期刊
EUROPEAN RADIOLOGY
卷 32, 期 3, 页码 1644-1651出版社
SPRINGER
DOI: 10.1007/s00330-021-08264-3
关键词
COVID-19; Lockdown; Breast cancer; Diagnosis; Neoplasm staging
The COVID-19 lockdown led to a 20% decrease in diagnosed breast cancer cases, but there was a 48% increase after the lockdown. Breast cancers diagnosed after the lockdown were more symptomatic, had larger tumors, and higher rates of lymph node invasion compared to the reference period.
Objectives Due to COVID-19, a lockdown took place between March 17 and May 1, 2020, in France. This study evaluates the impact of the lockdown on the diagnosis and staging of breast cancers in a tertiary cancer centre. Methods Our database was searched for all consecutive invasive breast cancers diagnosed in our institution during the lockdown (36 working days), during equivalent periods of 36 working days before and after lockdown and a reference period in 2019. The number and staging of breast cancers diagnosed during and after lockdown were compared to the pre-lockdown and reference periods. Tumour maximum diameters were compared using the Mann-Whitney test. Proportions of tumour size categories (T), ipsilateral axillary lymph node invasion (N) and presence of distant metastasis (M) were compared using Fisher's exact test. Results Compared to the reference period (n = 40 in average), the number of breast cancers diagnosed during lockdown (n = 32) decreased by 20% but increased by 48% after the lockdown (n = 59). After the lockdown, comparatively to the reference period, breast cancers were more often symptomatic (86% vs 57%; p = 0.001) and demonstrated bigger tumour sizes (p = 0.0008), the rates of small tumours (T1) were reduced by 38%, locally advanced cancers (T3, T4) increased by 80% and lymph node invasion increased by 64%. Conclusion The COVID-19 lockdown was associated with a 20% decrease in the number of diagnosed breast cancers. Because of delayed diagnosis, breast cancers detected after the lockdown had poorer prognosis with bigger tumour sizes and higher rates of node invasion.
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