based tobacco treatment component (eg, counseling and pharmacotherapy)-and smoking cessation effectiveness (effectiveness)-the proportion of patients reporting 7-day point prevalence abstinence at 6-month follow-up. Center-level differences in reach and effectiveness were examined by center characteristics, implementation strategies, and tobacco treatment components. RESULTS:Of the total 692,662 unique patients seen, 44,437 reported current smoking. Across centers, a median of 96% of patients were screened for tobacco use, median smoking prevalence was 7.4%, median reach was 15.4%, and median effectiveness was 18.4%. Center-level characteristics associated with higher reach included higher smoking prevalence, use of center-wide TTP, and lower patient-to-tobacco treatment specialist ratio. Higher effectiveness was observed at centers that served a larger overall population and population of patients who smoke, reported a higher smoking prevalence, and/or offered electronic health record referrals via a closed-loop system. CONCLUSION:Whole-center TTP implementation among inpatients and outpatients, and increasing staff-to-patient ratios may improve TTP reach. Designating personnel with tobacco treatment expertise and resources to increase tobacco treatment dose or intensity may improve smoking cessation effectiveness.

The health and safety of using e-cigarette products (vaping) have been challenging to assess and further regulate due to their complexity. Inhaled e-cigarette aerosols contain chemicals with under-recognized toxicological profiles, which could influence endogenous processes once inhaled. We urgently need more understanding on the metabolic effects of e-cigarette exposure and how they compare to combustible cigarettes. To date, the metabolic landscape of inhaled e-cigarette aerosols, including chemicals originated from vaping and perturbed endogenous metabolites in vapers, is poorly characterized. To better understand the metabolic landscape and potential health consequences of vaping, we applied liquid chromatography-mass spectrometry (LC-MS) based nontargeted metabolomics to analyze compounds in the urine of vapers, cigarette smokers, and nonusers. Urine from vapers (n = 34), smokers (n = 38), and nonusers (n = 45) was collected for verified LC-HRMS nontargeted chemical analysis. The altered features (839, 396, and 426 when compared smoker and control, vaper and control, and smoker and vaper, respectively) among exposure groups were deciphered for their structural identities, chemical similarities, and biochemical relationships. Chemicals originating from e-cigarettes and altered endogenous metabolites were characterized. There were similar levels of nicotine biomarkers of exposure among vapers and smokers. Vapers had higher urinary levels of diethyl phthalate and flavoring agents (e.g., delta-decalactone). The metabolic profiles featured clusters of acylcarnitines and fatty acid derivatives. More consistent trends of elevated acylcarnitines and acylglycines in vapers were observed, which may suggest higher lipid peroxidation. Our approach in monitoring shifts of the urinary chemical landscape captured distinctive alterations resulting from vaping. Our results suggest similar nicotine metabolites in vapers and cigarette smokers. Acylcarnitines are biomarkers of inflammatory status and fatty acid oxidation, which were dysregulated in vapers. With higher lipid peroxidation, radical-forming flavoring, and higher level of specific nitrosamine, we observed a trend of elevated cancer-related biomarkers in vapers as well. Together, these data present a comprehensive profiling of urinary biochemicals that were dysregulated due to vaping.

INTRODUCTION/BACKGROUND:Differences in public awareness and uptake of genetic testing among patients with inheritable cancers are not well understood. The purpose of this study is to examine self-reported rates of undergoing cancer-specific genetic testing in patients with breast/ovarian cancer vs prostate cancer from a nationally representative sample of U.S. PATIENTS/METHODS:Secondary objectives include examining sources of genetic testing information and perceptions of genetic testing for both patient populations as well as the general public. METHODS:testing was used to compare differences among categorical variables. RESULTS:= .003). Health care professionals were the most common source of genetic testing information for patients with breast/ovarian cancer whereas the Internet was the most common source for patients with prostate cancer. CONCLUSIONS:Our results suggest a lack of awareness and limited utilization of genetic testing among patients with prostate cancer relative to breast/ovarian cancer. Patients with prostate cancer cite the Internet and social media as sources of information, which may be an avenue for more optimal dissemination of evidence-based information.

PURPOSE/OBJECTIVE:Timely and appropriate discharge placement for patients who have undergone radical cystectomy (RC) remains challenging. Our objective was to improve the discharge planning process by creating a machine learning model that helps to predict the need for non-home hospital discharge to a higher level of care. MATERIALS AND METHODS/METHODS:Patients undergoing elective radical cystectomy for bladder cancer from 2014-2019 were identified in the ACS-NSQIP database. A gradient boosted decision tree was trained on selected predischarge variables to predict discharge location, dichotomized into home and non-home. We used threshold-moving to calibrate model predictions and evaluated model performance on a testing set using receiver operating characteristic and precision recall curves. Model performance was further examined in subgroups of interest. RESULTS AND CONCLUSIONS/CONCLUSIONS:A total of 11,881 patients met inclusion criteria with a mean age of 68.6 years. 10.6% of patients undergoing RC had non-home discharges. Our model predicting non-home discharge achieved an area under the receiver operating characteristic curve of 0.80 and an average precision of 0.33. After threshold-moving, our model had a recall of 0.757 and a precision of 0.211. Top variables by importance were septic shock occurrence, ventilator-use greater than 48 hours, organ space surgical site infection and unplanned intubation. Our model shows strong performance in identifying patients who required non-home discharge to higher levels of care, outperforming commonly used clinical indices and prior work. Modern machine learning techniques may be applied to support more timely and appropriate clinical decision making.

