New Analytic Approach for Valid Comparative Effectiveness Research [Methods Study], United Kingdom, 2015-2020

Comparative effectiveness research compares two or more treatments to see which treatment works better for which patients. Such research may include

Randomized controlled trials, or RCTs. Researchers assign patients to a treatment by chance. Researchers consider RCTs to be the best way to figure out when changes in patients' health result from the treatment.
Observational studies. Researchers study what happens when patients and their doctors choose treatments. Patient traits, such as age or health, may affect treatment choices. These traits may also affect patients' responses to treatments. Determining whether a patient's traits, the treatment, or a mix of the two affected how well the treatment worked may be difficult.

In observational studies, researchers use statistical methods to help find out whether changes in patients' health result from treatment or something else. Existing methods work well when studies look at whether treatment affects the risk of a health event, such as a heart attack. In these cases, researchers can compare how often patients had heart attacks before and after patients receive treatment. But existing methods don't work well when studies look at the risk of a one-time event, such as death.
In this study, the research team tested a new statistical method for observational studies called posttreatment event rate ratio, or PTERR, that helps figure out whether a treatment reduces the risk of death.