Nicotine & Tobacco Research Advance Access published February 1, 2016 Nicotine & Tobacco Research, 2016, 1–5 doi:10.1093/ntr/ntw010 Brief report
Brief report
Brief Tailored Smoking Cessation Counseling in a Lung Cancer Screening Population is Feasible: A Pilot Randomized Controlled Trial Downloaded from http://ntr.oxfordjournals.org/ at Flinders University of South Australia on February 3, 2016
Henry M. Marshall PhD, FRACP, Deborah A. Courtney BN, Linda H. Passmore BN, Elizabeth M. McCaul RN, Ian A. Yang PhD, FRACP, Rayleen V. Bowman PhD, FRACP, Kwun M. Fong PhD, FRACP University of Queensland Thoracic Research Centre, The Prince Charles Hospital, Brisbane, Australia Corresponding Author: Henry M. Marshall, PhD, FRACP, University of Queensland Thoracic Research Centre, The Prince Charles Hospital, Rode Road, Brisbane 4032 QLD, Australia. Telephone: 61-7-3139-4000; Fax: 61-7-3139-4510; E-mail: Henry. [email protected]
Abstract Introduction: Maximizing smoking abstinence in lung cancer screening participants is important to reduce individual risk of disease and improve screening cost-effectiveness; however, the optimal strategy remains undefined. We hypothesized that a single session of tailored face-to-face counseling on the day of screening CT scan, coupled with audio and printed cessation information would be feasible to deliver in a CT screening trial. Methods: We randomized volunteer smokers in the Queensland Lung Cancer Screening Study to intervention (counseling session, audio quit materials, printed quit materials, Quitline contact details) or control group (printed quit materials, Quitline contact details). Participants self-reported point prevalence quit rates at 1 year. Results: Fifty-five smokers were enrolled; 28 randomized to intervention and 27 controls. Median cigarette consumption was 25/day; 54/55 smoked at least 15 cigarettes per day. Median smoking duration was 46 years. Median Fagerström dependence score was 6. In total 58% did not report any quit attempt in the prior 12 months. Mean duration of counseling was 26.5 minutes. After 1 year, four participants (14.3%) in the intervention group and five participants (18.5%) in the control group had quit (P = .74). Combined annual point prevalence quit rate was 16.4%. Conclusions: Although feasible to deliver a single session of tailored counseling on the day of screening this intervention had no discernible impact on cessation over and above printed materials and Quitline access. As participants exhibited hardcore smoking characteristics, more intensive strategies, in larger cohorts, should be explored. Implications: The optimal smoking cessation strategy within a lung cancer screening program is not known. This study demonstrates that a single session of counseling can be feasibly delivered on the day of screening but may not have been intensive enough for long-term, hard-core smokers.
Introduction Low-dose computed tomography screening can reduce lung cancer mortality1 and may provide a “teachable moment” for smoking
cessation. Smoking cessation should be a core component of lowdose computed tomography screening.2,3 The process of low-dose computed tomography lung cancer screening itself does not appear to influence smoking behavior but positive CT scan results are
© The Author 2016. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: [email protected].
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Methods We tested the hypothesis that a single face to face session of tailored MI counseling supported by take-home audio quit educational materials (provided on an MP3 player) plus standard printed quit materials and Quitline30 telephone helpline referral would (1) be feasible when delivered on the day of screening and (2) result in higher selfreported point prevalence quit rates at 1 year compared to standard printed materials and Quitline referral alone. Counseling included discussion of lung function results and lung cancer risk.31 Smokers in the Queensland Lung Cancer Screening Study32,33 (age 60–74 years; ≥30 pack year smoking) were invited to enroll in the sub-study by letter prior to each scheduled CT screening scan. Institutional Research Ethics Committee approval was granted. Volunteers were randomized 1:1 to intervention (MI counseling, non-tailored audio materials, non-tailored printed materials, Quitline details) or control groups (nontailored printed materials, Quitline details) using a random number generator. Group allocation was concealed at randomization. To limit hospital visits and increase participant convenience the MI intervention was scheduled to coincide with their upcoming annual screening CT, however this precluded discussion of scan reports which were typically reported 1 week after acquisition. For consistency, a single thoracic physician (HMM) provided the counseling. Thirty audio tracks, based on Quitline materials (duration 0.5 to 4 minutes), and three relaxation tracks were provided on an MP3 player (Sansa Clip, SanDisk Corporation, Milpitas, CA). Pharmacological therapies were discussed but participants were directed to their family doctor for prescription. The primary outcome, self-reported point-prevalence smoking status at 12 months, was determined by response to the question “Do you NOW smoke cigarettes (one or more cigarettes per week)?” Self-report was validated by exhaled carbon monoxide (ECO) when possible (Bedfont Smokerlyser, Bedfont Scientific Limited, Rochester, United Kingdom); a threshold of at least 10 parts per million (ppm) indicating continued smoking.34 ECO was not always obtainable at the 12-month time point because the CT protocol allowed scans to take place between 11 and 15 months after the previous scan. Secondary outcomes such as change in readiness to quit, cigarettes per day, number of quit attempts were not assessed in this pilot study.
