1. Quitting smoking after diagnosis of lung, bladder or upper aerodigestive tract (UAT) cancer: is it supported in primary care and does it improve prognosis?
Dr Amanda Farley
University of Birmingham

2. Background
Smoking has been causally linked to a number of cancer including lung, UAT and bladder cancer
There is mounting evidence that continued smoking after diagnosis affects risk of complications and QOL and a limited number of studies also show that continued smoking may affect prognosis.
Despite this, smoking cessation care is not well integrated into cancer care and management of smoking in cancer patients is not incentivised in Primary Care.
Using routinely collected anonymised primary care data from the Clinical Practice Record Datalink (CPRD) we:
(1) Compared management of smoking in patients with three smoking related cancers (lung, bladder, H&N) with patients with CHD and investigated if any differences in management were influenced by introduction of incentives.
(2) Investigated the effect of quitting smoking on all cause, cancer specific mortality and death due to index cancer.

3. Methods – management of smoking in primary care
Extracted cases diagnosed between , current smokers and <3 years ex-smokers matched on smoking status, year of diagnosis and general practice
Lung n = 9347
Bladder n = 2050
UAT n =
Total study n= cancer CHD (total n=24786)
Using adjusted logistic regression, we compared the following between cancer and CHD patients:
Smoking status updated
Advice to quit
Prescription of smoking cessation medications
We tested the effect of incentivisation by comparing change in outcome pre- and post-QOF between CHD and cancer patients using an interaction term (pre/post QOF x case/control)

4. Results - Updating smoking status
UAT
UAT
All OR 0.18 (0.17, 0.19)
Lung OR 0.14 (0.13, 0.15)
UAT OR 0.27 (0.22, 0.33)
Bladder OR 0.38 (0.33, 0.44)
1 year survivors only
All OR 0.26 (0.23, 0.29)
Lung OR 0.25 (0.22, 0.29)
UAT OR 0.23 (0.17, 0.30)
Bladder OR 0.28 (0.22, 0.34)

5. Results - Updating smoking status
UAT
UAT
All OR 0.18 (0.17, 0.19)
Lung OR 0.14 (0.13, 0.15)
UAT OR 0.27 (0.22, 0.33)
Bladder OR 0.38 (0.33, 0.44)
1 year survivors only
All OR 0.26 (0.23, 0.29)
Lung OR 0.25 (0.22, 0.29)
UAT OR 0.23 (0.17, 0.30)
Bladder OR 0.28 (0.22, 0.34)

6. Results - Updating smoking status, effect of incentives
Was there a difference in the increase in
updating between cancer and CHD after
incentives were introduced?
incentives
p = 0.95

7. Results – Advice to quit
UAT
UAT
All OR 0.38 (0.36, 0.40)
Lung OR 0.28 (0.26, 0.30)
UAT OR 0.50 (0.41, 0.60)
Bladder OR 0.87 (0.76, 0.99)
1 year survivors only
All OR 0.60 (0.55, 0.66)
Lung OR 0.49 (0.43, 0.56)
UAT OR 0.58 (0.46, 0.74)
Bladder OR 0.84 (0.70, 0.99)

8. Results – Advice to quit
UAT
UAT
All OR 0.38 (0.36, 0.40)
Lung OR 0.28 (0.26, 0.30)
UAT OR 0.50 (0.41, 0.60)
Bladder OR 0.87 (0.76, 0.99)
1 year survivors only
All OR 0.60 (0.55, 0.66)
Lung OR 0.49 (0.43, 0.56)
UAT OR 0.58 (0.46, 0.74)
Bladder OR 0.84 (0.70, 0.99)

9. Results – Advice to quit, effect of incentives
Was there a difference in the increase in
updating between cancer and CHD after
incentives were introduced?
incentives
p = 0.02

10. Results – Advice to quit, effect of incentives
Lung p = 0.007
UAT p = 0.31
Bladder p = 0.54
incentives

11. Results - Smoking cessation prescriptions
UAT
UAT
All OR 0.67 (0.63, 0.73)
Lung OR 0.58 (0.53 to 0.63)
UAT OR 1.00 (0.80 to 1.24)
Bladder OR 0.96 (0.81 to 1.16)
1 year survivors only
All OR 1.05 (0.94, 1.17)
Lung OR 1.06 (0.91 to 1.23)
UAT OR 1.18 (0.89 to 1.55)
Bladder OR 1.02 (0.83 to 1.25)

12. Results - Smoking cessation prescriptions
UAT
UAT
All OR 0.67 (0.63, 0.73)
Lung OR 0.58 (0.53 to 0.63)
UAT OR 1.00 (0.80 to 1.24)
Bladder OR 0.96 (0.81 to 1.16)
1 year survivors only
All OR 1.05 (0.94, 1.17)
Lung OR 1.06 (0.91 to 1.23)
UAT OR 1.18 (0.89 to 1.55)
Bladder OR 1.02 (0.83 to 1.25)

