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The treatment of tobacco dependence: an effective treatment for lung cancer
Paul AveyardDepartment of Primary Care Health Sciences
University of OxfordWith special thanks to Amanda Farley (nee Parsons)
Conflicts of interest
• I have done research and consultancy for the manufacturers of smoking cessation medication
For every year a person smokes
after the age of 35 years, they will
lose 3 months of life
40 50 60 70 80Age
0
500
1000
1500
Lu
ng
ca
nc
er
de
ath
s p
er
10
0,0
00
Current
smokers
Never
smokers
quit 30-39
quit 40-49
quit 50-54
quit 55-59
quit 60-64
Halpern JNCI 1993: CPS2 data
Lung cancer risk by age of quitting
Does smoking cessation improve the prognosis of lung cancer?
• Parsons et al BMJ 2010:340:b5569
Methods 1
Search
Medline, Embase, CINAHL, Web of science and CENTRAL (database origin – Dec 2008).
MeSH term and text word search strategy
Title and abstract search.
Data extraction and quality assessment
Two reviewers
Predesigned tools.
Population and study characteristics, cigarette smoking and outcome.
Continued smokers v quit at diagnosis
Methods 2
• Data synthesis
– Data extracted as hazard ratios and 95% CI
– Combined using random effects inverse variance method
– I2 test for statistical heterogeneity
• Life table modelling– Estimated 5 year survival of 65 year old NSCLC
and SCLC population who quit smoking at diagnosis and who continued
– Risk estimates generated from the review
Results – 1. Included studies
6198 failed to meet
inclusion criteria
Title search
(n=6466)
Full text search
(n=268)
258 failed to meet
inclusion criteria
10 studies compared risk in patients who
continued smoking to those who quit at
diagnosis
Results – 2. Study characteristics
Author (year) n
smokers
% cont
smokers
males
(%)
Stage 1-
3A/ limited
(%)
Treatment Study quality
score
NSCLC studies
Baser (2006) 93 51 49 90 Mixed 9
Kawaguchi (2006) 35 46 81 100 Mixed 8
Nia (2005) 204 83 86 92.1 Mixed 7
Saito-Nakaya (2006) 98 6 60.9 81 Surgery 7
Shiba (2000) 69 12 72 100 Surgery 5
SCLC studies
Johnstone-Early (1980) 92 62 n/r 29 Cht/Rt 6
Kawahara (1988) 64 52 60 100 Cht/Rt 8
Tucker (1997) 395 54 55 79 Cht/Rt 7
Videtic (2003) 186 42 60 100 Cht/Rt 5
Yoshida (1996) 59 44 80.3 85 Cht/Rt 8
What where the outcomes examined?
• 5 studies estimated the impact of continued smoking on all cause mortality (4 NSCLC, 2 SCLC),
• 4 studies on the development of second primaries (1 NSCLC, 3 SCLC)
• 2 studies on recurrence of the primary tumour (1 NSCLC, 1 SCLC)
The effect of continued smoking on all cause mortality in non-small cell lung cancer
1
1 Adjusted for age, sex, type of operation, histology, postoperative radiotherapy, localisation, N status, T status, previous
malignancies and stage x smoking.
Non-small cell other outcomes
• One study reported no significant increase in the occurrence of second primaries (HR 2.29 (0.50-10.58)
• One study reported HR 1.86 (1.01-3.41) for risk of recurrence
The effect of continued smoking on all cause mortality in small cell lung cancer
1 Adjusted for age, sex and volume of limited disease
Other outcomes small cell
• 3 studies HR 4.31 (1.09-16.98) for second primaries
• 1 study HR 1.26 (1.06-1.50) for recurrence
Modelled small cell and NSCLC 5 year survival
0
10
20
30
40
50
60
70
80
NSCLC SCLC
Continued
Quit
70%
63%
33%29%
Discussion
• How confident are we that these results reflect a true effect?
