Successful Cessation Research Articles

Barriers and motivators for tobacco smoking cessation in people with multiple sclerosis

IntroductionSmoking is a key modifiable risk factor for health outcomes of people with multiple sclerosis (MS). Little evidence exists on whether the information and support needs of people with MS who smoke are met. This study aimed to explore knowledge, attitudes and beliefs about smoking and quitting, and quitting support needs in Australian people with MS. MethodsCurrent and recent smokers were recruited for phone interviews through social media and newsletters. Interview data were analysed in NVivo using framework analysis. ResultsWe interviewed 25 people with MS (20 current and five recent smokers). Many participants had little knowledge about the risks of smoking on MS progression. Some reported perceived benefits from smoking on MS symptoms, while others perceived smoking worsening their symptoms. Similarly, quitting was believed to have health benefits, but concerns about withdrawal symptoms and the impact on MS symptoms and relapses were common. Participants reported ambivalence discussing smoking with clinicians; some wanting more information and support, while also feeling shame or guilt. Many participants were asked about their smoking status by MS clinicians, however, the provision of evidence-based information, and referrals to quitting support services was very infrequent. General practitioners were often found helpful and supportive, but participants gave more weight to quit advice from MS clinicians. ConclusionOur results are the first to indicate that smoking cessation needs of Australian people with MS are not met. These findings should be confirmed in a larger sample, but there is potential to investigate whether implementing routine provision of brief advice in MS care, as a coordinated effort between MS researchers, practitioners, consumer advocates and behavioural intervention services, may meet these needs. Further, developing targeted resources and training quit counsellors to provide appropriate information and support specific to people with MS may improve smoking cessation success in people with MS.

E-cigarette and cigarette use among cancer survivors versus general population: a case-control study in Korea

Although successful smoking cessation after cancer diagnosis is important, research on e-cigarette use and smoking behavior among cancer survivors (CS) is limited. This study compared cigarette and e-cigarette use among CS and non-cancer populations in Korea. This study analyzed the 2013-2018 National Health and Nutrition Survey data to investigate e-cigarette use and smoking behavior among Korean CS. The data were categorized into 1260 CS and 5040 non-cancer populations using the propensity score matching method. A multiple logistic regression was conducted among CS who previously used cigarettes or e-cigarettes to evaluate factors influencing successful cessation. Regarding conventional smoking, the proportion of ex-smokers was higher (25.2% versus 19.9%) than current smokers (6.7% versus 10.6%) in the CS group than in the propensity matched non-cancer population (PMNCP) (p < 0.001). However, ever use of e-cigarettes did not differ between them (2.4% versus 2.7%, p = 0.529). Successful cessation, defined as not using either cigarettes or e-cigarettes, correlated with problem drinking (OR 0.442, 95% CI 0.207-0.940), depression (OR 0.276, 95% CI 0.087-0.872), and cancer sites. CS of stomach, liver, colorectal, and lung cancer maintained higher successful smoking cessation rates than PMNCP. Korean CS had a higher cessation rate than PMNCP regarding conventional smoking; however, there was no difference in e-cigarette use. In Korea, some CS continue to use e-cigarettes, and physicians should focus on helping them quit. Individualized and timely interventions should be provided for both cigarette and e-cigarette users, considering factors influencing successful cessation.

Providing Free Access to Smoking Cessation Medications: Does It Have an Impact on the Treatment Adherence and Success of Smoking Cessation?

Providing medications to patients free of charge is thought to be one of the factors affecting the success of smoking cessation. The aim of this study was to investigate the effect of providing free access to stop-smoking medications on the treatment adherence and short term success of quitting smoking. All smokers who applied to a smoking cessation outpatient clinic between September 2017 and December 2019 were included in this retrospective study. Data were collected from patients' files filled using an initial evaluation and follow-up protocol. During the study period, 518 smokers applied to our polyclinic for smoking cessation counseling. Medical therapy was prescribed for 411 (85.4%) of 481 patients who were supported by behavioral therapy. The patients had a mean age of 41.2 years, and 64.7% were male. Only 22.9% of smokers prescribed stop-smoking medications were able to obtain them for free. Patients who got the medications completely free of charge were 4 times more adherent to treatment. The success rate of quitting smoking at the end of the third month was 22.2%. The strongest effect was achieved by the full treatment compliance. At the end of 3 months, the success of quitting smoking was 14.1 times higher for those who were fully adherent to treatment than non-adherents. According to our study results, the most effective success factors in short-term smoking cessation are patient compliance to treatment and free supply of stop-smoking medications, one of the main determinants of treatment adherence.

