Causal inference is used to answer cause and effect research questions and yield estimates of effect. These study design considerations and statistical methods address the effects of confounding variables and other potential biases, and allow researchers to answer questions such as, “Does treatment A produce better patient outcomes as compared to Treatment B?”

RCTs are comparative studies that use randomization and scientifically rigorous methods that are sufficient for approval-related decision making. However, these studies may not have sufficient sample sizes to detect rare adverse events or may exclude people with certain characteristics. Researchers then turn to real-world data (RWD) to gather more information on vaccines and monitor their safety and effectiveness in practice.

In celebration of HealthCore’s 25th Anniversary of Founder’s Day, we’re rolling out a series of articles highlighting some of our most impactful work.

In celebration of HealthCore’s 25th Anniversary of Founder’s Day, we’re rolling out a series of articles highlighting some of our most impactful work.

Recently, researchers from the Safety and Epidemiology team at HealthCore conducted one of the first real-world studies investigating the safety of palbociclib, the most widely prescribed CDK4/6 inhibitor in the treatment of HR+/HER2- advanced stage breast cancer.

Real-world evidence can usefully support precision medicine and faster regulatory approvals. The use of statistical methods to develop better case-identifying algorithms enables use of claims databases to study rare diseases and other targeted indications as well as more valid outcome ascertainment for safety and effectiveness research.

Machine learning combines advanced statistical methods with the results from validation studies to construct new case-identifying algorithms. We have found these methods to offer marked improvement in the accuracy with which we can identify patients of interest. These methods not only reduce bias from misclassification, which translates into more valid research, but we have also been able to identify patients with conditions for which there are no diagnosis codes in claims, such as cancer stage or biomarker status.

As these various efforts to address the growing problem of prescription drug abuse and misuse play out, it will be important to monitor the degree to which they succeed in the real world. Safety and Epidemiology research is providing insights into the effectiveness of these efforts.