Clinical trial versus real-world data: the fundamentals

Written by The Evidence Base

We evaluate clinical trial and real-world data, assessing some of their comparative benefits, challenges and appropriateness for use in healthcare decision-making.

The term ‘gold standard’ has scarcely been used as an adjective for anything more than it has for traditional, randomized controlled trial data in the context of primary regulatory approval and regulatory decision-making. Increasingly, however, calls have been made for guidance on when and how real-world data may be considered in healthcare decision-making. In this article, we will explore the ‘what’, ‘how’s and ‘when’s of both clinical trial and real-world data and evidence, to determine their comparative benefits, challenges and appropriateness for use in healthcare decision making.


Clinical trials

Clinical trial data are generated by pre-defining a very specific study population, a protocol that must be stringently adhered to and measurable, quantifiable outcomes.

These trials often seek to demonstrate absolute effectiveness of a therapeutic intervention for a specified indication, in a specified patient population. There are multiple stages of clinical trials: traditionally, Phase I trials seek to determine product safety, Phase II investigations to demonstrate toxicity and tolerability in small patient populations and Phase III trials to determine safety, toxicity and tolerability in much larger, more representative, study cohorts.

Whilst effective, necessary and of rigorous methodologies, there are various challenges and limitations associated with conducting clinical trials. Some challenges apply in all instances and others pertain to certain disease indications more specifically.

For example, the conduct of a clinical trial carries with it enormous time and financial costs. There may also be instances when, such as if one is investigating a rare disease, the number of eligible patients required and available for recruitment and participation in a trial simply do not align [1].

Further, due to the strict inclusion, exclusion and protocol requirements of many clinical trials, they may be deemed to be poorly reflective of real-world conditions and individuals, who may have multiple co-morbidities, not adhere to their regimens as prescribed or simply be unable to physically participate in a trial, due to geographical location.

Enter…


Real-world data sources

Read-world data are, by definition, data collected outside of the context of traditional clinical trials. These data are reflective of real-world people, environments and conditions.

Real-world data can be obtained from several data sources associated with outcomes in heterogeneous patient populations, such as electronic health records and national registries. Real-world data can also be generated from patient-reported outcomes and app-based questionnaires, such as through analysis of data obtained from mobile devices, wearables and patient surveys.

The quality of real-world data, its data sources and the subsequent real-world evidence generated have been significant barriers to payers’ and regulators’ consideration and use of these data in drug development and approval processes.

In an interview with The Evidence Base®, Nancy Dreyer (IQVIA; NC, USA) commented: “[Randomized controlled trials] are considered the gold standard for evaluating whether a medical treatment can work, but not whether the treatment does work for diverse patients in real-world situations.”

However, Dreyer cautioned: “Real-world data, from which [real-world evidence] is derived, are everywhere and are often not specifically created for health research purposes. Understanding the data you want to use — how and why those data were created — and whether the patients and events of interest are likely to be recorded, is not always straightforward. Careful attention is required to study design and analysis. It is essential to ensure appropriate comparisons are made, including determining appropriate eligibility criteria, conducting relevant analyses and drawing justified interpretations.”


Study designs: real world versus really clinical

Randomized controlled trials are forms of interventional research: their designs are prospective and assign patients, randomly, to two (or more) groups, one of which will receive the intervention being studied, with the other receiving either another intervention (usually the current standard of care), a placebo or no intervention at all — this is the control group.

There are a variety of real-world evidence study designs; these may be purely observational, or interventional — prospective, retrospective, longitudinal, employ matching and more. Common amongst all real-world evidence studies is the large size of the study population, to allow for the generalizability of results to wider patient populations and a study cohort that is representative of a wide patient demographic in the first instance.

The differing natures and designs of real-world and randomized controlled studies mean that they are inherently primed to determine different qualities, for example:

  • clinical trials assess efficacy; real-world evidence studies assess effectiveness
  • clinical trials are conducted in experimental settings; real-world evidence studies are conducted in real-world settings
  • clinical trails assess homogenous, highly specific patient populations; real-world evidence studies assess heterogenous, representative patient populations [1]

Relevance to regulatory decision-making

Regulatory decisions concerning therapeutic products can be made at various stage during the clinical pipeline: pre-marketing, throughout the approval process, all the way up to post-marketing and label expansion.

