Evaluating the effect of smoking cessation treatment on a complex dynamical system

Understanding the motivational mechanisms for smoking and vaping among dual users and exclusive smokers

BACKGROUND

Understanding the motivational processes that influence e-cigarette use in a laboratory setting may help elucidate mechanisms that support long-term ecigarette use, which could have significant clinical and public health consequences.

METHODS

Secondary analyses were conducted on data from exclusive smokers (N=47) and dual users (N=88) who underwent a laboratory ad lib use session. Participants were given 10minutes to smoke (exclusive smokers) or vape (dual users) as much as they wanted. Withdrawal was assessed pre- and post-use. Smoking and vaping behavior was coded from session videos. Person-level predictors included cigarette/ecigarette craving-relief expectancies, demographics, and cigarette/e-cigarette use and dependence. Smoking and vaping status was assessed at Year 1 using self-reported 30-day point prevalence. Data were analyzed using general linear models and logistic regressions.

RESULTS

Both groups reported reductions in withdrawal after product use, including cigarette craving. Baseline e-cigarette craving-relief expectancies, pre-session ecigarette craving, heaviness of e-cigarette use, and relative e-cigarette dependence were significant univariate predictors of continued vaping in dual users at Year 1 (ORs>1.04, ps<.05). Dual users and exclusive smokers did not differ on use behavior (i.e., average number of puffs, ps>.16).

CONCLUSIONS

E-cigarette use alleviated withdrawal, including cigarette and e-cigarette craving, in dual users. Laboratory use behavior did not differ between dual users using e-cigarettes and exclusive smokers using cigarettes. Greater e-cigarette craving-relief expectancies, e-cigarette craving, heaviness of e-cigarette use, and morning product use pattern ('relative dependence') may reflect mechanisms that sustain e-cigarette use.

Predictors of substance use during treatment for addiction: A network analysis of ecological momentary assessment data

BACKGROUND AND AIMS

Ecological momentary assessment (EMA) studies have previously demonstrated a prospective influence of craving on substance use in the following hours. Conceptualizing substance use as a dynamic system of causal elements could provide valuable insights into the interaction of craving with other symptoms in the process of relapse. The aim of this study was to improve the understanding of these daily life dynamic inter-relationships by applying dynamic networks analyses to EMA data sets.

DESIGN, SETTING AND PARTICIPANTS

Secondary analyses were conducted on time-series data from two 2-week EMA studies. Data were collected in French outpatient addiction treatment centres. A total of 211 outpatients beginning treatment for alcohol, tobacco, cannabis, stimulants and opiate addiction took part.

MEASUREMENTS

Using mobile technologies, participants were questioned four times per day relative to substance use, craving, exposure to cues, mood, self-efficacy and pharmacological addiction treatment use. Multi-level vector auto-regression models were used to explore contemporaneous, temporal and between-subjects networks.

FINDINGS

Among the 8260 daily evaluations, the temporal network model, which depicts the lagged associations of symptoms within participants, demonstrated a unidirectional association between craving intensity at one time (T0) and primary substance use at the next assessment (T1, r = 0.1), after controlling for the effect of all other variables. A greater self-efficacy at T0 was associated with fewer cues (r = -0.04), less craving (r = -0.1) and less substance use at T1 (r = -0.07), and craving presented a negative feedback loop with self-efficacy (r = -0.09).

CONCLUSIONS

Dynamic network analyses showed that, among outpatients beginning treatment for addiction, high craving, together with low self-efficacy, appear to predict substance use more strongly than low mood or high exposure to cues.

Different doses, durations and modes of delivery of nicotine replacement therapy for smoking cessation

BACKGROUND

Nicotine replacement therapy (NRT) aims to replace nicotine from cigarettes. This helps to reduce cravings and withdrawal symptoms, and ease the transition from cigarette smoking to complete abstinence. Although there is high-certainty evidence that NRT is effective for achieving long-term smoking abstinence, it is unclear whether different forms, doses, durations of treatment or timing of use impacts its effects.

OBJECTIVES

To determine the effectiveness and safety of different forms, deliveries, doses, durations and schedules of NRT, for achieving long-term smoking cessation.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group trials register for papers mentioning NRT in the title, abstract or keywords, most recently in April 2022.

SELECTION CRITERIA

We included randomised trials in people motivated to quit, comparing one type of NRT use with another. We excluded studies that did not assess cessation as an outcome, with follow-up of fewer than six months, and with additional intervention components not matched between arms. Separate reviews cover studies comparing NRT to control, or to other pharmacotherapies.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods. We measured smoking abstinence after at least six months, using the most rigorous definition available. We extracted data on cardiac adverse events (AEs), serious adverse events (SAEs) and study withdrawals due to treatment.  MAIN RESULTS: We identified 68 completed studies with 43,327 participants, five of which are new to this update. Most completed studies recruited adults either from the community or from healthcare clinics. We judged 28 of the 68 studies to be at high risk of bias. Restricting the analysis only to those studies at low or unclear risk of bias did not significantly alter results for any comparisons apart from the preloading comparison, which tested the effect of using NRT prior to quit day whilst still smoking.  There is high-certainty evidence that combination NRT (fast-acting form plus patch) results in higher long-term quit rates than single form (risk ratio (RR) 1.27, 95% confidence interval (CI) 1.17 to 1.37; I2 = 12%; 16 studies, 12,169 participants). Moderate-certainty evidence, limited by imprecision, indicates that 42/44 mg patches are as effective as 21/22 mg (24-hour) patches (RR 1.09, 95% CI 0.93 to 1.29; I2 = 38%; 5 studies, 1655 participants), and that 21 mg patches are more effective than 14 mg (24-hour) patches (RR 1.48, 95% CI 1.06 to 2.08; 1 study, 537 participants). Moderate-certainty evidence, again limited by imprecision, also suggests a benefit of 25 mg over 15 mg (16-hour) patches, but the lower limit of the CI encompassed no difference (RR 1.19, 95% CI 1.00 to 1.41; I2 = 0%; 3 studies, 3446 participants). Nine studies tested the effect of using NRT prior to quit day (preloading) in comparison to using it from quit day onward. There was moderate-certainty evidence, limited by risk of bias, of a favourable effect of preloading on abstinence (RR 1.25, 95% CI 1.08 to 1.44; I2 = 0%; 9 studies, 4395 participants). High-certainty evidence from eight studies suggests that using either a form of fast-acting NRT or a nicotine patch results in similar long-term quit rates (RR 0.90, 95% CI 0.77 to 1.05; I2 = 0%; 8 studies, 3319 participants). We found no clear evidence of an effect of duration of nicotine patch use (low-certainty evidence); duration of combination NRT use (low- and very low-certainty evidence); or fast-acting NRT type (very low-certainty evidence). Cardiac AEs, SAEs and withdrawals due to treatment were all measured variably and infrequently across studies, resulting in low- or very low-certainty evidence for all comparisons. Most comparisons found no clear evidence of an effect on these outcomes, and rates were low overall. More withdrawals due to treatment were reported in people using nasal spray compared to patches in one study (RR 3.47, 95% CI 1.15 to 10.46; 1 study, 922 participants; very low-certainty evidence) and in people using 42/44 mg patches in comparison to 21/22 mg patches across two studies (RR 4.99, 95% CI 1.60 to 15.50; I2 = 0%; 2 studies, 544 participants; low-certainty evidence).

AUTHORS' CONCLUSIONS

There is high-certainty evidence that using combination NRT versus single-form NRT and 4 mg versus 2 mg nicotine gum can result in an increase in the chances of successfully stopping smoking. Due to imprecision, evidence was of moderate certainty for patch dose comparisons. There is some indication that the lower-dose nicotine patches and gum may be less effective than higher-dose products. Using a fast-acting form of NRT, such as gum or lozenge, resulted in similar quit rates to nicotine patches. There is moderate-certainty evidence that using NRT before quitting may improve quit rates versus using it from quit date only; however, further research is needed to ensure the robustness of this finding. Evidence for the comparative safety and tolerability of different types of NRT use is limited. New studies should ensure that AEs, SAEs and withdrawals due to treatment are reported.