Novel treatment options in advanced adenoid cystic carcinoma of the breast.

e13071 Background: Adenoid cystic carcinoma (ACC) accounts for less than 0.1% of all breast cancer cases. The disease typically remains localized and indolent, and frequently occurs with triple negative status. Methods: In patients with locally advanced or metastatic disease, chemotherapy for triple negative breast carcinoma is seldom effective. Thus new treatment paradigms are desired. Drug targeted analysis derived from next generation sequencing and identification of driver mutations may offer a bright future in treatment options in chemo-resistant malignancy. Results: A 53 year old woman presented with breast mass and mastectomy with stage pT3N0M0 triple negative ACC of the breast resulting in observation. She later relapsed with chest wall disease, resulting in resection and radiation therapy. Shortly thereafter, she relapsed with pulmonary metastatic disease. She was treated with carboplatin and doxorubicin which were discontinued due to disease progression. Liquid assay revealed an IDH2 mutation, prompting treatment with enasidenib with ongoing evidence of disease control at 4 months. Patient tolerated treatment well without grade 3 or 4 adverse reactions. A 48 year old woman presented with an increasing 9.5 cm unresectable breast mass without distant metastasis. Pathology showed triple negative ACC of the breast, resulting in chemotherapy with doxorubicin, cyclophosphamide, and paclitaxel with clinically progressive disease. She represented with necrotic and ulcerating changes of the breast. Foundational genomic testing showed an FGFR2 mutation. After four months of treatment with erdafitinib, she had resolution of pain and cessation of pain medication. Her therapy led to a grade 2 adverse event related to hyperphosphatemia. She underwent surgical resection with negative margins. Conclusions: These examples illustrate a potential treatment paradigm for a rare malignancy for which there is no standard of care. Here we present two desperate cases, one of which had a driver mutation of IDH2, and the other FGFR2 for which there are targeted therapies approved in other disease states. The use of these two agents resulted in clinical benefit. A patient with metastatic disease treated with enasidenib has ongoing disease control for over 4 months with minimal adverse reaction. A patient with advanced local disease requiring narcotics and gabapentin for pain control treated with erdafitinib had significant symptomatic control with successful cessation of pain medications and ability to undergo potentially curable mastectomy with negative margins despite progression on prior chemotherapy. In summary, ongoing research of ACC of the breast will be required. Alternative therapeutic options related to targeted treatment may offer promise to clinical outcomes in the future. For cases of locally advanced or metastatic disease, the use of targeted therapy may offer new therapeutic options.

Examining the effects of stress and psychological distress on smoking abstinence in cancer patients.

Cancer patients who smoke report more stress and psychological distress than patients who do not smoke. It is unclear how these emotional symptoms may modify smoking behavior in cancer patients. We examined the influence of a smoking cessation intervention for cancer patients on stress and distress, and the effects of these symptoms on smoking abstinence. Mixed-methods secondary analysis of data from the Smokefree Support Study, a two-site randomized controlled trial examining the efficacy of Intensive (IT; n=153) vs. Standard Treatment (ST; n=150) for smoking cessation in newly diagnosed cancer patients. Stress coping, perceived stress, distress, and anxiety were self-reported at baseline, 3, and 6months. Abstinence was biochemically-confirmed at 6months. A subset of patients (n=72) completed qualitative exit-interviews. Patients were on average, 58years old, 56% female, and smoked a median of 10 cigarettes/day. There were no significant treatment group×time interactions or main effects of treatment group on stress or distress measures (p's>0.05), however there were significant main effects of time suggesting symptom improvements on each measure in both study groups (p's<0.05). In adjusted logistic regression models, lower levels anxiety at 3months predicted confirmed smoking abstinence at 6months (p=.03). Qualitatively, at 6months, patients reported their stress and smoking were connected and that the cessation counseling was helpful. Cancer patients enrolled in a smoking cessation trial report decreases in stress, distress and anxiety over time, and anxiety symptoms may impact smoking cessation success at follow-up resulting in an important intervention target.

Studying the Utility of Using Genetics to Predict Smoking-Related Outcomes in a Population-Based Study and a Selected Cohort.

