The impact of perceived treatment assignment on smoking cessation outcomes among African-American smokers

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.

Assessment of patient perception of treatment assignment and patient-reported outcomes in a cannabis use disorder trial

Background: Blinding is a cornerstone of trial methodology. Prior work indicates participant-perceived assignment may be associated with trial outcomes. Less is known about how perception changes over time and if this is associated with outcomes.Objectives: To evaluate if participants change their perception of assignment over time in a blinded trial, and if perception is associated with different types of patient-reported outcomes (PROs).Methods: This was a secondary analysis of data from the Achieving Cannabis Cessation-Evaluating N-Acetylcysteine Treatment (ACCENT) trial, which evaluated the efficacy of N-acetylcysteine (NAC) relative to placebo for treating cannabis use disorder. Participants (N = 234; 164 men, 70 women) were asked at weeks 5 and 9 what treatment (placebo or NAC) they believed they were receiving. We included PROs proximal (cannabis-associated problems, craving) and distal (anxiety) to the intervention. Analysis was by multiple linear regression and mixed models.Results: Approximately 20% of participants in both arms changed their perception over time. Relative to participants who consistently perceived assignment to placebo, participants who consistently perceived assignment to NAC did not always have comparatively better average scores (coefficient -3.3 [95% CI: -7.0, 0.5]). In some analyses, participants who switched to guessing NAC from placebo had comparatively better average scores (coefficient -3.0 [95% CI: -9.3, 3.4]), but this was inconsistent across outcomes or strata defined by actual assignment or guess accuracy.Conclusion: The study suggests that the proportion of individuals who switch their perception over time is modest. However, this group may influence the estimates of intervention effects on some PROs.

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.

Mechanisms of Perceived Treatment Assignment and Subsequent Expectancy Effects in a Double Blind Placebo Controlled RCT of Major Depression

Objective: It has been suggested that patients' perception of treatment assignment might serve to bias results of double blind randomized controlled trials (RCT). Most previous evidence on the effects of patients' perceptions and the mechanisms influencing these perceptions relies on cross-sectional associations. This re-analysis of a double blind, placebo controlled RCT of pharmacological treatment of major depression set out to gather longitudinal evidence on the mechanism and effects of patients' perceived treatment assignment in the pharmacological treatment of major depression. Methods: One-hundred eighty-nine outpatients with DSM-IV diagnosed major depression were randomized to SAMe 1,600-3,200 mg/d, escitalopram 10-20 mg/days, or placebo for 12 weeks. Data on depressive symptoms (17-item Hamilton Depression Scale; HDRS-17), adverse events and patients' perceived treatment assignment was collected at baseline, week 6, and week 12. The re-analysis focused on N = 166 (out of the originally included 189 participants) with available data on perceived treatment assignment. Results: As in the parent trial, depressive symptoms (HDRS-17) significantly decreased over the course of 12 weeks and there was no difference between placebo, SAMe or escitalopram. A significant number of patients changed their perceptions about treatment assignment throughout the trial, especially between baseline and week 6. Improvement in depressive symptoms, but not adverse events significantly predicted perceived treatment assignment at week 6. In turn, perceived treatment assignment at week 6, but not actual treatment, predicted further improvement in depressive symptoms at week 12. Conclusions: The current results provide longitudinal evidence that patients' perception of treatment assignment systematically change despite a double blind procedure and in turn might trigger expectancy effects with the potential to bias the validity of an RCT. Parent study grant number: R01 AT001638 Parent study ClinicalTrials. gov Identifier: NCT00101452.

Randomized controlled trial examining expectancy effects on the accuracy of weight measurement

BACKGROUND

Researchers and participants' expectations can influence treatment response. Less is known about the effects of researchers' expectations on the accuracy of data collection in the context of a weight loss trial.

METHODS

Student raters (N = 58; age = 20.1 ± 2.3 years) were recruited to weigh individuals who they thought were completing a 12-month weight loss trial, although these 'participants' were actually standardized patients (SPs) playing these roles. Prior to data collection, student raters were provided information suggesting that the tested treatment had been effective. Each student rater received a list of 9-10 'participants' to weigh. While the list identified each person as 'treatment' or 'control', this assignment was at random, which allowed us to examine the effects of non-blinding and expectancy manipulation on weight measurement accuracy. We hypothesized that raters would record the weights of 'treatment participants' as lower than those of 'control participants'.

