Geographic Access to Early Pregnancy Loss Management.

Early pregnancy loss (EPL) is common, but patients face barriers to the most effective medication (mifepristone followed by misoprostol) and procedural (uterine aspiration) management options. This cross-sectional geospatial analysis evaluated access in New Mexico to mifepristone and misoprostol and uterine aspiration in emergency departments (comprehensive) and to uterine aspiration anywhere in a hospital (aspiration) for EPL. Access was defined as a 60-minute car commute. We collected data from hospital key informants and public databases and performed logistical regression to evaluate associations between access and rurality, area deprivation, race, and ethnicity. Thirty-five of 42 (83.3%) hospitals responded between October 2020 and August 2021. Two hospitals (5.7%) provided comprehensive management; 24 (68.6%) provided aspiration. Rural and higher deprivation areas had statistically significantly lower adjusted odds ratios for comprehensive management (0.03-0.07 and 0.3-0.4, respectively) and aspiration (0.03-0.06 and 0.1-0.3, respectively) access. Mifepristone and uterine aspiration implementation would address disparate access to EPL treatment.

Extending the Breast Cancer Surveillance Consortium Model of Invasive Breast Cancer.

PURPOSE: We extended the Breast Cancer Surveillance Consortium (BCSC) version 2 (v2) model of invasive breast cancer risk to include BMI, extended family history of breast cancer, and age at first live birth (version 3 [v3]) to better inform appropriate breast cancer prevention therapies and risk-based screening. METHODS: We used Cox proportional hazards regression to estimate the age- and race- and ethnicity-specific relative hazards for family history of breast cancer, breast density, history of benign breast biopsy, BMI, and age at first live birth for invasive breast cancer in the BCSC cohort. We evaluated calibration using the ratio of expected-to-observed (E/O) invasive breast cancers in the cohort and discrimination using the area under the receiver operating characteristic curve (AUROC). RESULTS: We analyzed data from 1,455,493 women age 35-79 years without a history of breast cancer. During a mean follow-up of 7.3 years, 30,266 women were diagnosed with invasive breast cancer. The BCSC v3 model had an E/O of 1.03 (95% CI, 1.01 to 1.04) and an AUROC of 0.646 for 5-year risk. Compared with the v2 model, discrimination of the v3 model improved most in Asian, White, and Black women. Among women with a BMI of 30.0-34.9 kg/m2, the true-positive rate in women with an estimated 5-year risk of 3% or higher increased from 10.0% (v2) to 19.8% (v3) and the improvement was greater among women with a BMI of ≥35 kg/m2 (7.6%-19.8%). CONCLUSION: The BCSC v3 model updates an already well-calibrated and validated breast cancer risk assessment tool to include additional important risk factors. The inclusion of BMI was associated with the largest improvement in estimated risk for individual women.

Differences in incidence, staging, and survival of urologic cancers in patients under 65 living in the US-Mexico border region.

Objectives: To describe and compare the incidence, stage at diagnosis, and survival for genitourinary cancers in the border regions and in Hispanic-Americans. Materials and methods: A population-based search was performed using the Surveillance, Epidemiology, and End Results Program 18 database and the Texas Cancer Registry from 2000 to 2017. Cox regression models were performed with adjusted for age, gender, race, cancer type, cancer stage, insurance status, and cause of death were used to compare cancer-specific survival. Results: A total of 63,236 kidney and renal pelvis, 38,398 bladder, 170,640 prostate, 24,313 testicular cancer cases were identified. Cancer-specific survival was found to be improved in Hispanic-Americans in kidney and renal pelvis (hazard ratio [HR], 0.903, 95% confidence interval [CI], 0.856-0.952, p = 0.0001), and bladder cancers (HR, 0.817, 95% CI, 0.743-0.898, p < 0.001), despite a more advanced stage at diagnosis in Hispanics with bladder cancer (p < 0.0074). Testicular cancer has a survival disadvantage for individuals living in the border region (HR, 1.315, 95% CI, 1.124-1.539, p = 0.0006). Conclusions: Disparities exist between Hispanic-Americans and Non-Hispanic White and also between individuals living in the border counties when compared to other regions. This is most significant in individuals with testicular cancer residing in the border region who demonstrate worse overall survival.

Test sensitivity in a prospective cancer screening program: A critique of a common proxy measure.