• When adjustment made for confounders, the effect size increased
• Publication bias
• Consistent effect size across studies
• Evidence that continued smoking increased the risk of recurrence and second primaries
• Preliminary evidence that continued smoking significantly reduces survival
• Smoking cessation beneficial for curatively treated patients
“I’m too stressed to stop smoking now”
Snapshots from a systematic review in progress (Taylor et al)
Negative affect
Negative affect
Smokers
Smokers
Negative affect
Negative affect
Quitters
Continuing
smokers
Change
Time (6 months)
Change
Psychological distress
Study or Subgroup
2.1.1 All populations
Balduyck EORTC QLQ-C3 12M
Blalock PANAS-N 3M
Chassin NA 6Y
Croghan SF-36 MH comp 12M
Mino GHQ-30 12M
Mitra SF-36 MH sub 3-4Y
Quist-Paulsen CAST 12M
Sarna SF-36 MH comp 8-9Y
Steinberg K-6 6M
Stewart SF-36 MH sub 6M
Subtotal (95% CI)
Heterogeneity: Tau² = 0.01; Chi² = 16.36, df = 9 (P = 0.06); I² = 45%
Test for overall effect: Z = 3.48 (P = 0.0005)
Weight
1.6%
1.7%
12.4%
9.9%
4.4%
5.8%
11.7%
28.0%
11.0%
13.5%
100.0%
IV, Random, 95% CI
-0.62 [-1.51, 0.28]
-0.21 [-1.08, 0.65]
-0.23 [-0.49, 0.02]
-0.37 [-0.68, -0.07]
-0.44 [-0.95, 0.08]
-0.60 [-1.03, -0.16]
0.00 [-0.27, 0.27]
-0.07 [-0.11, -0.03]
-0.29 [-0.57, -0.01]
-0.17 [-0.41, 0.06]
-0.21 [-0.33, -0.09]
Std. Mean Difference Std. Mean Difference
IV, Random, 95% CI
-0.5 -0.25 0 0.25 0.5
Favours quitters Favours smokers
Depression
Study or Subgroup
3.8.1 All populations
Berlin (cont) HAM-D 11W
Blalock CES-D 3M
Busch CES-D 12M
Dawkins HADS-D 3M
Kahler CES-D 6M
Kinnunen MMPI-2-D 5Y
Moreno-Coutino HAM-D 12M
Munafo EPDS 35M
Solomon BSI-D 7W
Tonnesen depression 4M
Subtotal (95% CI)
Heterogeneity: Tau² = 0.02; Chi² = 15.69, df = 9 (P = 0.07); I² = 43%
Test for overall effect: Z = 1.61 (P = 0.11)
Weight
9.3%
2.9%
11.2%
7.5%
9.6%
18.5%
1.3%
20.4%
11.3%
7.9%
100.0%
IV, Random, 95% CI
-0.30 [-0.73, 0.12]
-0.53 [-1.41, 0.36]
-0.30 [-0.67, 0.07]
-0.39 [-0.88, 0.11]
-0.28 [-0.69, 0.14]
-0.21 [-0.42, 0.01]
0.47 [-0.91, 1.85]
-0.09 [-0.27, 0.09]
0.01 [-0.35, 0.38]
0.64 [0.16, 1.12]
-0.13 [-0.29, 0.03]
Std. Mean Difference Std. Mean Difference
IV, Random, 95% CI
-0.5 -0.25 0 0.25 0.5
Favours quitters Favours smokers
Anxiety
Study or Subgroup
4.6.1 All populations
Aveyard STAI 6M
Becona STAI-T 12M
Chassin Stress 6Y
Dawkins HADS-A 3M
Hajek stress 12M
Manning PSS-14 6M
Solomon BSI-A 7W
Subtotal (95% CI)
Heterogeneity: Tau² = 0.02; Chi² = 10.20, df = 6 (P = 0.12); I² = 41%
Test for overall effect: Z = 3.74 (P = 0.0002)
Weight
17.0%
11.9%
17.3%
7.1%
23.0%
12.4%
11.2%
100.0%
IV, Random, 95% CI
-0.62 [-0.88, -0.36]
-0.09 [-0.43, 0.26]
-0.36 [-0.61, -0.10]
-0.19 [-0.68, 0.30]
-0.22 [-0.40, -0.03]
-0.25 [-0.58, 0.09]
-0.06 [-0.43, 0.30]
-0.28 [-0.43, -0.13]
Std. Mean Difference Std. Mean Difference
IV, Random, 95% CI
-0.5 -0.25 0 0.25 0.5
Favours quitters Favours smokers
0
5
10
15
20
25
30
35
40
45
50
Baseline 6 months
Whole sample
Psychiatricdisorder
Smoke to cope
% q
ua
lify
ing a
s a c
ase
What happens to patients now and what do patients want?
• Interview study
– Farley et al, in preparation
• Patients treated curatively
– Lobectomy/pneumonectomy
– VATS
– Radical radiotherapy
• Discharged from care
• Distressed, breathless, in pain
What did patients say?