Antidepressants for smoking cessation

BACKGROUND

The pharmacological profiles and mechanisms of antidepressants are varied. However, there are common reasons why they might help people to stop smoking tobacco: nicotine withdrawal can produce short-term low mood that antidepressants may relieve; and some antidepressants may have a specific effect on neural pathways or receptors that underlie nicotine addiction.

OBJECTIVES

To assess the evidence for the efficacy, harms, and tolerability of medications with antidepressant properties in assisting long-term tobacco smoking cessation in people who smoke cigarettes.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register, most recently on 29 April 2022.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) in people who smoked, comparing antidepressant medications with placebo or no pharmacological treatment, an alternative pharmacotherapy, or the same medication used differently. We excluded trials with fewer than six months of follow-up from efficacy analyses. We included trials with any follow-up length for our analyses of harms.

DATA COLLECTION AND ANALYSIS

We extracted data and assessed risk of bias using standard Cochrane methods. Our primary outcome measure was smoking cessation after at least six months' follow-up. We used the most rigorous definition of abstinence available in each trial, and biochemically validated rates if available. Our secondary outcomes were harms and tolerance outcomes, including adverse events (AEs), serious adverse events (SAEs), psychiatric AEs, seizures, overdoses, suicide attempts, death by suicide, all-cause mortality, and trial dropouts due to treatment. We carried out meta-analyses where appropriate.

MAIN RESULTS

We included a total of 124 studies (48,832 participants) in this review, with 10 new studies added to this update version. Most studies recruited adults from the community or from smoking cessation clinics; four studies focused on adolescents (with participants between 12 and 21 years old). We judged 34 studies to be at high risk of bias; however, restricting analyses only to studies at low or unclear risk of bias did not change clinical interpretation of the results.  There was high-certainty evidence that bupropion increased smoking cessation rates when compared to placebo or no pharmacological treatment (RR 1.60, 95% CI 1.49 to 1.72; I2 = 16%; 50 studies, 18,577 participants). There was moderate-certainty evidence that a combination of bupropion and varenicline may have resulted in superior quit rates to varenicline alone (RR 1.21, 95% CI 0.95 to 1.55; I2 = 15%; 3 studies, 1057 participants). However, there was insufficient evidence to establish whether a combination of bupropion and nicotine replacement therapy (NRT) resulted in superior quit rates to NRT alone (RR 1.17, 95% CI 0.95 to 1.44; I2 = 43%; 15 studies, 4117 participants; low-certainty evidence). There was moderate-certainty evidence that participants taking bupropion were more likely to report SAEs than those taking placebo or no pharmacological treatment. However, results were imprecise and the CI also encompassed no difference (RR 1.16, 95% CI 0.90 to 1.48; I2 = 0%; 23 studies, 10,958 participants). Results were also imprecise when comparing SAEs between people randomised to a combination of bupropion and NRT versus NRT alone (RR 1.52, 95% CI 0.26 to 8.89; I2 = 0%; 4 studies, 657 participants) and randomised to bupropion plus varenicline versus varenicline alone (RR 1.23, 95% CI 0.63 to 2.42; I2 = 0%; 5 studies, 1268 participants). In both cases, we judged evidence to be of low certainty. There was high-certainty evidence that bupropion resulted in more trial dropouts due to AEs than placebo or no pharmacological treatment (RR 1.44, 95% CI 1.27 to 1.65; I2 = 2%; 25 studies, 12,346 participants). However, there was insufficient evidence that bupropion combined with NRT versus NRT alone (RR 1.67, 95% CI 0.95 to 2.92; I2 = 0%; 3 studies, 737 participants) or bupropion combined with varenicline versus varenicline alone (RR 0.80, 95% CI 0.45 to 1.45; I2 = 0%; 4 studies, 1230 participants) had an impact on the number of dropouts due to treatment. In both cases, imprecision was substantial (we judged the evidence to be of low certainty for both comparisons). Bupropion resulted in inferior smoking cessation rates to varenicline (RR 0.73, 95% CI 0.67 to 0.80; I2 = 0%; 9 studies, 7564 participants), and to combination NRT (RR 0.74, 95% CI 0.55 to 0.98; I2 = 0%; 2 studies; 720 participants). However, there was no clear evidence of a difference in efficacy between bupropion and single-form NRT (RR 1.03, 95% CI 0.93 to 1.13; I2 = 0%; 10 studies, 7613 participants). We also found evidence that nortriptyline aided smoking cessation when compared with placebo (RR 2.03, 95% CI 1.48 to 2.78; I2 = 16%; 6 studies, 975 participants), and some evidence that bupropion resulted in superior quit rates to nortriptyline (RR 1.30, 95% CI 0.93 to 1.82; I2 = 0%; 3 studies, 417 participants), although this result was subject to imprecision. Findings were sparse and inconsistent as to whether antidepressants, primarily bupropion and nortriptyline, had a particular benefit for people with current or previous depression.