Results Out of 256 participants, 121 (47.3%) were baseline smokers or recent quitters (self-reported current smoker n = 109, or quit 55 years; ≥30 pack year smoking) found 36/63 participants (57.1 %) quit for at least 6 months following psychologist-delivered cognitive-behavioral counseling plus pharmacotherapy.22 Behavioral counseling plus pharmacotherapy in the MILD screening trial (age ≥49 years; ≥20 pack year smoking) produced 1-year continuous abstinence rates of 19.8% (37 of 187 patients).23 CT screening trials without counseling report quit rates of 14% to 15% at 1 year24,25 and 24% to 29% after 5 to 6 years.26,27 Annual point prevalence quit rates ranged from 11.6% to 13.4% in the NLST.28 Background quit rates are often considered to lie in the range of 5% to 10% per year.20,29
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Table 1. Baseline Characteristics of Smokers in the Smoking Cessation Sub-Study Variable, n(%) or median [IQR]
Intervention group, n = 28
63.0 [5] 17 (63.0) 15 (55.6) 8 (29.6) 7 (25.9)
63.0 [6] 18 (64.3) 15 (53.6) 8 (28.6) 11 (39.3)
25.0 [10] 16.0 [3] 57.5 [32] 46.0 [6] 6.0 [3] 11 (40.7) 0/13/12/1 (0/48.1/44.4/3.7) 14 (51.9)
25.0 [14] 17.0 [3] 57.5 [28] 46.0 [5] 6.0 [4] 12 (42.9) 1/18/9/0 (3.6/64.3/32.1/0) 13 (46.4)
4 (14.8) 14 (51.9) 20/5/2/0/0 (74.1/18.5/7.4/0/0) 90.2 [31.3] 14 (51.9)
5 (17.9) 14 (50.0) 19/5/1/3/0 (67.9/17.9/3.6/10.7/0) 86.7 [15.5] 18 (64.3)
12 (44.4) 7 (25.9) 3 (11.1) 3 (11.1) 12 (44.4) 4 (14.8) 5 (18.5) 4 (14.8) 2 (7.4)
16 (57.1) 9 (32.1) 0 4 (14.3) 6 (21.4) 8 (28.6) 2 (7.1) 8 (28.6) 5 (17.9)
IQR = interquartile range; LDCT = Low-dose computed tomography. a Fagerström Test for Nicotine Dependence. b Four categories: (1) No plan to quit in next 6 months; (2) Possible plan to quit in the next 6 months; (3) Definite plan to quit in the next month and (4) missing data. c Self-efficacy score 4 or 5 on a scale 1 to 5: “Do you believe you can stop smoking?” 1 being lowest level of belief and 5 being the highest. d Includes prior physician diagnosis of chronic obstructive pulmonary disease, emphysema, chronic bronchitis or chronic asthma. e Medical Research Council (MRC) dyspnea scale Grade 1 to 5 (1: Breathless only with strenuous exercise; 2: Short of breath when hurrying on the level or up a slight hill; 3: Slower than most people of the same age on a level surface or Have to stop when walking at my own pace on the level; 4: Stop for breath walking 100 meters or after a walking few minutes at my own pace on the level; 5: Too breathless to leave the house). f Noncalcified nodule ≥ 4mm diameter detected on LDCT; NRT—nicotine replacement therapy; FEV1%—Forced expiratory volume in 1 second, percent predicted.
Bupropion and hypnosis, only 7 (13%) participants had tried counseling. Expressions of self-efficacy and readiness to quit appeared reasonably high. Twenty-three out of 55 (42%) participants had made at least one quit attempt in the previous year and 32/55 (58%) did not report any quit attempt in the past 12 months. At 12 months, nine (16.4%) participants had quit (95% CI 9% to 28%); four (14.3%) in the intervention group and five (18.5%) in the control group (Fisher’s Exact Test P = .74). One intervention group and three control group quitters had ECO < 10 ppm, the remainder were not tested. Three out of 28 (10.7%) intervention group participants and 2/27 (7.4%) control group participants did not return 12-month questionnaires and were assumed to be smokers. Concordance between self-report and ECO measurement across all Queensland Lung Cancer Screening Study participants was 92.9% and 92.3% for nonsmokers and current smokers respectively (346 ECO measurements in 227 participants). Familiarity with MP3 players was low; six participants (11%) owned an MP3 player whereas 47/55 (85%) owned a computer.
Twelve out of 28 (43%) intervention group participants returned a questionnaire regarding the MP3 player; 10 participants used it five times or less, two used it more than five times. Nine participants who used it at least once rated usability as 4 out of 5.
Discussion We found it was feasible to deliver a single tailored session of MI counseling on the day of CT screening combined with nontailored take-home audio cessation materials. It appeared that MP3 players could be operated even in the absence of prior experience. The combined 12-month quit rate of 16.4% is consistent with other reports. Although biochemical validation was not achieved in most participants, concordance between ECO and self-report was more than 92% across Queensland Lung Cancer Screening Study as a whole, in line with previous studies.24,27 Our pilot study lacked statistical power to inform whether the intervention had an impact on cessation rates, however, as it had no clear advantage or even a trend
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Sociodemographic Age, years Male Education, >high school Lives with smoker >14 standard alcoholic drinks per week Smoking and quitting Cigarettes per day Age started smoking, years Pack years Duration of smoking, years Nicotine dependency scorea ≥1 quit attempts in past year Readiness to quitb High self-efficacyc Other Obstructive lung disease diagnosisd Cough symptom MRC Dyspnea scoree FEV1% predicted Positive baseline screening scanf Previous smoking cessation therapy NRT patch NRT gum NRT inhaler NRT lozenge Varenicline Bupropion Acupuncture Hypnosis Counseling /quit program
Control group, n = 27
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Funding Queensland Health, Smart State Research Grant (388600); National Health and Medical Research Council (NHMRC) National Research Centre for Asbestos-Related Diseases (NRCARD) (440812); The Prince Charles Hospital Foundation (FRC0207-24).
