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Yang et al. BMC Cancer (2020) 20:499 https://doi.org/10.1186/s12885-020-06992-1 RESEARCH ARTICLE Open Access Performance of ultrasonography screening for breast cancer: a systematic review and meta-analysis Lei Yang1†, Shengfeng Wang2†, Liwen Zhang3,4, Chao Sheng3,4, Fengju Song3,4, Ping Wang3,4 and Yubei Huang3,4* Abstract Background: To investigate the performance of primary ultrasound (P-US) screening for breast cancer, and that of supplemental ultrasound (S-US) screening for breast cancer after negative mammography (MAM). Methods: Electronic databases (PubMed, Scopus, Web of Science, and Embase) were systematically searched to identify relevant studies published between January 2003 and May 2018. Only high-quality or fair-quality studies reporting any of the following performance values for P-US or S-US screening were included: sensitivity, specificity, cancer detected rate (CDR), recall rate (RR), biopsy rate (BR), proportion of invasive cancers among screening-detected cancers (ProIC), and proportion of node-negative cancers among screening-detected invasive cancers (ProNNIC). Results: Twenty-three studies were included, including 12 studies in which S-US screening was used after negative MAM and 11 joint screening studies in which both primary MAM (P-MAM) and P-US were used. Meta-analyses revealed that SUS screening could detect 96% [95% confidential intervals (CIs): 82 to 99%] of occult breast cancers missed by MAM and identify 93% (95% CIs: 89 to 96%) of healthy women, with a CDR of 3.0/1000 (95% CIs: 1.8/1000 to 4.6/1000), RR of 8.8% (95% CIs: 5.0 to 13.4%), BR of 3.9% (95% CIs: 2.7 to 5.4%), ProIC of 73.9% (95% CIs: 49.0 to 93.7%), and ProNNIC of 70.9% (95% CIs: 46.0 to 91.6%). Compared with P-MAM screening, P-US screening led to the recall of significantly more women with positive screening results [1.5% (95% CIs:0.6 to 2.3%), P = 0.001] and detected significantly more invasive cancers [16.3% (95% CIs: 10.6 to 22.1%), P < 0.001]. However, there were no significant differences for other performance measures between the two screening methods, including sensitivity, specificity, CDR, BR, and ProNNIC. Conclusions: Current evidence suggests that S-US screening could detect occult breast cancers missed by MAM. P-US screening has shown to be comparable to P-MAM screening in women with dense breasts in terms of sensitivity, specificity, cancer detection rate, and biopsy rate, but with higher recall rates and higher detection rates for invasive cancers. Keywords: Breast cancer, Screening, Ultrasonography, Mammography, Supplemental ultrasonography * Correspondence: yubei_huang@163.com † Lei Yang and Shengfeng Wang contributed equally to this work. 3 Department of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy (Tianjin), Key Laboratory of Breast Cancer Prevention and Therapy (National Ministry of Education), Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China 4 National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Yang et al. BMC Cancer (2020) 20:499 Background Cancer is a global public health issue in the world. In 2016, an estimated 17.2 million cancer cases and 8.9 million cancer deaths occurred worldwide [1]. For women, both the most commonly occuring cancer and the leading cause of cancer deaths and disability-adjusted life-years (DALYs) was breast cancer (1.7 million incident cases, 535, 000 deaths, and 14.9 million DALYs) [1]. Over the years, the burden of cancer has shifted from more developed countries to less developed countries [2]. Moreover, the burden is expected to grow worldwide due to the aging of the population and the adoption of lifestyle behaviors such as smoking, poor diet, physical inactivity, and reproductive changes (including lower parity and later age at first birth), particularly in less developed countries [3]. Therefore, broad prevention