AUTHORS' CONCLUSIONS

There is high-certainty evidence that bupropion can aid long-term smoking cessation. However, bupropion may increase SAEs (moderate-certainty evidence when compared to placebo/no pharmacological treatment). There is high-certainty evidence that people taking bupropion are more likely to discontinue treatment compared with people receiving placebo or no pharmacological treatment. Nortriptyline also appears to have a beneficial effect on smoking quit rates relative to placebo, although bupropion may be more effective. Evidence also suggests that bupropion may be as successful as single-form NRT in helping people to quit smoking, but less effective than combination NRT and varenicline. In most cases, a paucity of data made it difficult to draw conclusions regarding harms and tolerability. Further studies investigating the efficacy of bupropion versus placebo are unlikely to change our interpretation of the effect, providing no clear justification for pursuing bupropion for smoking cessation over other licensed smoking cessation treatments; namely, NRT and varenicline. However, it is important that future studies of antidepressants for smoking cessation measure and report on harms and tolerability.

Associations between simultaneous alcohol and cannabis use and next-day negative affect among young adults: The role of sex and trait anxiety

BACKGROUND AND AIMS

The simultaneous use of alcohol and cannabis ("simultaneous alcohol and marijuana [SAM] use") is common among young adults and associated with negative substance-related consequences. SAM use may be tied to fluctuating mood states such as negative affect and individual characteristics including trait level of anxiety and sex. However, little is understood about their collective role. In this study, we sought to understand the daily link between SAM use and negative affect and whether this link might differ by both trait anxiety and sex.

METHOD

Participants were 154 young adults (57.8% female, 72.7% White, M age = 20.2) who completed baseline surveys on trait anxiety symptoms and up to 14 consecutive daily surveys on their substance use and affective states.

RESULTS

Multilevel models tested for associations of type of substance use day (i.e., alcohol-only days, cannabis-only days, and no use days relative to SAM use days) with next-day negative affect. Three-way and lower order interactions were tested for substance use day type, anxiety, and sex. Two three-way interactions between cannabis-only days, anxiety, and sex and between alcohol-only days, anxiety, and sex emerged such that SAM use was associated with greater next-day negative affect relative to single substance use days particularly among female participants with elevated anxiety.

CONCLUSIONS

Anxiety and sex are salient factors in the link between SAM use relative to single-substance use and daily negative affect. Study findings reinforce the need to account for all of these factors in order to develop maximally efficacious substance use interventions.

Dynamic models of stress-smoking responses based on high-frequency sensor data

Self-reports indicate that stress increases the risk for smoking; however, intensive data from sensors can provide a more nuanced understanding of stress in the moments leading up to and following smoking events. Identifying personalized dynamical models of stress-smoking responses can improve characterizations of smoking responses following stress, but techniques used to identify these models require intensive longitudinal data. This study leveraged advances in wearable sensing technology and digital markers of stress and smoking to identify person-specific models of stress and smoking system dynamics by considering stress immediately before, during, and after smoking events. Adult smokers (n = 45) wore the AutoSense chestband (respiration-inductive plethysmograph, electrocardiogram, accelerometer) with MotionSense (accelerometers, gyroscopes) on each wrist for three days prior to a quit attempt. The odds of minute-level smoking events were regressed on minute-level stress probabilities to identify person-specific dynamic models of smoking responses to stress. Simulated pulse responses to a continuous stress episode revealed a consistent pattern of increased odds of smoking either shortly after the beginning of the simulated stress episode or with a delay, for all participants. This pattern is followed by a dramatic reduction in the probability of smoking thereafter, for about half of the participants (49%). Sensor-detected stress probabilities indicate a vulnerability for smoking that may be used as a tailoring variable for just-in-time interventions to support quit attempts.

