h"p://www.pri.org/stories/2012-12-03/video-land-tobacco

Session 2: Smoking and lung cancer

Dr Clarence Tam(clarence_tam@nuhs.edu.sg) Saw Swee Hock School of Public Health National University of Singapore

SPH2101: Public Health and Epidemiology

Session objec+ves

Overview of lung cancer epidemiology Epidemiological evidence for the associa+on between smoking and lung cancer

Tobacco control strategies Introduce epidemiological concepts:

Incidence and prevalence Measures of associa@on Types of epidemiological studies

LUNG CANCER BURDEN AND EPIDEMIOLOGY

Global burden of lung cancer

Most common cause of cancer-related death worldwide (~1.6 million in 2012)

Accounts for ~13% of all cancers ~70% of lung cancer deaths caused by tobacco use

Lung cancer deaths expected to rise to ~2.4 million worldwide by 2030

IHME: h"p://vizhub.healthdata.org/gbd-compare/

globalcancermap.com

In Singapore, lung cancer is the second most common cancer in men, and the most common

cause of cancer-related mortality

(it is the third most common cancer in women and the second most common cause of cancer-related mortality)

Lim. Singapore Med J 2012;53(1):3

Lung Cancer (C33-C34): 2010-2011Net Survival up to Ten Years after Diagnosis, Adults (Aged 15-99), England and Wales

Please include the citation provided in our Frequently Asked Questions when reproducing this chart: http://info.cancerresearchuk.org/cancerstats/faqs/#HowPrepared by Cancer Research UKOriginal data sources:Survival estimates were provided on request by the Cancer Research UK Cancer Survival Group at the London School of Hygiene and Tropical Medicine. http://www.lshtm.ac.uk/eph/ncde/cancersurvival/

If youre diagnosed with lung cancer, your chances of surviving 5 years are

~10%

Lung Cancer (C33-C34): 1971-2011Age-Standardised Five-Year Net Survival, England and Wales

Please include the citation provided in our Frequently Asked Questions when reproducing this chart: http://info.cancerresearchuk.org/cancerstats/faqs/#HowPrepared by Cancer Research UKOriginal data sources:Survival estimates were provided on request by the Cancer Research UK Cancer Survival Group at the London School of Hygiene and Tropical Medicine. http://www.lshtm.ac.uk/eph/ncde/cancersurvival/http://www.lshtm.ac.uk/eph/ncde/cancersurvival/

Despite medical advances, 5-year survival rates have not improved drama@cally since the

1970s

Lung cancer prevalence

In 2012, 1.89 million people worldwide were living with lung cancer

This equates to ~0.03% of the worlds popula+on, or ~3 in 10,000 people

We call this the prevalence of lung cancer

Prevalence

What propor@on of the popula@on has a given disease at a given point

in @me?

Includes all those with exis@ng disease at @me of study (whether onset was recent or

a long @me ago)

Number of people with disease at a given +me x 100%

Total number of people in the popula+on

These people (the numerator)

must be included in

These people (the denominator) Expressing the number of cases

rela@ve to the popula@on size allows us to compare popula@ons of

dierent sizes

Prevalence calcula+on

Prevalence examples

On 1 January 2010, 0.16% of women in the USA had a history of cervical cancer

The prevalence of Hepa@@s B virus surface an@gen among Singaporeans aged 18 to 69 years in 2005 was 2.8%

Have you smoked at least 1 cigare_e in the previous 12 months?

Dividing the number of Yes responses by the number of respondents would give us an es@mate of the prevalence

of smoking over 1 year among SPH2101 students

But how good is this es@mate? Well come back to this in Tutorial 1

New or exis+ng disease?

Epidemiologists dieren@ate between new (incident) and exis@ng (prevalent) disease

Why?

Incidence and prevalence

Loeb et al. Cancer Res 1984;44:5950-58

Many chronic diseases do not develop un@l years or decades ager exposure, e.g. cancer

Many infec@ous

diseases have long incuba@on periods

between infec@on and clinical symptoms, e.g. HIV/AIDS, tuberculosis

Incidence and prevalence Prevalent (exis@ng) disease is aected by disease trends both now and in the past Lung cancer cases among middle-aged men today tell you

about smoking pa"erns a few decades ago AIDS cases today tell you about HIV transmission pa"erns a

decade ago

Incident (new) disease reects recent trends If you want to know whether recent policies to

reduce lung cancer are working, you need to look at new cancer cases and deaths

If you want to know if HIV transmission is going down, you need to study new HIV infec@ons, not AIDS

Which is the most successful mobile phone company?

