Measuring Real-World Breast Cancer Outcomes
Allison Kurian , M.D. -
|Award Cycle:||2010 (Cycle 16)||Grant #: 16OB-0149||Award: $1,066,225|
|Award Type:||Translational Research Award|
|Detection, Prognosis and Treatment>Innovative Treatment Modalities: search for a cure|
Initial Award Abstract (2010)
Randomized trials have proven that diagnostic and therapeutic interventions can reduce breast cancer mortality. However, breast cancer care in the “real-world” setting of clinical practice, delivered across a broad range of health care systems and patient populations, deviates greatly from the standards set by clinical trials. Disparities in breast cancer survival persist; interventions are often not used as recommended by evidence-based practice guidelines. There are major areas of controversy at the leading-edge of breast cancer care, for which we lack consensus on how to apply emerging research in the clinical setting. Thus, “real-world” breast cancer care remains an uncharted territory where we lack understanding of what drives specific treatment approaches, and more importantly, how different approaches impact individual patients.
To address critical issues surrounding “real world” issues in breast cancer treatment and care, we will investigate the usage patterns of specific treatments across different California institutions. For this, we will build an internet-based tool that enables patients to report their care preferences, and we will determine how patient preferences shape care. Rather than testing a hypothesis, our proposed work will create, and demonstrate the use of, a ground-breaking breast cancer outcomes research methodology, delivering a uniquely informative report on “real world” breast cancer care.
Specifically, we aim to translate the electronic health records (EHRs) across California institutions into a shareable research tool that generates high-resolution “portraits” of breast cancer care, and identifies specific strategies that yield good and bad outcomes. We will expand a developing database, called OncoShare, through which we link records of breast cancer patients at Stanford University Cancer Center and Palo Alto Medical Foundation (PAMF). First, we will analyze patterns of breast cancer care among a retrospective cohort of 2520 women treated at Stanford and PAMF from 2006-2009, focusing on major treatment controversies at the leading-edge of care. Next, we will develop an electronic patient survey that elicits care preferences and health-related quality of life, with links to individual-level EHR data in OncoShare. Finally, we will enroll a prospective cohort of women starting breast cancer treatment at Stanford and PAMF over the course of one year (target N=320), and administer the patient survey before their first course of therapy. In total, we will evaluate patterns of care matched against the treatment controversies, and identify how patient preferences shape care. We will follow the patient cohorts for cancer recurrence and survival, and identify how specific care patterns serve to optimize these long-term outcomes.
OncoShare extracts de-identified data from the EHRs of all patients receiving breast cancer care at Stanford and PAMF from 2006-2009 (N=2520), including demographics, chemotherapy drug orders, laboratory, radiologic, and pathologic test results. A unique innovation in OncoShare is its ability to “mine” physician’s clinic visit notes through “Natural Language Processing” technology, to obtain details of clinical decision-making. In this study we plan to enhance OncoShare with patient-reported data, by developing a survey instrument in partnership with breast cancer advocates (Breast Cancer Connections in Palo Alto), and administering it to a prospective cohort of women starting therapy at Stanford and PAMF. We will use statistical tests to evaluate patterns of care in the retrospective (N=2520) and prospective (target N=320) cohorts, and to determine the impact of patient-reported information on care.
At the conclusion of this project we will: 1) deliver a detailed analysis of breast cancer care across two major California health care institutions; 2) deliver OncoShare: a highly innovative, widely reproducible methodology for integrating medical records and patients’ own reported experiences into a powerful breast cancer outcomes research tool; 3) transform the kinds of questions that can be asked and answered about breast cancer outcomes across the California and U.S. populations, and 4) adapt EHRs into a tool to measure and optimize real-world breast cancer outcomes.
Final Report (2014)
Emerging interventions are improving breast cancer survival; however, we still know very little about their impact on the "real world" of breast cancer care. We have built a highly innovative data resource, called Oncoshare, using the electronic health records (EHRs) at Stanford University Cancer Institute and Palo Alto Medical Foundation (PAMF). Our specific aims were: 1) to investigate how controversial treatments have been used across academic and community institutions; 2) to partner with patients and advocates to develop a survey about care preferences and decision-making; and 3) to administer this survey prospectively to patients, integrate their responses into Oncoshare, and identify key factors that shape treatment decisions and outcomes.
We completed Specific Aim 1, merging data sources including the EHRs and state-wide California Cancer Registry, to develop a cohort of 12,115 breast cancer patients treated at Stanford and/or PAMF from 2000- 2010. We published four articles reporting on the development of Oncoshare (2011-2012). Oncoshare now includes granular information on race/ethnicity, socioeconomic variables, tumor characteristics including stage, grade, and marker-defined subtype, treatments including mastectomy (unilateral and bilateral), chemotherapy (with detail on agents such as anthacyclines, taxanes, and trastuzumab), radiation therapy, and novel diagnostics including breast magnetic resonance imaging, positron emission tomography, genetic and genomic tests. We observed significant variability in care across patient sub-groups, and we just published this work as an original article in the journal Cancer (2013, online publication September 24).
We completed Specific Aim 2 by partnering with breast cancer survivors at Breast Cancer Connections, a community advocacy organization, to conduct focus groups about the patient experience of breast cancer care. We observed a strong emphasis on the need for more personalized care. We used these results to develop a survey on patients’ preferences and goals in breast cancer care, which we are now administering prospectively (Specific Aim 3). We have submitted four manuscripts reporting the results of Specific Aims 2 and 3.
This project resulted in a uniquely informative multidisciplinary research tool, Oncoshare. Oncoshare contains de-identified data from >15,000 California breast cancer patients diagnosed since 2000, and investigators from multiple institutions are using it to understand, and ultimately to improve, real-world breast cancer care.
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Navigating choices when applying multiple imputation in the presence of multi-level categorical interaction effects
A simple heuristic for blindfolded record linkage.
Periodical:Journal of the American Medical Informatics Association
Authors: Weber SC, Lowe H, Das A, Ferris T.
|Yr: 2012||Vol: 19||Nbr:||Abs:||Pg:e157-e161|
Breast cancer treatment across health care systems: linking electronic medical records and state registry data to enable outcomes research.
Index Medicus: Cancer
Authors: Kurian AW, Mitani A, Desai M, et al.
Chromosomal copy number alterations for risk assessment of ductal carcinoma in situ
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