Rebecca Smith-Bindman

Radiation Dose Associated With Common Computed Tomography Examinations and the Associated Lifetime Attributable Risk of Cancer

BACKGROUND Use of computed tomography (CT) for diagnostic evaluation has increased dramatically over the past 2 decades. Even though CT is associated with substantially higher radiation exposure than conventional radiography, typical doses are not known. We sought to estimate the radiation dose associated with common CT studies in clinical practice and quantify the potential cancer risk associated with these examinations. METHODS We conducted a retrospective cross-sectional study describing radiation dose associated with the 11 most common types of diagnostic CT studies performed on 1119 consecutive adult patients at 4 San Francisco Bay Area institutions in California between January 1 and May 30, 2008. We estimated lifetime attributable risks of cancer by study type from these measured doses. RESULTS Radiation doses varied significantly between the different types of CT studies. The overall median effective doses ranged from 2 millisieverts (mSv) for a routine head CT scan to 31 mSv for a multiphase abdomen and pelvis CT scan. Within each type of CT study, effective dose varied significantly within and across institutions, with a mean 13-fold variation between the highest and lowest dose for each study type. The estimated number of CT scans that will lead to the development of a cancer varied widely depending on the specific type of CT examination and the patients age and sex. An estimated 1 in 270 women who underwent CT coronary angiography at age 40 years will develop cancer from that CT scan (1 in 600 men), compared with an estimated 1 in 8100 women who had a routine head CT scan at the same age (1 in 11 080 men). For 20-year-old patients, the risks were approximately doubled, and for 60-year-old patients, they were approximately 50% lower. CONCLUSION Radiation doses from commonly performed diagnostic CT examinations are higher and more variable than generally quoted, highlighting the need for greater standardization across institutions.

Benefits and Harms of CT Screening for Lung Cancer: A Systematic Review

CONTEXT Lung cancer is the leading cause of cancer death. Most patients are diagnosed with advanced disease, resulting in a very low 5-year survival. Screening may reduce the risk of death from lung cancer. OBJECTIVE To conduct a systematic review of the evidence regarding the benefits and harms of lung cancer screening using low-dose computed tomography (LDCT). A multisociety collaborative initiative (involving the American Cancer Society, American College of Chest Physicians, American Society of Clinical Oncology, and National Comprehensive Cancer Network) was undertaken to create the foundation for development of an evidence-based clinical guideline. DATA SOURCES MEDLINE (Ovid: January 1996 to April 2012), EMBASE (Ovid: January 1996 to April 2012), and the Cochrane Library (April 2012). STUDY SELECTION Of 591 citations identified and reviewed, 8 randomized trials and 13 cohort studies of LDCT screening met criteria for inclusion. Primary outcomes were lung cancer mortality and all-cause mortality, and secondary outcomes included nodule detection, invasive procedures, follow-up tests, and smoking cessation. DATA EXTRACTION Critical appraisal using predefined criteria was conducted on individual studies and the overall body of evidence. Differences in data extracted by reviewers were adjudicated by consensus. RESULTS Three randomized studies provided evidence on the effect of LDCT screening on lung cancer mortality, of which the National Lung Screening Trial was the most informative, demonstrating that among 53,454 participants enrolled, screening resulted in significantly fewer lung cancer deaths (356 vs 443 deaths; lung cancer−specific mortality, 274 vs 309 events per 100,000 person-years for LDCT and control groups, respectively; relative risk, 0.80; 95% CI, 0.73-0.93; absolute risk reduction, 0.33%; P = .004). The other 2 smaller studies showed no such benefit. In terms of potential harms of LDCT screening, across all trials and cohorts, approximately 20% of individuals in each round of screening had positive results requiring some degree of follow-up, while approximately 1% had lung cancer. There was marked heterogeneity in this finding and in the frequency of follow-up investigations, biopsies, and percentage of surgical procedures performed in patients with benign lesions. Major complications in those with benign conditions were rare. CONCLUSION Low-dose computed tomography screening may benefit individuals at an increased risk for lung cancer, but uncertainty exists about the potential harms of screening and the generalizability of results.

The use of computed tomography in pediatrics and the associated radiation exposure and estimated cancer risk

IMPORTANCE Increased use of computed tomography (CT) in pediatrics raises concerns about cancer risk from exposure to ionizing radiation. OBJECTIVES To quantify trends in the use of CT in pediatrics and the associated radiation exposure and cancer risk. DESIGN Retrospective observational study. SETTING Seven US health care systems. PARTICIPANTS The use of CT was evaluated for children younger than 15 years of age from 1996 to 2010, including 4 857 736 child-years of observation. Radiation doses were calculated for 744 CT scans performed between 2001 and 2011. MAIN OUTCOMES AND MEASURES Rates of CT use, organ and effective doses, and projected lifetime attributable risks of cancer. RESULTS The use of CT doubled for children younger than 5 years of age and tripled for children 5 to 14 years of age between 1996 and 2005, remained stable between 2006 and 2007, and then began to decline. Effective doses varied from 0.03 to 69.2 mSv per scan. An effective dose of 20 mSv or higher was delivered by 14% to 25% of abdomen/pelvis scans, 6% to 14% of spine scans, and 3% to 8% of chest scans. Projected lifetime attributable risks of solid cancer were higher for younger patients and girls than for older patients and boys, and they were also higher for patients who underwent CT scans of the abdomen/pelvis or spine than for patients who underwent other types of CT scans. For girls, a radiation-induced solid cancer is projected to result from every 300 to 390 abdomen/pelvis scans, 330 to 480 chest scans, and 270 to 800 spine scans, depending on age. The risk of leukemia was highest from head scans for children younger than 5 years of age at a rate of 1.9 cases per 10 000 CT scans. Nationally, 4 million pediatric CT scans of the head, abdomen/pelvis, chest, or spine performed each year are projected to cause 4870 future cancers. Reducing the highest 25% of doses to the median might prevent 43% of these cancers. CONCLUSIONS AND RELEVANCE The increased use of CT in pediatrics, combined with the wide variability in radiation doses, has resulted in many children receiving a high-dose examination. Dose-reduction strategies targeted to the highest quartile of doses could dramatically reduce the number of radiation-induced cancers.

Use of diagnostic imaging studies and associated radiation exposure for patients enrolled in large integrated health care systems, 1996-2010

CONTEXT Use of diagnostic imaging has increased significantly within fee-for-service models of care. Little is known about patterns of imaging among members of integrated health care systems. OBJECTIVE To estimate trends in imaging utilization and associated radiation exposure among members of integrated health care systems. DESIGN, SETTING, AND PARTICIPANTS Retrospective analysis of electronic records of members of 6 large integrated health systems from different regions of the United States. Review of medical records allowed direct estimation of radiation exposure from selected tests. Between 1 million and 2 million member-patients were included each year from 1996 to 2010. MAIN OUTCOME MEASURE Advanced diagnostic imaging rates and cumulative annual radiation exposure from medical imaging. RESULTS During the 15-year study period, enrollees underwent a total of 30.9 million imaging examinations (25.8 million person-years), reflecting 1.18 tests (95% CI, 1.17-1.19) per person per year, of which 35% were for advanced diagnostic imaging (computed tomography [CT], magnetic resonance imaging [MRI], nuclear medicine, and ultrasound). Use of advanced diagnostic imaging increased from 1996 to 2010; CT examinations increased from 52 per 1000 enrollees in 1996 to 149 per 1000 in 2010, 7.8% annual increase (95% CI, 5.8%-9.8%); MRI use increased from 17 to 65 per 1000 enrollees, 10% annual growth (95% CI, 3.3%-16.5%); and ultrasound rates increased from 134 to 230 per 1000 enrollees, 3.9% annual growth (95% CI, 3.0%-4.9%). Although nuclear medicine use decreased from 32 to 21 per 1000 enrollees, 3% annual decline (95% CI, 7.7% decline to 1.3% increase), PET imaging rates increased after 2004 from 0.24 to 3.6 per 1000 enrollees, 57% annual growth. Although imaging use increased within all health systems, the adoption of different modalities for anatomic area assessment varied. Increased use of CT between 1996 and 2010 resulted in increased radiation exposure for enrollees, with a doubling in the mean per capita effective dose (1.2 mSv vs 2.3 mSv) and the proportion of enrollees who received high (>20-50 mSv) exposure (1.2% vs 2.5%) and very high (>50 mSv) annual radiation exposure (0.6% vs 1.4%). By 2010, 6.8% of enrollees who underwent imaging received high annual radiation exposure (>20-50 mSv) and 3.9% received very high annual exposure (>50 mSv). CONCLUSION Within integrated health care systems, there was a large increase in the rate of advanced diagnostic imaging and associated radiation exposure between 1996 and 2010.