The true sensitivity of a cancer screening test, defined as the frequency with which the test returns a positive result if the cancer is present, is a key indicator of diagnostic performance. Given the challenges of directly assessing test sensitivity in a prospective screening program, proxy measures for true sensitivity are frequently reported. We call one such proxy empirical sensitivity, as it is given by the observed ratio of screen-detected cancers to the sum of screen-detected and interval cancers. In the setting of the canonical three-state Markov model for progression from preclinical onset to clinical diagnosis, we formulate a mathematical relationship for how empirical sensitivity varies with the screening interval and the mean preclinical sojourn time and identify conditions under which empirical sensitivity exceeds or falls short of true sensitivity. In particular, when the inter-screening interval is short relative to the mean sojourn time, empirical sensitivity tends to exceed true sensitivity, unless true sensitivity is high. The Breast Cancer Surveillance Consortium (BCSC) has reported an estimate of 0.87 for the empirical sensitivity of digital mammography. We show that this corresponds to a true sensitivity of 0.82 under a mean sojourn time of 3.6 years estimated based on breast cancer screening trials. However, the BCSC estimate of empirical sensitivity corresponds to even lower true sensitivity under more contemporary, longer estimates of mean sojourn time. Consistently applied nomenclature that distinguishes empirical sensitivity from true sensitivity is needed to ensure that published estimates of sensitivity from prospective screening studies are properly interpreted.

Risk of cancer versus risk of cancer diagnosis? Accounting for diagnostic bias in predictions of breast cancer risk by race and ethnicity.

OBJECTIVES: Cancer risk prediction may be subject to detection bias if utilization of screening is related to cancer risk factors. We examine detection bias when predicting breast cancer risk by race/ethnicity. METHODS: We used screening and diagnosis histories from the Breast Cancer Surveillance Consortium to estimate risk of breast cancer onset and calculated relative risk of onset and diagnosis for each racial/ethnic group compared with non-Hispanic White women. RESULTS: Of 104,073 women aged 40-54 receiving their first screening mammogram at a Breast Cancer Surveillance Consortium facility between 2000 and 2018, 10.2% (n = 10,634) identified as Asian, 10.9% (n = 11,292) as Hispanic, and 8.4% (n = 8719) as non-Hispanic Black. Hispanic and non-Hispanic Black women had slightly lower screening frequencies but biopsy rates following a positive mammogram were similar across groups. Risk of cancer diagnosis was similar for non-Hispanic Black and White women (relative risk vs non-Hispanic White = 0.90, 95% CI 0.65 to 1.14) but was lower for Asian (relative risk = 0.70, 95% CI 0.56 to 0.97) and Hispanic women (relative risk = 0.82, 95% CI 0.62 to 1.08). Relative risks of disease onset were 0.78 (95% CI 0.68 to 0.88), 0.70 (95% CI 0.59 to 0.83), and 0.95 (95% CI 0.84 to 1.09) for Asian, Hispanic, and non-Hispanic Black women, respectively. CONCLUSIONS: Racial/ethnic differences in mammography and biopsy utilization did not induce substantial detection bias; relative risks of disease onset were similar to or modestly different than relative risks of diagnosis. Asian and Hispanic women have lower risks of developing breast cancer than non-Hispanic Black and White women, who have similar risks.

Cumulative 6-Year Risk of Screen-Detected Ductal Carcinoma In Situ by Screening Frequency.

