Effect of Health Service Area on Primary Care Physician Provision of Low-Value Cancer Screening.

BACKGROUND: Using a health systems approach to investigate low-value care (LVC) may provide insights into structural drivers of this pervasive problem. OBJECTIVE: To evaluate the influence of service area practice patterns on low-value mammography and prostate-specific antigen (PSA) testing. DESIGN: Retrospective study analyzing LVC rates between 2008 and 2018, leveraging physician relocation in 3-year intervals of matched physician and patient groups. SETTING: U.S. Medicare claims data. PARTICIPANTS: 8254 physicians and 56 467 patients aged 75 years or older. MEASUREMENTS: LVC rates for physicians staying in their original service area and those relocating to new areas. RESULTS: Physicians relocating from higher-LVC areas to low-LVC areas were more likely to provide lower rates of LVC. For mammography, physicians staying in high-LVC areas (LVC rate, 10.1% [95% CI, 8.8% to 12.2%]) or medium-LVC areas (LVC rate, 10.3% [CI, 9.0% to 12.4%]) provided LVC at a higher rate than physicians relocating from those areas to low-LVC areas (LVC rates, 6.0% [CI, 4.4% to 7.5%] [difference, -4.1 percentage points {CI, -6.7 to -2.3 percentage points}] and 5.9% [CI, 4.6% to 7.8%] [difference, -4.4 percentage points {CI, -6.7 to -2.4 percentage points}], respectively). For PSA testing, physicians staying in high- or moderate-LVC service areas provided LVC at a rate of 17.5% (CI, 14.9% to 20.7%) or 10.6% (CI, 9.6% to 13.2%), respectively, compared with those relocating from those areas to low-LVC areas (LVC rates, 9.9% [CI, 7.5% to 13.2%] [difference, -7.6 percentage points {CI, -10.9 to -3.8 percentage points}] and 6.2% [CI, 3.5% to 9.8%] [difference, -4.4 percentage points {CI, -7.6 to -2.2 percentage points}], respectively). Physicians relocating from lower- to higher-LVC service areas were not more likely to provide LVC at a higher rate. LIMITATION: Use of retrospective observational data, possible unmeasured confounding, and potential for relocating physicians to practice differently from those who stay. CONCLUSION: Physicians relocating to service areas with lower rates of LVC provided less LVC than physicians who stayed in areas with higher rates of LVC. Systemic structures may contribute to LVC. Understanding which factors are contributing may present opportunities for policy and interventions to broadly improve care. PRIMARY FUNDING SOURCE: National Cancer Institute of the National Institutes of Health.

Urban relatives ameliorate survival disparities for genitourinary cancer in rural patients.

INTRODUCTION: Patients living in rural areas have worse cancer-specific outcomes. This study examines the effect of family-based social capital on genitourinary cancer survival. We hypothesized that rural patients with urban relatives have improved survival relative to rural patients without urban family. METHODS: We examined rural and urban based Utah individuals diagnosed with genitourinary cancers between 1968 and 2018. Familial networks were determined using the Utah Population Database. Patients and relatives were classified as rural or urban based on 2010 rural-urban commuting area codes. Overall survival was analyzed using Cox proportional hazards models. RESULTS: We identified 24,746 patients with genitourinary cancer with a median follow-up of 8.72 years. Rural cancer patients without an urban relative had the worst outcomes with cancer-specific survival hazard ratios (HRs) at 5 and 10 years of 1.33 (95% CI 1.10-1.62) and 1.46 (95% CI 1.24-1.73), respectively relative to urban patients. Rural patients with urban first-degree relatives had improved survival with 5- and 10-year survival HRs of 1.21 (95% CI 1.06-1.40) and 1.16 (95% CI 1.03-1.31), respectively. CONCLUSIONS: Our findings suggest rural patients who have been diagnosed with a genitourinary cancer have improved survival when having relatives in urban centers relative to rural patients without urban relatives. Further research is needed to better understand the mechanisms through which having an urban family member contributes to improved cancer outcomes for rural patients. Better characterization of this affect may help inform policies to reduce urban-rural cancer disparities.

Describing patterns of familial cancer risk in subfertile men using population pedigree data.

STUDY QUESTION: Can we simultaneously assess risk for multiple cancers to identify familial multicancer patterns in families of azoospermic and severely oligozoospermic men? SUMMARY ANSWER: Distinct familial cancer patterns were observed in the azoospermia and severe oligozoospermia cohorts, suggesting heterogeneity in familial cancer risk by both type of subfertility and within subfertility type. WHAT IS KNOWN ALREADY: Subfertile men and their relatives show increased risk for certain cancers including testicular, thyroid, and pediatric. STUDY DESIGN, SIZE, DURATION: A retrospective cohort of subfertile men (N = 786) was identified and matched to fertile population controls (N = 5674). Family members out to third-degree relatives were identified for both subfertile men and fertile population controls (N = 337 754). The study period was 1966-2017. Individuals were censored at death or loss to follow-up, loss to follow-up occurred if they left Utah during the study period. PARTICIPANTS/MATERIALS, SETTING, METHODS: Azoospermic (0 × 106/mL) and severely oligozoospermic (<1.5 × 106/mL) men were identified in the Subfertility Health and Assisted Reproduction and the Environment cohort (SHARE). Subfertile men were age- and sex-matched 5:1 to fertile population controls and family members out to third-degree relatives were identified using the Utah Population Database (UPDB). Cancer diagnoses were identified through the Utah Cancer Registry. Families containing ≥10 members with ≥1 year of follow-up 1966-2017 were included (azoospermic: N = 426 families, 21 361 individuals; oligozoospermic: N = 360 families, 18 818 individuals). Unsupervised clustering based on standardized incidence ratios for 34 cancer phenotypes in the families was used to identify familial multicancer patterns; azoospermia and severe oligospermia families were assessed separately. MAIN RESULTS AND THE ROLE OF CHANCE: Compared to control families, significant increases in cancer risks were observed in the azoospermia cohort for five cancer types: bone and joint cancers hazard ratio (HR) = 2.56 (95% CI = 1.48-4.42), soft tissue cancers HR = 1.56 (95% CI = 1.01-2.39), uterine cancers HR = 1.27 (95% CI = 1.03-1.56), Hodgkin lymphomas HR = 1.60 (95% CI = 1.07-2.39), and thyroid cancer HR = 1.54 (95% CI = 1.21-1.97). Among severe oligozoospermia families, increased risk was seen for three cancer types: colon cancer HR = 1.16 (95% CI = 1.01-1.32), bone and joint cancers HR = 2.43 (95% CI = 1.30-4.54), and testis cancer HR = 2.34 (95% CI = 1.60-3.42) along with a significant decrease in esophageal cancer risk HR = 0.39 (95% CI = 0.16-0.97). Thirteen clusters of familial multicancer patterns were identified in families of azoospermic men, 66% of families in the azoospermia cohort showed population-level cancer risks, however, the remaining 12 clusters showed elevated risk for 2-7 cancer types. Several of the clusters with elevated cancer risks also showed increased odds of cancer diagnoses at young ages with six clusters showing increased odds of adolescent and young adult (AYA) diagnosis [odds ratio (OR) = 1.96-2.88] and two clusters showing increased odds of pediatric cancer diagnosis (OR = 3.64-12.63). Within the severe oligozoospermia cohort, 12 distinct familial multicancer clusters were identified. All 12 clusters showed elevated risk for 1-3 cancer types. An increase in odds of cancer diagnoses at young ages was also seen in five of the severe oligozoospermia familial multicancer clusters, three clusters showed increased odds of AYA diagnosis (OR = 2.19-2.78) with an additional two clusters showing increased odds of a pediatric diagnosis (OR = 3.84-9.32). LIMITATIONS, REASONS FOR CAUTION: Although this study has many strengths, including population data for family structure, cancer diagnoses and subfertility, there are limitations. First, semen measures are not available for the sample of fertile men. Second, there is no information on medical comorbidities or lifestyle risk factors such as smoking status, BMI, or environmental exposures. Third, all of the subfertile men included in this study were seen at a fertility clinic for evaluation. These men were therefore a subset of the overall population experiencing fertility problems and likely represent those with the socioeconomic means for evaluation by a physician. WIDER IMPLICATIONS OF THE FINDINGS: This analysis leveraged unique population-level data resources, SHARE and the UPDB, to describe novel multicancer clusters among the families of azoospermic and severely oligozoospermic men. Distinct overall multicancer risk and familial multicancer patterns were observed in the azoospermia and severe oligozoospermia cohorts, suggesting heterogeneity in cancer risk by type of subfertility and within subfertility type. Describing families with similar cancer risk patterns provides a new avenue to increase homogeneity for focused gene discovery and environmental risk factor studies. Such discoveries will lead to more accurate risk predictions and improved counseling for patients and their families. STUDY FUNDING/COMPETING INTEREST(S): This work was funded by GEMS: Genomic approach to connecting Elevated germline Mutation rates with male infertility and Somatic health (Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD): R01 HD106112). The authors have no conflicts of interest relevant to this work. TRIAL REGISTRATION NUMBER: N/A.

Evaluating county-level lung cancer incidence from environmental radiation exposure, PM2.5, and other exposures with regression and machine learning models.

Characterizing the interplay between exposures shaping the human exposome is vital for uncovering the etiology of complex diseases. For example, cancer risk is modified by a range of multifactorial external environmental exposures. Environmental, socioeconomic, and lifestyle factors all shape lung cancer risk. However, epidemiological studies of radon aimed at identifying populations at high risk for lung cancer often fail to consider multiple exposures simultaneously. For example, moderating factors, such as PM2.5, may affect the transport of radon progeny to lung tissue. This ecological analysis leveraged a population-level dataset from the National Cancer Institute's Surveillance, Epidemiology, and End-Results data (2013-17) to simultaneously investigate the effect of multiple sources of low-dose radiation (gross [Formula: see text] activity and indoor radon) and PM2.5 on lung cancer incidence rates in the USA. County-level factors (environmental, sociodemographic, lifestyle) were controlled for, and Poisson regression and random forest models were used to assess the association between radon exposure and lung and bronchus cancer incidence rates. Tree-based machine learning (ML) method perform better than traditional regression: Poisson regression: 6.29/7.13 (mean absolute percentage error, MAPE), 12.70/12.77 (root mean square error, RMSE); Poisson random forest regression: 1.22/1.16 (MAPE), 8.01/8.15 (RMSE). The effect of PM2.5 increased with the concentration of environmental radon, thereby confirming findings from previous studies that investigated the possible synergistic effect of radon and PM2.5 on health outcomes. In summary, the results demonstrated (1) a need to consider multiple environmental exposures when assessing radon exposure's association with lung cancer risk, thereby highlighting (1) the importance of an exposomics framework and (2) that employing ML models may capture the complex interplay between environmental exposures and health, as in the case of indoor radon exposure and lung cancer incidence.

