Abstract P3-03-24: The WISDOM Study: Early Ascertainment of Breast Cancer Diagnoses by Utilizing Self-Reported Questionnaires and Data Warehouse Electronic Health Records

BACKGROUND WISDOM (Women Informed to Screen Depending on Measures of risk) is a pragmatic trial comparing the safety, efficacy, cost, and patient acceptability of personalized versus annual breast cancer screening in women ages 40-74 years with no personal history of breast cancer. Cancer registry reporting is considered the gold standard for ascertaining cancer diagnosis data; however, the time lag between diagnosis and reporting (1-2 years or more) by the California Cancer Registry (CCR) presents challenges. The WISDOM study must quickly ascertain and report accurate cancer diagnoses to the Data Safety Monitoring Board; delays could lead to preventable harm, unnecessary costs, and unwarranted early trial termination. To ascertain cancer diagnoses in a timely manner, we used multiple data collection methods and compared self-reported with Electronic Health Records (EHR) information, and in some cases verified with chart review. Specifically, we conducted a procedural study with WISDOM participants who sought care at a University of California (UC) health system by extracting their data from the University of California Data Warehouse (UCDW) to 1) verify self-reported breast cancer diagnoses in WISDOM; 2) ensure that all on-study breast cancer diagnoses have been captured within the WISDOM study cohort; and 3) assess the accuracy and reliability of self-reported data. The UCDW provides harmonized EHR data from the six University of California (UC) health systems and constitutes ~120 billion data points from 7.8 million patient records. METHODS We provided the UCDW with a list of WISDOM participants who indicated they had sought care from a UC health system. Participants with recorded breast cancer diagnostic code (ICD-10CM C50.) were matched with the WISDOM self-reported cancer dataset to uncover participants who had no recorded breast cancer diagnosis in the study system. For those individuals with no recorded self-report diagnosis, coordinators conducted manual chart review to determine whether the participants had been diagnosed with breast cancer. RESULTS This cohort included 11,314 enrolled WISDOM participants who self-reported care at a UC and had at least one diagnostic or procedural breast care code. Among these participants, 160 had a ICD-10-CM C50 breast cancer diagnostic code of which 132 breast cancer cases were confirmed: 111 were already self-reported through WISDOM and 21 additional confirmed breast cancer cases were identified through the UCDW. As a standard process, only WISDOM self-reported cancer cases that were confirmed by chart review are entered into the study database. The percentage of confirmed UCDW-identified cases that were not also self-reported was greater for recent diagnoses (16% overall and 6% for period prior to June 2020). Among the 11,314 participants in our cohort, the CCR identified 61 pre-June 2020 cancer diagnoses. Of these 61 diagnoses, 92% (56) were identified by the UCDW procedural process. If the UCDW had been used as the single source for cancer diagnosis, 21 participants without cancer and 7 participants with unclear status (unlocated or inaccessible records) would have been classified as cancer cases. DISCUSSION/CONCLUSION Self-reported data provides quick ascertainment with relative accuracy compared to cancer registry. Cancer ascertainment can be further improved by combining self-reported data with EHR data from a health system data warehouse registry, particularly for self-reported questionnaire issues such as timing and lack of response. Accuracy of self-reported cancer diagnosis from annually distributed questionnaires improves over time. Identifying cancer diagnosis discordance between data sources can inform processes to improve self-reported study accuracy.

Citation Format: Katherine Leggat-Barr, Rita H. Ryu, Allison Stover Fiscalini, Tomiyuri Lewis, Rohini S. Bulusu, Samrrah A. Raouf, Hannah Lui Park, Alyssa N. Rocha, Liliana Johansen, Laura Van ’t Veer, Laura J. Esserman, Michael A. Hogarth. The WISDOM Study: Early Ascertainment of Breast Cancer Diagnoses by Utilizing Self-Reported Questionnaires and Data Warehouse Electronic Health Records [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-03-24.

Early Ascertainment of Breast Cancer Diagnoses Comparing Self-Reported Questionnaires and Electronic Health Record Data Warehouse: The WISDOM Study

PURPOSE

The goal of this study was to use real-world data sources that may be faster and more complete than self-reported data alone, and timelier than cancer registries, to ascertain breast cancer cases in the ongoing screening trial, the WISDOM Study.

METHODS

We developed a data warehouse procedural process (DWPP) to identify breast cancer cases from a subgroup of WISDOM participants (n = 11,314) who received breast-related care from a University of California Health Center in the period 2012-2021 by searching electronic health records (EHRs) in the University of California Data Warehouse (UCDW). Incident breast cancer diagnoses identified by the DWPP were compared with those identified by self-report via annual follow-up online questionnaires.

RESULTS

Our study identified 172 participants with confirmed breast cancer diagnoses in the period 2016-2021 by the following sources: 129 (75%) by both self-report and DWPP, 23 (13%) by DWPP alone, and 20 (12%) by self-report only. Among those with International Classification of Diseases 10th revision cancer diagnostic codes, no diagnosis was confirmed in 18% of participants.

CONCLUSION

For diagnoses that occurred ≥20 months before the January 1, 2022, UCDW data pull, WISDOM self-reported data via annual questionnaire achieved high accuracy (96%), as confirmed by the cancer registry. More rapid cancer ascertainment can be achieved by combining self-reported data with EHR data from a health system data warehouse registry, particularly to address self-reported questionnaire issues such as timing delays (ie, time lag between participant diagnoses and the submission of their self-reported questionnaire typically ranges from a month to a year) and lack of response. Although cancer registry reporting often is not as timely, it does not require verification as does the DWPP or self-report from annual questionnaires.