Using Clinical Factors and Mammographic Breast Density to Estimate Breast Cancer Risk: Development and Validation of a New Predictive Model

Context Existing breast cancer prediction tools do not account for breast density, a strong risk factor for breast cancer and have been studied in white women only. Contribution The authors developed a breast cancer risk prediction model that incorporates a measure of breast density routinely reported with mammography. Its predictions were accurate, but it had only modest ability to distinguish women who did not develop cancer from those who did, and it misclassified risk in some subgroups. Implication The model requires validation in additional populations. A breast cancer prediction model that incorporates breast density does well in some but not all domains of predicting risk. Its accuracy should be better characterized before it is used clinically. The Editors In 2007, breast cancer will have been diagnosed in more than 178000 women in the United States, and more than 40000 women will have died of breast cancer (1). Most of these women never had their risk for breast cancer assessed, and even fewer considered chemoprevention (25). Providing women with an estimate of their risk for breast cancer would provide an opportunity for them to consider options to decrease their risk. Women at low short-term risk for breast cancer may experience less anxiety about their health and would be less likely to benefit from prevention efforts. Women at very high risk may warrant additional screening tests, such as breast magnetic resonance imaging (6), and might benefit from chemoprevention of breast cancer with tamoxifen or raloxifene. The standard risk assessment model available to practitioners (the Gail model) (7) identifies only a minority of women who eventually develop breast cancer being at high risk (8). Better breast cancer risk prediction tools are needed (9). The radiographic appearance of the breast has been consistently shown to be a major risk factor for breast cancer, whether it is defined by a qualitative assessment of the parenchymal pattern or a quantitative measure of percentage of density (1012). Women in whom more than 50% of total breast area is mammographically dense have high breast density and are at 3- to 5-fold greater risk for breast cancer than women in whom breast density is less than 25% (10, 1316). The increased risk for breast cancer associated with breast density is due in part to the lower sensitivity of mammography in dense breasts (1719), but the association remains strong after accounting for masking (20, 21). Mammographically dense breast tissue is rich in epithelium and stroma (10), and the association could represent activation of epithelial cells or fibroblasts (2225). Recently, several models have been published that incorporate breast density: One uses a continuous measure of breast density that is not available to clinicians and has not been validated (26), and the other predicts 1-year risk for breast cancer (27). We previously demonstrated that a simple model based on age, ethnicity, and a categorical measure of breast density had predictive accuracy similar to that of the Gail model in a multiethnic cohort of women receiving screening mammograms in northern California (28). We expand on that work by using data from more than 1 million ethnically diverse women throughout the United States to develop and validate a risk assessment tool that incorporates breast density and therefore might improve breast cancer screening and prevention efforts. Methods Study Population We included 1095484 women age 35 years or older who had had at least 1 mammogram with breast density measured by using the Breast Imaging Reporting and Data System (BI-RADS) classification system in any of the 7 mammography registries participating in the National Cancer Institutefunded Breast Cancer Surveillance Consortium (BCSC) (available at breastscreening.cancer.gov) (29). The BCSC is a community-based, ethnically and geographically diverse sample that broadly represents the United States (30). We excluded women who had a diagnosis of breast cancer before their first eligible mammography examination. Because our goal was to develop a model of long-term risk for invasive breast cancer, we excluded women with cancer diagnosed in the first 6 months of follow-up to minimize the number of cases of cancer included in the model that were diagnosed on the basis of the mammogram used for risk assessment. Women were also excluded if they had breast implants. Women in whom ductal carcinoma in situ was diagnosed were censored at the time of diagnosis in the primary analysis. When women had several mammograms, we based our analysis on findings from the first mammogram. Each registry obtains annual approval from its institutional review board for consenting processes or a waiver of consent, enrollment of participants, and ongoing data linkage for research purposes. All registries have received a Certificate of Confidentiality from the federal government that protects the identities of research participants. Measurement of Risk Factors Patient information