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Ray KM. Interval Cancers in Understanding Screening Outcomes. Radiol Clin North Am 2024; 62:559-569. [PMID: 38777533 DOI: 10.1016/j.rcl.2023.12.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/25/2024]
Abstract
Interval breast cancers are not detected at routine screening and are diagnosed in the interval between screening examinations. A variety of factors contribute to interval cancers, including patient and tumor characteristics as well as the screening technique and frequency. The interval cancer rate is an important metric by which the effectiveness of screening may be assessed and may serve as a surrogate for mortality benefit.
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Affiliation(s)
- Kimberly M Ray
- Department of Radiology and Biomedical Sciences, University of California, San Francisco, UCSF Medical Center, 1825 4th Street, L3185, Box 4034, San Francisco, CA 94107, USA.
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Trentham-Dietz A, Chapman CH, Jayasekera J, Lowry KP, Heckman-Stoddard BM, Hampton JM, Caswell-Jin JL, Gangnon RE, Lu Y, Huang H, Stein S, Sun L, Gil Quessep EJ, Yang Y, Lu Y, Song J, Muñoz DF, Li Y, Kurian AW, Kerlikowske K, O'Meara ES, Sprague BL, Tosteson ANA, Feuer EJ, Berry D, Plevritis SK, Huang X, de Koning HJ, van Ravesteyn NT, Lee SJ, Alagoz O, Schechter CB, Stout NK, Miglioretti DL, Mandelblatt JS. Collaborative Modeling to Compare Different Breast Cancer Screening Strategies: A Decision Analysis for the US Preventive Services Task Force. JAMA 2024; 331:1947-1960. [PMID: 38687505 DOI: 10.1001/jama.2023.24766] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/02/2024]
Abstract
Importance The effects of breast cancer incidence changes and advances in screening and treatment on outcomes of different screening strategies are not well known. Objective To estimate outcomes of various mammography screening strategies. Design, Setting, and Population Comparison of outcomes using 6 Cancer Intervention and Surveillance Modeling Network (CISNET) models and national data on breast cancer incidence, mammography performance, treatment effects, and other-cause mortality in US women without previous cancer diagnoses. Exposures Thirty-six screening strategies with varying start ages (40, 45, 50 years) and stop ages (74, 79 years) with digital mammography or digital breast tomosynthesis (DBT) annually, biennially, or a combination of intervals. Strategies were evaluated for all women and for Black women, assuming 100% screening adherence and "real-world" treatment. Main Outcomes and Measures Estimated lifetime benefits (breast cancer deaths averted, percent reduction in breast cancer mortality, life-years gained), harms (false-positive recalls, benign biopsies, overdiagnosis), and number of mammograms per 1000 women. Results Biennial screening with DBT starting at age 40, 45, or 50 years until age 74 years averted a median of 8.2, 7.5, or 6.7 breast cancer deaths per 1000 women screened, respectively, vs no screening. Biennial DBT screening at age 40 to 74 years (vs no screening) was associated with a 30.0% breast cancer mortality reduction, 1376 false-positive recalls, and 14 overdiagnosed cases per 1000 women screened. Digital mammography screening benefits were similar to those for DBT but had more false-positive recalls. Annual screening increased benefits but resulted in more false-positive recalls and overdiagnosed cases. Benefit-to-harm ratios of continuing screening until age 79 years were similar or superior to stopping at age 74. In all strategies, women with higher-than-average breast cancer risk, higher breast density, and lower comorbidity level experienced greater screening benefits than other groups. Annual screening of Black women from age 40 to 49 years with biennial screening thereafter reduced breast cancer mortality disparities while maintaining similar benefit-to-harm trade-offs as for all women. Conclusions This modeling analysis suggests that biennial mammography screening starting at age 40 years reduces breast cancer mortality and increases life-years gained per mammogram. More intensive screening for women with greater risk of breast cancer diagnosis or death can maintain similar benefit-to-harm trade-offs and reduce mortality disparities.
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Affiliation(s)
- Amy Trentham-Dietz
- Department of Population Health Sciences and Carbone Cancer Center, School of Medicine and Public Health, University of Wisconsin-Madison
| | - Christina Hunter Chapman
- Department of Radiation Oncology and Center for Innovations in Quality, Safety, and Effectiveness, Baylor College of Medicine, Houston, Texas
| | - Jinani Jayasekera
- Health Equity and Decision Sciences (HEADS) Research Laboratory, Division of Intramural Research at the National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, Maryland
| | | | - Brandy M Heckman-Stoddard
- Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - John M Hampton
- Department of Population Health Sciences and Carbone Cancer Center, School of Medicine and Public Health, University of Wisconsin-Madison
| | | | - Ronald E Gangnon
- Department of Population Health Sciences and Carbone Cancer Center, School of Medicine and Public Health, University of Wisconsin-Madison
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison
| | - Ying Lu
- Stanford University, Stanford, California
| | - Hui Huang
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Sarah Stein
- Harvard Pilgrim Health Care Institute, Boston, Massachusetts
| | - Liyang Sun
- Stanford University, Stanford, California
| | | | | | - Yifan Lu
- Department of Industrial and Systems Engineering and Carbone Cancer Center, University of Wisconsin-Madison
| | - Juhee Song
- University of Texas MD Anderson Cancer Center, Houston
| | | | - Yisheng Li
- University of Texas MD Anderson Cancer Center, Houston
| | - Allison W Kurian
- Departments of Medicine and Epidemiology and Population Health, Stanford University, Stanford, California
| | - Karla Kerlikowske
- Departments of Medicine and Epidemiology and Biostatistics, University of California San Francisco
| | - Ellen S O'Meara
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | | | - Anna N A Tosteson
- Dartmouth Institute for Health Policy and Clinical Practice and Departments of Medicine and Community and Family Medicine, Dartmouth Geisel School of Medicine, Hanover, New Hampshire
| | - Eric J Feuer
- Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Donald Berry
- University of Texas MD Anderson Cancer Center, Houston
| | - Sylvia K Plevritis
- Departments of Biomedical Data Science and Radiology, Stanford University, Stanford, California
| | - Xuelin Huang
- University of Texas MD Anderson Cancer Center, Houston
| | | | | | - Sandra J Lee
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Oguzhan Alagoz
- Department of Industrial and Systems Engineering and Carbone Cancer Center, University of Wisconsin-Madison
| | | | - Natasha K Stout
- Harvard Pilgrim Health Care Institute, Boston, Massachusetts
- Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Diana L Miglioretti
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
- Department of Public Health Sciences, University of California Davis
| | - Jeanne S Mandelblatt
- Departments of Oncology and Medicine, Georgetown University Medical Center, and Georgetown Lombardi Comprehensive Institute for Cancer and Aging Research at Georgetown University Lombardi Comprehensive Cancer Center, Washington, DC
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3
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Nicholson WK, Silverstein M, Wong JB, Barry MJ, Chelmow D, Coker TR, Davis EM, Jaén CR, Krousel-Wood M, Lee S, Li L, Mangione CM, Rao G, Ruiz JM, Stevermer JJ, Tsevat J, Underwood SM, Wiehe S. Screening for Breast Cancer: US Preventive Services Task Force Recommendation Statement. JAMA 2024; 331:1918-1930. [PMID: 38687503 DOI: 10.1001/jama.2024.5534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/02/2024]
Abstract
Importance Among all US women, breast cancer is the second most common cancer and the second most common cause of cancer death. In 2023, an estimated 43 170 women died of breast cancer. Non-Hispanic White women have the highest incidence of breast cancer and non-Hispanic Black women have the highest mortality rate. Objective The USPSTF commissioned a systematic review to evaluate the comparative effectiveness of different mammography-based breast cancer screening strategies by age to start and stop screening, screening interval, modality, use of supplemental imaging, or personalization of screening for breast cancer on the incidence of and progression to advanced breast cancer, breast cancer morbidity, and breast cancer-specific or all-cause mortality, and collaborative modeling studies to complement the evidence from the review. Population Cisgender women and all other persons assigned female at birth aged 40 years or older at average risk of breast cancer. Evidence Assessment The USPSTF concludes with moderate certainty that biennial screening mammography in women aged 40 to 74 years has a moderate net benefit. The USPSTF concludes that the evidence is insufficient to determine the balance of benefits and harms of screening mammography in women 75 years or older and the balance of benefits and harms of supplemental screening for breast cancer with breast ultrasound or magnetic resonance imaging (MRI), regardless of breast density. Recommendation The USPSTF recommends biennial screening mammography for women aged 40 to 74 years. (B recommendation) The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of screening mammography in women 75 years or older. (I statement) The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of supplemental screening for breast cancer using breast ultrasonography or MRI in women identified to have dense breasts on an otherwise negative screening mammogram. (I statement).
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Affiliation(s)
| | | | - John B Wong
- Tufts University School of Medicine, Boston, Massachusetts
| | | | | | | | - Esa M Davis
- University of Maryland School of Medicine, Baltimore
| | | | | | - Sei Lee
- University of California, San Francisco
| | - Li Li
- University of Virginia, Charlottesville
| | | | - Goutham Rao
- Case Western Reserve University, Cleveland, Ohio
| | | | | | - Joel Tsevat
- The University of Texas Health Science Center, San Antonio
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4
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Henderson JT, Webber EM, Weyrich MS, Miller M, Melnikow J. Screening for Breast Cancer: Evidence Report and Systematic Review for the US Preventive Services Task Force. JAMA 2024; 331:1931-1946. [PMID: 38687490 DOI: 10.1001/jama.2023.25844] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/02/2024]
Abstract
Importance Breast cancer is a leading cause of cancer mortality for US women. Trials have established that screening mammography can reduce mortality risk, but optimal screening ages, intervals, and modalities for population screening guidelines remain unclear. Objective To review studies comparing different breast cancer screening strategies for the US Preventive Services Task Force. Data Sources MEDLINE, Cochrane Library through August 22, 2022; literature surveillance through March 2024. Study Selection English-language publications; randomized clinical trials and nonrandomized studies comparing screening strategies; expanded criteria for screening harms. Data Extraction and Synthesis Two reviewers independently assessed study eligibility and quality; data extracted from fair- and good-quality studies. Main Outcomes and Measures Mortality, morbidity, progression to advanced cancer, interval cancers, screening harms. Results Seven randomized clinical trials and 13 nonrandomized studies were included; 2 nonrandomized studies reported mortality outcomes. A nonrandomized trial emulation study estimated no mortality difference for screening beyond age 74 years (adjusted hazard ratio, 1.00 [95% CI, 0.83 to 1.19]). Advanced cancer detection did not differ following annual or biennial screening intervals in a nonrandomized study. Three trials compared digital breast tomosynthesis (DBT) mammography screening with digital mammography alone. With DBT, more invasive cancers were detected at the first screening round than with digital mammography, but there were no statistically significant differences in interval cancers (pooled relative risk, 0.87 [95% CI, 0.64-1.17]; 3 studies [n = 130 196]; I2 = 0%). Risk of advanced cancer (stage II or higher) at the subsequent screening round was not statistically significant for DBT vs digital mammography in the individual trials. Limited evidence from trials and nonrandomized studies suggested lower recall rates with DBT. An RCT randomizing individuals with dense breasts to invitations for supplemental screening with magnetic resonance imaging reported reduced interval cancer risk (relative risk, 0.47 [95% CI, 0.29-0.77]) and additional false-positive recalls and biopsy results with the intervention; no longer-term advanced breast cancer incidence or morbidity and mortality outcomes were available. One RCT and 1 nonrandomized study of supplemental ultrasound screening reported additional false-positives and no differences in interval cancers. Conclusions and Relevance Evidence comparing the effectiveness of different breast cancer screening strategies is inconclusive because key studies have not yet been completed and few studies have reported the stage shift or mortality outcomes necessary to assess relative benefits.
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Affiliation(s)
- Jillian T Henderson
- Kaiser Permanente Evidence-based Practice Center, Center for Health Research, Portland, Oregon
| | - Elizabeth M Webber
- Kaiser Permanente Evidence-based Practice Center, Center for Health Research, Portland, Oregon
| | - Meghan S Weyrich
- University of California Davis Center for Healthcare Policy and Research, Sacramento
| | - Marykate Miller
- University of California Davis Center for Healthcare Policy and Research, Sacramento
| | - Joy Melnikow
- University of California Davis Center for Healthcare Policy and Research, Sacramento
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5
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Yoon SC, Ballantyne N, Grimm LJ, Baker JA. Impact of Interruptions During Screening Mammography on Physician Well-Being and Patient Care. J Am Coll Radiol 2024; 21:896-904. [PMID: 38056581 DOI: 10.1016/j.jacr.2023.11.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 10/26/2023] [Accepted: 11/07/2023] [Indexed: 12/08/2023]
Abstract
OBJECTIVE To assess the impact of interruptions on radiologists' efficiency, accuracy, and job satisfaction in interpreting screening mammograms. METHODS This institutional review board-approved retrospective reader study recruited nine breast radiologists from a single academic institution [name withheld] to interpret 150 screening mammograms performed between December 1, 2008, and December 31, 2015 under two different reading conditions, as follows: (1) uninterrupted batch reading and (2) interrupted reading. The 150 cases consisted of 125 normal mammograms and 25 mammograms with subtle breast cancers. Cases were divided into two groups of 75 cases each (cohort 1 and cohort 2), with a comparable distribution of cancer cases. Four rounds of 75 cases each were conducted with a 6-week washout period between rounds 2 and 3. After completing each interpretation session, readers completed a seven-question survey, assessing perceptions of mental and physical effort, level of frustration, and performance satisfaction. Clinical performance metrics (reading time, recall rate, sensitivity, specificity, accuracy, and positive predictive value 1) were calculated. RESULTS Recall rates were significantly (P = .04) higher during interrupted reading sessions (35.4%) than they were during uninterrupted batch reading sessions (31.4%). Accuracy was significantly (P = .049) worse in the interrupted reading sessions (69.5%), compared with uninterrupted sessions (73.6%). Differences in overall image interpretation times were not statistically significant (P = .065). Compared with uninterrupted batch reading sessions, readers during interrupted sessions reported feeling busier (P < .001), encountered higher levels of cognitive demand (P = .005), experienced elevated levels of physical fatigue (P = .004), and expressed lower levels of satisfaction with their performance (P = .041). CONCLUSION Interruptions during interpretation of screening mammography have deleterious effects on physician performance and their sense of well-being.
