Harnessing Real-World Evidence to Advance Cancer Research

Abstract

Randomized controlled trials (RCTs) form a cornerstone of oncology research by generating evidence about the efficacy of therapies in selected patient populations. However, their implementation is often resource- and cost-intensive, and their generalisability to patients treated in routine practice may be limited. Real-world evidence leverages data collected about patients receiving clinical care in routine practice outside of clinical trial settings and provides opportunities to identify and address gaps in clinical trial evidence. This review outlines the strengths and limitations of real-world and RCT evidence and proposes a framework for the complementary use of the two bodies of evidence to advance cancer research. There are challenges to the implementation of real-world research in oncology, including heterogeneity of data sources, timely access to high-quality data, and concerns about the quality of methods leveraging real-world data, particularly causal inference. Improved understanding of the strengths and limitations of real-world data and ongoing efforts to optimise the conduct of real-world evidence research will improve its reliability, understanding and acceptance, and enable the full potential of real-world evidence to be realised in oncology practice.

Real‐world treatment patterns for palbociclib plus an aromatase inhibitor, or an aromatase inhibitor alone, for patients with metastatic breast cancer in the Flatiron Database

“…Importantly, real-world studies can help us understand treatment patterns and clinical effectiveness or safety in a heterogeneous population in routine clinical practice, which can be informative for clinical treatment decisions. [9][10][11][12] In the case of palbociclib, real-world data added support to the clinical data in male breast cancer patients for a label expansion in 2019 to include men with HR+/HER2À mBC. [13][14][15] Over 8 years of postapproval real-world patient experience and more than 665 000 patients prescribed palbociclib globally (including nearly 173 000 in the US as of June 2020) make it possible to study comparative effectiveness in a large and diverse population of patients with HR+/HER2À mBC within the US.…”

“…Controlled clinical trials can limit the clinical and demographic characteristics of patients who are studied due to strict inclusion and exclusion criteria and as a result may have limited patients with worse Eastern Cooperative Oncology Group (ECOG) performance status, multiple comorbidities, or who are elderly or frail. Importantly, real‐world studies can help us understand treatment patterns and clinical effectiveness or safety in a heterogeneous population in routine clinical practice, which can be informative for clinical treatment decisions 9‐12 . In the case of palbociclib, real‐world data added support to the clinical data in male breast cancer patients for a label expansion in 2019 to include men with HR+/HER2− mBC 13‐15 .…”

Cancer survivor late-effects, chronic health problems after cancer treatment: what’s the evidence from population and registry data and where are the gaps?

“…This impacts the external validity of results [40,41]. Population and cohort studies can be useful for insights into rare cancers and exploring cancer treatment efficacy beyond clinical trials [42,43▪], providing real-world outcomes beyond that of the short time frame of clinical trials and highlighting long term and late effects of cancer treatment. Studies that included PROs increase the quality of information and measure the personal impact of symptoms on survivors HRQOL rather than what is documented in routine clinical records [44].…”

Big data and RCT's in surgical oncology: Impact on improving hepatopancreatobiliary cancer surgical care on the global stage

“…To overcome the pitfalls of surgical RCTs, there has been a growing interest in alternative research methodologies, such as the use of large database studies, or big data analytics 11,12 . Large‐scale data obtained from health records, cancer registries, image libraries, wearable technology, patient portals, and multiple other sources has the potential to unlock important insights into surgical treatments of cancer and their outcomes that are difficult to be tested or are incompletely answered by RCTs 12,13 . This “Real world data” enables the assessment of interventions as observed in a real‐life environment as opposed to the controlled environment of a trial.…”

“…11,12 Large-scale data obtained from health records, cancer registries, image libraries, wearable technology, patient portals, and multiple other sources has the potential to unlock important insights into surgical treatments of cancer and their outcomes that are difficult to be tested or are incompletely answered by RCTs. 12,13 This "Real world data" enables the assessment of interventions as observed in a real-life environment as opposed to the controlled environment of a trial. Moreover, big data can generate answers to questions much faster contrary to RCTs.…”