A fully Bayesian mixture model approach for identifying noncompliance in a regulatory tobacco clinical trial.

ABSTRACT: Identifying noncompliance in a randomized trial is challenging, but could be improved by leveraging biomarker data to identify participants that did not comply with their assigned treatment. For randomized trials of very low nicotine content (VLNC) cigarettes, the biomarker of total nicotine equivalents (TNE) could be used to identify noncompliance. Compliant participants should have lower levels of TNEs than participants that did not comply and smoked normal nicotine content cigarettes, resulting in a mixture of compliant and noncompliant participants at each dose level. Thresholds of TNE could then be identified from the compliant groups at each dose level and used to determine which study participants were compliant. Furthermore, proposed biological relationships of TNE with nicotine do

SUBMITTER: Kaizer AM 

PROVIDER: S-EPMC7470177 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature