Consequences of the impact of COVID-19 pandemic on breast cancer at a single Italian institution

Impact of the COVID-19 Pandemic and Vaccine Availability on Utilization of Breast Imaging in a Multistate Radiology Practice

Method

Data were obtained from medical health records across 77 Radiology Partners practices in the US. The data provided us with the total monthly mammography, breast ultrasound, and breast MRI procedures from January 2019 to September 2022. An interrupted time-series (ITS) analysis was conducted to evaluate the effect of the COVID-19 pandemic and the COVID-19 vaccination. We chose March 2020 and December 2020 as critical time points in the pandemic and analyzed trends before and after these dates.

Results

The starting level (at baseline in January 2019) of the total breast imaging procedure volume was estimated at 114,901.5, and this volume appeared to significantly increase every month prior to March 2020 by 4,864.0 (p < 0.0001, CI = [3,077.1, 6,650.9]). In March 2020, there appeared to be a significant decrease in volume by 104,446.3 (p=0.003, CI = [-172,063.1, -36,829.5]), followed by a significant increase in the monthly trend of service volume (relative to the pre-COVID trend) of 20,660.7 per month (p=0.001, CI = [8,828.5, 32,493.0]). In December 2020, there appeared to be a significant decrease in service volume by 69,791.2 (p=0.012, CI = [-123,602.6, -15,979.7]). Compared to the period from March to November 2020, there was a decrease in the monthly trend of service volumes per month by 24,213.9 (p < 0.0001, CI = [-36,027.6, -12,400.2]). After March 2020, the total service volume increased at the rate of 25,524.7 per month (p < 0.0001, CI = [13,828.2, 37,221.2]). In contrast, the service volumes after December 2020 appeared to grow steadily and slowly at a rate of 1,310.8 per month (p=0.118, CI = [-348.8, 2970.3]).

Conclusion

Our study revealed that there has been a recovery and a further increase in breast imaging service volumes compared to prepandemic levels. The increase can be best explained by vaccination rollout, reopening of elective/nonemergency healthcare services, insurance coverage expansion, the decline in the US uninsured rate due to government interventions and policies, and the recovery of jobs with employer-provided medical insurance post-pandemic.

Breast Density Evaluation According to BI-RADS 5th Edition on Digital Breast Tomosynthesis: AI Automated Assessment Versus Human Visual Assessment

Background: The assessment of breast density is one of the main goals of radiologists because the masking effect of dense fibroglandular tissue may affect the mammographic identification of lesions. The BI-RADS 5th Edition has revised the mammographic breast density categories, focusing on a qualitative evaluation rather than a quantitative one. Our purpose is to compare the concordance of the automatic classification of breast density with the visual assessment according to the latest available classification. Methods: A sample of 1075 digital breast tomosynthesis images from women aged between 40 and 86 years (58 ± 7.1) was retrospectively analyzed by three independent readers according to the BI-RADS 5th Edition. Automated breast density assessment was performed on digital breast tomosynthesis images with the Quantra software version 2.2.3. Interobserver agreement was assessed with kappa statistics. The distributions of breast density categories were compared and correlated with age. Results: The agreement on breast density categories was substantial to almost perfect between radiologists (κ = 0.63–0.83), moderate to substantial between radiologists and the Quantra software (κ = 0.44–0.78), and the consensus of radiologists and the Quantra software (κ = 0.60–0.77). Comparing the assessment for dense and non-dense breasts, the agreement was almost perfect in the screening age range without a statistically significant difference between concordant and discordant cases when compared by age. Conclusions: The categorization proposed by the Quantra software has shown a good agreement with the radiological evaluations, even though it did not completely reflect the visual assessment. Thus, clinical decisions regarding supplemental screening should be based on the radiologist’s perceived masking effect rather than the data produced exclusively by the Quantra software.

Mammography in Breast Disease Screening and Diagnosis

Female breasts can suffer from a wide spectrum of pathologies, ranging from inflammatory diseases to benign and malignant tumors [...].

Changes in breast cancer staging trends among Egyptian women after COVID-19: A retrospective single-center study

OBJECTIVES

Since being declared a global pandemic, the SARS-CoV-2 virus had a significant impact on the entire globe. The pandemic has placed a heavy burden on healthcare systems worldwide, and cancer patients are particularly prone. Despite the fact that initial international reports suggest delays in breast cancer (BC) diagnosis and screening programs, the Egyptian context requires additional research on this topic. To examine whether COVID-19 has changed the pattern of disease presentation before and after the pandemic, focusing on the tumor, node, and metastasis (TNM) staging of the disease at the initial presentation.

METHODS

This single-center, retrospective study of female BC patients initially diagnosed at Baheya Foundation was conducted during the following time frames: from Jan 2019 to Jan 2020 (Pre COVID-19 cohort) and from Mar 2020 to Mar 2021 (post-COVID-19 cohort). We compared the two cohorts in terms of clinical characteristics, tumor characteristics, and the number of days from presentation to treatment. Our primary endpoint was the difference in the TNM stage of BC at the initial presentation.

RESULTS

This analysis included 710 BC patients, 350 from the pre-COVID cohort and 360 from the post-COVID group. We detected a 27.9% increase in late-stage BC (stages III-IV) in the post-pandemic cohort compared to the pre-pandemic (60.1% vs. 47%, p < 0.001). The time from diagnosis to commencement of treatment was significantly longer (28.34 ± 18.845 vs 36.04 ± 23.641 days, p < 0.001) in the post-COVID cohort (mean difference = 7.702, 95% CI 4.54-10.85, p < 0.001). A higher percentage of patients in the post-pandemic cohort received systemic neoadjuvant therapy (p-value for Exact's test for all treatment options = 0.001).

CONCLUSIONS

The number of patients requiring systemic neoadjuvant chemotherapy increased dramatically in the post-pandemic group with advanced stages of BC at presentation. This study highlights the need for proper management of cancer patients during any future pandemic.