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Affiliation(s)
- Sora C Yoon
- Fellowship Director, Duke Breast Imaging, Department of Radiology, Duke University Medical Center, Durham, North Carolina.
| | - Nancy Ballantyne
- Breast Imaging Radiologist, Greensboro Radiology, Greensboro, North Carolina
| | - Lars J Grimm
- Department of Radiology, Duke University Medical Center, Durham, North Carolina; and Chair, National Mammography Database, ACR
| | - Jay A Baker
- Vice Chair, Faculty Affairs & Appointments, Promotions, Department of Radiology, Duke University Medical Center, Durham, North Carolina
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Marcon M, Fuchsjäger MH, Clauser P, Mann RM. ESR Essentials: screening for breast cancer - general recommendations by EUSOBI. Eur Radiol 2024:10.1007/s00330-024-10740-5. [PMID: 38656711 DOI: 10.1007/s00330-024-10740-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 02/13/2024] [Accepted: 02/17/2024] [Indexed: 04/26/2024]
Abstract
Breast cancer is the most frequently diagnosed cancer in women accounting for about 30% of all new cancer cases and the incidence is constantly increasing. Implementation of mammographic screening has contributed to a reduction in breast cancer mortality of at least 20% over the last 30 years. Screening programs usually include all women irrespective of their risk of developing breast cancer and with age being the only determining factor. This approach has some recognized limitations, including underdiagnosis, false positive cases, and overdiagnosis. Indeed, breast cancer remains a major cause of cancer-related deaths in women undergoing cancer screening. Supplemental imaging modalities, including digital breast tomosynthesis, ultrasound, breast MRI, and, more recently, contrast-enhanced mammography, are available and have already shown potential to further increase the diagnostic performances. Use of breast MRI is recommended in high-risk women and women with extremely dense breasts. Artificial intelligence has also shown promising results to support risk categorization and interval cancer reduction. The implementation of a risk-stratified approach instead of a "one-size-fits-all" approach may help to improve the benefit-to-harm ratio as well as the cost-effectiveness of breast cancer screening. KEY POINTS: Regular mammography should still be considered the mainstay of the breast cancer screening. High-risk women and women with extremely dense breast tissue should use MRI for supplemental screening or US if MRI is not available. Women need to participate actively in the decision to undergo personalized screening. KEY RECOMMENDATIONS: Mammography is an effective imaging tool to diagnose breast cancer in an early stage and to reduce breast cancer mortality (evidence level I). Until more evidence is available to move to a personalized approach, regular mammography should be considered the mainstay of the breast cancer screening. High-risk women should start screening earlier; first with yearly breast MRI which can be supplemented by yearly or biennial mammography starting at 35-40 years old (evidence level I). Breast MRI screening should be also offered to women with extremely dense breasts (evidence level I). If MRI is not available, ultrasound can be performed as an alternative, although the added value of supplemental ultrasound regarding cancer detection remains limited. Individual screening recommendations should be made through a shared decision-making process between women and physicians.
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Affiliation(s)
- Magda Marcon
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland.
- Institute of Radiology, Hospital Lachen, Oberdorfstrasse 41, 8853, Lachen, Switzerland.
| | - Michael H Fuchsjäger
- Division of General Radiology, Department of Radiology, Medical University Graz, Auenbruggerplatz 9, 8036, Graz, Austria
| | - Paola Clauser
- Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Research Group: Molecular and Gender Imaging, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Wien, Austria
| | - Ritse M Mann
- Department of Diagnostic Imaging, Radboud University Medical Centre, Geert Grotteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands
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Cai L, Sidey-Gibbons C, Nees J, Riedel F, Schäfgen B, Togawa R, Killinger K, Heil J, Pfob A, Golatta M. Can multi-modal radiomics using pretreatment ultrasound and tomosynthesis predict response to neoadjuvant systemic treatment in breast cancer? Eur Radiol 2024; 34:2560-2573. [PMID: 37707548 PMCID: PMC10957593 DOI: 10.1007/s00330-023-10238-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 07/17/2023] [Accepted: 08/01/2023] [Indexed: 09/15/2023]
Abstract
OBJECTIVES Response assessment to neoadjuvant systemic treatment (NAST) to guide individualized treatment in breast cancer is a clinical research priority. We aimed to develop an intelligent algorithm using multi-modal pretreatment ultrasound and tomosynthesis radiomics features in addition to clinical variables to predict pathologic complete response (pCR) prior to the initiation of therapy. METHODS We used retrospective data on patients who underwent ultrasound and tomosynthesis before starting NAST. We developed a support vector machine algorithm using pretreatment ultrasound and tomosynthesis radiomics features in addition to patient and tumor variables to predict pCR status (ypT0 and ypN0). Findings were compared to the histopathologic evaluation of the surgical specimen. The main outcome measures were area under the curve (AUC) and false-negative rate (FNR). RESULTS We included 720 patients, 504 in the development set and 216 in the validation set. Median age was 51.6 years and 33.6% (242 of 720) achieved pCR. The addition of radiomics features significantly improved the performance of the algorithm (AUC 0.72 to 0.81; p = 0.007). The FNR of the multi-modal radiomics and clinical algorithm was 6.7% (10 of 150 with missed residual cancer). Surface/volume ratio at tomosynthesis and peritumoral entropy characteristics at ultrasound were the most relevant radiomics. Hormonal receptors and HER-2 status were the most important clinical predictors. CONCLUSION A multi-modal machine learning algorithm with pretreatment clinical, ultrasound, and tomosynthesis radiomics features may aid in predicting residual cancer after NAST. Pending prospective validation, this may facilitate individually tailored NAST regimens. CLINICAL RELEVANCE STATEMENT Multi-modal radiomics using pretreatment ultrasound and tomosynthesis showed significant improvement in assessing response to NAST compared to an algorithm using clinical variables only. Further prospective validation of our findings seems warranted to enable individualized predictions of NAST outcomes. KEY POINTS • We proposed a multi-modal machine learning algorithm with pretreatment clinical, ultrasound, and tomosynthesis radiomics features to predict response to neoadjuvant breast cancer treatment. • Compared with the clinical algorithm, the AUC of this integrative algorithm is significantly higher. • Used prior to the initiative of therapy, our algorithm can identify patients who will experience pathologic complete response following neoadjuvant therapy with a high negative predictive value.
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Affiliation(s)
- Lie Cai
- Department of Obstetrics and Gynecology, Heidelberg University Hospital, Im Neuenheimer Feld 440, 69120, Heidelberg, Germany
| | - Chris Sidey-Gibbons
- Department of Symptom Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- MD Anderson Center for INSPiRED Cancer Care (Integrated Systems for Patient-Reported Data), The University of Texas MD Anderson Cancer Center, Houston, USA
| | - Juliane Nees
- Department of Obstetrics and Gynecology, Heidelberg University Hospital, Im Neuenheimer Feld 440, 69120, Heidelberg, Germany
| | - Fabian Riedel
- Department of Obstetrics and Gynecology, Heidelberg University Hospital, Im Neuenheimer Feld 440, 69120, Heidelberg, Germany
| | - Benedikt Schäfgen
- Department of Obstetrics and Gynecology, Heidelberg University Hospital, Im Neuenheimer Feld 440, 69120, Heidelberg, Germany
| | - Riku Togawa
- Department of Obstetrics and Gynecology, Heidelberg University Hospital, Im Neuenheimer Feld 440, 69120, Heidelberg, Germany
| | - Kristina Killinger
- Department of Obstetrics and Gynecology, Heidelberg University Hospital, Im Neuenheimer Feld 440, 69120, Heidelberg, Germany
| | - Joerg Heil
- Department of Obstetrics and Gynecology, Heidelberg University Hospital, Im Neuenheimer Feld 440, 69120, Heidelberg, Germany
| | - André Pfob
- Department of Obstetrics and Gynecology, Heidelberg University Hospital, Im Neuenheimer Feld 440, 69120, Heidelberg, Germany.
- MD Anderson Center for INSPiRED Cancer Care (Integrated Systems for Patient-Reported Data), The University of Texas MD Anderson Cancer Center, Houston, USA.
- National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Michael Golatta
- Department of Obstetrics and Gynecology, Heidelberg University Hospital, Im Neuenheimer Feld 440, 69120, Heidelberg, Germany.
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Loveland J, Mackenzie A. Radiation doses received in the UK breast screening programmes 2019-2023. Br J Radiol 2024; 97:787-793. [PMID: 38291906 PMCID: PMC11027334 DOI: 10.1093/bjr/tqad039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 11/05/2023] [Accepted: 11/20/2023] [Indexed: 02/01/2024] Open
Abstract
OBJECTIVE To report the latest UK mammography dose survey results and to compare radiation doses from digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) in UK breast screening. METHODS Anonymized exposure factors were collected for 111 152 screening cases and 5113 assessment cases from 405 x-ray sets across the United Kingdom using an online submission system linked to a national database of mammography quality control data. Output and beam quality measurements from each set were combined with exposure data to estimate mean glandular doses (MGD). RESULTS FFDM doses increased by ∼10% compared to the 2016-2019 national survey but compressed breast thicknesses (CBT) remained similar. DBT doses were 34%-40% higher than FFDM overall and 34% higher than FFDM for breasts 50-60 mm thick. We found a possible overestimation of PMMA breast equivalent thicknesses at low CBTs, but the evidence was not conclusive. CONCLUSION Recent changes to the mix of x-ray models in use in UK breast screening have resulted in higher FFDM breast doses. DBT doses in the NHSBSP are on average higher than FFDM by ∼34%-40%. ADVANCES IN KNOWLEDGE This is the first national study to report DBT and FFDM MGDs in UK breast screening.
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Affiliation(s)
- John Loveland
- National Coordinating Centre for the Physics in Mammography (NCCPM), Royal Surrey NHS Foundation Trust, 18 Frederick Sanger Road Surrey Research Park, Guildford, GU2 7YD, United Kingdom
| | - Alistair Mackenzie
- National Coordinating Centre for the Physics in Mammography (NCCPM), Royal Surrey NHS Foundation Trust, 18 Frederick Sanger Road Surrey Research Park, Guildford, GU2 7YD, United Kingdom
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Giorgi Rossi P, Mancuso P, Pattacini P, Campari C, Nitrosi A, Iotti V, Ponti A, Frigerio A, Correale L, Riggi E, Giordano L, Segnan N, Di Leo G, Magni V, Sardanelli F, Fornasa F, Romanucci G, Montemezzi S, Falini P, Auzzi N, Zappa M, Ottone M, Mantellini P, Duffy SW, Armaroli P, Coriani C, Pescarolo M, Stefanelli G, Tondelli G, Beretti F, Caffarri S, Marchesi V, Canovi L, Colli M, Boschini M, Bertolini M, Ragazzi M, Pattacini P, Giorgi Rossi P, Iotti V, Ginocchi V, Ravaioli S, Vacondio R, Campari C, Caroli S, Nitrosi A, Braglia L, Cavuto S, Mancuso P, Djuric O, Venturelli F, Vicentini M, Braghiroli MB, Lonetti J, Davoli E, Bonelli E, Fornasa F, Montemezzi S, Romanucci G, Lucchi I, Martello G, Rossati C, Mantellini P, Ambrogetti D, Iossa A, Carnesciali E, Mazzalupo V, Falini P, Puliti D, Zappa M, Battisti F, Auzzi N, Verdi S, Degl'Innocenti C, Tramalloni D, Cavazza E, Busoni S, Betti E, Peruzzi F, Regini F, Sardanelli F, Di Leo G, Carbonaro LA, Magni V, Cozzi A, Spinelli D, Monaco CG, Schiaffino S, Benedek A, Menicagli L, Ferraris R, Favettini E, Dettori D, Falco P, Presti P, Segnan N, Ponti A, Frigerio A, Armaroli P, Correale L, Marra V, Milanesio L, Artuso F, Di Leo A, Castellano I, Riggi E, Casella D, Pitarella S, Vergini V, Giordano L, Duffy SW, Graewingholt A, Lang K, Falcini F. Comparing accuracy of tomosynthesis plus digital mammography or synthetic 2D mammography in breast cancer screening: baseline results of the MAITA RCT consortium. Eur J Cancer 2024; 199:113553. [PMID: 38262307 DOI: 10.1016/j.ejca.2024.113553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 01/01/2024] [Accepted: 01/06/2024] [Indexed: 01/25/2024]
Abstract
AIM The analyses here reported aim to compare the screening performance of digital tomosynthesis (DBT) versus mammography (DM). METHODS MAITA is a consortium of four Italian trials, REtomo, Proteus, Impeto, and MAITA trial. The trials adopted a two-arm randomised design comparing DBT plus DM (REtomo and Proteus) or synthetic-2D (Impeto and MAITA trial) versus DM; multiple vendors were included. Women aged 45 to 69 years were individually randomised to one round of DBT or DM. FINDINGS From March 2014 to February 2022, 50,856 and 63,295 women were randomised to the DBT and DM arm, respectively. In the DBT arm, 6656 women were screened with DBT plus synthetic-2D. Recall was higher in the DBT arm (5·84% versus 4·96%), with differences between centres. With DBT, 0·8/1000 (95% CI 0·3 to 1·3) more women received surgical treatment for a benign lesion. The detection rate was 51% higher with DBT, ie. 2·6/1000 (95% CI 1·7 to 3·6) more cancers detected, with a similar relative increase for invasive cancers and ductal carcinoma in situ. The results were similar below and over the age of 50, at first and subsequent rounds, and with DBT plus DM and DBT plus synthetic-2D. No learning curve was appreciable. Detection of cancers >= 20 mm, with 2 or more positive lymph nodes, grade III, HER2-positive, or triple-negative was similar in the two arms. INTERPRETATION Results from MAITA confirm that DBT is superior to DM for the detection of cancers, with a possible increase in recall rate. DBT performance in screening should be assessed locally while waiting for long-term follow-up results on the impact of advanced cancer incidence.
