RWE: Need to Know, Nice to Know

January 20, 2023

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Many well-known terms have a particular meaning when applied to real-world evidence studies. To clear up any possible confusion, we’ve defined seven core concepts. For those interested in more depth and detail, we also recommend some key readings.

RWE Definitions

1. Real-world data¹
Real-world data (RWD) refers to data on health outcomes that is collected from a variety of sources outside the clinical trial setting, such as health records, registries, and patient support programs.

2. Real-world evidence^1,2
Real-world evidence (RWE) describes evidence about the appropriate use and potential benefits of a medical intervention, based on analysis of data generated in a real-world setting.

3. Bias^3,5
In RWE studies, bias refers to flaws in the design or execution of the study that may lead to a deviation from “true” or “accurate” results. Examples of bias include selection bias, which occurs when the study subjects don’t represent the target population, and missing data. Another category of bias, called publication bias, occurs when the findings of a study affect the likelihood that the study will be published.

4. Data provenance^4,6
The term denotes the process of tracing the source of the data and documenting how the data has been altered throughout its lifecycle. This process can help establish the trustworthiness and reliability of a data source. Considerations in data provenance also include data collection, coverage, and governance.

5. Data governance⁶
Data governance comprises the policies and procedures used to ensure the data input is accurate and the data is appropriately stored, manipulated, accessed, and deleted.

6. Trust^4,7
As pertaining to data, trust (or trustworthiness) alludes to the overall integrity of the data, as well as the ability to validate it. The growing interest in RWD has created an urgency to develop processes that promote trust in the data.

7. Transparency⁸
Transparency signifies open and accurate communication of RWE research processes (including research questions, data source, data provenance, methods, designs, endpoints, and analyses) throughout the course of an RWE investigation.

RWE Must-reads

INESSS State of Knowledge Report: integration of real-word data and evidence to support decision making in the pharmaceutical sector⁹

· Publication date: January 2022

· Why it is important: The document focuses on the methodology for appraising and implementing RWE in the pharmaceutical sector.

· Of note: CADTH leveraged this document in the development of its RWE reporting guidance.

NICE real-world evidence framework⁴

· Publication date: June 2022

· Why it is important: The document goes beyond research and provides guidance for RWE submissions, including when to use RWE.

· Of note: Shortly after the publication of this document, CADTH cited it in its HTA recommendation for nusinersen (SPINRAZA).¹⁰

CADTH Canadian real-world evidence reporting guidance¹¹

· Publication date: November 2022 (draft); final document to be published in spring 2023, following a consultation period ending in January 2023.

· Why it is important: This highly anticipated pan-Canadian document, currently in draft form, highlights best practices and methodology for submitting RWE to regulatory and HTA bodies.

· Of note: The question of when to generate RWE falls outside the scope of the document. CADTH plans to address this question in future guidance on the implementation and incorporation of RWE in decision making.

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References

1. Real-world evidence: a primer. CADTH. Dec. 10, 2022. https://www.cadth.ca/real-world-evidence-primer

2. Framework for FDA’s real-world evidence program. December 2018. https://www.fda.gov/media/120060/download

3. NICE glossary, letter B. 2022. https://www.nice.org.uk/Glossary?letter=B

4. NICE real-world evidence framework. June 23, 2022. https://www.nice.org.uk/corporate/ecd9/resources/nice-realworld-evidence-framework-pdf-1124020816837

5. Categories of bias. CEBM & University of Oxford. https://catalogofbias.org/biases/publication-bias/

6. NICE glossary, letter D. 2022. https://www.nice.org.uk/Glossary?letter=D

7. Kraut J et al. Realizing RWE’s potential. Flatiron. January 25, 2021. https://flatiron.com/blog/realizing-rwes-potential-reproducibility-transparency-and-the-future-of-rwd-analyses/

8. Orsini LS et al. ISPOR report. Value Health 2020; 23:1128.

9. Integration of real-world data and evidence to support decision-making in the pharmaceutical sector. INESSS. January 2022. https://www.inesss.qc.ca/fileadmin/doc/INESSS/Rapports/Medicaments/INESSS_Real_world_data_SK.pdf

10. CADTH reimbursement recommendation. Nusinersen (Spinraza). August 2022. https://www.cadth.ca/sites/default/files/DRR/2022/SR0713-Spinraza-Reassessment.pdf

11. RWE guidance document (draft). CADTH. November 2022. https://www.cadth.ca/sites/default/files/RWE/pdf/RWE%20Reprting%20Guidance%20-%20Draft%20for%20Consultation.pdf