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Breast cancer is the most common malignant tumor in Chinese women, and its incidence is increasing. Regular screening is an effective method for early tumor detection and improving patient prognosis. In this review, we analyze the epidemiological changes and risk factors associated with breast cancer in China and describe the establishment of a screening strategy suitable for Chinese women. Chinese patients with breast cancer tend to be younger than Western patients and to have denser breasts. Therefore, the age of initial screening in Chinese women should be earlier, and the importance of screening with a combination of ultrasound and mammography is stressed. Moreover, Chinese patients with breast cancers have several ancestry-specific genetic features, and aiding in the determination of genetic screening strategies for identifying high-risk populations. On the basis of current studies, we summarize the development of risk-stratified breast cancer screening guidelines for Chinese women and describe the significant improvement in the prognosis of patients with breast cancer in China.


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Breast cancer screening and early diagnosis in Chinese women

Show Author's information Rui Ding1,2,*Yi Xiao1,2,*Miao Mo3Ying Zheng3Yi-Zhou Jiang1,2 ( )Zhi-Ming Shao1,2,4 ( )
Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China
Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
Department of Cancer Prevention, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
Precision Cancer Medicine Center, Fudan University Shanghai Cancer Center, Shanghai 200032, China

*These authors contributed equally to this work.

Abstract

Breast cancer is the most common malignant tumor in Chinese women, and its incidence is increasing. Regular screening is an effective method for early tumor detection and improving patient prognosis. In this review, we analyze the epidemiological changes and risk factors associated with breast cancer in China and describe the establishment of a screening strategy suitable for Chinese women. Chinese patients with breast cancer tend to be younger than Western patients and to have denser breasts. Therefore, the age of initial screening in Chinese women should be earlier, and the importance of screening with a combination of ultrasound and mammography is stressed. Moreover, Chinese patients with breast cancers have several ancestry-specific genetic features, and aiding in the determination of genetic screening strategies for identifying high-risk populations. On the basis of current studies, we summarize the development of risk-stratified breast cancer screening guidelines for Chinese women and describe the significant improvement in the prognosis of patients with breast cancer in China.

Keywords: Breast cancer, Chinese, screening, imaging screening, genetic test

References(151)

1

Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021; 71: 209-49.

2

Zhang S, Sun K, Zheng R, Zeng H, Wang S, Chen R, et al. Cancer incidence and mortality in China, 2015. J Natl Cancer Center. 2021; 1: 2-11.

3

Moss SM, Cuckle H, Evans A, Johns L, Waller M, Bobrow L. Effect of mammographic screening from age 40 years on breast cancer mortality at 10 years’ follow-up: a randomised controlled trial. Lancet. 2006; 368: 2053-60.

4

Pace LE, Keating NL. A systematic assessment of benefits and risks to guide breast cancer screening decisions. JAMA. 2014; 311: 1327-35.

5

Breen N, Gentleman JF, Schiller JS. Update on mammography trends: comparisons of rates in 2000, 2005, and 2008. Cancer. 2011; 117: 2209-18.

6

Expert Panel on Breast Imaging, Mainiero MB, Moy L, Baron P, Didwania AD, diFlorio RM, et al. Acr appropriateness criteria® breast cancer screening. J Am Coll Radiol. 2017; 14: S383-90.

7

Lauby-Secretan B, Scoccianti C, Loomis D, Benbrahim-Tallaa L, Bouvard V, Bianchini F, et al. Breast-cancer screening – viewpoint of the IARC Working Group. N Engl J Med. 2015; 372: 2353-8.

8

Qaseem A, Lin JS, Mustafa RA, Horwitch CA, Wilt TJ, Clinical Guidelines Committee of the American College of Physicians; Forciea MA, et al. Screening for breast cancer in average-risk women: a guidance statement from the American college of physicians. Ann Intern Med. 2019; 170: 547-60.

9
World Health Organization. Who position paper on mammography screening. https://www.Who.Int/publications/i/item/who-position-paper-on-mammography-screening. Published February 16, 2014.
10

Oeffinger KC, Fontham ET, Etzioni R, Herzig A, Michaelson JS, Shih YC, et al. Breast cancer screening for women at average risk: 2015 guideline update from the American cancer society. JAMA. 2015; 314: 1599-614.

11

Saslow D, Boetes C, Burke W, Harms S, Leach MO, Lehman CD, et al. American cancer society guidelines for breast screening with MRI as an adjunct to mammography. CA Cancer J Clin. 2007; 57: 75-89.

12

Schunemann HJ, Lerda D, Quinn C, Follmann M, Alonso-Coello P, Rossi PG, et al. Breast cancer screening and diagnosis: a synopsis of the European breast guidelines. Ann Intern Med. 2020; 172: 46-56.

