DOI: 10.3886/icpsr39577.v1
title: New Analytic Approach for Valid Comparative Effectiveness Research [Methods Study], United Kingdom, 2015-2020
title: Version 1

description: 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.
description: To examine a new method, the posttreatment event rate ratio (PTERR), to address unmeasured confounding in observational studies with mortality as the study outcome. Specific aims were to (1) assess a novel variation of PERR that addresses the death outcome; (2) apply the death outcome strategy to cardiovascular outcomes to assess the influence of temporal changes in possible effects of unmeasured confounders on PERR; and (3) perform new database studies of kidney disease progression to empirically test a continuous and composite kidney outcome and to determine whether observational study designs of therapeutic effectiveness using EHR data can reproduce results from a randomized controlled trial (RCT).
description: In this study, researchers examined the PTERR to address unmeasured confounding in studies with mortality as the outcome. Using data from the period following the end of treatment, PTERR calculates adjusted hazard ratios by comparing mortality risk for study participants who did and did not receive treatment.
First, researchers showed the assumptions under which the PTERR could alleviate unmeasured confounding. To test the sensitivity of the PTERR estimates to the statistical assumptions, researchers conducted simulation studies using generated data with different baseline mortality rates.
Then researchers used data from three sets of previous observational studies: thiazolidinedione studies, angiotensin-converting enzyme inhibitor (ACEI) studies, and the Women's Health Initiative (WHI) intact uterus and hysterectomy studies. Researchers examined mortality for patients who did and did not receive treatment during two periods: from the start of the study until patients receiving treatment stopped it, and from the time patients stopped treatment until a predefined end date or death. Researchers compared PTERR mortality hazard ratios from the observational studies with mortality hazard ratios from randomized controlled trials (RCTs) to determine if estimates were similar.
description: Datasets: 
DS1: New Analytic Approach for Valid Comparative Effectiveness Research [Methods Study], United Kingdom, 2015-2020