Temporal networks of tobacco withdrawal symptoms during smoking cessation treatment

A recently developed network perspective on tobacco withdrawal posits that withdrawal symptoms causally influence one another across time, rather than simply being indicators of a latent syndrome. Evidence supporting a network perspective would shift the focus of tobacco withdrawal research and intervention toward studying and treating individual withdrawal symptoms and intersymptom associations. Here we construct and examine temporal tobacco withdrawal networks that describe the interplay among withdrawal symptoms across time using experience-sampling data from 1,210 participants (58.35% female, 86.24% White) undergoing smoking cessation treatment. We also construct person-specific withdrawal networks and capture individual differences in the extent to which withdrawal symptom networks promote the spread of symptom activity through the network across time using impulse response analysis. Results indicate substantial moment-to-moment associations among withdrawal symptoms, substantial between-person differences in withdrawal network structure, and reductions in the interplay among withdrawal symptoms during combination smoking cessation treatment. Overall, findings suggest the utility of a network perspective and also highlight challenges associated with the network approach stemming from vast between-person differences in symptom networks. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Antidepressants for smoking cessation

BACKGROUND

Whilst the pharmacological profiles and mechanisms of antidepressants are varied, there are common reasons why they might help people to stop smoking tobacco. Firstly, nicotine withdrawal may produce depressive symptoms and antidepressants may relieve these. Additionally, some antidepressants may have a specific effect on neural pathways or receptors that underlie nicotine addiction.

OBJECTIVES

To assess the evidence for the efficacy, safety and tolerability of medications with antidepressant properties in assisting long-term tobacco smoking cessation in people who smoke cigarettes.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Specialized Register, which includes reports of trials indexed in the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PsycINFO, clinicaltrials.gov, the ICTRP, and other reviews and meeting abstracts, in May 2019.

SELECTION CRITERIA

We included randomized controlled trials (RCTs) that recruited smokers, and compared antidepressant medications with placebo or no treatment, an alternative pharmacotherapy, or the same medication used in a different way. We excluded trials with less than six months follow-up from efficacy analyses. We included trials with any follow-up length in safety analyses.

DATA COLLECTION AND ANALYSIS

We extracted data and assessed risk of bias using standard Cochrane methods. We also used GRADE to assess the certainty of the evidence. The primary outcome measure was smoking cessation after at least six months follow-up, expressed as a risk ratio (RR) and 95% confidence intervals (CIs). We used the most rigorous definition of abstinence available in each trial, and biochemically validated rates if available. Where appropriate, we performed meta-analysis using a fixed-effect model. Similarly, we presented incidence of safety and tolerance outcomes, including adverse events (AEs), serious adverse events (SAEs), psychiatric AEs, seizures, overdoses, suicide attempts, death by suicide, all-cause mortality, and trial dropout due to drug, as RRs (95% CIs).