Importance: Detection of ductal carcinoma in situ (DCIS) by mammography screening is a controversial outcome with potential benefits and harms. The association of mammography screening interval and woman's risk factors with the likelihood of DCIS detection after multiple screening rounds is poorly understood. Objective: To develop a 6-year risk prediction model for screen-detected DCIS according to mammography screening interval and women's risk factors. Design, Setting, and Participants: This Breast Cancer Surveillance Consortium cohort study assessed women aged 40 to 74 years undergoing mammography screening (digital mammography or digital breast tomosynthesis) from January 1, 2005, to December 31, 2020, at breast imaging facilities within 6 geographically diverse registries of the consortium. Data were analyzed between February and June 2022. Exposures: Screening interval (annual, biennial, or triennial), age, menopausal status, race and ethnicity, family history of breast cancer, benign breast biopsy history, breast density, body mass index, age at first birth, and false-positive mammography history. Main Outcomes and Measures: Screen-detected DCIS defined as a DCIS diagnosis within 12 months after a positive screening mammography result, with no concurrent invasive disease. Results: A total of 916 931 women (median [IQR] age at baseline, 54 [46-62] years; 12% Asian, 9% Black, 5% Hispanic/Latina, 69% White, 2% other or multiple races, and 4% missing) met the eligibility criteria, with 3757 screen-detected DCIS diagnoses. Screening round-specific risk estimates from multivariable logistic regression were well calibrated (expected-observed ratio, 1.00; 95% CI, 0.97-1.03) with a cross-validated area under the receiver operating characteristic curve of 0.639 (95% CI, 0.630-0.648). Cumulative 6-year risk of screen-detected DCIS estimated from screening round-specific risk estimates, accounting for competing risks of death and invasive cancer, varied widely by all included risk factors. Cumulative 6-year screen-detected DCIS risk increased with age and shorter screening interval. Among women aged 40 to 49 years, the mean 6-year screen-detected DCIS risk was 0.30% (IQR, 0.21%-0.37%) for annual screening, 0.21% (IQR, 0.14%-0.26%) for biennial screening, and 0.17% (IQR, 0.12%-0.22%) for triennial screening. Among women aged 70 to 74 years, the mean cumulative risks were 0.58% (IQR, 0.41%-0.69%) after 6 annual screens, 0.40% (IQR, 0.28%-0.48%) for 3 biennial screens, and 0.33% (IQR, 0.23%-0.39%) after 2 triennial screens. Conclusions and Relevance: In this cohort study, 6-year screen-detected DCIS risk was higher with annual screening compared with biennial or triennial screening intervals. Estimates from the prediction model, along with risk estimates of other screening benefits and harms, could help inform policy makers' discussions of screening strategies.

Multilevel Factors Associated With Time to Biopsy After Abnormal Screening Mammography Results by Race and Ethnicity.

Importance: Diagnostic delays in breast cancer detection may be associated with later-stage disease and higher anxiety, but data on multilevel factors associated with diagnostic delay are limited. Objective: To evaluate individual-, neighborhood-, and health care-level factors associated with differences in time from abnormal screening to biopsy among racial and ethnic groups. Design, Setting, and Participants: This prospective cohort study used data from women aged 40 to 79 years who had abnormal results in screening mammograms conducted in 109 imaging facilities across 6 US states between 2009 and 2019. Data were analyzed from February 21 to November 4, 2021. Exposures: Individual-level factors included self-reported race and ethnicity, age, family history of breast cancer, breast density, previous breast biopsy, and time since last mammogram; neighborhood-level factors included geocoded education and income based on residential zip codes and rurality; and health care-level factors included mammogram modality, screening facility academic affiliation, and facility onsite biopsy service availability. Data were also assessed by examination year. Main Outcome and Measures: The main outcome was unadjusted and adjusted relative risk (RR) of no biopsy within 30, 60, and 90 days using sequential log-binomial regression models. A secondary outcome was unadjusted and adjusted median time to biopsy using accelerated failure time models. Results: A total of 45 186 women (median [IQR] age at screening, 56 [48-65] years) with 46 185 screening mammograms with abnormal results were included. Of screening mammograms with abnormal results recommended for biopsy, 15 969 (34.6%) were not resolved within 30 days, 7493 (16.2%) were not resolved within 60 days, and 5634 (12.2%) were not resolved within 90 days. Compared with White women, there was increased risk of no biopsy within 30 and 60 days for Asian (30 days: RR, 1.66; 95% CI, 1.31-2.10; 60 days: RR, 1.58; 95% CI, 1.15-2.18), Black (30 days: RR, 1.52; 95% CI, 1.30-1.78; 60 days: 1.39; 95% CI, 1.22-1.60), and Hispanic (30 days: RR, 1.50; 95% CI, 1.24-1.81; 60 days: 1.38; 95% CI, 1.11-1.71) women; however, the unadjusted risk of no biopsy within 90 days only persisted significantly for Black women (RR, 1.28; 95% CI, 1.11-1.47). Sequential adjustment for selected individual-, neighborhood-, and health care-level factors, exclusive of screening facility, did not substantially change the risk of no biopsy within 90 days for Black women (RR, 1.27; 95% CI, 1.12-1.44). After additionally adjusting for screening facility, the increased risk for Black women persisted but showed a modest decrease (RR, 1.20; 95% CI, 1.08-1.34). Conclusions and Relevance: In this cohort study involving a diverse cohort of US women recommended for biopsy after abnormal results on screening mammography, Black women were the most likely to experience delays to diagnostic resolution after adjusting for multilevel factors. These results suggest that adjustment for multilevel factors did not entirely account for differences in time to breast biopsy, but unmeasured factors, such as systemic racism and other health care system factors, may impact timely diagnosis.

