How we think about carrying evidence across country borders→
Can the experience of US patients tell a reliable story applicable to patients from other countries?
The articles and videos in this section cover the fundamentals of using real-world data (RWD) — where it comes from, how it is curated, processed and ultimately adopted for use by life science companies, regulators and other decision-making bodies throughout the oncology drug development lifecycle.
Realizing the promise of real-world data requires alignment and consensus across many fronts, including the vocabulary of this emerging field.
Flatiron team members discuss the evolving role of machine learning and natural language processing (NLP) in real-world evidence along with appropriate applications for these technologies. Learn more about machine learning and AI.
Discover how real-world endpoints are enabling new approaches and how Flatiron is partnering with regulatory and industry stakeholders to develop and evaluate them. Learn about how real-world endpoints are derived in oncology
Chana Weinstock, MD, of the FDA discusses the use of real-world evidence in oncology drug approvals, the role of external control arms and how COVID-19 is impacting regulatory decision making. Watch her talk now.
RWE is becoming a critical component of Health Technology Appraisals (HTAs) worldwide, particularly in oncology. However, questions remain about how it can be used effectively to support market access.
Looking beyond real-world evidence, what does the future of evidence generation look like? Experts discuss the concept of integrated evidence and how it will power smarter care for every patient.
Real-world evidence (RWE) is being increasingly used by life science companies to accelerate oncology R&D, help inform clinical trial design, fulfill post-marketing requirements and more. This collection of research, videos, case studies and more help to illustrate how your peers are adopting RWE.
Clinical trials can provide the most definitive and robust evidence for efficacy and safety. In 2021, the average oncology phase 3 study costs nearly 250 million dollars and takes more than 3 years to read out. Today, RWD is helping to improve trial designs decisions and accelerate drug development timelines. Read this collection to learn how researchers are using RWD to predict control arm performance, establish protocols according to the latest standards of care and more.
Overall survival is a key endpoint in clinical trials. But when using RWD, how is missing data addressed?
This exploratory study assessed whether EHR-derived patient cohorts can emulate the control arms of published clinical trials that supported FDA approvals of anticancer therapies across multiple tumor types.
Real-world data is curated to track novel therapies in real-time, when registries may lag for years. This makes it possible to anticipate and design trials based on actual current outcomes.
Combining real-world data to genomic datasets enables discovery of new prognostic biomarkers, and provides clinical evidence within unique populations needed for trial design.
In this episode, we examine racial and ethnic disparities through the lens of oncology, real-world data and health policy.
This article provides Flatiron research partners with a general overview of some of the common forms of statistical bias that can arise when working with RWD.
This study ultimately provided evidence that the frequency of imaging assessments to detect disease progression can differ by treatment type in real-world patients with cancer and researchers should remain cognizant of the potential influence of surveillance bias when working with RWD.
With rapid advancements and improved access to broad-based genomic sequencing, there is a growing volume of data that can provide researchers with a unique opportunity to tease out novel resistance mechanisms, co-mutations or other genomic drivers for outcomes. Pairing this genomic data with clinically deep, longitudinal clinical data allows researchers to make the critical connection between a genomic profile and patient outcomes. See how researchers are using RWD to support the development of novel targeted therapies in the age of precision oncology.
This talk is part of the ResearchX session: The role of real-world data in tumor-agnostic drug development.
Combining RWD to genomic datasets can leverage the discovery of associations between different mutations. This study evaluated the prognosis of co-occurring STK11 and KEAP1 mutations in lung cancer.
RWD, and especially those linked to genomics and real-world outcomes information, can help to accelerate and de-risk drug development pipelines. See how.
This article reviews some of the basic considerations and caveats when building biomarker positive and/or negative cohorts with Flatiron RWD.
This study found that patients with RAS amplification without RAS mutations have poor outcomes on EGFRmAb.
Real-world evidence generated from electronic health records has been shown to be more relevant, timely, and representative for health technology assessments (HTA) compared to evidence from clinical trials. Longitudinal EHR data is uniquely positioned to answer effectiveness questions that are core to HTA decision making. Explore how real-world data are being used for HTA & Market Access, including what the National Institute for Health and Care Excellence (NICE) considers the role of EHR-derived RWE for HTA decision-making to be.
US-generated RWE for HTA use cases requires stakeholders to think carefully about their target population and whether that population is represented in the data. Our framework intends to help with that process.
