Impact of the COVID-19 breast cancer screening hiatus on clinical stage and racial disparities in New York City.

BACKGROUND: The impact of the COVID-19 mammography screening hiatus as well as of post-hiatus efforts promoting restoration of elective healthcare on breast cancer detection patterns and stage distribution is unknown. METHODS: Newly diagnosed breast cancer patients (2019-2021) at the New York Presbyterian (NYP) Hospital Network were analyzed. Chi-square and student's t-test compared characteristics of patients presenting before and after the screening hiatus. RESULTS: A total of 2137 patients were analyzed. Frequency of screen-detected and early-stage breast cancer declined post-hiatus (59.7%), but returned to baseline (69.3%). Frequency of screen-detected breast cancer was lowest for African American (AA) (57.5%) and Medicaid patients pre-hiatus (57.2%), and this disparity was reduced post-hiatus (65.3% for AA and 63.2% for Medicaid). CONCLUSIONS: The return to baseline levels of screen-detected cancer, particularly among AA and Medicaid patients suggest that large-scale breast health education campaigns may be effective in resuming screening practices and in mitigating disparities.

Development of a Model to Estimate the Association Between Delay in Cancer Treatment and Local Tumor Control and Risk of Metastases.

Importance: The coronavirus disease 2019 (COVID-19) pandemic has led to treatment delays for many patients with cancer. While published guidelines provide suggestions on which cases are appropriate for treatment delay, there are no good quantitative estimates on the association of delays with tumor control or risk of new metastases. Objectives: To develop a simplified mathematical model of tumor growth, control, and new metastases for cancers with varying doubling times and metastatic potential and to estimate tumor control probability (TCP) and metastases risk as a function of treatment delay interval. Design, Setting, and Participants: This decision analytical model describes a quantitative model for 3 tumors (ie, head and neck, colorectal, and non-small cell lung cancers). Using accepted ranges of tumor doubling times and metastatic development from the clinical literature from 2001 to 2020, estimates of tumor growth, TCP, and new metastases were analyzed for various treatment delay intervals. Main Outcomes and Measures: Risk estimates for potential decreases in local TCP and increases in new metastases with each interval of treatment delay. Results: For fast-growing head and neck tumors with a 2-month treatment delay, there was an estimated 4.8% (95% CI, 3.4%-6.4%) increase in local tumor control risk and a 0.49% (0.47%-0.51%) increase in new distal metastases risk. A 6-month delay was associated with an estimated 21.3% (13.4-30.4) increase in local tumor control risk and a 6.0% (5.2-6.8) increase in distal metastases risk. For intermediate-growing colorectal tumors, there was a 2.1% (0.7%-3.5%) increase in local tumor control risk and a 2.7% (2.6%-2.8%) increase in distal metastases risk at 2 months and a 7.6% (2.2%-14.2%) increase in local tumor control risk and a 24.7% (21.9%-27.8%) increase in distal metastases risk at 6 months. For slower-growing lung tumors, there was a 1.2% (0.0%-2.8%) increase in local tumor control risk and a 0.19% (0.18%-0.20%) increase in distal metastases risk at 2 months, and a 4.3% (0.0%-10.6%) increase in local tumor control risk and a 1.9% (1.6%-2.2%) increase in distal metastases risk at 6 months. Conclusions and Relevance: This study proposed a model to quantify the association of treatment delays with local tumor control and risk of new metastases. The detrimental associations were greatest for tumors with faster rates of proliferation and metastasis. The associations were smaller, but still substantial, for slower-growing tumors.