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Affiliation(s)
| | | | | | - Cinzia Campari
- Screening coordinating centre, AUSL - IRCCS di Reggio Emilia, Italy
| | - Andrea Nitrosi
- Medical Physics unit, AUSL - IRCCS di Reggio Emilia, Italy
| | | | - Antonio Ponti
- SSD Epidemiologia e Screening. AOU Città della Salute e della Scienza, CPO Piemonte Torino, Italy
| | - Alfonso Frigerio
- SSD Senologia di Screening AOU Città della Salute e della Scienza, CPO Piemonte Torino, Italy
| | - Loredana Correale
- SSD Epidemiologia e Screening. AOU Città della Salute e della Scienza, CPO Piemonte Torino, Italy
| | - Emilia Riggi
- SSD Epidemiologia e Screening. AOU Città della Salute e della Scienza, CPO Piemonte Torino, Italy
| | - Livia Giordano
- SSD Epidemiologia e Screening. AOU Città della Salute e della Scienza, CPO Piemonte Torino, Italy
| | - Nereo Segnan
- SSD Epidemiologia e Screening. AOU Città della Salute e della Scienza, CPO Piemonte Torino, Italy
| | - Giovanni Di Leo
- IRCC Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Milan, Italy
| | - Veronica Magni
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milan, Italy
| | - Francesco Sardanelli
- IRCC Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milan, Italy
| | - Francesca Fornasa
- Breast Unit ULSS9 Scaligera, Ospedale Fracastoro, Via Circonvallazione, 1, 37047 San Bonifacio, VR, Italy
| | - Giovanna Romanucci
- Breast Unit ULSS9 Scaligera, Ospedale Fracastoro, Via Circonvallazione, 1, 37047 San Bonifacio, VR, Italy
| | | | - Patrizia Falini
- ISPRO - Istituto per lo Studio, la Prevenzione e la Rete Oncologica, Firenze, Italy
| | - Noemi Auzzi
- ISPRO - Istituto per lo Studio, la Prevenzione e la Rete Oncologica, Firenze, Italy
| | - Marco Zappa
- ISPRO - Istituto per lo Studio, la Prevenzione e la Rete Oncologica, Firenze, Italy
| | - Marta Ottone
- Epidemiology Unit, AUSL - IRCCS di Reggio Emilia, Italy
| | - Paola Mantellini
- ISPRO - Istituto per lo Studio, la Prevenzione e la Rete Oncologica, Firenze, Italy
| | - Stephen W Duffy
- Wolfson Institute of Population Health, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK
| | - Paola Armaroli
- SSD Epidemiologia e Screening. AOU Città della Salute e della Scienza, CPO Piemonte Torino, Italy
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Francesca Fornasa
- Breast Unit ULSS9 Scaligera, Ospedale Fracastoro, Via Circonvallazione, 1, 37047 San Bonifacio, VR, Italy
| | | | - Giovanna Romanucci
- Breast Unit ULSS9 Scaligera, Ospedale Fracastoro, Via Circonvallazione, 1, 37047 San Bonifacio, VR, Italy
| | - Ilaria Lucchi
- Breast Unit ULSS9 Scaligera, Ospedale Fracastoro, Via Circonvallazione, 1, 37047 San Bonifacio, VR, Italy
| | - Gessica Martello
- Breast Unit ULSS9 Scaligera, Ospedale Fracastoro, Via Circonvallazione, 1, 37047 San Bonifacio, VR, Italy
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Giovanni Di Leo
- IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy
| | | | - Veronica Magni
- IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy
| | - Andrea Cozzi
- IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy
| | - Diana Spinelli
- IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy
| | | | | | - Adrienn Benedek
- IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy
| | - Laura Menicagli
- IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Axel Graewingholt
- Mammographiescreening-Zentrum Paderborn, Breast Cancer Screening, Paderborn, NRW, Germany
| | - Kristina Lang
- Departement of Translational Medicine, Lund University, Unilabs Mammography Unit, Skåne University Hospital, Malmö, Sweden
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10
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Onega T, Abraham L, Miglioretti DL, Lee CI, Henderson LM, Kerlikowske K, Tosteson ANA, Weaver D, Sprague BL, Bowles EJA, di Florio-Alexander RM. Digital mammography and digital breast tomosynthesis for detecting invasive lobular and ductal carcinoma. Breast Cancer Res Treat 2023; 202:505-514. [PMID: 37697031 DOI: 10.1007/s10549-023-07051-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 07/13/2023] [Indexed: 09/13/2023]
Abstract
PURPOSE Invasive lobular carcinoma (ILC) is a distinct histological subtype of breast cancer that can make early detection with mammography challenging. We compared imaging performance of digital breast tomosynthesis (DBT) to digital mammography (DM) for diagnoses of ILC, invasive ductal carcinoma (IDC), and invasive mixed carcinoma (IMC) in a screening population. METHODS We included screening exams (DM; n = 1,715,249 or DBT; n = 414,793) from 2011 to 2018 among 839,801 women in the Breast Cancer Surveillance Consortium. Examinations were followed for one year to ascertain incident ILC, IDC, or IMC. We measured cancer detection rate (CDR) and interval invasive cancer rate/1000 screening examinations for each histological subtype and stratified by breast density and modality. We calculated relative risk (RR) for DM vs. DBT using log-binomial models to adjust for the propensity of receiving DBT vs. DM. RESULTS Unadjusted CDR per 1000 mammograms of ILC overall was 0.33 (95%CI: 0.30-0.36) for DM; 0.45 (95%CI: 0.39-0.52) for DBT, and for women with dense breasts- 0.33 (95%CI: 0.29-0.37) for DM and 0.54 (95%CI: 0.43-0.66) for DBT. Similar results were noted for IDC and IMC. Adjusted models showed a significantly increased RR for cancer detection with DBT compared to DM among women with dense breasts for all three histologies (RR; 95%CI: ILC 1.53; 1.09-2.14, IDC 1.21; 1.02-1.44, IMC 1.76; 1.30-2.38), but no significant increase among women with non-dense breasts. CONCLUSION DBT was associated with higher CDR for ILC, IDC, and IMC for women with dense breasts. Early detection of ILC with DBT may improve outcomes for this distinct clinical entity.
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Affiliation(s)
- Tracy Onega
- Department of Population Health Sciences, and the Huntsman Cancer Institute, University of Utah, 2000 Circle of Hope Dr., RS 4725, Salt Lake City, UT, 84018, USA.
| | - Linn Abraham
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, USA
| | - Diana L Miglioretti
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, USA
- Department of Public Health Sciences, University of California, Davis, CA, USA
| | - Christoph I Lee
- Department of Radiology, University of Washington, and Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Louise M Henderson
- Department of Radiology, University of North Carolina, Chapel Hill, NC, USA
| | - Karla Kerlikowske
- Departments of Medicine and Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
- General Internal Medicine Section, Department of Veterans Affairs, University of California, San Francisco, CA, USA
| | - Anna N A Tosteson
- The Dartmouth Institute for Health Policy and Clinical Practice and Dartmouth Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Donald Weaver
- Department of Pathology, University of Vermont, Burlington, VT, USA
| | - Brian L Sprague
- Departments of Surgery and Radiology, University of Vermont Cancer Center, University of Vermont, Burlington, VT, USA
| | - Erin J Aiello Bowles
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, USA
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11
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Weigel S, Heindel W, Decker T, Weyer-Elberich V, Kerschke L, Gerß J, Hense HW. Digital Breast Tomosynthesis versus Digital Mammography for Detection of Early-Stage Cancers Stratified by Grade: A TOSYMA Subanalysis. Radiology 2023; 309:e231533. [PMID: 38051184 DOI: 10.1148/radiol.231533] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2023]
Abstract
Background Breast cancer screening with digital breast tomosynthesis (DBT) plus synthesized mammography (SM) increases invasive tumor detection compared with digital mammography (DM). However, it is not known how the prognostic characteristics of the cancers detected with the two screening approaches differ. Purpose To compare invasive breast cancers detected with DBT plus SM (test arm) versus DM (control arm) screening with regard to tumor stage, histologic grade, patient age, and breast density. Materials and Methods This exploratory subanalysis of the Tomosynthesis plus Synthesized Mammography (TOSYMA) study, which is a multicenter randomized controlled trial embedded in the German mammography screening program, recruited women aged 50-70 years from July 2018 to December 2020. It compared invasive cancer detection rates (iCDRs), rate differences, and odds ratios (ORs) between the arms stratified by Union for International Cancer Control (UICC) stage (I vs II-IV), histologic grade (1 vs 2 or 3), age group (50-59 vs 60-70 years), and Breast Imaging Reporting and Data System categories of breast density (A or B vs C or D). Results In total, 49 462 (median age, 57 years [IQR, 53-62 years]) and 49 669 (median age, 57 years [IQR, 53-62 years]) participants were allocated to DBT plus SM and DM screening, respectively. The iCDR of stage I tumors with DBT plus SM was 51.6 per 10 000 women (255 of 49 462) and with DM it was 30.0 per 10 000 women (149 of 49 669). DBT plus SM depicted more stage I tumors with grade 2 or 3 (166 of 49 462, 33.7 per 10 000 women) than DM (106 of 49 669, 21.3 per 10 000 women; rate difference, +12.3 per 10 000 women [95% CI: 0.3, 24.9]; OR, 1.6 [95% CI: 0.9, 2.7]). DBT plus SM achieved the highest iCDR of stage I tumors with grade 2 or 3 among women aged 60-70 years with dense breasts (41 of 7364, 55.4 per 10 000 women; rate difference, +21.6 per 10 000 women [95% CI: -21.1, 64.3]; OR, 1.6 [95% CI: 0.6, 4.5]). Conclusion DBT plus SM screening appears to lead to higher detection of early-stage invasive breast cancers of grade 2 or 3 than DM screening, with the highest rate among women aged 60-70 years with dense breasts. Clinical trial registration no. NCT03377036 © RSNA, 2023 See also the editorial by Ha and Chang in this issue.
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Affiliation(s)
- Stefanie Weigel
- From the Clinic for Radiology and Reference Center for Mammography Münster (S.W., W.H., T.D.), Institute of Biostatistics and Clinical Research (V.W.E., L.K., J.G.), and Institute of Epidemiology and Social Medicine (H.W.H.), University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany
| | - Walter Heindel
- From the Clinic for Radiology and Reference Center for Mammography Münster (S.W., W.H., T.D.), Institute of Biostatistics and Clinical Research (V.W.E., L.K., J.G.), and Institute of Epidemiology and Social Medicine (H.W.H.), University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany
| | - Thomas Decker
- From the Clinic for Radiology and Reference Center for Mammography Münster (S.W., W.H., T.D.), Institute of Biostatistics and Clinical Research (V.W.E., L.K., J.G.), and Institute of Epidemiology and Social Medicine (H.W.H.), University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany
| | - Veronika Weyer-Elberich
- From the Clinic for Radiology and Reference Center for Mammography Münster (S.W., W.H., T.D.), Institute of Biostatistics and Clinical Research (V.W.E., L.K., J.G.), and Institute of Epidemiology and Social Medicine (H.W.H.), University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany
| | - Laura Kerschke
- From the Clinic for Radiology and Reference Center for Mammography Münster (S.W., W.H., T.D.), Institute of Biostatistics and Clinical Research (V.W.E., L.K., J.G.), and Institute of Epidemiology and Social Medicine (H.W.H.), University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany
| | - Joachim Gerß
- From the Clinic for Radiology and Reference Center for Mammography Münster (S.W., W.H., T.D.), Institute of Biostatistics and Clinical Research (V.W.E., L.K., J.G.), and Institute of Epidemiology and Social Medicine (H.W.H.), University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany
| | - Hans-Werner Hense
- From the Clinic for Radiology and Reference Center for Mammography Münster (S.W., W.H., T.D.), Institute of Biostatistics and Clinical Research (V.W.E., L.K., J.G.), and Institute of Epidemiology and Social Medicine (H.W.H.), University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany
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12
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Berg WA, Seitzman RL, Pushkin J. Implementing the National Dense Breast Reporting Standard, Expanding Supplemental Screening Using Current Guidelines, and the Proposed Find It Early Act. JOURNAL OF BREAST IMAGING 2023; 5:712-723. [PMID: 38141231 DOI: 10.1093/jbi/wbad034] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Indexed: 12/25/2023]
Abstract
Thirty-eight states and the District of Columbia (DC) have dense breast notification laws that mandate varying levels of patient notification about breast density after a mammogram, and these cover over 90% of American women. On March 10, 2023, the Food and Drug Administration issued a final rule amending regulations under the Mammography Quality Standards Act for a national dense breast reporting standard for both patient results letters and mammogram reports. Effective September 10, 2024, letters will be required to tell a woman her breasts are "dense" or "not dense," that dense tissue makes it harder to find cancers on a mammogram, and that it increases the risk of developing cancer. Women with dense breasts will also be told that other imaging tests in addition to a mammogram may help find cancers. The specific density category can be added (eg, if mandated by a state "inform" law). Reports to providers must include the Breast Imaging Reporting and Data System density category. Implementing appropriate supplemental screening should be based on patient risk for missed breast cancer on mammography; such assessment should include consideration of breast density and other risk factors. This article discusses strategies for implementation. Currently 21 states and DC have varying insurance laws for supplemental breast imaging; in addition, Oklahoma requires coverage for diagnostic breast imaging. A federal insurance bill, the Find It Early Act, has been introduced that would ensure no-cost screening and diagnostic imaging for women with dense breasts or at increased risk and close loopholes in state laws.
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Affiliation(s)
- Wendie A Berg
- University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Department of Radiology, Pittsburgh, PA, USA
| | - Robin L Seitzman
- Seitzman Epidemiology, LLC, San Diego, CA, USA
- DenseBreast-info, Inc, Deer Park, NY, USA
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13
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Holen ÅS, Bergan MB, Lee CI, Zackrisson S, Moshina N, Aase HS, Haldorsen IS, Hofvind S. Early screening outcomes before, during, and after a randomized controlled trial with digital breast tomosynthesis. Eur J Radiol 2023; 167:111069. [PMID: 37708674 DOI: 10.1016/j.ejrad.2023.111069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 07/31/2023] [Accepted: 08/28/2023] [Indexed: 09/16/2023]
Abstract
PURPOSE To describe and compare early screening outcomes before, during and after a randomized controlled trial with digital breast tomosynthesis (DBT) including synthetic 2D mammography versus standard digital mammography (DM) (To-Be 1) and a follow-up cohort study using DBT (To-Be 2). METHODS Retrospective results of 125,020 screening examinations from four consecutive screening rounds performed in 2014-2021 were described and compared for pre-To-Be 1 (DM), To-Be 1 (DM or DBT), To-Be 2 (DBT), and post-To-Be 2 (DM) cohorts. Descriptive analyses of rates of recall, biopsy, screen-detected and interval cancer, distribution of histopathologic tumor characteristics and time spent on image interpretation and consensus were presented for the four rounds including five cohorts, one cohort in each screening round except for the To-Be 1 trail, which included a DBT and a DM cohort. Odds ratios (OR) with 95% CIs was calculated for recall and cancer detection rates. RESULTS Rate of screen-detected cancer was 0.90% for women screened with DBT in To-Be 2 and 0.64% for DM in pre-To-Be 1. The rates did not differ for the To-Be 1 DM (0.61%), To-Be 1 DBT (0.66%) and post-To-Be 2 DM (0.67%) cohorts. The interval cancer rates ranged between 0.13% and 0.20%. The distribution of histopathologic tumor characteristics did not differ between the cohorts. CONCLUSIONS Screening all women with DBT following a randomized controlled trial in an organized, population-based screening program showed a temporary increase in the rate of screen-detected cancer.