13
Siu AL, U.S. Preventive Services Task Force. Screening for breast cancer: U.S. Preventive services task force recommendation statement. Ann Intern Med. 2016; 164: 279-96.
DOI
14

Bao Y, Kwok C, Lee CF. Breast cancer screening behaviors among chinese women in mainland China. Nurs Health Sci. 2018; 20: 445-51.

15

Ellis L, Canchola AJ, Spiegel D, Ladabaum U, Haile R, Gomez SL. Racial and ethnic disparities in cancer survival: the contribution of tumor, sociodemographic, institutional, and neighborhood characteristics. J Clin Oncol. 2018; 36: 25-33.

16

Fan L, Strasser-Weippl K, Li J-J, St Louis J, Finkelstein DM, Yu K-D, et al. Breast cancer in china. Lancet Oncol. 2014; 15: e279-89.

17

Global Burden of Disease Cancer Collaboration, Fitzmaurice C, Abate D, Abbasi N, Abbastabar H, Abd-Allah F, et al. Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life-years for 29 cancer groups, 1990 to 2017: a systematic analysis for the global burden of disease study. JAMA Oncol. 2019; 5: 1749-68.

18
International agency for research on cancer. The global cancer observatory 2020 china fact sheets. https://gco.Iarc.Fr/today/data/factsheets/populations/160-china-fact-sheets.Pdf. Published March, 2021.
19

Chen W, Sun K, Zheng R, Zeng H, Zhang S, Xia C, et al. Cancer incidence and mortality in China, 2014. Chin J Cancer Res. 2018; 30: 1-12.

20

Chen W, Zheng R, Zeng H, Zhang S, He J. Annual report on status of cancer in china, 2011. Chin J Cancer Res. 2015; 27: 2-12.

21

Chen W, Zheng R, Zhang S, Zhao P, Zeng H, Zou X, et al. Annual report on status of cancer in China, 2010. Chin J Cancer Res. 2014; 26: 48-58.

22

Chen W, Zheng R, Zuo T, Zeng H, Zhang S, He J. National cancer incidence and mortality in China, 2012. Chin J Cancer Res. 2016; 28: 1-11.

23

Yu XQ, Baade P. Re: Cancer incidence and mortality in China, 2013 by Chen et al. Cancer Lett. 2017; 401: 72-3.

24
Ervik M, Lam F, Laversanne M, Ferlay J, Bray F. Global cancer observatory: cancer over time. Lyon, France: international Agency for Research on Cancer. 2021. Available from: https://gco.Iarc.Fr/overtime. Accessed 05 February 2022.
25

Rossouw JE, Anderson GL, Prentice RL, LaCroix AZ, Kooperberg C, Stefanick ML, et al. Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results From the Women’s Health Initiative randomized controlled trial. JAMA. 2002; 288: 321-33.

26

Fan L, Zheng Y, Yu KD, Liu GY, Wu J, Lu JS, et al. Breast cancer in a transitional society over 18 years: trends and present status in Shanghai, China. Breast Cancer Res Treat. 2009; 117: 409-16.

27
Ferlay J, Ervik M, Lam F, Colombet M, Mery L, Piñeros M, et al. Global cancer observatory: cancer today. Lyon, France: international agency for research on cancer. 2020. Available from: https://gco.Iarc.Fr/today. Accessed 05 February 2022.
28
National Bureau of Statistics PRC. Tabulation on the 2010 population census of the people’s republic of China. China Statistics Press. 2012.04 http://www.Stats.Gov.Cn/tjsj/pcsj/rkpc/6rp/indexch.htm.
29
National Bureau of Statistics PRC. A press conference on the results of the seventh national population census. http://www.Stats.Gov.Cn/ztjc/zdtjgz/zgrkpc/dqcrkpc/ggl/202105/t20210519_1817702.html. Published May 11, 2021.
30

Jiang Q, Yang S, Li S, Feldman MW. The decline in China’s fertility level: a decomposition analysis. J Biosoc Sci. 2019; 51: 785-98.

31

Gao Y-T, Shu X-O, Dai Q, Potter JD, Brinton LA, Wen W, et al. Association of menstrual and reproductive factors with breast cancer risk: results from the Shanghai breast cancer study. Int J Cancer. 2000; 87: 295-300.

32

Huang Z, Beeghly-Fadiel A, Gao YT, Zheng Y, Dai Q, Lu W, et al. Associations of reproductive time events and intervals with breast cancer risk: a report from the Shanghai breast cancer study. Int J Cancer. 2014; 135: 186-95.

33

Zhang JY, Wang MX, Wang X, Li YL, Liang ZZ, Lin Y, et al. Associations of reproductive factors with breast cancer prognosis and the modifying effects of menopausal status. Cancer Med. 2020; 9: 385-93.

34

Li L, Ji J, Wang JB, Niyazi M, Qiao YL, Boffetta P. Attributable causes of breast cancer and ovarian cancer in china: reproductive factors, oral contraceptives and hormone replacement therapy. Chin J Cancer Res. 2012; 24: 9-17.