How does calendar-time consideration play out in HTA-related comparative effectiveness studies? Take a journey to the fictional country of Zamunda to find out.
Dr. Pall Jonsson from NICE presents research as part of the three-year research collaboration between Flatiron and NICE.
In this case study, investigators from Flatiron Health and NICE focused on an immunotherapy drug in advanced lung cancer to see if RWD could have been used to address uncertainty regarding long-term survival.
In this video, Dr. Scott Ramsey discusses the current evidence gaps in HTAs and how real-world data can address those gaps and Dr. Dominik Heinzmann walks attendees through a practical use case of RWE for HTAs.
By considering the strengths and limitations of an optimized and realized population, we establish how EHR data can be used to identify appropriate populations for indirect treatment comparisons when assessing the benefit of a new medicine.
In this session, use cases demonstrating the value of using RWE in the HTA setting were showcased as well as a discussion on the role of RWE with NICE.
As FDA works to strike a balance between accelerated cancer therapy approvals and ensuring patient safety from unrecognized adverse events, life science companies are quickly incurring regulatory debt by way of post marketing requirements and commitments (PMRs/PMCs). This collection shows how real-world data can be utilized to fulfill PMRs and PMCs by seeing how approved therapies are affecting patients who were not eligible to participate in the pivotal studies due to demographics or comorbidities.
Real-world data linked to a genomic dataset can further inform us whether clinical outcomes in rare subtypes are similar in the real-world compared to within clinical trials.
RWE can inform us whether clinical outcomes after FDA approval are similar in the real-world compared to within clinical trials. This study looks at PDL1 outcomes after 1 year post-approval.
EHR derived data can evaluate patient populations that may be excluded within a clinical trial setting. This study assessed the use of immunotherapy among patients with organ dysfunction
Perhaps the most commonly performed time-to-event analysis on Flatiron’s RWD is overall survival (OS) analysis.This article provides conceptual instruction on OS analysis and guidance for how real-world OS should be estimated using Flatiron data.
As much as 71% of adult cancer patients are reported to have received at least one off-label treatment. This presents a ripe opportunity for life science organizations to look at real-world data to understand how their therapies are being used in routine clinical care. Unlike claims-based RWD which may not show a complete picture due to potential issues with off-label reimbursement, RWD derived from the electronic health record provides a window into off-label use.
This talk is part of the ResearchX session: Applying RWE to Regulatory Applications.
Real-world data can evaluate clinical outcomes of patients who were excluded in trials due to organ dysfunction, which enhances our safety data, and can lead to label expansion.
Real-world data makes it possible to evaluate treatment outcomes of patients that were initially excluded in clinical trials. This study expanded use of palbociclib in male breast cancer patients.
Given its longitudinal nature, Flatiron RWD is often used for various types of time-to-event analyses, including treatment discontinuation. This article provides conceptual instruction on time to treatment discontinuation (TTD) analysis and guidance for how real-world TTD should be estimated using Flatiron data.
Inequities in cancer care and outcomes are a major societal challenge, adversely affecting groups of people who have systematically experienced greater obstacles to health based on characteristics historically linked to discrimination or exclusion, including racial or ethnic group, religion, socioeconomic status, and gender. Real-world data has proven to be a critical tool to evaluate care patterns and health outcomes and ultimately help to shape health policy and promote health equity.
In this episode, we examine racial and ethnic disparities through the lens of oncology, real-world data and health policy
Racial disparities in healthcare delivery and outcomes are a major societal concern. This study sought to look at racial differences in treatment beyond 1L for patients with breast cancer.
This study investigated potential racial disparities in in-person and telemedicine visits during the pandemic for patients with documented active treatment for hematologic malignancies.
Researchers aimed to describe racial and age-related differences in the impact of high-risk cytogenetic abnormalities (HRCAs) on survival in multiple myeloma
This study, which was originally accepted as a 2019 ASCO Plenary Session, found that state Medicaid expansions were associated with a reduction in the Black-White racial disparity in timely treatment of patients diagnosed with advanced cancers.
Researchers from Flatiron Health looked to develop a natural language processing-based approach to detect transgender and GNC patients based on patient charts within a real-world dataset.
As real-world data and real-world evidence continue to grow in adoption, the scientific community has increasingly discussed regulatory success and learnings, methodological considerations, data quality and endpoint validation. Explore events where RWE is on the agenda and join the conversation.