Quantifying the risk-reduction potential of new Modified Risk Tobacco Products

Biomarker data, collected in clinical studies, can be analyzed to estimate the effects of switching to an MRTP as compared to quitting smoking. Based on transparent assumptions, a link function is formulated that translates these effects into the F-factor. The concepts of 'lack of sufficiency' and 'necessity' are introduced, allowing for a parametrization of a family of link functions. These can be uniformly sampled, thus providing different 'scenarios' on how biomarker-based evidence can be translated into the F-factor to inform the PHIM.