Besides IPD meta-analyses, a statistical approach called predictive analytics can be applied to previous trials or other research data to provide more-personalized results that can optimize the use of specific treatments. This approach can be helpful in studies with a diverse group of people and a wide range in individual responses to an intervention. We have to date awarded one secondary data reuse project.

Using Statistical Methods to Predict Treatment Response Based on Patients' Likelihood of Having Benefits or Side Effects from the Treatment

The objective of this study, which was completed in 2019, was to examine the value of assessing heterogeneity of treatment benefits and harms in guiding clinical choices across patients. In this study, the research team grouped people based on their likelihood of having benefits or side effects from a certain medicine.

The study team reported that grouping data on people based on their likelihood of having benefits or side effects from each medicine showed differences in how the medicines affected them. The group of patients with a low risk of breaking a bone was more likely to benefit from pioglitazone. Patients in the group less likely to benefit from anthracycline had more heart problems. The team added that researchers can use the statistical methods to better understand how likely patients are to have benefits or harms from medicines.

Project Details

Principal Investigator: David Kent, MD, MS
Organization: Tufts Medical Center, Inc.
State: Massachusetts