• The most common thing was that staff did not talk to them about their smoking
• Some found it difficult to admit to smoking
• All patients wanted to discuss their smoking with the staff
• All patients would rather be non-smokers
• Some experienced an ‘epiphany’ and threw away their cigarettes and never looked back
• Some relapsed to smoking
• Almost all continuing smokers relapsed and this was not a choice
• Relapse occurred after leaving hospital
Something made me started worrying I think... it just started building up, having to ring for ambulances to get to the hospital for blood and this that and the other. And it more or less got on top of me an all. I’ve got to have a cigarette, so I did. I had one and then of course the craving came back 3 o’clock in the morning, I’ve got to have a fag. I need a fag. But you don’t give in. Same first thing in the morning. Got to have a fag. But the craving’s there all the time... PID003
When I did stop smoking I felt marvellous, because I did stop for about, uh three weeks, not long, but I felt so good. 'Well one won't hurt' because I felt so well...it's when I feel well, that's my danger time. I mean it's not when I'm stressed...It's when I feel good I think." PID023
Nicotine addiction
27
Ventral tegmental area
Nucleus
accumbens
Mechanisms
Associative learning
Pleasure
Nicotine hunger
Withdrawal
Higher functions
Cochrane review: smoking cessation interventions for hospitalised patients
• Cochrane review of smoking cessation for hospitalised patients– 15 minutes in-hospital counselling OR 1.15 (0.80-1.67)
– Longer in-hospital counselling OR 1.08 (0.89-1.29)
– Longer in-hospital counselling with brief post-discharge support OR 1.09 (0.90-1.31)
• Counselling that starts in hospital but is complemented by at least 4 weeks of further support– OR 1.65 (1.44-1.90)
Evidence for the efficacy of smoking cessation treatment from the Cochrane
reviews• Medication
– Varenicline RR 2.33 (1.95 to 2.80)
– NRT RR 1.58 (1.50 to 1.66)
– Combination NRT vs single form RR 1.35 (1.11 to 1.63)
– Bupropion RR 1.69 (1.53 to 2.85)
– Nortriptyline RR 2.03 (1.48 to 2.78)
– Cytisine RR 3.4 (1.7 to 7.1)
• Remote support– Internet/text RR 1.8 (1.4-2.3)
– Telephone OR 1.41 (1.27 to 1.57)
29
The best way to help your patients stop smoking
• Prescribe and refer to a behavioural support programme
• Physicians randomised to encourage and support cessation themselves or to refer to a quit line
• People who got quit line support were 2-3 times more likely to succeed– 1.92 (95% CI 1.17–3.13] at 3 months
– 2.86 (95% CI 0.94–8.71] at 12 months• Family Practice (2008) 25(5): 382-389 first published online August 9,
2008 doi:10.1093/fampra/cmn046
The second best way- you give brief advice and support
• Set a day as the last day of smoking.
• Think of yourself as a non-smoker. Smoking is not even an option. Even one cigarette will seriously reduce your chance of making it.
• Plan ways to deal with the cigarettes that will be hardest to let go; often one at the start of the day but also ones that you smoke in the evening. This may involve changing the normal routines to avoid cues to smoke.
• Have a plan for dealing with cravings
• Alcohol is a major cause of relapse. Perhaps avoid it altogether for the first week or two. Do not get drunk.
• Review regularly
Dealing with lapses
• The golden rule is to continue medication
• On NRT consider adding another form
• Ask the patient ‘Tell me what you will do next time a similar situation occurs’ [other than smoke]– Make sure that they come up with a plan- not ‘I’ll
try harder’
• Ensure they understand the Not a Puff Rule and recommit to total abstinence
Putting it all together: what should you do?
• Talk about smoking
• Show that you are sympathetic to their plight as smokers
– “Cigarettes are really addictive”
• Make it easy to confess to smoking
– “...so many patients find they go back to smoking... I wonder whether you have...”
• Deal with the gap between patients optimism and reality....arrange a treatment programme
– Press treatment on the patient
– Arrange ongoing support
– At the very least ensure that they have a plan for dealing with lapses
• Deal with guilt at failed quitting
– “We might not get you quit this time, but if we stick at it we’ll find something that helps you.”
‘I’ve tried everything doctor. What else have you got for me?’
Options to consider
• Some options for ‘standard’ quit attempts– Nortriptyline– Increasing the dose
• Some options for smokers who’ve tried everything or are ambivalent– Being patient– Start again– Longer treatment courses before quitting
Study Design
Baseline TQDWeek 1
+ 12 weeksWeek 2 Week 3
Varenilcine
Placebo
Visit Visit Visit Visit
+ 1 week
+ 2 weeks
+ 3 weeks
+ 4 weeks
Visit Visit VisitPhone Phone Phone
+ 24 hrs
Phone
Hajek et al, Archives of
Internal Medicine
2011;171(8):770-777
Effect on cotinine prior to TQD
0
50
100
150
200
250
300
350
400
450
Baseline Week 3 Quit Date
Saliv
ary
co
tin
ine c
on
cen
trati
on
(n
g/m
l)
Time
varenicline (n=47) placebo (n=41)
Pre-quit strength of urges to smoke
1
2
3
4
5
Baseline Week 1 Week 2 Week 3 Quit Day
Rating(1=much stronger;
3=same as before; 5=much weaker)
Time
varenicline (n=39) placebo (n=37)
Change in enjoyment of cigarettes
1
2
3
4
5
Baseline Week 1 Week 2 Week 3 Quit Day
Rating(1=much more
enjoyable; 3=same as
before; 5=much less enjoyable)
Time
varenicline (n=35) placebo (n=36)
Effect on quit rates
0%
10%
20%
30%
40%
50%
60%
4 12
Varenicline
Placebo
You can tell if your strategy is likely to work by the degree of reduction
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
4 12
Reducer
Non-reducer
NRT patches (might) work too
Or ask your patient to do it step by step
• Smokers who have no immediate plans to quit but are prepared to try to reduce their smoking
• Double the rate of abstinence with NRT
• The costs of treating smokers to reduce or treating them to quit abruptly are roughly equal
Conclusions
• Smoking appears to be a risk factor for recurrence and death
• Smoking does not make patients happier- it makes them feel worse
• Clinicians are reluctant to address this but patients want them to
• Treatment requires starting (prior to) during hospital but crucially continuing after hospital
• Patients deserve treatment, which is cheap, simple, and proven effective