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Affiliation(s)
- Åsne Sørlien Holen
- Section for Breast Cancer Screening, Cancer Registry of Norway, Oslo, Norway.
| | - Marie Burns Bergan
- Section for Breast Cancer Screening, Cancer Registry of Norway, Oslo, Norway.
| | - Christoph I Lee
- Department of Radiology, University of Washington School of Medicine, Seattle, WA, USA; Department of Health Systems and Population Health, University of Washington School of Public Health, Seattle, WA, USA.
| | - Sophia Zackrisson
- Department of Translational Medicine, Diagnostic Radiology, Lund University, Malmö, Sweden; Department of Imaging and Functional Medicine, Skåne University Hospital, Malmö, Sweden.
| | - Nataliia Moshina
- Section for Breast Cancer Screening, Cancer Registry of Norway, Oslo, Norway.
| | | | - Ingfrid Salvesen Haldorsen
- Mohn Medical Imaging and Visualization Center, Department of Radiology, Haukeland University Hospital, Bergen, Norway; Department of Clinical Medicine, University of Bergen, Bergen, Norway.
| | - Solveig Hofvind
- Section for Breast Cancer Screening, Cancer Registry of Norway, Oslo, Norway; Department of Health and Care Sciences, Faculty of Health Sciences, UiT, The Arctic University of Norway, Tromsø, Norway.
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14
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Zhou C, Xie H, Zhu F, Yan W, Yu R, Wang Y. Improving the malignancy prediction of breast cancer based on the integration of radiomics features from dual-view mammography and clinical parameters. Clin Exp Med 2023; 23:2357-2368. [PMID: 36413273 DOI: 10.1007/s10238-022-00944-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 11/05/2022] [Indexed: 11/23/2022]
Abstract
Radiomics has been a promising imaging biomarker for many malignant diseases. We developed a novel radiomics strategy that incorporating radiomics features extracted from dual-view mammograms and clinical parameters for identifying benign and malignant breast lesions, and validated whether the radiomics assessment could improve the accurate diagnosis of breast cancer. A total of 380 patients (mean age, 52 ± 7 years) with 621 breast lesions utilizing mammograms on craniocaudal (CC) and mediolateral oblique (MLO) views were randomly allocated into the training (n = 486) and testing (n = 135) sets in this retrospective study. A total of 1184 and 2368 radiomics features were extracted from single-position region of interest (ROI) and position-paired ROI, separately. Clinical parameters were then combined for better prediction. Recursive feature elimination and least absolute shrinkage and selection operator methods were applied to select optimal predictive features. Random forest was used to conduct the predictive model. Intraclass correlation coefficient test was used to assess repeatability and reproducibility of features. After preprocessing, 467 radiomics features and clinical parameters remained in the single-view and dual-view models. The performance and significance of models were quantified by the area under the curve (AUC), sensitivity, specificity, and accuracy. The correlation analysis between variables was evaluated using the correlation ratio and Pearson correlation coefficient. The model using a combination of dual-view radiomics and clinical parameters achieved a favorable performance (AUC: 0.804, 95% CI: 0.668-0.916), outperformed single-view model and model without clinical parameters. Incorporating with radiomics features of dual-view (CC&MLO) mammogram, age, breast density, and type of suspicious lesions can provide a noninvasive approach to evaluate the malignancy of breast lesions and facilitate clinical decision-making.
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Affiliation(s)
- Chenyi Zhou
- Department of Radiology, The People's Hospital of Suzhou New District, Suzhou, 215129, Jiangsu, China
| | - Hui Xie
- Department of Radiology, The People's Hospital of Suzhou New District, Suzhou, 215129, Jiangsu, China
| | - Fanglian Zhu
- Department of Radiology, The People's Hospital of Suzhou New District, Suzhou, 215129, Jiangsu, China
| | - Wanying Yan
- Beijing Infervision Technology Co. Ltd., Beijing, 100025, Beijing, China
| | - Ruize Yu
- Beijing Infervision Technology Co. Ltd., Beijing, 100025, Beijing, China
| | - Yanling Wang
- Department of Radiology, The People's Hospital of Suzhou New District, Suzhou, 215129, Jiangsu, China.
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15
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Nguyen AA, McCarthy AM, Kontos D. Combining Molecular and Radiomic Features for Risk Assessment in Breast Cancer. Annu Rev Biomed Data Sci 2023; 6:299-311. [PMID: 37159874 DOI: 10.1146/annurev-biodatasci-020722-092748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Breast cancer risk is highly variable within the population and current research is leading the shift toward personalized medicine. By accurately assessing an individual woman's risk, we can reduce the risk of over/undertreatment by preventing unnecessary procedures or by elevating screening procedures. Breast density measured from conventional mammography has been established as one of the most dominant risk factors for breast cancer; however, it is currently limited by its ability to characterize more complex breast parenchymal patterns that have been shown to provide additional information to strengthen cancer risk models. Molecular factors ranging from high penetrance, or high likelihood that a mutation will show signs and symptoms of the disease, to combinations of gene mutations with low penetrance have shown promise for augmenting risk assessment. Although imaging biomarkers and molecular biomarkers have both individually demonstrated improved performance in risk assessment, few studies have evaluated them together. This review aims to highlight the current state of the art in breast cancer risk assessment using imaging and genetic biomarkers.
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Affiliation(s)
- Alex A Nguyen
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Anne Marie McCarthy
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Despina Kontos
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA;
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16
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Sprague BL, Coley RY, Lowry KP, Kerlikowske K, Henderson LM, Su YR, Lee CI, Onega T, Bowles EJA, Herschorn SD, diFlorio-Alexander RM, Miglioretti DL. Digital Breast Tomosynthesis versus Digital Mammography Screening Performance on Successive Screening Rounds from the Breast Cancer Surveillance Consortium. Radiology 2023; 307:e223142. [PMID: 37249433 PMCID: PMC10315524 DOI: 10.1148/radiol.223142] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 03/23/2023] [Accepted: 03/29/2023] [Indexed: 05/31/2023]
Abstract
Background Prior cross-sectional studies have observed that breast cancer screening with digital breast tomosynthesis (DBT) has a lower recall rate and higher cancer detection rate compared with digital mammography (DM). Purpose To evaluate breast cancer screening outcomes with DBT versus DM on successive screening rounds. Materials and Methods In this retrospective cohort study, data from 58 breast imaging facilities in the Breast Cancer Surveillance Consortium were collected. Analysis included women aged 40-79 years undergoing DBT or DM screening from 2011 to 2020. Absolute differences in screening outcomes by modality and screening round were estimated during the study period by using generalized estimating equations with marginal standardization to adjust for differences in women's risk characteristics across modality and round. Results A total of 523 485 DBT examinations (mean age of women, 58.7 years ± 9.7 [SD]) and 1 008 123 DM examinations (mean age, 58.4 years ± 9.8) among 504 863 women were evaluated. DBT and DM recall rates decreased with successive screening round, but absolute recall rates in each round were significantly lower with DBT versus DM (round 1 difference, -3.3% [95% CI: -4.6, -2.1] [P < .001]; round 2 difference, -1.8% [95% CI: -2.9, -0.7] [P = .003]; round 3 or above difference, -1.2% [95% CI: -2.4, -0.1] [P = .03]). DBT had significantly higher cancer detection (difference, 0.6 per 1000 examinations [95% CI: 0.2, 1.1]; P = .009) compared with DM only for round 3 and above. There were no significant differences in interval cancer rate (round 1 difference, 0.00 per 1000 examinations [95% CI: -0.24, 0.30] [P = .96]; round 2 or above difference, 0.04 [95% CI: -0.19, 0.31] [P = .76]) or total advanced cancer rate (round 1 difference, 0.00 per 1000 examinations [95% CI: -0.15, 0.19] [P = .94]; round 2 or above difference, -0.06 [95% CI: -0.18, 0.11] [P = .43]). Conclusion DBT had lower recall rates and could help detect more cancers than DM across three screening rounds, with no difference in interval or advanced cancer rates. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Skaane in this issue.
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Affiliation(s)
- Brian L. Sprague
- From the Departments of Surgery (B.L.S.) and Radiology (B.L.S., S.D.H.), University of Vermont Cancer Center, University of Vermont Larner College of Medicine, UHC Bldg, Room 4425, 1 S Prospect St, Burlington, VT 05401; Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Wash (R.Y.C., Y.R.S., E.J.A.B., D.L.M.); Department of Radiology, University of Washington, Fred Hutchinson Cancer Center, Seattle, Wash (K.P.L., C.I.L.); Departments of Medicine and Epidemiology and Biostatistics, University of California–San Francisco, San Francisco, Calif (K.K.); Department of Radiology, University of North Carolina, Chapel Hill, NC (L.M.H.); Department of Population Health Sciences, University of Utah, Huntsman Cancer Institute, Salt Lake City, Utah (T.O.); Department of Radiology, Giesel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.F.A.); and Division of Biostatistics, Department of Public Health Sciences, University of California–Davis, Davis, Calif (D.L.M.)
| | - Rebecca Yates Coley
- From the Departments of Surgery (B.L.S.) and Radiology (B.L.S., S.D.H.), University of Vermont Cancer Center, University of Vermont Larner College of Medicine, UHC Bldg, Room 4425, 1 S Prospect St, Burlington, VT 05401; Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Wash (R.Y.C., Y.R.S., E.J.A.B., D.L.M.); Department of Radiology, University of Washington, Fred Hutchinson Cancer Center, Seattle, Wash (K.P.L., C.I.L.); Departments of Medicine and Epidemiology and Biostatistics, University of California–San Francisco, San Francisco, Calif (K.K.); Department of Radiology, University of North Carolina, Chapel Hill, NC (L.M.H.); Department of Population Health Sciences, University of Utah, Huntsman Cancer Institute, Salt Lake City, Utah (T.O.); Department of Radiology, Giesel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.F.A.); and Division of Biostatistics, Department of Public Health Sciences, University of California–Davis, Davis, Calif (D.L.M.)
| | - Kathryn P. Lowry
- From the Departments of Surgery (B.L.S.) and Radiology (B.L.S., S.D.H.), University of Vermont Cancer Center, University of Vermont Larner College of Medicine, UHC Bldg, Room 4425, 1 S Prospect St, Burlington, VT 05401; Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Wash (R.Y.C., Y.R.S., E.J.A.B., D.L.M.); Department of Radiology, University of Washington, Fred Hutchinson Cancer Center, Seattle, Wash (K.P.L., C.I.L.); Departments of Medicine and Epidemiology and Biostatistics, University of California–San Francisco, San Francisco, Calif (K.K.); Department of Radiology, University of North Carolina, Chapel Hill, NC (L.M.H.); Department of Population Health Sciences, University of Utah, Huntsman Cancer Institute, Salt Lake City, Utah (T.O.); Department of Radiology, Giesel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.F.A.); and Division of Biostatistics, Department of Public Health Sciences, University of California–Davis, Davis, Calif (D.L.M.)
| | - Karla Kerlikowske
- From the Departments of Surgery (B.L.S.) and Radiology (B.L.S., S.D.H.), University of Vermont Cancer Center, University of Vermont Larner College of Medicine, UHC Bldg, Room 4425, 1 S Prospect St, Burlington, VT 05401; Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Wash (R.Y.C., Y.R.S., E.J.A.B., D.L.M.); Department of Radiology, University of Washington, Fred Hutchinson Cancer Center, Seattle, Wash (K.P.L., C.I.L.); Departments of Medicine and Epidemiology and Biostatistics, University of California–San Francisco, San Francisco, Calif (K.K.); Department of Radiology, University of North Carolina, Chapel Hill, NC (L.M.H.); Department of Population Health Sciences, University of Utah, Huntsman Cancer Institute, Salt Lake City, Utah (T.O.); Department of Radiology, Giesel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.F.A.); and Division of Biostatistics, Department of Public Health Sciences, University of California–Davis, Davis, Calif (D.L.M.)
| | - Louise M. Henderson
- From the Departments of Surgery (B.L.S.) and Radiology (B.L.S., S.D.H.), University of Vermont Cancer Center, University of Vermont Larner College of Medicine, UHC Bldg, Room 4425, 1 S Prospect St, Burlington, VT 05401; Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Wash (R.Y.C., Y.R.S., E.J.A.B., D.L.M.); Department of Radiology, University of Washington, Fred Hutchinson Cancer Center, Seattle, Wash (K.P.L., C.I.L.); Departments of Medicine and Epidemiology and Biostatistics, University of California–San Francisco, San Francisco, Calif (K.K.); Department of Radiology, University of North Carolina, Chapel Hill, NC (L.M.H.); Department of Population Health Sciences, University of Utah, Huntsman Cancer Institute, Salt Lake City, Utah (T.O.); Department of Radiology, Giesel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.F.A.); and Division of Biostatistics, Department of Public Health Sciences, University of California–Davis, Davis, Calif (D.L.M.)
| | - Yu-Ru Su
- From the Departments of Surgery (B.L.S.) and Radiology (B.L.S., S.D.H.), University of Vermont Cancer Center, University of Vermont Larner College of Medicine, UHC Bldg, Room 4425, 1 S Prospect St, Burlington, VT 05401; Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Wash (R.Y.C., Y.R.S., E.J.A.B., D.L.M.); Department of Radiology, University of Washington, Fred Hutchinson Cancer Center, Seattle, Wash (K.P.L., C.I.L.); Departments of Medicine and Epidemiology and Biostatistics, University of California–San Francisco, San Francisco, Calif (K.K.); Department of Radiology, University of North Carolina, Chapel Hill, NC (L.M.H.); Department of Population Health Sciences, University of Utah, Huntsman Cancer Institute, Salt Lake City, Utah (T.O.); Department of Radiology, Giesel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.F.A.); and Division of Biostatistics, Department of Public Health Sciences, University of California–Davis, Davis, Calif (D.L.M.)