Declaration of Interests None declared.
References 1. National Lung Screening Trial Research Team. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011;365(5):395–409. doi:10.1056/NEJMoa1102873. 2. Moyer VA. Screening for lung cancer: U.S. preventive services task force recommendation statement. Ann Intern Med. 2014;160(5):330–338. doi:10.7326/M13-2771. 3. Centers for Medicare and Medicaid Services. Decision Memo for Screening for Lung Cancer with Low Dose Computed Tomography (LDCT) (CAG00439N). 2015. www.cms.gov/medicare-coverage-database/details/ncadecision-memo.aspx?NCAId=274. Accessed January 21, 2016. 4. Slatore C, Baumann C, Pappas M, Humphrey LL. Smoking behaviors among patients receiving computed tomography for lung cancer screening: systematic review in support of the U.S. preventive services task force. Ann Am Thorac Soc. 2014;11(4):619–627. doi:10.1513/ AnnalsATS.201312-460OC. 5. Tammemagi MC, Berg CD, Riley TL, Cunningham CR, Taylor KL. Impact of lung cancer screening results on smoking cessation. J Natl Cancer Inst. 2014;106(6):dju084. doi:10.1093/jnci/dju084. 6. McMahon PM, Kong CY, Bouzan C, et al. Cost-effectiveness of computed tomography screening for lung cancer in the United States. J Thorac Oncol. 2011;6(11):1841–1848. doi:10.1097/JTO.0b013e31822e59b3. 7. Villanti AC, Jiang Y, Abrams DB, Pyenson BS. A cost-utility analysis of lung cancer screening and the additional benefits of incorporating smoking cessation interventions. PLoS One. 2013;8(8):e71379. doi:10.1371/ journal.pone.0071379. 8. Zeliadt SB, Heffner JL, Sayre G, et al. Attitudes and perceptions about smoking cessation in the context of lung cancer screening. JAMA Internal Medicine. 2015;175(9):1530–1537. doi:10.1001/ jamainternmed.2015.3558. 9. Clark MM, Cox LS, Jett JR, et al. Effectiveness of smoking cessation self-help materials in a lung cancer screening population. Lung Cancer. 2004;44(1):13–21. doi:10.1016/j.lungcan.2003.10.001. 10. van der Aalst CM, de Koning HJ, van den Bergh KA, Willemsen MC, van Klaveren RJ. The effectiveness of a computer-tailored smoking cessation intervention for participants in lung cancer screening: a randomised controlled trial. Lung Cancer. 2012;76(2):204–210. doi:10.1016/j. lungcan.2011.10.006. 11. Pua BB, Dou E, O’Connor K, Crawford CB. Integrating smoking cessation into lung cancer screening programs [published online ahead of print May 16, 2015]. Clin Imaging. doi:10.1016/j.clinimag.2015.05.004. 12. Goulart BHL, Bensink ME, Mummy DG, Ramsey SD. Lung cancer screening with low-dose computed tomography: costs, national expenditures, and cost-effectiveness. J Natl Compr Canc Netw. 2012;10(2): 267–275. www.jnccn.org/content/10/2/267.abstract. Accessed January 21, 2016. 13. Ma J, Ward EM, Smith R, Jemal A. Annual number of lung cancer deaths potentially avertable by screening in the United States. Cancer. 2013;119(7):1381–1385. doi:10.1002/cncr.27813. 14. Tobacco Use and Dependence Guideline Panel. Treating Tobacco Use and Dependence: 2008 Update. Rockville, MD: US Department of Health and Human Services; 2008. 15. Rogers AR, Christensen T, Welsh EM, Faseru B. Patient–provider discussions about lung cancer screening: results from the 2012/2013 Kansas
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to advantage over Quitline and printed materials, this intervention unmodified should not be pursued. We envisage future studies might incorporate an assessment of baseline risk for continued smoking5 and target participants with a low predicted chance of quitting with more intensive interventions, possibly a single face to face session at the time of screening scan followed by telephone counseling combined with pharmacotherapy. This would allow better utilization of resources and allow leverage of positive scan results, a factor often found to be associated with cessation.4,5 Although in this small trial counseling was delivered by a physician it is doubtful that this would be feasible or cost-effective in a real-world, high-throughput screening program. Other studies have used a psychologist but this could also be subject to the same limitations of cost and availability as a physician.22,23 MI meta-analysis shows many healthcare workers can make a significant impact on smoking outcomes,20 thus we expect a nurse or smoking-cessation counselor would take on this role. This pilot trial focused on the primary outcome of cessation. Few data exist on secondary or surrogate outcomes such as change in readiness to quit, smoking intensity, number of quit attempts. Such data may possibly provide clues to improving cessation interventions. However, it is also recognized that predictive variables for quit attempts may not be the same as those associated with maintenance of abstinence.37–39 A much larger, statistically powered study would be required to explore multivariate risk predictors of successful cessation. The NLST-LSS recently published a model using participant baseline variables but did not include variables on nicotine dependence and motivation.5 In addition, qualitative data from counseling