Nomogram to predict successful smoking cessation in a Chinese outpatient population
Ning Zhu# 1
,   Shanhong Lin# 2,   Chao Cao 1,   Ning Xu 1,   Xiaopin Yu 3,   Xueqin Chen 4  
More details
Hide details
Department of Respiratory and Critical Care Medicine, Ningbo First Hospital, Ningbo, China
Department of Ultrasound, Ningbo First Hospital, Ningbo, China
Department of Prevention and Health Care, Ningbo First Hospital, Ningbo, China
Department of Traditional Medicine, Ningbo First Hospital, Ningbo, China
Xueqin Chen   

Department of Traditional Medicine, Ningbo First Hospital, 59 Liuting Street, Ningbo 315010, Zhejiang Province, China
Publication date: 2020-10-16
Tob. Induc. Dis. 2020;18(October):86
# Contributed equally, co-first authors
The study aimed to establish and internally validate a nomogram to predict successful smoking cessation in a Chinese outpatient population.

A total of 278 participants were included, and data were collected from March 2016 to December 2018. Predictors for successful smoking cessation were evaluated by 3-month sustained abstinence rates. Least absolute shrinkage and selection operator (LASSO) regression was used to select variables for the model to predict successful smoking cessation, and multivariable logistic regression analysis was performed to establish a novel predictive model. The discriminatory ability, calibration, and clinical usefulness of the nomogram were determined by the concordance index (C-index), calibration plot, and decision curve analysis, respectively. Internal validation with bootstrapping was performed.

The nomogram included living with a smoker or experiencing workplace smoking, number of outpatient department visits, reason for quitting tobacco, and varenicline use. The nomogram demonstrated valuable predictive performance, with a C-index of 0.816 and good calibration. A high C-index of 0.804 was reached with interval validation. Decision curve analysis revealed that the nomogram for predicting successful smoking cessation was clinically significant when intervention was conducted at a successful cessation of smoking possibility threshold of 19%.

This novel nomogram for successful smoking cessation can be conveniently used to predict successful cessation of smoking in outpatients.