| | - Christoph I. Lee
- From the Departments of Surgery (B.L.S.) and Radiology (B.L.S., S.D.H.), University of Vermont Cancer Center, University of Vermont Larner College of Medicine, UHC Bldg, Room 4425, 1 S Prospect St, Burlington, VT 05401; Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Wash (R.Y.C., Y.R.S., E.J.A.B., D.L.M.); Department of Radiology, University of Washington, Fred Hutchinson Cancer Center, Seattle, Wash (K.P.L., C.I.L.); Departments of Medicine and Epidemiology and Biostatistics, University of California–San Francisco, San Francisco, Calif (K.K.); Department of Radiology, University of North Carolina, Chapel Hill, NC (L.M.H.); Department of Population Health Sciences, University of Utah, Huntsman Cancer Institute, Salt Lake City, Utah (T.O.); Department of Radiology, Giesel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.F.A.); and Division of Biostatistics, Department of Public Health Sciences, University of California–Davis, Davis, Calif (D.L.M.)
| | - Tracy Onega
- From the Departments of Surgery (B.L.S.) and Radiology (B.L.S., S.D.H.), University of Vermont Cancer Center, University of Vermont Larner College of Medicine, UHC Bldg, Room 4425, 1 S Prospect St, Burlington, VT 05401; Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Wash (R.Y.C., Y.R.S., E.J.A.B., D.L.M.); Department of Radiology, University of Washington, Fred Hutchinson Cancer Center, Seattle, Wash (K.P.L., C.I.L.); Departments of Medicine and Epidemiology and Biostatistics, University of California–San Francisco, San Francisco, Calif (K.K.); Department of Radiology, University of North Carolina, Chapel Hill, NC (L.M.H.); Department of Population Health Sciences, University of Utah, Huntsman Cancer Institute, Salt Lake City, Utah (T.O.); Department of Radiology, Giesel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.F.A.); and Division of Biostatistics, Department of Public Health Sciences, University of California–Davis, Davis, Calif (D.L.M.)
| | - Erin J. A. Bowles
- From the Departments of Surgery (B.L.S.) and Radiology (B.L.S., S.D.H.), University of Vermont Cancer Center, University of Vermont Larner College of Medicine, UHC Bldg, Room 4425, 1 S Prospect St, Burlington, VT 05401; Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Wash (R.Y.C., Y.R.S., E.J.A.B., D.L.M.); Department of Radiology, University of Washington, Fred Hutchinson Cancer Center, Seattle, Wash (K.P.L., C.I.L.); Departments of Medicine and Epidemiology and Biostatistics, University of California–San Francisco, San Francisco, Calif (K.K.); Department of Radiology, University of North Carolina, Chapel Hill, NC (L.M.H.); Department of Population Health Sciences, University of Utah, Huntsman Cancer Institute, Salt Lake City, Utah (T.O.); Department of Radiology, Giesel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.F.A.); and Division of Biostatistics, Department of Public Health Sciences, University of California–Davis, Davis, Calif (D.L.M.)
| | - Sally D. Herschorn
- From the Departments of Surgery (B.L.S.) and Radiology (B.L.S., S.D.H.), University of Vermont Cancer Center, University of Vermont Larner College of Medicine, UHC Bldg, Room 4425, 1 S Prospect St, Burlington, VT 05401; Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Wash (R.Y.C., Y.R.S., E.J.A.B., D.L.M.); Department of Radiology, University of Washington, Fred Hutchinson Cancer Center, Seattle, Wash (K.P.L., C.I.L.); Departments of Medicine and Epidemiology and Biostatistics, University of California–San Francisco, San Francisco, Calif (K.K.); Department of Radiology, University of North Carolina, Chapel Hill, NC (L.M.H.); Department of Population Health Sciences, University of Utah, Huntsman Cancer Institute, Salt Lake City, Utah (T.O.); Department of Radiology, Giesel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.F.A.); and Division of Biostatistics, Department of Public Health Sciences, University of California–Davis, Davis, Calif (D.L.M.)
| | - Roberta M. diFlorio-Alexander
- From the Departments of Surgery (B.L.S.) and Radiology (B.L.S., S.D.H.), University of Vermont Cancer Center, University of Vermont Larner College of Medicine, UHC Bldg, Room 4425, 1 S Prospect St, Burlington, VT 05401; Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Wash (R.Y.C., Y.R.S., E.J.A.B., D.L.M.); Department of Radiology, University of Washington, Fred Hutchinson Cancer Center, Seattle, Wash (K.P.L., C.I.L.); Departments of Medicine and Epidemiology and Biostatistics, University of California–San Francisco, San Francisco, Calif (K.K.); Department of Radiology, University of North Carolina, Chapel Hill, NC (L.M.H.); Department of Population Health Sciences, University of Utah, Huntsman Cancer Institute, Salt Lake City, Utah (T.O.); Department of Radiology, Giesel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.F.A.); and Division of Biostatistics, Department of Public Health Sciences, University of California–Davis, Davis, Calif (D.L.M.)
| | - Diana L. Miglioretti
- From the Departments of Surgery (B.L.S.) and Radiology (B.L.S., S.D.H.), University of Vermont Cancer Center, University of Vermont Larner College of Medicine, UHC Bldg, Room 4425, 1 S Prospect St, Burlington, VT 05401; Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Wash (R.Y.C., Y.R.S., E.J.A.B., D.L.M.); Department of Radiology, University of Washington, Fred Hutchinson Cancer Center, Seattle, Wash (K.P.L., C.I.L.); Departments of Medicine and Epidemiology and Biostatistics, University of California–San Francisco, San Francisco, Calif (K.K.); Department of Radiology, University of North Carolina, Chapel Hill, NC (L.M.H.); Department of Population Health Sciences, University of Utah, Huntsman Cancer Institute, Salt Lake City, Utah (T.O.); Department of Radiology, Giesel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.F.A.); and Division of Biostatistics, Department of Public Health Sciences, University of California–Davis, Davis, Calif (D.L.M.)
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Jiang S, Bennett DL, Rosner BA, Colditz GA. Longitudinal Analysis of Change in Mammographic Density in Each Breast and Its Association With Breast Cancer Risk. JAMA Oncol 2023; 9:808-814. [PMID: 37103922 PMCID: PMC10141289 DOI: 10.1001/jamaoncol.2023.0434] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 01/27/2023] [Indexed: 04/28/2023]
Abstract
Importance Although breast density is an established risk factor for breast cancer, longitudinal changes in breast density have not been extensively studied to determine whether this factor is associated with breast cancer risk. Objective To prospectively evaluate the association between change in mammographic density in each breast over time and risk of subsequent breast cancer. Design, Setting, and Participants This nested case-control cohort study was sampled from the Joanne Knight Breast Health Cohort of 10 481 women free from cancer at entry and observed from November 3, 2008, to October 31, 2020, with routine screening mammograms every 1 to 2 years, providing a measure of breast density. Breast cancer screening was provided for a diverse population of women in the St Louis region. A total of 289 case patients with pathology-confirmed breast cancer were identified, and approximately 2 control participants were sampled for each case according to age at entry and year of enrollment, yielding 658 controls with a total number of 8710 craniocaudal-view mammograms for analysis. Exposures Exposures included screening mammograms with volumetric percentage of density, change in volumetric breast density over time, and breast biopsy pathology-confirmed cancer. Breast cancer risk factors were collected via questionnaire at enrollment. Main Outcomes and Measures Longitudinal changes over time in each woman's volumetric breast density by case and control status. Results The mean (SD) age of the 947 participants was 56.67 (8.71) years at entry; 141 were Black (14.9%), 763 were White (80.6%), 20 were of other race or ethnicity (2.1%), and 23 did not report this information (2.4%). The mean (SD) interval was 2.0 (1.5) years from last mammogram to date of subsequent breast cancer diagnosis (10th percentile, 1.0 year; 90th percentile, 3.9 years). Breast density decreased over time in both cases and controls. However, there was a significantly slower decrease in rate of decline in density in the breast that developed breast cancer compared with the decline in controls (estimate = 0.027; 95% CI, 0.001-0.053; P = .04). Conclusions and Relevance This study found that the rate of change in breast density was associated with the risk of subsequent breast cancer. Incorporation of longitudinal changes into existing models could optimize risk stratification and guide more personalized risk management.
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Affiliation(s)
- Shu Jiang
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine in St Louis, St Louis, Missouri
| | - Debbie L. Bennett
- Department of Radiology, Washington University School of Medicine in St Louis, St Louis, Missouri
| | - Bernard A. Rosner
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Graham A. Colditz
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine in St Louis, St Louis, Missouri
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18
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Lee CI, Abraham L, Miglioretti DL, Onega T, Kerlikowske K, Lee JM, Sprague BL, Tosteson ANA, Rauscher GH, Bowles EJA, diFlorio-Alexander RM, Henderson LM. National Performance Benchmarks for Screening Digital Breast Tomosynthesis: Update from the Breast Cancer Surveillance Consortium. Radiology 2023; 307:e222499. [PMID: 37039687 PMCID: PMC10323294 DOI: 10.1148/radiol.222499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 02/03/2023] [Accepted: 02/20/2023] [Indexed: 04/12/2023]
Abstract
Background It is important to establish screening mammography performance benchmarks for quality improvement efforts. Purpose To establish performance benchmarks for digital breast tomosynthesis (DBT) screening and evaluate performance trends over time in U.S. community practice. Materials and Methods In this retrospective study, DBT screening examinations were collected from five Breast Cancer Surveillance Consortium (BCSC) registries between 2011 and 2018. Performance measures included abnormal interpretation rate (AIR), cancer detection rate (CDR), sensitivity, specificity, and false-negative rate (FNR) and were calculated based on the American College of Radiology Breast Imaging Reporting and Data System, fifth edition, and compared with concurrent BCSC DM screening examinations, previously published BCSC and National Mammography Database benchmarks, and expert opinion acceptable performance ranges. Benchmarks were derived from the distribution of performance measures across radiologists (n = 84 or n = 73 depending on metric) and were presented as percentiles. Results A total of 896 101 women undergoing 2 301 766 screening examinations (458 175 DBT examinations [median age, 58 years; age range, 18-111 years] and 1 843 591 DM examinations [median age, 58 years; age range, 18-109 years]) were included in this study. DBT screening performance measures were as follows: AIR, 8.3% (95% CI: 7.5, 9.3); CDR per 1000 screens, 5.8 (95% CI: 5.4, 6.1); sensitivity, 87.4% (95% CI: 85.2, 89.4); specificity, 92.2% (95% CI: 91.3, 93.0); and FNR per 1000 screens, 0.8 (95% CI: 0.7, 1.0). When compared with BCSC DM screening examinations from the same time period and previously published BCSC and National Mammography Database performance benchmarks, all performance measures were higher for DBT except sensitivity and FNR, which were similar to concurrent and prior DM performance measures. The following proportions of radiologists achieved acceptable performance ranges with DBT: 97.6% for CDR, 91.8% for sensitivity, 75.0% for AIR, and 74.0% for specificity. Conclusion In U.S. community practice, large proportions of radiologists met acceptable performance ranges for screening performance metrics with DBT. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Lee and Moy in this issue.
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Affiliation(s)
- Christoph I. Lee
- From the Department of Radiology, University of Washington School of
Medicine, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson
Cancer Center, 825 Eastlake Ave E, LG-200, Seattle, WA 98109 (C.I.L., J.M.L.);
Department of Health Systems & Population Health, University of
Washington School of Public Health, Seattle, Wash (C.I.L.); Kaiser Permanente
Washington Health Research Institute, Kaiser Permanente Washington, Seattle,
Wash (C.I.L., L.A., D.L.M., J.M.L., E.J.A.B.); Division of Biostatistics,
Department of Public Health Sciences, University of California Davis School of
Medicine, Davis, Calif (D.L.M.); Department of Population Health Sciences, and
the Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (T.O.);
Department of Medicine, Department of Epidemiology and Biostatistics, and
General Internal Medicine Section, Department of Veterans Affairs, University of
California, San Francisco, San Francisco, Calif (K.K.); Department of Surgery,
Office of Health Promotion Research, Larner College of Medicine at the
University of Vermont and University of Vermont Cancer Center, Burlington, Vt
(B.L.S.); The Dartmouth Institute for Health Policy and Clinical Practice,
Geisel School of Medicine at Dartmouth and Norris Cotton Cancer Center, Lebanon,
NH (A.N.A.T.); Division of Epidemiology and Biostatistics, School of Public
Health, University of Illinois at Chicago, Chicago, Ill (G.H.R.); Department of
Radiology, Geisel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.A.); and
Department of Radiology, University of North Carolina, Chapel Hill, NC
(L.M.H.)
| | - Linn Abraham
- From the Department of Radiology, University of Washington School of
Medicine, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson
Cancer Center, 825 Eastlake Ave E, LG-200, Seattle, WA 98109 (C.I.L., J.M.L.);
Department of Health Systems & Population Health, University of
Washington School of Public Health, Seattle, Wash (C.I.L.); Kaiser Permanente
Washington Health Research Institute, Kaiser Permanente Washington, Seattle,
Wash (C.I.L., L.A., D.L.M., J.M.L., E.J.A.B.); Division of Biostatistics,
Department of Public Health Sciences, University of California Davis School of
Medicine, Davis, Calif (D.L.M.); Department of Population Health Sciences, and
the Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (T.O.);
Department of Medicine, Department of Epidemiology and Biostatistics, and
General Internal Medicine Section, Department of Veterans Affairs, University of
California, San Francisco, San Francisco, Calif (K.K.); Department of Surgery,
Office of Health Promotion Research, Larner College of Medicine at the
University of Vermont and University of Vermont Cancer Center, Burlington, Vt
(B.L.S.); The Dartmouth Institute for Health Policy and Clinical Practice,
Geisel School of Medicine at Dartmouth and Norris Cotton Cancer Center, Lebanon,
NH (A.N.A.T.); Division of Epidemiology and Biostatistics, School of Public
Health, University of Illinois at Chicago, Chicago, Ill (G.H.R.); Department of
Radiology, Geisel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.A.); and
Department of Radiology, University of North Carolina, Chapel Hill, NC
(L.M.H.)