The purpose of this study is to examine the predictive utility of polygenic risk scores (PRSs) for smoking behaviors. Using summary statistics from the Sequencing Consortium of Alcohol and Nicotine use consortium, we generated PRSs of ever smoking, age of smoking initiation, cigarettes smoked per day, and smoking cessation for participants in the population-based Atherosclerosis Risk in Communities (ARIC) study (N = 8638), and the Collaborative Genetic Study of Nicotine Dependence (COGEND) (N = 1935). The outcomes were ever smoking, age of smoking initiation, heaviness of smoking, and smoking cessation. In the European ancestry cohorts, each PRS was significantly associated with the corresponding smoking behavior outcome. In the ARIC cohort, the PRS z-score for ever smoking predicted smoking (odds ratio [OR]: 1.37; 95% confidence interval [CI]: 1.31, 1.43); the PRS z-score for age of smoking initiation was associated with age of smoking initiation (OR: 0.87; 95% CI: 0.82, 0.92); the PRS z-score for cigarettes per day was associated with heavier smoking (OR: 1.17; 95% CI: 1.11, 1.25); and the PRS z-score for smoking cessation predicted successful cessation (OR: 1.24; 95% CI: 1.17, 1.32). In the African ancestry cohort, the PRSs did not predict smoking behaviors. Smoking-related PRSs were associated with smoking-related behaviors in European ancestry populations. This improvement in prediction is greatest in the lowest and highest genetic risk categories. The lack of prediction in African ancestry populations highlights the urgent need to increase diversity in research so that scientific advances can be applied to populations other than those of European ancestry. This study shows that including both genetic ancestry and PRSs in a single model increases the ability to predict smoking behaviors compared with the model including only demographic characteristics. This finding is observed for every smoking-related outcome. Even though adding genetics is more predictive, the demographics alone confer substantial and meaningful predictive power. However, with increasing work in PRSs, the predictive ability will continue to improve.

Harm Reduction in Male Patients Actively Using Anabolic Androgenic Steroids (AAS) and Performance-Enhancing Drugs (PEDs): a Review.

Anabolic androgenic steroid (AAS) and performance-enhancing drug (PED) use is a prevalent medical issue, especially among men, with an estimated 2.9-4 million Americans using AAS in their lifetime. Prior studies of AAS use reveal an association with polycythemia, dyslipidemia, infertility, hypertension, left ventricular hypertrophy, and multiple behavioral disorders. AAS withdrawal syndrome, a state of depression, anhedonia, and sexual dysfunction after discontinuing AAS use, is a common barrier to successful cessation. Clinical resources for these patients and training of physicians on management of the patient using AAS are limited. Many men are hesitant to seek traditional medical care due to fear of judgment and lack of confidence in physician knowledge base regarding AAS. While proposed approaches to weaning patients off AAS are published, guidance on harm reduction for actively using patients remains sparse. Medical education regarding the management of AAS use disorder is paramount to improving care of this currently underserved patient population. Management of these patients must be non-judgmental and focus on patient education, harm reduction, and support for cessation. The approach to harm reduction should be guided by the specific AAS/PEDs used.

Evaluating the feasibility and acceptability of a mobile-based health technology for smoking cessation: Mobile Anxiety Sensitivity Program.

Cigarette smoking is the leading preventable cause of death and disability. Although most US smokers want to quit, more than 95% of cessation attempts end in relapse within 6 months. To improve cessation outcomes, research has turned to targetable mechanisms, such as anxiety sensitivity (AS), which maintain smoking behaviour, impede cessation success, and can be effectively targeted in the context of psychosocial interventions. Although integrated treatment programmes that address AS reduction in the context of smoking cessation have demonstrated promising results, presently, no mobile, technology-based integrated treatment exists to expressly address smoking and AS. The current study evaluated the initial feasibility and acceptability of a mobile smoking cessation intervention, Mobile Anxiety Sensitivity Program for smoking (MASP). Participants were 15 daily adult combustible cigarette smokers (females n = 6, Mage = 46.5 years, SD = 13.3) who completed a 6-week total intervention period (baseline visit, 2 weeks pre-quit, 4 weeks post-quit, follow-up visit). Most participants (N = 12) completed the full 6-week intervention, and participant engagement with MASP was high. Participants reported that MASP was acceptable. Biochemical verification of smoking abstinence indicated 25% of smokers were abstinent for at least 24 hr prior to the in-person 4 weeks post-quit follow-up visit. Findings indicated that MASP has the potential to provide effective assistance to those wanting to quit cigarettes. Mobile-based smoking cessation interventions may be a promising treatment option, particularly for those of lower socio-economic status. Targeting AS in the context of a mobile-based smoking cessation app may be a viable way to improve smoking cessation success and treatment outcome. Due to the pilot nature of this study, there was no control group. Thus, comparative conclusions and generalizability based on the current study must be made with caution.

Self-Efficacy and Motivation to Quit of Smokers Seeking to Quit: Quantitative Assessment of Smoking Cessation Mobile Apps.

