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.

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.

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.

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.

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.

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.

Abstract P5-09-05: A model with polygenic risk score and mammographic density predicts interval cancers

Introduction:

Interval breast cancers present with clinical symptoms following a normal screening mammogram. They are associated with unfavorable biological features and with dense breasts. Models predictive of aggressive phenotypes may facilitate tailored screening for women at elevated risk of interval cancers. Polygenic risk scores (PRS) represent the cumulative effects of multiple single nucleotide polymorphisms (SNPs) and can be used to risk-stratify women. In prior reports, PRS is preferentially associated with screen-detected rather than interval cancers. We investigated methods to refine the PRS to preferentially predict interval cancers, and tested the performance of the PRS in joint models with mammographic breast density (MBD).

Methods:

We used data from 1058 breast cancer cases from The Cancer Genome Atlas (TCGA) as the discovery set for our PRS. We selected 107 SNPs from genomewide association studies of breast cancer risk for testing against tumor status at last follow-up in TCGA. Presence of tumor indicated recurrence, progression, or positive margins after resection. Women with tumor present at &lt;100 days of follow-up were excluded. Suggestive associations (p&lt;0.2) were used to construct a PRS, calculated as the sum across all SNPs of the per-allele log-odds ratio multiplied by the number of risk alleles for each SNP. We tested the performance of the PRS in a nested case-control dataset with 471 cases (102 interval cancers, 369 screen detected) and 496 controls from the California Pacific Medical Center Research Institute cohort. Logistic regression was used to evaluate the association between PRS, MBD and interval cancers. Area under the receiver operating characteristic (AUROC) curve was used to measure discrimination.

Results:

Of 107 SNPs, 23 had suggestive associations with presence of tumor at last follow-up in TCGA. The 23-SNP PRS discriminated between women with interval cancers and controls, with AUROC 0.57 (95% CI 0.51-0.63). With the inclusion of MBD in the model, the AUROC was 0.68 (95% CI 0.62-0.74). Women in the highest PRS quintile had an unadjusted 2.07-fold odds (95% CI 1.05-4.07) of developing interval cancers compared with women in the lowest quintile; adjustment for MBD did not change the point estimate. The PRS also discriminated between women with interval and screen-detected cancers, although the findings did not reach statistical significance (AUROC 0.55, 95% CI 0.48-0.61). With the inclusion of MBD in the model, the AUROC was 0.63 (95% CI 0.57-0.69).

Discussion:

A PRS associated with presence of tumor at last follow-up was independently predictive of interval cancers relative to controls. Models with PRS and MBD discriminated between interval and screen-detected cancers, although MBD provided most of the predictive power. Our findings are limited by the size and low number of recurrences in TCGA. It is possible that tumor status largely reflects treatment received, and may only partially represent the biological pathways of interval cancers. Our results suggest that SNPs may potentially identify women at risk for developing interval breast cancer, although further validation is required.

Citation Format: Shieh Y, Hu D, Huntsman S, Ma L, Gard CC, Leung JWT, Tice JA, Cummings SR, Kerlikowske K, Ziv E. A model with polygenic risk score and mammographic density predicts interval cancers [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P5-09-05.

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 Density and Benign Breast Disease: Risk Assessment to Identify Women at High Risk of Breast Cancer

PURPOSE

Women with proliferative breast lesions are candidates for primary prevention, but few risk models incorporate benign findings to assess breast cancer risk. We incorporated benign breast disease (BBD) diagnoses into the Breast Cancer Surveillance Consortium (BCSC) risk model, the only breast cancer risk assessment tool that uses breast density.

METHODS

We developed and validated a competing-risk model using 2000 to 2010 SEER data for breast cancer incidence and 2010 vital statistics to adjust for the competing risk of death. We used Cox proportional hazards regression to estimate the relative hazards for age, race/ethnicity, family history of breast cancer, history of breast biopsy, BBD diagnoses, and breast density in the BCSC.