35

Porter P. “Westernizing” women’s risks? Breast cancer in lowerincome countries. N Engl J Med. 2008; 358: 213-6.

36

Cui X, Dai Q, Tseng M, Shu XO, Gao YT, Zheng W. Dietary patterns and breast cancer risk in the shanghai breast cancer study. Cancer Epidemiol Biomarkers Prev. 2007; 16: 1443-8.

37

Mi YJ, Zhang B, Wang HJ, Yan J, Han W, Zhao J, et al. Prevalence and secular trends in obesity among chinese adults, 1991-2011. Am J Prev Med. 2015; 49: 661-9.

38

Pattacini P, Nitrosi A, Giorgi Rossi P, Iotti V, Ginocchi V, Ravaioli S, et al. Digital mammography versus digital mammography plus tomosynthesis for breast cancer screening: The Reggio Emilia Tomosynthesis randomized trial. Radiology. 2018; 288: 375-85.

39

Hofvind S, Holen ÅS, Aase HS, Houssami N, Sebuødegård S, Moger TA, et al. Two-view digital breast tomosynthesis versus digital mammography in a population-based breast cancer screening programme (To-Be): a randomised, controlled trial. Lancet Oncol. 2019; 20: 795-805.

40

Hofvind S, Moshina N, Holen ÅS, Danielsen AS, Lee CI, Houssami N, et al. Interval and subsequent round breast cancer in a randomized controlled trial comparing digital breast tomosynthesis and digital mammography screening. Radiology. 2021; 300: 66-76.

41

Phi XA, Tagliafico A, Houssami N, Greuter MJW, de Bock GH. Digital breast tomosynthesis for breast cancer screening and diagnosis in women with dense breasts – a systematic review and meta-analysis. BMC Cancer. 2018; 18: 380.

42

Marinovich ML, Hunter KE, Macaskill P, Houssami N. Breast cancer screening using tomosynthesis or mammography: a metaanalysis of cancer detection and recall. J Natl Cancer Inst. 2018; 110: 942-9.

43

Sung JS, Lebron L, Keating D, D’Alessio D, Comstock CE, Lee CH, et al. Performance of dual-energy contrast-enhanced digital mammography for screening women at increased risk of breast cancer. Radiology. 2019; 293: 81-8.

44

Sorin V, Yagil Y, Yosepovich A, Shalmon A, Gotlieb M, Neiman OH, et al. Contrast-enhanced spectral mammography in women with intermediate breast cancer risk and dense breasts. AJR Am J Roentgenol. 2018; 211: W267-74.

45

Cheung YC, Lin YC, Wan YL, Yeow KM, Huang PC, Lo YF, et al. Diagnostic performance of dual-energy contrast-enhanced subtracted mammography in dense breasts compared to mammography alone: interobserver blind-reading analysis. Eur Radiol. 2014; 24: 2394-403.

46

Hadadi I, Rae W, Clarke J, McEntee M, Ekpo E. Diagnostic performance of adjunctive imaging modalities compared to mammography alone in women with non-dense and dense breasts: a systematic review and meta-analysis. Clin Breast Cancer. 2021; 21: 278-91.

47

Melnikow J, Fenton JJ, Whitlock EP, Miglioretti DL, Weyrich MS, Thompson JH, et al. Supplemental screening for breast cancer in women with dense breasts: a systematic review for the U.S. Preventive Service Task Force, Rockville (MD). Ann Intern Med. 2016;164:268-78.

48

Wang L, Qi ZH. Automatic breast volume scanner versus handheld ultrasound in differentiation of benign and malignant breast lesions: a systematic review and meta-analysis. Ultrasound Med Biol. 2019; 45: 1874-81.

49

Comstock CE, Gatsonis C, Newstead GM, Snyder BS, Gareen IF, Bergin JT, et al. Comparison of abbreviated breast MRI vs digital breast tomosynthesis for breast cancer detection among women with dense breasts undergoing screening. JAMA. 2020; 323: 746-56.

50

Bakker MF, de Lange SV, Pijnappel RM, Mann RM, Peeters PHM, Monninkhof EM, et al. Supplemental MRI screening for women with extremely dense breast tissue. N Engl J Med. 2019; 381: 2091-102.

51

Saadatmand S, Geuzinge HA, Rutgers EJT, Mann RM, de Roy van Zuidewijn DBW, Zonderland HM, et al. MRI versus mammography for breast cancer screening in women with familial risk (FaMRIsc): a multicentre, randomised, controlled trial. Lancet Oncol. 2019; 20: 1136-47.

52

Miller AB. Digital mammography. J Natl Cancer Inst. 2014; 106: dju125.

53

Pisano ED, Yaffe MJ. Digital mammography. Radiology. 2005; 234: 353-62.

54

Nelson HD, Fu R, Cantor A, Pappas M, Daeges M, Humphrey L. Effectiveness of breast cancer screening: systematic review and meta-analysis to update the 2009 U.S. Preventive Services Task Force Recommendation. Ann Intern Med. 2016; 164: 244-55.

55

Otto SJ, Fracheboud J, Looman CWN, Broeders MJM, Boer R, Hendriks JHCL, et al. Initiation of population-based mammography screening in Dutch municipalities and effect on breast-cancer mortality: a systematic review. Lancet. 2003; 361: 1411-17.

56

Jorgensen KJ, Gotzsche PC. Overdiagnosis in publicly organised mammography screening programmes: systematic review of incidence trends. BMJ. 2009; 339: b2587.

57

Chong A, Weinstein SP, McDonald ES, Conant EF. Digital breast tomosynthesis: concepts and clinical practice. Radiology. 2019; 292: 1-14.

58

Gastounioti A, McCarthy AM, Pantalone L, Synnestvedt M, Kontos D, Conant EF. Effect of mammographic screening modality on breast density assessment: digital mammography versus digital breast tomosynthesis. Radiology. 2019; 291: 320-7.

59

Conant EF, Barlow WE, Herschorn SD, Weaver DL, Beaber EF, Tosteson ANA, et al. Association of digital breast tomosynthesis vs digital mammography with cancer detection and recall rates by age and breast density. JAMA Oncol. 2019; 5: 635-42.

60

Rafferty EA, Durand MA, Conant EF, Copit DS, Friedewald SM, Plecha DM, et al. Breast cancer screening using tomosynthesis and digital mammography in dense and nondense breasts. JAMA. 2016; 315: 1784-6.

61

Skaane P, Bandos AI, Niklason LT, Sebuødegård S, Østerås BH, Gullien R, et al. Digital mammography versus digital mammography plus tomosynthesis in breast cancer screening: the oslo tomosynthesis screening trial. Radiology. 2019; 291: 23-30.

62

Pisano ED, Yaffe MJ. Breast cancer screening: should tomosynthesis replace digital mammography? JAMA. 2014; 311: 2488-9.

63

Jochelson MS, Lobbes MBI. Contrast-enhanced mammography: state of the art. Radiology. 2021; 299: 36-48.

64

Jochelson MS, Pinker K, Dershaw DD, Hughes M, Gibbons GF, Rahbar K, et al. Comparison of screening CEDM and MRI for women at increased risk for breast cancer: a pilot study. Eur J Radiol. 2017; 97: 37-43.

65

Lee-Felker SA, Tekchandani L, Thomas M, Gupta E, Andrews-Tang D, Roth A, et al. Newly diagnosed breast cancer: comparison of contrast-enhanced spectral mammography and breast MR imaging in the evaluation of extent of disease. Radiology. 2017; 285: 389-400.

66

Sumkin JH, Berg WA, Carter GJ, Bandos AI, Chough DM, Ganott MA, et al. Diagnostic performance of MRI, molecular breast imaging, and contrast-enhanced mammography in women with newly diagnosed breast cancer. Radiology. 2019; 293: 531-40.

67

Phillips J, Mihai G, Hassonjee SE, Raj SD, Palmer MR, Brook A, et al. Comparative dose of contrast-enhanced spectral mammography (CESM), digital mammography, and digital breast tomosynthesis. AJR Am J Roentgenol. 2018; 211: 839-46.

68

Zanardo M, Cozzi A, Trimboli RM, Labaj O, Monti CB, Schiaffino S, et al. Technique, protocols and adverse reactions for contrast-enhanced spectral mammography (CESM): a systematic review. Insights Imaging. 2019; 10: 76.

69

Hooley RJ, Scoutt LM, Philpotts LE. Breast ultrasonography: state of the art. Radiology. 2013; 268: 642-59.

70

Lee SH, Chung J, Choi HY, Choi SH, Ryu EB, Ko KH, et al. Evaluation of screening US-detected breast masses by combined use of elastography and color doppler US with B-mode US in women with dense breasts: a multicenter prospective study. Radiology. 2017; 285: 660-9.

71

Yang WT, Metreweli C, Lam PK, Chang J. Benign and malignant breast masses and axillary nodes: evaluation with echo-enhanced color power Doppler US. Radiology. 2001; 220: 795-802.

72

Sigrist RMS, Liau J, Kaffas AE, Chammas MC, Willmann JK. Ultrasound elastography: review of techniques and clinical applications. Theranostics. 2017; 7: 1303-29.

73

Harada-Shoji N, Suzuki A, Ishida T, Zheng YF, Narikawa-Shiono Y, Sato-Tadano A, et al. Evaluation of adjunctive ultrasonography for breast cancer detection among women aged 40-49 years with varying breast density undergoing screening mammography: a secondary analysis of a randomized clinical trial. JAMA Netw Open. 2021; 4: e2121505.