Path-BigBird: An AI-Driven Transformer Approach to Classification of Cancer Pathology Reports.

PURPOSE: Surgical pathology reports are critical for cancer diagnosis and management. To accurately extract information about tumor characteristics from pathology reports in near real time, we explore the impact of using domain-specific transformer models that understand cancer pathology reports. METHODS: We built a pathology transformer model, Path-BigBird, by using 2.7 million pathology reports from six SEER cancer registries. We then compare different variations of Path-BigBird with two less computationally intensive methods: Hierarchical Self-Attention Network (HiSAN) classification model and an off-the-shelf clinical transformer model (Clinical BigBird). We use five pathology information extraction tasks for evaluation: site, subsite, laterality, histology, and behavior. Model performance is evaluated by using macro and micro F1 scores. RESULTS: We found that Path-BigBird and Clinical BigBird outperformed the HiSAN in all tasks. Clinical BigBird performed better on the site and laterality tasks. Versions of the Path-BigBird model performed best on the two most difficult tasks: subsite (micro F1 score of 72.53, macro F1 score of 35.76) and histology (micro F1 score of 80.96, macro F1 score of 37.94). The largest performance gains over the HiSAN model were for histology, for which a Path-BigBird model increased the micro F1 score by 1.44 points and the macro F1 score by 3.55 points. Overall, the results suggest that a Path-BigBird model with a vocabulary derived from well-curated and deidentified data is the best-performing model. CONCLUSION: The Path-BigBird pathology transformer model improves automated information extraction from pathology reports. Although Path-BigBird outperforms Clinical BigBird and HiSAN, these less computationally expensive models still have utility when resources are constrained.

Attention Mechanisms in Clinical Text Classification: A Comparative Evaluation.

Attention mechanisms are now a mainstay architecture in neural networks and improve the performance of biomedical text classification tasks. In particular, models that perform automated medical encoding of clinical documents make extensive use of the label-wise attention mechanism. A label-wise attention mechanism increases a model's discriminatory ability by using label-specific reference information. This information can either be implicitly learned during training or explicitly provided through embedded textual code descriptions or information on the code hierarchy; however, contemporary studies arbitrarily select the type of label-specific reference information. To address this shortcoming, we evaluated label-wise attention initialized with either implicit or explicit label-specific reference information against two common baseline methods-target-attention and text-encoder architecture-specific methods-to generate document embeddings across four text-encoder architectures-a convolutional neural network, two recurrent neural networks, and a transformer. We also present an extension of label-wise attention that can embed the information on the code hierarchy. We performed our experiments on the MIMIC III dataset, which is a standard dataset in the clinical text classification domain. Our experiments showed that using pretrained reference information and the hierarchical design helped improve classification performance. These performance improvements had less impact on larger datasets and label spaces across all text-encoder architectures. In our analysis, we used an attention mechanism's energy scores to explain the perceived differences in performance and interpretability between the text-encoder architectures and types of label-attention.

Low-Value Prostate Cancer Screening Among Young Men With Private Insurance.

INTRODUCTION: No professional society guidelines recommend PSA screening in men younger than age 40; however, data suggest testing occurs at meaningful rates in this age group. The purpose of this study was to identify the rate of PSA testing in men under 40. METHODS: This is a population-based, retrospective cohort study from 2008 to 2017. Using the MarketScan database, rates of testing for the sum of the annual population of men at risk were evaluated. Descriptive statistics and statistical analyses were performed in men continuously enrolled in the database for at least 5 year. Results were stratified by receipt of PSA testing and by age group. The association of diagnoses and Charlson Comorbidity Index with receipt of PSA test was evaluated using multivariable logistic regression models. RESULTS: We identified 3,230,748 men ages 18 to 39 who were enrolled for at least 5 years. The rate of ever receiving PSA testing was 0.6%, 1.7%, 8.5%, and 9.1% in men less than 25, 25 to 29, 30 to 34, and 35 to 39 years, respectively. Multivariable logistic regression showed that relative to all men 18 to 39, patients who received PSA testing had higher odds of a diagnosis of hypogonadism (OR 11.77) or lower urinary tract symptoms (OR 4.19). CONCLUSIONS: This study found a remarkable number of young men receive PSA testing, with a strong association with diagnoses of lower urinary tract symptoms and hypogonadism. Clinicians need to be educated that assessment and management guidelines for other urologic diagnoses now defer PSA testing to prostate cancer screening guidelines.

