Is there an association between a history of military service and cancer diagnosis? Results from a US national-level study of self-reported outcomes.

PURPOSE: To examine cancer prevalence in men with and without military service history, using national-level self-reported outcomes. METHODS: A cross-sectional survey-based US study, including men aged 18 and above from the Health Information National Trends Survey database between 2011 and 2014. The primary endpoint was self-reported cancer prevalence. Multivariable logistic regression analyses assessed the association of various covariates with the prevalence of cancer. RESULTS: A total of 4,527 men were analyzed, with 1,352 (29.9%) reporting a history of military service. Compared to men with no military service history, men with a military service history were older (median of 65 [IQR 56, 74] vs. 53 [IQR 41, 62] years, p < 0.0001), more commonly Caucasian (71.4% vs. 61.4%, p < 0.0001), born in the US (95.6% vs. 79.5%, p < 0.0001), attained higher education level and annual household income (p < 0.0001), and consisted of more smokers(58.3% vs. 44.5%, p < 0.0001). The age-adjusted comparison demonstrated a higher cancer prevalence in men with military service history (20.5% vs. 7.6%, p < 0.0001). Specifically, genitourinary, dermatological, gastrointestinal, and hematological cancers were generally more prevalent. Adjusting for all available confounders, multivariable models showed that military service history was associated with 1.56 (95% CI 1.20-2.03), and 1.57 (95% CI 1.07-2.31) increased odds of having any cancer, and specifically genitourinary cancer, respectively. CONCLUSIONS: Further research is needed to ascertain whether the association between military service and increased cancer diagnosis results from better screening programs or increased exposure to risk factors during military service.

Twitter and academic Urology in the United States and Canada: a comprehensive assessment of the Twitterverse in 2019.

OBJECTIVE: To provide the first comprehensive analysis of the Twitterverse amongst academic urologists and programmes in North America. METHODS: Using national accreditation and individual programme websites, all active urology residency programmes (USA and Canada) and academic Urology faculty at these programmes were identified. Demographic data for each programme American Urological Association [AUA] section, resident class size) and physician (title, fellowship training, Scopus Hirsch index [H-index] and citations) were documented. Twitter metrics (Twitter handle, date joined, # tweets, # followers, # following, likes) for programmes and physicians were catalogued (data capture: March-April 2019). Descriptive analyses and temporal trends in Twitter utilisation amongst programmes and physicians were assessed. Multivariable logistic regression was used to identify predictors of Twitter use. RESULTS: In all, 156 academic programmes (143 USA, 13 Canada) and 2214 academic faculty (2015 USA, 199 Canada) were identified. Twitter utilisation is currently 49.3% and 34.1% amongst programmes and physicians, respectively, and continues to increase. On multivariable analysis, programmes with 3-5 residents/year and programmes with a higher percentage of faculty Twitter engagement were more likely to have Twitter accounts. From a physician perspective, those with fellowship training, lower academic rank (Clinical Instructor, Assistant Professor, Associate Professor vs Professor) and higher H-indices were more likely to have individual Twitter accounts. CONCLUSION: There is a steady increase in Twitter engagement amongst Urology programmes and academic physicians. Faculty Twitter utilisation is an important driver of programme Twitter engagement. Twitter social media activity is strongly associated with academic productivity, and may in fact drive academic metrics. Within Urology, social media presence appears to be proportional to academic activity.

Setting the Standards: Examining Research Productivity Among Academic Urologists in the USA and Canada in 2019.