was obtained primarily from self-report at the time of mammography. We selected 2 risk factors in addition to breast density for inclusion in the model on the basis of simplicity (yes or no) and a high attributable risk: history of breast cancer in a first-degree relative and history of a breast biopsy. Body mass index was later considered for addition to the model, but it was excluded to maintain parsimony and because it had minimal effect on model discrimination (the increase in the concordance statistic [c-statistic] was only 0.003). For modeling and validation, missing data for relatives with breast cancer and number of breast biopsies were set to 0. The 5-year Gail risk was computed for each woman by using the algorithms provided by the National Cancer Institute to calculate the Gail model risk for individual women (31). For Gail model calculations, missing data were coded as specified by that model (age at menarche as14 years, age at first live birth as<20 years, number of breast biopsies as 0, and number of first-degree relatives as 0). Ethnicity was coded by using the expanded race and ethnicity definition currently used in the Surveillance, Epidemiology, and End Results (SEER) database and U.S. Vital Statistics (non-Hispanic White, non-Hispanic Black, Asian or Pacific Islander, Native American/Alaskan Native, Hispanic, or other). We classified women who self-identified as mixed or other race with participants who did not report race and ethnicity. Breast Density Community radiologists at each site classified breast density on screening mammograms as part of routine clinical practice by using the American College of Radiology BI-RADS density categories (32): almost entirely fat (category 1), scattered fibroglandular densities (category 2), heterogeneously dense (category 3), and extremely dense (category 4). The BI-RADS category 2 was used as the reference group for breast density because it formed the largest group. Ascertainment of Breast Cancer Cases Breast cancer outcomes (invasive cancer and ductal carcinoma in situ) were obtained at each site through linkage with the regional population-based SEER program, state tumor registries, and pathology databases. Vital Status Vital status was obtained through linkage to SEER registries, state tumor registries, and the individual state vital statistics or the National Death Index. Model Development We used a proportional hazards model of invasive breast cancer to estimate the hazard ratios for each BI-RADS breast density category. Women entered the model 6 months after the index mammogram and were censored at the time of death, diagnosis of ductal carcinoma in situ, or the end of follow-up. All models were adjusted for age (in 5-year intervals) and race and ethnicity. The strength of the breast density association with breast cancer was greater for women younger than age 65 years (P for interaction< 0.001). Thus, separate models were fitted for women younger than age 65 years and for women age 65 years or older. No other interaction terms were included in the final model. We calculated similar estimates for first-degree relatives with breast cancer (yes or no) and a personal history of breast biopsy (yes or no) from the BCSC. All predictors met the proportional hazards assumption that was assessed by loglog plots and by including interaction terms with time for each predictor variable. We then developed an absolute risk model by using methods described in the Appendix Figure. The model primarily estimates predicted incidence of invasive breast cancer by using age, race or ethnicity, and breast density. These estimates are then adjusted for family history and biopsy history if available. We based our estimates of breast cancer incidence on the SEER age- and ethnicity-specific risk for invasive breast cancer (1992 to 2002) (33). Age-specific incidence for each ethnic group was estimated by fitting a third-order polynomial model to the SEER data. Age-specific incidence rates for the Native American and Alaskan Native group were inconsistent in SEER, so we excluded this group from further analyses. We calculated the baseline risk for the model by adjusting SEER incidence for the populations attributable risk for each breast density subgroup. We estimated the age- and ethnicity-specific distribution of mammographic breast density needed for these calculations by using data from a larger set of 3343047 mammograms from the BCSC. The distribution of breast density varied statistically significantly by age and by race or ethnicity (P< 0.001 for each comparison). The model used these variations by age and race to distribute the 5-year risk for invasive breast cancer across the 4 breast density subgroups. We used the methods described by Gail and colleagues (7) to translate the hazard ratios and risk factor distributions into absolute risks. The age-, sex-, and ethnicity-specific competing risks for death for women were calcula

Is Computed Tomography Safe

Dr. Rebecca Smith-Bindman writes that the risk of cancer from a single CT scan could be as high as 1 in 80 — unacceptably high, given the capacity to reduce these doses of radiation.

