Meghan S. Weyrich

Supplemental Screening for Breast Cancer in Women With Dense Breasts: A Systematic Review for the U.S. Preventive Services Task Force

Dense breasts are defined by mammographic appearance. The American College of Radiologys (ACRs) Breast Imaging Reporting and Data System (BI-RADS) classifies breasts as almost entirely fatty (BI-RADS category a), scattered areas of fibroglandular density (category b), heterogeneously dense (category c), or extremely dense (category d). About 27.6 million (43%) women aged 40 to 74 years in the United States have dense breasts; most of these are classified as category c (1). Higher breast density is associated with decreased mammographic sensitivity and specificity and also with increased breast cancer risk. The relative hazard of breast cancer for women with dense breasts ranged from 1.50 (women aged 65 to 74 years) to 1.83 (women aged 40 to 49 years) in an analysis of 1169248 women enrolled in the Breast Cancer Surveillance Consortium (unpublished data). Increased breast density has been associated with hormone replacement therapy use, younger age, and lower body mass index (2). Data on breast density and race or ethnicity are limited. In the United States, Asian women have higher breast density (3) but lower than average incidence of breast cancer (4). Increased breast density is not associated with higher breast cancer mortality among women with dense breasts diagnosed with breast cancer, after adjustment for stage and mode of detection (5). Supplemental breast cancer screening with additional screening modalities has been proposed to improve the early detection of breast cancers. No clinical guidelines explicitly recommend use of supplemental breast cancer screening on women with dense breasts (69), but as of September 2015, 24 states had enacted legislation requiring that women be notified of breast density with their mammography results; 9 more states are considering mandatory notification (10) (Appendix Table 1). Most states require specific language distinguishing dense (BI-RADS c and d) from nondense breasts, and 4 states require that insurers cover subsequent examinations and tests for women with dense breasts (1114). Federal legislation requiring breast density notification is pending (15). Appendix Table 1. Breast Density Legislation in the United States This report summarizes a systematic review of current evidence on the reproducibility of BI-RADS breast density determinations and on test performance characteristics and outcomes of supplemental screening of women with dense breasts by using hand-held ultrasonography (HHUS), automated whole-breast ultrasonography (ABUS), breast magnetic resonance imaging (MRI), and digital breast tomosynthesis (DBT). Mandatory reporting laws frame notification of women as dense/nondense, so this review focused on this categorization. Methods The review protocol included an analytic framework with 4 key questions (KQs) (Appendix Figure 1). Detailed methods, including search strategies, detailed inclusion criteria, and excluded studies, are available in the full evidence report (16). Appendix Figure 1. Analytic framework. BI-RADS = Breast Imaging Reporting and Data System; DCIS = ductal carcinoma in-situ; KQ = key question; MRI = magnetic resonance imaging. Data Sources and Searches MEDLINE, PubMed, EMBASE, and the Cochrane Library were searched for relevant English-language studies published between January 2000 and July 2015. We reviewed reference lists from retrieved articles and references suggested by experts. Study Selection Two investigators independently reviewed abstracts and full-text articles for inclusion according to predetermined criteria (E.P.W. and J.H.T. for KQ 1, J.M. and J.J.F. for KQs 2 to 4). Included studies examining the reproducibility of BI-RADS breast density categorization focused on asymptomatic women aged 40 years or older undergoing digital or film mammography. Included studies on supplemental screening with HHUS, ABUS, MRI, or DBT reported outcomes for asymptomatic women with dense breasts aged 40 years and older. In studies that focused primarily on women at high risk for breast cancer (including those with preexisting breast cancer or high-risk breast lesions [such as ductal carcinoma in situ, atypical hyperplasia, and lobular carcinoma in situ], BRCA mutations, familial breast cancer syndromes, or previous chest-wall radiation) and studies that included women with nondense breasts, we analyzed the relevant subset when available in the publication or provided by the authors. A priori inclusion criteria limited studies on BI-RADS reproducibility to fair- or good-quality randomized, controlled trials; cohort studies; or test sets involving multiple blind readings by at least 3 readers. Studies on test performance characteristics and outcomes of supplemental screening modalities were limited to fair- or good-quality randomized, controlled trials; cohort studies; or diagnostic accuracy studies with reference standards applied to all participants. We examined sensitivity, specificity, positive predictive values (PPVs), negative