Cumulative Advanced Breast Cancer Risk Prediction Model Developed in a Screening Mammography Population.

BACKGROUND: Estimating advanced breast cancer risk in women undergoing annual or biennial mammography could identify women who may benefit from less or more intensive screening. We developed an actionable model to predict cumulative 6-year advanced cancer (prognostic pathologic stage II or higher) risk according to screening interval. METHODS: We included 931 186 women aged 40-74 years in the Breast Cancer Surveillance Consortium undergoing 2 542 382 annual (prior mammogram within 11-18 months) or 752 049 biennial (prior within 19-30 months) screening mammograms. The prediction model includes age, race and ethnicity, body mass index, breast density, family history of breast cancer, and prior breast biopsy subdivided by menopausal status and screening interval. We used fivefold cross-validation to internally validate model performance. We defined higher than 95th percentile as high risk (>0.658%), higher than 75th percentile to 95th or less percentile as intermediate risk (0.380%-0.658%), and 75th or less percentile as low to average risk (<0.380%). RESULTS: Obesity, high breast density, and proliferative disease with atypia were strongly associated with advanced cancer. The model is well calibrated and has an area under the receiver operating characteristics curve of 0.682 (95% confidence interval = 0.670 to 0.694). Based on women's predicted advanced cancer risk under annual and biennial screening, 69.1% had low or average risk regardless of screening interval, 12.4% intermediate risk with biennial screening and average risk with annual screening, and 17.4% intermediate or high risk regardless of screening interval. CONCLUSION: Most women have low or average advanced cancer risk and can undergo biennial screening. Intermediate-risk women may consider annual screening, and high-risk women may consider supplemental imaging in addition to annual screening.

Comparing Mammographic Density Assessed by Digital Breast Tomosynthesis or Digital Mammography: The Breast Cancer Surveillance Consortium.

Background Consistency in reporting Breast Imaging Reporting and Data System (BI-RADS) breast density on mammograms is important because breast density is used for breast cancer risk assessment and is reported directly to women and clinicians to inform decisions about supplemental screening. Purpose To assess the consistency of BI-RADS density reporting between digital breast tomosynthesis (DBT) and digital mammography (DM) and evaluate density as a breast cancer risk factor when assessed using DM versus DBT. Materials and Methods The Breast Cancer Surveillance Consortium is a prospective cohort study of women undergoing mammography with DM or DBT. This secondary analysis included women aged 40-79 years who underwent at least two screening mammography examinations less than 36 months apart. Percentage agreement and κ statistic were estimated for pairs of BI-RADS density assessments. Cox proportional hazards regression was used to calculate hazard ratios (HRs) of breast density as a risk factor for invasive breast cancer. Results A total of 403 326 pairs of mammograms from 342 149 women were evaluated. There were no significant differences in breast density assessment in pairs consisting of one DM and one DBT examination (57 516 of 74 729 [77%]; κ = 0.64), two DM examinations (238 678 of 301 743 [79%]; κ = 0.67), and two DBT examinations (20 763 of 26 854 [77%]; κ = 0.65). Results were similar when restricting the analyses to pairs read by the same radiologist. The breast cancer HRs for breast density were similar for DM and DBT (P = .45 for interaction). The HRs for density acquired using DM and DBT, respectively, were 0.55 (95% CI: 0.49, 0.63) and 0.37 (95% CI: 0.21, 0.66) for almost entirely fat, 1.47 (95% CI: 1.37, 1.58) and 1.36 (95% CI: 1.02, 1.82) for heterogeneously dense, and 1.72 (95% CI: 1.54, 1.93) and 2.05 (95% CI: 1.25, 3.36) for extremely dense breasts. Conclusion Radiologist reporting of Breast Imaging Reporting and Data System density obtained with digital breast tomosynthesis did not differ from that obtained with digital mammography. © RSNA, 2021 Online supplemental material is available for this article.

Examining the Prevalence of Peripartum Depressive Symptoms in a Border Community.