We are deeply grateful to all the smokers who were associated with our medical practice.
The authors have each completed and submitted an ICMJE form for disclosure of potential conflicts of interest. The authors declare that they have no competing interests, financial or otherwise, related to the current work. All the authors report grants from the Science and Technology Innovation 2025 Major Project of Ningbo (2019B10037), during the conduct of the study.
This study was supported by the Science and Technology Innovation 2025 Major Project of Ningbo (2019B10037).
Not commissioned; externally peer reviewed.
World Health Organization. WHO report on the global tobacco epidemic, 2017:Monitoring tobacco use and prevention policies. Published 2017. Accessed April 16, 2019.
Vangeli E, Stapleton J, Smit E, Borland R, West R. Predictors of attempts to stop smoking and their success in adult general population samples: a systematic review. Addiction (Abingdon, England). 2011;106(12):2110-2121. doi:10.1111/j.1360-0443.2011.03565.x.
Huang WH, Hsu HY, Chang BC, Chang FC. Factors Correlated with Success Rate of Outpatient Smoking Cessation Services in Taiwan. Int J Environ Res Public Health. 2018;15(6). doi:10.3390/ijerph15061218.
Shie HG, Pan SW, Yu WK, Chen WC, Ho LI, Ko HK. Levels of exhaled carbon monoxide measured during an intervention program predict 1-year smoking cessation: a retrospective observational cohort study. NPJ Prim Care Respir Med. 2017;27(1):59. doi:10.1038/s41533-017-0060-8.
Tomioka H, Wada T, Yamazoe M, Yoshizumi Y, Nishio C, Ishimoto G. Ten-year experience of smoking cessation in a single center in Japan. Respir Investig. 2019;57(4):380-387. doi:10.1016/j.resinv.2019.01.007.
McGhee SM, Ho LM, Lapsley HM, et al. Cost of tobacco-related diseases, including passive smoking, in Hong Kong. Tob Control. 2006;15(2):125-130. doi:10.1136/tc.2005.013292.
Sharbaugh M, Althouse A, Thoma F, Lee J, Figueredo V, Mulukutla S. Impact of cigarette taxes on smoking prevalence from 2001-2015: A report using the Behavioral and Risk Factor Surveillance Survey (BRFSS). PloS One. 2018;13(9):e0204416. doi:10.1371/journal.pone.0204416.
Yang GH, Li Q, Wang CX, et al. Findings from 2010 Global Adult Tobacco Survey: implementation of MPOWER policy in China. Biomed Environ Sci. 2010;23(6):422-429. doi:10.1016/S0895-3988(11)60002-0.
Jiang Y, Ong MK, Tong EK, et al. Chinese Physicians and Their Smoking Knowledge, Attitudes, and Practices. Am J Prev Med. 2007;33(1):15-22. doi:10.1016/j.amepre.2007.02.037.
Smit E, Hoving C, Schelleman-Offermans K, West R, de Vries H. Predictors of successful and unsuccessful quit attempts among smokers motivated to quit. Addict Behav. 2014;39(9):1318-1324. doi:10.1016/j.addbeh.2014.04.017.
Zhou X, Nonnemaker J, Sherrill B, Gilsenan A, Coste F, West R. Attempts to quit smoking and relapse: factors associated with success or failure from the ATTEMPT cohort study. Addict Behav. 2009;34(4):365-373. doi:10.1016/j.addbeh.2008.11.013.
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(Supplement 1):S4-S11. doi:10.1093/ntr/ntq050.
Fagerström KO. Measuring degree of physical dependence to tobacco smoking with reference to individualization of treatment. Addict Behav. 1978;(3):235-241. doi:10.1016/0306-4603(78)90024-2.
Sauerbrei W, Royston P, Binder H. Selection of important variables and determination of functional form for continuous predictors in multivariable model building. Stat Med. 2007;26(30):5512-5528. doi:10.1002/sim.3148.
Friedman J, Hastie T, Tibshirani R. Regularization Paths for Generalized Linear Models via Coordinate Descent. J Stat Softw. 2010;33(1):1-22. PMID:20808728.
Kidd AC, McGettrick M, Tsim S, Halligan D, Bylesjo M, Blyth K. Survival prediction in mesothelioma using a scalable Lasso regression model: instructions for use and initial performance using clinical predictors. BMJ Open Respir Res. 2018;5(1):e000240. doi:10.1136/bmjresp-2017-000240.
Cahill K, Stevens S, Perera R, Lancaster T. Pharmacological interventions for smoking cessation: an overview and network meta-analysis. Cochrane Database Syst Rev. 2013;(5):CD009329. doi:10.1002/14651858.CD009329.pub2.