RESULTS

We included 1,135,977 women age 35 to 74 years undergoing mammography with no history of breast cancer; 17% of the women had a prior breast biopsy. During a mean follow-up of 6.9 years, 17,908 women were diagnosed with invasive breast cancer. The BCSC BBD model slightly overpredicted risk (expected-to-observed ratio, 1.04; 95% CI, 1.03 to 1.06) and had modest discriminatory accuracy (area under the receiver operator characteristic curve, 0.665). Among women with proliferative findings, adding BBD to the model increased the proportion of women with an estimated 5-year risk of 3% or higher from 9.3% to 27.8% (P<.001).

CONCLUSION

The BCSC BBD model accurately estimates women's risk for breast cancer using breast density and BBD diagnoses. Greater numbers of high-risk women eligible for primary prevention after BBD diagnosis are identified using the BCSC BBD model.

Misclassification of Breast Imaging Reporting and Data System (BI-RADS) Mammographic Density and Implications for Breast Density Reporting Legislation

USA states have begun legislating mammographic breast density reporting to women, requiring that women undergoing screening mammography who have dense breast tissue (Breast Imaging Reporting and Data System [BI-RADS] density c or d) receive written notification of their breast density; however, the impact that misclassification of breast density will have on this reporting remains unclear. The aim of this study was to assess reproducibility of the four-category BI-RADS density measure and examine its relationship with a continuous measure of percent density. We enrolled 19 radiologists, experienced in breast imaging, from a single integrated health care system. Radiologists interpreted 341 screening mammograms at two points in time 6 months apart. We assessed intra- and interobserver agreement in radiologists'; interpretations of BI-RADS density and explored whether agreement depended upon radiologist characteristics. We examined the relationship between BI-RADS density and percent density in a subset of 282 examinations. Intraradiologist agreement was moderate to substantial, with kappa varying across radiologists from 0.50 to 0.81 (mean = 0.69, 95% CI [0.63, 0.73]). Intraradiologist agreement was higher for radiologists with ≥10 years experience interpreting mammograms (difference in mean kappa = 0.10, 95% CI [0.01, 0.24]). Interradiologist agreement varied widely across radiologist pairs from slight to substantial, with kappa ranging from 0.02 to 0.72 (mean = 0.46, 95% CI [0.36, 0.55]). Of 145 examinations interpreted as "nondense" (BI-RADS density a or b) by the majority of radiologists, 82.8% were interpreted as "dense" (BI-RADS density c or d) by at least one radiologist. Of 187 examinations interpreted as "dense" by the majority of radiologists, 47.1% were interpreted as "nondense" by at least one radiologist. While the examinations of almost half of the women in our study were interpreted clinically as having BI-RADS density c or d, only about 10% of examinations had percent density >50%. Our results suggest that breast density reporting based on a single BI-RADS density interpretation may be misleading due to high interradiologist variability and a lack of correspondence between BI-RADS density and percent density.

One versus Two Breast Density Measures to Predict 5- and 10-Year Breast Cancer Risk

BACKGROUND

One measure of Breast Imaging Reporting and Data System (BI-RADS) breast density improves 5-year breast cancer risk prediction, but the value of sequential measures is unknown. We determined whether two BI-RADS density measures improve the predictive accuracy of the Breast Cancer Surveillance Consortium 5-year risk model compared with one measure.

METHODS

We included 722,654 women of ages 35 to 74 years with two mammograms with BI-RADS density measures on average 1.8 years apart; 13,715 developed invasive breast cancer. We used Cox regression to estimate the relative hazards of breast cancer for age, race/ethnicity, family history of breast cancer, history of breast biopsy, and one or two density measures. We developed a risk prediction model by combining these estimates with 2000-2010 Surveillance, Epidemiology, and End Results incidence and 2010 vital statistics for competing risk of death.

RESULTS

The two-measure density model had marginally greater discriminatory accuracy than the one-measure model (AUC, 0.640 vs. 0.635). Of 18.6% of women (134,404 of 722,654) who decreased density categories, 15.4% (20,741 of 134,404) of women whose density decreased from heterogeneously or extremely dense to a lower density category with one other risk factor had a clinically meaningful increase in 5-year risk from <1.67% with the one-density model to ≥1.67% with the two-density model.