RESULTS

Contrary to our hypothesis, raters recorded weights that were 0.293 kg heavier when weighing 'treatment' vs. 'control' SPs, although this difference was not significant (P = 0.175).

CONCLUSIONS

This pilot study found no evidence that manipulating expectancies about treatment efficacy or not blinding raters biased measurements. Future work should examine other biases which may be created by not blinding research staff who implement weight loss trials as well as the participants in those trials.

Smokers' Treatment Expectancies Predict Smoking Cessation Success

INTRODUCTION

Smokers' treatment expectancies may influence their choice of a particular medication as well as their medication experience.

AIMS

This study examined the role of smokers' treatment expectancies to their smoking cessation outcomes in a completed, randomized, placebo-controlled trial of naltrexone for smoking cessation, controlling for perceptions of treatment assignment.

METHODS

Treatment seeking cigarette smokers (N = 315) were randomized to receive either naltrexone (50 mg) or placebo in combination with nicotine patch and behavioral counseling. Expectancies for naltrexone as a smoking cessation aid were assessed at baseline and 4 weeks after the quit date.

RESULTS

More positive baseline medication expectancies predicted higher quit rates at one month in the naltrexone (OR =1.45, p =.04) group but were associated with lower quit rates in the placebo group (OR =.66, p =.03). Maintaining and/or increasing positive medication expectancies in the first month of treatment was associated with better pill adherence during this interval in the naltrexone group (ps <.05). Positive baseline medication expectancies were also associated with the perception of having received naltrexone over placebo among all participants.

CONCLUSIONS

Positive medication expectancies in smokers may contribute to better treatment response. Assessing treatment expectancies and attempting to maintain or improve them may be important for the delivery, evaluation, and targeting of smoking cessation treatments.

Perceived medication assignment during a placebo-controlled laboratory study of varenicline: temporal associations of treatment expectancies with smoking-related outcomes

RATIONALE

Expectancies regarding treatment assignment may influence outcomes in placebo-controlled trials above and beyond actual treatment assignment. For smoking pharmacotherapies, guessing enrollment in the active medication treatment is associated with higher abstinence rates. However, placebo-controlled trials of smoking pharmacotherapies rarely assess perceived treatment assignment and those that do only collect this information after reaching full dosage.

OBJECTIVES

To determine the temporal relationship between treatment expectancies and smoking-related variables, we assessed the impact of treatment guess during a placebo-controlled laboratory study of varenicline on measures of craving, smoking reward, and smoking reinforcement. We hypothesized that treatment guess at mid-titration would influence smoking-related measures at full dosage, above and beyond actual medication effects. We also explored factors related to guess stability and differences in blind fidelity between mid-drug titration and full dosage.

METHODS

Eighty-eight participants completed laboratory assessments at baseline, mid-titration, and full dosage that involved self-report and behavioral measures of tonic craving, cue-provoked craving, smoking reward, and smoking reinforcement. Participants guessed treatment assignment at mid-titration and full dosage.

RESULTS

Generalized linear models confirmed that, beyond actual treatment assignment, treatment guess improved model fit for both self-report and behavioral smoking-related measures. Further, accuracy of treatment guess improved from titration to full dosage, and specific demographic factors (e.g., gender, race) were associated with type of treatment guess and guess stability across time.

CONCLUSIONS

These results reinforce the importance of assessing perceived treatment assignment repeatedly during placebo-controlled trials and suggest that treatment expectancies during titration can affect outcomes once full dosage has been reached.

Antidepressants for smoking cessation

BACKGROUND

There are at least three reasons to believe antidepressants might help in smoking cessation. Firstly, nicotine withdrawal may produce depressive symptoms or precipitate a major depressive episode and antidepressants may relieve these. Secondly, nicotine may have antidepressant effects that maintain smoking, and antidepressants may substitute for this effect. Finally, some antidepressants may have a specific effect on neural pathways (e.g. inhibiting monoamine oxidase) or receptors (e.g. blockade of nicotinic-cholinergic receptors) underlying nicotine addiction.