Does Utilization of Screening Mammography Explain Racial and Ethnic Differences in Breast Cancer

Context Breast cancer mortality rates have fallen but still differ by race and ethnicity. One explanation might be differences in mammography use. Content These investigators linked data from mammography registries to tumor registries and showed that African-American and Hispanic women have longer intervals between mammography and are more likely to have advanced-stage tumors at diagnosis and to die of breast cancer than white women. However, in women with similar screening histories, these rates were similar regardless of race or ethnicity. Implications Differences in mammography use may explain ethnic disparities in the incidence of advanced-stage breast cancer and in mortality rates. The Editors Breast cancer mortality rates in the United States began to decrease in the 1990s (1) because of increased use of screening mammography and improved breast cancer treatment (2, 3). However, these decreases have primarily benefited non-Hispanic white women, whereas the mortality rate for breast cancer in African-American women changed little (1). Although racial and ethnic differences in breast cancer mortality rates have been consistently documented (1, 4-9), reasons for the persistence of these differences have been difficult to ascertain (10). Possible explanations include differences in biological characteristics of tumors (11-13); patient characteristics, such as obesity, that may affect prognosis; mammography use (14, 15); timeliness and completeness of breast cancer diagnosis and treatment (16, 17); social factors, such as education, literacy, and cultural beliefs; and economic factors, such as income level and health insurance coverage, that might affect a patients access to and choices for breast cancer screening and treatment (18-22). Stage at diagnosis, the strongest predictor of breast cancer survival (23), is proportionally higher in all non-Asian minority groups than in white women (8). Although minority women have historically undergone less mammography than white women (14), several recent surveys have found only small differences in mammography use between white and nonwhite women (24, 25). These observations raised doubt that tumors go undiagnosed until later stages in minority women because of infrequent breast cancer screening (26). However, the 2 most widely cited surveys of mammography use are based on self-report and only inquire about recent use, not adherence over time (24, 25). We explored stage of disease at diagnosis, tumor characteristics (including size and grade), and lymph node involvement among women of different races and ethnicities whose patterns of mammography use were similar. We hypothesized that differences in tumor characteristics may result primarily from differences in mammography use and that women with similar patterns of mammography use may have similar tumor characteristics. We had sufficient sample sizes within each racial and ethnic group and obtained sufficiently detailed data regarding mammography use to permit stratification of the cohort by pattern of mammography use; this technique enabled us to compare tumor characteristics among women with similar screening histories. Methods Data Source We pooled data from facilities that participate in 7 mammography registries that form the National Cancer Institutefunded Breast Cancer Surveillance Consortium: San Francisco Mammography Registry, San Francisco, California; Group Health Cooperative, Seattle, Washington; Colorado Mammography Project, Denver, Colorado; Vermont Breast Cancer Surveillance System, Burlington, Vermont; New Hampshire Mammography Network, Lebanon, New Hampshire; Carolina Mammography Registry, Chapel Hill, North Carolina; and New Mexico Mammography Project, Albuquerque, New Mexico. The data consisted of information sent to the registries regarding all mammographic evaluations performed at these facilities, including radiology reports and breast health surveys. The surveys, which were completed by patients at each mammography examination, included questions regarding race, ethnicity, presence of breast symptoms, and previous mammography use. Breast cancer diagnoses and tumor characteristics were obtained through linkage with state tumor registries; regional Surveillance, Epidemiology, and End Results programs; and hospital-based pathology services. Previous research has shown that at least 94% of cancer cases are identified through these linkages (27). Each surveillance registry captures most mammography case reports within its respective geographic area, and mammograms in these registries include approximately 2% of mammographic examinations performed in the United States. Each registry obtains annual approval from its institutional review board to collect mammography-related information and to link with tumor registries. Participants This study included women without a history of breast cancer who were 40 years of age and older who had undergone