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Optimising real-world studies

A recent editorial published in Translational Breast Cancer Research has summarised the concept of real-world studies (RWS) and the opportunities in ensuring high-quality evidence.

From RCTs to RWS

Non-communicable diseases, such as cancer, account for 71% of all global deaths. Randomised controlled trials (RCTs) have been critical in providing medical evidence. However, their extensive costs and uncertain external validity have become a significant concern. As a result, in the past decade, attention has shifted to RWS. RWS are more economically feasible and possess greater external validity than RCTs. Within the editorial, the authors discuss and clarify definitions relevant to RWS, highlight the opportunities that RWS bring and suggest ways to ensure high-quality evidence.

Defining real-world studies

The concept of ‘real world’ has been around for over 50 years; however, it only began to receive significant attention two decades ago. According to the FDA:

  • RWS are a study design that include, but are not limited to, randomised and non-randomised trials as well as observational studies.
  • Real-world data (RWD) relates to patient health status and/or the delivery of healthcare from a variety of sources such as electronic health records.
  • Real-world evidence (RWE) refers to clinical evidence about the usage and potential benefits/risks of a medical product obtained from RWD analysis.

RCTs are commonly thought to not reflect real-world settings. However, the authors express that this is not the case and they can in fact include real-world settings, such as observational studies. Therefore, it is not appropriate to completely separate RCTs from RWS.

Opportunities of real-world studies

RWS can be used for post market surveillance:

  • They can act as a confirmation study to further confirm the efficacy and safety of approved interventions based on pivotal RCTs.
  • RWS have the ability to replicate clinical trials.
  • With large sample sizes, RWS can provide sufficient statistical power to investigate the long-term impact of rare or suboptimal outcomes in pivotal RCTs. This includes adverse effects and quality of life.

RWS also allow researchers, healthcare professionals and stakeholders to investigate the effectiveness of interventions in clinical practice. This includes within under-represented subgroups. Research could also be extended in different geographic or economic contexts to verify the effectiveness of interventions within different populations.

RWS make conducting longitudinal studies of patients’ cancer experiences more feasible. Investigations can examine different time points along the treatment pathway or across the cancer continuum. The large quantity of these linked datasets could help answer a wide range of key research questions. 

Ensuring high-quality evidence

While RWS provide considerable research opportunities, their role in decision-making is still controversial. The nature of RWS preclude them from having the same rigorous study design and methodology as RCTs. In other words, they do not have the same accuracy that can ensure enhancement of internal validity. As a result, the strength of evidence from RWS according to the editorial has become a primary concern.

Ensuring high quality of evidence from RWS is critical. The authors emphasise that quality control, proper methodology design and good reporting are important when conducting valid RWS.

They suggest that prospective data collection of RWE should be vital to preserve internal validity. The researchers suggest that vigilance, and administrative, financial and technical support are key in assuring data quality. They propose that potential biases caused by confounding factors during RWS could be mitigated through logic-based approaches, e.g. using pragmatic clinical trials. They suggest that these can augment internal and external validity, and better ensure generalisability.

In terms of reporting, the researchers recommend that future RWS comply with established principles from relevant guidelines. These include GRADE guidelines, the STROBE statement, the extension of the CONSORT statement and more relevant guidelines on the EQUATOR network. They urge that more studies need to investigate the quality of published RWS as well as studies educating key players on how to comply with quality design, methodology and reporting guidelines/statements.

Concluding thoughts

In summary, researchers use RWD to conduct RWS in real-world scenarios. RWS provide opportunities for optimising clinical evidence generation and verification. To help increase the strength of evidence from RWS, it is important to ensure reliable data quality, proper research design and methodology, and standardised reporting.

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