measures, such as cancer screening, are urgently needed to control this increasing burden, especially in less developed countries. Mammography (MAM) has been used to screen for breast cancer since the 1970s and is now widely available in developed countries. However, in less developed counties, such as China, MAM is not easily accessible due to several barriers, including insufficient MAM equipment, inadequate insurance coverage for MAM, and widely dispersed populations [3]. Moreover, MAM has a low sensitivity in women with dense breasts [4], who could suffer a higher risk of breast cancer than those without dense breasts [5]. Worrisome researches from Denmark and Netherlands showed that nearly one in every three or half of screening-detected breast cancers represents overdiagnosis, respectively [6, 7]. Recent data indicates that supplemental ultrasonography (S-US) screening could detect occult breast cancers missed by MAM, and primary ultrasonography (P-US) screening seems to perform comparably to primary MAM (P-MAM) screening [8–11]. However, systematic reviews of the performances of S-US or P-US screening have been published only in limited studies. Moreover, among broad screening studies in which both P-MAM and P-US were used, researchers just focused on the performance differences between joint screening and P-MAM screening alone. Limited studies investigated the independent performances of P-US screening. Therefore, we conducted this systematic review and meta-analysis to provide a global profile of S-US screening after negative MAM screening or P-US screening for breast cancers. Methods This meta-analysis was reported in line with the preferred reporting items for a systematic review and meta-analysis of diagnostic test accuracy studies: The PRISMA-DTA Statement [12]. Types of studies and participants Randomized-controlled trials (RCTs), prospective or retrospective screening cohort studies focusing on the Page 2 of 15 performance of P-US screening for breast cancer or performance of S-US screening for breast cancer after negative MAM were included. The screening performance included the following indicators: sensitivity, specificity, cancer detected rate (CDR), recall rate (RR), biopsy rate (BR), proportions of invasive cancers among screeningdetected cancers (ProIC), and proportions of node-negative invasive cancers among screening-detected invasive cancers (ProNNIC). The types of ultrasonography (US) included were hand-held ultrasonography (HHUS) and automated whole breast ultrasonography (ABUS). Diagnostic studies of patients with histopathologically proven breast cancer or women with suspicious finding after initial screening were excluded. Screening studies for second cancers among women previously diagnosed with breast cancer were also excluded. Searching strategies A comprehensive search was conducted according to the Cochrane handbook guidelines. The American College of Radiology (ACR) developed the Breast Imaging Reporting and Data System (BI-RADS) classification for breast ultrasonography examinations starting in 2003 [13]. Electronic databases (PubMed, Scopus, Web of Science, and Embase) were systematically searched to identify relevant studies published in English between January 2003 and May 2018. Five groups of key words were used in the searching strategies: (1) breast neoplasm, breast cancer, breast carcinoma; (2) ultrasound, ultrasonography; (3) screening; (4) supplemental, supplementary, adjunct, adjunctive, combined, joint, primary, single, alone; (5) sensitivity, specificity, detection rate, recall rate, biopsy rate. Reference lists from retrieved articles were also reviewed. Detailed searching strategies are referred to in the supplementary S1. Selection of studies Two authors independently screened the titles and abstracts of all selected articles to confirm their eligibility. All selected articles were analyzed