mammography at least once for screening or diagnostic purposes between 1996 and 2002 (n= 1010515). We categorized the race and ethnicity of the participating women (the mammography registry cohort) as non-Hispanic white (n= 789997), non-Hispanic African American/black (n= 62408), Hispanic (n= 90642), Asian/Pacific Islander (n= 49867), or Native American/Native Alaskan (n= 17601). We excluded women who did not report their race or ethnicity (n= 133235 [12%]) or reported mixed or other race (n= 6003 [<1%]). Breast cancer was diagnosed in a subset of the women in the mammography registry cohort (Table 1). Table 1. General Categorization of Study Participants Characterization of Mammography Use We included all mammographic evaluations in eligible women that were performed during the study period. We characterized each mammogram that was included in the study by the time interval between that mammogram and the one most recently preceding it. We determined these intervals by using examination dates that were recorded in the database (data were available for 85% of patients) and self-reported dates that the remaining women provided at the time of their examination. The mammography screening intervals were categorized into the following groups: within 1 year (4 to 17 months); 2 years (18 to 29 months); 3 years (30 to 41 months); and 4 years or longer (>41 months). At the time of each mammogram, women completed a breast health survey and provided the date of their last mammogram. We created 2 classifications for first mammograms. Mammography was classified as a first screening if the radiologist coded the examination as screening and the woman reported no breast symptoms. The mammogram was classified as diagnostic if the radiologist coded the examination as diagnostic or if the woman reported a breast mass or nipple discharge. Women whose first mammogram was diagnostic were assigned to the never screened group. Of note, a woman could have had mammography more than once during the study period and therefore could contribute more than 1 observation to the analyses. A woman could have observations that were categorized into different mammography screening intervals. For example, a woman could have had her first mammographic evaluation in 1998 and had subsequent mammography in 1999 and 2001. Her first mammogram would have been categorized as a first screening or as diagnostic, depending on the radiologists indication for that examination and whether the patient reported symptoms. Her second mammogram would have been categorized in the 1 year group, and her third mammography would have been categorized in the 2 year group. Breast Cancer To determine breast cancer status, we tracked each participants mammogram for 365 days following the date it had been obtained or until the patient underwent her next mammographic examination (whichever came first). Consequently, each tumor was associated with a single mammogramthat obtained closest to the date of diagnosis. We characterized breast cancer as either invasive or ductal carcinoma in situ. Large tumors were defined as invasive tumors that were 15 mm or larger in diameter. We used the TNM (tumor, node, metastasis) system (which is based on the criteria of the American Joint Committee on Cancer) to classify stage at diagnosis as 0 (ductal carcinoma in situ), 1, 2, 3, or 4 (28); advanced-stage tumors were defined as invasive lesions of stage 2 or higher. High-grade tumors were defined as invasive lesions of grades 3 and 4. Lymph node status was defined as positive, negative, or unknown. Advanced disease was defined as the presence of a large, advanced-stage, high-grade tumor or lymph nodepositive tumor at the time of diagnosis. Statistical Analysis We calculated the frequency distributions of various risk factors for all women in the mammography registry cohort. Among the subset of women with breast cancer (n= 17558), we calculated the proportion of tumors that were invasive and, among invasive tumors, the proportion that were advanced-stage or high-grade tumors; we then calculated the distribution by race and ethnicity. For all women in the cohort, we evaluated whether overall and advanced cancer rates per 1000 mammograms were similar across racial and ethnic groups after we adjusted for age and registry by using Poisson regression. We then calculated whether adjusted overall and advanced cancer rates per 1000 mammograms were similar across mammography screening interval groups. Because overall and advanced cancer rates varied across racial and ethnic groups (P< 0.001) and by previous mammography use (P< 0.001), and because mammography use potentially varied by race and ethnicity, we modeled cancer rates among similarly screened women in each ethnic group. We used Poisson regression to adjust for age and registry; an interaction term between race and ethnicity and previous mammography use was included in the Poisson model to allow for possible differences in the association between ethnicity and cancer rates by mammography group