Samsung vs Apple

Prevalence is inuenced by incidence and disease dura@on

Rahul Patwari: h"ps://www.youtube.com/watch?v=1jzZe3ORdd8

TIME

Disease onset

Prevalence over this :me period includes 2 new cases + 3 exis:ng

cases

Prevalence depends on incidence and disease dura@on

TIME

Death

Prevalence over this :me period includes 2 new cases only

If disease survival is short, prevalence and incidence will be similar

X

X

X

X

X

Measuring incidence What does this tell you about lung cancer

incidence?

Where are you most likely to get lung cancer?

Absolute numbers tell us only where most cases occur

To learn about the risk of contrac@ng lung cancer, we need to know the size of the popula@on in which those deaths occur

Country New lung cancer cases (2012)

Singapore 1,590

Vietnam 19,559

India 63,759

China 597,182

USA 167,545

Calcula+ng incidence rates

Country New lung cancer cases

(2012)

Popula>on (mid-2012)

New cases per 100,000 persons (2012)

Singapore 1,974 5,250,000 37.6 Vietnam 21,865 89,610,656 24.4

India 70,275 1,254,910,714 5.6

China 652,842 1,360,087,500 48.0 USA 214,226 315,967,552 67.8

The lung cancer rate is the number of newly diagnosed cases in the popula@on

during 2012, divided by the size of the popula@on (usually the mid-year

es@mate)

1,974 / 5,250,000 * 100,000 = 37.6 cases per 100,000 persons in Singapore in 2012

We ogen express this as cases per 100,000 persons:

Kimman. Asian Pacic J Cancer Prev 2012;13:411-20

Comparing incidence rates

But its not that simple! WHY?

37.624.4 =1.54

Lung cancer rate in Singapore appears to be 1.54 @mes (or 54%) higher than in Vietnam

Country New lung cancer cases

(2012)

Popula>on (mid-2012)

New cases per 100,000 persons

(2012)

Singapore 1,974 5,250,000 37.6

Vietnam 21,865 89,610,656 24.4

India 70,275 1,254,910,714 5.6

China 652,842 1,360,087,500 48

USA 214,226 315,967,552 67.8

We can take the ra@o of rates between countries, e.g.:

This is the rate ra:o

Singapore has a higher propor@on of the popula@on in older age groups, who have a higher risk of lung cancer

Country New lung cancer cases

(2012)

Popula>on (mid-2012)

New cases per 100,000 persons

(2012)

Age-standardised cases per 100,000

Singapore 1,974 5,250,000 37.6 24.9

Vietnam 21,865 89,610,656 24.4 25.2

India 70,275 1,254,910,714 5.6 6.9

China 652,842 1,360,087,500 48 36.1

USA 214,226 315,967,552 67.8 38.4

If we use some sta@s@cal techniques to account for dierences in the popula@on age structure of dierent countries, the picture looks quite dierent!

The rate ra@o is now: 24.925.2 =0.98 i.e. lung cancer incidence in Singapore is about the same as in Vietnam

We call these age-standardised rates

So why does this happen?

Life expectancy is lower in Vietnam a smaller frac@on of the popula@on

survive to older age when lung cancer risk is higher

If Vietnam had the same popula@on age structure as Singapore, lung

cancer rates would similar in the two countries

In epidemiology, we say that age confounds the associa@on between country and lung cancer incidence

At rst look, it seems as if Singapore has higher lung cancer incidence than Vietnam, but

this is really explained by dierences in age structure

You will learn more about confounding later in the module

A quick recap

Weve done quite a lot of epidemiology so far

We learn how important a disease is in a popula@on by measuring how common it is, e.g. cases, deaths: Prevalence Incidence These are measures of disease frequency

Absolute numbers dont tell us much about disease risk need to know popula@on size (denominator)

We can compare disease frequency between groups or popula@ons, e.g.: Risk ra@o Mortality ra@o

These are measures of associa:on

We must be careful that these associa@ons are real and not due to other dierences between popula@ons, e.g.: Age structure Socioeconomic status Ethnicity

These are ogen confounders in our analysis

LUNG CANCER WHAT CAUSES IT AND HOW DO WE KNOW?