BACKGROUND: Research productivity among academic urologists is strongly encouraged, but little data are available on productivity metrics within the field. OBJECTIVE: To provide the first comprehensive survey of research productivity among academic urologists in the USA and Canada. DESIGN, SETTING, AND PARTICIPANTS: Using the Accreditation Council for Graduate Medical Education, the Canadian Resident Matching Service, and individual program websites, all active accredited urology faculties were identified. For each individual, we collected data on American Urological Association section, title, gender, fellowship training, Scopus H-index, and citations. Comprehensive searches were completed during March-May 2019. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Descriptive statistics for demographic comparisons were performed using analysis of variance for continuous variables and chi-square test for categorical variables. Multivariable logistic regressions were used to identify the predictors of H-index greater than the median. RESULTS AND LIMITATIONS: A total of 2214 academic urology faculties (2015 in USA and 199 in Canada) were identified. The median and mean H-indices for the entire cohort of physicians were 11 and 16.1, respectively. On multivariable analysis, physicians in the North Central and Western Sections (vs mid-Atlantic), who were fellowship trained (vs no fellowship training), and of higher academic rank (professor and associate professor vs clinical instructor) were more likely to have H-index values greater than the median. Additionally, female physicians (vs male) were more likely to have H-index values less than the median. CONCLUSIONS: This study represents the first comprehensive assessment of research productivity metrics among academic urologists. These represent key benchmarks for trainees considering careers in academics and for practicing physicians gauging their own productivity in relation to their peers. PATIENT SUMMARY: In this study, we provide the first comprehensive assessment of research productivity among academic urologists in the USA and Canada. Our results help provide key benchmarks for trainees considering careers in academics and for practicing physicians gauging their own productivity in relation to peers.

Clinical-genomic Characterization Unveils More Aggressive Disease Features in Elderly Prostate Cancer Patients with Low-grade Disease.

BACKGROUND: Over 20% of men diagnosed with prostate cancer (PC) are ≥75 yr old. More objective disease-specific indices for predicting outcomes beyond chronological age are necessary. OBJECTIVE: To analyze age-related differences in clinical-genomic prognostic features of aggressiveness in localized PC. DESIGN, SETTING, AND PARTICIPANTS: A retrospective multicenter cross-sectional study reported the use of the Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK) guidelines. Clinical-genomic data of patients who underwent a prostate biopsy or radical prostatectomy (RP) were obtained from the Decipher Genomic Resource Information Database (NCT02609269). INTERVENTION: Our analyses focused on the 22-gene Decipher genomic classifier (GC) and 50-gene (PAM50) models in the biopsy and RP cohorts stratified by age. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The primary endpoint was the impact of age on GC scores and PAM50 molecular subtypes. Prognostic indices including Decipher GC scores, PAM50 molecular subtypes, National Comprehensive Cancer Network risk categories, and ISUP grade groups (IGGs) were stratified by age using multivariable logistic regression analyses. RESULTS AND LIMITATIONS: Within histological low-risk IGGs, there were a higher proportion of patients with high-risk Decipher biopsy scores with age (age <60 yr: 10.1% IGG 1 and 29.9% IGG 2 vs age ≥80 yr: 22% IGG 1 and 37.7% IGG 2). The prevalence of the adverse phenotype luminal B (PAM50-defined) increased with age (age <60 yr: 22.7% and 40.2% vs age ≥80 yr: 29.7% and 49.1%, in patients with IGG 1 and IGG 2, respectively). In IGGs 3-5, no age differences were observed. Multivariable models demonstrated that each age decile entailed a 19% (odds ratio [OR] 1.19, 95% confidence interval [CI] 1.10-1.29, p < 0.001) and a 10% (OR 1.1, 95% CI 1.05-1.16) increased probability for a high-risk Decipher biopsy and RP score, respectively. Aside from an obvious selection bias, data on race, family history, prostate volume, and long-term follow-up outcomes were unavailable. CONCLUSIONS: These data demonstrated that elderly men with favorable pathology (IGG 1-2), might harbor more aggressive disease than younger patients based on validated GC scores. PATIENT SUMMARY: The presented clinical-genomic data demonstrate that elderly patients with low-risk prostate cancer might harbor more aggressive disease than their younger counterparts. This suggests that standard well-accepted paradigm of elderly prostate cancer patients not being aggressively treated, based solely on their chronological age, might need to be reconsidered.