by EndNote software that allows reviewers to manage articles and detect duplicate publications. When two or more articles from the same trial were selected, the article with the larger sample size, longer duration of follow-up, or the latest results was included. Any disagreement on the selection of articles was discussed and arbitrated by a third author. Details of the selection process are provided in the supplementary S2. Data extraction Two authors independently extracted the following data from the qualifying studies: general information (name of first author, year of publication, and country or countries where the study was performed), design of study (sample size, median age, percent of women with dense Yang et al. BMC Cancer (2020) 20:499 breasts among the whole population, type of US, screening mode), performance of US, and information for risk assessment of bias (detailed information referred to in the following section). Since there was not a consistent conclusion that dense breast can be regarded as an independent risk factor of breast cancer [5, 14], in order to avoid bringing ‘high risk’ labels to women with dense breasts, we collected information of dense breast as an attribute for average risk women. All data was entered into STATA 14.0 software for analysis. Any disagreements on data extracted were also discussed and arbitrated by the same third author. Risk assessment of bias in included studies Two investigators critically appraised all included studies independently according to the pre-specified criteria, which were adjusted from the USPSTF’s design-specific criteria and the STARD checklist for reporting diagnostic accuracy studies [15, 16]. The adjusted criteria included 7 items: source of population, sample size, inclusion and exclusion criteria, blinding of test, data completeness, BIRADS criteria, and reference standards. Result of each item was classified as high-risk or low-risk. Detailed information of the adjusted risk assessment criteria of bias refered to supplementary S3. According to the above-mentioned criteria, highquality studies were defined as those meeting at least six low-risk items for joint screening studies and five lowrisk items for S-US screening studies. Fair-quality studies meet four or five low-risk items for joint screening studies and three or four low-risk items for S-US screening studies. Poor quality studies were defined as those meeting less than four low-risk items for joint screening studies and three low-risk items for S-US screening studies. Poor studies were excluded from the review. Data synthesis and analysis All data were extracted with pre-specified uniform tables and recalculated with uniform methods. The corresponding authors were contacted to obtain any missing information from their studies. For those studies in which the number of ‘examinations’ rather than the number of ‘women’ as the denominator to calculate the detection rate of breast cancer, each woman would be followed up several times, and every time she had an examination. Therefore, each woman would have several examinations in these stuides. In this study, if we changed the number of ‘women’ as the denominator to calculate the detection rate for these studies, the results would significantly be overestimated since the number of ‘women’ was significantly less than the number of ‘examinations’. Therefore, in order to follow the analysis protocol in the original studies and avoid potential overestimate in detection rate, we equate each examination Page 3 of 15 with an independent woman. However, equating each examination with an independent woman could bias the estimate because observations within a woman are not ‘independent’ observations. Cancer detected rate was defined as any cancer detected (including carcinoma in situ and invasive cancer but not high-risk precancerous lesion) among all examinations/participants. The