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E-Cigarettes: Promise, Peril, and

Probabilistic Population Prediction

Bill Poland, PhD

Bill.Poland@Certara.com

INFORMS Annual Meeting, 10 November 2014

E-cigarettes, which deliver nicotine without carcinogenic tar, hold the

promise to save the lives of many smokers who switch to them, but risks

include failure to quit cigarettes (dual use), increased initiation to nicotine

products among youth, relapse of former smokers to e-cigarettes, and e-

cigarettes becoming a “gateway to smoking.” To capture these uncertainties

and weigh benefits vs. risks, prediction of e-cigarette health impacts must

use a broad range of probability-weighted scenarios.

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After the “cigarette century”: what’s the end game?

2http://www.surgeongeneral.gov/library/reports/50-years-of-progress/index.html#fullreport

2014

©

Smoking still kills about 480,000 Americans per year, reducing life

spans 11-12 years.

3

http://www.surgeongeneral.gov/library/reports/50-years-of-progress/index.html#fullreport

©Sugerman DT. e-Cigarettes. JAMA 2014;311(2):212. http://jama.jamanetwork.com/article.aspx?articleid=1812964

* Herzog B, Wells Fargo Securities presentation, 2014. http://www.ecigarette-politics.com/files/WF-DallasMarch2014.ppt4

Sales of e-cigarettes have been roughly doubling annually since

US introduction in 2007 and could overtake cigarettes by 2023*,

raising hopes and fears.

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Cigarettes deliver nicotine (addictive but relatively safe) and

tar (toxic partially combusted tobacco); e-cigs avoid the tar.

Nicotine

Produced by the tobacco plant as a natural pesticide

• Used as a pesticide in early 1900s

Highly addictive for many, mildly addictive for others

Suggestion but no solid evidence linking to cancer

• Ames assay for genotoxicity negative

• But promotes angiogenesis and tumors in some experimental models

Exposure during adolescence and in utero appears to cause long-term brain changes

Nicotine Replacement Therapy (NRT) such as patches and gum, and drugs like Chantix, minimize addiction risk but have a low success rate

Tar

Contains hundreds of mutagens,

carcinogens, and other toxins

• “Cigarette smoking has been causally

linked to diseases of nearly all organs

of the body”

• Surgeon General’s Report, 2014

• Top diseases: lung cancer, COPD,

CHD

• Also diabetes, rheumatoid arthritis, and

colorectal cancer, as well as

inflammation and impaired immune

function.

Damages lungs (coats the cilia

causing them to stop working and

eventually die) and mouth.

5

©

One eminent researcher concluded “e-cigarettes, with prudent ...

regulations, do have the potential to make the combusting of

tobacco obsolete ... just as digital cameras made film obsolete.”

6 Abrams DB. JAMA 2014;311(2): 135-136. http://jama.jamanetwork.com/article.aspx?articleid=1812971

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Another researcher emphasizes a worst-case scenario.

Time for probabilistic modeling!

Best Case

Massive migration of smokers into e-cig vaping

• Like digital cameras replacing film

• CV and respiratory disease decline, followed by cancers

Dual use is temporary

Many e-cig users then quit nicotine entirely

• Users work their way down to low and no-nicotine e-cigs

• Total nicotine use drops

Youths who would have smoked take up e-cigs instead

Long-term vapor inhalation is found safe.

Worst Case

Massive migration of smokers and non-smokers into e-cig vaping

• Like cell phone adoption

• Non-users drawn in by purported safety

Dual use persists

• Mortality benefit of fewer cigarettes smoked/day is less than hoped

E-cigs attract youth and experimenters, addict them to nicotine, and become a “gateway to smoking”

E-cigarette advertising renormalizes tobacco product use so that smoking prevalence increases.

Long-term exposure to fine particles in vapor turns out to be harmful.

7

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Population models predict smoking prevalence and

mortality under various scenarios.

8

Mendez D 2011. Modeling the Population Dynamics of Smoking Prevalence and Health Effects, Washington DC, 9 May2011. http://www.iom.edu/~/media/Files/Activity%20Files/PublicHealth/ReducedRiskTobacco/MendezPresentation.pdf

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Mortality risk relative to nonsmokers has been modeled vs. years

since quitting. Quitting by 40 may return risk to non-smoker levels.

9

Mendez D, Warner KE 2001. “The relative risk of death for former smokers: the influence of age and years-quit.” Unpublished

research monograph. www.umich.edu/~dmendez/tobacco/RRiskmonograph.doc

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Few attempts have been made to relate mortality to use levels

(intensity)—important with e-cigs. Here a Tobacco Exposure Index

balances lifetime smoke toxin accumulation with natural purging.

10

Miller LS et al. 2010. Evaluation of the economic impact of California’s Tobacco Control Program: a dynamic model

approach. Tobacco Control 19(Suppl 1):i68-i76. http://tobaccocontrol.bmj.com/content/19/Suppl_1/i68.full.pdf

never-smoker2 packs/day

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A new generation of population models tries to predict

effects of two tobacco products and dual use.

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Verzi S 2014.

http://www.fda.gov/downloads/Advis

oryCommittees/CommitteesMeetingMa

terials/TobaccoProductsScientificAdvis

oryCommittee/UCM394231.pdf

Cigarette/e-cig

“gateway

to smoking”

relapse

by former

smoker

via e-cigs

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Even with simplifications, over a dozen highly uncertain

transition rates remain.

