Impact of the COVID-19 Pandemic on Histopathological Diagnosis of Breast Tumours in Calabar, Nigeria
PDF

Keywords

COVID-19 pandemic,
breast tumours,
malignant,
benign
diagnosis,
artificial neural networks,

How to Cite

Udonkang, M., Umoh, N., Ogba, O., Bebia, G., Onwineng, D., ANKU, B., & Ernest, N. (2023). Impact of the COVID-19 Pandemic on Histopathological Diagnosis of Breast Tumours in Calabar, Nigeria . Nigerian Journal of Physiological Sciences, 38(1), 23–28. https://doi.org/10.54548/njps.v38i1.5

Abstract

The Coronavirus-19 transmitted through physical contact, droplets, and fomites caused severe respiratory disease resulting in high mortality worldwide. The COVID-19 pandemic caused innumerable hardships, panic, and restrictions of movement which negatively affected the assessment of healthcare services like breast cancer diagnosis in many countries. The results from the histopathological diagnosis of breast tumours have been routinely employed for the treatment and management of these diseases. This study investigated the impact of the COVID-19 pandemic on the histopathological diagnosis of breast tumours in Calabar. A retrospective study of the newly diagnosed breast tumours recorded in the Histopathology Laboratory register during the COVID-19 and the post-COVID-19 recovery from January 2020-February 2021 was compared with cases diagnosed before the pandemic from January 2018 to February 2019. Descriptive and inferential statistics and the Artificial Neural Network (ANN) of Statistical Package for Social Sciences (SPSS) were used for data analysis. New breast tumours diagnosed based on month showed low rates of 2.4% and 1.2% during the first and second waves of the pandemic respectively. The diagnosed cases increased to 11.8% and 8.2% after the first and second waves of the virus respectively. There was a significantly strong negative correlation between the COVID-19 pandemic and lockdown measures with breast tumour diagnosis (r=-0.919, p=0.001). More benign tumours of 56(58.3%) cases with a mean age of 25.3±11.1 years were recorded before the pandemic and were statistically significant (F=64.260, p=0.004). More malignant cases of 48(57.1%) with a mean age of 47.5±11.7 years were recorded during the pandemic. The diagnosis of malignant tumours was statistically significant between both periods (F=183.550, p=0.001). The ANN model predicted a 25% reduction in breast tumour diagnosis during the pandemic. There was a 100% impact of the pandemic on tumour type, the nature of specimen, and mean age of subjects. The COVID-19 pandemic disrupted the assessment of healthcare services as a smaller number of women were diagnosed with breast tumours during the period. This may have caused delays and late presentation leading to the diagnosis of more malignant tumours. There is a need to put adequate measures to encourage the assessment of diagnostic services during pandemics as delays may lead to an increase in morbidity and mortality

https://doi.org/10.54548/njps.v38i1.5
PDF

References

Bosch G, Posso M, Louro J, Roman M, Porta M, Castells X, et al. (2022). Impact of the COVID-19 pandemic on breast cancer screening indicators in a Spanish population-based program: a cohort study. eLife. 11; e77434.

Breast Screening Working Group (WG2) of the Covid-19 and Cancer Global Modelling Consortium, Figueroa, JD, Gray, E; Pashayan, N., Deandrea, S., Karch, A., et al. (2021). The impact of the Covid-19 pandemic on breast cancer early detection and screening. Prev Med. 151: 106585.

Ebughe GA, Ekanem IA, Omoronyia OE, Nnoli MA, Nwagbara VJ, Udosen JE, et al. (2016). Age specific incidence of breast cancer in Calabar, Nigeria. Int J Trop Dis Health. 16(4): 1-12.

Ebughe GA, Ugbem TI, Ushie DE, Effewongbe S. (2019). Cancer in Cross River State. J Adv. Med. Medi. Res. 30: 1-8.

Ekpenyong B, Obinwanne CJ, Ovenseri-Ogbomo G, Ahaiwe K, Lewis OO, Echendu DC, et al. (2020). Assessment of knowledge, practice and guidelines towards the Novel COVID-19 among eye care practitioners in Nigeria- A survey-based study. Int. J Environ. Res. Public Health. 17(14): 5141.

Goyal, M. (2013). Research methodology for health professionals including proposal, thesis and article writing, 1st ed. Jaypee Brothers Medical Publishers, New Delhi: pp45-86.

Lee M and Sultanian HT. (2015). Breast fibroadenoma in adolescents: Current perspectives. Adolesc. Health Med. Ther. 6: 159-63.

Nigeria Centre for Disease Control (NCDC). (2020a). COVID-19 outbreak in Nigeria situation report on 9th March, 2020. Serial Number: 010. http//:www.NCDC%20COVID%20UPDATE/COVID%20MAR9%202020.pdf

Nigeria Centre for Disease Control (NCDC) (2020b). COVID-19 situation weekly epidemiological report on 1st November 2020 for Week 44 covering 26th October – 1st November 2020. http//:NCDC%20COVID%20UPDATE/COVID%20WEEK44%20OCT%20NOV2020.pdf

Olabumuyi AA, Ali-Gombe M, Biyi-Olutunde OA, Gbolahan O, Iwuji CO, Joseph AO, et al. (2020). Oncology practice in the COVID-19 pandemic: a report of a Nigerian expert panel discussion (oncology care in Nigeria during the COVID-19 pandemic). Pan Afr. Med. J. 36: 153.

Udonkang M, Ugbem T, Eze I, Offem E, Akom A, Johnson S, et al. (2021b). Pattern of immunohistochemical expression of inherited breast cancer genes and collagen changes among African women with early breast cancer in Calabar, Nigeria. Global J. Pure Appl. Sci. 27(3): 327-34.

Udonkang M, Ene C, Archibong A, Egbe A, Inyang I. (2021b). Aqueous beetroot dye as an alternative to haematoxylin and eosin in the diagnosis of breast tumours. Global J. Pure Appl. Sci. 27(4): 417-423.

Udonkang MI, Ugbem TI, Egbe AE, Archibong AM, Oborairuvwe OB. Ulom DI. & Omoni OA (2022). The Pattern of Occurrence, Risk Factor and Biomarkers Associated with Leiomyoma in Calabar, Nigeria. Afr. J. Health Sci. 35(5): 628-638.

Vrdoljak E, Balja MP, Marušić Z, Avirović M, Blažičević V, Tomasović C, et al. (2021). COVID-19 Pandemic Effects on Breast Cancer Diagnosis in Croatia: A Population- and Registry-Based Study. The Oncologist. 26(7): e1156-e1160.

World Health Organisation (WHO). (2020a). Director-General's remarks at the media briefing on 2019-nCoV on 11 February 2020. https://www.who.int/dg/speeches/detail/who-director-general-s-remarks-at-the-media-briefingon-2019-ncov-on-11-february-20.

World Health Organization (WHO). (2020b). Coronavirus disease 2019 (COVID-19) Situation Report – 46. 2020b: 1-2. Retrieved online on 06 March 2020. https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200306-sitrep-46-covid-19.pdf?sfvrsn=96b04adf_2

Yong, JH, Mainprize JG, Yaffe MJ, Ruan Y, Poirier AE, Coldman A, et al. (2021). The impact of episodic screening interruption: COVID-19 and population-based cancer screening in Canada. J. Med. Screening. 28:100–107.

Zacharis, NZ (2016). Predicting student academic performance in blended learning using artificial neural networks. Int. J. Art. Intel. Appl. 7(5): 17-29.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright (c) 2023 Nigerian Journal of Physiological Sciences