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Effect of Varenicline Added to Counseling on Smoking Cessation Among African American Daily Smokers The Kick It at Swope IV Randomized Clinical Trial

Author/s: 
Cox, L. S., Nollen, N. L., Mayo, M. S., Faseru, B., Greiner, A., Ellerbeck, E. F., Krebill, R., Tyndale, R. F., Benowitz, N. L., Ahluwalia, J. S.

Importance: African American smokers have among the highest rates of tobacco-attributable morbidity and mortality in the US, and effective treatment is needed for all smoking levels.

Objectives: To evaluate the efficacy of varenicline vs placebo among African American adults who are light, moderate, and heavy daily smokers.

Design, setting, and participants: The Kick It at Swope IV (KIS-IV) trial was a randomized, double-blind, placebo-controlled clinical trial conducted at a federally qualified health center in Kansas City. A total of 500 African American adults who were daily smokers of all smoking levels were enrolled from June 2015 to December 2017; final follow-up was completed in June 2018.

Interventions: Participants were provided 6 sessions of culturally relevant individualized counseling and were randomized (in a 3:2 ratio) to receive varenicline (1 mg twice daily; n = 300) or placebo (n = 200) for 12 weeks. Randomization was stratified by sex and smoking level (1-10 cigarettes/d [light smokers] or >10 cigarettes/d [moderate to heavy smokers]).

Main outcomes and measures: The primary outcome was salivary cotinine-verified 7-day point prevalence smoking abstinence at week 26. The secondary outcome was 7-day point prevalence smoking abstinence at week 12, with subgroup analyses for light smokers (1-10 cigarettes/d) and moderate to heavy smokers (>10 cigarettes/d).

Results: Among 500 participants who were randomized and completed the baseline visit (mean age, 52 years; 262 [52%] women; 260 [52%] light smokers; 429 [86%] menthol users), 441 (88%) completed the trial. Treating those lost to follow-up as smokers, participants receiving varenicline were significantly more likely than those receiving placebo to be abstinent at week 26 (15.7% vs 6.5%; difference, 9.2% [95% CI, 3.8%-14.5%]; odds ratio [OR], 2.7 [95% CI, 1.4-5.1]; P = .002). The varenicline group also demonstrated greater abstinence than the placebo group at the end of treatment week 12 (18.7% vs 7.0%; difference, 11.7% [95% CI, 6.0%-17.7%]; OR, 3.0 [95% CI, 1.7-5.6]; P < .001). Smoking abstinence at week 12 was significantly greater for individuals receiving varenicline compared with placebo among light smokers (22.1% vs 8.5%; difference, 13.6% [95% CI, 5.2%-22.0%]; OR, 3.0 [95% CI, 1.4-6.7]; P = .004) and among moderate to heavy smokers (15.1% vs 5.3%; difference, 9.8% [95% CI, 2.4%-17.2%]; OR, 3.1 [95% CI, 1.1-8.6]; P = .02), with no significant smoking level × treatment interaction (P = .96). Medication adverse events were generally comparable between treatment groups, with nausea reported more frequently in the varenicline group (163 of 293 [55.6%]) than the placebo group (90 of 196 [45.9%]).

Conclusions and relevance: Among African American adults who are daily smokers, varenicline added to counseling resulted in a statistically significant improvement in the rates of 7-day point prevalence smoking abstinence at week 26 compared with counseling and placebo. The findings support the use of varenicline in addition to counseling for tobacco use treatment among African American adults who are daily smokers.

Keywords 
Varenicline smoking African Americans Smokers clinical trial

Mobile phone text messaging and app-based interventions for smoking cessation

Author/s: 
Whittaker, Robyn, McRobbie, Hayden, Bullen, Chris, Rodgers, Anthony, Gu, Yulong, Dobson, Rosie

Background: Mobile phone-based smoking cessation support (mCessation) offers the opportunity to provide behavioural support to those who cannot or do not want face-to-face support. In addition, mCessation can be automated and therefore provided affordably even in resource-poor settings. This is an update of a Cochrane Review first published in 2006, and previously updated in 2009 and 2012.

Objectives: To determine whether mobile phone-based smoking cessation interventions increase smoking cessation rates in people who smoke.

