Evaluation of Ki67 Biomarker as a Prognostic Marker in Breast Invasive Ductal Carcinoma in Khartoum State in Sudan

Introduction: Worldwide, breast cancer is the most prevalent cancer among women to be diagnosed, and it is the primary cause of cancer-related mortality, coming in second only to lung cancer. High levels of Ki67, a nuclear marker of cell proliferation, in breast cancer are linked to worse outcomes. Methods and materials: This retrospective cross-sectional laboratory investigation aimed to examine Ki67 expression as a prognostic predictor in invasive ductal carcinoma (IDC) utilizing manual tissue microarrays (MTMAs) technology. The study was done from June 2018 to July 2019 at the Elrahman Health Centre in Khartoum, Sudan, using thirty-five paraffin block samples collected from patients previously diagnosed with invasive ductal carcinoma (IDC). The study population ranged in age from 31 to 71 years. Results: The study found that 94.3% (n=33/35) of the tissues were positive for the Ki67 antigen, while 5.7% (n=2/35) were negative. Age and score correlation is (P=0.047), and a favorable prognosis could be the cause of the two unfavorable results. Conclusion: This study highlights the importance of the Ki67 biomarker as a prognostic indicator in invasive ductal carcinoma (IDC) of the breast. High levels of Ki67 expression (94.3%) were associated with more aggressive tumors and poorer prognostic outcomes. However, there was no significant correlation between Ki67 scores and patient age, indicating age does not influence the prognostic value of Ki67 in this cohort.

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Journal
Biomedical & Pharmacology Journal
Published
2024-09-30
DOI
https://doi.org/10.13005/bpj/2995
Primary Topic
AI in cancer detection
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article
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article

Evaluation of Ki67 Biomarker as a Prognostic Marker in Breast Invasive Ductal Carcinoma in Khartoum State in Sudan

Abdalraheem Ali Babiker, Salma Elnour, Khalid Abbas Owish Sukar, Marwan Ismail et al.
Biomedical & Pharmacology Journal
AI in cancer detection
article

Evaluation of Ki67 Biomarker as a Prognostic Marker in Breast Invasive Ductal Carcinoma in Khartoum State in Sudan

Abdalraheem Ali Babiker, Salma Elnour, Khalid Abbas Owish Sukar, Marwan Ismail, Mohamed Alfaki, Asaad Babker, Sarah Ali, Qubaa Ahmed Elzubair, Musaab Ahmed, Salma A. Mohamed, Alaa M. Abdalhadi, Sofiyat Zayyad
article en

Abstract

Introduction: Worldwide, breast cancer is the most prevalent cancer among women to be diagnosed, and it is the primary cause of cancer-related mortality, coming in second only to lung cancer. High levels of Ki67, a nuclear marker of cell proliferation, in breast cancer are linked to worse outcomes. Methods and materials: This retrospective cross-sectional laboratory investigation aimed to examine Ki67 expression as a prognostic predictor in invasive ductal carcinoma (IDC) utilizing manual tissue microarrays (MTMAs) technology. The study was done from June 2018 to July 2019 at the Elrahman Health Centre in Khartoum, Sudan, using thirty-five paraffin block samples collected from patients previously diagnosed with invasive ductal carcinoma (IDC). The study population ranged in age from 31 to 71 years. Results: The study found that 94.3% (n=33/35) of the tissues were positive for the Ki67 antigen, while 5.7% (n=2/35) were negative. Age and score correlation is (P=0.047), and a favorable prognosis could be the cause of the two unfavorable results. Conclusion: This study highlights the importance of the Ki67 biomarker as a prognostic indicator in invasive ductal carcinoma (IDC) of the breast. High levels of Ki67 expression (94.3%) were associated with more aggressive tumors and poorer prognostic outcomes. However, there was no significant correlation between Ki67 scores and patient age, indicating age does not influence the prognostic value of Ki67 in this cohort.

Biomedical & Pharmacology JournalVol. 17(3)
Qatar Airways (Qatar) (QA), XLAB (Slovenia) (SI), Gulf Medical University (AE), Al Emadi Hospital (QA), Sidra Medical and Research Center (QA), University of Gezira (SD)
No poverty
Openalex Percentile: Top 85%
AI in cancer detection
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