| | - Diana L. Miglioretti
- From the Department of Radiology, University of Washington School of
Medicine, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson
Cancer Center, 825 Eastlake Ave E, LG-200, Seattle, WA 98109 (C.I.L., J.M.L.);
Department of Health Systems & Population Health, University of
Washington School of Public Health, Seattle, Wash (C.I.L.); Kaiser Permanente
Washington Health Research Institute, Kaiser Permanente Washington, Seattle,
Wash (C.I.L., L.A., D.L.M., J.M.L., E.J.A.B.); Division of Biostatistics,
Department of Public Health Sciences, University of California Davis School of
Medicine, Davis, Calif (D.L.M.); Department of Population Health Sciences, and
the Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (T.O.);
Department of Medicine, Department of Epidemiology and Biostatistics, and
General Internal Medicine Section, Department of Veterans Affairs, University of
California, San Francisco, San Francisco, Calif (K.K.); Department of Surgery,
Office of Health Promotion Research, Larner College of Medicine at the
University of Vermont and University of Vermont Cancer Center, Burlington, Vt
(B.L.S.); The Dartmouth Institute for Health Policy and Clinical Practice,
Geisel School of Medicine at Dartmouth and Norris Cotton Cancer Center, Lebanon,
NH (A.N.A.T.); Division of Epidemiology and Biostatistics, School of Public
Health, University of Illinois at Chicago, Chicago, Ill (G.H.R.); Department of
Radiology, Geisel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.A.); and
Department of Radiology, University of North Carolina, Chapel Hill, NC
(L.M.H.)
| | - Tracy Onega
- From the Department of Radiology, University of Washington School of
Medicine, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson
Cancer Center, 825 Eastlake Ave E, LG-200, Seattle, WA 98109 (C.I.L., J.M.L.);
Department of Health Systems & Population Health, University of
Washington School of Public Health, Seattle, Wash (C.I.L.); Kaiser Permanente
Washington Health Research Institute, Kaiser Permanente Washington, Seattle,
Wash (C.I.L., L.A., D.L.M., J.M.L., E.J.A.B.); Division of Biostatistics,
Department of Public Health Sciences, University of California Davis School of
Medicine, Davis, Calif (D.L.M.); Department of Population Health Sciences, and
the Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (T.O.);
Department of Medicine, Department of Epidemiology and Biostatistics, and
General Internal Medicine Section, Department of Veterans Affairs, University of
California, San Francisco, San Francisco, Calif (K.K.); Department of Surgery,
Office of Health Promotion Research, Larner College of Medicine at the
University of Vermont and University of Vermont Cancer Center, Burlington, Vt
(B.L.S.); The Dartmouth Institute for Health Policy and Clinical Practice,
Geisel School of Medicine at Dartmouth and Norris Cotton Cancer Center, Lebanon,
NH (A.N.A.T.); Division of Epidemiology and Biostatistics, School of Public
Health, University of Illinois at Chicago, Chicago, Ill (G.H.R.); Department of
Radiology, Geisel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.A.); and
Department of Radiology, University of North Carolina, Chapel Hill, NC
(L.M.H.)
| | - Karla Kerlikowske
- From the Department of Radiology, University of Washington School of
Medicine, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson
Cancer Center, 825 Eastlake Ave E, LG-200, Seattle, WA 98109 (C.I.L., J.M.L.);
Department of Health Systems & Population Health, University of
Washington School of Public Health, Seattle, Wash (C.I.L.); Kaiser Permanente
Washington Health Research Institute, Kaiser Permanente Washington, Seattle,
Wash (C.I.L., L.A., D.L.M., J.M.L., E.J.A.B.); Division of Biostatistics,
Department of Public Health Sciences, University of California Davis School of
Medicine, Davis, Calif (D.L.M.); Department of Population Health Sciences, and
the Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (T.O.);
Department of Medicine, Department of Epidemiology and Biostatistics, and
General Internal Medicine Section, Department of Veterans Affairs, University of
California, San Francisco, San Francisco, Calif (K.K.); Department of Surgery,
Office of Health Promotion Research, Larner College of Medicine at the
University of Vermont and University of Vermont Cancer Center, Burlington, Vt
(B.L.S.); The Dartmouth Institute for Health Policy and Clinical Practice,
Geisel School of Medicine at Dartmouth and Norris Cotton Cancer Center, Lebanon,
NH (A.N.A.T.); Division of Epidemiology and Biostatistics, School of Public
Health, University of Illinois at Chicago, Chicago, Ill (G.H.R.); Department of
Radiology, Geisel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.A.); and
Department of Radiology, University of North Carolina, Chapel Hill, NC
(L.M.H.)
| | - Janie M. Lee
- From the Department of Radiology, University of Washington School of
Medicine, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson
Cancer Center, 825 Eastlake Ave E, LG-200, Seattle, WA 98109 (C.I.L., J.M.L.);
Department of Health Systems & Population Health, University of
Washington School of Public Health, Seattle, Wash (C.I.L.); Kaiser Permanente
Washington Health Research Institute, Kaiser Permanente Washington, Seattle,
Wash (C.I.L., L.A., D.L.M., J.M.L., E.J.A.B.); Division of Biostatistics,
Department of Public Health Sciences, University of California Davis School of
Medicine, Davis, Calif (D.L.M.); Department of Population Health Sciences, and
the Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (T.O.);
Department of Medicine, Department of Epidemiology and Biostatistics, and
General Internal Medicine Section, Department of Veterans Affairs, University of
California, San Francisco, San Francisco, Calif (K.K.); Department of Surgery,
Office of Health Promotion Research, Larner College of Medicine at the
University of Vermont and University of Vermont Cancer Center, Burlington, Vt
(B.L.S.); The Dartmouth Institute for Health Policy and Clinical Practice,
Geisel School of Medicine at Dartmouth and Norris Cotton Cancer Center, Lebanon,
NH (A.N.A.T.); Division of Epidemiology and Biostatistics, School of Public
Health, University of Illinois at Chicago, Chicago, Ill (G.H.R.); Department of
Radiology, Geisel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.A.); and
Department of Radiology, University of North Carolina, Chapel Hill, NC
(L.M.H.)
| | - Brian L. Sprague
- From the Department of Radiology, University of Washington School of
Medicine, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson
Cancer Center, 825 Eastlake Ave E, LG-200, Seattle, WA 98109 (C.I.L., J.M.L.);
Department of Health Systems & Population Health, University of
Washington School of Public Health, Seattle, Wash (C.I.L.); Kaiser Permanente
Washington Health Research Institute, Kaiser Permanente Washington, Seattle,
Wash (C.I.L., L.A., D.L.M., J.M.L., E.J.A.B.); Division of Biostatistics,
Department of Public Health Sciences, University of California Davis School of
Medicine, Davis, Calif (D.L.M.); Department of Population Health Sciences, and
the Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (T.O.);
Department of Medicine, Department of Epidemiology and Biostatistics, and
General Internal Medicine Section, Department of Veterans Affairs, University of
California, San Francisco, San Francisco, Calif (K.K.); Department of Surgery,
Office of Health Promotion Research, Larner College of Medicine at the
University of Vermont and University of Vermont Cancer Center, Burlington, Vt
(B.L.S.); The Dartmouth Institute for Health Policy and Clinical Practice,
Geisel School of Medicine at Dartmouth and Norris Cotton Cancer Center, Lebanon,
NH (A.N.A.T.); Division of Epidemiology and Biostatistics, School of Public
Health, University of Illinois at Chicago, Chicago, Ill (G.H.R.); Department of
Radiology, Geisel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.A.); and
Department of Radiology, University of North Carolina, Chapel Hill, NC
(L.M.H.)
| | - Anna N. A. Tosteson
- From the Department of Radiology, University of Washington School of
Medicine, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson
Cancer Center, 825 Eastlake Ave E, LG-200, Seattle, WA 98109 (C.I.L., J.M.L.);
Department of Health Systems & Population Health, University of
Washington School of Public Health, Seattle, Wash (C.I.L.); Kaiser Permanente
Washington Health Research Institute, Kaiser Permanente Washington, Seattle,
Wash (C.I.L., L.A., D.L.M., J.M.L., E.J.A.B.); Division of Biostatistics,
Department of Public Health Sciences, University of California Davis School of
Medicine, Davis, Calif (D.L.M.); Department of Population Health Sciences, and
the Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (T.O.);
Department of Medicine, Department of Epidemiology and Biostatistics, and
General Internal Medicine Section, Department of Veterans Affairs, University of
California, San Francisco, San Francisco, Calif (K.K.); Department of Surgery,
Office of Health Promotion Research, Larner College of Medicine at the
University of Vermont and University of Vermont Cancer Center, Burlington, Vt
(B.L.S.); The Dartmouth Institute for Health Policy and Clinical Practice,
Geisel School of Medicine at Dartmouth and Norris Cotton Cancer Center, Lebanon,
NH (A.N.A.T.); Division of Epidemiology and Biostatistics, School of Public
Health, University of Illinois at Chicago, Chicago, Ill (G.H.R.); Department of
Radiology, Geisel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.A.); and
Department of Radiology, University of North Carolina, Chapel Hill, NC
(L.M.H.)
| | - Garth H. Rauscher
- From the Department of Radiology, University of Washington School of
Medicine, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson
Cancer Center, 825 Eastlake Ave E, LG-200, Seattle, WA 98109 (C.I.L., J.M.L.);
Department of Health Systems & Population Health, University of
Washington School of Public Health, Seattle, Wash (C.I.L.); Kaiser Permanente
Washington Health Research Institute, Kaiser Permanente Washington, Seattle,
Wash (C.I.L., L.A., D.L.M., J.M.L., E.J.A.B.); Division of Biostatistics,
Department of Public Health Sciences, University of California Davis School of
Medicine, Davis, Calif (D.L.M.); Department of Population Health Sciences, and
the Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (T.O.);
Department of Medicine, Department of Epidemiology and Biostatistics, and
General Internal Medicine Section, Department of Veterans Affairs, University of
California, San Francisco, San Francisco, Calif (K.K.); Department of Surgery,
Office of Health Promotion Research, Larner College of Medicine at the
University of Vermont and University of Vermont Cancer Center, Burlington, Vt
(B.L.S.); The Dartmouth Institute for Health Policy and Clinical Practice,
Geisel School of Medicine at Dartmouth and Norris Cotton Cancer Center, Lebanon,
NH (A.N.A.T.); Division of Epidemiology and Biostatistics, School of Public
Health, University of Illinois at Chicago, Chicago, Ill (G.H.R.); Department of
Radiology, Geisel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.A.); and
Department of Radiology, University of North Carolina, Chapel Hill, NC
(L.M.H.)
| | - Erin J. A. Bowles
- From the Department of Radiology, University of Washington School of
Medicine, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson
Cancer Center, 825 Eastlake Ave E, LG-200, Seattle, WA 98109 (C.I.L., J.M.L.);
Department of Health Systems & Population Health, University of
Washington School of Public Health, Seattle, Wash (C.I.L.); Kaiser Permanente
Washington Health Research Institute, Kaiser Permanente Washington, Seattle,
Wash (C.I.L., L.A., D.L.M., J.M.L., E.J.A.B.); Division of Biostatistics,
Department of Public Health Sciences, University of California Davis School of
Medicine, Davis, Calif (D.L.M.); Department of Population Health Sciences, and
the Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (T.O.);
Department of Medicine, Department of Epidemiology and Biostatistics, and
General Internal Medicine Section, Department of Veterans Affairs, University of
California, San Francisco, San Francisco, Calif (K.K.); Department of Surgery,
Office of Health Promotion Research, Larner College of Medicine at the
University of Vermont and University of Vermont Cancer Center, Burlington, Vt
(B.L.S.); The Dartmouth Institute for Health Policy and Clinical Practice,
Geisel School of Medicine at Dartmouth and Norris Cotton Cancer Center, Lebanon,
NH (A.N.A.T.); Division of Epidemiology and Biostatistics, School of Public
Health, University of Illinois at Chicago, Chicago, Ill (G.H.R.); Department of
Radiology, Geisel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.A.); and
Department of Radiology, University of North Carolina, Chapel Hill, NC
(L.M.H.)
| | - Roberta M. diFlorio-Alexander
- From the Department of Radiology, University of Washington School of
Medicine, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson
Cancer Center, 825 Eastlake Ave E, LG-200, Seattle, WA 98109 (C.I.L., J.M.L.);
Department of Health Systems & Population Health, University of
Washington School of Public Health, Seattle, Wash (C.I.L.); Kaiser Permanente
Washington Health Research Institute, Kaiser Permanente Washington, Seattle,
Wash (C.I.L., L.A., D.L.M., J.M.L., E.J.A.B.); Division of Biostatistics,
Department of Public Health Sciences, University of California Davis School of
Medicine, Davis, Calif (D.L.M.); Department of Population Health Sciences, and
the Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (T.O.);
Department of Medicine, Department of Epidemiology and Biostatistics, and
General Internal Medicine Section, Department of Veterans Affairs, University of
California, San Francisco, San Francisco, Calif (K.K.); Department of Surgery,
Office of Health Promotion Research, Larner College of Medicine at the
University of Vermont and University of Vermont Cancer Center, Burlington, Vt
(B.L.S.); The Dartmouth Institute for Health Policy and Clinical Practice,
Geisel School of Medicine at Dartmouth and Norris Cotton Cancer Center, Lebanon,
NH (A.N.A.T.); Division of Epidemiology and Biostatistics, School of Public
Health, University of Illinois at Chicago, Chicago, Ill (G.H.R.); Department of
Radiology, Geisel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.A.); and
Department of Radiology, University of North Carolina, Chapel Hill, NC
(L.M.H.)
