Impact of the COVID-19 pandemic on newly-diagnosed breast cancer

COVID-19 大流行对新诊断乳腺癌的影响

• 批准号: 10359555
• 负责人: Sarah Jane Nyante
• 金额: $ 7.78万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10359555
• 关键词: Address; Affect; Age; American Joint Committee on Cancer; Area; Biometry; Black race; Breast Cancer Detection; Breast Cancer Epidemiology; Breast Cancer Patient; COVID-19; COVID-19 pandemic; COVID-19 pandemic effects; Cancer Burden; Cancer Hospital; Cancer Patient; Cancer Prognosis; Caring; Cessation of life; Characteristics; Data; Detection; Diagnosis; Diagnostic; Diagnostic Services; Engineering; Epidemiology; Ethnic Origin; Event; Evidence based intervention; Gold; Health; Health Insurance; Healthcare Systems; Height; Hospitals; Incidence; Infection; Institution; Insurance; Insurance Coverage; Interruption; Intervention; Knowledge; Lead; Link; Malignant Neoplasms; Mammographic screening; Mammography; Measures; Medical center; Medicine; Methodology; Methods; Mission; Modification; Morbidity - disease rate; Neighborhoods; Newly Diagnosed; North Carolina; Observational Study; Oncology; Outcome; Pathology; Patients; Pattern; Population; Population Distributions; Population Heterogeneity; Positive Lymph Node; Premenopause; Process; Prognosis; Public Health; Race; Radiology Specialty; Reporting; Research; Series; Socioeconomic Factors; Socioeconomic Status; Source; Stage at Diagnosis; Subgroup; Symptoms; Testing; Time; Time Series Analysis; Tumor stage; United States National Academy of Sciences; Universities; Woman; attributable mortality; base; breast cancer diagnosis; breast cancer survival; cancer care; cancer diagnosis; cancer health disparity; cancer subtypes; combat; data standards; deprivation; evidence base; follow-up; health equity; hormone receptor-negative; indexing; intervention effect; lymph nodes; malignant breast neoplasm; mortality; neoplasm registry; pandemic disease; patient population; prognostic; racial disparity; receptor; screening; screening services; socioeconomics; survival disparity; trend; tumor; tumor diagnosis

The COVID-19 pandemic resulted in dramatic reductions in use of breast cancer screening and diagnostic services, with screening mammography plunging by up to 99% at the lowest point. Screening and other diagnostic delays have the potential to result in shifts in the population distribution of breast cancer characteristics, resulting in tumors that are larger, higher grade, and more often lymph node positive – all factors associated with increased breast cancer mortality. In observational studies, these effects were more pronounced among Black and premenopausal women, suggesting that pandemic-related changes in the distribution of breast cancer characteristics could worsen existing breast cancer disparities. Despite this emerging evidence, there is little real-world data that quantifies the magnitude of the delay’s effects on the epidemiology of breast cancer. This lack of information inhibits the ability to develop systematic, evidence-based interventions that might reduce excess deaths. Therefore, the objective of this study is to measure the pandemic’s impact on the epidemiology of breast cancer, using data from 3,780 women diagnosed with breast cancer at University of North Carolina (UNC) Medical Center, UNC Rex, and Nash UNC hospitals during the pandemic (March 2020- November 2021), compared to 8,947 breast cancer patients diagnosed at the same hospitals before the pandemic (March 2015-February 2020). The underlying hypothesis is that overall breast cancer incidence declined following the pandemic onset, but that among the breast cancers that were diagnosed tumors with poor prognostic characteristics were over-represented. The hypothesis will be evaluated by pursuing the following specific aims: (1) evaluating pandemic vs. pre-pandemic changes in breast cancer incidence by comparing incidence overall and according to prognostic characteristics (e.g., stage at diagnosis, tumor size, tumor grade, lymph node status, breast cancer subtype); and (2) evaluating pandemic vs. pre-pandemic differences in breast cancer incidence according to indicators of socioeconomic status (e.g., area deprivation index, health insurance status) and patient factors associated with breast cancer survival disparities (age, race/ethnicity). These trends will be evaluated using interrupted time series analysis, a methodologically rigorous approach that allows for the control of pre-pandemic trends while testing for an effect of the intervention. Patient cancer diagnosis and personal information will be obtained from hospital cancer registries, which abstract high-quality, standardized data ~6 months before similar data become publicly available through other sources (e.g., state cancer registry), allowing for the timely identification of changes in breast cancer incidence patterns. Evaluating the pandemic’s impact on the epidemiology of breast cancer will facilitate identification of interventions (e.g., modifications to the diagnostic process, targeting of affected demographic subgroups to decrease loss to follow-up, etc.) to alleviate the impact of pandemic-related delays in care and reduce the number of excess breast cancer deaths attributable to the pandemic.

新冠肺炎大流行导致乳腺癌筛查和诊断的使用大幅减少 服务，筛查乳房X光检查最低点暴跌99%。筛选和其他 诊断延误有可能导致乳腺癌人群分布的转变。 特征，导致肿瘤更大，更高级别，更多的淋巴结阳性-所有因素 与乳腺癌死亡率增加有关。在观察性研究中，这些影响更为明显。 在黑人和绝经前女性中，表明与大流行相关的乳房分布变化 癌症特征可能会加剧现有的乳腺癌差异。尽管有这些新出现的证据，但有 很少有真实世界的数据量化延迟对乳腺癌流行病学影响的程度。 这种信息的缺乏抑制了制定系统的、基于证据的干预措施的能力 可能会减少额外的死亡人数。因此，这项研究的目的是衡量大流行对 乳腺癌的流行病学，使用了来自加州大学3780名被诊断为乳腺癌的女性的数据 大流行期间，北卡罗来纳州(UNC)医疗中心、北卡罗来纳州霸王龙和纳什北卡罗来纳州医院(2020年3月- 2021年11月)，相比之下，在此之前，同一家医院确诊的乳腺癌患者为8947人 大流行(2015年3月至2020年2月)。潜在的假设是乳腺癌的总发病率 在大流行爆发后有所下降，但在被诊断为肿瘤较差的乳腺癌中 预后特征被过度描述。这一假设将通过追求以下几点来评估 具体目标：(1)通过比较大流行与大流行前乳腺癌发病率的变化来评估大流行与大流行前乳腺癌发病率的变化 根据预后特征(例如，诊断阶段、肿瘤大小、肿瘤分级、 淋巴状态、乳腺癌亚型)；以及(2)评估大流行与大流行前乳房的差异 根据社会经济状况指标(例如，地区剥夺指数、医疗保险)计算的癌症发病率 与乳腺癌存活率差异相关的患者因素(年龄、种族/民族)。这些趋势 将使用中断时间序列分析进行评估，这是一种在方法上严格的方法，允许 控制大流行前的趋势，同时测试干预的效果。患者癌症诊断和治疗 个人信息将从医院癌症登记处获得，这些登记处抽象出高质量、标准化的 在类似数据通过其他来源(例如，州癌症登记)公开之前约6个月， 从而能够及时识别乳腺癌发病模式的变化。评估大流行的 对乳腺癌流行病学的影响将有助于确定干预措施(例如，修改 诊断过程、针对受影响的人口亚群以减少后续行动的损失等。)缓解 与大流行有关的护理延误的影响，并减少可归因于乳腺癌的过量死亡人数 对大流行的影响。