CONCLUSION

The two-density model has similar overall discrimination to the one-density model for predicting 5-year breast cancer risk and improves risk classification for women with risk factors and a decrease in density.

IMPACT

A two-density model should be considered for women whose density decreases when calculating breast cancer risk.

Reported mammographic density: film-screen versus digital acquisition

PURPOSE

To test the hypothesis that American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) categories for breast density reported by radiologists are lower when digital mammography is used than those reported when film-screen (FS) mammography is used.

MATERIALS AND METHODS

This study was institutional review board approved and HIPAA compliant. Demographic data, risk factors, and BI-RADS breast density categories were collected from five mammography registries that were part of the Breast Cancer Surveillance Consortium. Active, passive, or waiver of consent was obtained for all participants. Women aged 40 years and older who underwent at least two screening mammographic examinations less than 36 months apart between January 1, 2000, and December 31, 2009, were included. Women with prior breast cancer, augmentation, or use of agents known to affect density were excluded. The main sample included 89 639 women with both FS and digital mammograms. The comparison group included 259 046 women with two FS mammograms and 87 066 women with two digital mammograms. BI-RADS density was cross-tabulated according to the order in which the two types of mammogram were acquired and by the first versus second interpretation.

RESULTS

Regardless of acquisition method, the percentage of women with a change in density from one reading to the next was similar. Breast density was lower in 19.8% of the women who underwent FS before digital mammography and 17.1% of those who underwent digital before FS mammography. Similarly, lower density classifications were reported on the basis of the second mammographic examination regardless of acquisition method (15.8%-19.8%). The percentage of agreement between density readings was similar regardless of mammographic types paired (67.3%-71.0%).

CONCLUSION

The study results showed no difference in reported BI-RADS breast density categories according to acquisition method. Reported BI-RADS density categories may be useful in the development of breast cancer risk models in which FS, digital, or both acquisition methods are used.

Reproducibility of BI-RADS breast density measures among community radiologists: a prospective cohort study

Using data from the Vermont Breast Cancer Surveillance System (VBCSS), we studied the reproducibility of Breast Imaging Reporting and Data System (BI-RADS) breast density among community radiologists interpreting mammograms in a cohort of 11,755 postmenopausal women. Radiologists interpreting two or more film-screen screening or bilateral diagnostic mammograms for the same woman within a 3- to 24-month period during 1996-2006 were eligible. We observed moderate-to-substantial overall intra-rater agreement for use of BI-RADS breast density in clinical practice, with an overall intra-radiologist percent agreement of 77.2% (95% confidence interval (CI), 74.5-79.5%), an overall simple kappa of 0.58 (95% CI, 0.55-0.61), and an overall weighted kappa of 0.70 (95% CI, 0.68-0.73). Agreement exhibited by individual radiologists varied widely, with intra-radiologist percent agreement ranging from 62.1% to 87.4% and simple kappa ranging from 0.19 to 0.69 across individual radiologists. Our findings underscore the need for additional evaluation of the BI-RADS breast density categorization system in clinical practice.

Performance of diagnostic mammography differs in the United States and Denmark

Diagnostic mammography is the primary imaging modality to diagnose breast cancer. However, few studies have evaluated variability in diagnostic mammography performance in communities, and none has done so between countries. We compared diagnostic mammography performance in community-based settings in the United States and Denmark. The performance of 93,585 diagnostic mammograms from 180 facilities contributing data to the US Breast Cancer Surveillance Consortium (BCSC) from 1999 to 2001 was compared to that of all 51,313 diagnostic mammograms performed at Danish clinics in 2000. We used the imaging workup's final assessment to determine sensitivity, specificity and an estimate of accuracy: area under the receiver-operating characteristics (ROCs) curve (AUC). Diagnostic mammography had slightly higher sensitivity in the United States (85%) than in Denmark (82%). In contrast, it had higher specificity in Denmark (99%) than in the United States (93%). The AUC was high in both countries: 0.91 in United States and 0.95 in Denmark. Denmark's higher accuracy may result from supplementary ultrasound examinations, which are provided to 74% of Danish women but only 37% to 52% of US women. In addition, Danish mammography facilities specialize in either diagnosis or screening, possibly leading to greater diagnostic mammography expertise in facilities dedicated to symptomatic patients. Performance of community-based diagnostic mammography settings varied markedly between the 2 countries, indicating that it can be further optimized.

When radiologists perform best: the learning curve in screening mammogram interpretation

PURPOSE

To examine changes in screening mammogram interpretation as radiologists with and radiologists without fellowship training in breast imaging gain clinical experience.

MATERIALS AND METHODS

In an institutional review board-approved HIPAA-compliant study, the performance of 231 radiologists who interpreted screen-film screening mammograms from 1996 to 2005 at 280 facilities that contribute data to the Breast Cancer Surveillance Consortium was examined. Radiologists' demographic data and clinical experience levels were collected by means of a mailed survey. Mammograms were grouped on the basis of how many years the interpreting radiologist had been practicing mammography, and the influence of increasing experience on performance was examined separately for radiologists with and those without fellowship training in breast imaging, taking into account case-mix and radiologist-level differences.

RESULTS

A total of 1 599 610 mammograms were interpreted during the study period. Performance for radiologists without fellowship training improved most during their 1st 3 years of clinical practice, when the odds of a false-positive reading dropped 11%-15% per year (P < .015) with no associated decrease in sensitivity (P > .89). The number of women recalled per breast cancer detected decreased from 33 for radiologists in their 1st year of practice to 24 for radiologists with 3 years of experience to 19 for radiologists with 20 years of experience. Radiologists with fellowship training in breast imaging experienced no learning curve and reached desirable goals during their 1st year of practice.

CONCLUSION

Radiologists' interpretations of screening mammograms improve during their first few years of practice and continue to improve throughout much of their careers. Additional residency training and targeted continuing medical education may help reduce the number of work-ups of benign lesions while maintaining high cancer detection rates.

A coarsened multinomial regression model for perinatal mother to child transmission of HIV

Background

In trials designed to estimate rates of perinatal mother to child transmission of HIV, HIV assays are scheduled at multiple points in time. Still, infection status for some infants at some time points may be unknown, particularly when interim analyses are conducted.

Methods

Logistic regression models are commonly used to estimate covariate-adjusted transmission rates, but their methods for handling missing data may be inadequate. Here we propose using coarsened multinomial regression models to estimate cumulative and conditional rates of HIV transmission. Through simulation, we compare the proposed models to standard logistic models in terms of bias, mean squared error, coverage probability, and power. We consider a range of treatment effect and visit process scenarios, while including imperfect sensitivity of the assay and contamination of the endpoint due to early breastfeeding transmission. We illustrate the approach through analysis of data from a clinical trial designed to prevent perinatal transmission.

Results

The proposed cumulative and conditional models performed well when compared to their logistic counterparts. Performance of the proposed cumulative model was particularly strong under scenarios where treatment was assumed to increase the risk of in utero transmission but decrease the risk of intrapartum and overall perinatal transmission and under scenarios designed to represent interim analyses. Power to estimate intrapartum and perinatal transmission was consistently higher for the proposed models.

Conclusion

Coarsened multinomial regression models are preferred to standard logistic models for estimation of perinatal mother to child transmission of HIV, particularly when assays are missing or occur off-schedule for some infants.

Pregnancy intentions and happiness among pregnant black women at high risk for adverse infant health outcomes

CONTEXT

Unintended pregnancy is associated with risk behaviors and increased morbidity or mortality for mothers and infants, but a woman's feelings about pregnancy may be more predictive of risk and health outcomes than her intentions.