Exploring the Spatial Patterning of Sociodemographic Disparities in Extreme Heat Exposure at Multiple Scales Across the Conterminous United States.

Climate change has led to an increase in heat-related morbidity and mortality. The impact of heat on health is unequally distributed amongst different socioeconomic and demographic groups. We use high-resolution daily air temperature-based heat wave intensity (HWI) and neighborhood-scale sociodemographic information from the conterminous United States to evaluate the spatial patterning of extreme heat exposure disparities. Assuming differences in spatial patterns at national, regional, and local scales; we assess disparities in heat exposure across race, housing characteristics, and poverty level. Our findings indicate small differences in HWI based on these factors at the national level, with the magnitude and direction of the differences varying by region. The starkest differences are present over the Northeast and Midwest, where primarily Black neighborhoods are exposed to higher HWI than predominantly White areas. At the local level, we find the largest difference by socioeconomic status. We also find that residents of nontraditional housing are more vulnerable to heat exposure. Previous studies have either evaluated such disparities for specific cities and/or used a satellite-based land surface temperature, which, although correlated with air temperature, does not provide the true measure of heat exposure. This study is the first of its kind to incorporate high-resolution gridded air temperature-based heat exposure in the evaluation of sociodemographic disparities at a national scale. The analysis suggests the unequal distribution of heat wave intensities across communities-with higher heat exposures characterizing areas with high proportions of minorities, low socioeconomic status, and homes in need of retrofitting to combat climate change.

Disparities and determinants of place of death: Insights from the Utah Population Database.

To better understand determinants and potential disparities in end of life, we model decedents' place of death with explanatory variables describing familial, social, and economic resources. A retrospective cohort of 204,041 decedents and their family members are drawn from the Utah Population Database family caregiving dataset. Using multinomial regression, we model place of death, categorized as at home, in a hospital, in another location, or unknown. The model includes family relationship variables, sex, race and ethnicity, and a socioeconomic status score, with control variables for age at death and death year. We identified the effect of a family network of multiple caregivers, with 3+ daughters decreasing odds of a hospital death by 17 percent (OR: 0.83 [0.79, 0.87], p < 0.001). Place of death also varies significantly by race and ethnicity, with most nonwhite groups more likely to die in a hospital. These determinants may contribute to disparities in end of life.

Familial Associations of Prevalence and Cause-Specific Mortality for Thoracic Aortic Disease and Bicuspid Aortic Valve in a Large-Population Database.

BACKGROUND: Thoracic aortic disease and bicuspid aortic valve (BAV) likely have a heritable component, but large population-based studies are lacking. This study characterizes familial associations of thoracic aortic disease and BAV, as well as cardiovascular and aortic-specific mortality, among relatives of these individuals in a large-population database. METHODS: In this observational case-control study of the Utah Population Database, we identified probands with a diagnosis of BAV, thoracic aortic aneurysm, or thoracic aortic dissection. Age- and sex-matched controls (10:1 ratio) were identified for each proband. First-degree relatives, second-degree relatives, and first cousins of probands and controls were identified through linked genealogical information. Cox proportional hazard models were used to quantify the familial associations for each diagnosis. We used a competing-risk model to determine the risk of cardiovascular-specific and aortic-specific mortality for relatives of probands. RESULTS: The study population included 3 812 588 unique individuals. Familial hazard risk of a concordant diagnosis was elevated in the following populations compared with controls: first-degree relatives of patients with BAV (hazard ratio [HR], 6.88 [95% CI, 5.62-8.43]); first-degree relatives of patients with thoracic aortic aneurysm (HR, 5.09 [95% CI, 3.80-6.82]); and first-degree relatives of patients with thoracic aortic dissection (HR, 4.15 [95% CI, 3.25-5.31]). In addition, the risk of aortic dissection was higher in first-degree relatives of patients with BAV (HR, 3.63 [95% CI, 2.68-4.91]) and in first-degree relatives of patients with thoracic aneurysm (HR, 3.89 [95% CI, 2.93-5.18]) compared with controls. Dissection risk was highest in first-degree relatives of patients who carried a diagnosis of both BAV and aneurysm (HR, 6.13 [95% CI, 2.82-13.33]). First-degree relatives of patients with BAV, thoracic aneurysm, or aortic dissection had a higher risk of aortic-specific mortality (HR, 2.83 [95% CI, 2.44-3.29]) compared with controls. CONCLUSIONS: Our results indicate that BAV and thoracic aortic disease carry a significant familial association for concordant disease and aortic dissection. The pattern of familiality is consistent with a genetic cause of disease. Furthermore, we observed higher risk of aortic-specific mortality in relatives of individuals with these diagnoses. This study provides supportive evidence for screening in relatives of patients with BAV, thoracic aneurysm, or dissection.

Generating Older Adult Multimorbidity Trajectories Using Various Comorbidity Indices and Calculation Methods.