OBJECTIVES

The aim of this review is to assess the effect and safety of antidepressant medications to aid long-term smoking cessation. The medications include bupropion; doxepin; fluoxetine; imipramine; lazabemide; moclobemide; nortriptyline; paroxetine; S-Adenosyl-L-Methionine (SAMe); selegiline; sertraline; St. John's wort; tryptophan; venlafaxine; and zimeledine.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register which includes reports of trials indexed in the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, and PsycINFO, and other reviews and meeting abstracts, in July 2013.

SELECTION CRITERIA

We considered randomized trials comparing antidepressant medications to placebo or an alternative pharmacotherapy for smoking cessation. We also included trials comparing different doses, using pharmacotherapy to prevent relapse or re-initiate smoking cessation or to help smokers reduce cigarette consumption. We excluded trials with less than six months follow-up.

DATA COLLECTION AND ANALYSIS

We extracted data and assessed risk of bias using standard methodological procedures expected by the Cochrane Collaboration.The main outcome measure was abstinence from smoking after at least six months follow-up in patients smoking at baseline, expressed as a risk ratio (RR). 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.

MAIN RESULTS

Twenty-four new trials were identified since the 2009 update, bringing the total number of included trials to 90. There were 65 trials of bupropion and ten trials of nortriptyline, with the majority at low or unclear risk of bias. There was high quality evidence that, when used as the sole pharmacotherapy, bupropion significantly increased long-term cessation (44 trials, N = 13,728, risk ratio [RR] 1.62, 95% confidence interval [CI] 1.49 to 1.76). There was moderate quality evidence, limited by a relatively small number of trials and participants, that nortriptyline also significantly increased long-term cessation when used as the sole pharmacotherapy (six trials, N = 975, RR 2.03, 95% CI 1.48 to 2.78). There is insufficient evidence that adding bupropion (12 trials, N = 3487, RR 1.9, 95% CI 0.94 to 1.51) or nortriptyline (4 trials, N = 1644, RR 1.21, 95% CI 0.94 to 1.55) to nicotine replacement therapy (NRT) provides an additional long-term benefit. Based on a limited amount of data from direct comparisons, bupropion and nortriptyline appear to be equally effective and of similar efficacy to NRT (bupropion versus nortriptyline 3 trials, N = 417, RR 1.30, 95% CI 0.93 to 1.82; bupropion versus NRT 8 trials, N = 4096, RR 0.96, 95% CI 0.85 to 1.09; no direct comparisons between nortriptyline and NRT). Pooled results from four trials comparing bupropion to varenicline showed significantly lower quitting with bupropion than with varenicline (N = 1810, RR 0.68, 95% CI 0.56 to 0.83). Meta-analyses did not detect a significant increase in the rate of serious adverse events amongst participants taking bupropion, though the confidence interval only narrowly missed statistical significance (33 trials, N = 9631, RR 1.30, 95% CI 1.00 to 1.69). There is a risk of about 1 in 1000 of seizures associated with bupropion use. Bupropion has been associated with suicide risk, but whether this is causal is unclear. Nortriptyline has the potential for serious side-effects, but none have been seen in the few small trials for smoking cessation.There was no evidence of a significant effect for selective serotonin reuptake inhibitors on their own (RR 0.93, 95% CI 0.71 to 1.22, N = 1594; 2 trials fluoxetine, 1 paroxetine, 1 sertraline) or as an adjunct to NRT (3 trials of fluoxetine, N = 466, RR 0.70, 95% CI 0.64 to 1.82). Significant effects were also not detected for monoamine oxidase inhibitors (RR 1.29, 95% CI 0.93 to 1.79, N = 827; 1 trial moclobemide, 5 selegiline), the atypical antidepressant venlafaxine (1 trial, N = 147, RR 1.22, 95% CI 0.64 to 2.32), the herbal therapy St John's wort (hypericum) (2 trials, N = 261, RR 0.81, 95% CI 0.26 to 2.53), or the dietary supplement SAMe (1 trial, N = 120, RR 0.70, 95% CI 0.24 to 2.07).