74

Sprague BL, Stout NK, Schechter C, van Ravesteyn NT, Cevik M, Alagoz O, et al. Benefits, harms, and cost-effectiveness of supplemental ultrasonography screening for women with dense breasts. Ann Intern Med. 2015; 162: 157-66.

75

Berg WA, Mendelson EB. Technologist-performed handheld screening breast US imaging: how is it performed and what are the outcomes to date? Radiology. 2014; 272: 12-27.

76

Rella R, Belli P, Giuliani M, Bufi E, Carlino G, Rinaldi P, et al. Automated breast ultrasonography (ABUS) in the screening and diagnostic setting: Indications and practical use. Acad Radiol. 2018; 25: 1457-70.

77

Vourtsis A. Three-dimensional automated breast ultrasound: technical aspects and first results. Diagn Interv Imaging. 2019; 100: 579-92.

78

Jia M, Lin X, Zhou X, Yan H, Chen Y, Liu P, et al. Diagnostic performance of automated breast ultrasound and handheld ultrasound in women with dense breasts. Breast Cancer Res Treat. 2020; 181: 589-97.

79

Lin X, Jia M, Zhou X, Bao L, Chen Y, Liu P, et al. The diagnostic performance of automated versus handheld breast ultrasound and mammography in symptomatic outpatient women: a multicenter, cross-sectional study in China. Eur Radiol. 2021; 31: 947-57.

80

Vourtsis A, Kachulis A. The performance of 3D ABUS versus HHUS in the visualisation and BI-RADS characterisation of breast lesions in a large cohort of 1,886 women. Eur Radiol. 2018; 28: 592-601.

81

Xin Y, Zhang X, Yang Y, Chen Y, Wang Y, Zhou X, et al. A multicenter, hospital-based and non-inferiority study for diagnostic efficacy of automated whole breast ultrasound for breast cancer in China. Sci Rep. 2021; 11: 13902.

82

Zhang X, Lin X, Tan Y, Zhu Y, Wang H, Feng R, et al. A multicenter hospital-based diagnosis study of automated breast ultrasound system in detecting breast cancer among Chinese women. Chin J Cancer Res. 2018; 30: 231-9.

83

Mann RM, Cho N, Moy L. Breast MRI: state of the art. Radiology. 2019; 292: 520-36.

84

Mann RM, Kuhl CK, Moy L. Contrast-enhanced MRI for breast cancer screening. J Magn Reson Imaging. 2019; 50: 377-90.

85

Onishi N, Sadinski M, Gibbs P, Gallagher KM, Hughes MC, Ko ES, et al. Differentiation between subcentimeter carcinomas and benign lesions using kinetic parameters derived from ultrafast dynamic contrast-enhanced breast MRI. Eur Radiol. 2020; 30: 756-66.

86

Gao Y, Heller SL. Abbreviated and ultrafast breast MRI in clinical practice. Radiographics. 2020; 40: 1507-27.

87

Cheon H, Kim HJ, Kim TH, Ryeom HK, Lee J, Kim GC, et al. Invasive breast cancer: prognostic value of peritumoral edema identified at preoperative MR imaging. Radiology. 2018; 287: 68-75.

88

Amornsiripanitch N, Bickelhaupt S, Shin HJ, Dang M, Rahbar H, Pinker K, et al. Diffusion-weighted MRI for unenhanced breast cancer screening. Radiology. 2019; 293: 504-20.

89

Berg WA, Zhang Z, Lehrer D, Jong RA, Pisano ED, Barr RG, et al. Detection of breast cancer with addition of annual screening ultrasound or a single screening MRI to mammography in women with elevated breast cancer risk. JAMA. 2012; 307: 1394-404.

90

Smith RA. The evolving role of MRI in the detection and evaluation of breast cancer. N Engl J Med. 2007; 356: 1362-4.

91

Kuhl CK. Abbreviated magnetic resonance imaging (MRI) for breast cancer screening: rationale, concept, and transfer to clinical practice. Annu Rev Med. 2019; 70: 501-19.

92

US Preventive Services Task Force. Screening for breast cancer: U.S. Preventive services task force recommendation statement. Ann Intern Med. 2009; 151: 716-26.

93

Harkness EF, Astley SM, Evans DG. Risk-based breast cancer screening strategies in women. Best Pract Res Clin Obstet Gynaecol. 2020; 65: 3-17.

94

Mulder RL, Kremer LCM, Hudson MM, Bhatia S, Landier W, Levitt G, et al. Recommendations for breast cancer surveillance for female survivors of childhood, adolescent, and young adult cancer given chest radiation: a report from the International Late Effects of Childhood Cancer Guideline Harmonization Group. Lancet Oncol. 2013; 14: e621-9.

95

Smith RA, Andrews KS, Brooks D, Fedewa SA, Manassaram-Baptiste D, Saslow D, et al. Cancer screening in the United States, 2019: a review of current American Cancer Society guidelines and current issues in cancer screening. CA Cancer J Clin. 2019; 69: 184-210.

96

Dai H, Yan Y, Wang P, Liu P, Cao Y, Xiong L, et al. Distribution of mammographic density and its influential factors among Chinese women. Int J Epidemiol. 2014; 43: 1240-51.

97

Maskarinec G, Meng L, Ursin G. Ethnic differences in mammographic densities. Int J Epidemiol. 2001; 30: 959-65.

98

Flobbe K, Nelemans PJ, Kessels AGH, Beets GL, von Meyenfeldt MF, van Engelshoven JMA. The role of ultrasonography as an adjunct to mammography in the detection of breast cancer. Eur J Cancer. 2002; 38: 1044-50.

99

Rebolj M, Assi V, Brentnall A, Parmar D, Duffy SW. Addition of ultrasound to mammography in the case of dense breast tissue: systematic review and meta-analysis. Br J Cancer. 2018; 118: 1559-70.

100

Kolb TM, Lichy J, Newhouse JH. Comparison of the performance of screening mammography, physical examination, and breast US and evaluation of factors that influence them: an analysis of 27,825 patient evaluations. Radiology. 2002; 225: 165-75.

101

Zhao H, Zou L, Geng X, Zheng S. Limitations of mammography in the diagnosis of breast diseases compared with ultrasonography: a single-center retrospective analysis of 274 cases. Eur J Med Res. 2015; 20: 49.

102

Wang FL, Chen F, Yin H, Xu N, Wu XX, Ma JJ, et al. Effects of age, breast density and volume on breast cancer diagnosis: a retrospective comparison of sensitivity of mammography and ultrasonography in China’s rural areas. Asian Pac J Cancer Prev. 2013; 14: 2277-82.

103

Pu H, Peng J, Xu F, Liu N, Wang F, Huang X, et al. Ultrasound and clinical characteristics of false-negative results in mammography screening of dense breasts. Clin Breast Cancer. 2020; 20: 317-25.

104

Berg WA, Blume JD, Cormack JB, Mendelson EB, Lehrer D, Bohm-Velez M, et al. Combined screening with ultrasound and mammography vs mammography alone in women at elevated risk of breast cancer. JAMA. 2008; 299: 2151-63.

105

Brem RF, Tabar L, Duffy SW, Inciardi MF, Guingrich JA, Hashimoto BE, et al. Assessing improvement in detection of breast cancer with three-dimensional automated breast US in women with dense breast tissue: the SomoInsight Study. Radiology. 2015; 274: 663-73.

106

Lee JM, Arao RF, Sprague BL, Kerlikowske K, Lehman CD, Smith RA, et al. Performance of screening ultrasonography as an adjunct to screening mammography in women across the spectrum of breast cancer risk. JAMA Intern Med. 2019; 179: 658-67.

107

Ohuchi N, Suzuki A, Sobue T, Kawai M, Yamamoto S, Zheng Y-F, et al. Sensitivity and specificity of mammography and adjunctive ultrasonography to screen for breast cancer in the Japan Strategic Anti-cancer Randomized Trial (J-START): a randomised controlled trial. Lancet. 2016; 387: 341-8.

108

Tagliafico AS, Calabrese M, Mariscotti G, Durando M, Tosto S, Monetti F, et al. Adjunct screening with tomosynthesis or ultrasound in women with mammography-negative dense breasts: interim report of a prospective comparative trial. J Clin Oncol. 2016; 34: 1882-8.

109

Mo M, Liu GY, Zheng Y, Di LF, Ji YJ, Lv LL, et al. Performance of breast cancer screening methods and modality among Chinese women: a report from a society-based breast screening program (SBSP) in Shanghai. Springerplus. 2013; 2: 276.

110
Wu F, Mo M, Qin XX, Fang H, Zhao GM, Liu GY, et al.[cost-effectiveness of multiple screening modalities on breast cancer in Chinese women from Shanghai]. Zhonghua Liu Xing Bing Xue Za Zhi. 2017; 38: 1665-71.
111

Ya-jie J, Wei-jun P, Cai C, Jian-hui D, Wei Z, Min C, et al. Application of breast ultrasound in a mammography-based Chinese breast screening study. Cell Biochem Biophys. 2012; 65: 37-41.

112

Dong H, Huang Y, Song F, Dai H, Liu P, Zhu Y, et al. Improved performance of adjunctive ultrasonography after mammography screening for breast cancer among Chinese females. Clin Breast Cancer. 2018; 18: e353-61.

113

Shen S, Zhou Y, Xu Y, Zhang B, Duan X, Huang R, et al. A multicentre randomised trial comparing ultrasound vs mammography for screening breast cancer in high-risk Chinese women. Br J Cancer. 2015; 112: 998-1004.