MAIN RESULTS

We included 115 studies (33 new to this update) in this review; most recruited adult participants from the community or from smoking cessation clinics. We judged 28 of the studies to be at high risk of bias; however, restricting analyses only to studies at low or unclear risk did not change clinical interpretation of the results. There was high-certainty evidence that bupropion increased long-term smoking cessation rates (RR 1.64, 95% CI 1.52 to 1.77; I2 = 15%; 45 studies, 17,866 participants). There was insufficient evidence to establish whether participants taking bupropion were more likely to report SAEs compared to those taking placebo. Results were imprecise and CIs encompassed no difference (RR 1.16, 95% CI 0.90 to 1.48; I2 = 0%; 21 studies, 10,625 participants; moderate-certainty evidence, downgraded one level due to imprecision). We found high-certainty evidence that use of bupropion resulted in more trial dropouts due to adverse events of the drug than placebo (RR 1.37, 95% CI 1.21 to 1.56; I2 = 19%; 25 studies, 12,340 participants). Participants randomized to bupropion were also more likely to report psychiatric AEs compared with those randomized to placebo (RR 1.25, 95% CI 1.15 to 1.37; I2 = 15%; 6 studies, 4439 participants). We also looked at the safety and efficacy of bupropion when combined with other non-antidepressant smoking cessation therapies. There was insufficient evidence to establish whether combination bupropion and nicotine replacement therapy (NRT) resulted in superior quit rates to NRT alone (RR 1.19, 95% CI 0.94 to 1.51; I2 = 52%; 12 studies, 3487 participants), or whether combination bupropion and varenicline resulted in superior quit rates to varenicline alone (RR 1.21, 95% CI 0.95 to 1.55; I2 = 15%; 3 studies, 1057 participants). We judged the certainty of evidence to be low and moderate, respectively; in both cases due to imprecision, and also due to inconsistency in the former. Safety data were sparse for these comparisons, making it difficult to draw clear conclusions. A meta-analysis of six studies provided evidence that bupropion resulted in inferior smoking cessation rates to varenicline (RR 0.71, 95% CI 0.64 to 0.79; I2 = 0%; 6 studies, 6286 participants), whilst there was no evidence of a difference in efficacy between bupropion and NRT (RR 0.99, 95% CI 0.91 to 1.09; I2 = 18%; 10 studies, 8230 participants). We also found some evidence that nortriptyline aided smoking cessation when compared with placebo (RR 2.03, 95% CI 1.48 to 2.78; I2 = 16%; 6 studies, 975 participants), whilst there was insufficient evidence to determine whether bupropion or nortriptyline were more effective when compared with one another (RR 1.30 (favouring bupropion), 95% CI 0.93 to 1.82; I2 = 0%; 3 studies, 417 participants). There was no evidence that any of the other antidepressants tested (including St John's Wort, selective serotonin reuptake inhibitors (SSRIs), monoamine oxidase inhibitors (MAOIs)) had a beneficial effect on smoking cessation. Findings were sparse and inconsistent as to whether antidepressants, primarily bupropion and nortriptyline, had a particular benefit for people with current or previous depression.

AUTHORS' CONCLUSIONS

There is high-certainty evidence that bupropion can aid long-term smoking cessation. However, bupropion also increases the number of adverse events, including psychiatric AEs, and there is high-certainty evidence that people taking bupropion are more likely to discontinue treatment compared with placebo. However, there is no clear evidence to suggest whether people taking bupropion experience more or fewer SAEs than those taking placebo (moderate certainty). Nortriptyline also appears to have a beneficial effect on smoking quit rates relative to placebo. Evidence suggests that bupropion may be as successful as NRT and nortriptyline in helping people to quit smoking, but that it is less effective than varenicline. There is insufficient evidence to determine whether the other antidepressants tested, such as SSRIs, aid smoking cessation, and when looking at safety and tolerance outcomes, in most cases, paucity of data made it difficult to draw conclusions. Due to the high-certainty evidence, further studies investigating the efficacy of bupropion versus placebo are unlikely to change our interpretation of the effect, providing no clear justification for pursuing bupropion for smoking cessation over front-line smoking cessation aids already available. However, it is important that where studies of antidepressants for smoking cessation are carried out they measure and report safety and tolerability clearly.

The Network Structure of Tobacco Withdrawal in a Community Sample of Smokers Treated With Nicotine Patch and Behavioral Counseling

INTRODUCTION

Network theories of psychopathology highlight that, rather than being indicators of a latent disorder, symptoms of disorders can causally interact with one another in a network. This study examined tobacco withdrawal from a network perspective.

METHODS

Participants (n = 525, 50.67% female) completed the Minnesota Tobacco Withdrawal Scale four times (2 weeks prior to a target quit day, on the target quit day, and 4 and 8 weeks after the target quit day) over the course of 8 weeks of treatment with nicotine patch and behavioral counseling within a randomized clinical trial testing long-term nicotine patch therapy in treatment-seeking smokers. The conditional dependence among seven withdrawal symptoms was estimated at each of the four measurement occasions. Influential symptoms of withdrawal were identified using centrality indices. Changes in network structure were examined using the Network Comparison Test.