AUTHORS' CONCLUSIONS

The antidepressants bupropion and nortriptyline aid long-term smoking cessation. Adverse events with either medication appear to rarely be serious or lead to stopping medication. Evidence suggests that the mode of action of bupropion and nortriptyline is independent of their antidepressant effect and that they are of similar efficacy to nicotine replacement. Evidence also suggests that bupropion is less effective than varenicline, but further research is needed to confirm this finding. Evidence suggests that neither selective serotonin reuptake inhibitors (e.g. fluoxetine) nor monoamine oxidase inhibitors aid cessation.

Influence of methylphenidate treatment assumptions on cognitive function in healthy young adults in a double-blind, placebo-controlled trial

Background

Increasing numbers of students use stimulants such as methylphenidate (MPH) to improve their study capacity, making them prone to subsequent prolonged drug abuse. This study explored the cognitive effects of MPH in students who either assumed they received MPH or assumed they received a placebo.

Methods

In a double-blind, randomized, placebo-controlled trial with a between-subjects design, 21 students were subjected to partial sleep deprivation, receiving no more than 4 hours sleep the night before they were tested. In the morning, they were given either a placebo or 20 mg of MPH. They then performed free recall verbal tests and Go/No-Go tasks repeatedly, their moods were evaluated using Profile of Mood States and their tiredness was assessed using a visual analog scale, with evaluation of vigilance.

Results

No significant differences were found between those subjects who received MPH and those who received a placebo. However, significant differences were found between subjects who assumed they had received MPH or had no opinion, and those who assumed they had received a placebo. At three minutes, one hour, and one day after memorizing ten lists of 20 words, those who assumed they had received MPH recalled 54%, 58%, and 54% of the words, respectively, whereas those who assumed they had received placebo only recalled 35%, 37%, and 34%.

Conclusion

Healthy, partially sleep-deprived young students who assume they have received 20 mg of MPH experience a substantial placebo effect that improves consolidation of information into long-term memory. This is independent of any pharmacologic effects of MPH, which had no significant effects on verbal memory in this study. This information may be used to dissuade students from taking stimulants such as MPH during examination periods, thus avoiding subsequent abuse and addiction.

Perceived treatment assignment and smoking cessation in a clinical trial of bupropion versus placebo

INTRODUCTION

Psychoactive effects of smoking cessation medi cations such as bupropion may allow participants in smoking cessation clinical trials to correctly guess their treatment assignment at rates greater than chance. Previous research has found an association between perceived treatment assignment and smoking cessation rates among moderate to heavy smokers (≥ 10 cigarettes per day [cpd]) in two bupropion clinical trials.

METHODS

The aim of this study was to determine the impact of perceived treatment assignment on end-of-treatment cotinine-verified smoking abstinence at Week 7 and Week 26 among African American light smokers (≤ 10 cpd) enrolled in a double-blind, placebo-controlled study of bupropion. Participants (n = 390) included in this study reported their perceived treatment assignment on the end-of-treatment (Week 7) survey.

RESULTS

Participants were predominantly female (63.1%), 48.1 years of age (SD = 11.2), and smoked an average of 8 cpd (SD = 2.5). Participants given bupropion were more likely to correctly guess their treatment assignment (69%; 140/203) than those assigned to placebo (51.3%; 96/187) (p < .0001). After adjusting for treatment condition, participants who perceived assignment to bupropion versus placebo were not more likely to be abstinent than those who perceived assignment to placebo at Week 7 or at Week 26. The interaction between treatment and perceived treatment assignment was also nonsignificant.

CONCLUSIONS

Consistent with two previous studies testing bupropion, participants assigned to bupropion were more likely to correctly guess their treatment assignment than those assigned to placebo. However, in contrast to previous studies with heavier smokers, perceived treatment assignment did not significantly impact cotinine-verified abstinence in light smokers.