Abstract PD14-07: PD14-07 Associations of Breast Cancer Risk Level and Prediction of Tumor Aggressiveness in the Athena Breast Health Network

Background: The Athena Breast Health Network (Athena) is a University of California (UC) initiative integrating clinical care and research to drive improvements in breast cancer screening. Through standardized, self-reported clinical intake forms, a patient’s breast health status and information regarding their breast cancer risk is captured before each mammography appointment. Breast cancer risk models provide a level of risk to develop breast cancer but do not take into account aggressiveness of breast cancer. Here, we evaluated outcome data of a large screening cohort for association between risk level and aggressiveness at diagnosis. Methods: We calculated Breast Cancer Surveillance Consortium (BCSC) risk scores for a cohort of 8,923 consented UCSF Athena participants from the years 2012-2018 with a median follow-up of 5-years. To identify those who developed invasive breast cancer on or after completing an Athena intake form, we performed a cancer linkage with the San Francisco Mammography Registry (SFMR), a local registry that regularly collects cancer data from the California Cancer Registry. We classified tumors as aggressive if they met one or more of the following criteria: hormone receptor (HR)-negative, HER2-positive, grade 3. All other tumors were classified as non-aggressive. We used student’s t-tests to examine associations between BCSC 5-year risk score, the development of invasive breast cancer, and tumor aggressiveness among cases. To account for the association between older age and higher BCSC risk score (as well as HR-positive subtypes), we stratified by percentiles of BCSC risk by age (top 2.5% vs. bottom 97.5%). The top 2.5% by age threshold consistently identifies women with lifetime risk of 23–28% and was chosen as high-risk threshold to trigger annual screening in the WISDOM study (Dreher: PMID34843026). Results: Of 8,923 participants, 170 (2%) developed breast cancer during the follow-up period. The average 5-year BCSC risk score for women with breast cancer was 1.81% and 1.47% for those without (p< 0.001). Among women with breast cancer, 123 (72%) developed non-aggressive cancers and 47 (28%) developed aggressive cancers. The average 5-year BCSC risk score for women with non-aggressive and aggressive cancers was 1.89% and 1.60%, respectively (p=0.13). In analyses stratified by percentile of BCSC risk by age, 521 (6%) participants had a BCSC 5-year risk score in the top 2.5% by age and 8,402 (94%) participants had a BCSC 5-year risk score in the bottom 97.5%. A higher percentage of women with non-aggressive cancers vs healthy women (controls) were in the top 2.5% by age (p = 0.001), but the percentage of aggressive cancers vs healthy women in the top 2.5% by age was similar (p = 0.61). Conclusion: Through this study we confirmed that higher 5-year BCSC risk scores are associated with higher overall breast cancer development. Interestingly, participants with the highest 5-year BCSC risk scores (top 2.5% by age), are more likely to develop cancers with non-aggressive features (low grade, hormone positive). This suggests that the BCSC model may preferentially predict less aggressive tumors, and those with the highest 5-year BCSC risk may be more likely to benefit from endocrine risk reduction therapy. There remains a gap in our ability to identity those at risk for aggressive cancers. Our findings highlight the need for screening programs to better understand who is at risk for what type of breast cancer. Current work is focused on developing models tailored to risk prediction of aggressive cancers.

Citation Format: Katherine Leggat-Barr, Tomiyuri Lewis, Rosalyn Sayaman, Paige Warner, Kathy Malvin, Leah Sabacan, Elene Tsopurashvili, WISDOM Study and Athena Breast Health Network Investigators and Advocate Partners, Allison Stover Fiscalini, Jeffrey Tice, Karla Kerlikowske, Yiwey Shieh, Laura J. Esserman, Laura Van ’t Veer. PD14-07 Associations of Breast Cancer Risk Level and Prediction of Tumor Aggressiveness in the Athena Breast Health Network [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD14-07.

A roadmap to reduce the incidence and mortality of breast cancer by rethinking our approach to women's health

Despite progress, breast cancer remains the most feared disease among women. In the USA alone, the incidence is now almost 300,000 new cancers per year, a rate that has nearly doubled in the last 30 years. Most women survive, but over 40,000 women a year still die of their disease [99]. It is the most diagnosed cancer among women and the second leading cause of cancer death. Important disparities exist in breast cancer outcomes among African American women, where women die of breast cancer at higher rates, are diagnosed younger, and at a more advanced stage. We are proposing a radical shift in our thinking about breast cancer prevention with an aspiration to dramatically lower breast cancer incidence. Most breast cancers are driven by steroid hormones. Throughout the life course, women are offered an array of hormonal treatments for menstrual cycle control, family planning, in vitro fertilization, postpartum weaning, and menopausal symptom management. There are mixed data on the extent to which each of these may contribute to increased or decreased risk for breast cancer. These endocrine manipulations could represent a great opportunity to potentially reduce breast cancer incidence and improve quality of life for survivors. To date, they have not been designed to explicitly reduce breast cancer risk. A new holistic approach will require scientists, drug developers, breast oncologists, obstetricians, gynecologists, endocrinologists, radiologists, and family medicine/internists to work together toward the common goal of reducing breast cancer risk while addressing other critical issues in women's health.