13. Results – Smoking cessation pharmacotherapy prescriptions, effect of incentives
Was there a difference in the increase in
updating between cancer and CHD after
incentives were introduced?
incentives
p = 0.70

14. Summary - management Status update and advice to quit
Cancer patients significantly less likely to have smoking status updated or be advised to quit compared with CHD patients in the first year after diagnosis
Not explained by incentivisation for CHD
Not explained by survival to 1 year
Not explained by consultation rates
GP barriers?
Prescription of smoking cessation medications
Most cancer and CHD patients are not prescribed smoking cessation medications in their first year after diagnosis. Incentives made only a small difference to prescribing.
CHD patients were also found to be more likely to quit that cancer patients in first year after diagnosis
There is an opportunity to offer smoking cessation support in primary care for cancer patients that is being missed.

15. Methods - prognosis
Extracted cases diagnosed between 1999 and 2013 who were recorded as smoking at diagnosis and survived for at least 1 year
Classified patients as continued smokers/quitters/missing based smoking status recorded in 1st year after diagnosis:
Lung UAT Bladder
Continued smokers (39%) 281 (37%) 850 (49%)
Quitter (27%) 216 (29%) 356 (21%)
Missing (34%) 260 (34%) 857 (30%)
Using cox proportional hazard modelling, estimated HRs for quitters compared with continued smokers adjusted for key confounders
Sensitivity analyses to account for missing data

16. Results - All cause mortality
Lung cancer (n= 2982)
UAT cancer (n=757)
Bladder cancer (n=2063)
Quit v continued smoking*
HR 0.82 (0.73, 0.92)
Adding unknowns to continued smokers*
HR 0.81 (0.73, 0.89)
Multiple imputation**
HR 0.82 (0.74, 0.92)
Quit v continued smoking*
HR (0.54, 1.00)
Adding unknowns to continued smokers*
HR 0.71 (0.55, 0.93)
Multiple imputation**
HR 0.81 (0.58, 1.14)
Quit v continued smoking*
HR 1.00 (0.79, 1.26)
Adding unknowns to continued smokers*
HR 0.97 (0.78, 1.19)
Multiple imputation**
HR 1.02 (0.81, 1.30)
* adjusted for gender, age, comorbidity, treatment
**adjusted for gender, age, IMD, alcohol consumption, comorbidity, treatment

17. Results - Cancer specific mortality
Lung cancer (n=1 635)
UAT cancer (n= 428)
Bladder cancer (n=1 733)
Quit v continued smoking*
HR 1.29 (0.79, 2.09)
Adding unknowns to continued smokers*
HR 1.11 (0.71, 1.73)
Multiple imputation**
HR 1.23 (0.81, 1.86)
Quit v continued smoking*
HR 0.88 (0.75, 1.03)
Adding unknowns to continued smokers*
HR 0.85 (0.73, 0.98)
Multiple imputation**
HR 0.89 (0.76, 1.04)
Quit v continued smoking*
HR 0.92 (0.56, 1.50)
Adding unknowns to continued smokers*
HR 0.94 (0.61, 1.44)
Multiple imputation**
HR 0.84 (0.48, 1.45)
* adjusted for gender, age, comorbidity, treatment
**adjusted for gender, age, IMD, alcohol consumption, comorbidity, treatment

18. Results - Death due to lung cancer
Lung cancer (n=1 635)
UAT cancer (n= 428)
Bladder cancer (n=1 733)
Quit v continued smoking*
HR 0.87 (0.74, 1.04)
Adding unknowns to continued smokers*
HR 0.84 (0.73, 0.98)
Multiple imputation**
HR 0.90 (0.77, 1.05)
Quit v continued smoking*
HR 0.77 (0.43, 1.40)
Adding unknowns to continued smokers*
HR0.78 (0.45, 1.34)
Multiple imputation**
HR 0.75 (0.42, 1.35)
Quit v continued smoking*
HR 1.23 (0.76, 2.02)
Adding unknowns to continued smokers*
HR 1.11 (0.71, 1.73)
Multiple imputation**
HR 1.25 (0.71, 2.20)
* adjusted for gender, age, comorbidity, treatment
**adjusted for gender, age, IMD, alcohol consumption, comorbidity, treatment

19. Conclusions
Strongest evidence that quitting smoking reduces risk of death in lung cancer patients, also suggestion of this for UAT cancer although confidence intervals were wide
Quitting smoking unlikely to affect prognosis for bladder cancer patients
Support for smoking cessation needs to be better integrated into care for cancer patients

20. Acknowledgements Funding a.c.farley@bham.ac.uk
Constantinos Koshiaris – Statistician, University of Oxford
Jason Oke – Statistician, University of Oxford
Paul Aveyard – Professor of Behavioural Medicine, University of Oxford
Richard Stevens – Statistician, University of Oxford
Lisa Szatkowski – Associate professor, University of Nottingham
Ronan Ryan – Research Fellow, University of Birmingham
Funding
NIHR School of Primary Care Research