BACKGROUND:Tobacco cessation, at the time of cancer diagnosis, has been associated with better oncologic outcomes. Cancer diagnosis has been shown to serves as a "teachable moment," inspiring tobacco cessation. However, the sustainability of abstinence from smoking is understudied. Similarly, there is a paucity of data regarding the utility of behavioral/pharmacologic intervention to support continued smoking cessation. METHODS:A systematic literature review was conducted in August 2021 with no date limits. Relevant studies that reported tobacco smoking relapse rates for patients who quit at the time of cancer diagnosis were included. Our literature search identified 1620 articles and 29 met inclusion criteria. The primary endpoint of the study was smoking relapse rate. Secondary outcome was a descriptive assessment of behavioral and pharmacologic interventions to promote continued cessation. Exploratory outcomes included a regression analysis to examine associations between study factors and relapse rates. RESULTS:There were 3021 smokers who quit at the time of cancer diagnosis. Weighted overall relapse rate for the study population was 44 % (range 5-57 %). Interventions to support smoking cessation were employed in 17 of the 29 included studies and protocols were heterogenous, including behavioral, pharmacologic, or mixed intervention strategies. Exploratory analysis demonstrated no association between relapse rates and publication year, gender, or study type. Relapse rates were indirectly associated with age (p = .003), suggesting that younger patients were more likely to relapse. CONCLUSION/CONCLUSIONS:The sustainability of smoking cessation after a cancer diagnosis is understudied, and existing literature is difficult to interpret due to heterogeneity. Relapse rates remain significant and, although many studies have included the employment of an intervention to promote continued cessation, few studies have measured the effect of a protocolized intervention to support abstinence.

INTRODUCTION/BACKGROUND:Given the increasing interest in partial gland cryo-ablation as a treatment modality and the lack of data surrounding urinary and sexual outcomes after the procedure, the goal of this analysis was to assess functional outcomes following partial gland cryo-ablation (PGCA) stratified according to baseline severity of lower urinary tract symptoms (LUTS) and erectile function (EF). A secondary goal was to also determine if there were any clinical factors associated with significant change in LUTS and EF. MATERIALS AND METHODS/METHODS:Since 3/2017, all men undergoing primary PGCA were offered enrollment into an IRB-approved prospective outcomes registry. Men were given International Prostate Symptom Score (IPSS) and Sexual Health Inventory for Men (SHIM) surveys prior to and 6 months post treatment. Differences in IPSS and SHIM scores are described, and factors associated with clinically significant change were assessed using univariate and multivariate analysis. RESULTS:A total of 100 men completed 6 month follow up. The mean IPSS for the overall cohort decreased 2.1 units (p > 0.05). The mean changes in IPSS for men with baseline mild, moderate, and severe LUTS were 0.9 (p = 0.06), -4.2 (p = 0.001), and -11.1(p = 0.001) units, respectively. The mean changes in the SHIM score for all men were - 5.1 units (p = 0.001). The mean changes in SHIM score for baseline none, mild/mild-to-moderate, moderate-severe ED were -7.6 (p = 0.001), -6.5 (p = 0.001) and -1.1 units (p = 0.27), respectively. No variables of interest were significantly associated with changes in IPSS or SHIM scores. CONCLUSION/CONCLUSIONS:Stratifying functional outcomes according to baseline IPSS and SHIM is imperative to assess the true impact of PGCA on functional outcomes.

To identify biomarkers of exposure present in Heated Tobacco Products (HTPs) users' urine which are associated with bladder cancer and to compare quantitative biomarker levels to those seen in combustible cigarette users. A systematic literature review was conducted in December 2020 with no date limits. Relevant studies that reported quantitative urinary biomarker of exposure in HTP users were included. Biomarkers and their parent compounds were classified by carcinogenicity according to the International Agency for Research on Cancer Monographs and were cross-referenced with the Collaborative on Health and the Environment Toxicant and Disease Database to determine associations with bladder cancer. Our literature search identified 561 articles and 30 clinical trial reports. 11 studies met inclusion criteria. These studies identified 29 biomarkers of exposure present in HTP users' urine, which reflect exposure to 21 unique parent compounds. Of these parent compounds, 14 are carcinogens and 10 have a known link to bladder cancer. HTP users' biomarkers of exposure were present at lower levels than combustible cigarette users but higher than never-smokers. Biomarkers of exposure to bladder carcinogens are present in the urine of HTP users. While levels of these biomarkers appear to be lower than combustible cigarette users, chronic urothelial exposure to bladder carcinogens is concerning and degree of bladder cancer risk remains unknown. Further long-term study is needed to elucidate the bladder cancer risk of HTP use.

BACKGROUND:The quality of prostate cancer (PCa) content on Instagram is unknown. METHODS:We examined 62 still-images and 64 video Instagram posts using #prostatecancer on 5/18/20. Results were assessed with validated tools. RESULTS:Most content focused on raising awareness or sharing patient stories (46%); only 9% was created by physicians. 90% of content was low-to-moderate quality and most was understandable, but actionability was 0%. Of the 30% of content including objective information, 40% contained significant misinformation. Most posts had comments offering social support. CONCLUSIONS:Instagram is a source of understandable PCa content and social support; however, information was poorly actionable and had some misinformation.