Search methods: For this update, we searched the Cochrane Tobacco Addiction Group's Specialised Register, along with clinicaltrials.gov and the ICTRP. The date of the most recent searches was 29 October 2018.

Selection criteria: Participants were smokers of any age. Eligible interventions were those testing any type of predominantly mobile phone-based programme (such as text messages (or smartphone app) for smoking cessation. We included randomised controlled trials with smoking cessation outcomes reported at at least six-month follow-up.

Data collection and analysis: We used standard methodological procedures described in the Cochrane Handbook for Systematic Reviews of Interventions. We performed both study eligibility checks and data extraction in duplicate. We performed meta-analyses of the most stringent measures of abstinence at six months' follow-up or longer, using a Mantel-Haenszel random-effects method, pooling studies with similar interventions and similar comparators to calculate risk ratios (RR) and their corresponding 95% confidence intervals (CI). We conducted analyses including all randomised (with dropouts counted as still smoking) and complete cases only.

Main results: This review includes 26 studies (33,849 participants). Overall, we judged 13 studies to be at low risk of bias, three at high risk, and the remainder at unclear risk. Settings and recruitment procedures varied across studies, but most studies were conducted in high-income countries. There was moderate-certainty evidence, limited by inconsistency, that automated text messaging interventions were more effective than minimal smoking cessation support (RR 1.54, 95% CI 1.19 to 2.00; I2 = 71%; 13 studies, 14,133 participants). There was also moderate-certainty evidence, limited by imprecision, that text messaging added to other smoking cessation interventions was more effective than the other smoking cessation interventions alone (RR 1.59, 95% CI 1.09 to 2.33; I2 = 0%, 4 studies, 997 participants). Two studies comparing text messaging with other smoking cessation interventions, and three studies comparing high- and low-intensity messaging, did not show significant differences between groups (RR 0.92 95% CI 0.61 to 1.40; I2 = 27%; 2 studies, 2238 participants; and RR 1.00, 95% CI 0.95 to 1.06; I2 = 0%, 3 studies, 12,985 participants, respectively) but confidence intervals were wide in the former comparison. Five studies compared a smoking cessation smartphone app with lower-intensity smoking cessation support (either a lower-intensity app or non-app minimal support). We pooled the evidence and deemed it to be of very low certainty due to inconsistency and serious imprecision. It provided no evidence that smartphone apps improved the likelihood of smoking cessation (RR 1.00, 95% CI 0.66 to 1.52; I2 = 59%; 5 studies, 3079 participants). Other smartphone apps tested differed from the apps included in the analysis, as two used contingency management and one combined text messaging with an app, and so we did not pool them. Using complete case data as opposed to using data from all participants randomised did not substantially alter the findings.

Authors' conclusions: There is moderate-certainty evidence that automated text message-based smoking cessation interventions result in greater quit rates than minimal smoking cessation support. There is moderate-certainty evidence of the benefit of text messaging interventions in addition to other smoking cessation support in comparison with that smoking cessation support alone. The evidence comparing smartphone apps with less intensive support was of very low certainty, and more randomised controlled trials are needed to test these interventions.

Keywords 
Text Messaging cell phone smoking cessation tobacco Smokers

Association Between E-Cigarette Use and Chronic Obstructive Pulmonary Disease by Smoking Status: Behavioral Risk Factor Surveillance System 2016 and 2017

Author/s: 
Osei , A.D., Mirbolouk, M., Orimoloye, O.A., Dzaye, O.

Introduction: The association between e-cigarette use and chronic bronchitis, emphysema, and
chronic obstructive pulmonary disease has not been studied thoroughly, particularly in populations
defined by concomitant combustible smoking status.

Methods: Using pooled 2016 and 2017 data from the Behavioral Risk Factor Surveillance System,
investigators studied 705,159 participants with complete self-reported information on e-cigarette use,
combustible cigarette use, key covariates, and chronic bronchitis, emphysema, or chronic obstructive
pulmonary disease. Current e-cigarette use was the main exposure, with current use further classified
as daily or occasional use. The main outcome was defined as reported ever having a diagnosis of

chronic bronchitis, emphysema, or chronic obstructive pulmonary disease. For all the analyses, multi-
variable adjusted logistic regression was used, with the study population stratified by combustible ciga-
rette use status (never, former, or current). All the analyses were conducted in 2019.