predictive values (NPVs), and available clinical outcomes (including cancer detection rates, recall rates, and biopsy rates). We defined recall as the need for any additional diagnostic testing after supplemental screening, including imaging and biopsy. Data Extraction and Quality Assessment Two investigators (E.P.W. and J.H.T. for KQ 1, J.M. and J.J.F. for KQs 2 to 4) critically appraised all included studies independently using the U.S. Preventive Services Task Forces (USPSTFs) design-specific criteria (17), supplemented with the National Institute for Health and Clinical Excellence methodology checklists (18) and the Quality Appraisal Tool for Studies of Diagnostic Reliability (19). According to USPSTF criteria, a good-quality study generally met all prespecified criteria; fair-quality studies did not meet all criteria but had no important limitations. Poor-quality studies had important limitations that could invalidate results (inadequate or biased application of reference standard; population limited to very high-risk patients). Data Synthesis and Analysis When available or provided by the authors, results of supplemental screening for subgroups of women with dense breasts were extracted; we excluded those with other risk factors for breast cancer. We calculated the sensitivity and specificity of the supplemental breast screening tests for women with negative mammography results. Only cancers detected by the supplemental test after negative mammography results and cancers found at interval follow-up were included. Hence, the values reported represent the sensitivity and specificity for detection of additional cancer in women with negative mammography findings. Similarly, we defined cancer detection rates, recall rates, and biopsy rates to include only those cancer cases, recalls, and biopsies related to supplemental screening after negative results on mammography. Meta-analysis was not performed because there were few good-quality studies. Role of the Funding Source This research was funded by the Agency for Healthcare Research and Quality (AHRQ) under a contract to support the work of the USPSTF. The investigators worked with USPSTF members to develop and refine the scope, analytic frameworks, and KQs. AHRQ had no role in study selection, quality assessment, synthesis, or development of conclusions. AHRQ provided project oversight; reviewed the draft report; and distributed the draft for peer review, including to representatives of professional societies and federal agencies. AHRQ performed a final review of the manuscript to ensure that the analysis met methodological standards. The investigators are solely responsible for the content and the decision to submit the manuscript for publication. Results The literature search yielded 2067 unique citations; 128 full-text articles considered potentially relevant were reviewed to identify 24 unique studies meeting inclusion criteria (Appendix Figure 2). Table 1 (2043) provides the characteristics of included studies. No studies addressed the effect of supplemental screening (compared with women without supplemental screening) on breast cancer morbidity or mortality. Appendix Figure 2. Summary of evidence search and selection. KQ = key question. Table 1. Characteristics of Included Studies Accuracy and Reliability of BI-RADS Density Determination Absent a gold standard for breast density, studies could not evaluate the accuracy of BI-RADS density determinations. Five studies reported repeated assignment of categorical BI-RADS breast density classification by the same or different radiologists, altogether including more than 440000 women, almost all with data from 2 sequential screening mammograms. To reflect current U.S. practice, we included only studies based on the BI-RADS density categories. The 3 largest studies were set in the United States. Two used data from the Breast Cancer Surveillance Consortium (20, 22), and the third presented findings from community radiologists conducting repeated readings of a large screening test set (24). Two other small studies (not discussed here) were based on mammographic screening programs in Spain (21) and Italy (23). All United Statesbased studies reflected community practice by use of clinical readings from community screening programs or test set readings by practicing community radiologists without additional training. Overall, group prevalence of BI-RADS density ratings was similar across initial and subsequent examinations among community radiologists (Appendix Table 2), but there was greater disagreement at the individual level. On subsequent screening examinations, approximately 1 in 5 women (23%) was placed in a different BI-RADS density category (a, b, c, d) by the same radiologist, while approximately 1 in 3 was categorized differently when a different radiologist read the subsequent examination result (Table 2). Considering clinical interpretations that combine categories (dense representing those with BI-RAD

Defining Risk of Prescription Opioid Overdose: Pharmacy Shopping and Overlapping Prescriptions Among Long-Term Opioid Users in Medicaid