transcripts may provide useful insights into smokers’ perceptions.40 There is a definite need for more data in this area. Although no universally accepted definition of hardcore (resistant) smoker exists, the participants exhibited hardcore smoking characteristics; 98% smoked at least 15 cigarettes per day and 58% did not report any quit attempt in the past 12 months. In the Australian general population, the comparable proportions are 42.3% and 55.8%.41 Thus on one hand a 16.4% 1-year quit rate in this population could be considered a modest success, on the other hand this means more than 80% of hardcore smokers continued to smoke. As more intense smoking interventions generally produce higher quit rates it is possible that such a resistant population may require more than a single counseling session, possibly delivered by telephone. Combining counseling with pharmacotherapy also increases effectiveness14 and the more active components of the “5A’s” (“Assist” and “Arrange follow-up”) are associated with higher quit rates.18 Thus provision of pharmacotherapy within a screening program should be considered but with due regard to the potentially massive pool of smokers who may be eligible for screening. Smokers display a range of smoking beliefs and preferred learning needs. Eighty-five percent of our participants owned computers, but previous studies show up to 70% of smokers do not access cessation information online.9,10 Unfamiliarity with MP3 players could have limited their use. Nevertheless for some individuals, audio materials may be very convenient (eg, whilst jogging or for vision-impaired). Thus individualized, multidisciplinary cessation interventions are probably required to address the complexity of smokers’ needs. In conclusion, a single face to face tailored counseling session supported by take-home audio cessation materials at the time of CT screening is feasible. However, the need to find an effective highthroughput smoking intervention that can be easily integrated with CT screening remains unmet.
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5-year screening programme. Thorax. 2014;69(6):574–579. doi:10.1136/ thoraxjnl-2013-203849. 28. Clark MA, Gorelick JJ, Sicks JD, et al. The relations between false positive and negative screens and smoking cessation and relapse in the National Lung Cancer Screening Trial: implications for public health. Nicotine Tob Res. 2015;18(1):17–24. doi:10.1093/ntr/ntv037. 29. Hartmann-Boyce J, Lancaster T, Stead LF. Print-based self-help interventions for smoking cessation. Cochrane Database Syst Rev. 2014;6:CD001118. doi:10.1002/14651858.CD001118.pub3. 30. Quitline. www.qld.gov.au/health/staying-healthy/atods/smoking/index. html. Accessed January 21, 2016. 31. Bach PB, Kattan MW, Thornquist MD, et al. Variations in lung cancer risk among smokers. J Natl Cancer Inst. 2003;95(6):470–478. www.ncbi.nlm. nih.gov/pubmed/12644540. Accessed January 21, 2016. 32. Marshall HM, Bowman RV, Ayres J, et al. Lung cancer screening feasibility in Australia. Eur Respir J. 2015;45(6):1734–1737. doi:10.1183/09031936.00208714. 33. Marshall HM, Bowman RV, Crossin J, et al. Queensland Lung Cancer Screening Study: rationale, design and methods. Intern Med J. 2013;43(2):174–182. doi:10.1111/j.1445-5994.2012.02789.x. 34. West R, Hajek P, Stead L, Stapleton J. Outcome criteria in smoking cessation trials: proposal for a common standard. Addiction. 2005;100(3):299– 303. doi:10.1111/j.1360-0443.2004.00995.x. 35. National Health and Medical Research Council. Australian Guidelines to Reduce Health Risks From Drinking Alcohol. 2009. www.nhmrc.gov.au/ health-topics/alcohol-guidelines. Accessed January 21, 2016. 36. Heatherton TF, Kozlowski LT, Frecker RC, Fagerstrom KO. The Fagerstrom Test for Nicotine Dependence: a revision of the Fagerstrom Tolerance Questionnaire. Br J Addict. 1991;86(9):1119–1127. www.ncbi. nlm.nih.gov/pubmed/1932883. Accessed January 21, 2016. 37. Lee CW, Kahende J. Factors associated with successful smoking cessation in the United States, 2000. Am J Public Health. 2007;97(8):1503–1509. doi:10.2105/AJPH.2005.083527. 38. Borland R, Yong HH, Balmford J, et al. Motivational factors predict quit attempts but not maintenance of smoking cessation: findings from the International Tobacco Control Four country project. Nicotine Tob Res. 2010;12(suppl):S4–11. doi:10.1093/ntr/ntq050. 39. Bailey SR, Bryson SW, Killen JD. Predicting successful 24-hr quit attempt in a smoking cessation intervention. Nicotine Tob Res. 2011;13(11):1092– 1097. doi:10.1093/ntr/ntr151. 40. Park ER, Streck JM, Gareen IF, et al. A qualitative study of lung cancer risk perceptions and smoking beliefs among national Lung Screening Trial participants. Nicotine Tob Res. 2014;16(2):166–173. doi:10.1093/ntr/ntt133. 41. Clare P, Bradford D, Courtney RJ, Martire K, Mattick RP. The relationship between socioeconomic status and ‘hardcore’ smoking over time – greater accumulation of hardened smokers in low-SES than high-SES smokers. Tob Control. 2014;23(e2):e133–138. doi:10.1136/tobaccocontrol-2013-051436.
