Login Register Cart 0
Generic placeholder image

Current Radiopharmaceuticals

Editor-in-Chief

ISSN (Print): 1874-4710
ISSN (Online): 1874-4729

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

Development and Validation of a Nomogram for Predicting Breast Malignancy in Male Patients Based on Clinical and Ultrasound Features

Author(s): Wei-Hong Dong, Gang Wu*, Nan Zhao and Juan Zhang

Volume 17, Issue 3, 2024

Published on: 29 January, 2024

Page: [266 - 275] Pages: 10

DOI: 10.2174/0118744710274400231219060149

Price: $65

Abstract

Objective: This study aimed to construct a nomogram based on clinical and ultrasound (US) features to predict breast malignancy in males.

Methods: The medical records between August, 2021 and February, 2023 were retrospectively collected from the database. Patients included in this study were randomly divided into training and validation sets in a 7:3 ratio. The models for predicting the risk of malignancy in male patients with breast lesions were virtualized by the nomograms.

Results: Among the 71 enrolled patients, 50 were grouped into the training set, while 21 were grouped into the validation set. After the multivariate analysis was done, pain, BI-RADS category, and elastography score were identified as the predictors for malignancy risk and were selected to generate the nomogram. The C-index was 0.931 for the model. Concordance between predictions and observations was detected by calibration curves and was found to be good in this study. The model achieved a net benefit across all threshold probabilities, which was shown by the decision curve analysis (DCA) curve.

Conclusion: We successfully constructed a nomogram to evaluate the risk of breast malignancy in males using clinical and US features, including pain, BI-RADS category, and elastography score, which yielded good predictive performance.

