Altria Group, Inc. · NYSE:MO
Altria — CORESTA Congress 2018, Kunming, China
25 slides from Altria's conference presentation, Oct 22, 2018
Slide 1: Assessing the population health impact of authorizing a smokeless tobacco product with a modified risk claim
Assessing the population health impact of authorizing the marketing of a smokeless tobacco product with a proposed modified risk claim R. Muhammad-Kah1, Y. B. Pithawalla1, M. Jones1, L.Wei1, T. Bryan1, R. Black1, E. Boone2 & M. Sarkar1 1Center for Research & Technology, Altria Client Services, Richm
Slide 2: PMTA / MRTPA Requirements (§910/911)
PMTA / MRTPA Requirements (§910/911) Section 910 - Premarket Section 911(g)(1) - Modified Tobacco Product Application Risk Tobacco Products (PMTA) - New Tobacco (MRTP) - Reduced Risk Products* Demonstrate that a MRTP as used by the Demonstrate that... “…is appropriate for consumers will: the protect
Slide 3: Population Health Standard
Population Health Standard - Assessing impact on population as a whole including users and non-users NET BENEFIT / RISK Relative Risk of New Product Changes in Product Compared to Current Product Use Patterns Population modeling can be used to estimate the combined impact of both components *FDA’s D
Slide 4: Population Models - New Tobacco Products
Population Models - New Tobacco Products Several population models have been developed, such as: • RAIS (Bachand & Sulsky, 2013) • FDA CTP/Sandia Lab (Vurgin et al., 2015) • PMI (Weitkunat et al., 2015) • Warner & Mendez (2018) • BAT (Hill & Camacho, 2017) • Levy et al. (2018) • JT (Poland & Teisc
Slide 5: Illustration of the ALCS Cohort Model
Illustration of the ALCS Cohort Model Evaluating Impact of Authorizing a Modified Risk Claim for a Product Currently on the U.S. Market USSTC submitted MRTPA for Copenhagen Snuff Fine Cut on March 20, 2018 Accepted and filed for scientific review by FDA on Sept. 14, 2018 MRTPA = Modified Risk Tobacc
Slide 6: Modeling Framework: Evaluating Impact of MRTP Authorization
Modeling Framework: Evaluating Impact of MRTP Authorization Compare difference in All-cause Mortality between Base Case (Status Quo) and Modified Case A future state where both Both cigarettes and cigarettes and MST MST products co- products co-exist in the exist in the U.S. U.S. market, but MST is
Slide 7: ALCS Cohort Model
ALCS Cohort Model Consists of two interlinked sub-models: - Transition Sub-model - Mortality Sub-model Can be employed in: - Single Cohort Format* - Multiple Cohort Format - Population Level estimates * The single cohort model is similar in structure to the model shared in Bachand AM and Sulsky
Slide 8: Inputs and Assumptions
Inputs and Assumptions Mortality Sub-model Never Tobacco Users, Smokers and Former Smokers Mortality: - Developed from analysis of the 60,000 cohort sample based “Smoking and Mortality: The Kaiser-Permanente (KP) Experience” study* - Adjusted KP data to reflect U.S. population of Yr. 2000 - Built
Slide 9: Excess Relative Risk (ERR) based on Hazard Ratios (HR)
Excess Relative Risk (ERR) based on Hazard Ratios (HR) HR for all-cause mortality developed from ALCS Linked Mortality Analysis* Never User HR=1 Current ST HR=1.10 Current Smoker HR=2.12 ERR estimate for Smokeless Tobacco User compared to Cigarette Smoker 𝑯𝑹𝑴𝑺𝑻 − 𝟏 𝟏. 𝟏𝟎 − 𝟏…
Slide 10: Inputs and Assumptions
Inputs and Assumptions Transition Sub-model Base Case Transition Rates: Nationally representative transition probabilities estimated from Tam et al. (2015)* Modified Case Transition Rates: Study Title: Claim Comprehension & Intentions Study Population Sampled: tobacco users and never-users
Slide 11: Model Inputs from Claim Comprehension & Intentions Study (CCIS)
Model Inputs from Claim Comprehension & Intentions Study (CCIS) Exposure to ad Pre Ad intentions to Post Ad intentions to Control material without use/switch/dual use use/switch/ dual use label claim Pre Ad intentions to Exposure to ad Post Ad intentions to Test material with use/switch/dual use use
Slide 12: Modified Case Transition Rates from ALCS CCIS
Modified Case Transition Rates from ALCS CCIS Base Case Relative percent difference Transition Rates Tobacco Use Transition Transition Rates between response of Test Modified by CCIS from Tam et al. and Control group in CCIS Never User of tobacco initiating MST candidate product (Initiation) 1.6% -4