Introduction: Depression is one of the most common complications in pregnancy, affecting 10% to 20% of women. Untreated peripartum depression increases the risk of adverse life events, more considerable distress, homelessness, and illness later in life. This study explored the prevalence of peripartum depression and associated demographic characteristics in a population of low-income, Healthy Start program participants in one New Mexico county along the U.S.-Mexico border where knowledge of depression prevalence is lacking. Materials and Methods: Healthy Start caseworkers routinely administered the 10-item Edinburgh Postnatal Depression Scale (EPDS) to all pregnant and recently pregnant program participants between 2009 and 2017. Scores for the first prenatal screen, first postpartum screen, and all screens for 1453 women were studied. A score of >10 points out of a possible 30 indicated a positive screen. Screening outcome was examined in relation to age, race, ethnicity, primary language, and trimester of the prenatal screen. Crude and adjusted odds ratios were generated from logistic regression models. Results: Overall, 16.4% of women screened positive for depression. English-speaking women, non-Hispanic white women, and those ages >35 years were more likely to screen positive. Women >35 years also had higher odds of reporting thoughts of self-harm than younger women. Conclusion: In this low-income border population, non-Hispanic white, English-speaking women over the age of 35 were at the greatest risk of peripartum depression. These findings underscore the need for peripartum depression screening in this population.

Breast Cancer Population Attributable Risk Proportions Associated with Body Mass Index and Breast Density by Race/Ethnicity and Menopausal Status.

BACKGROUND: Overweight/obesity and dense breasts are strong breast cancer risk factors whose prevalences vary by race/ethnicity. The breast cancer population attributable risk proportions (PARP) explained by these factors across racial/ethnic groups are unknown. METHODS: We analyzed data collected from 3,786,802 mammography examinations (1,071,653 women) in the Breast Cancer Surveillance Consortium, associated with 21,253 invasive breast cancers during a median of 5.2 years follow-up. HRs for body mass index (BMI) and breast density, adjusted for age and registry were estimated using separate Cox regression models by race/ethnicity (White, Black, Hispanic, Asian) and menopausal status. HRs were combined with observed risk-factor proportions to calculate PARPs for shifting overweight/obese to normal BMI and shifting heterogeneously/extremely dense to scattered fibroglandular densities. RESULTS: The prevalences and HRs for overweight/obesity and heterogeneously/extremely dense breasts varied across races/ethnicities and menopausal status. BMI PARPs were larger for postmenopausal versus premenopausal women (12.0%-28.3% vs. 1.0%-9.9%) and nearly double among postmenopausal Black women (28.3%) than other races/ethnicities (12.0%-15.4%). Breast density PARPs were larger for premenopausal versus postmenopausal women (23.9%-35.0% vs. 13.0%-16.7%) and lower among premenopausal Black women (23.9%) than other races/ethnicities (30.4%-35.0%). Postmenopausal density PARPs were similar across races/ethnicities (13.0%-16.7%). CONCLUSIONS: Overweight/obesity and dense breasts account for large proportions of breast cancers in White, Black, Hispanic, and Asian women despite large differences in risk-factor distributions. IMPACT: Risk prediction models should consider how race/ethnicity interacts with BMI and breast density. Efforts to reduce BMI could have a large impact on breast cancer risk reduction, particularly among postmenopausal Black women.

Testicular Cancer Incidence and Mortality in New Mexico.

Objective: To examine incidence and survival of testicular cancer in New Mexico, overall and separately for border and non-border counties. Methods: Incidence and 5-year survival rates for testicular cancer were obtained from the SEER18 database using the SEER*Stat program following established NCI protocols. Incidence data were compared using Student's t-test. Age-adjusted 5-year survival and Kaplan-Meier method were used to estimate survival. Log-rank tests were used to compare survival for New Mexico to the remaining17 geographical areas of the SEER 18 and for the New Mexico border counties to the New Mexico non-border counties. Odds ratios were used to compare testicular stage at diagnosis. Cox proportional hazards regression was performed to account for race/ethnicity, and border status. Results: From 2000-2015, New Mexico had a testicular cancer incidence rate of 6.3 per 100,000 people, significantly higher than SEER18 (P<.001). The 5-year survival rate in New Mexico did not differ significantly from the SEER18 (P=.3). Border Hispanics had a lower survival rate than border non-Hispanic populations (P=.03). From 2000-2018, New Mexico had a significantly higher proportion of distant cancers than the SEER18 (OR: 1.29, 95% CI: 1.08 to 1.53, P=.005). Conclusions: The higher incidence of testicular cancer in New Mexico does not appear to have a clear explanation based on the current understanding of risk factors; however, the increased incidence in New Mexico does not appear to be associated with increased mortality. The higher proportion of advanced testicular cancers in New Mexico may represent a delay in diagnosis. The increased mortality rate seen in Hispanic border populations may be due in part to barriers to care.