Background and Objectives: Older adult multimorbidity trajectories are helpful for understanding the current and future health patterns of aging populations. The construction of multimorbidity trajectories from comorbidity index scores will help inform public health and clinical interventions targeting those individuals that are on unhealthy trajectories. Investigators have used many different techniques when creating multimorbidity trajectories in prior literature, and no standard way has emerged. This study compares and contrasts multimorbidity trajectories constructed from various methods. Research Design and Methods: We describe the difference between aging trajectories constructed with the Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI). We also explore the differences between acute (single-year) and chronic (cumulative) derivations of CCI and ECI scores. Social determinants of health can affect disease burden over time; thus, our models include income, race/ethnicity, and sex differences. Results: We use group-based trajectory modeling (GBTM) to estimate multimorbidity trajectories for 86,909 individuals aged 66-75 in 1992 using Medicare claims data collected over the following 21 years. We identify low-chronic disease and high-chronic disease trajectories in all 8 generated trajectory models. Additionally, all 8 models satisfied prior established statistical diagnostic criteria for well-performing GBTM models. Discussion and Implications: Clinicians may use these trajectories to identify patients on an unhealthy path and prompt a possible intervention that may shift the patient to a healthier trajectory.

Environmental exposure to industrial air pollution is associated with decreased male fertility.

OBJECTIVE: To understand how chronic exposure to industrial air pollution is associated with male fertility through semen parameters. DESIGN: Retrospective cohort study. PATIENTS: Men in the Subfertility, Health, and Assisted Reproduction cohort who underwent a semen analysis in the two largest healthcare systems in Utah from 2005-2017 with ≥1 measured semen parameter (N = 21,563). INTERVENTION(S): Residential histories for each man were constructed using locations from administrative records linked through the Utah Population Database. Industrial facilities with air emissions of nine endocrine-disrupting compound chemical classes were identified from the Environmental Protection Agency Risk-Screening Environmental Indicators microdata. Chemical levels were linked with residential histories for the 5 years before each semen analysis. MAIN OUTCOME MEASURES: Semen analyses were classified as azoospermic or oligozoospermic (< 15 M/mL) using World Health Organization cutoffs for concentration. Bulk semen parameters such as concentration, total count, ejaculate volume, total motility, total motile count, and total progressive motile count were also measured. Multivariable regression models with robust standard errors were used to associate exposure quartiles for each of the nine chemical classes with each semen parameter, adjusting for age, race, and ethnicity, as well as neighborhood socioeconomic disadvantage. RESULTS: After adjustment for demographic covariates, several chemical classes were associated with azoospermia and decreased total motility and volume. For exposure in the 4th relative to 1st quartile, significant associations were observed for acrylonitrile (ßtotal motility = -0.87 pp), aromatic hydrocarbons (odds ratio [OR]azoospermia = 1.53; ßvolume = -0.14 mL), dioxins (ORazoospermia = 1.31; ßvolume = -0.09 mL; ßtotal motility = -2.65 pp), heavy metals (ßtotal motility = -2.78pp), organic solvents (ORazoospermia = 1.75; ßvolume = -0.10 mL), organochlorines (ORazoospermia = 2.09; ßvolume = -0.12 mL), phthalates (ORazoospermia = 1.44; ßvolume = -0.09 mL; ßtotal motility = -1.21 pp), and silver particles (ORazoospermia = 1.64; ßvolume = -0.11 mL). All semen parameters significantly decreased with increasing socioeconomic disadvantage. Men who lived in the most disadvantaged areas had concentration, volume, and total motility of 6.70 M/mL, 0.13 mL, and 1.79 pp lower, respectively. Count, motile count, and total progressive motile count all decreased by 30-34 M. CONCLUSION(S): Several significant associations between chronic low-level environmental exposure to endocrine-disrupting compound air pollution from industrial sources and semen parameters were observed. The strongest associations were seen for increased odds of azoospermia and declines in total motility and volume. More research is needed to further explore additional social and exposure factors as well as expand on the risk posed to male reproductive health by the studied chemicals.

Risk Factors and Trends for HPV-Associated Subsequent Malignant Neoplasms among Adolescent and Young Adult Cancer Survivors.

BACKGROUND: Subsequent malignant neoplasms (SMN; new cancers that arise after an original diagnosis) contribute to premature mortality among adolescent and young adult (AYA) cancer survivors. Because of the high population prevalence of human papillomavirus (HPV) infection, we identify demographic and clinical risk factors for HPV-associated SMNs (HPV-SMN) among AYA cancer survivors in the SEER-9 registries diagnosed from 1976 to 2015. METHODS: Outcomes included any HPV-SMN, oropharyngeal-SMN, and cervical-SMN. Follow-up started 2 months after their original diagnosis. Standardized incidence ratios (SIR) compared risk between AYA survivors and general population. Age-period-cohort (APC) models examined trends over time. Fine and Gray's models identified therapy effects controlling for cancer and demographic confounders. RESULTS: Of 374,408 survivors, 1,369 had an HPV-SMN, occurring on average 5 years after first cancer. Compared with the general population, AYA survivors had 70% increased risk for any HPV-SMN [95% confidence interval (CI), 1.61-1.79] and 117% for oropharyngeal-SMN (95% CI, 2.00-2.35); cervical-SMN risk was generally lower in survivors (SIR, 0.85; 95% CI, 0.76-0.95), but Hispanic AYA survivors had a 8.4 significant increase in cervical-SMN (SIR, 1.46; 95% CI, 1.01-2.06). AYAs first diagnosed with Kaposi sarcoma, leukemia, Hodgkin, and non-Hodgkin lymphoma had increased HPV-SMN risks compared with the general population. Oropharyngeal-SMN incidence declined over time in APC models. Chemotherapy and radiation were associated with any HPV-SMN among survivors with first HPV-related cancers, but not associated among survivors whose first cancers were not HPV-related. CONCLUSIONS: HPV-SMN in AYA survivors are driven by oropharyngeal cancers despite temporal declines in oropharyngeal-SMN. Hispanic survivors are at risk for cervical-SMN relative to the general population. IMPACT: Encouraging HPV vaccination and cervical and oral cancer screenings may reduce HPV-SMN burden among AYA survivors.