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Cigarette/e-cig

x

x x

x

x

x

Assume

• one product change at a time

• no relapse, except former

smokers via e-cigs

x

“gateway

to smoking”

x x

x

x

relapse

by former

smoker

via e-cigs

xx

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Data sources include:

For cigarette smoking initiation, prevalence, use levels, and cessation rates: US national surveys, with age and gender breakdown

• National Survey on Drug Use and Health (NSDUH)

• National Health Interview Survey (NHIS)

• Tobacco Use Supplement to the Current Population Survey (TUS-CPS)

• A decade or more of annual data allows model calibration

For smoking-related mortality: large survey-based relative risk studies

• By age, gender, use levels, time since quitting

For e-cig use patterns:

• Randomized controlled studies of smokers offered e-cigs

• Surveys of e-cig use (problematic due to biases)

• Studies of Swedish snus as a possible e-cigarette analog

• In the 1970s snus started displacing cigarettes in Sweden, resulting in the lowest smoking rate in Europe for the past 15+ years.

• BUT e-cig technology and use patterns are evolving quickly!

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©

Assuming a linear system with constant coefficients results in a weighted

sum of matrix exponentials describing the states over time, e.g., smoker,

e-cig user, dual user, former user, and never-user categories.

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Continuous Discrete

Equation

(x is a vector, A &

P are matrices)

dx/dt = A x + b,

x(0) = x0

x(t+1) = P x(t) + B (t=0, 1, ...),

x(0) = x0

Units A: units of x/t (≥0)

b: units of x

P: no units (range 0-1)

B: units of x

xEquilibrium: x(∞)

(dx/dt = 0,

x(t+1) = x(t))

-A-1 b (I–P)-1 B

Solution x(t) eAt x0 + (I-eAt) xEq Pt x0 + (I-Pt) xEq

Equivalent if: P = eA,

B = -(I-P) A-1 b

Exponential approach to equilibriumExponential approach to equilibrium

Proportional transition rates Constant growth rateConstant growth rate“Survival” proportion

Most population models are discrete, but continuous and discrete linear models are equivalent:

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One insight from such linear models is that even if parameters are

fixed, equilibrium (-A-1 b) may take centuries to reach.

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Current Smokers

Former Smokers

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2000 2050 2100 2150 2200

Ne

ve

r-S

mo

ke

r P

rop

ort

ion

Sm

oke

r P

rop

ort

ion

Year

Note Former Smoker prevalence increases, then decreases.

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For flexibility, we use quasi Monte Carlo simulation of individual

tobacco use histories across a large population.

Most population health effect models define Markov states and

calculate annual proportions of users in each state (deterministically).

Advantage of individual simulation: the number of states considered is

no longer a limitation.

• E.g., mortality can be made a function of year of age, gender,

smoking intensity, e-cig use status, former status history, etc

Disadvantage: tens of thousands of individuals need to be simulated for

stable results in each sub-category.

Use of quasi Monte Carlo numbers (selected to cover the space rather

than fully random) reduce this disadvantage, by reducing the number of

simulated individuals needed by several-fold.

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Probabilistic analysis translates input uncertainty into

output uncertainty.

Wide input distributions result in wide distributions on possible net

health impacts of e-cigs, from negative to positive.

• Wide distributions are more “honest” than point estimates

Deterministic and probabilistic sensitivity analysis

show which variables are most important for

reducing uncertainty on health impacts.

• Tornado charts sweep one variable at a time

through a range, sorting by bar length to form

a tornado shape.

Breakeven analysis shows how much beneficial effect (like switches

from smoking to e-cigs) is needed to offset a harmful effect (like

switches the other way).

• Called “tipping point analysis” in Swedish Match’s 2014 snus

application to the FDA’s Center for Tobacco Products.

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0.80

1.00

0.38

0.92

0.9%

0.4%

0.35

1.20

1.85

0.60

1.10

2.7%

1.2%

0.45

Base

-200,000 0 200,000 400,000 600,000

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Key tasks in evaluating net health effects of e-cigs include:

Improve estimates and ranges of e-cig transition rates

• Initiation, full and partial switching from cigarettes, relapse back to cigarettes, “gateway” from e-cigs to cigarettes, quit rates

• Snus analogy is useful as a scenario

• Elicit subjective ranges from an expert panel?

• As a function of time (e.g., 2020 and 2050)

• Conditioned on various e-cig market growth scenarios

Adjust mortality rates to account for history of cigarette use levels

• Critical because smokers trying e-cigs reduce, but are slow to eliminate, smoking.

Predict impact of e-cigs on morbidity as well as mortality

• Morbidity effects show up sooner than mortality effects.

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Thank you! Questions?

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Abrams 2014. e-Cigarettes: Can we use them to make combusting of tobacco obsolete - end the “cigarette century” and its

preventable deaths? Presentation to American Academy of Health Behavior 14th Annual Meeting.

http://www.aahb.org/Resources/Pictures/Meetings/2014-Charleston/PPT%20Presentations/Sunday%20Welcome/Abrams.AAHB.3.13.v1.o.pdf