Anthenelli RM, Benowitz NL, West R, et al. Neuropsychiatric safety and efficacy of varenicline, bupropion, and nicotine patch in smokers with and without psychiatric disorders (EAGLES): a double-blind, randomised, placebo-controlled clinical trial. Lancet. 2016;387(10037):2507-2520. doi:10.1016/S0140-6736(16)30272-0.
Caponnetto P, Polosa R. Common predictors of smoking cessation in clinical practice. Respir Med. 2008;102(8):1182-1192. doi:10.1016/j.rmed.2008.02.017.
Ho KS, Choi BWC, Chan HCH, Ching KW. Evaluation of biological, psychosocial, and interventional predictors for success of a smoking cessation programme in Hong Kong. Hong Kong Med J. 2016;22(2):158-164. doi:10.12809/hkmj154549.
Wiggers LCW, Stalmeier PFM, Oort FJ, Smets EMA, Legemate DA, de Haes JCJM. Do patients' preferences predict smoking cessation? Prev Med. 2005;41(2):667-675. doi:10.1016/j.ypmed.2004.12.009.
Hartmann-Boyce J, Hong B, Livingstone-Banks J, Wheat H, Fanshawe T. Additional behavioural support as an adjunct to pharmacotherapy for smoking cessation. Cochrane Database Syst Rev. 2019;(6):CD009670. doi:10.1002/14651858.CD009670.pub4.
Janson C, Künzli N, de Marco R, et al. Changes in active and passive smoking in the European Community Respiratory Health Survey. Eur Respir J. 2006;27(3):517-524. doi:10.1183/09031936.06.00106605.
Hymowitz N, Cummings KM, Hyland A, Lynn W, Pechacek T, Hartwell T. Predictors of smoking cessation in a cohort of adult smokers followed for five years. Tob Control. 1997;6 Suppl 2:S57-S62. doi:10.1136/tc.6.suppl_2.s57.
Chandola T, Head J, Bartley M. Socio-demographic predictors of quitting smoking: how important are household factors? Addiction. 2004;99(6):770-777. doi:10.1111/j.1360-0443.2004.00756.x.
Osler M, Prescott E. Psychosocial, behavioural, and health determinants of successful smoking cessation: a longitudinal study of Danish adults. Tob Control. 1998;7(3):262-267. doi:10.1136/tc.7.3.262.
Monsó E, Campbell J, Tønnesen P, Gustavsson G, Morera J. Sociodemographic predictors of success in smoking intervention. Tob Control. 2001;10(2):165-169. doi:10.1136/tc.10.2.165.
Kim YJ. Predictors for successful smoking cessation in Korean adults. Asian Nurs Res (Korean Soc Nurs Sci). 2014;8(1):1-7. doi:10.1016/j.anr.2013.09.004.
Hyland A, Borland R, Li Q, et al. Individual-level predictors of cessation behaviours among participants in the International Tobacco Control (ITC) Four Country Survey. Tob Control. 2006;15:iii83-iii94. doi:10.1136/tc.2005.013516.
Dale LC, Glover ED, Sachs DP, et al. Bupropion for smoking cessation: predictors of successful outcome. Chest. 2001;119(5):1357-1364. doi:10.1378/chest.119.5.1357.
Gonzales D, Rennard S, Nides M, et al. Varenicline, an alpha4beta2 nicotinic acetylcholine receptor partial agonist, vs sustained-release bupropion and placebo for smoking cessation: a randomized controlled trial. JAMA. 2006;296(1):47-55. doi:10.1001/jama.296.1.47.
Jorenby D, Hays J, Rigotti N, et al. Efficacy of varenicline, an alpha4beta2 nicotinic acetylcholine receptor partial agonist, vs placebo or sustained-release bupropion for smoking cessation: a randomized controlled trial. JAMA. 2006;296(1):56-63. doi:10.1001/jama.296.1.56.
Anthenelli R, Benowitz N, West R, et al. Neuropsychiatric safety and efficacy of varenicline, bupropion, and nicotine patch in smokers with and without psychiatric disorders (EAGLES): a double-blind, randomised, placebo-controlled clinical trial. Lancet. 2016;387(10037):2507-2520. doi:10.1016/s0140-6736(16)30272-0.
Rennard S, Hughes J, Cinciripini P, et al. A randomized placebo-controlled trial of varenicline for smoking cessation allowing flexible quit dates. Nicotine Tob Res. 2012;14(3):343-350. doi:10.1093/ntr/ntr220.
Hajek P, McRobbie H, Myers K, Stapleton J, Dhanji AR. Use of varenicline for 4 weeks before quitting smoking: decrease in ad lib smoking and increase in smoking cessation rates. Arch Intern Med. 2011;171(8):770-777. doi:10.1001/archinternmed.2011.138.
Hawk L, Ashare R, Lohnes S, et al. The effects of extended pre-quit varenicline treatment on smoking behavior and short-term abstinence: a randomized clinical trial. Clin Pharmacol Ther. 2012;91(2):172-180. doi:10.1038/clpt.2011.317.
Ashare R, Tang K, Mesaros A, Blair I, Leone F, Strasser A. Effects of 21 days of varenicline versus placebo on smoking behaviors and urges among non-treatment seeking smokers. J Psychopharmacol. 2012;26(10):1383-1390. doi:10.1177/0269881112449397.