A population-wide analysis of the familial risk of suicide in Utah, USA.

BACKGROUND: The degree to which suicide risk aggregates in US families is unknown. The authors aimed to determine the familial risk of suicide in Utah, and tested whether familial risk varies based on the characteristics of the suicides and their relatives. METHODS: A population-based sample of 12 160 suicides from 1904 to 2014 were identified from the Utah Population Database and matched 1:5 to controls based on sex and age using at-risk sampling. All first through third- and fifth-degree relatives of suicide probands and controls were identified (N = 13 480 122). The familial risk of suicide was estimated based on hazard ratios (HR) from an unsupervised Cox regression model in a unified framework. Moderation by sex of the proband or relative and age of the proband at time of suicide (<25 v. ⩾25 years) was examined. RESULTS: Significantly elevated HRs were observed in first- (HR 3.45; 95% CI 3.12-3.82) through fifth-degree relatives (HR 1.07; 95% CI 1.02-1.12) of suicide probands. Among first-degree relatives of female suicide probands, the HR of suicide was 6.99 (95% CI 3.99-12.25) in mothers, 6.39 in sisters (95% CI 3.78-10.82), and 5.65 (95% CI 3.38-9.44) in daughters. The HR in first-degree relatives of suicide probands under 25 years at death was 4.29 (95% CI 3.49-5.26). CONCLUSIONS: Elevated familial suicide risk in relatives of female and younger suicide probands suggests that there are unique risk groups to which prevention efforts should be directed - namely suicidal young adults and women with a strong family history of suicide.

Deep Transcriptome Profiling of Multiple Myeloma Using Quantitative Phenotypes.

BACKGROUND: Transcriptome studies are gaining momentum in genomic epidemiology, and the need to incorporate these data in multivariable models alongside other risk factors brings demands for new approaches. METHODS: Here we describe SPECTRA, an approach to derive quantitative variables that capture the intrinsic variation in gene expression of a tissue type. We applied the SPECTRA approach to bulk RNA sequencing from malignant cells (CD138+) in patients from the Multiple Myeloma Research Foundation CoMMpass study. RESULTS: A set of 39 spectra variables were derived to represent multiple myeloma cells. We used these variables in predictive modeling to determine spectra-based risk scores for overall survival, progression-free survival, and time to treatment failure. Risk scores added predictive value beyond known clinical and expression risk factors and replicated in an external dataset. Spectrum variable S5, a significant predictor for all three outcomes, showed pre-ranked gene set enrichment for the unfolded protein response, a mechanism targeted by proteasome inhibitors which are a common first line agent in multiple myeloma treatment. We further used the 39 spectra variables in descriptive modeling, with significant associations found with tumor cytogenetics, race, gender, and age at diagnosis; factors known to influence multiple myeloma incidence or progression. CONCLUSIONS: Quantitative variables from the SPECTRA approach can predict clinical outcomes in multiple myeloma and provide a new avenue for insight into tumor differences by demographic groups. IMPACT: The SPECTRA approach provides a set of quantitative phenotypes that deeply profile a tissue and allows for more comprehensive modeling of gene expression with other risk factors.

Barriers to and solutions for representative inclusion across the lifespan and in life course research: The need for structural competency highlighted by the COVID-19 pandemic.

Exclusion of special populations (older adults; pregnant women, children, and adolescents; individuals of lower socioeconomic status and/or who live in rural communities; people from racial and ethnic minority groups; individuals from sexual or gender minority groups; and individuals with disabilities) in research is a pervasive problem, despite efforts and policy changes by the National Institutes of Health and other organizations. These populations are adversely impacted by social determinants of health (SDOH) that reduce access and ability to participate in biomedical research. In March 2020, the Northwestern University Clinical and Translational Sciences Institute hosted the "Lifespan and Life Course Research: integrating strategies" "Un-Meeting" to discuss barriers and solutions to underrepresentation of special populations in biomedical research. The COVID-19 pandemic highlighted how exclusion of representative populations in research can increase health inequities. We applied findings of this meeting to perform a literature review of barriers and solutions to recruitment and retention of representative populations in research and to discuss how findings are important to research conducted during the ongoing COVID-19 pandemic. We highlight the role of SDOH, review barriers and solutions to underrepresentation, and discuss the importance of a structural competency framework to improve research participation and retention among special populations.