UNLABELLED Use of multiple pharmacies concurrently (pharmacy shopping) and overlapping prescriptions may be indicators of potential misuse or abuse of prescription opioid medications. To evaluate strategies for identifying patients at high risk, we first compared different definitions of pharmacy shopping and then added the indicator of overlapping opioid prescriptions. We identified a cohort of 90,010 Medicaid enrollees who used ≥ 3 opioid prescriptions for ≥ 90 days during 2008 to 2010 from a multistate Medicaid claims database. We compared the diagnostic odds ratios for opioid overdose events of 9 pharmacy shopping definitions. Within a 90-day interval, a threshold of 4 pharmacies had the highest diagnostic odds ratio and was used to define pharmacy shopping. The overdose rate was higher in the subgroup with overlapping prescriptions (18.5 per 1,000 person-years [PYs]) than in the subgroup with pharmacy shopping as the sole indicator (10.7 per 1,000 PYs). Among the subgroup with both conditions, the overdose rate was 26.3 per 1,000 PYs, compared with 4.3 per 1,000 PYs for those with neither condition. Overlapping opioid prescriptions and pharmacy shopping measures had adjusted hazard ratios of 3.0 and 1.8, respectively, for opioid overdose. Using these measures will improve accurate identification of patients at highest risk of opioid overdose, the first step in implementing targeted prevention policies. PERSPECTIVE Long-term prescription opioid use may lead to adverse events, including overdose. Both pharmacy shopping and overlapping opioid prescriptions are associated with adverse outcomes. This study demonstrates that using both indicators will better identify those at high risk of overdose.

Prostate-specific antigen-based screening for prostate cancer evidence report and systematic review for the us preventive services task force

Importance Prostate cancer is the second leading cause of cancer death among US men. Objective To systematically review evidence on prostate-specific antigen (PSA)–based prostate cancer screening, treatments for localized prostate cancer, and prebiopsy risk calculators to inform the US Preventive Services Task Force. Data Sources Searches of PubMed, EMBASE, Web of Science, and Cochrane Registries and Databases from July 1, 2011, through July 15, 2017, with a surveillance search on February 1, 2018. Study Selection English-language reports of randomized clinical trials (RCTs) of screening; cohort studies reporting harms; RCTs and cohort studies of active localized cancer treatments vs conservative approaches (eg, active surveillance, watchful waiting); external validations of prebiopsy risk calculators to identify aggressive cancers. Data Extraction and Synthesis One investigator abstracted data; a second checked accuracy. Two investigators independently rated study quality. Main Outcomes and Measures Prostate cancer and all-cause mortality; false-positive screening results, biopsy complications, overdiagnosis; adverse effects of active treatments. Random-effects meta-analyses were conducted for treatment harms. Results Sixty-three studies in 104 publications were included (N = 1 904 950). Randomization to PSA screening was not associated with reduced risk of prostate cancer mortality in either a US trial with substantial control group contamination (n = 76 683) or a UK trial with low adherence to a single PSA screen (n = 408 825) but was associated with significantly reduced prostate cancer mortality in a European trial (n = 162 243; relative risk [RR], 0.79 [95% CI, 0.69-0.91]; absolute risk reduction, 1.1 deaths per 10 000 person-years [95% CI, 0.5-1.8]). Of 61 604 men screened in the European trial, 17.8% received false-positive results. In 3 cohorts (n = 15 136), complications requiring hospitalization occurred in 0.5% to 1.6% of men undergoing biopsy after abnormal screening findings. Overdiagnosis was estimated to occur in 20.7% to 50.4% of screen-detected cancers. In an RCT of men with screen-detected prostate cancer (n = 1643), neither radical prostatectomy (hazard ratio [HR], 0.63 [95% CI, 0.21-1.93]) nor radiation therapy (HR, 0.51 [95% CI, 0.15-1.69]) were associated with significantly reduced prostate cancer mortality vs active monitoring, although each was associated with significantly lower risk of metastatic disease. Relative to conservative management, radical prostatectomy was associated with increased risk of urinary incontinence (pooled RR, 2.27 [95% CI, 1.82-2.84]; 3 trials; n = 1796) and erectile dysfunction (pooled RR, 1.82 [95% CI, 1.62-2.04]; 2 trials; n = 883). Relative to conservative management (8 cohort studies; n = 3066), radiation therapy was associated with increased risk of erectile dysfunction (pooled RR, 1.31 [95% CI, 1.20-1.42]). Conclusions and Relevance PSA screening may reduce prostate cancer mortality risk but is associated with false-positive results, biopsy complications, and overdiagnosis. Compared with conservative approaches, active treatments for screen-detected prostate cancer have unclear effects on long-term survival but are associated with sexual and urinary difficulties.

