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h"p://www.pri.org/stories/2012-12-03/video-land-tobacco
Session 2: Smoking and lung cancer
Dr Clarence Tam([email protected]) 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