recall rate was calculated as the number of women recalled for further diagnosed examinations divided by the total number of women who participated the screening. If the number of women recalled for any further diagnosed examinations was not available, the number of women with a positive result of index screening modality was used instead. The biopsy rate was calculated as the number of women recalled for pathological examination divided by the total number of women participated the screening. The variation in different screening performances attributable to heterogeneity was measured as I2. If the P value for I2 was less than 0.1, significant heterogeneity was indicated among included trials and the random-effect model was used to combine screening performances [17]. Otherwise, the fixed-effect model was used if the P value for I2 was larger than 0.1. To search for sources of heterogeneity and obtain clinically meaningful estimates, subgroup analyses were conducted according to different studies characteristics, such as sample size > 1000 (Yes/No), all women with dense breasts (Yes/No), type of US (HHUS/ABUS), and quality assessment (Yes/No), whenever possible. The package “midas” was used to combine sensitivity and specificity, to investigate whether there were potential publication biases among included studies, and to plot the summary receiver operating characteristic (SROC) curve with its 95% confidence and prediction contours [18]. The package “metaprop” was used to combine CDR, RR, BR, ProIC, and ProNNIC [19]. In addition, the package “metan” was used to compare the performances between MAM and US [20]. All meta-analyses were conducted with STATA software (version 14.0). All tests were two-sided, and P values of less than 0.05 for all meta-analyses indicated statistical significance. Results Supplementary S2 shows a flowchart of the study selection procedure. The electronic searches yielded 1162 potentially relevant studies, of which 23 eligible studies were included in the final review [9–11, 21–40], including 12 studies in which S-US screening was used after negative MAM and 11 joint screening studies in which both P-MAM and P-US were used. Table 1 shows the baseline characteristics of the 23 studies. Twelve studies were conducted among women with dense breasts. Twenty studies screened women with HHUS. Twelve studies were conducted among general Country South Korea United States South Korea Kim, 2016 [22] Weigert, 2015 [26] Hwang, 2015 45 NR 48 Singapore United States Italy South Korea Italy Leong, 2012 [32] Hooley, 2012 [31] Corsetti, 2011 [33] Youk, 2011 [34] Brancato, 2007 [36] Japan United States China United States China United States Sweden Italy United States Japan Ohuchi, 2016 [10] Berg, 2016 [11] Shen, 2015 [23] Brem, 2015 [39] Huang, 2012 [30] Kelly, 2010 [40] Wilczek, 2016 [38] Venturini, 2013 [29] Weinstein, 2009 [35] Honjo, 2007 [37] NR 49 46 50 53 46 53 46 55 44 52 52 52 NR 60 55 100 68 48 100 NR 100 NR 44 100 100 100 100 100 45 100 64 78 100 100 100 PerDB, % HHUS HHUS HHUS ABUS ABUS HHUS ABUS HHUS HHUS HHUS HHUS HHUS HHUS HHUS HHUS HHUS HHUS HHUS HHUS HHUS HHUS HHUS HHUS Type of US 3453 609 1666 1668 4419 3028 15,318 4135 2662 36,752 31,918 5227 446 3356 648 106 22,131 5519 2005 1727 10,282 3171 3231 Sample size Community High-risk Community Community High-risk Opportunistic Community High-risk High-risk Community Community Opportunistic Opportunistic Opportunistic Opportunistic Community Opportunistic Opportunistic Opportunistic Opportunistic Opportunistic Opportunistic Community Screening mode NR No Yes Yes No Yes Yes Yes Yes Yes Yes NR No Yes No No No No NR No NR Yes Yes Exclusion of BC Yes Yes Yes Yes Yes – – – – – Yes Yes No No Yes Yes No Yes Yes Yes Yes No No Yes Yes Yes Yes No Yes Yes Yes Yes – Yes Yes Yes No – – Yes – – Yes Yes – Complete data – Blinding No Yes Yes No Yes Yes Yes Yes Yes Yes No Yes