May 25, 2021

In 2016, the 21st Century Cures Act (Cures Act)  directed the Food and Drug Administration (FDA) to accept statistical methods that include Real-World Data (RWD) and Real-World Evidence (RWE). The next year, the Center for Devices and Radiological Health (CDRH) and Center for Biologics Evaluation and Research (CBER) issued guidance regarding the submission of RWD and RWE to the FDA.

The Role of RWD and RWE

Both RWD and RWE have important roles as defined by the legislation to:

1. Monitor post-market safety and adverse events that result in regulatory decisions

2. Expedite approval of innovative therapeutic approaches, RWD and RWE support clinical trial designs, including approval of new indications for approved drugs

3. Develop therapeutic guidelines and decision support tools for clinical practice

4. Support healthcare insurance coverage decisions

Sources of RWD

RWD may come from various government and commercial sources including:

• Electronic health records
• Claims databases
• Billings databases
• Registries: product and disease
• Patient-generated data
• Health status data from mobile devices

To mitigate potential bias, the use of RWD requires a careful study design, protocol, and analysis plan that is comparable to a more traditional investigation, like a randomized controlled clinical trial, with strict inclusion/exclusion criteria and clinical endpoints.

Control Arms 

There are some challenges with prospective, randomized, controlled clinical trials. Two major drawbacks:

1. Large numbers of patients are required to conduct the study

2. Slow patient accrual; strict patient eligibility

Study needs, research ideas and business strategy including synthetic control arms, also known as historical control arms or external control arms, are important to consider. 

This type of control arm is defined as a group of patients treated at an earlier time (historical control) or a group treated during the same time period, in another setting. 

Emergence of RWD and RWE provides new opportunities to efficiently conduct large-scale studies that have many of the benefits of randomized controlled clinical trials, while being generalizable to broad populations. 

Discovering and analyzing RWD provides information regarding the clinical outcomes associated with a therapeutic approach. These outcomes, from a wide range of study designs, generate RWE.

When RWE is submitted to the FDA, both the RWD and RWE must conform to recognized data standards for file formats and data structures, using standardized variables and definitions.

Advantages and Outcomes

Historical or external control arms overcome many barriers to the completion of clinical trials, and provide a representative, rather than a highly selected, patient population in randomized controlled trials. 

In cancer trials, there are many advantages including patient access to therapeutic breakthroughs. 

Watch this video to learn more about this important topic

Medical paradigms are changing. Inefficiencies when conducting clinical trials are being addressed. Therapeutics are no longer siloed by medical subspecialty. Long recognized risks for development of disease are better understood by interconnecting biological pathways.

Outcomes are more than survival; they now also reflect the importance of controlling symptoms of disease and treatment. Greater emphasis is placed on outcomes beyond the clinical trial and in real world populations. Outcomes within real-world experiences reflect both the personal and societal cost of disease.

References

Berger T, Rozovski U, Moshe Y, et.al. Midostaurin in combination with intensive chemotherapy is safe and associated with improved remission rates and higher transplantation rates in first remission – a multi-center historical control study.  Ann Hematol. 2019; 98:2711-7.

Center for Devices and Radiological Health (CDRH) 2016-2017 Strategic/Priorities/Accomplishments.

DiMasi JA, Grabowski HG, Hansen RW. The cost of drug development.  [Correspondence] N Engl J Med. May 14, 2015

Dowden H, Munro J. Trends in clinical success rates and therapeutic focus. 2019.

Edelmann D, Habermehl C, Schlenk RF, et al. Adjusting Simon’s optimal two-stage design for heterogeneous populations based on stratification or using historical controls. Biom J. 2020;62:311-29.  

Fogel DB. Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: A review. Contemp Clin Trial Communication. 2018;11:156-64.

Huss R. The High Price Of Failed Clinical Trials: Time To Rethink The Model. 2019. 

Makady A, deBoer A, Hillege H, et. al. What is real-world data? A review of definitions based on literature and stakeholder interviews. Value Health. 2017;20:858-865.

Shadman M, Maloney DG, Storer B, et.al. Rituximab-based allogeneic transplant for chronic lymphocytic leukemia with comparison to historical experience. Bone Marrow Transplant. 2020;55:172-81. 

Shah AN, Flaum L, Helenowski I, et. al. Phase II study of pembrolizumab and capecitabine for triple negative and hormone receptor-positive HER2-negative endocrine-refractory metastatic breast cancer. J ImmunoTherapy Cancer. 2020;8:e000173. doi:10.1136/jitc-2019-000173. 

Span P. The clinical trial is open. The elderly need not apply. N.Y. Times. April 13, 2018.

U.S. Food and Drug Administration. Balancing Premarket and Postmarket Data Collection for Devices Subject to Premarket Approval.

U.S. Food and Drug Administration.  Real-world evidence: Real-world data (RWD) and real-world evidence (RWE) are playing an increasing role in health care decisions.  

U.S. Food and Drug Administration, Center for Devices and Radiological Health, Center for Biologics Evaluation and Research. Use of Real-World Evidence to support regulatory decision-making for medical devices. Guidance for industry and Food and Drug Administration Staff. August 31, 2017.  

William Jr WN, Tsao AS, Feng L, et. al. Single arm, Phase II study of cisplatin, docetaxel, and erlotinib in patients with recurrent and/or metastatic head and neck squamous cell carcinomas. Oncologist. 2018;23:526-e49. 

Wong CH, Siah K. Estimation of clinical trial success rates and related parameters. Biostatistics. 2019;20:273-86. 

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