The Association Between Family History and Diverticulitis Recurrence: A Population-Based Study.

BACKGROUND: After initial nonoperative management of diverticulitis, individuals with a family history of diverticulitis may have increased risk of recurrent disease. OBJECTIVE: This study measured the association between family history and recurrent diverticulitis in a population-based cohort. DESIGN: This is a retrospective, population-based cohort study. SETTINGS: The cohort was identified from the Utah Population Database, a statewide resource linking hospital and genealogy records. PATIENTS: Individuals evaluated in an emergency department or hospitalized between 1998 and 2018 for nonoperatively managed diverticulitis were included. INTERVENTION: The primary predictor was a positive family history of diverticulitis, defined as diverticulitis in a first-, second-, or third-degree relative. MAIN OUTCOME MEASURES: This study measured the adjusted association between family history and the primary outcome of recurrent diverticulitis. A secondary outcome was elective surgery for diverticulitis. Additional analyses evaluated risk by degree of relation of the affected family member. RESULTS: The cohort included 4426 individuals followed for a median of 71 months. Median age was 64 years and 45% were male; 17% had complicated disease, 11% had recurrence, and 15% underwent elective surgery. After adjustment, individuals with a family history of diverticulitis had a similar risk of recurrence when compared to those without a family history (HR 1.0; 95% CI 0.8-1.2). However, individuals with a family history of diverticulitis were more likely to undergo elective surgery (HR 1.4; 95% CI 1.1-1.6). This effect was most pronounced in those with an affected first-degree family member (HR 1.7; 95% CI 1.4-2.2). LIMITATIONS: The use of state-specific data may limit generalizability. CONCLUSIONS: In this population-based analysis, individuals with a family history of diverticulitis were more likely to undergo elective surgery than those without a family history, despite similar risks of recurrence and complicated diverticulitis. Further work is necessary to understand the complex social, environmental, and genetic factors that influence diverticulitis treatment and outcomes. See Video Abstract at http://links.lww.com/DCR/B876 . ASOCIACIN ENTRE LOS ANTECEDENTES FAMILIARES Y LA RECURRENCIA DE LA DIVERTICULITIS UN ESTUDIO POBLACIONAL: ANTECEDENTES:Después del tratamiento inicial no quirúrgico de la diverticulitis, las personas con antecedentes familiares de diverticulitis pueden tener un mayor riesgo de enfermedad recurrente.OBJETIVO:Este estudio midió la asociación entre antecedentes familiares y diverticulitis recurrente en una cohorte poblacional.DISEÑO:Este es un estudio de cohorte retrospectivo de la población.ENTORNO CLÍNICO:La cohorte se identificó a partir de la Base de datos de población de Utah, un recurso estatal que vincula los registros hospitalarios y genealógicos.PACIENTES:Se incluyeron individuos evaluados en un departamento de emergencias u hospitalizados entre 1998 y 2018 por diverticulitis manejada de forma no quirúrgica.INTERVENCIÓN:El predictor principal fue un historial familiar positivo de diverticulitis, definida como diverticulitis en un familiar de primer, segundo o tercer grado.PRINCIPALES MEDIDAS DE VALORACIÓN:Este estudio midió la asociación ajustada entre los antecedentes familiares y el resultado primario de diverticulitis recurrente. Un resultado secundario fue la cirugía electiva por diverticulitis. Análisis adicionales evaluaron el riesgo por grado de parentesco del familiar afectado.RESULTADOS:La cohorte incluyó a 4.426 individuos seguidos durante una mediana de 71 meses. La mediana de edad fue de 64 años y el 45% eran varones. El 17% tenía enfermedad complicada, el 11% recidiva y el 15% se sometió a cirugía electiva. Después del ajuste, los individuos con antecedentes familiares de diverticulitis tenían un riesgo similar de recurrencia en comparación con aquellos sin antecedentes familiares (HR 1,0; IC del 95%: 0,8-1,2). Sin embargo, las personas con antecedentes familiares de diverticulitis tenían más probabilidades de someterse a una cirugía electiva (HR 1,4; IC del 95%: 1,1-1,6). Este efecto fue más pronunciado en aquellos con un familiar de primer grado afectado (HR 1,7; IC del 95%: 1,4-2,2).LIMITACIONES:El uso de datos específicos del estado puede limitar la generalización.CONCLUSIONES:En este análisis poblacional, los individuos con antecedentes familiares de diverticulitis tenían más probabilidades de someterse a una cirugía electiva que aquellos sin antecedentes familiares, a pesar de riesgos similares de recurrencia y diverticulitis complicada. Es necesario seguir trabajando para comprender los complejos factores sociales, ambientales y genéticos que influyen en el tratamiento y los resultados de la diverticulitis. Consulte Video Resumen en http://links.lww.com/DCR/B876 . (Traducción-Dr. Ingrid Melo ).

Impact of choosing wisely on imaging in men with newly diagnosed prostate cancer.