Results: Of 705,159 participants, 25,175 (3.6%) were current e-cigarette users, 64,792 (9.2%) current
combustible cigarette smokers, 207,905 (29.5%) former combustible cigarette smokers, 432,462

(61.3%) never combustible cigarette smokers, and 14,036 (2.0%) dual users of e-cigarettes and combus-
tible cigarettes. A total of 53,702 (7.6%) participants self-reported chronic bronchitis, emphysema, or

chronic obstructive pulmonary disease. Among never combustible cigarette smokers, current e-ciga-
rette use was associated with 75% higher odds of chronic bronchitis, emphysema, or chronic obstruc-
tive pulmonary disease compared with never e-cigarette users (OR=1.75, 95% CI=1.25, 2.45), with

daily users of e-cigarettes having the highest odds (OR=2.64, 95% CI=1.43, 4.89). Similar associations
between e-cigarette use and chronic bronchitis, emphysema, or chronic obstructive pulmonary disease
were noted among both former and current combustible cigarette smokers.
Conclusions: The results suggest possible e-cigarette−related pulmonary toxicity across all thecategories of combustible cigarette smoking status, including those who had never smoked combus-
tible cigarettes.

Keywords 
vaping e-cigarette

Association of E-Cigarette Use With Respiratory Disease Among Adults: A Longitudinal Analysis

Author/s: 
Bhatta, DN, Glantz, SA

INTRODUCTION:

E-cigarettes deliver an aerosol of nicotine by heating a liquid and are promoted as an alternative to combustible tobacco. This study determines the longitudinal associations between e-cigarette use and respiratory disease controlling for combustible tobacco use.

METHODS:

This was a longitudinal analysis of the adult Population Assessment of Tobacco and Health Waves 1, 2, and 3. Multivariable logistic regression was performed to determine the associations between e-cigarette use and respiratory disease, controlling for combustible tobacco smoking, demographic, and clinical variables. Data were collected in 2013-2016 and analyzed in 2018-2019.

RESULTS:

Among people who did not report respiratory disease (chronic obstructive pulmonary disease, chronic bronchitis, emphysema, or asthma) at Wave 1, the longitudinal analysis revealed statistically significant associations between former e-cigarette use (AOR=1.31, 95% CI=1.07, 1.60) and current e-cigarette use (AOR=1.29, 95% CI=1.03, 1.61) at Wave 1 and having incident respiratory disease at Waves 2 or 3, controlling for combustible tobacco smoking, demographic, and clinical variables. Current combustible tobacco smoking (AOR=2.56, 95% CI=1.92, 3.41) was also significantly associated with having respiratory disease at Waves 2 or 3. Odds of developing respiratory disease for a current dual user (e-cigarette and all combustible tobacco) were 3.30 compared with a never smoker who never used e-cigarettes. Analysis controlling for cigarette smoking alone yielded similar results.

CONCLUSIONS:

Use of e-cigarettes is an independent risk factor for respiratory disease in addition to combustible tobacco smoking. Dual use, the most common use pattern, is riskier than using either product alone.

Keywords 
e-cigarette or vaping product use-associated lung injury vaping e-cigarettes smoking lung injury tobacco copd respiratory disease

Mobile phone text messaging and app-based interventions for smoking cessation

Author/s: 
Whittaker, R, McRobbie, H, Bullen, C, Rodgers, A, Gu, Y, Dobson, R

Abstract

Background

Mobile phone‐based smoking cessation support (mCessation) offers the opportunity to provide behavioural support to those who cannot or do not want face‐to‐face support. In addition, mCessation can be automated and therefore provided affordably even in resource‐poor settings. This is an update of a Cochrane Review first published in 2006, and previously updated in 2009 and 2012.

Objectives

To determine whether mobile phone‐based smoking cessation interventions increase smoking cessation rates in people who smoke.

Search methods

For this update, we searched the Cochrane Tobacco Addiction Group's Specialised Register, along with clinicaltrials.gov and the ICTRP. The date of the most recent searches was 29 October 2018.

