Using Real-World Evidence in Healthcare Decisions
Section Editor: George Papadopoulos, BSc(Hons), GradDipEpi, MAICD Partner & Director, Lucid Health Consulting & School of Medicine, UNSW, Sydney, NSW, Australia
The articles featured in this issue’s Research Roundup look at the current state of real-world evidence (RWE). Real-world data (RWD) and RWE are playing an increasing role in healthcare decisions. The healthcare community is using these data to support coverage decisions and to develop guidelines and decision support tools for use in clinical practice, while developers of pharmaceuticals are using RWD and RWE to support clinical trial designs and observational studies to generate innovative and new treatments. We have identified 5 research papers that encapsulate these characteristics and are worth reading.
Role of Real-World Evidence for Oncology Product Registration in the United States: A Review of Approvals by the US Food and Drug Administration from 2015 to 2019
Arondekar B, Bhak R, DerSarkissian M, et al.
J Clin Oncol. 2020;38(suppl 15). doi: 10.1200/JCO.2020.38.15_suppl.e14130. Published online May 25, 2020.
There are few concrete examples of RWE used to support clinical development in regulatory filings despite growing interest in this field. This study systematically reviewed the US Food and Drug Administration’s (FDA) oncology approvals from 2015-2019 to identify cases of use of RWE that led to FDA decisions. Ninety-three approved new drug applications and biologics license applications were identified. Only 6 (6.5%) included RWE in support of efficacy, approved on or after 2017, and these data were largely retrospective studies that contextualized results to pivotal trials, with primary endpoints including overall survival, overall response rate, and time-to-treatment discontinuation. Among cases with RWE, all study designs were retrospective and 3 were database analyses, and 1 each of expanded access program, meta-analysis, and chart review analyses.
In the past 5 years, only a few FDA decisions incorporated RWE in oncology drug approvals but when utilized, RWE has been a complement rather than a supplement for clinical trial data. The key determinants for successful use of RWE in FDA decision making are early engagement, a priori protocol development, and robust research design.
Feasibility of Using Real-World Data to Replicate Clinical Trial Evidence
Bartlett Vl, Dhruva SS, Shah ND, Ryan P, Ross JS.
JAMA Netw Open. 2019;2(10):e1912869
This was a cross-sectional study of US-based clinical trials published in 2017 in the top 7 highest impact general medical journals that looked to establish how they could be feasibly replicated using observational data from insurance claims and/or electronic health records. Of the 220 trials analyzed, 33 (15.0%) could be replicated using observational data because their intervention, indication, inclusion, and exclusion criteria, and primary endpoints could be routinely ascertained from insurance claims and/or electronic health record data.
The research findings suggest the potential for observational data to complement but not completely replace clinical trials and that, although the increasing use of RWE in medical research presents opportunities to complement, supplement, or even replace some clinical trials, observational methods are not likely to obviate the need for traditional clinical trials any time soon.
Economic Evaluations Informed Exclusively by Real World Data: A Systematic Review
Parody-Rúa E, Rubio-Valera M, Guevara-Cuellar C, et al.
Int J Environ Res Public Health. 2020;17(4):1171.
A very timely and thorough systematic review via the established databases regarding the quality of full economic evaluations developed using RWD. The authors used the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist to assess the methodological quality of the studies. Their initial search identified a massive 14,011 studies, of which only 93 were included for review of their methodological quality, after an initial 593 were potentially eligible following review of title and abstract. Article selection and reasons for exclusion, mainly those studies using economic evaluation models, studies not using RWD, or those that did not perform complete economic evaluations. The most frequently assessed illnesses were neoplasms while the most evaluated interventions were pharmacological. The main source of costs and effects of RWD were information systems and the most frequent clinical outcome was survival. However, only 47% of studies met at least 80% of CHEERS criteria.
This review highlights that the use of RWD in carrying out economic evaluations with individual patient data is an increasingly common practice; however, more attention should be paid to the reporting of methodologies and results in economic evaluations. Use of the CHEERS checklist showed that there are important aspects of RWD that are not considered and that it would be valuable to have available an economic evaluation checklist that includes RWD.
Developing a Framework to Incorporate Real-World Evidence in Cancer Drug Funding Decisions: The Canadian Real-World Evidence for Value of Cancer Drugs (CanREValue) Collaboration
Chan K, Nam S, Evans W, et al.
BMJ Open 2020;10:e032884.
While the potential value of RWE is well established in oncology research, technical and methodological challenges exist in its generation and use by different stakeholders. The authors propose a framework; the CanREValue collaboration (Canadian Real-world Evidence for Value of Cancer Drugs) aims to address these challenges and establish a framework for Canadian provinces regarding the generation and use of RWE for cancer drug funding decision making. The CanREValue collaboration will focus on the generation of RWE using RWD collected from existing population-level administrative health databases. The CanREValue collaboration has established 5 formal working groups to focus on specific processes in the generation and use of RWE for cancer drug funding decisions in Canada; 1) Planning and Drug Selection; 2) Methods; 3) Data; 4) Reassessment and Uptake; 5) Engagement.
The framework can potentially enable the reassessment of cancer drugs, refinement of funding recommendations, and use of novel funding mechanisms by decision makers/payers across Canada to ensure the healthcare system is providing clinical benefits and value for money. It will be of value to follow this collaboration over its 4-year lifespan as the working groups act collaboratively to develop a working and validated framework and evaluate how it will help integrate the final RWE framework into the Canadian healthcare system.
Real-World Evidence Use in Assessments of Cancer Drugs by NICE
Bullement A, Podkonjak T, Robinson MJ, Benson E.
Int J Technol Assess Health Care. 2020;
The authors reviewed the single technology appraisals (STAs) of cancer drugs conducted by the National Institute for Health and Care Excellence (NICE) to establish how RWE has been used. The STAs published by NICE from April 2011 to October 2018 that evaluated cancer treatments were reviewed. One hundred and 13 relevant STAs were identified and analyzed, of which 96% included some form of RWE within the company-submitted cost-effectiveness analysis. The most common categories of RWE use concerned the health-related quality of life of patients (71%), costs (46%), and medical resource utilization (40%). Interestingly, while the sources of RWE were routinely criticized as part of the appraisal process, the authors identified only 2 cases where the use of RWE was overtly rejected, concluding that in the majority of cases, RWE was accepted in cancer drug submissions to NICE. The key criticisms of RWE in submissions to NICE were typically concerned with specific data sources or analytical methods and the applicability of these to the decision problem.
The use of RWE in NICE submissions of cancer drugs was found to be extensive, and in general appeared to have provided a valuable source of information to aid the decision making. The recommendation is that submissions to NICE should aim to proactively acknowledge the common criticisms leveled at inclusion of RWE through clear justification of the approaches taken to analyze RWE and the relevance of the RWD source. •