INTRODUCTION: Encouraging the appropriate use of staging imaging in patients with newly diagnosed prostate cancer remains a challenge. Assessing the effects of national efforts may help guide future initiatives in curtailing low-value care. The purpose of this study was to determine the impact of the Choosing Wisely campaign on imaging utilization among men with prostate cancer. METHODS: Surveillance, Epidemiology, and End Results - Medicare data were used to complete a longitudinal population-based study of men diagnosed with prostate cancer from 2007 to 2015. An interrupted time series analysis evaluated the impact of the Choosing Wisely campaign on trends of imaging utilization. RESULTS: From 2007 to 2015 imaging utilization in low-risk patients decreased, with computed tomography (CT) usage declining from 45.0% to 34.4% (P<0.001) and nuclear medicine bone scan (NMBS) from 27.8% to 11.7% (P<0.001). Choosing Wisely likely contributed to an absolute reduction of 2.9% (P=0.03) in utilization of NMBS in the low-risk population. Imaging usage for all modalities increased in the high-risk population, but with 32.8% continuing to not receive guideline-supported imaging. CONCLUSIONS: In 2012, the Choosing Wisely campaign sought to decrease inappropriate staging imaging for men with low-risk prostate cancer and encourage stewardship of medical resources. Overall decreases in staging imaging trends suggest a move towards higher value care. However, this study found that the Choosing Wisely recommendations had a modest impact on utilization of NMBS, but not CT or PET scans. These results may help inform future efforts to promote guideline concordant imaging.

Patterns of indoor radon concentrations, radon-hazard potential, and radon testing on a small geographic scale in Utah.

INTRODUCTION: Currently, there are no publicly-available estimates of indoor radon concentration at scales smaller than the county. Radon-hazard potential soil maps that reflect underlying geologic factors can be created at small geographic scale and linked to residential and census data. We determined the association between residential radon tests and high radon-hazard potential soil at the residential and block group levels using a large Utah-based dataset. We also identified characteristics of block groups with limited tests in the dataset. METHODS: We geocoded a dataset of residential radon tests obtained from 2001 to 2017 by a statewide educational program. We linked each location to maps of radon-hazard potential soil, the Environmental Protection Agency's (EPA) county radon zones. We also calculated the number of tests conducted in each block group and linked block groups to demographic data from the 2020 United States census. Log-linear and logistic models identified the association between residential home test results and 1) radon-hazard potential soil of each residence, 2) percent of residences on high radon-hazard potential soils in block groups, and 3) EPA's radon zones. We compared demographic characteristics among block groups with ≥5 or <5 residential tests in our dataset. RESULTS: Approximately 42% of homes in the dataset tested ≥4 pCi/L. We found significant positive associations for residential radon test results with 1) residential location on high radon-hazard potential soil and 2) block groups with >0% of residences on high radon-hazard potential soil. EPA radon zones were not associated with residential test results. Block groups with <5 tests had higher than the statewide median percentage of Hispanic residents (OR = 2.46, 95% CI = 1.89-3.21) and were located in rural counties. DISCUSSION: Radon-hazard potential soil has a significant association with residential home radon tests. More efforts are needed to improve radon testing in block groups that are rural and have greater percentages of racial minorities.

Geographic Proximity of Family Members and Healthcare Utilization After Complex Surgical Procedures.

OBJECTIVE: We sought to determine the relationship between a patient's proximal familial social support, defined as the geographic proximity of family members, and healthcare utilization after complex cardiovascular and oncologic procedures. BACKGROUND: Social support mechanisms are increasingly identified as modifiable risk factors for healthcare utilization. METHODS: We performed a retrospective cohort study of 60,895 patients undergoing complex cardiovascular procedures or oncologic procedures. We defined healthcare utilization outcomes as 30-day all-cause readmission unplanned readmission, nonindex hospital readmission, index hospital length of stay, and home discharge disposition. For each patient, we aggregated the number of first-degree relatives (FDR) living within 30 miles of the patient's home address at the time of the surgical procedure into the following categories: 0 to 1, 2 to 3, 4 to 5, 6+ FDRs. We developed hierarchical multivariable regression models to determine the relationship between the number of FDR living within 30 miles of the patient and the healthcare utilization outcomes. RESULTS: Compared with patients with 0 to 1 FDRs, patients with 6+ FDRs living in close proximity had significantly lower rates of all-cause readmission (12.1% vs 13.5%, P <0.001), unplanned readmission (10.9% vs 12.0%, P =0.001), nonindex readmission (2.6% vs 3.2%, P =0.003); higher rates of home discharge (88.0% vs 85.3%, P <0.001); and shorter length of stay (7.3 vs 7.5 days, P =0.02). After multivariable adjustment, a larger number of FDRs living within 30 miles of the patient was significantly associated with a lower likelihood of all-cause readmission ( P <0.001 for trend), 30-day unplanned readmission ( P <0.001), nonindex readmission ( P <0.001); higher likelihood of home discharge ( P <0.001); and shorter index length of stay ( P <0.001). CONCLUSIONS: The geographic proximity of family members is significantly associated with decreased healthcare utilization after complex cardiovascular and oncologic surgical procedures.