Perceived drug assignment and treatment outcome in smokers given nicotine patch therapy

This study assessed the relationship between treatment outcome and perceived drug assignment in smokers (nicotine patch [NP] or placebo) using abstinence and relapse status. Smokers (N = 424) were randomly assigned to receive either NP or placebo as part of a study that examined the effects of combining NP with self-help programs. Beliefs about drug assignment, assessed at the 12-month follow-up, were obtained from 384 participants. Beliefs were related to abstinence at the 2-month, p < .05, and 6-month follow-ups, p < .05, for the NP group, but not the placebo. Beliefs were not related to abstinence at 12 months for either group. Survival analysis assessing relapse revealed that beliefs were related to relapse status, regardless of actual group assignment. Our results suggest that there is a relationship between perceived drug assignment and treatment outcome. Future studies using multiple treatment outcome measures and assessments of beliefs over time are warranted.

Participant expectancies in double-blind randomized placebo-controlled trials: potential limitations to trial validity

BACKGROUND

Randomized controlled trials (RCTs) that use placebo controls to achieve double-blinding intend to establish the efficacy of a treatment over and above expectancy and other forms of bias. Despite this, a growing body of research suggests that participant expectancies can influence the outcomes of these trials.

PURPOSE

and

METHODS

This nonsystematic review examines research assessing the role of participant expectancies in double-blind placebo-controlled RCTs in order to determine if and how they can limit these types of trials.

RESULTS

There appear to be at least three ways in which participant expectancies can limit the validity of double-blind placebo-controlled RCTs. First, when blinding fails researches cannot determine whether any observed improvement in the group receiving active treatment resulted because of the treatment's effect or because of participants' expectancies. Second, participant expectancies could create ceiling effects if there are strong placebo effects in each treatment arm and this may falsely suggest that the active treatment is ineffective without expectancy. Third, the knowledge that a participant will be allocated active treatment or placebo in double-blind placebo-controlled RCTs is likely to lead to weaker treatment responses than would be expected in standard clinical practice, in which patients are unlikely to doubt that they have been given an active treatment.

CONCLUSIONS

Participants' expectancies can undermine the validity of double-blind placebo-controlled RCTs. Researchers conducting these trials should assess participants' beliefs about their treatment allocation and actively investigate if and how these beliefs may have influenced the trial's outcome. Clinical Trials 2010; 7: 246-255. http://ctj.sagepub.com.

Perceived treatment, feedback, and placebo effects in double-blind RCTs: an experimental analysis

INTRODUCTION

In double-blind randomized placebo-controlled trials (RCT) of therapeutic interventions, the effects of the treatment may provide feedback that undermines blinding and consequently distorts measures of the effectiveness of the intervention.

METHODS AND RESULTS

This possibility was confirmed in an experimental model using a dummy placebo procedure whereby participants were led to believe that they were taking part in testing a cognitive-enhancing drug. In two experiments, false feedback given about cognitive performance influenced participants' beliefs about whether they had been allocated to the active treatment or placebo. These beliefs also appeared to influence actual cognitive performance in that participants who believed they had taken the active treatment had higher accuracy in Experiment 1 and faster reaction times in Experiment 2 than those who believed they had been given a placebo. The addition of no treatment control groups in Experiment 2 showed that these effects could not be accounted for by the feedback manipulation itself, thereby supporting expectancy as a causal factor.

DISCUSSION

These results indicate the importance of assessing participants' beliefs about their treatment allocation in real double-blind RCTs and considering if and how these may have affected the trial's outcome.

Perceived treatment, feedback, and placebo effects in double-blind RCTs: an experimental analysis

INTRODUCTION

In double-blind randomized placebo-controlled trials (RCT) of therapeutic interventions, the effects of the treatment may provide feedback that undermines blinding and consequently distorts measures of the effectiveness of the intervention.