Screening for Cervical Cancer With High-Risk Human Papillomavirus Testing: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force

Importance Cervical cancer can be prevented with detection and treatment of precancerous cell changes caused primarily by high-risk types of human papillomavirus (hrHPV), the causative agents in more than 90% of cervical cancers. Objective To systematically review benefits and harms of cervical cancer screening for hrHPV to inform the US Preventive Services Task Force. Data Sources MEDLINE, PubMed, PsycINFO, and the Cochrane Collaboration Registry of Controlled Trials from January 2011 through February 15, 2017; surveillance through May 25, 2018. Study Selection Randomized clinical trials (RCTs) and cohort studies comparing primary hrHPV screening alone or hrHPV cotesting (both hrHPV testing and cytology) with cytology (Papanicolaou [Pap] test) screening alone. Data Extraction and Synthesis Two investigators independently reviewed abstracts and full-text articles and quality rated included studies; data were qualitatively synthesized. Main Outcomes and Measures Invasive cervical cancer; cervical intraepithelial neoplasia (CIN); false-positive, colposcopy, and biopsy rates; psychological harms. Results Eight RCTs (n = 410 556), 5 cohort studies (n = 402 615), and 1 individual participant data (IPD) meta-analysis (n = 176 464) were included. Trials were heterogeneous for screening interval, number of rounds, and protocol. For primary hrHPV screening, evidence was consistent across 4 trials demonstrating increased detection of CIN 3 or worse (CIN 3+) in round 1 (relative risk [RR] range, 1.61 [95% CI, 1.09-2.37] to 7.46 [95% CI, 1.02-54.66]). Among 4 hrHPV cotesting trials, first-round CIN 3+ detection was not significantly different between screening groups; RRs for cumulative CIN 3+ detection over 2 screening rounds ranged from 0.91 to 1.13. In first-round screening, false-positive rates for primary hrHPV screening ranged from 6.6% to 7.4%, compared with 2.6% to 6.5% for cytology. For cotesting, false-positives ranged from 5.8% to 19.9% in the first round of screening, compared with 2.6% to 10.9% for cytology. First-round colposcopy rates were also higher, ranging 1.2% to 7.9% for primary hrHPV testing, compared with 1.1% to 3.1% for cytology alone; colposcopy rates for cotesting ranged from 6.8% to 10.9%, compared with 3.3% to 5.2% for cytology alone. The IPD meta-analysis of data from 4 cotesting trials and 1 primary hrHPV screening trial found lower risk of invasive cervical cancer with any hrHPV screening compared with cytology alone (pooled RR, 0.60 [95% CI, 0.40-0.89]). Conclusions and Relevance Primary hrHPV screening detected higher rates of CIN 3+ at first-round screening compared with cytology. Cotesting trials did not show initial increased CIN 3+ detection. Both hrHPV screening strategies had higher false-positive and colposcopy rates than cytology, which could lead to more treatments with potential harms.

Supplemental Screening for Breast Cancer in Women With Dense Breasts: A Systematic Review for the U.S. Preventive Services Task ForceSupplemental Breast Cancer Screening in Women With Dense Breasts

Dense breasts are defined by mammographic appearance. The American College of Radiologys (ACRs) Breast Imaging Reporting and Data System (BI-RADS) classifies breasts as almost entirely fatty (BI-RADS category a), scattered areas of fibroglandular density (category b), heterogeneously dense (category c), or extremely dense (category d). About 27.6 million (43%) women aged 40 to 74 years in the United States have dense breasts; most of these are classified as category c (1). Higher breast density is associated with decreased mammographic sensitivity and specificity and also with increased breast cancer risk. The relative hazard of breast cancer for women with dense breasts ranged from 1.50 (women aged 65 to 74 years) to 1.83 (women aged 40 to 49 years) in an analysis of 1169248 women enrolled in the Breast Cancer Surveillance Consortium (unpublished data). Increased breast density has been associated with hormone replacement therapy use, younger age, and lower body mass index (2). Data on breast density and race or ethnicity are limited. In the United States, Asian women have higher breast density (3) but lower than average incidence of breast cancer (4). Increased breast density is not associated with higher breast cancer mortality among women with dense breasts diagnosed with breast cancer, after adjustment for stage and mode of detection (5). Supplemental breast cancer screening with additional screening modalities has been proposed to improve the early detection of breast cancers. No clinical guidelines explicitly recommend use of supplemental breast cancer screening on women with dense breasts (69), but as of September 2015, 24 states had enacted legislation requiring that women be notified of breast density with their mammography results; 9 more states are considering mandatory notification (10) (Appendix Table 1). Most states require specific language distinguishing dense (BI-RADS c and d) from nondense breasts, and 4 states require that insurers cover subsequent examinations and tests for women with dense breasts (1114). Federal legislation requiring breast density notification is pending (15). Appendix Table 1. Breast Density Legislation in the United States This report summarizes a systematic review of current evidence on the reproducibility of BI-RADS breast density determinations and on test performance characteristics and outcomes of supplemental screening of women with dense breasts by using hand-held ultrasonography (HHUS), automated whole-breast ultrasonography (ABUS), breast magnetic resonance imaging (MRI), and digital breast tomosynthesis (DBT). Mandatory reporting laws frame notification of women as dense/nondense, so this review focused on this categorization. Methods The review protocol included an analytic framework with 4 key questions (KQs) (Appendix Figure 1). Detailed methods, including search strategies, detailed inclusion criteria, and excluded studies, are available in the full evidence report (16). Appendix Figure 1. Analytic framework. BI-RADS = Breast Imaging Reporting and Data System; DCIS = ductal carcinoma in-situ; KQ = key question; MRI = magnetic resonance imaging. Data Sources and Searches MEDLINE, PubMed, EMBASE, and the Cochrane Library were searched for relevant English-language studies published between January 2000 and July 2015. We reviewed reference lists from retrieved articles and references suggested by experts. Study Selection Two investigators independently reviewed abstracts and full-text articles for inclusion according to predetermined criteria (E.P.W. and J.H.T. for KQ 1, J.M. and J.J.F. for KQs 2 to 4). Included studies examining the reproducibility of BI-RADS breast density categorization focused on asymptomatic women aged 40 years or older undergoing digital or film mammography. Included studies on supplemental screening with HHUS, ABUS, MRI, or DBT reported outcomes for asymptomatic women with dense breasts aged 40 years and older. In studies that focused primarily on women at high risk for breast cancer (including those with preexisting breast cancer or high-risk breast lesions [such as ductal carcinoma in situ, atypical hyperplasia, and lobular carcinoma in situ], BRCA mutations, familial breast cancer syndromes, or previous chest-wall radiation) and studies that included women with nondense breasts, we analyzed the relevant subset when available in the publication or provided by the authors. A priori inclusion criteria limited studies on BI-RADS reproducibility to fair- or good-quality randomized, controlled trials; cohort studies; or test sets involving multiple blind readings by at least 3 readers. Studies on test performance characteristics and outcomes of supplemental screening modalities were limited to fair- or good-quality randomized, controlled trials; cohort studies; or diagnostic accuracy studies with reference standards applied to all participants. We examined sensitivity, specificity, positive predictive values (PPVs), negative predictive values (NPVs), and available clinical outcomes (including cancer detection rates, recall rates, and biopsy rates). We defined recall as the need for any additional diagnostic testing after supplemental screening, including imaging and biopsy. Data Extraction and Quality Assessment Two investigators (E.P.W. and J.H.T. for KQ 1, J.M. and J.J.F. for KQs 2 to 4) critically appraised all included studies independently using the U.S. Preventive Services Task Forces (USPSTFs) design-specific criteria (17), supplemented with the National Institute for Health and Clinical Excellence methodology checklists (18) and the Quality Appraisal Tool for Studies of Diagnostic Reliability (19). According to USPSTF criteria, a good-quality study generally met all prespecified criteria; fair-quality studies did not meet all criteria but had no important limitations. Poor-quality studies had important limitations that could invalidate results (inadequate or biased application of reference standard; population limited to very high-risk patients). Data Synthesis and Analysis When available or provided by the authors, results of supplemental screening for subgroups of women with dense breasts were extracted; we excluded those with other risk factors for breast cancer. We calculated the sensitivity and specificity of the supplemental breast screening tests for women with negative mammography results. Only cancers detected by the supplemental test after negative mammography results and cancers found at interval follow-up were included. Hence, the values reported represent the sensitivity and specificity for detection of additional cancer in women with negative mammography findings. Similarly, we defined cancer detection rates, recall rates, and biopsy rates to include only those cancer cases, recalls, and biopsies related to supplemental screening after negative results on mammography. Meta-analysis was not performed because there were few good-quality studies. Role of the Funding Source This research was funded by the Agency for Healthcare Research and Quality (AHRQ) under a contract to support the work of the USPSTF. The investigators worked with USPSTF members to develop and refine the scope, analytic frameworks, and KQs. AHRQ had no role in study selection, quality assessment, synthesis, or development of conclusions. AHRQ provided project oversight; reviewed the draft report; and distributed the draft for peer review, including to representatives of professional societies and federal agencies. AHRQ performed a final review of the manuscript to ensure that the analysis met methodological standards. The investigators are solely responsible for the content and the decision to submit the manuscript for publication. Results The literature search yielded 2067 unique citations; 128 full-text articles considered potentially relevant were reviewed to identify 24 unique studies meeting inclusion criteria (Appendix Figure 2). Table 1 (2043) provides the characteristics of included studies. No studies addressed the effect of supplemental screening (compared with women without supplemental screening) on breast cancer morbidity or mortality. Appendix Figure 2. Summary of evidence search and selection. KQ = key question. Table 1. Characteristics of Included Studies Accuracy and Reliability of BI-RADS Density Determination Absent a gold standard for breast density, studies could not evaluate the accuracy of BI-RADS density determinations. Five studies reported repeated assignment of categorical BI-RADS breast density classification by the same or different radiologists, altogether including more than 440000 women, almost all with data from 2 sequential screening mammograms. To reflect current U.S. practice, we included only studies based on the BI-RADS density categories. The 3 largest studies were set in the United States. Two used data from the Breast Cancer Surveillance Consortium (20, 22), and the third presented findings from community radiologists conducting repeated readings of a large screening test set (24). Two other small studies (not discussed here) were based on mammographic screening programs in Spain (21) and Italy (23). All United Statesbased studies reflected community practice by use of clinical readings from community screening programs or test set readings by practicing community radiologists without additional training. Overall, group prevalence of BI-RADS density ratings was similar across initial and subsequent examinations among community radiologists (Appendix Table 2), but there was greater disagreement at the individual level. On subsequent screening examinations, approximately 1 in 5 women (23%) was placed in a different BI-RADS density category (a, b, c, d) by the same radiologist, while approximately 1 in 3 was categorized differently when a different radiologist read the subsequent examination result (Table 2). Considering clinical interpretations that combine categories (dense representing those with BI-RAD