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Adult Tobacco Survey. Prev Med Rep. 2015;2:577–579. doi:10.1016/j. pmedr.2015.06.018. 16. Papadakis S, Gharib M, Hambleton J, Reid RD, Assi R, Pipe AL. Delivering evidence-based smoking cessation treatment in primary care practice: experience of Ontario family health teams. Can Fam Physician. 2014;60(7):e362–371. www.ncbi.nlm.nih.gov/pubmed/25022655. Accessed January 21, 2016. 17. Lewis JA, Petty WJ, Tooze JA, et al. Low-dose CT lung cancer screening practices and attitudes among primary care providers at an academic medical center. Cancer Epidemiol Biomark Prev. 2015;24(4):664–670. doi:10.1158/1055-9965.epi-14-1241. 18. Park ER, Gareen IF, Japuntich S, et al. Primary care provider-delivered smoking cessation interventions and smoking cessation among participants in the National Lung Screening Trial. JAMA Intern Med. 2015;175(9):1509–1516. doi:10.1001/jamainternmed.2015.2391. 19. Hoffman RM, Sussman AL, Getrich CM, et al. Attitudes and beliefs of primary care providers in New Mexico about lung cancer screening using low-dose computed tomography. Prev Chronic Dis. 2015;12:E108. doi:10.5888/pcd12.150112. 20. Lindson-Hawley N, Thompson TP, Begh R. Motivational interviewing for smoking cessation. Cochrane Database Syst Rev. 2015;3:CD006936. doi:10.1002/14651858.CD006936.pub3. 21. Ferketich AK, Otterson GA, King M, Hall N, Browning KK, Wewers ME. A pilot test of a combined tobacco dependence treatment and lung cancer screening program. Lung Cancer. 2012;76(2):211–215. doi:10.1016/j. lungcan.2011.10.011. 22. Filippo L, Principe R, Cesario A, et al. Smoking cessation intervention within the framework of a lung cancer screening program: preliminary results and clinical perspectives from the “Cosmos-II” Trial. Lung. 2015;193(1):147–149. doi:10.1007/s00408-014-9661-y. 23. Pozzi P, Munarini E, Bravi F, et al. A combined smoking cessation intervention within a lung cancer screening trial: a pilot observational study. Tumori. 2015;101(3):306–311. doi:10.5301/tj.5000282. 24. Cox LS, Clark MM, Jett JR, et al. Change in smoking status after spiral chest computed tomography scan screening. Cancer. 2003;98(11):2495– 2501. doi:10.1002/cncr.11813. 25. Styn MA, Land SR, Perkins KA, Wilson DO, Romkes M, Weissfeld JL. Smoking behavior 1 year after computed tomography screening for lung cancer: effect of physician referral for abnormal CT findings. Cancer Epidemiol Biomarkers Prev. 2009;18(12):3484–3489. doi:10.1158/10559965.epi-09-0895. 26. Anderson CM, Yip R, Henschke CI, Yankelevitz DF, Ostroff JS, Burns DM. Smoking cessation and relapse during a lung cancer screening program. Cancer Epidemiol Biomarkers Prev. 2009;18(12):3476–3483. doi:10.1158/1055-9965.epi-09-0176. 27. Ashraf H, Saghir Z, Dirksen A, et al. Smoking habits in the randomised Danish Lung Cancer Screening Trial with low-dose CT: final results after a
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Brief report
Brief Tailored Smoking Cessation Counseling in a Lung Cancer Screening Population is Feasible: A Pilot Randomized Controlled Trial Downloaded from http://ntr.oxfordjournals.org/ at Flinders University of South Australia on February 3, 2016
Henry M. Marshall PhD, FRACP, Deborah A. Courtney BN, Linda H. Passmore BN, Elizabeth M. McCaul RN, Ian A. Yang PhD, FRACP, Rayleen V. Bowman PhD, FRACP, Kwun M. Fong PhD, FRACP University of Queensland Thoracic Research Centre, The Prince Charles Hospital, Brisbane, Australia Corresponding Author: Henry M. Marshall, PhD, FRACP, University of Queensland Thoracic Research Centre, The Prince Charles Hospital, Rode Road, Brisbane 4032 QLD, Australia. Telephone: 61-7-3139-4000; Fax: 61-7-3139-4510; E-mail: Henry. [email protected]
Abstract Introduction: Maximizing smoking abstinence in lung cancer screening participants is important to reduce individual risk of disease and improve screening cost-effectiveness; however, the optimal strategy remains undefined. We hypothesized that a single session of tailored face-to-face counseling on the day of screening CT scan, coupled with audio and printed cessation information would be feasible to deliver in a CT screening trial. Methods: We randomized volunteer smokers in the Queensland Lung Cancer Screening Study to intervention (counseling session, audio quit materials, printed quit materials, Quitline contact details) or control group (printed quit materials, Quitline contact details). Participants self-reported point prevalence quit rates at 1 year. Results: Fifty-five smokers were enrolled; 28 randomized to intervention and 27 controls. Median cigarette consumption was 25/day; 54/55 smoked at least 15 cigarettes per day. Median smoking duration was 46 years. Median Fagerström dependence score was 6. In total 58% did not report any quit attempt in the prior 12 months. Mean duration of counseling was 26.5 minutes. After 1 year, four participants (14.3%) in the intervention group and five participants (18.5%) in the control group had quit (P = .74). Combined annual point prevalence quit rate was 16.4%. Conclusions: Although feasible to deliver a single session of tailored counseling on the day of screening this intervention had no discernible impact on cessation over and above printed materials and Quitline access. As participants exhibited hardcore smoking characteristics, more intensive strategies, in larger cohorts, should be explored. Implications: The optimal smoking cessation strategy within a lung cancer screening program is not known. This study demonstrates that a single session of counseling can be feasibly delivered on the day of screening but may not have been intensive enough for long-term, hard-core smokers.