How do we know that smoking causes lung cancer?

Epidemiological evidence

Secular trends in cigare_e sales and lung cancer deaths

Ecological data Early case-control studies Cohort studies Second-hand smoking

Loeb et al. Cancer Res 1984;44:5950-58

Increases in sales of cigare"es precede increases in lung cancer by about 20 years, in both males and females

Historical data

Strength of evidence: WEAK Many other things

could precede rises in lung cancer death

www.gapminder.org

Ecological data We can look at

correla@ons between the % of the

popula@on that smokes and lung

cancer mortality for dierent countries

This is called an ecological study

Strength of evidence: WEAK TO MODERATE Many other things

could correlate with lung cancer mortality

This does not mean that smoking more will make

you live longer!

Ecological data cant tell you if its the people who

smoke who get lung cancer

(although this seems reasonable!)

www.gapminder.org

More on ecological studies later in the module

Ecological studies are a quick way to explore associa@ons between diseases and risk factors Need only aggregate sta@s@cs on disease frequency and the risk factor of interest

Associa@on Causa@on!

BUT

What else could we do?

Compare lung cancer pa@ents with healthy individuals do lung cancer pa@ents smoke more?

This is a case-control study

Compare smokers and non-smokers do smokers have a higher risk of lung cancer?

This is a cohort study

Sir Richard Doll: Smoking and lung cancer

Richard Doll conducted seminal studies to establish the link between smoking and lung

cancer

At the @me, other environmental factors were thought to cause lung cancer, e.g. tarmac, car

fumes

His ndings convinced him to quit smoking!

In a case-control study, we recruit people with lung cancer (cases) and a comparable group of people without lung cancer

(controls)

We then look back to see if lung cancer pa@ents are

more likely to have smoked in the past

We call this the outcome

This is the exposure or risk factor

Cases and controls should be as similar as possible except for disease status

this is not easy!

cases controls

A higher % of lung cancer pa@ents were smokers

But note that most people were smokers at the @me, even among non-cancer pa@ents!

But lung cancer pa@ents also smoked more heavily

This is an example of dose response

Strength of evidence: MODERATE TO STRONG Lung cancer pa@ents more likely to be smokers Among smokers, lung cancer pa@ents also smoke more Not due to other dierences between lung cancer cases and controls wrt:

age, sex, social class or place of residence

Iden+fy individuals with disease (cases) and without disease

(controls)

Compare smoking history between cases and controls Are cases more likely smoke

than controls?

Look back at smoking history

POPULATION LUNG CANCER CASES

CONTROLS

Smoker

Non-smoker

Smoker

Non-smoker

Look back at smoking history

TIME

Some issues with case-control studies How reliably do people report life@me exposure to smoking?

Because we collect informa@on on lung cancer and smoking history at the same @me, can we be sure that its smoking that causes lung cancer?

Perhaps lung cancer pa@ents are more stressed, so they take up smoking

This is an example of reverse causality

Perhaps lung cancer pa@ents have thought more about what could have caused their illness, so they

remember smoking history more accurately

This is an example of recall bias

More on these issues later in the module

Credit: CJ Dub

The Bri@sh Doctors Study involved 34,439 doctors born before 1930

They provided informa@on about smoking habits in 1951, 1957, 1966, 1971, 1978, 1991 and 2001

Compared annual risk of death between smokers and non-smokers

Sir Richard Doll (1912 2005) established the rst cohort study to show deni@vely the health

eects of smoking

Smokers aged 45+ years had more than twice the risk of

death each year compared with lifelong non-smokers

Smokers were also 15 @mes more likely to die from lung cancer compared with lifelong non-smokers

More on this in Tutorial 1

Strength of evidence: STRONG Very large study Data on smoking and death collected over several decades Can be sure that lung cancer occurred ager people started smoking avoids reverse causality

Iden+fy smokers and non-smokers in the popula+on

follow-up at pre-determined +me points to see who died from

lung cancer

compare mortality between groups

Is mortality higher among smokers?