METHODS

A sample of 1,044 black women who were at increased risk were enrolled at prenatal care clinics in the District of Columbia in 2001-2003. Bivariate and multivariate analyses assessed associations between pregnancy intentions or level of happiness about being pregnant and multiple psychosocial and behavioral risk factors, and identified correlates of happiness to be pregnant.

RESULTS

Pregnancy intentions and happiness were strongly associated, but happiness was the better predictor of risk. Unhappy women had higher odds than happy women of smoking, being depressed, experiencing intimate partner violence, drinking and using illicit drugs (odds ratios, 1.7-2.6). The odds of being happy were reduced among women who had other children or a child younger than two, who were single or did not have a current partner, who had had more than one sexual partner in the past year and who reported that the baby's father did not want the pregnancy (0.3-0.6). In contrast, the odds of being happy were elevated among women who had better coping strategies (1.03), who had not used birth control at conception (1.6) and who had 1-2 household members, rather than five or more (2.1).

CONCLUSIONS

Additional psychosocial screening for happiness about being pregnant and for partner characteristics, particularly the father's desire to have this child, may help improve prenatal care services and prevent adverse health outcomes.

Rehospitalization of extremely low birth weight (ELBW) infants: are there racial/ethnic disparities?

BACKGROUND

Premature infants are at increased risk for rehospitalization after discharge from the hospital. Racial disparities are known to exist in pediatric health care.

OBJECTIVE

To evaluate whether racial disparities exist in the proportion of extremely low birth weight (ELBW) infants rehospitalized prior to 18 months corrected age and the causes of rehospitalization.

METHODS

The National Institute of Child Health and Human Development Neonatal Research Network database was used to identify all ELBW infants (n=2446) who were born between November 1, 1998 and May 31, 2000 at the 14 participating centers and discharged alive (n=1591). Infants were seen at 18-22 months corrected age for followup. Data related to maternal variables, race, socioeconomic status, medical morbidities, insurance, and rehospitalizations were recorded from the medical record and parent interview. Logistic regression analyses were used to examine the relationship of race/ethnicity and rehospitalization while controlling for gestational age, gender, center, maternal education, family income, bronchopulmonary dysplasia (BPD), necrotizing enterocolitis, ventriculoperitoneal (VP) shunt, respiratory syncytial virus (RSV) prophylaxis, and insurance type.

RESULTS

In all, 1405 (88%) infants were evaluated at followup. The racial distribution of infants admitted, discharged, seen at followup, and rehospitalized were similar. Rehospitalization occurred at least once in 49% of the infants. In the logistic regression analyses, race was not a significant predictor for rehospitalization. The odds of rehospitalization were related to low family income, type of insurance, BPD, VP shunt, RSV prophylaxis, and center.

CONCLUSION

Race was not a predominant variable in the risk of rehospitalization in this cohort of ELBW infants. Medical morbidities and low family income appear to be the major risk factors for rehospitalization.

Low birth weight and preterm births: etiologic fraction attributable to prenatal drug exposure

OBJECTIVES

To determine the factors that would increase the likelihood of outcomes: low birth weight (LBW), preterm births and intrauterine growth restriction (IUGR).

STUDY DESIGN

Secondary data analysis from a multi-center study. Risk factors for each outcome were derived from logistic regression models. Odds ratios (OR), 95% confidence intervals, and population-attributable risk proportions (PAR%) were estimated.

RESULTS

Prenatal cocaine exposure increased the likelihood of LBW (OR: 3.59), prematurity (OR: 1.25), and IUGR (OR: 2.24). Tobacco, but not marijuana, significantly influenced these outcomes. Alcohol had an effect on LBW and IUGR. Etiologic fractions (PAR%) attributable to tobacco for LBW, prematurity, and IUGR were 5.57, 3.66, and 13.79%, respectively. With additional drug exposure including cocaine, estimated summary PAR% increased to 7.20% (LBW), 5.68% (prematurity), and 17.96% (IUGR).

CONCLUSION

Disease burden for each outcome increases with each added drug exposure; however, etiologic fraction attributable to tobacco is greater than for cocaine.