« Previous Next »
Graphical Abstract

[1]
Yadav, S.; Karam, D.; Bin Riaz, I.; Xie, H.; Durani, U.; Duma, N.; Giridhar, K.V.; Hieken, T.J.; Boughey, J.C.; Mutter, R.W.; Hawse, J.R.; Jimenez, R.E.; Couch, F.J.; Leon-Ferre, R.A.; Ruddy, K.J. Male breast cancer in the United States: Treatment patterns and prognostic factors in the 21st century. Cancer, 2020, 126(1), 26-36.
[http://dx.doi.org/10.1002/cncr.32472] [PMID: 31588557]
[2]
Nofal, M.N.; Yousef, A.J. The diagnosis of male breast cancer. Neth. J. Med., 2019, 77(10), 356-359.
[PMID: 31880271]
[3]
Gucalp, A.; Traina, T.A.; Eisner, J.R.; Parker, J.S.; Selitsky, S.R.; Park, B.H.; Elias, A.D.; Baskin-Bey, E.S.; Cardoso, F. Male breast cancer: A disease distinct from female breast cancer. Breast Cancer Res. Treat., 2019, 173(1), 37-48.
[http://dx.doi.org/10.1007/s10549-018-4921-9] [PMID: 30267249]
[4]
Guo, R.; Lu, G.; Qin, B.; Fei, B. Ultrasound imaging technologies for breast cancer detection and management: A review. Ultrasound Med. Biol., 2018, 44(1), 37-70.
[http://dx.doi.org/10.1016/j.ultrasmedbio.2017.09.012] [PMID: 29107353]
[5]
Yang, K.; Ye, X.; Tian, H.; Li, Q.; Liu, Q.; Li, J.; Guo, J.; Xu, J.; Dong, F. Development and validation of a nomogram for discriminating between benign and malignant breast masses by conventional ultrasound and dual-mode elastography: A multicenter study. Quant. Imaging Med. Surg., 2023, 13(2), 865-877.
[http://dx.doi.org/10.21037/qims-22-237] [PMID: 36819244]
[6]
Zhang, Q.; Zhang, Q.; Liu, T.; Bao, T.; Li, Q.; Yang, Y. Development and external validation of a simple-to-use dynamic nomogram for predicting breast malignancy based on ultrasound morphometric features: A retrospective multicenter study. Front. Oncol., 2022, 12, 868164.
[http://dx.doi.org/10.3389/fonc.2022.868164]
[7]
Luo, WQ.; Huang, QX.; Huang, XW.; Hu, HT.; Zeng, FQ.; Wang, W. Predicting breast cancer in breast imaging reporting and data system (BI-RADS) ultrasound category 4 or 5 lesions: A nomogram combining radiomics and BI-RADS. Sci. Rep., 2019, 9(1), 11921.
[http://dx.doi.org/10.1038/s41598-019-48488-4]
[8]
Spak, D.A.; Plaxco, J.S.; Santiago, L.; Dryden, M.J.; Dogan, B.E. BI-RADS® fifth edition: A summary of changes. Diagn Interv Imaging, 2017, 98(3), 179-190.
[http://dx.doi.org/10.1016/j.diii.2017.01.001]
[9]
Lin, X.; Zhuang, S.; Yang, S.; Lai, D.; Chen, M.; Zhang, J. Development and internal validation of a conventional ultrasound-based nomogram for predicting malignant nonmasslike breast lesions. Quant. Imaging Med. Surg., 2022, 12(12), 5452-5461.
[http://dx.doi.org/10.21037/qims-22-378] [PMID: 36465828]
[10]
Wang, Z.L.; Li, N.; Li, M.; Wan, W.B. Non-mass-like lesions on breast ultrasound: classification and correlation with histology. Radiol. Med., 2015, 120(10), 905-910.
[http://dx.doi.org/10.1007/s11547-014-0493-x] [PMID: 25725790]
[11]
Kapetas, P.; Clauser, P.; Woitek, R.; Wengert, G.J.; Lazar, M.; Pinker, K.; Helbich, T.H.; Baltzer, P.A.T. Quantitative multiparametric breast ultrasound. Invest. Radiol., 2019, 54(5), 257-264.
[http://dx.doi.org/10.1097/RLI.0000000000000543] [PMID: 30632985]
[12]
Liang, T.; Cong, S.; Yi, Z.; Liu, J.; Huang, C.; Shen, J.; Pei, S.; Chen, G.; Liu, Z. ULTRASOUND-BASED nomogram for distinguishing malignant tumors from nodular sclerosing adenoses in solid breast lesions. J. Ultrasound Med., 2021, 40(10), 2189-2200.
[http://dx.doi.org/10.1002/jum.15612] [PMID: 33438775]
[13]
Yao, N.; Shi, W.; Liu, T. Clinicopathologic characteristics and prognosis for male breast cancer compared to female breast cancer. Sci. Rep., 2022, 12(1), 220.
[http://dx.doi.org/10.1038/s41598-021-04342-0]
[14]
Dave, RV.; Bromley, H.; Taxiarchi, VP. No association between breast pain and breast cancer: A prospective cohort study of 10 830 symptomatic women presenting to a breast cancer diagnostic clinic. Br J Gen Pract., 2022, 72(717), e234-e243.
[http://dx.doi.org/10.3399/BJGP.2021.0475]
[15]