Yes No Yes No Yes Yes Yes Yes Yes No No BIRADS criteria Fair Fair ≥18 Fair Fair High High High High High High High Fair Fair Fair Fair Fair Fair Fair Fair Fair Fair Fair Fair Quality assessment 12 6 24 12 12 12 12 > 12 12 12 NR 24 12 > 15 12–24 NR NR 24 12 6 12 < 12 FU, months Prospective Prospective Prospective Prospective Prospective Prospective Prospective Prospective Prospective Prospective Prospective Prospective Retrospective Retrospective Retrospective Prospective Retrospective Retrospective Retrospective Retrospective Retrospective Retrospective Prospective Cohort type PerDB Percent of women with dense breasts accounted for the whole population; US Ultrasonography; BC Breast cancer; BIRADS Breast Imaging-Reporting and Data System; FU Follow-up; HHUS/ABUS Hand-held / automated breast ultrasonography China Dong, 2017 [9] Joint screening studies 51 Italy Girardi, 2013 [27] 53 52 South Korea United States Moon, 2015 [24] 50 NR NR 51 Age, years Parris, 2013 [28] [25] Italy [21] Tagliafico, 2016 [21] Supplemental US screening studies Author, year Table 1 Characteristics of included studies Yang et al. BMC Cancer (2020) 20:499 Page 4 of 15 Yang et al. BMC Cancer (2020) 20:499 Page 5 of 15 community women or well-defined high-risk women. Eleven studies excluded women who had a personal history of breast cancer. Eight joint screening studies masked the results of P-MAM screening and P-US screening. Nineteen studies had low risk of incomplete data. Sixteen studies reported US results according to BI-RADS classification criteria. The reference standard in seventeen studies was pathologic examination combined with 12-month clinical follow-up. Finally, according to the pre-specified criteria, seven studies were of high quality, while the remaining 16 were of fair quality. Screening accuracy for S-US and P-US screening Table 2 shows the original data of screening accuracy for S-US and P-US screening among the included studies. Based on meta-analyses, S-US screening could detect Table 2 Screening accuracy for supplemental and primary US screening Author, year Method Case Non-case + – + – 23 1 65 3142 Sensitivity (95% CI) Specificity (95% CI) 0.96(0.77–1.00) 0.98(0.97–0.98) Supplemental US screening studies Tagliafico, 2016 [21] Supplemental US Kim, 2016 [22] Supplemental US 9 0 822 2340 1.00(0.63–1.00) 0.74(0.72–0.76) Weigert, 2015 [26] Supplemental US 24 15 411 9832 0.62(0.45–0.76) 0.96(0.96–0.96) Hwang, 2015 [25] Supplemental US 8 1 92 1626 0.89(0.51–0.99) 0.95(0.93–0.96) Moon, 2015 [24] Supplemental US 4 0 619 1382 1.00(0.40–1.00) 0.69(0.67–0.71) Parris, 2013 [28] Supplemental US 10 0 171 5338 1.00(0.66–1.00) 0.97(0.96–0.97) 0.98(0.98–0.98) Girardi, 2013 [27] Supplemental US 41 0 381 21,709 1.00(0.89–1.00) Leong, 2012 [32] Supplemental US 2 0 12 127 1.00(0.20–1.00) 0.91(0.85–0.95) Hooley, 2012 [31] Supplemental US 3 0 150 495 1.00(0.31–1.00) 0.77(0.73–0.80) Corsetti, 2011 [33] Supplemental US 32 8 363 6821 0.80(0.64–0.90) 0.95(0.94–0.95) Youk, 2011 [34] Supplemental US 10 1 41 394 0.91(0.57–1.00) 0.91(0.87–0.93) Brancato, 2007 [36] Supplemental US 2 0 106 5119 1.00(0.20–1.00) 0.98(0.98–0.98) Dong, 2017 [9] Primary MAM 84 15 604 31,215 0.85(0.76–0.91) 0.98(0.98–0.98) Primary US 61 38 389 31,430 0.62(0.51–0.71) 0.99(0.99–0.99) Ohuchi, 2016 [10] Primary MAM 117 85 2300 33,547 0.58(0.51–0.65) 0.94(0.93–0.94) Primary US 143 59 2289 33,558 0.71(0.64–0.77) 0.94(0.93–0.94) Primary MAM 59 52 700 6662 0.53(0.43–0.63) 0.90(0.90–0.91) Primary US 58 53 1012 6350 0.52(0.43–0.62) 0.86(0.85–0.87) Primary MAM 8 6 3 6913 0.57(0.30–0.81) 1.00(1.00–1.00) Primary US 14 0 6 6910 1.00(0.73–1.00) 1.00(1.00–1.00) Primary MAM 82 30 2219 12,987 0.73(0.64–0.81) 0.85(0.85–0.86) Primary US 95 17 2656 12,550 0.85(0.77–0.91) 0.83(0.82–0.83) Primary MAM 28 5 48 2947 0.85(0.67–0.94) 0.98(0.98–0.99) Primary US 24 9 19 2976 0.73(0.54–0.86) 0.99(0.99–1.00) 0.99(0.99–0.99) Joint