114

Li J, Xing P, Feng L, Dong H, Jin F, Wu Y, et al. The value of substratified combined imaging assessment with mammography and ultrasonography for Chinese women with palpable breast masses. Breast Cancer Res Treat. 2014; 144: 391-6.

115

Yang X, Wu J, Lu J, Liu G, Di G, Chen C, et al. Identification of a comprehensive spectrum of genetic factors for hereditary breast cancer in a Chinese population by next-generation sequencing. PLoS One. 2015; 10: e0125571.

116

Yao L, Sun J, Zhang J, He Y, Ouyang T, Li J, et al. Breast cancer risk in Chinese women with BRCA1 or BRCA2 mutations. Breast Cancer Res Treat. 2016; 156: 441-5.

117

Couch FJ, Shimelis H, Hu C, Hart SN, Polley EC, Na J, et al. Associations between cancer predisposition testing panel genes and breast cancer. JAMA Oncol. 2017; 3: 1190-6.

118

Deng M, Chen HH, Zhu X, Luo M, Zhang K, Xu CJ, et al. Prevalence and clinical outcomes of germline mutations in BRCA1/2 and PALB2 genes in 2769 unselected breast cancer patients in China. Int J Cancer. 2019; 145: 1517-28.

119

Kurian AW, Ward KC, Howlader N, Deapen D, Hamilton AS, Mariotto A, et al. Genetic testing and results in a population-based cohort of breast cancer patients and ovarian cancer patients. J Clin Oncol. 2019; 37: 1305-15.

120

Sun J, Meng H, Yao L, Lv M, Bai J, Zhang J, et al. Germline mutations in cancer susceptibility genes in a large series of unselected breast cancer patients. Clin Cancer Res. 2017; 23: 6113-9.

121

Tung N, Lin NU, Kidd J, Allen BA, Singh N, Wenstrup RJ, et al. Frequency of germline mutations in 25 cancer susceptibility genes in a sequential series of patients with breast cancer. J Clin Oncol. 2016; 34: 1460-8.

122

Zeng C, Guo X, Wen W, Shi J, Long J, Cai Q, et al. Evaluation of pathogenetic mutations in breast cancer predisposition genes in population-based studies conducted among Chinese women. Breast Cancer Res Treat. 2020; 181: 465-73.

123

Xiao W, Zhang G, Chen B, Chen X, Wen L, Lai J, et al. Characterization of frequently mutated cancer genes and tumor mutation burden in Chinese breast cancer. Front Oncol. 2021; 11: 618767.

124

Sheng S, Xu Y, Guo Y, Yao L, Hu L, Ouyang T, et al. Prevalence and clinical impact of TP53 germline mutations in Chinese women with breast cancer. Int J Cancer. 2020; 146: 487-95.

125

Wu Y, Huang D, Zhang H, Weng X, Wang H, Zhou Q, et al. The frequency of PTEN germline mutations in Chinese breast cancer patients: the PTEN gene may not be closely associated with breast cancer in the Chinese population. Gene. 2020; 744: 144630.

126

Lang GT, Shi JX, Hu X, Zhang CH, Shan L, Song CG, et al. The spectrum of BRCA mutations and characteristics of BRCA-associated breast cancers in China: screening of 2,991 patients and 1,043 controls by next-generation sequencing. Int J Cancer. 2017; 141: 129-42.

127

Ma D, Chen SY, Ren JX, Pei YC, Jiang CW, Zhao S, et al. Molecular features and functional implications of germline variants in triplenegative breast cancer. J Natl Cancer Inst. 2021; 113: 884-92.

128

Couch FJ, Hart SN, Sharma P, Toland AE, Wang X, Miron P, et al. Inherited mutations in 17 breast cancer susceptibility genes among a large triple-negative breast cancer cohort unselected for family history of breast cancer. J Clin Oncol. 2015; 33: 304-11.

129

Chen X, Li Y, Ouyang T, Li J, Wang T, Fan Z, et al. Associations between RAD51D germline mutations and breast cancer risk and survival in BRCA1/2-negative breast cancers. Ann Oncol. 2018; 29: 2046-51.

130

Yang X, Song H, Leslie G, Engel C, Hahnen E, Auber B, et al. Ovarian and breast cancer risks associated with pathogenic variants in RAD51C and RAD51D. J Natl Cancer Inst. 2020; 112: 1242-50.

131

Lang GT, Jiang YZ, Shi JX, Yang F, Li XG, Pei YC, et al. Characterization of the genomic landscape and actionable mutations in Chinese breast cancers by clinical sequencing. Nat Commun. 2020; 11: 5679.

132

Wang X, Huang Y, Li L, Dai H, Song F, Chen K. Assessment of performance of the Gail model for predicting breast cancer risk: a systematic review and meta-analysis with trial sequential analysis. Breast Cancer Res. 2018; 20: 18.