Blundell, S.; Deshmukh, M.; McGregor, A. A painful breast mass. Clin. Infect. Dis., 2022, 75(12), 2275-2277.
[http://dx.doi.org/10.1093/cid/ciac250] [PMID: 36533895]
[16]
Farras Roca, J.A.; Tardivon, A.; Thibault, F.; Rouzier, R.; Klijanienko, J. Correlation of ultrasound, cytological, and histological features of 110 benign BI-RADS categories 4C and 5 nonpalpable breast lesions. The Institut Curie’s experience. Cancer Cytopathol., 2021, 129(6), 479-488.
[http://dx.doi.org/10.1002/cncy.22402] [PMID: 33689204]
[17]
Taylor, K.; Britton, P.; O’Keeffe, S.; Wallis, M.G. Quantification of the UK 5-point breast imaging classification and mapping to BI-RADS to facilitate comparison with international literature. Br. J. Radiol., 2011, 84(1007), 1005-1010.
[http://dx.doi.org/10.1259/bjr/48490964] [PMID: 22011830]
[18]
Liu, J.; Xu, M.; Ren, J.; Li, Z.; Xi, L.; Chen, B. Synthetic MRI, multiplexed sensitivity encoding, and BI-RADS for benign and malignant breast cancer discrimination. Front. Oncol., 2023, 12, 1080580.
[http://dx.doi.org/10.3389/fonc.2022.1080580]
[19]
Zheng, X.; Li, F.; Xuan, ZD.; Wang, Y.; Zhang, L. Combination of shear wave elastography and BI-RADS in identification of solid breast masses. BMC Med Imaging., 2021, 21(1), 183.
[http://dx.doi.org/10.1186/s12880-021-00702-4]
[20]
Hong, ZL.; Chen, S.; Peng, XR.; Li, JW.; Yang, JC.; Wu, SS. Nomograms for prediction of breast cancer in breast imaging reporting and data system (BI-RADS) ultrasound category 4 or 5 lesions: A single-center retrospective study based on radiomics features. Front Oncol., 2022, 12, 894476.
[http://dx.doi.org/10.3389/fonc.2022.894476]
[21]
Schwab, F.; Redling, K.; Siebert, M.; Schötzau, A.; Schoenenberger, C.A.; Zanetti-Dällenbach, R. Inter- and intra-observer agreement in ultrasound BI-RADS classification and real-time elastography tsukuba score assessment of breast lesions. Ultrasound Med. Biol., 2016, 42(11), 2622-2629.
[http://dx.doi.org/10.1016/j.ultrasmedbio.2016.06.017] [PMID: 27503826]
[22]
Bojanic, K.; Katavic, N.; Smolic, M.; Peric, M.; Kralik, K.; Sikora, M.; Vidačić, K.; Pacovski, M.; Stimac, D.; Ivanac, G. Implementation of elastography score and strain ratio in combination with b-mode ultrasound avoids unnecessary biopsies of breast lesions. Ultrasound Med. Biol., 2017, 43(4), 804-816.
[http://dx.doi.org/10.1016/j.ultrasmedbio.2016.11.019] [PMID: 28094066]
[23]
Chen, W.; Fang, L.X.; Chen, H.L.; Zheng, J.H. Accuracy of ultrasound elastography for predicting breast cancer response to neoadjuvant chemotherapy: A systematic review and meta-analysis. World J. Clin. Cases, 2022, 10(11), 3436-3448.
[http://dx.doi.org/10.12998/wjcc.v10.i11.3436] [PMID: 35611212]
[24]
Turnaoğlu, H.; Haberal, KM.; Arslan, S.; Yavuz Çolak, M.; Ulu Öztürk, F.; Uslu, N. Interobserver and intermethod variability in data interpretation of breast strain elastography in suspicious breast lesions. Turk J Med Sci., 2021, 51(2), 547-554.
[http://dx.doi.org/10.3906/sag-2006-257]
[25]
Sinha, D.; Sharma, S.; Kundaragi, N.G.; Kale, S.K. Added value of strain elastography in the characterisation of breast lesions: A prospective study. Ultrasound, 2020, 28(3), 164-173.
[http://dx.doi.org/10.1177/1742271X20912762] [PMID: 32831889]
[26]
Guo, G.; Feng, J.; Jin, C. A novel nomogram based on imaging biomarkers of shear wave elastography, angio planewave ultrasensitive imaging, and conventional ultrasound for preoperative prediction of malignancy in patients with breast lesions. Diagnostics, 2023, 13(3), 540.
[http://dx.doi.org/10.3390/diagnostics13030540]
[27]
Jiang, M.; Li, C.L.; Chen, R.X.; Tang, S.C.; Lv, W.Z.; Luo, X.M.; Chuan, Z.R.; Jin, C.Y.; Liao, J.T.; Cui, X.W.; Dietrich, C.F. Management of breast lesions seen on US images: Dual-model radiomics including shear-wave elastography may match performance of expert radiologists. Eur. J. Radiol., 2021, 141, 109781.
[http://dx.doi.org/10.1016/j.ejrad.2021.109781] [PMID: 34029933]

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy