Bill Poland1, Florian Teischinger2. 1. Strategic Consulting, Certara, Menlo Park, CA. 2. SRA, JT International SA, Geneva, Switzerland.
Abstract
INTRODUCTION: As suggested by the Food and Drug Administration (FDA) Modified Risk Tobacco Product (MRTP) Applications Draft Guidance, we developed a statistical model based on public data to explore the effect on population mortality of an MRTP resulting in reduced conventional cigarette smoking. Many cigarette smokers who try an MRTP persist as dual users while smoking fewer conventional cigarettes per day (CPD). Lower-CPD smokers have lower mortality risk based on large cohort studies. However, with little data on the effect of smoking reduction on mortality, predictive modeling is needed. METHODS: We generalize prior assumptions of gradual, exponential decay of Excess Risk (ER) of death, relative to never-smokers, after quitting or reducing CPD. The same age-dependent slopes are applied to all transitions, including initiation to conventional cigarettes and to a second product (MRTP). A Monte Carlo simulation model generates random individual product use histories, including CPD, to project cumulative deaths through 2060 in a population with versus without the MRTP. Transitions are modeled to and from dual use, which affects CPD and cigarette quit rates, and to MRTP use only. RESULTS: Results in a hypothetical scenario showed high sensitivity of long-run mortality to CPD reduction levels and moderate sensitivity to ER transition rates. CONCLUSIONS: Models to project population effects of an MRTP should account for possible mortality effects of reduced smoking among dual users. In addition, studies should follow dual-user CPD histories and quit rates over long time periods to clarify long-term usage patterns and thereby improve health impact projections. IMPLICATIONS: We simulated mortality effects of a hypothetical MRTP accounting for cigarette smoking reduction by smokers who add MRTP use. Data on relative mortality risk versus CPD suggest that this reduction may have a substantial effect on mortality rates, unaccounted for in other models. This effect is weighed with additional hypothetical effects in an example.
INTRODUCTION: As suggested by the Food and Drug Administration (FDA) Modified Risk Tobacco Product (MRTP) Applications Draft Guidance, we developed a statistical model based on public data to explore the effect on population mortality of an MRTP resulting in reduced conventional cigarette smoking. Many cigarette smokers who try an MRTP persist as dual users while smoking fewer conventional cigarettes per day (CPD). Lower-CPD smokers have lower mortality risk based on large cohort studies. However, with little data on the effect of smoking reduction on mortality, predictive modeling is needed. METHODS: We generalize prior assumptions of gradual, exponential decay of Excess Risk (ER) of death, relative to never-smokers, after quitting or reducing CPD. The same age-dependent slopes are applied to all transitions, including initiation to conventional cigarettes and to a second product (MRTP). A Monte Carlo simulation model generates random individual product use histories, including CPD, to project cumulative deaths through 2060 in a population with versus without the MRTP. Transitions are modeled to and from dual use, which affects CPD and cigarette quit rates, and to MRTP use only. RESULTS: Results in a hypothetical scenario showed high sensitivity of long-run mortality to CPD reduction levels and moderate sensitivity to ER transition rates. CONCLUSIONS: Models to project population effects of an MRTP should account for possible mortality effects of reduced smoking among dual users. In addition, studies should follow dual-user CPD histories and quit rates over long time periods to clarify long-term usage patterns and thereby improve health impact projections. IMPLICATIONS: We simulated mortality effects of a hypothetical MRTP accounting for cigarette smoking reduction by smokers who add MRTP use. Data on relative mortality risk versus CPD suggest that this reduction may have a substantial effect on mortality rates, unaccounted for in other models. This effect is weighed with additional hypothetical effects in an example.
Authors: Lai Wei; Raheema S Muhammad-Kah; Thaddaeus Hannel; Yezdi B Pithawalla; Maria Gogova; Simeon Chow; Ryan A Black Journal: Harm Reduct J Date: 2020-06-29
Authors: Raheema S Muhammad-Kah; Yezdi B Pithawalla; Edward L Boone; Lai Wei; Michael A Jones; Ryan A Black; Thomas M Bryan; Mohamadi A Sarkar Journal: Int J Environ Res Public Health Date: 2019-04-09 Impact factor: 3.390
Authors: Peter N Lee; David Abrams; Annette Bachand; Gizelle Baker; Ryan Black; Oscar Camacho; Geoffrey Curtin; Smilja Djurdjevic; Andrew Hill; David Mendez; Raheema S Muhammad-Kah; Jose Luis Murillo; Raymond Niaura; Yezdi B Pithawalla; Bill Poland; Sandra Sulsky; Lai Wei; Rolf Weitkunat Journal: Nicotine Tob Res Date: 2021-02-16 Impact factor: 4.244