RESULTS

Findings indicated many associations among the individual symptoms of withdrawal. The strongest associations that emerged were between sleep problems and restlessness, and associations among affective symptoms. Restlessness and affective symptoms emerged as the most central symptoms in the withdrawal networks. Minimal differences in the structure of the withdrawal networks emerged across time.

CONCLUSIONS

The cooccurrence of withdrawal symptoms may result from interactions among symptoms of withdrawal rather than simply reflecting passive indicators of a latent disorder. Findings encourage greater consideration of individual withdrawal symptoms and their potential interactions and may be used to generate hypotheses that may be tested in future intensive longitudinal studies.

IMPLICATIONS

This study provides a novel, network perspective on tobacco withdrawal. Drawing on network theories of psychopathology, we suggest that the cooccurrence of withdrawal symptoms may result from interactions among symptoms of withdrawal over time, rather than simply reflecting passive indicators of a latent disorder. Results indicating many associations among individual symptoms of withdrawal are consistent with a network perspective. Other results of interest include minimal changes in the network structure of withdrawal across four measurement occasions prior to and during treatment with nicotine patch and behavioral counseling.

Different doses, durations and modes of delivery of nicotine replacement therapy for smoking cessation

BACKGROUND

Nicotine replacement therapy (NRT) aims to replace nicotine from cigarettes to ease the transition from cigarette smoking to abstinence. It works by reducing the intensity of craving and withdrawal symptoms. Although there is clear evidence that NRT used after smoking cessation is effective, it is unclear whether higher doses, longer durations of treatment, or using NRT before cessation add to its effectiveness.

OBJECTIVES

To determine the effectiveness and safety of different forms, deliveries, doses, durations and schedules of NRT, for achieving long-term smoking cessation, compared to one another.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group trials register, and trial registries for papers mentioning NRT in the title, abstract or keywords. Date of most recent search: April 2018.

SELECTION CRITERIA

Randomized trials in people motivated to quit, comparing one type of NRT use with another. We excluded trials that did not assess cessation as an outcome, with follow-up less than six months, and with additional intervention components not matched between arms. Trials comparing NRT to control, and trials comparing NRT to other pharmacotherapies, are covered elsewhere.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods. Smoking abstinence was measured after at least six months, using the most rigorous definition available. We extracted data on cardiac adverse events (AEs), serious adverse events (SAEs), and study withdrawals due to treatment. We calculated the risk ratio (RR) and the 95% confidence interval (CI) for each outcome for each study, where possible. We grouped eligible studies according to the type of comparison. We carried out meta-analyses where appropriate, using a Mantel-Haenszel fixed-effect model.

