New research powered by CancerLinQ Discovery® de-identified data sets that is being presented at the 2021 ASCO® Quality Care Symposium (QCS) identified factors that predict the likelihood of short-term mortality for patients with metastatic breast cancer; highlighted important demographic and clinical differences between patients with breast cancer typically considered to be candidates for clinical trials and those seen in routine clinical practice; and characterized the use of telehealth for end-of-life cancer care during the pandemic.
“CancerLinQ® has been growing its capabilities in the collection and analysis of real-world data,” said CancerLinQ LLC CEO Sean Khozin, MD, MPH. “We are very proud of our efforts to advance cancer care quality and research by focusing on the experience and outcomes of patients with cancer at the point of routine care across the U.S. and supporting analytical solutions that can provide deeper insights into variations in treatment response, inequities in access to care, and other clinically relevant questions that cannot be addressed in traditional clinical trials.”
The three studies being presented at QCS are:
- “Development of a breast cancer-specific prognostic tool using CancerLinQ Discovery” by Emily Miller Ray, MD, et al., which used an electronic health record (EHR) data set from CancerLinQ Discovery to help identify patients with metastatic breast cancer at high risk of short-term mortality. The authors found that certain demographic and clinical variables can be used to predict the risk of death within 30 days of a clinical encounter for these patients.
- This abstract (#275) will be featured at Poster Session B: Patient Experience; Quality, Safety, and Implementation Science; Technology and Innovation in Quality of Care on Sept. 25 from 7–7:55 a.m. and 11:55 a.m.–1:25 p.m. (ET) in Back Bay Hall, 3rd Floor.
- “Survival in the real world: A national analysis of patients treated for early-stage breast cancer” by Jeffrey Franks, MSPH, et al., is a retrospective cohort study that used a CancerLinQ Discovery data set of women diagnosed with early-stage (I-III) breast cancer between 2005–2015. The analysis showed that more than half of patients in this dataset would be considered underrepresented or unrepresented in clinical trials due to age, comorbidity, or race/ethnicity. The authors note that the findings serve as a reminder for researchers to ensure clinical trial participants reflect the real-world disease population to support evidence-based decision making for all individuals with cancer.
- This abstract (#75) will be featured at the general session “Eliminating Barriers to Clinical Trial Access” on Sept. 24 from 4:20 – 5:20 p.m. (ET) in Grand Ballroom, Salon F, 4th Floor.
- “Care at the end of life during the COVID-19 pandemic: A CancerLinQ Discovery (CLQD) analysis” by Gabrielle Betty Rocque, MD, et al., which used data from CancerLinQ Discovery of patients seen in oncology practices and cancer centers in the U.S. between January 2019 and September 2020, found that during the COVID-19 pandemic, telehealth use was limited at end of life compared to other stages of care.
- This abstract (#310) will be featured at Poster Session B on Sept. 25 from 7–7:55 a.m. and 11:55 a.m.–1:25 p.m. (ET) in Back Bay Hall, 3rd Floor (poster board #E10).
CancerLinQ® is a real-world oncology data platform developed by ASCO that collects and aggregates longitudinal EHR data from oncology practices throughout the United States. CancerLinQ improves the quality of patient care and accelerates discovery by securely compiling, harmonizing, analyzing, and de-identifying vast amounts of information on patient characteristics (e.g., molecular profiles, comorbidities), treatments, and long-term side effects. By using data from over five million patients in near real time, CancerLinQ can identify trends and associations between myriad variables, thereby enabling physicians to generate new hypotheses and apply those conclusions to improve care in real-world settings.
About CancerLinQ Discovery
CancerLinQ Discovery®, which was rolled out in November 2016, offers de-identified data sets derived from the vast pool of real-world electronic health record data contributed by participating practices across the U.S. to the CancerLinQ® database. These curated data sets are used by academic researchers, government agencies, major cancer centers, and others in the oncology community to generate practical knowledge that improves cancer care, as well new hypotheses for clinical research.