| | - Louise M. Henderson
- From the Department of Radiology, University of Washington School of
Medicine, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson
Cancer Center, 825 Eastlake Ave E, LG-200, Seattle, WA 98109 (C.I.L., J.M.L.);
Department of Health Systems & Population Health, University of
Washington School of Public Health, Seattle, Wash (C.I.L.); Kaiser Permanente
Washington Health Research Institute, Kaiser Permanente Washington, Seattle,
Wash (C.I.L., L.A., D.L.M., J.M.L., E.J.A.B.); Division of Biostatistics,
Department of Public Health Sciences, University of California Davis School of
Medicine, Davis, Calif (D.L.M.); Department of Population Health Sciences, and
the Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (T.O.);
Department of Medicine, Department of Epidemiology and Biostatistics, and
General Internal Medicine Section, Department of Veterans Affairs, University of
California, San Francisco, San Francisco, Calif (K.K.); Department of Surgery,
Office of Health Promotion Research, Larner College of Medicine at the
University of Vermont and University of Vermont Cancer Center, Burlington, Vt
(B.L.S.); The Dartmouth Institute for Health Policy and Clinical Practice,
Geisel School of Medicine at Dartmouth and Norris Cotton Cancer Center, Lebanon,
NH (A.N.A.T.); Division of Epidemiology and Biostatistics, School of Public
Health, University of Illinois at Chicago, Chicago, Ill (G.H.R.); Department of
Radiology, Geisel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.A.); and
Department of Radiology, University of North Carolina, Chapel Hill, NC
(L.M.H.)
| | - for the Breast Cancer Surveillance Consortium
- From the Department of Radiology, University of Washington School of
Medicine, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson
Cancer Center, 825 Eastlake Ave E, LG-200, Seattle, WA 98109 (C.I.L., J.M.L.);
Department of Health Systems & Population Health, University of
Washington School of Public Health, Seattle, Wash (C.I.L.); Kaiser Permanente
Washington Health Research Institute, Kaiser Permanente Washington, Seattle,
Wash (C.I.L., L.A., D.L.M., J.M.L., E.J.A.B.); Division of Biostatistics,
Department of Public Health Sciences, University of California Davis School of
Medicine, Davis, Calif (D.L.M.); Department of Population Health Sciences, and
the Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah (T.O.);
Department of Medicine, Department of Epidemiology and Biostatistics, and
General Internal Medicine Section, Department of Veterans Affairs, University of
California, San Francisco, San Francisco, Calif (K.K.); Department of Surgery,
Office of Health Promotion Research, Larner College of Medicine at the
University of Vermont and University of Vermont Cancer Center, Burlington, Vt
(B.L.S.); The Dartmouth Institute for Health Policy and Clinical Practice,
Geisel School of Medicine at Dartmouth and Norris Cotton Cancer Center, Lebanon,
NH (A.N.A.T.); Division of Epidemiology and Biostatistics, School of Public
Health, University of Illinois at Chicago, Chicago, Ill (G.H.R.); Department of
Radiology, Geisel School of Medicine at Dartmouth, Lebanon, NH (R.M.d.A.); and
Department of Radiology, University of North Carolina, Chapel Hill, NC
(L.M.H.)
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19
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Berg WA, Zuley ML, Chang TS, Gizienski TA, Chough DM, Böhm-Vélez M, Sharek DE, Straka MR, Hakim CM, Hartman JY, Harnist KS, Tyma CS, Kelly AE, Waheed U, Houshmand G, Nair BE, Shinde DD, Lu AH, Bandos AI, Berg JM, Lettiere NB, Ganott MA. Prospective Multicenter Diagnostic Performance of Technologist-Performed Screening Breast Ultrasound After Tomosynthesis in Women With Dense Breasts (the DBTUST). J Clin Oncol 2023; 41:2403-2415. [PMID: 36626696 PMCID: PMC10150890 DOI: 10.1200/jco.22.01445] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2022] [Revised: 10/25/2022] [Accepted: 11/19/2022] [Indexed: 01/11/2023] Open
Abstract
PURPOSE To assess diagnostic performance of digital breast tomosynthesis (DBT) alone or combined with technologist-performed handheld screening ultrasound (US) in women with dense breasts. METHODS In an institutional review board-approved, Health Insurance Portability and Accountability Act-compliant multicenter protocol in western Pennsylvania, 6,179 women consented to three rounds of annual screening, interpreted by two radiologist observers, and had appropriate follow-up. Primary analysis was based on first observer results. RESULTS Mean participant age was 54.8 years (range, 40-75 years). Across 17,552 screens, there were 126 cancer events in 125 women (7.2/1,000; 95% CI, 5.9 to 8.4). In year 1, DBT-alone cancer yield was 5.0/1,000, and of DBT+US, 6.3/1,000, difference 1.3/1,000 (95% CI, 0.3 to 2.1; P = .005). In years 2 + 3, DBT cancer yield was 4.9/1,000, and of DBT+US, 5.9/1,000, difference 1.0/1,000 (95% CI, 0.4 to 1.5; P < .001). False-positive rate increased from 7.0% for DBT in year 1 to 11.5% for DBT+US and from 5.9% for DBT in year 2 + 3 to 9.7% for DBT+US (P < .001 for both). Nine cancers were seen only by double reading DBT and one by double reading US. Ten interval cancers (0.6/1,000 [95% CI, 0.2 to 0.9]) were identified. Despite reduction in specificity, addition of US improved receiver operating characteristic curves, with area under receiver operating characteristic curve increasing from 0.83 for DBT alone to 0.92 for DBT+US in year 1 (P = .01), with smaller improvements in subsequent years. Of 6,179 women, across all 3 years, 172/6,179 (2.8%) unique women had a false-positive biopsy because of DBT as did another 230/6,179 (3.7%) women because of US (P < .001). CONCLUSION Overall added cancer detection rate of US screening after DBT was modest at 19/17,552 (1.1/1,000; CI, 0.5- to 1.6) screens but potentially overcomes substantial increases in false-positive recalls and benign biopsies.
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Affiliation(s)
- Wendie A. Berg
- Department of Radiology, University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Pittsburgh, PA
| | - Margarita L. Zuley
- Department of Radiology, University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Pittsburgh, PA
| | | | - Terri-Ann Gizienski
- Department of Radiology, University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Pittsburgh, PA
| | - Denise M. Chough
- Department of Radiology, University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Pittsburgh, PA
| | | | | | | | - Christiane M. Hakim
- Department of Radiology, University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Pittsburgh, PA
| | - Jamie Y. Hartman
- Department of Radiology, University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Pittsburgh, PA
| | - Kimberly S. Harnist
- Department of Radiology, University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Pittsburgh, PA
| | - Cathy S. Tyma
- Department of Radiology, University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Pittsburgh, PA
- Department of Radiology, New York University Grossman School of Medicine, New York, NY
| | - Amy E. Kelly
- Department of Radiology, University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Pittsburgh, PA
| | - Uzma Waheed
- Department of Radiology, University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Pittsburgh, PA
- Department of Radiology, Stanford University School of Medicine, Stanford, CA
| | - Golbahar Houshmand
- Department of Radiology, University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Pittsburgh, PA
- Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Bronwyn E. Nair
- Department of Radiology, University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Pittsburgh, PA
| | - Dilip D. Shinde
- Department of Radiology, University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Pittsburgh, PA
| | - Amy H. Lu
- Department of Radiology, University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Pittsburgh, PA
| | - Andriy I. Bandos
- Department of Biostatistics, University of Pittsburgh School of Public Health, Pittsburgh, PA
| | - Jeremy M. Berg
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Nicole B. Lettiere
- Department of Radiology, University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Pittsburgh, PA
- ICON-Amgen, Pittsburgh, PA
| | - Marie A. Ganott
- Department of Radiology, University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, Pittsburgh, PA
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20
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Conant EF, Talley MM, Parghi CR, Sheh BC, Liang SY, Pohlman S, Rane A, Jung Y, Stevens LAS, Paulus JK, Alsheik N. Mammographic Screening in Routine Practice: Multisite Study of Digital Breast Tomosynthesis and Digital Mammography Screenings. Radiology 2023; 307:e221571. [PMID: 36916891 DOI: 10.1148/radiol.221571] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
Background The use of digital breast tomosynthesis (DBT) is increasing over digital mammography (DM) following studies demonstrating lower recall rates (RRs) and higher cancer detection rates (CDRs). However, inconsistent interpretation of evidence on the risks and benefits of mammography has resulted in varying screening mammography recommendations. Purpose To evaluate screening outcomes among women in the United States who underwent routine DM or DBT mammographic screening. Materials and Methods This retrospective cohort study included women aged 40-79 years who underwent DM or DBT screening mammograms between January 2014 and December 2020. Outcomes of RR, CDR, positive predictive value of recall (PPV1), biopsy rate, and positive predictive value of biopsy (PPV3) were compared between DM and DBT with use of adjusted multivariable logistic regression models. Results A total of 2 528 063 screening mammograms from 1 100 447 women (mean age, 57 years ± 10 [SD]) were included. In crude analyses, DBT (1 693 727 screening mammograms vs 834 336 DM screening mammograms) demonstrated lower RR (10.3% [95% CI: 10.3, 10.4] for DM vs 8.9% [95% CI: 8.9, 9.0] for DBT; P < .001) and higher CDR (4.5 of 1000 screening mammograms [95% CI: 4.3, 4.6] vs 5.3 of 1000 [95% CI: 5.2, 5.5]; P < .001), PPV1 (4.3% [95% CI: 4.2, 4.5] vs 5.9% [95% CI: 5.7, 6.0]; P < .001), and biopsy rates (14.5 of 1000 screening mammograms [95% CI: 14.2, 14.7] vs 17.6 of 1000 [95% CI: 17.4, 17.8]; P < .001). PPV3 was similar between cohorts (30.0% [95% CI: 29.2, 30.9] for DM vs 29.3% [95% CI: 28.7, 29.9] for DBT; P = .16). After adjustment for age, breast density, site, and index year, associations remained stable with respect to statistical significance. Conclusion Women undergoing digital breast tomosynthesis had improved screening mammography outcomes compared with women who underwent digital mammography. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Bae and Seo in this issue.
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Affiliation(s)
- Emily F Conant
- From the Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce St, Philadelphia, PA 19104 (E.F.C.); Sanford Health, Sioux Falls, SD (M.M.T.); Solis Mammography, Houston, Tex (C.R.P.); Sutter Health, Fremont, Calif (B.C.S.); Sutter Health, Palo Alto, Calif (S.Y.L.); Hologic, Marlborough, Mass (S.P., A.R.); OM1, Boston, Mass (Y.J., L.A.S.S., J.K.P.); and Department of Radiology, Advocate Caldwell Breast Center, Park Ridge, Ill (N.A.)
| | - Melinda M Talley
- From the Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce St, Philadelphia, PA 19104 (E.F.C.); Sanford Health, Sioux Falls, SD (M.M.T.); Solis Mammography, Houston, Tex (C.R.P.); Sutter Health, Fremont, Calif (B.C.S.); Sutter Health, Palo Alto, Calif (S.Y.L.); Hologic, Marlborough, Mass (S.P., A.R.); OM1, Boston, Mass (Y.J., L.A.S.S., J.K.P.); and Department of Radiology, Advocate Caldwell Breast Center, Park Ridge, Ill (N.A.)
| | - Chirag R Parghi
- From the Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce St, Philadelphia, PA 19104 (E.F.C.); Sanford Health, Sioux Falls, SD (M.M.T.); Solis Mammography, Houston, Tex (C.R.P.); Sutter Health, Fremont, Calif (B.C.S.); Sutter Health, Palo Alto, Calif (S.Y.L.); Hologic, Marlborough, Mass (S.P., A.R.); OM1, Boston, Mass (Y.J., L.A.S.S., J.K.P.); and Department of Radiology, Advocate Caldwell Breast Center, Park Ridge, Ill (N.A.)
| | - Bryant C Sheh
- From the Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce St, Philadelphia, PA 19104 (E.F.C.); Sanford Health, Sioux Falls, SD (M.M.T.); Solis Mammography, Houston, Tex (C.R.P.); Sutter Health, Fremont, Calif (B.C.S.); Sutter Health, Palo Alto, Calif (S.Y.L.); Hologic, Marlborough, Mass (S.P., A.R.); OM1, Boston, Mass (Y.J., L.A.S.S., J.K.P.); and Department of Radiology, Advocate Caldwell Breast Center, Park Ridge, Ill (N.A.)
| | - Su-Ying Liang
- From the Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce St, Philadelphia, PA 19104 (E.F.C.); Sanford Health, Sioux Falls, SD (M.M.T.); Solis Mammography, Houston, Tex (C.R.P.); Sutter Health, Fremont, Calif (B.C.S.); Sutter Health, Palo Alto, Calif (S.Y.L.); Hologic, Marlborough, Mass (S.P., A.R.); OM1, Boston, Mass (Y.J., L.A.S.S., J.K.P.); and Department of Radiology, Advocate Caldwell Breast Center, Park Ridge, Ill (N.A.)
| | - Scott Pohlman
- From the Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce St, Philadelphia, PA 19104 (E.F.C.); Sanford Health, Sioux Falls, SD (M.M.T.); Solis Mammography, Houston, Tex (C.R.P.); Sutter Health, Fremont, Calif (B.C.S.); Sutter Health, Palo Alto, Calif (S.Y.L.); Hologic, Marlborough, Mass (S.P., A.R.); OM1, Boston, Mass (Y.J., L.A.S.S., J.K.P.); and Department of Radiology, Advocate Caldwell Breast Center, Park Ridge, Ill (N.A.)
| | - Amey Rane
- From the Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce St, Philadelphia, PA 19104 (E.F.C.); Sanford Health, Sioux Falls, SD (M.M.T.); Solis Mammography, Houston, Tex (C.R.P.); Sutter Health, Fremont, Calif (B.C.S.); Sutter Health, Palo Alto, Calif (S.Y.L.); Hologic, Marlborough, Mass (S.P., A.R.); OM1, Boston, Mass (Y.J., L.A.S.S., J.K.P.); and Department of Radiology, Advocate Caldwell Breast Center, Park Ridge, Ill (N.A.)
| | - Yoojin Jung
- From the Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce St, Philadelphia, PA 19104 (E.F.C.); Sanford Health, Sioux Falls, SD (M.M.T.); Solis Mammography, Houston, Tex (C.R.P.); Sutter Health, Fremont, Calif (B.C.S.); Sutter Health, Palo Alto, Calif (S.Y.L.); Hologic, Marlborough, Mass (S.P., A.R.); OM1, Boston, Mass (Y.J., L.A.S.S., J.K.P.); and Department of Radiology, Advocate Caldwell Breast Center, Park Ridge, Ill (N.A.)
| | - Lauren A S Stevens
- From the Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce St, Philadelphia, PA 19104 (E.F.C.); Sanford Health, Sioux Falls, SD (M.M.T.); Solis Mammography, Houston, Tex (C.R.P.); Sutter Health, Fremont, Calif (B.C.S.); Sutter Health, Palo Alto, Calif (S.Y.L.); Hologic, Marlborough, Mass (S.P., A.R.); OM1, Boston, Mass (Y.J., L.A.S.S., J.K.P.); and Department of Radiology, Advocate Caldwell Breast Center, Park Ridge, Ill (N.A.)
| | - Jessica K Paulus
- From the Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce St, Philadelphia, PA 19104 (E.F.C.); Sanford Health, Sioux Falls, SD (M.M.T.); Solis Mammography, Houston, Tex (C.R.P.); Sutter Health, Fremont, Calif (B.C.S.); Sutter Health, Palo Alto, Calif (S.Y.L.); Hologic, Marlborough, Mass (S.P., A.R.); OM1, Boston, Mass (Y.J., L.A.S.S., J.K.P.); and Department of Radiology, Advocate Caldwell Breast Center, Park Ridge, Ill (N.A.)
| | - Nila Alsheik
- From the Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce St, Philadelphia, PA 19104 (E.F.C.); Sanford Health, Sioux Falls, SD (M.M.T.); Solis Mammography, Houston, Tex (C.R.P.); Sutter Health, Fremont, Calif (B.C.S.); Sutter Health, Palo Alto, Calif (S.Y.L.); Hologic, Marlborough, Mass (S.P., A.R.); OM1, Boston, Mass (Y.J., L.A.S.S., J.K.P.); and Department of Radiology, Advocate Caldwell Breast Center, Park Ridge, Ill (N.A.)