MAIN RESULTS

We identified 63 trials with 41,509 participants. Most recruited adults either from the community or from healthcare clinics. People enrolled in the studies typically smoked at least 15 cigarettes a day. We judged 24 of the 63 studies to be at high risk of bias, but restricting the analysis only to those studies at low or unclear risk of bias did not significantly alter results, apart from in the case of the preloading comparison. There is high-certainty evidence that combination NRT (fast-acting form + patch) results in higher long-term quit rates than single form (RR 1.25, 95% CI 1.15 to 1.36, 14 studies, 11,356 participants; I² = 4%). Moderate-certainty evidence, limited by imprecision, indicates that 42/44 mg are as effective as 21/22 mg (24-hour) patches (RR 1.09, 95% CI 0.93 to 1.29, 5 studies, 1655 participants; I² = 38%), and that 21 mg are more effective than 14 mg (24-hour) patches (RR 1.48, 95% CI 1.06 to 2.08, 1 study, 537 participants). Moderate-certainty evidence (again limited by imprecision) also suggests a benefit of 25 mg over 15 mg (16-hour) patches, but the lower limit of the CI encompassed no difference (RR 1.19, 95% CI 1.00 to 1.41, 3 studies, 3446 participants; I² = 0%). Five studies comparing 4 mg gum to 2 mg gum found a benefit of the higher dose (RR 1.43, 95% CI 1.12 to 1.83, 5 studies, 856 participants; I² = 63%); however, results of a subgroup analysis suggest that only smokers who are highly dependent may benefit. Nine studies tested the effect of using NRT prior to quit day (preloading) in comparison to using it from quit day onward; there was moderate-certainty evidence, limited by risk of bias, of a favourable effect of preloading on abstinence (RR 1.25, 95% CI 1.08 to 1.44, 9 studies, 4395 participants; I² = 0%). High-certainty evidence from eight studies suggests that using either a form of fast-acting NRT or a nicotine patch results in similar long-term quit rates (RR 0.90, 95% CI 0.77 to 1.05, 8 studies, 3319 participants; I² = 0%). We found no evidence of an effect of duration of nicotine patch use (low-certainty evidence); 16-hour versus 24-hour daily patch use; duration of combination NRT use (low- and very low-certainty evidence); tapering of patch dose versus abrupt patch cessation; fast-acting NRT type (very low-certainty evidence); duration of nicotine gum use; ad lib versus fixed dosing of fast-acting NRT; free versus purchased NRT; length of provision of free NRT; ceasing versus continuing patch use on lapse; and participant- versus clinician-selected NRT. However, in most cases these findings are based on very low- or low-certainty evidence, and are the findings from single studies.AEs, SAEs and withdrawals due to treatment were all measured variably and infrequently across studies, resulting in low- or very low-certainty evidence for all comparisons. Most comparisons found no evidence of an effect on cardiac AEs, SAEs or withdrawals. Rates of these were low overall. Significantly more withdrawals due to treatment were reported in participants using nasal spray in comparison to patch in one trial (RR 3.47, 95% CI 1.15 to 10.46, 922 participants; very low certainty) and in participants using 42/44 mg patches in comparison to 21/22 mg patches across two trials (RR 4.99, 95% CI 1.60 to 15.50, 2 studies, 544 participants; I² = 0%; low certainty).

AUTHORS' CONCLUSIONS

There is high-certainty evidence that using combination NRT versus single-form NRT, and 4 mg versus 2 mg nicotine gum, can increase the chances of successfully stopping smoking. For patch dose comparisons, evidence was of moderate certainty, due to imprecision. Twenty-one mg patches resulted in higher quit rates than 14 mg (24-hour) patches, and using 25 mg patches resulted in higher quit rates than using 15 mg (16-hour) patches, although in the latter case the CI included one. There was no clear evidence of superiority for 42/44 mg over 21/22 mg (24-hour) patches. Using a fast-acting form of NRT, such as gum or lozenge, resulted in similar quit rates to nicotine patches. There is moderate-certainty evidence that using NRT prior to quitting may improve quit rates versus using it from quit date only; however, further research is needed to ensure the robustness of this finding. Evidence for the comparative safety and tolerability of different types of NRT use is of low and very low certainty. New studies should ensure that AEs, SAEs and withdrawals due to treatment are both measured and reported.

Longer duration of smoking abstinence is associated with waning cessation fatigue

BACKGROUND

Cessation fatigue, a construct theorized to reflect exhaustion of coping resources due to quitting smoking, has been found to predict relapse. This study examines the association between cessation fatigue and duration of abstinence among 1397 adult former smokers who participated in the 2016 International Tobacco Control (ITC) Four Country Smoking and Vaping Wave 1 Survey (4CV). We hypothesized lower levels of cessation fatigue will be correlated with longer duration of abstinence.

METHOD

Data for this cross-sectional study were collected in a web-based survey which recruited national samples from Australia, Canada, England, and United States. Former smokers were abstinent up to five years.

RESULTS

Lower cessation fatigue was associated with longer duration of smoking abstinence. Cessation fatigue was highest in former smokers that had been quit for up to six months, with lower cessation fatigue found in those quit for at least seven months and another drop-off in fatigue observed for those quit for at least two years.

CONCLUSIONS

Cessation fatigue is highest soon after quitting smoking but declines over time for those who remain abstinent. Understanding the mechanisms by which cessation fatigue is related to abstinence could potentially offer insights into ways to help individuals sustain quitting.