Rising Use Of Diagnostic Medical Imaging In A Large Integrated Health System

Little has been published characterizing specific patterns of the dramatic rise in diagnostic imaging during the past decade. In a large health plan, 377,048 patients underwent 4.9 million diagnostic tests from 1997 through 2006. Cross-sectional imaging nearly doubled over those years, rising from 260 to 478 examinations per thousand enrollees per year. Imaging with computed tomography (CT) doubled, and imaging with magnetic resonance imaging (MRI) tripled. Cross-sectional studies added to existing studies instead of replacing them, and the annual per enrollee cost of radiology imaging more than doubled. The dramatic rise in imaging raises both costs and radiation exposure.

Factors Associated with Mammography Utilization: A Systematic Quantitative Review of the Literature

OBJECTIVE A significant segment of women remains underscreened with mammography. We sought to summarize literature related to factors associated with receipt of mammography. For data sources, we used English language papers published between 1988 and 2007, including 221 studies describing 4,957,347 women. METHODS We calculated odds ratios (ORs) associated with receipt of mammography. Random effects modeling was used to assess trends in mammography utilization and to calculate summary multivariate point estimates. Results were stratified by age, race/ethnicity, and study year. We summarized results between 1988 and 2004 and compared recent years with these results. RESULTS Physician access barriers, such as not having a physician-recommend mammography (adjusted OR 0.16, 95% CI 0.08-0.33) and having no primary care provider (OR 0.41, 95% CI 0.32-0.53), were highly predictive of not obtaining mammography. Past screening behavior correlated strongly with receipt of mammography (clinical breast examination, adjusted OR 9.15, 95% CI 3.49-23.98) and Pap test (adjusted OR 3.45, 95% CI 2.12-5.62). With the exception of having no insurance (adjusted OR 0.47, 95% CI 0.39-0.57), several potential socioeconomic barriers did not appear to have an important impact on screening. Racial and ethnic differences were seen. Concerns about cost, mammography safety, and pain were more important to African American and Latina women, and having no insurance was more important to white and Chinese women. Cost concerns and the presence of a family history of breast cancer were less important to older women, whereas screening knowledge had a stronger impact on mammography use in women aged > or =65 years. When we compared study results before 2004 with those later, we found very little difference in the multivariate, adjusted ORs over time. CONCLUSIONS Women with poor access to physicians are much less likely to undergo mammography. Improving the frequency and scope of mammography recommendation by primary care providers is the single most important direct contribution the medical community can make toward increasing mammography use.

Ultrasonography versus Computed Tomography for Suspected Nephrolithiasis

BACKGROUND There is a lack of consensus about whether the initial imaging method for patients with suspected nephrolithiasis should be computed tomography (CT) or ultrasonography. METHODS In this multicenter, pragmatic, comparative effectiveness trial, we randomly assigned patients 18 to 76 years of age who presented to the emergency department with suspected nephrolithiasis to undergo initial diagnostic ultrasonography performed by an emergency physician (point-of-care ultrasonography), ultrasonography performed by a radiologist (radiology ultrasonography), or abdominal CT. Subsequent management, including additional imaging, was at the discretion of the physician. We compared the three groups with respect to the 30-day incidence of high-risk diagnoses with complications that could be related to missed or delayed diagnosis and the 6-month cumulative radiation exposure. Secondary outcomes were serious adverse events, related serious adverse events (deemed attributable to study participation), pain (assessed on an 11-point visual-analogue scale, with higher scores indicating more severe pain), return emergency department visits, hospitalizations, and diagnostic accuracy. RESULTS A total of 2759 patients underwent randomization: 908 to point-of-care ultrasonography, 893 to radiology ultrasonography, and 958 to CT. The incidence of high-risk diagnoses with complications in the first 30 days was low (0.4%) and did not vary according to imaging method. The mean 6-month cumulative radiation exposure was significantly lower in the ultrasonography groups than in the CT group (P<0.001). Serious adverse events occurred in 12.4% of the patients assigned to point-of-care ultrasonography, 10.8% of those assigned to radiology ultrasonography, and 11.2% of those assigned to CT (P=0.50). Related adverse events were infrequent (incidence, 0.4%) and similar across groups. By 7 days, the average pain score was 2.0 in each group (P=0.84). Return emergency department visits, hospitalizations, and diagnostic accuracy did not differ significantly among the groups. CONCLUSIONS Initial ultrasonography was associated with lower cumulative radiation exposure than initial CT, without significant differences in high-risk diagnoses with complications, serious adverse events, pain scores, return emergency department visits, or hospitalizations. (Funded by the Agency for Healthcare Research and Quality.).