screening studies Berg, 2016 [11] Shen, 2015 [23] Brem, 2015 [39] Huang, 2012 [30] Kelly, 2010 [40] Primary MAM 23 34 36 4326 0.40(0.28–0.54) Primary US 38 19 61 4301 0.67(0.53–0.78) 0.99(0.98–0.99) Wilczek, 2016 [38] Primary MAM 7 4 16 1641 0.64(0.32–0.88) 0.99(0.98–0.99) Primary US 11 0 27 1630 1.00(0.68–1.00) 0.98(0.98–0.99) Venturini, 2013 [29] Primary MAM 12 2 99 1553 0.86(0.56–0.97) 0.94(0.93–0.95) Primary US 2 12 8 813 0.14(0.03–0.44) 0.99(0.98–1.00) Primary MAM 7 13 37 512 0.35(0.16–0.59) 0.93(0.91–0.95) Primary US 3 17 36 511 0.15(0.04–0.39) 0.93(0.91–0.95) Primary MAM 8 5 271 3259 0.62(0.32–0.85) 0.92(0.91–0.93) Primary US 7 6 158 3372 0.54(0.26–0.80) 0.96(0.95–0.96) Weinstein, 2009 [35] Honjo, 2007 [37] CI Confidential interval; MAM Mammography; US Ultrasonography Yang et al. BMC Cancer (2020) 20:499 Page 6 of 15 96% [95% confidential intervals (CIs): 82 to 99%; I2 = 64.9%, P < 0.01] of occult breast cancers missed by MAM and identify 93% (95% CIs: 89 to 96%; I2 = 99.8%, P < 0.01) of healthy women (Fig. 1a, supplementary S4). The area under the SROC (AUC) for S-US screening was 98% (95CIs: 97 to 99%) (Fig. 1a). No publication bias was found among these studies (P = 0.397). Among 11 joint screening studies, P-MAM screening could detect 65% (95% CIs: 53 to 75%; I2 = 93.2%, P < 0.01) of breast cancers and identify 97% (95% CIs: 93 to 99%; I2 = 99.9%, P < 0.01) of healthy women (Fig. 1b, supplementary S5), respectively. P-US screening could detect 68% (95% CIs: 45 to 85%; I2 = 96.2%, P < 0.01) of breast cancers and identify 98% (95CIs: 94 to 99%; I2 = 100%, P < 0.01) of healthy women (Fig. 1c, supplementary S6). The AUCs for P-MAM screening and P-US screening were 88% (95CIs: 85 to 91%) (Fig. 1b) and 96% (95CIs: 94 to 97%) (Fig. 1c), respectively. No publication bias was found for both P-MAM screening (P = 0.215) and P-US screening (P = 0.266). No significant differences were found for either sensitivity [0.3% (95% CIs: − 14.4 to 14.9%), P = 0.970; I2 = 88.0%, P < 0.001] or specificity [− 0.1% (95% CIs: − 0.7 to 0.5%), P = 0.860; I2 = 96.3%, P < 0.001] between P-MAM screening and P-US screening (Fig. 2). studies. The studies from Corsetti [13], Hwang [25], Youk [32], and Brancato [34] among the S-US screening studies, as well as Shen [21] among joint screening studies did not report detailed information of invasive cancers or node-negative invasive cancers among screening detected cancers, therefore, they are missed in Table 4. After meta-analyses, 73.9% (95% CIs: 49.0 to 93.7%; I2 = 66.4%, P = 0.007) of cancers detected by S-US screening were invasive cancers, while 70.9% (95% CIs: 46.0 to 91.6%) of cancers were node-negative invasive cancers (Fig. 3). Among 11 joint screening studies, 65.1% (95% CIs: 57.5 to 72.5%; I2 = 45.9%, P = 0.055) and 86.9% (95% CIs: 77.4 to 94.5%; I2 = 72.5%, P < 0.001) of cancers detected by P-MAM screening and by P-US were invasive cancers, while 82.0% (95% CIs: 59.7 to 97.6%; I2 = 82.8%, P < 0.001) and 83.4% (95% CIs: 64.9 to 96.7%; I2 = 81.2%, P < 0.001) of cancers were node-negative invasive cancers (Fig. 4). Compared to P-MAM screening, P-US screening detected significantly more invasive cancers [16.3, 95% CIs (10.6 to 22.1%), P < 0.001; I2 = 0, P = 0.623] but a similar number of node-negative invasive cancers [0.3, 95% CIs (− 6.0 to 6.7%), P = 0.916; I2 = 0, P = 0.923] (Fig. 2). Screening efficacy for S-US and P-US screening Subgroup analyses Table 3 shows the original data for screening accuracy for S-US and P-US screening reported by the included studies. Meta-analyses showed that the summary CDR for S-US screening was 3.0/1000 (95% CIs: 1.8/1000 to 4.6/1000; I2 = 85.1%, P < 0.001), with a RR of 8.8% (95% CIs: 5.0 to 13.4%; I2 = 99.7%, P < 0.001) and a BR of 3.9% (95% CIs: 2.7 to 5.4%; I2 = 98.0%, P < 0.001) (Fig. 3). Among 11 joint screening studies, the summary CDRs for P-MAM screening and P-US