133

Li XQ, Mo M, Wu F, Liu GY, Xu WH, Shao ZM. Artificial neural network models based on questionnaire survey for prediction of breast cancer risk among chinese women in shanghai. Tumor. 2018; 38: 883-93.

134

Han Y, Lv J, Yu C, Guo Y, Bian Z, Hu Y, et al. Development and external validation of a breast cancer absolute risk prediction model in Chinese population. Breast Cancer Res. 2021; 23: 62.

135

Wang L, Liu L, Lou Z, Ding L, Guan H, Wang F, et al. Risk prediction for breast Cancer in Han Chinese women based on a cause-specific Hazard model. BMC Cancer. 2019; 19: 128.

136

China Anti-Cancer Association, National Clinical Research Center for Cancer. Breast cancer screening guideline for Chinese women. Cancer Biol Med. 2019; 16: 822-4.

137

Chinese Anti-Cancer Association, Committee of Breast Cancer Society. Chinese Anti-Cancer Association breast cancer diagnosis and treatment guidelines. China Oncology. 2021; 31: 954-1040.

138

Huang Y, Tong Z, Chen K, Wang Y, Liu P, Gu L, et al. Interpretation of breast cancer screening guideline for chinese women. Cancer Biol Med. 2019; 16: 825-35.

139

Speicher MR, Geigl JB, Tomlinson IP. Effect of genome-wide association studies, direct-to-consumer genetic testing, and highspeed sequencing technologies on predictive genetic counselling for cancer risk. Lancet Oncol. 2010; 11: 890-8.

140

Aboutalib SS, Mohamed AA, Berg WA, Zuley ML, Sumkin JH, Wu S. Deep learning to distinguish recalled but benign mammography images in breast cancer screening. Clin Cancer Res. 2018; 24: 5902-9.

141

Kim H-E, Kim HH, Han B-K, Kim KH, Han K, Nam H, et al. Changes in cancer detection and false-positive recall in mammography using artificial intelligence: a retrospective, multireader study. Lancet Digit Health. 2020; 2: e138-48.

142

Lotter W, Diab AR, Haslam B, Kim JG, Grisot G, Wu E, et al. Robust breast cancer detection in mammography and digital breast tomosynthesis using an annotation-efficient deep learning approach. Nat Med. 2021; 27: 244-9.

143

McKinney SM, Sieniek M, Godbole V, Godwin J, Antropova N, Ashrafian H, et al. International evaluation of an AI system for breast cancer screening. Nature. 2020; 577: 89-94.

144

Rodriguez-Ruiz A, Krupinski E, Mordang JJ, Schilling K, Heywang-Kobrunner SH, Sechopoulos I, et al. Detection of breast cancer with mammography: effect of an artificial intelligence support system. Radiology. 2019; 290: 305-14.

145

Rodriguez-Ruiz A, Lang K, Gubern-Merida A, Broeders M, Gennaro G, Clauser P, et al. Stand-alone artificial intelligence for breast cancer detection in mammography: comparison with 101 radiologists. J Natl Cancer Inst. 2019; 111: 916-22.

146

Dembrower K, Liu Y, Azizpour H, Eklund M, Smith K, Lindholm P, et al. Comparison of a deep learning risk score and standard mammographic density score for breast cancer risk prediction. Radiology. 2020; 294: 265-72.

147

Kakileti ST, Madhu HJ, Manjunath G, Wee L, Dekker A, Sampangi S. Personalized risk prediction for breast cancer pre-screening using artificial intelligence and thermal radiomics. Artif Intell Med. 2020; 105: 101854.

148

Ming C, Viassolo V, Probst-Hensch N, Dinov ID, Chappuis PO, Katapodi MC. Machine learning-based lifetime breast cancer risk reclassification compared with the BOADICEA model: impact on screening recommendations. Br J Cancer. 2020; 123: 860-7.

149

Yala A, Lehman C, Schuster T, Portnoi T, Barzilay R. A deep learning mammography-based model for improved breast cancer risk prediction. Radiology. 2019; 292: 60-6.

150

Zubor P, Kubatka P, Kajo K, Dankova Z, Polacek H, Bielik T, et al. Why the gold standard approach by mammography demands extension by multiomics? Application of liquid biopsy mirna profiles to breast cancer disease management. Int J Mol Sci. 2019; 20: 2878.

151

Zhang X, Zhao D, Yin Y, Yang T, You Z, Li D, et al. Circulating cellfree DNA-based methylation patterns for breast cancer diagnosis. NPJ Breast Cancer. 2021; 7: 106.

Publication history
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Publication history

Received: 17 December 2021
Accepted: 21 February 2022
Published: 01 April 2022
Issue date: April 2022

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©2022 Cancer Biology & Medicine.

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