Multi-level Drivers of Disparities in Hispanic Cesarean Delivery Rates in US-Mexico Border States.

BACKGROUND: Hispanic women living along the US-Mexico border have higher cesarean delivery rates than non-Hispanic white women, African American women, and other Hispanic women in the USA. Their rates also exceed those of other Hispanic women in states that border Mexico and non-Hispanic white women along the border. Our objective was to determine the causes of the disparities in border Hispanic cesarean rates. METHODS: Using the 2015 birth certificate file and other sources, we performed a twofold Oaxaca-Blinder decomposition analysis of the disparities in low-risk primary and repeat cesarean rates between Hispanic and non-Hispanic white women in the US-Mexico border counties and Hispanic women residing in nonborder counties of border states. RESULTS: Rates of low-risk primary cesarean among border Hispanic, nonborder Hispanic, and border non-Hispanic white women were 21.1%, 15.0%, and 16.5%, respectively. Higher Hispanic concentration in county of residence, a larger proportion of for-profit hospital beds, and greater poverty accounted for 24.7%, 22.1%, and 11.1% of the border-nonborder Hispanic difference, respectively. No other variable explained more than 5% of the difference. Higher Hispanic concentration, more for-profit beds, less attendance by an MD, higher BMI, and greater poverty explained 60.6%, 42.4%, 42.4%, 27.4%, and 21.3%, respectively, of the Hispanic-non-Hispanic white difference. Hispanic concentration and for-profit beds were also important explanatory variables for low-risk repeat cesareans. CONCLUSION: Efforts to address potentially unnecessary cesareans among Hispanic women on the border should recognize that community demographic and health delivery system characteristics are more influential than maternal medical risk factors.

Validation of the breast cancer surveillance consortium model of breast cancer risk.

PURPOSE: In order to use a breast cancer prediction model in clinical practice to guide screening and prevention, it must be well calibrated and validated in samples independent from the one used for development. We assessed the accuracy of the breast cancer surveillance consortium (BCSC) model in a racially diverse population followed for up to 10 years. METHODS: The BCSC model combines breast density with other risk factors to estimate a woman's 5- and 10-year risk of invasive breast cancer. We validated the model in an independent cohort of 252,997 women in the Chicago area. We evaluated calibration using the ratio of expected to observed (E/O) invasive breast cancers in the cohort and discrimination using the area under the receiver operating characteristic curve (AUROC). RESULTS: In an independent cohort of 252,997 women (median age 50 years, 26% non-Hispanic Black), the BCSC model was well calibrated (E/O = 0.94, 95% confidence interval [CI] 0.90-0.98), but underestimated the incidence of invasive breast cancer in younger women and in women with low mammographic density. The AUROC was 0.633, similar to that observed in prior validation studies. CONCLUSIONS: The BCSC model is a well-validated risk assessment tool for breast cancer that may be particularly useful when assessing the utility of supplemental screening in women with dense breasts.

In States That Border Mexico, Cesarean Rates Were Highest For Hispanic Women Living In Border Counties In 2015.

Hispanic women living on the US-Mexico border have had higher cesarean delivery rates than other Hispanic women in the US. Using birth certificate and other data, we compared cesarean rates among Hispanic women living in US border counties with rates among other Hispanic women in border states during 2015. Using linear regression, we also determined which medical, hospital, and sociodemographic characteristics accounted for intercounty variations in rates. In border counties the rates were 38.3 percent for all births, 31.3 percent for low-risk nulliparous mothers, 21.0 percent for primary cesareans, and 94.7 percent for repeat cesareans. In nonborder counties the rates were 30.9 percent, 24.4 percent, 15.1 percent, and 90.5 percent, respectively. Maternal medical characteristics explained over 50 percent of the variation for all cesarean outcomes. Other characteristics that were major contributors to higher cesarean rates included for-profit hospital status, delivery by a physician as opposed to a midwife, and residence in a county with a larger Hispanic fraction of the population. Addressing potentially unnecessary cesareans among Hispanic women on the border will likely require a multicomponent strategy.