screening were 4.6/ 1000 (95% CIs: 3.2/1000 to 6.1/1000; I2 = 89.8%, P < 0.001) and 4.6/1000 (95% CIs: 3.1/1000 to 6.3/1000; I2 = 91.9%, P < 0.001), with summary RRs of 4.6% (95% CIs: 2.2 to 7.7%; I2 = 99.8%, P < 0.001) and 5.9% (95% CIs: 2.7 to 10.2%; I2 = 99.8%, P < 0.001), and summary BRs of 1.5% (95% CIs: 0.5 to 3.0%; I2 = 98.9%, P < 0.001) and 2.3% (95% CIs: 0.9 to 4.5%; I2 = 99.2%, P < 0.001) (Fig. 4). Compared to P-MAM screening, P-US screening recalled significantly more women with positive screening results [1.5% (95% CIs: 0.6 to 2.3%), P = 0.001] (Fig. 2). No significant differences were found for either CDR [− 0.2/1000 (95% CIs:-1.1/1000 to 0.6/1000, P = 0.581; I2 = 46.1%, P = 0.046] or BR [− 1.0% (95% CIs: − 2.0 to 0.6%), P = 0.066; I2 = 96.6%, P < 0.001] for P-MAM screening compared to P-US screening (Fig. 2). Subgroup analyses showed very similar results to those of primary analyses (Supplementary S7 and S8). In addition to results comparable to those observed in the primary analyses, lower sensitivity, higher specificity, higher cancer detection rate, and higher biopsy rate were found for S-US screening among women with dense breasts compared to those without dense breasts (Supplementary S7). Moreover, the differences for sensitivities, specificities, and cancer detection rates between P-MAM screening and PUS screening were larger among women with dense breasts compared to those without dense breasts (Supplementary S8). Cancer characteristics for S-US and P-US screening Table 4 shows the original data for cancer characteristics for S-US and P-US screening reported by the included Discussion The U.S. Preventive Services Task Force (USPSTF) had initially reviewed the performances and clinical outcomes of S-US screening in women with dense breasts or negative mammography [15]. However, only two studies were included. The authors concluded that the effects of S-US screening on breast cancer outcomes remain unclear due to sparse good evidence [15]. In addition, Gartlehnerhad systematically reviewed the evidence investigating the joint effectiveness of screening with P-MAM and P-US compared to MAM screening alone [41]. However, this review did not investigate the performance of P-US screening. Our study is the first systematic review and meta-analysis to investigate the performance of P-US screening for breast cancer, and Yang et al. BMC Cancer (2020) 20:499 Page 7 of 15 Fig. 1 Summary receiver operating characteristic (SROC) curve for S-US screening (a), P-MAM screening (b), and P-US screening (c) for breast cancer Yang et al. BMC Cancer (2020) 20:499 Fig. 2 Comparisons on the performances for P-MAM and P-US screening for breast cancer Page 8 of 15 Yang et al. BMC Cancer (2020) 20:499 Page 9 of 15 Table 3 Screening efficacy for supplemental and primary US screening Author, year Method Cancer detected rate, 1/1000 Recall rate, % Number 95% CI Number 95% CI Biopsy rate, % Number 95% CI Supplemental US screening studies Tagliafico, 2016 [21] Supplemental US 23/3231 women 7.1(4.6–10.8) 88/3231 2.7(2.2–3.4) 46/3231 1.4(1.1–1.9) Kim, 2016 [22] Supplemental US 9/3171 women 2.8(1.4–5.6) 831/3171 26.2(24.7–27.8) 147/3171 4.6(3.9–5.4) Weigert, 2015 [26] Supplemental US 24/10282 women 2.3(1.5–3.5) 435/10282 4.2(3.9–4.6) Hwang, 2015 [25] Supplemental US 8/1727 women 4.6(2.2–9.5) 100/1727 5.8(4.8–7.0) 37/1727 2.1(1.5–3.0) Moon, 2015 [24] Supplemental US 4/2005 women 2.0(0.6–5.5) 623/2005 31.1(29.1–33.2) Parris, 2013 [28] Supplemental US 10/5519 women 1.8(0.9–3.4) 181/5519 3.3(2.8–3.8) 181/5519 3.3(2.8–3.8) Girardi, 2013 [27] Supplemental US 41/22131 women 1.9(1.3–2.5) 422/22131 1.9(1.7–2.1) 422/22131 1.9(1.7–2.1) Leong, 2012 [32] Supplemental US 2/141 women 14.2(2.5–55.5) 14/141 9.9(5.7–16.4) 14/141 9.9(5.7–16.4) Hooley, 2012 [31] Supplemental US 3/648 women 4.6(1.2–14.7) 153/648 23.6(20.4–27.1) 46/648 7.1(5.3–9.4) Corsetti, 2011 [33] Supplemental