SMOKERS

NON-SMOKERS

Lung cancer death

Survivor

Lung cancer death Survivor

follow-up at pre-determined +me points to see who died from

lung cancer

POPULATION

TIME

Another quick recap

We can inves@gate associa@ons between exposures (risk factors) and outcomes (disease, death) using dierent epidemiological

study designs

Historical trends in exposure and disease

Ecological studies: plot aggregate sta@s@cs of exposure and outcome for dierent popula@ons, e.g. ci@es, countries, and look for correla@ons

Case-control studies: compare exposure history in cases of disease and disease-free controls

Cohort studies: follow up exposed and unexposed groups over @me and compare risk of acquiring disease (incidence)

Researchers recruited children with leukaemia and children without leukaemia into a study. They found that leukaemia children were more likely than non-leukaemia children to have been exposed to X-rays in utero. What

type of study is this?

This is a case-control study we compare cases of leukaemia with non-leukaemia controls to see if cases are more likely to

have been exposed to X-rays in utero

A study inves@gated whether air pollu@on is linked to heart disease deaths. Researchers compared data on average air pollu@on levels and heart disease

mortality from 25 ci@es. What type of study is this?

This is an ecological data aggregated (not individual) data on air pollu@on and heart disease mortality are

compared between ci@es

CONTROL MEASURES TOBACCO PROJECTIONS

Tobacco-related mortality is expected to rise by 40-50% in low/middle-

income countries by 2030

Mathers. PLoS Medicine 2006; 3(11): e442

Deaths in low/middle-income countries Donor funding in low/middle-income countries

CONTROL MEASURES WHAT WORKS?

In 2005, the WHO Framework Conven@on on Tobacco Control (FCTC) was

ra@ed by the UN

In 2008, WHO introduced MPOWER, a package of 6 evidence-based measures to reduce tobacco use

Taxa+on 10% increase in tobacco price reduced consump@on by 4% in

high-income countries

Smoking reduc@ons more pronounced in young people

Increased tax revenue from tobacco can be used to directly fund health programmes

240 Filipinos die each day from tobacco-related diseases

Increased tax on tobacco raised US$1.2 billion in the rst year,

used to provide healthcare to an

addi@onal 14 million families

Bans on Tobacco Adver+sing, Promo+on and Sponsorship (TAPS)

TAPS includes direct and indirect adver@sing: Commercials Events sponsorship Product placement Corporate social responsibility ac@vi@es Branding Price discounts In-store displays

Since 1998, the Master Se"lement Agreement in the US restricts product

placement deals with the movie industry

Brand appearances and tobacco screen @me have decreased yearly in the 100 top-grossing Hollywood

lms

Bergamini et al. JAMA Pediatrics 2013;167(7):634-9

Packaging

Restrict use of misleading descriptors, e.g. LIGHT, SMOOTH, GOLD

No evidence that these are less

harmful

Packaging

Use of health warnings

Graphic pictures more eec@ve than plain text

Packaging

Reduces appeal, par@cularly to children

Helps to make health warnings more visible

Plain packaging

Smoking restric+ons

Restrict smoking in the work place and public spaces

Reduce exposure to second hand

smoke

Second hand smoke kills

600,000 people a year h"p://www.who.int/tobacco/mpower/publica@ons/en_{i_mpower_brochure_p.pdf?ua=1

Smoking cessa+on Integrate cessa@on advice into rou@ne

healthcare Access to quitlines and cessa@on

treatments Train healthcare workers in cessa@on

support

Advice from a healthcare worker increases quit rates

Summary

Lung cancer is the most common cancer worldwide

Tobacco accounts for ~70% of cases worldwide Major progress in high-income countries, but challenges ahead in low/middle-income countries

Eec+ve control measures outlined in WHO Framework Conven+on on Tobacco Control (FCTC) through MPOWER measures

We measure how common a disease is using: Prevalence: percentage of popula+on with disease Incidence: measures occurrence of new disease

We can compare disease frequency between popula+ons, e.g. using risk ra+os But need to account for important dierences that aect risk of disease, e.g. age, sex

We can study associa+ons between diseases and exposures using dierent study designs: Ecological Cross-sec+onal Case-control Cohort