Traditionally, the evidence required to support product approval applications and regulatory decisions has solely taken the form of randomized clinical trial data. Increasingly, however, calls for guidance on when and how real-world evidence may be incorporated and considered in these processes have been made.

In our recent editorial ‘in focus’ feature, we explored the current and future states of utilizing real-world evidence in regulatory decision making.

The 21st Century Cures Act

The 21st Century Cures Act was passed in 2016 in the USA; this act intended to promote more rapid development of drugs and biologics by modifying the US FDA drug approvals process and allowing companies to incorporate real-world evidence, patient input and claims data into their drug approval applications, rather than clinical trial data only. The Act also set in place the infrastructure and requirement for the FDA to develop a framework and guidance for evaluating RWE in approving therapeutic products.

A pragmatic clinical trial — the case of INVEGA SUSTENNA®

In January 2018, the conduct of real-world, open-label, pragmatic clinical trial resulted in the label expansion of INVEGA SUSTENNA® (paliperidone palmitate) to include individuals with schizophrenia [3].

As this trial was conducted in real-world clinical practice settings, relaxed participation criteria were defined, to all for higher risk individuals to be included in the study.

This investigation was significant as it represented the first instance of the FDA approving a label expansion based solely on real-world evidence from a pragmatic clinical trial.

Historical real-world evidence to complement clinical trial data: the case of BAVENCIO®

In May 2019, the US FDA approved Bavencio® (avelumab), in combination with INLYTA® (axitinib), as a first-line treatment for individuals with metastatic Merkel cell carcinoma [3].

In an interview with The Evidence Base, Murtuza Bharmal (Merck KGaA; Darmstadt, Germany) stated: “Before the approval of avelumab, there existed no standard of care [for metastatic Merkel cell carcinoma]. Conducting a traditional randomized controlled study was ethically challenging and not feasible from an operational perspective.”

Approval of Bavencio for this indication resulted from findings from a singlearm, openlabel, Phase II study, in which electronic health record data were utilized to characterize the natural history of the disease and effectiveness of the therapeutic strategy.

“The [real-world evidence] enabled the regulatory authorities to put the efficacy of avelumab, as measured in the single-arm trials, into context, like a historic control arm,” stated Bharmal.

Label expansion: IBRANCE® — the unassuming game changer

In April 2019, the US FDA approved a supplemental New Drug Application from Pfizer (NY, USA) to expand the use of IBRANCE®, in combination with an aromatase inhibitor or fulvestrant, to include men with hormone receptor-positive, HER2-negative, advanced or metastatic breast cancer.

Commenting on this approval, Bret Miller, Founder of the Male Breast Cancer Coalition, stated: “Men with breast cancer have limited treatment options, making access to medicines such as Ibrance critically important. We applaud the use of real-world data, a new approach to drug review, to make Ibrance available to certain men with metastatic breast cancer and help address an unmet need for these patients.”

This approval was especially significant as it means that Ibrance now represents the first and only CDK4/6 inhibitor indicated in combination with an aromatase inhibitor for the first-line treatment of men with hormone receptor-positive, HER2- metastatic breast cancer in the USA.

Discover more on these topics in our dedicated ‘in focus’ feature or real-world evidence channel>>


References:

[1] Wu J, Wang C, Toh S, Pisa FE, Bauer L. Use of real-world evidence in regulatory decisions for rare diseases in the United States-Current status and future directions. Pharmacoepidemiol Drug Saf. doi: 10.1002/pds.4962 (2020) (Epub ahead of print);

[2] Kim H-S, Lee S, Kim JH. Real-world evidence versus randomized controlled trial: clinical research based on electronic medical records. J Korean Med Sci. 33(34): e213; (2018);

[3] Baumfeld AE, Reynolds R, Caubel P, Azoulay L, Dreyer NA. Trial designs using real-world data: the changing landscape of the regulatory approval process. Pharmacoepidemiol Drug Saf. doi: 10.1002/pds.4932 (2019) (Epub ahead of print).