Trends in Hispanic and non-Hispanic white cesarean delivery rates on the US-Mexico border, 2000-2015.

BACKGROUND: Cesarean delivery occurs in one in three US births and poses risks for mothers and infants. Hispanic cesarean rates were higher than non-Hispanic white rates in the US in 2016. In 2009, cesarean rates among Hispanics on the US-Mexico border exceeded rates among US Hispanics. Since 2009, rates have declined nationwide, but border Hispanic rates have not been studied. OBJECTIVE: To compare cesarean delivery rates and trends in Hispanics and non-Hispanic whites in border and nonborder counties of the four US border states before and after 2009. STUDY DESIGN: We used data from birth certificates to calculate percentages of cesarean deliveries among all births and births to low-risk nulliparous women during 2000-2015, and among births to low-risk women with and without a previous cesarean during 2009-2015. We calculated 95% confidence intervals around rates and used regular and piecewise linear regression to estimate trends for four ethnic-geographic subpopulations defined by combinations of Hispanic ethnicity and border-nonborder status. RESULTS: Of the four subpopulations, border Hispanic rates were highest every year for all cesarean outcomes. In 2015 they were 38.3% overall, 31.4% among low-risk nulliparous women, and 21.1% and 94.6% among low-risk women without and with a previous cesarean, respectively. Nonborder Hispanic rates in 2015 were lowest for all outcomes but repeat cesarean. Rates for all four subpopulations rose steadily during 2000-2009. Unlike rates for non-Hispanic whites, border and nonborder Hispanic rates did not decline post-2009. Most of the border Hispanic excess can be attributed to higher cesarean rates in Texas. DISCUSSION: Border Hispanic cesarean rates remain higher than those among other Hispanics and non-Hispanic whites in border states and show no signs of declining. This continuing disparity warrants further analysis using individual as well as hospital, environmental and other contextual factors to help target prevention measures.

Short-Range Responses of the Kissing Bug Triatoma rubida (Hemiptera: Reduviidae) to Carbon Dioxide, Moisture, and Artificial Light.

The hematophagous bug Triatoma rubida is a species of kissing bug that has been marked as a potential vector for the transmission of Chagas disease in the Southern United States and Northern Mexico. However, information on the distribution of T. rubida in these areas is limited. Vector monitoring is crucial to assess disease risk, so effective trapping systems are required. Kissing bugs utilize extrinsic cues to guide host-seeking, aggregation, and dispersal behaviors. These cues have been recognized as high-value targets for exploitation by trapping systems. A modern video-tracking system was used with a four-port olfactometer system to quantitatively assess the behavioral response of T. rubida to cues of known significance. Also, response of T. rubida adults to seven wavelengths of light-emitting diodes (LED) in paired-choice pitfall was evaluated. Behavioral data gathered from these experiments indicate that T. rubida nymphs orient preferentially to airstreams at either 1600 or 3200 ppm carbon dioxide and prefer relative humidity levels of about 30%, while adults are most attracted to 470 nm light. These data may serve to help design an effective trapping system for T. rubida monitoring. Investigations described here also demonstrate the experimental power of combining an olfactometer with a video-tracking system for studying insect behavior.

Joint relative risks for estrogen receptor-positive breast cancer from a clinical model, polygenic risk score, and sex hormones.

BACKGROUND: Models that predict the risk of estrogen receptor (ER)-positive breast cancers may improve our ability to target chemoprevention. We investigated the contributions of sex hormones to the discrimination of the Breast Cancer Surveillance Consortium (BCSC) risk model and a polygenic risk score comprised of 83 single nucleotide polymorphisms. METHODS: We conducted a nested case-control study of 110 women with ER-positive breast cancers and 214 matched controls within a mammography screening cohort. Participants were postmenopausal and not on hormonal therapy. The associations of estradiol, estrone, testosterone, and sex hormone binding globulin with ER-positive breast cancer were evaluated using conditional logistic regression. We assessed the individual and combined discrimination of estradiol, the BCSC risk score, and polygenic risk score using the area under the receiver operating characteristic curve (AUROC). RESULTS: Of the sex hormones assessed, estradiol (OR 3.64, 95% CI 1.64-8.06 for top vs bottom quartile), and to a lesser degree estrone, was most strongly associated with ER-positive breast cancer in unadjusted analysis. The BCSC risk score (OR 1.32, 95% CI 1.00-1.75 per 1% increase) and polygenic risk score (OR 1.58, 95% CI 1.06-2.36 per standard deviation) were also associated with ER-positive cancers. A model containing the BCSC risk score, polygenic risk score, and estradiol levels showed good discrimination for ER-positive cancers (AUROC 0.72, 95% CI 0.65-0.79), representing a significant improvement over the BCSC risk score (AUROC 0.58, 95% CI 0.50-0.65). CONCLUSION: Adding estradiol and a polygenic risk score to a clinical risk model improves discrimination for postmenopausal ER-positive breast cancers.

