The Analysis Group, which specializes in health economics and outcomes research, as well as regulatory epidemiology, has published a study that replaced the US Food and Drug Administration (FDA) comment on the use of real-world evidence (RWE) in successful approvals of oncological Products examined between 2015 and 2020. The group says the analysis, published in Clinical cancer research, is the first of its kind to systematically aggregate detailed regulatory feedback to give drug developers practical insights.
While existing FDA guidelines provide a theoretical framework for conducting regulatory RWE studies, the details of the actual design and analysis of appropriate real studies are largely ignored. To address this critical knowledge gap for drug developers, a team of researchers from the Analysis Group, Pfizer, and the Dana-Farber Cancer Institute analyzed 133 original and 573 supplemental approvals for new drugs in oncology and license applications for biologics to identify the characteristics of a successful RWE study that contribute to accelerated or full drug approval. The work was financed by Pfizer.
“Drug developers have to make hundreds of decisions about RWE’s use, and [the findings of this review] can be used to quickly make the most effective decisions for their submissions, ”said co-author Mei Sheng Duh, MPH, ScD, executive director of the Analysis Group. “The FDA comments are an invaluable resource for looking through the ambiguity in the official guidance documents. For example, the most common primary endpoint used as an external control for contextualization or comparison with the pivotal study was overall response rate. The most common statistical method used to compensate for differences in patient characteristics was the inverse probability of treatment weighting. “
For the creation of stronger submission dossiers for RWE studies, the following findings were obtained, among others:
- Engage the FDA early to confirm suitable data sources and whether the RWE study should be designed as a natural history study for contextualization or as an external control study for comparison with the approval study.
- Make sure that the real world data (RWD) you use is high quality and fit for purpose.
- Align the RWE and approval-relevant study populations by comparing the inclusion and exclusion criteria of the study as far as possible and adjusting the remaining imbalance in the initial characteristics using the method for weighting the inclination points.
- Describe methods for minimizing residual and unmeasured confounding, including appropriate index data and reducing missing values.
“Analyzing the FDA comments, it is clear that the agency believes that high quality RWD is of the utmost importance,” said Dr. Maral DerSarkissian, co-author and vice president of the Analysis Group. “The accuracy of the primary endpoints, key covariates such as previous lines of therapy, and imputation models for missing values all need to be validated. In addition, we found that the inclusion of RWE helped to reduce the development times for cancer drugs by one to three years. This is directly related to the fact that urgently needed treatments are falling into the hands of patients with difficult-to-treat cancers. “
Edited by Gary Cramer