Slide 13: Results: 1MM Male Single Cohort
Results: 1MM Male Single Cohort Comparison of Survivors in the Base Case versus Modified Case Age Mean Difference in Mean Number of Survivors Mean Number of Survivors 95% Credible Number of Survivors (y) (Base Case) (Modified Case) Interval (Modified Case-Base Case) 43 954,680 954,754 74 (64, 85) 48
Slide 14: Results: Understanding Impact of Individual Transitions
Results: Understanding Impact of Individual Transitions Transitioning of cigarette smokers to exclusive MST use and/or dual use contribute significantly to the overall benefit Dual User = Current cigarette smoker and MST user; MRTP = MST marketed with a modified risk claim. Mean difference in number
Slide 15: Multiple Cohort Approach - Population Level Estimates
Multiple Cohort Approach - Population Level Estimates Native Born Male Base Case: Both cigarettes and MST Population in Yr. 2075 products co-exist in the U.S. market Age Group (y) Modified Case: Assumes MST 11.52MM 0-4 products receive authorization to be 0-4 yrs. 5-9 11.39MM labeled as an MRTP
Slide 16: Results: Multiple Cohort Setting - Population Level Estimates
Results: Multiple Cohort Setting - Population Level Estimates Difference in the Number of Survivors Between the Modified and Base Case Model predicts ~ 93,000 premature deaths will be prevented over a 60-year period, following authorization to market MST with a label claim The premature deaths p
Slide 17: Output Maps Example - Risk/Benefit Sensitivity Analysis
Output Maps Example - Risk/Benefit Sensitivity Analysis Concurrently vary: Risk: Increasing ERR Benefit: % of Would be Smokers initiating MST instead of smoking All other transition rates kept the same as those in the Modified Case scenario Benefit Risk Altria Client Services | Sr. Director,
Slide 18: Output Maps Example - Risk/Benefit Sensitivity Analysis
Output Maps Example - Risk/Benefit Sensitivity Analysis Concurrently vary: Risk: Change in rate of Never Tobacco Users initiating on MST (Initiation) Benefit: Change in rate of Cigarette Smokers switching to MST (Switching) All other transition rates kept the same as those in the Modified Ca
Slide 19: Limitations
Limitations Assumption that product-specific initiation, cessation, and other transition rates do not change over the modeling time period Models do not currently estimate morbidity Relative percent change in intentions is used as a proxy for relative percent change in behavior Our models do
Slide 20: Summary
Summary We developed the ALCS Cohort Model using well-established best modeling practices and tested it using uncertainty and sensitivity analyses Modeling results indicates that FDA authorization of the proposed modified risk claim yields a modest net health benefit to the population as a whole
Slide 21: Thank You
Thank You For copies of this presentation visit the Altria’s Science Website at www.altria.com/alcs-science Altria Client Services | Sr. Director, Regulatory Sciences | CORESTA Congress, Kunming, China | Oct. 22-26, 2018 | 21
Slide 22: Advertising with the Proposed Modified Risk Claim
Advertising with the Proposed Modified Risk Claim Altria Client Services | Sr. Director, Regulatory Sciences | CORESTA Congress, Kunming, China | Oct. 22-26, 2018 | 22
Slide 23: Epidemiological Data Sources for Relative Risk Estimates
Epidemiological Data Sources for Relative Risk Estimates - ALCS Linked Mortality Analysis National Health Interview Survey National Longitudinal Mortality Study Survey Years: 1987 – 2005 (intermittent) Based on the Current Population Survey ~155,000 total respondents Survey years: 1993-2005
Slide 24: Harm Reduction Opportunities - Smokeless Tobacco
Harm Reduction Opportunities - Smokeless Tobacco ~6.6 MM Adult Smokeless Consumers 2.3 Million Adult Dual Users ~43 MM Adult Cigarette Smokers Based on ALCS analysis of PATH Wave 1 data [Sep 12, 2013 – Dec 14, 2014] Altria Client Services | Sr. Director, Regulatory Sciences | CORESTA Congress, Kunmi
Slide 25: Modeling Good Research Practices
Modeling Good Research Practices* Right amount of complexity to allow for informed decision making Clearly defining assumptions Using validation and sensitivity analysis to ensure that outcomes are reasonable Systematic identification and justification for use of best available data sources