US 32/7224 examinations 4.4(3.1–6.3) 395/7224 5.5(5.0–6.0) 395/7224 5.5(5.0–6.0) Youk, 2011 [34] Supplemental US 10/446 examinations 22.4(11.4–42.2) 51/446 11.4(8.7–14.8) 49/446 11.0(8.3–14.4) Brancato, 2007 [36] Supplemental US 2/5227 women 0.4(0.1–1.5) 108/5227 2.1(1.7–2.5) 58/5227 1.1(0.9–1.4) Primary MAM 84/31918 women 2.6(2.1–3.3) 688/31918 2.2(2.0–2.3) Primary US 61/31918 women 1.9(1.5–2.5) 450/31918 1.4(1.3–1.5) Primary MAM 117/36049 women 3.2(2.7–3.9) 2417/36049 6.7(6.4–7.0) Joint screening studies Dong, 2017 [9] Ohuchi, 2016 [10] Primary US 143/36049 women 4.0(3.4–4.7) 2432/36049 6.7(6.5–7.0) Berg, 2016 [11] Primary MAM 59/7473 examinations 7.9(6.1–10.2) 759/7473 10.2(9.5–10.9) 162/7473 2.2(1.9–2.5) Primary US 58/7473 examinations 7.8(6.0–10.1) 1070/7473 14.3(13.5–15.1) 499/7473 6.7(6.1–7.3) Shen, 2015 [23] Primary MAM 8/6930 examinations 1.2(0.5–2.4) 11/6930 0.2(0.1–0.3) 7/6930 0.1(0.0–0.2) Primary US 14/6930 examinations 2.0(1.2–3.5) 20/6930 0.3(0.2–0.5) 17/6930 0.2(0.1–0.4) Brem, 2015 [39] Primary MAM 82/15318 women 5.4(4.3–6.7) 2301/15318 15.0(14.5–15.6) 586/15318 3.8(3.5–4.1) Primary US 95/15318 women 6.2(5.0–7.6) 2751/15318 18.0(17.4–18.6) 552/15318 3.6(3.3–3.9) Huang, 2012 [30] Primary MAM 28/3028 women 9.2(6.3–13.5) 105/3028 3.5(2.9–4.2) Primary US 24/3028 women 7.9(5.2–12.0) 318/3028 10.5(9.4–11.7) Kelly, 2010 [40] Primary MAM 23/4419 women 5.2(3.4–7.9) 59/4419 1.3(1.0–1.7) 59/4419 1.3(1.0–1.7) Primary US 38/4419 women 8.6(6.2–11.9) 99/4419 2.2(1.8–2.7) 99/4419 2.2(1.8–2.7) Wilczek, 2016 [38] Primary MAM 7/1668 women 4.2(1.8–9.0) 23/1668 1.4(0.9–2.1) 11/1668 0.7(0.3–1.2) Primary US 11/1668 women 6.6(3.5–12.2) 38/1668 2.3(1.6–3.1) 23/1668 1.4(0.9–2.1) Primary MAM 12/1666 women 7.2(3.9–12.9) 76/1666 4.6(3.6–5.7) 14/1666 0.8(0.5–1.4) Primary US 2/835 women 2.4(0.4–9.6) 87/835 10.4(8.5–12.7) 10/835 1.2(0.6–2.3) Primary MAM 7/569 women 12.3(5.4–26.3) 42/569 6.9(5.1–9.3) 20/569 3.3(2.1–5.1) Primary US 3/567 women 5.3(1.4–16.7) 39/567 6.9(5.0–9.4) 20/567 3.5(2.2–5.5) Primary MAM 8/3543 women 2.3(1.1–4.6) 279/3543 7.9(7.0–8.8) Primary US 5/3543 women 2.0(0.9–4.3) 165/3543 4.7(4.0–5.4) Venturini, 2013 [29] Weinstein, 2009 [35] Honjo, 2007 [37] CI Confidential interval; MAM Mammography; US Ultrasonography this is also an important up-to-date systematic review and meta-analysis investigating the performance of S-US screening. The role of S-US screening was first addressed in ACRIN 6666 by Berg in 2008 [4]. Berg concluded that SUS screening to P-MAM screening would yield an additional 1.1 to 7.2 cancers per 1000 high-risk women [4]. Our analyses also found a similar additional 0.4 to 22.4 cancers per 1000 examinations. Moreover, after reanalysis of ACRIN 6666, Berg concluded that ultrasound could be used as the primary screening method for breast cancer [11]. However, up to now, there have been no consistent conclusions concerning whether US screening should be recommended as the primary Yang et al. BMC Cancer (2020) 20:499 Page 10 of 15 Fig. 3 Screening efficacy for S-US screening for breast cancer screening method for women in the screening guidelines for breast cancer. For example, the National Comprehensive Cancer Network, the European Society of Breast Imaging (EUSOBI), the Japanese Breast Cancer Society, and the Chinese Anti-Cancer Association (CACA) supported that S-US screening should be recommended for women with dense breasts after negative MAM [42–45], while no clear recommendations of US screening were suggested by the USPSTF, the American Cancer Society, the American College of Physicians, and the Canadian Task Force on Preventive Health Care [46–49]. Several reasons would lead to these inconsistent recommendations among current guidelines. As argued by USPSTF, sparse good evidence would be the major reason. However, as shown in our study, several high-quality studies and fair-quality studies had been conducted since