Introduction Low-dose computed tomography screening can reduce lung cancer mortality1 and may provide a “teachable moment” for smoking
cessation. Smoking cessation should be a core component of lowdose computed tomography screening.2,3 The process of low-dose computed tomography lung cancer screening itself does not appear to influence smoking behavior but positive CT scan results are
© The Author 2016. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: [email protected].
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Methods We tested the hypothesis that a single face to face session of tailored MI counseling supported by take-home audio quit educational materials (provided on an MP3 player) plus standard printed quit materials and Quitline30 telephone helpline referral would (1) be feasible when delivered on the day of screening and (2) result in higher selfreported point prevalence quit rates at 1 year compared to standard printed materials and Quitline referral alone. Counseling included discussion of lung function results and lung cancer risk.31 Smokers in the Queensland Lung Cancer Screening Study32,33 (age 60–74 years; ≥30 pack year smoking) were invited to enroll in the sub-study by letter prior to each scheduled CT screening scan. Institutional Research Ethics Committee approval was granted. Volunteers were randomized 1:1 to intervention (MI counseling, non-tailored audio materials, non-tailored printed materials, Quitline details) or control groups (nontailored printed materials, Quitline details) using a random number generator. Group allocation was concealed at randomization. To limit hospital visits and increase participant convenience the MI intervention was scheduled to coincide with their upcoming annual screening CT, however this precluded discussion of scan reports which were typically reported 1 week after acquisition. For consistency, a single thoracic physician (HMM) provided the counseling. Thirty audio tracks, based on Quitline materials (duration 0.5 to 4 minutes), and three relaxation tracks were provided on an MP3 player (Sansa Clip, SanDisk Corporation, Milpitas, CA). Pharmacological therapies were discussed but participants were directed to their family doctor for prescription. The primary outcome, self-reported point-prevalence smoking status at 12 months, was determined by response to the question “Do you NOW smoke cigarettes (one or more cigarettes per week)?” Self-report was validated by exhaled carbon monoxide (ECO) when possible (Bedfont Smokerlyser, Bedfont Scientific Limited, Rochester, United Kingdom); a threshold of at least 10 parts per million (ppm) indicating continued smoking.34 ECO was not always obtainable at the 12-month time point because the CT protocol allowed scans to take place between 11 and 15 months after the previous scan. Secondary outcomes such as change in readiness to quit, cigarettes per day, number of quit attempts were not assessed in this pilot study.
Results Out of 256 participants, 121 (47.3%) were baseline smokers or recent quitters (self-reported current smoker n = 109, or quit 55 years; ≥30 pack year smoking) found 36/63 participants (57.1 %) quit for at least 6 months following psychologist-delivered cognitive-behavioral counseling plus pharmacotherapy.22 Behavioral counseling plus pharmacotherapy in the MILD screening trial (age ≥49 years; ≥20 pack year smoking) produced 1-year continuous abstinence rates of 19.8% (37 of 187 patients).23 CT screening trials without counseling report quit rates of 14% to 15% at 1 year24,25 and 24% to 29% after 5 to 6 years.26,27 Annual point prevalence quit rates ranged from 11.6% to 13.4% in the NLST.28 Background quit rates are often considered to lie in the range of 5% to 10% per year.20,29
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Table 1. Baseline Characteristics of Smokers in the Smoking Cessation Sub-Study Variable, n(%) or median [IQR]
Intervention group, n = 28
63.0 [5] 17 (63.0) 15 (55.6) 8 (29.6) 7 (25.9)
63.0 [6] 18 (64.3) 15 (53.6) 8 (28.6) 11 (39.3)
25.0 [10] 16.0 [3] 57.5 [32] 46.0 [6] 6.0 [3] 11 (40.7) 0/13/12/1 (0/48.1/44.4/3.7) 14 (51.9)
25.0 [14] 17.0 [3] 57.5 [28] 46.0 [5] 6.0 [4] 12 (42.9) 1/18/9/0 (3.6/64.3/32.1/0) 13 (46.4)
4 (14.8) 14 (51.9) 20/5/2/0/0 (74.1/18.5/7.4/0/0) 90.2 [31.3] 14 (51.9)
5 (17.9) 14 (50.0) 19/5/1/3/0 (67.9/17.9/3.6/10.7/0) 86.7 [15.5] 18 (64.3)
12 (44.4) 7 (25.9) 3 (11.1) 3 (11.1) 12 (44.4) 4 (14.8) 5 (18.5) 4 (14.8) 2 (7.4)
16 (57.1) 9 (32.1) 0 4 (14.3) 6 (21.4) 8 (28.6) 2 (7.1) 8 (28.6) 5 (17.9)
IQR = interquartile range; LDCT = Low-dose computed tomography. a Fagerström Test for Nicotine Dependence. b Four categories: (1) No plan to quit in next 6 months; (2) Possible plan to quit in the next 6 months; (3) Definite plan to quit in the next month and (4) missing data. c Self-efficacy score 4 or 5 on a scale 1 to 5: “Do you believe you can stop smoking?” 1 being lowest level of belief and 5 being the highest. d Includes prior physician diagnosis of chronic obstructive pulmonary disease, emphysema, chronic bronchitis or chronic asthma. e Medical Research Council (MRC) dyspnea scale Grade 1 to 5 (1: Breathless only with strenuous exercise; 2: Short of breath when hurrying on the level or up a slight hill; 3: Slower than most people of the same age on a level surface or Have to stop when walking at my own pace on the level; 4: Stop for breath walking 100 meters or after a walking few minutes at my own pace on the level; 5: Too breathless to leave the house). f Noncalcified nodule ≥ 4mm diameter detected on LDCT; NRT—nicotine replacement therapy; FEV1%—Forced expiratory volume in 1 second, percent predicted.