Risk Factors That Increase Risk of Estrogen Receptor-Positive and -Negative Breast Cancer.

Background: Risk factors may differentially influence development of estrogen receptor (ER)-positive vs -negative breast cancer. We examined associations with strong, prevalent risk factors by ER subtype. Methods: Of 1 279 443 women age 35 to 74 years participating in the Breast Cancer Surveillance Consortium, 14 969 developed ER-positive and 3617 developed ER-negative invasive breast cancer. We calculated hazard ratios (HRs) using Cox regression and compared ER subtype hazard ratios at representative ages or by menopausal status using Wald tests. All statistical tests were two-sided. Results: For women age 40 years, compared with no prior biopsy, ER-positive vs ER-negative HRs were 1.53 (95% CI = 1.30 to 1.81) vs 1.26 (95% CI = 0.90 to 1.76) for nonproliferative disease, 1.63 (95% CI = 1.23 to 2.17) vs 1.41 (95% CI = 0.78 to 2.57) for proliferative disease without atypia, and 4.47 (95% CI = 2.88 to 6.96) vs 0.20 (95% CI = 0.02 to 2.51) for proliferative disease with atypia. Benign disease proliferation risk was stronger for ER-positive than ER-negative cancer for women age 35 years (Wald P = .04), age 40 years (Wald P = .04), and age 50 years (Wald P = .06). Among pre/perimenopausal women, body mass index (BMI) had a stronger association with ER-negative than ER-positive cancer (obese II/III vs. normal weight: HR = 1.52, 95% CI = 1.19 to 1.94; vs 1.21, 95% CI = 1.08 to 1.36). Increasing BMI similarly increased ER-positive and ER-negative cancer risk among postmenopausal hormone users (Wald P = .15) and nonusers (Wald P = .08). Associations with ER subtype varied by race/ethnicity across all ages (P < .001) and by family history of breast cancer and breast density for specific ages. Conclusions: Strength of risk factor associations differed by ER subtype. Separate risk models for ER subtypes may improve identification of women for targeted prevention strategies.

Breast cancer risk prediction using a clinical risk model and polygenic risk score.

Breast cancer risk assessment can inform the use of screening and prevention modalities. We investigated the performance of the Breast Cancer Surveillance Consortium (BCSC) risk model in combination with a polygenic risk score (PRS) comprised of 83 single nucleotide polymorphisms identified from genome-wide association studies. We conducted a nested case-control study of 486 cases and 495 matched controls within a screening cohort. The PRS was calculated using a Bayesian approach. The contributions of the PRS and variables in the BCSC model to breast cancer risk were tested using conditional logistic regression. Discriminatory accuracy of the models was compared using the area under the receiver operating characteristic curve (AUROC). Increasing quartiles of the PRS were positively associated with breast cancer risk, with OR 2.54 (95 % CI 1.69-3.82) for breast cancer in the highest versus lowest quartile. In a multivariable model, the PRS, family history, and breast density remained strong risk factors. The AUROC of the PRS was 0.60 (95 % CI 0.57-0.64), and an Asian-specific PRS had AUROC 0.64 (95 % CI 0.53-0.74). A combined model including the BCSC risk factors and PRS had better discrimination than the BCSC model (AUROC 0.65 versus 0.62, p = 0.01). The BCSC-PRS model classified 18 % of cases as high-risk (5-year risk ≥3 %), compared with 7 % using the BCSC model. The PRS improved discrimination of the BCSC risk model and classified more cases as high-risk. Further consideration of the PRS's role in decision-making around screening and prevention strategies is merited.