Differentiation of Microvessel Density Based on The Breast Cancer Patient Characteristics Including Age, Stage, Tumor Size, and Lymph Node Metastasis

Tasya Salsabila, Sari Eka Pratiwi, Heru Fajar Trianto, Muhammad In'am Ilmiawan, Desriani Lestari, Iit Fitrianingrum, Henky Hartono


Background: Breast cancer is the most common malignant tumor in the world and Indonesia. One well-known prognostic marker is microvessel density (MVD), the numerical value of angiogenesis. In recent years, it has been recognized that tumor growth depends on angiogenesis. Therefore, this study aimed to determine the differentiation of MVD based on the breast cancer patients' characteristics including age, stage, tumor size, and lymph node metastasis in the Anatomical Pathology Laboratory of Soedarso Hospital.


Methods: This research was an observational study with a cross-sectional approach. The study was conducted by observing the slides of Hematoxylin-Eosin (HE) in breast cancer patients. Samples were taken using the total sampling technique. The samples were observed by two observers. 51 tissue preparations met the inclusions and exclusions criteria. MVD cut-off points are taken by calculating the median. Research analysis was using the Kruskal-Wallis test in SPSS version 24.


Results: All samples of this study were women and had invasive ductal carcinoma. Breast cancer tends to occur in patients aged 48-53 years, has stage III, lymph node metastasis (N2). The patients have a low MVD rate but have a large tumor size (T4). Kruskal Wallis test showed that there was a differentiation of MVD based on age (p = 0.029). While, there was no differentiation of MVD based on stage (p=0.974), tumor size (0.069), and lymph node metastasis (0.571).


Conclusions: There was a differentiation of MVD based on the age of breast cancer patients in the Anatomical Pathology Laboratory at Soedarso Hospital.


breast cancer, microvessel density, tumor size

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DOI: 10.33371/ijoc.v18i2.1041

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Ghoncheh M, Mahdavifar N, Darvishi E, Salehiniya H. Epidemiology, Incidence and Mortality of Breast Cancer in Asia. Asian Pacific J Cancer Prev. 2016;17:47–52.

World Health Organization. Breast Cancer [Internet]. WHO; 2021 [cited 2023 Feb 28]. Available from: https://www.who.int/news-room/fact-sheets/detail/breast-cancer

Kementerian Kesehatan Republik Indonesia. Kanker Payudara Paling Banyak di Indonesia, Kemenkes Targetkan Pemerataan Layanan Kesehatan [Internet]. Kemkes; 2022 [cited 2023 Feb 28]. Available from: https://www.kemkes.go.id/article/view/22020400002/kanker-payudara- paling-banyak-di-indonesia-kemenkes-targetkan-pemerataan-layanan-kesehatan.html.

Fitriyani. Kecemasan Wanita Penderita Kanker Payudara Di Ruang Bedah Wanita Di RSUD Dr. Soedarso [Internet]. 2016 [cited 2023 Feb 28]. Available from: http://repository.unmuhpnk.ac.id/890/2/BAB I.pdf.

Dyanti G. Faktor-Faktor Keterlambatan Penderita Kanker Payudara Dalam Melakukan Pemeriksaan Awal Ke Pelayanan Kesehatan. J Kesehat Masy. 2016;11(2):96–104.

Septiawati T, Bagus I, Wibawa Manuaba T, Anda P. Hubungan antara Microvessel Density dan Lymphovascular Invasion Dengan Metastasis Jauh Pada Pasien Kanker Payudara di RSUP Sanglah, Bali, Indonesia. Intisari Sains Medis. 2020;11(3):1436–42.

Kraby MR, Opdahl S, Russnes HG, Bofin AM. Microvessel density in Breast Cancer: The Impact of Field Area on Prognostic Informativeness. J Clin Pathol. 2019;72(4):304–10.

Satya W, Niryana IW, Anda TA, Pande AD. Gambaran stadium dan jenis histopatologi kanker payudara di Subbagian Bedah Onkologi RSUP Sanglah Denpasar tahun 2015-2016. Intisari Sains Medis. 2018;9(1):80–4.

Rizki Alfalah. Jenis Histopatologi Berdasarkan Stadium Pada Pasien Kanker Payudara di RSUCM Aceh Utara Tahun 2020. Matriks J Sos dan Sains [Internet]. 2022;4(1):21–30.

Yuliana. Risiko dan Deteksi Dini Kanker Payudara. Cermin Dunia Kedokt. 2018;45(2):144–9.

Robbin, Cotran K. Review of Pathology. Fourth ed. Elsevier Inc.; 2015.

Ilham MF, Yusuf H, Hidayat W. Karakteristik Usia, Gambaran Klinis dan Histopatologi Pasien Kanker Payudara di RSUD Al-Ihsan Provinsi Jawa Barat Periode Januari 2018 - Oktober 2020. J Ris Kedokt. 2021;1(2):85–91.

Krishnapriya S, Malipatil B, Surekha S, Sundersingh S, et al. Microvessel Density in Locally Advanced Breast Cancer. Asian Pacific J Cancer Prev. 2019;20(5):1537–45.

Firasi AA, Jkd Y, Yudhanto E. Hubungan Usia Terhadap Derajat Diferensiasi Kanker Payudara Pada Wanita. J Kedokt Diponegoro [Internet]. 2016;5(4):327–36.

Tichy JR, Lim E AC. Breast Cancer Facts & Figures 2009–2010. In Atlanta: American Cancer Society; 2012.

Putri AR. Studi Literatur Penggunaan Psikoterapi Dalam Mengatasi Efek Samping Kemoterapi Pada Pasien Ca Mammae. 2020;14–5.

Windarti I. Characteristic Of Breast Cancer In Young Women In H. Abdul Moeloek Hospital Bandar Lampung. 2014;4(7):131–5.

Stankov A, Bargallo-Rocha JE, Silvio AN. Prognostic Factors and Recurrence in Breast Cancer: Experience at the National Cancer Institute of Mexico. ISRN Oncol. 2012;2012(Lvi):1–7.

Agnani B, Solanki R, Ansari M. Prognostic Significance of Microvessel Density as Assessed by anti CD34 Monoclonal Antibody in Invasive Ductal Carcinoma of Breast. Asian Pacific J Cancer Biol. 2020;5(3):75–9.

Fang L, He Y, Liu Y, Ding H, et al. Adjustment of Microvessel Area by Stromal Area to Improve Survival Prediction in Non-Small Cell Lung Cancer. J Cancer. 2019;10(15):3397–406.

Marpaung MRA, Khambri D, Asterina A. Karakteristik Penderita Kanker Payudara dengan Metastasis Jauh Tunggal di Kota Padang Tahun 2014-2018. J Ilmu Kesehat Indones. 2021;2(1):82– 9.

Jamnasi J, Gondhowiardjo S, Djoerban Z SN, Poetiray EDC TA. Faktor Risiko Terjadinya Metastasis Jauh Pada Pasien Kanker Payudara. Radioter Onkol Indones. 2016;7(2):55–9.

Xiao W, Zheng S, Yang A, Zhang X, et al. Breast Cancer Subtypes and The Risk of Distant Metastasis at Initial Diagnosis: A Population-Based Study. Cancer Manag Res. 2018;10:5329–38.

Yi F, Yang L, Wang S, Guo L, Huang C, et al. Microvessel Prediction in H&E Stained Pathology Images Using Fully Convolutional Neural Networks. BMC Bioinformatics. 2018;19(1):1–9.

Muhammad EM. Correlation of Microvessel Density and Proliferation Index (Pi) With Clinico- Pathological Parameters in Breast Carcinoma. Assiut Med J. 2013;37(3):155–74.

Comsa S, Cîmpean AM, Ceausu R, Suciu C, et al. Correlations Between Vascular Endothelial Growth Factor Expression, Microvascular Density in Tumor Tissues and TNM Staging in Breast Cancer. Arch Biol.Sci. 2012;64(2):409–18.

Emami Nejad A, Najafgholian S, Rostami A, Sistani A, Shojaeifar S, Esparvarinha M, et al. The Role of Hypoxia in The Tumor Microenvironment and Development of Cancer Stem Cell: a Novel Approach to Developing Treatment. Cancer Cell Int [Internet]. 2021;21(1):1–26. Available from: https://doi.org/10.1186/s12935-020-01719-5.

Biesaga B, Niemiec J, Ziobro M. Microvessel Density and Status of p53 Protein as Potential Prognostic Factors for Adjuvant Anthracycline Chemotherapy in Retrospective Analysis of Early Breast Cancer Patients Group. Pathol Oncol Res. 2012;949–60.

Torii M, Fukui T, Inoue M, Kanao S, et al. Analysis of The Microvascular Morphology and Hemodynamics of Breast Cancer in Mice Using Spring-8 Synchrotron Radiation Microangiography. J Synchrotron Radiat. 2017;24(5):1039–47.

Goodwin P. Stage I-III Breast Cancer. Oncol Times. 2013;35(22):54–5.

American Joint Committee on Cancer. AJCC Cancer Staging Manual. 5th ed. New York: Springer; 2015.


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