Selection criteria

Participants were smokers of any age. Eligible interventions were those testing any type of predominantly mobile phone‐based programme (such as text messages (or smartphone app) for smoking cessation. We included randomised controlled trials with smoking cessation outcomes reported at at least six‐month follow‐up.

Data collection and analysis

We used standard methodological procedures described in the Cochrane Handbook for Systematic Reviews of Interventions. We performed both study eligibility checks and data extraction in duplicate. We performed meta‐analyses of the most stringent measures of abstinence at six months' follow‐up or longer, using a Mantel‐Haenszel random‐effects method, pooling studies with similar interventions and similar comparators to calculate risk ratios (RR) and their corresponding 95% confidence intervals (CI). We conducted analyses including all randomised (with dropouts counted as still smoking) and complete cases only.

Main results

This review includes 26 studies (33,849 participants). Overall, we judged 13 studies to be at low risk of bias, three at high risk, and the remainder at unclear risk. Settings and recruitment procedures varied across studies, but most studies were conducted in high‐income countries. There was moderate‐certainty evidence, limited by inconsistency, that automated text messaging interventions were more effective than minimal smoking cessation support (RR 1.54, 95% CI 1.19 to 2.00; I2 = 71%; 13 studies, 14,133 participants). There was also moderate‐certainty evidence, limited by imprecision, that text messaging added to other smoking cessation interventions was more effective than the other smoking cessation interventions alone (RR 1.59, 95% CI 1.09 to 2.33; I2 = 0%, 4 studies, 997 participants). Two studies comparing text messaging with other smoking cessation interventions, and three studies comparing high‐ and low‐intensity messaging, did not show significant differences between groups (RR 0.92 95% CI 0.61 to 1.40; I2 = 27%; 2 studies, 2238 participants; and RR 1.00, 95% CI 0.95 to 1.06; I2 = 0%, 3 studies, 12,985 participants, respectively) but confidence intervals were wide in the former comparison. Five studies compared a smoking cessation smartphone app with lower‐intensity smoking cessation support (either a lower‐intensity app or non‐app minimal support). We pooled the evidence and deemed it to be of very low certainty due to inconsistency and serious imprecision. It provided no evidence that smartphone apps improved the likelihood of smoking cessation (RR 1.00, 95% CI 0.66 to 1.52; I2 = 59%; 5 studies, 3079 participants). Other smartphone apps tested differed from the apps included in the analysis, as two used contingency management and one combined text messaging with an app, and so we did not pool them. Using complete case data as opposed to using data from all participants randomised did not substantially alter the findings.

Authors' conclusions

There is moderate‐certainty evidence that automated text message‐based smoking cessation interventions result in greater quit rates than minimal smoking cessation support. There is moderate‐certainty evidence of the benefit of text messaging interventions in addition to other smoking cessation support in comparison with that smoking cessation support alone. The evidence comparing smartphone apps with less intensive support was of very low certainty, and more randomised controlled trials are needed to test these interventions.

Plain Language Summary

Can programmes delivered by mobile phones help people to stop smoking?

Background

Tobacco smoking is a leading cause of preventable death. Mobile phones can be used to support people who want to quit smoking. In this review, we have focused on programmes that use text messages or smartphone apps to do so.

Search date

We searched for published and unpublished studies in October 2018.

Study characteristics

We included 26 randomised controlled studies (involving over 33,000 people) that compared smoking quit rates in people who received text messages or smartphone apps to help them quit, with people who did not receive these programmes. We were interested in studies that measured smoking for six months or longer.

Key results

We found that text messaging programmes may be effective in supporting people to quit, increasing quit rates by 50% to 60%. This was the case when they were compared to minimal support or were tested as an addition to other forms of stop‐smoking support. There was not enough evidence to determine the effect of smartphone apps.

Quality and completeness of the evidence

Most of the studies were of high quality, although three studies had high drop out rates. We are moderately confident in the results of the text messaging interventions, but there were some issues with unexplained differences between study findings and for some comparisons there was not much data. We have low confidence in the results concerning smartphone apps, and more studies are needed in this field.

Keywords 
smoking cessation mobile phone tobacco tobacco use text message
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