Bupropion and hypnosis, only 7 (13%) participants had tried counseling. Expressions of self-efficacy and readiness to quit appeared reasonably high. Twenty-three out of 55 (42%) participants had made at least one quit attempt in the previous year and 32/55 (58%) did not report any quit attempt in the past 12 months. At 12 months, nine (16.4%) participants had quit (95% CI 9% to 28%); four (14.3%) in the intervention group and five (18.5%) in the control group (Fisher’s Exact Test P = .74). One intervention group and three control group quitters had ECO < 10 ppm, the remainder were not tested. Three out of 28 (10.7%) intervention group participants and 2/27 (7.4%) control group participants did not return 12-month questionnaires and were assumed to be smokers. Concordance between self-report and ECO measurement across all Queensland Lung Cancer Screening Study participants was 92.9% and 92.3% for nonsmokers and current smokers respectively (346 ECO measurements in 227 participants). Familiarity with MP3 players was low; six participants (11%) owned an MP3 player whereas 47/55 (85%) owned a computer.
Twelve out of 28 (43%) intervention group participants returned a questionnaire regarding the MP3 player; 10 participants used it five times or less, two used it more than five times. Nine participants who used it at least once rated usability as 4 out of 5.
Discussion We found it was feasible to deliver a single tailored session of MI counseling on the day of CT screening combined with nontailored take-home audio cessation materials. It appeared that MP3 players could be operated even in the absence of prior experience. The combined 12-month quit rate of 16.4% is consistent with other reports. Although biochemical validation was not achieved in most participants, concordance between ECO and self-report was more than 92% across Queensland Lung Cancer Screening Study as a whole, in line with previous studies.24,27 Our pilot study lacked statistical power to inform whether the intervention had an impact on cessation rates, however, as it had no clear advantage or even a trend
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Sociodemographic Age, years Male Education, >high school Lives with smoker >14 standard alcoholic drinks per week Smoking and quitting Cigarettes per day Age started smoking, years Pack years Duration of smoking, years Nicotine dependency scorea ≥1 quit attempts in past year Readiness to quitb High self-efficacyc Other Obstructive lung disease diagnosisd Cough symptom MRC Dyspnea scoree FEV1% predicted Positive baseline screening scanf Previous smoking cessation therapy NRT patch NRT gum NRT inhaler NRT lozenge Varenicline Bupropion Acupuncture Hypnosis Counseling /quit program
Control group, n = 27
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Funding Queensland Health, Smart State Research Grant (388600); National Health and Medical Research Council (NHMRC) National Research Centre for Asbestos-Related Diseases (NRCARD) (440812); The Prince Charles Hospital Foundation (FRC0207-24).
Declaration of Interests None declared.