METHODS AND RESULTS

This possibility was confirmed in an experimental model using a dummy placebo procedure whereby participants were led to believe that they were taking part in testing a cognitive-enhancing drug. In two experiments, false feedback given about cognitive performance influenced participants' beliefs about whether they had been allocated to the active treatment or placebo. These beliefs also appeared to influence actual cognitive performance in that participants who believed they had taken the active treatment had higher accuracy in Experiment 1 and faster reaction times in Experiment 2 than those who believed they had been given a placebo. The addition of no treatment control groups in Experiment 2 showed that these effects could not be accounted for by the feedback manipulation itself, thereby supporting expectancy as a causal factor.

DISCUSSION

These results indicate the importance of assessing participants' beliefs about their treatment allocation in real double-blind RCTs and considering if and how these may have affected the trial's outcome.

Antidepressants for smoking cessation

BACKGROUND

There are at least two theoretical reasons to believe antidepressants might help in smoking cessation. Nicotine withdrawal may produce depressive symptoms or precipitate a major depressive episode and antidepressants may relieve these. Nicotine may have antidepressant effects that maintain smoking, and antidepressants may substitute for this effect. Alternatively, some antidepressants may have a specific effect on neural pathways underlying nicotine addiction, (e.g. blocking nicotine receptors) independent of their antidepressant effects.

OBJECTIVES

The aim of this review is to assess the effect of antidepressant medications in aiding long-term smoking cessation. The medications include bupropion; doxepin; fluoxetine; imipramine; moclobemide; nortriptyline; paroxetine; sertraline, tryptophan and venlafaxine.

SEARCH STRATEGY

We searched the Cochrane Tobacco Addiction Group trials register which includes trials indexed in MEDLINE, EMBASE, SciSearch and PsycINFO, and other reviews and meeting abstracts, in September 2006.

SELECTION CRITERIA

We considered randomized trials comparing antidepressant medications to placebo or an alternative pharmacotherapy for smoking cessation. We also included trials comparing different doses, using pharmacotherapy to prevent relapse or re-initiate smoking cessation or to help smokers reduce cigarette consumption. We excluded trials with less than six months follow up.

DATA COLLECTION AND ANALYSIS

We extracted data in duplicate on the type of study population, the nature of the pharmacotherapy, the outcome measures, method of randomization, and completeness of follow up. The main outcome measure was abstinence from smoking after at least six months follow up in patients smoking at baseline, expressed as an odds ratio (OR). 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.

MAIN RESULTS

Seventeen new trials were identified since the last update in 2004 bringing the total number of included trials to 53. There were 40 trials of bupropion and eight trials of nortriptyline. When used as the sole pharmacotherapy, bupropion (31 trials, odds ratio [OR] 1.94, 95% confidence interval [CI] 1.72 to 2.19) and nortriptyline (four trials, OR 2.34, 95% CI 1.61 to 3.41) both doubled the odds of cessation. There is insufficient evidence that adding bupropion or nortriptyline to nicotine replacement therapy provides an additional long-term benefit. Three trials of extended therapy with bupropion to prevent relapse after initial cessation did not find evidence of a significant long-term benefit. From the available data bupropion and nortriptyline appear to be equally effective and of similar efficacy to nicotine replacement therapy. Pooling three trials comparing bupropion to varenicline showed a lower odds of quitting with bupropion (OR 0.60, 95% CI 0.46 to 0.78). There is a risk of about 1 in 1000 of seizures associated with bupropion use. Concerns that bupropion may increase suicide risk are currently unproven. Nortriptyline has the potential for serious side-effects, but none have been seen in the few small trials for smoking cessation. There were six trials of selective serotonin reuptake inhibitors; four of fluoxetine, one of sertraline and one of paroxetine. None of these detected significant long-term effects, and there was no evidence of a significant benefit when results were pooled. There was one trial of the monoamine oxidase inhibitor moclobemide, and one of the atypical antidepressant venlafaxine. Neither of these detected a significant long-term benefit.

AUTHORS' CONCLUSIONS

The antidepressants bupropion and nortriptyline aid long-term smoking cessation but selective serotonin reuptake inhibitors (e.g. fluoxetine) do not. Evidence suggests that the mode of action of bupropion and nortriptyline is independent of their antidepressant effect and that they are of similar efficacy to nicotine replacement. Adverse events with both medications are rarely serious or lead to stopping medication.