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21
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Cömert D, van Gils CH, Veldhuis WB, Mann RM. Challenges and Changes of the Breast Cancer Screening Paradigm. J Magn Reson Imaging 2023; 57:706-726. [PMID: 36349728 DOI: 10.1002/jmri.28495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 10/07/2022] [Accepted: 10/07/2022] [Indexed: 11/11/2022] Open
Abstract
Since four decades mammography is used for early breast cancer detection in asymptomatic women and still remains the gold standard imaging modality. However, population screening programs can be personalized and women can be divided into different groups based on risk factors and personal preferences. The availability of new and evolving imaging modalities, for example, digital breast tomosynthesis, dynamic-contrast-enhanced magnetic resonance imaging (MRI), abbreviated MRI protocols, diffusion-weighted MRI, and contrast-enhanced mammography leads to new challenges and perspectives regarding the feasibility and potential harms of breast cancer screening. The aim of this review is to discuss the current guidelines for different risk groups, to analyze the recent published studies about the diagnostic performance of the imaging modalities and to discuss new developments and future perspectives. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 6.
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Affiliation(s)
- Didem Cömert
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.,Department of Radiology and Nuclear Medicine, Utrecht University Medical Center, Utrecht, The Netherlands
| | - Carla H van Gils
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Wouter B Veldhuis
- Department of Radiology and Nuclear Medicine, Utrecht University Medical Center, Utrecht, The Netherlands
| | - Ritse M Mann
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.,Department of Radiology, The Netherlands Cancer Institute/Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
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22
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Weigel S, Heindel W, Hense HW, Decker T, Gerß J, Kerschke L. Breast Density and Breast Cancer Screening with Digital Breast Tomosynthesis: A TOSYMA Trial Subanalysis. Radiology 2023; 306:e221006. [PMID: 36194110 DOI: 10.1148/radiol.221006] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Background Digital breast tomosynthesis (DBT) plus synthesized mammography (SM) reduces the diagnostic pitfalls of tissue superimposition, which is a limitation of digital mammography (DM). Purpose To compare the invasive breast cancer detection rate (iCDR) of DBT plus SM versus DM screening for different breast density categories. Materials and Methods An exploratory subanalysis of the TOmosynthesis plus SYnthesized MAmmography (TOSYMA) study, a randomized, controlled, multicenter, parallel-group trial recruited within the German mammography screening program from July 2018 to December 2020. Women aged 50-69 years were randomly assigned (1:1) to DBT plus SM or DM screening examination. Breast density categories A-D were visually assessed according to the Breast Imaging Reporting and Data System Atlas. Exploratory analyses were performed of the iCDR in both study arms and stratified by breast density, and odds ratios and 95% CIs were determined. Results A total of 49 762 women allocated to DBT plus SM and 49 796 allocated to DM (median age, 57 years [IQR, 53-62 years]) were included. In the DM arm, the iCDR was 3.6 per 1000 screening examinations in category A (almost entirely fatty) (16 of 4475 screenings), 4.3 in category B (102 of 23 534 screenings), 6.1 in category C (116 of 19 051 screenings), and 2.3 in category D (extremely dense breasts) (six of 2629 screenings). The iCDR in the DBT plus SM arm was 2.7 per 1000 screening examinations in category A (12 of 4439 screenings), 6.9 in category B (154 of 22 328 screenings), 8.3 in category C (156 of 18 772 screenings), and 8.1 in category D (32 of 3940 screenings). The odds ratio for DM versus DBT plus SM in category D was 3.8 (95% CI: 1.5, 11.1). The invasive cancers detected with DBT plus SM were most often grade 2 tumors; in category C, it was 58% (91 of 156 invasive cancers), and in category D, it was 47% (15 of 32 invasive cancers). Conclusion The TOmosynthesis plus SYnthesized MAmmography trial revealed higher invasive cancer detection rates with digital breast tomosynthesis plus synthesized mammography than digital mammography in dense breasts, relatively and absolutely most marked among women with extremely dense breasts. ClinicalTrials.gov registration no.: NCT03377036 © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Lee and Moy in this issue.
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Affiliation(s)
- Stefanie Weigel
- From the Clinic for Radiology and Reference Center for Mammography Münster, University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany (S.W., W.H., T.D.); Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany (H.W.H.); and Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany (J.G., L.K.)
| | - Walter Heindel
- From the Clinic for Radiology and Reference Center for Mammography Münster, University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany (S.W., W.H., T.D.); Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany (H.W.H.); and Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany (J.G., L.K.)
| | - Hans-Werner Hense
- From the Clinic for Radiology and Reference Center for Mammography Münster, University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany (S.W., W.H., T.D.); Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany (H.W.H.); and Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany (J.G., L.K.)
| | - Thomas Decker
- From the Clinic for Radiology and Reference Center for Mammography Münster, University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany (S.W., W.H., T.D.); Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany (H.W.H.); and Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany (J.G., L.K.)
| | - Joachim Gerß
- From the Clinic for Radiology and Reference Center for Mammography Münster, University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany (S.W., W.H., T.D.); Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany (H.W.H.); and Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany (J.G., L.K.)
| | - Laura Kerschke
- From the Clinic for Radiology and Reference Center for Mammography Münster, University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany (S.W., W.H., T.D.); Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany (H.W.H.); and Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany (J.G., L.K.)
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- From the Clinic for Radiology and Reference Center for Mammography Münster, University of Münster and University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, D-48149 Münster, Germany (S.W., W.H., T.D.); Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany (H.W.H.); and Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany (J.G., L.K.)
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23
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Zhuang L, Chen Q, Chen H, Zheng X, Liu X, Feng Z, Wu S, Liu L, Shen X. Breast cancer-related lymphedema and recurrence of breast cancer: Protocol for a prospective cohort study in China. PLoS One 2023; 18:e0285772. [PMID: 37192209 DOI: 10.1371/journal.pone.0285772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 04/29/2023] [Indexed: 05/18/2023] Open
Abstract
INTRODUCTION The primary aim is to determine the factors associated with breast cancer-related lymphedema and to identify new associated factors for the recurrence of breast cancer and depression. The secondary objective is to investigate the incidence of breast cancer-related events (breast cancer-related lymphedema, recurrence of breast cancer, and depression). Finally, we want to explore and validate the complex relationship among multiple factors influencing breast cancer complications and breast cancer recurrence. PATIENTS AND METHODS A cohort study of females with unilateral breast cancer will be conducted in West China Hospital between February 2023 and February 2026. Breast cancer survivors in the age range of 17-55 will be recruited before breast cancer surgery. We will recruit 1557 preoperative patients with a first invasive breast cancer diagnosis. Consenting breast cancer survivors will complete demographic information, clinicopathological factors, surgery information, baseline information, and a baseline depression questionnaire. Data will be collected at four stages: the perioperative stage, chemotherapy therapy stage, radiation therapy stage, and follow-up stage. Data including the incidence and correlation of breast cancer-related lymphedema, breast cancer recurrence, depression, and medical cost will be collected and computed through the four stages above. For every statistical analysis, the participants will be classified into two groups based on whether they develop secondary lymphedema. Incidence rates of breast cancer recurrence and depression will be calculated separately for groups. Multivariate logistic regression will be used to determine whether secondary lymphedema and other parameters can predict breast cancer recurrence. DISCUSSION Our prospective cohort study will contribute to establishing an early detection program for breast cancer-related lymphedema and recurrence of breast cancer, which are both associated with poor quality of life and reduced life expectancy. Our study can also provide new insights into the physical, economic, treatment-related and mental burdens of breast cancer survivors.
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Affiliation(s)
- Linli Zhuang
- Department of Rheumatology and Immunology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Qian Chen
- Center of Biostatistics, Design, Measurement and Evaluation, Department of Clinical Research Management, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Huaying Chen
- Department of Head and Neck Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Xuemei Zheng
- Department of Head and Neck Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Xia Liu
- Department of Abdominal Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Zhenzhen Feng
- Department of Head and Neck Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
- Unit of Cancer Day Care, West China Hospital, Sichuan University, Chengdu, China
| | - Shaoyong Wu
- Department of Head and Neck Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Li Liu
- Department of Head and Neck Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Xiaolin Shen
- Department of Rheumatology and Immunology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
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24
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Potnis KC, Ross JS, Aneja S, Gross CP, Richman IB. Artificial Intelligence in Breast Cancer Screening: Evaluation of FDA Device Regulation and Future Recommendations. JAMA Intern Med 2022; 182:1306-1312. [PMID: 36342705 PMCID: PMC10623674 DOI: 10.1001/jamainternmed.2022.4969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Importance Contemporary approaches to artificial intelligence (AI) based on deep learning have generated interest in the application of AI to breast cancer screening (BCS). The US Food and Drug Administration (FDA) has approved several next-generation AI products indicated for BCS in recent years; however, questions regarding their accuracy, appropriate use, and clinical utility remain. Objectives To describe the current FDA regulatory process for AI products, summarize the evidence used to support FDA clearance and approval of AI products indicated for BCS, consider the advantages and limitations of current regulatory approaches, and suggest ways to improve the current system. Evidence Review Premarket notifications and other publicly available documents used for FDA clearance and approval of AI products indicated for BCS from January 1, 2017, to December 31, 2021. Findings Nine AI products indicated for BCS for identification of suggestive lesions and mammogram triage were included. Most of the products had been cleared through the 510(k) pathway, and all clearances were based on previously collected retrospective data; 6 products used multicenter designs; 7 products used enriched data; and 4 lacked details on whether products were externally validated. Test performance measures, including sensitivity, specificity, and area under the curve, were the main outcomes reported. Most of the devices used tissue biopsy as the criterion standard for BCS accuracy evaluation. Other clinical outcome measures, including cancer stage at diagnosis and interval cancer detection, were not reported for any of the devices. Conclusions and Relevance The findings of this review suggest important gaps in reporting of data sources, data set type, validation approach, and clinical utility assessment. As AI-assisted reading becomes more widespread in BCS and other radiologic examinations, strengthened FDA evidentiary regulatory standards, development of postmarketing surveillance, a focus on clinically meaningful outcomes, and stakeholder engagement will be critical for ensuring the safety and efficacy of these products.
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Affiliation(s)
| | - Joseph S Ross
- Section of General Medicine, Department of Medicine, Yale School of Medicine, New Haven, Connecticut
- Center for Outcomes Research and Evaluation, Yale School of Medicine, New Haven, Connecticut
- Department of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut
| | - Sanjay Aneja
- Center for Outcomes Research and Evaluation, Yale School of Medicine, New Haven, Connecticut
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, Connecticut
| | - Cary P Gross
- Section of General Medicine, Department of Medicine, Yale School of Medicine, New Haven, Connecticut
- Cancer Outcomes, Public Policy, and Effectiveness Research Center, Yale School of Medicine, New Haven, Connecticut
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut
| | - Ilana B Richman
- Section of General Medicine, Department of Medicine, Yale School of Medicine, New Haven, Connecticut
- Cancer Outcomes, Public Policy, and Effectiveness Research Center, Yale School of Medicine, New Haven, Connecticut
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25
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Yong-Hing CJ, Gordon PB, Appavoo S, Fitzgerald SR, Seely JM. Addressing Misinformation About the Canadian Breast Screening Guidelines. Can Assoc Radiol J 2022; 74:388-397. [PMID: 36048585 DOI: 10.1177/08465371221120798] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Screening mammography has been shown to reduce breast cancer mortality by 41% in screened women ages 40-69 years. There is misinformation about breast screening and the Canadian breast screening guidelines. This can decrease confidence in screening mammography and can lead to suboptimal recommendations. We review some of this misinformation to help radiologists and referring physicians navigate the varied international and provincial guidelines. We address the ages to start and stop breast screening. We explore how these recommendations may vary for specific populations such as patients who are at increased risk, transgender patients and minorities. We identify who would benefit from supplemental screening and review the available supplemental screening modalities including ultrasound, MRI, contrast-enhanced mammography and others. We describe emerging technologies including the potential use of artificial intelligence for breast screening. We provide background on why screening policies vary across the country between provinces and territories. This review is intended to help radiologists and referring physicians understand and navigate the varied international and provincial recommendations and guidelines and make the best recommendations for their patients.
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Affiliation(s)
- Charlotte J Yong-Hing
- Faculty of Medicine, Department of Radiology, 8166University of British Columbia, Vancouver, BC, Canada
| | - Paula B Gordon
- Faculty of Medicine, Department of Radiology, 8166University of British Columbia, Vancouver, BC, Canada
| | - Shushiela Appavoo
- Department of Radiology and Diagnostic Imaging, 3158University of Alberta, Edmonton, AB, Canada
| | - Sabrina R Fitzgerald
- Faculty of Medicine, Department of Radiology, 7938University of Toronto, Toronto, ON, Canada
| | - Jean M Seely
- Faculty of Medicine, Department of Radiology, University of Ottawa, Ottawa, ON, Canada.,Ottawa Hospital Research Institute, Ottawa, ON, Canada.,Ontario Breast Screening Program, Ottawa, ON, Canada
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