References 1. National Lung Screening Trial Research Team. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011;365(5):395–409. doi:10.1056/NEJMoa1102873. 2. Moyer VA. Screening for lung cancer: U.S. preventive services task force recommendation statement. Ann Intern Med. 2014;160(5):330–338. doi:10.7326/M13-2771. 3. Centers for Medicare and Medicaid Services. Decision Memo for Screening for Lung Cancer with Low Dose Computed Tomography (LDCT) (CAG00439N). 2015. www.cms.gov/medicare-coverage-database/details/ncadecision-memo.aspx?NCAId=274. Accessed January 21, 2016. 4. Slatore C, Baumann C, Pappas M, Humphrey LL. Smoking behaviors among patients receiving computed tomography for lung cancer screening: systematic review in support of the U.S. preventive services task force. Ann Am Thorac Soc. 2014;11(4):619–627. doi:10.1513/ AnnalsATS.201312-460OC. 5. Tammemagi MC, Berg CD, Riley TL, Cunningham CR, Taylor KL. Impact of lung cancer screening results on smoking cessation. J Natl Cancer Inst. 2014;106(6):dju084. doi:10.1093/jnci/dju084. 6. McMahon PM, Kong CY, Bouzan C, et al. Cost-effectiveness of computed tomography screening for lung cancer in the United States. J Thorac Oncol. 2011;6(11):1841–1848. doi:10.1097/JTO.0b013e31822e59b3. 7. Villanti AC, Jiang Y, Abrams DB, Pyenson BS. A cost-utility analysis of lung cancer screening and the additional benefits of incorporating smoking cessation interventions. PLoS One. 2013;8(8):e71379. doi:10.1371/ journal.pone.0071379. 8. Zeliadt SB, Heffner JL, Sayre G, et al. Attitudes and perceptions about smoking cessation in the context of lung cancer screening. JAMA Internal Medicine. 2015;175(9):1530–1537. doi:10.1001/ jamainternmed.2015.3558. 9. Clark MM, Cox LS, Jett JR, et al. Effectiveness of smoking cessation self-help materials in a lung cancer screening population. Lung Cancer. 2004;44(1):13–21. doi:10.1016/j.lungcan.2003.10.001. 10. van der Aalst CM, de Koning HJ, van den Bergh KA, Willemsen MC, van Klaveren RJ. The effectiveness of a computer-tailored smoking cessation intervention for participants in lung cancer screening: a randomised controlled trial. Lung Cancer. 2012;76(2):204–210. doi:10.1016/j. lungcan.2011.10.006. 11. Pua BB, Dou E, O’Connor K, Crawford CB. Integrating smoking cessation into lung cancer screening programs [published online ahead of print May 16, 2015]. Clin Imaging. doi:10.1016/j.clinimag.2015.05.004. 12. Goulart BHL, Bensink ME, Mummy DG, Ramsey SD. Lung cancer screening with low-dose computed tomography: costs, national expenditures, and cost-effectiveness. J Natl Compr Canc Netw. 2012;10(2): 267–275. www.jnccn.org/content/10/2/267.abstract. Accessed January 21, 2016. 13. Ma J, Ward EM, Smith R, Jemal A. Annual number of lung cancer deaths potentially avertable by screening in the United States. Cancer. 2013;119(7):1381–1385. doi:10.1002/cncr.27813. 14. Tobacco Use and Dependence Guideline Panel. Treating Tobacco Use and Dependence: 2008 Update. Rockville, MD: US Department of Health and Human Services; 2008. 15. Rogers AR, Christensen T, Welsh EM, Faseru B. Patient–provider discussions about lung cancer screening: results from the 2012/2013 Kansas
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to advantage over Quitline and printed materials, this intervention unmodified should not be pursued. We envisage future studies might incorporate an assessment of baseline risk for continued smoking5 and target participants with a low predicted chance of quitting with more intensive interventions, possibly a single face to face session at the time of screening scan followed by telephone counseling combined with pharmacotherapy. This would allow better utilization of resources and allow leverage of positive scan results, a factor often found to be associated with cessation.4,5 Although in this small trial counseling was delivered by a physician it is doubtful that this would be feasible or cost-effective in a real-world, high-throughput screening program. Other studies have used a psychologist but this could also be subject to the same limitations of cost and availability as a physician.22,23 MI meta-analysis shows many healthcare workers can make a significant impact on smoking outcomes,20 thus we expect a nurse or smoking-cessation counselor would take on this role. This pilot trial focused on the primary outcome of cessation. Few data exist on secondary or surrogate outcomes such as change in readiness to quit, smoking intensity, number of quit attempts. Such data may possibly provide clues to improving cessation interventions. However, it is also recognized that predictive variables for quit attempts may not be the same as those associated with maintenance of abstinence.37–39 A much larger, statistically powered study would be required to explore multivariate risk predictors of successful cessation. The NLST-LSS recently published a model using participant baseline variables but did not include variables on nicotine dependence and motivation.5 In addition, qualitative data from counseling transcripts may provide useful insights into smokers’ perceptions.40 There is a definite need for more data in this area. Although no universally accepted definition of hardcore (resistant) smoker exists, the participants exhibited hardcore smoking characteristics; 98% smoked at least 15 cigarettes per day and 58% did not report any quit attempt in the past 12 months. In the Australian general population, the comparable proportions are 42.3% and 55.8%.41 Thus on one hand a 16.4% 1-year quit rate in this population could be considered a modest success, on the other hand this means more than 80% of hardcore smokers continued to smoke. As more intense smoking interventions generally produce higher quit rates it is possible that such a resistant population may require more than a single counseling session, possibly delivered by telephone. Combining counseling with pharmacotherapy also increases effectiveness14 and the more active components of the “5A’s” (“Assist” and “Arrange follow-up”) are associated with higher quit rates.18 Thus provision of pharmacotherapy within a screening program should be considered but with due regard to the potentially massive pool of smokers who may be eligible for screening. Smokers display a range of smoking beliefs and preferred learning needs. Eighty-five percent of our participants owned computers, but previous studies show up to 70% of smokers do not access cessation information online.9,10 Unfamiliarity with MP3 players could have limited their use. Nevertheless for some individuals, audio materials may be very convenient (eg, whilst jogging or for vision-impaired). Thus individualized, multidisciplinary cessation interventions are probably required to address the complexity of smokers’ needs. In conclusion, a single face to face tailored counseling session supported by take-home audio cessation materials at the time of CT screening is feasible. However, the need to find an effective highthroughput smoking intervention that can be easily integrated with CT screening remains unmet.
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