BackgroundDecreasing trends in the number of individuals accessing face-to-face support are leaving a significant gap in the treatment options for smokers seeking to quit. Face-to-face behavioral support and other interventions attempt to target psychological factors such as the self-efficacy and motivation to quit of smokers, as these factors are associated with an increased likelihood of making quit attempts and successfully quitting. Although digital interventions, such as smoking cessation mobile apps, could provide a promising avenue to bridge the growing treatment gap, little is known about their impact on psychological factors that are vital for smoking cessation.ObjectiveThis study aims to better understand the possible impact of smoking cessation mobile apps on important factors for successful cessation, such as self-efficacy and motivation to quit. Our aim is to assess the self-efficacy and motivation to quit levels of smokers before and after the use of smoking cessation mobile apps.MethodsSmokers seeking to quit were recruited to participate in a 4-week app-based study. After screening, eligible participants were asked to use a mobile app (Kwit or Quit Genius). The smoking self-efficacy questionnaire and the motivation to stop smoking scale were used to measure the self-efficacy and motivation to quit, respectively. Both were assessed at baseline (before app use), midstudy (2 weeks after app use), and end-study (4 weeks after app use). Paired sample two-tailed t tests were used to investigate whether differences in self-efficacy and motivation between study time points were statistically significant. Linear regression models investigated associations between change in self-efficacy and change in motivation to quit before and after app use with age, gender, and nicotine dependence.ResultsA total of 116 participants completed the study, with the majority being male (71/116, 61.2%), employed (76/116, 65.6%), single (77/116, 66.4%), and highly educated (87/116, 75.0%). A large proportion of participants had a low to moderate dependence on nicotine (107/116, 92.2%). A statistically significant increase of 5.09 points (95% CI 1.83-8.34) from 37.38 points at baseline in self-efficacy was found at the end of the study. Statistically significant increases were also found for the subcomponents of self-efficacy (intrinsic and extrinsic self-efficacies). Similarly, a statistically significant increase of 0.38 points (95% CI 0.06-0.70) from 5.94 points at baseline in motivation to quit was found at the end of the study. Gender, age, and nicotine dependence were not statistically significantly associated with changes in self-efficacy and motivation to quit.ConclusionsThe assessed mobile apps positively impacted the self-efficacy and motivation to quit of smokers making quit attempts. This has important implications on the possible future use of digitalized interventions and how they could influence important psychological factors for quitting such as self-efficacy and motivation. However, further research is needed to assess whether digital interventions can supplement or replace traditional forms of therapy.

The Influence of Increasing Levels of Provider-Patient Discussion on Quit Behavior: An Instrumental Variable Analysis of a National Survey.

Objective: We aimed to examine the influence of increasing levels of discussion (both asked and advised, either asked or advised but not both, and neither asked nor advised) on quit behavior. Methods: We included 4133 adult current smokers from the 2015 National Health Interview Survey. The primary outcomes were quit intent and quit attempt, and the secondary outcomes were methods used for quitting. We used an instrumental variable analysis, as well as propensity score weighted and multivariable logistic regressions. Results: Compared to no discussion, having both or only one discussion, respectively, increased quit intent (OR = 1.65, 95% CI = 1.63–1.66 and OR = 1.02, 95% CI = 0.99–1.05), quit attempt (OR = 1.76, 95% CI = 1.75–1.77 and OR = 1.60, 95% CI = 1.57–1.63). Among those who attempted to quit (n = 1536), having both or only one discussion increased the use of pharmacologic (OR = 1.99, 95% CI = 1.97–2.02 and OR = 1.56, 95% CI = 1.49–1.63) or behavioral (OR = 2.01, 95% CI = 1.94–2.08 and OR = 2.91, 95% CI = 2.74–3.08) quit methods. Conclusions: Increasing levels of provider–patient discussion encourages quit behavior, and should be an integral part of reducing the health and economic burden of smoking. Strategies that promote the adherence and compliance of providers to communicate with patients may help increase the success of smoking cessation.

Comparative Analysis of Three Different Drug Distribution Schemes for Smoking Cessation.

This study aimed to compare the success rate of 3 different drug prescription policies: Free drugs with online system prescription, free drugs with doctor's prescription, and drugs paid for by patients with doctor's prescription. The effect of 2 different Ministry of Health (MoH) projects with free-of-charge and self-payment pharmacotherapies for smoking cessation were compared. Patients who completed 6 months of pharmacotherapy and follow-up were evaluated. The first period was free-of-charge medication, which was determined by an online system, the following period was the self-payment period, and the third period was free medication, which was prescribed by a doctor. In all the groups, smoking habits in pack years and comorbidities of the patients were recorded, and pulmonary function tests (PFTs) and expiratory carbon dioxide (CO2) measurements were performed. Patients who had an expiratory CO2 level >5 ppm at the control visits were accepted as quitters. A total of 829 patients with 438 patients in the first free-of-charge period (group 1), 111 in the self-payment period (group 2), and 280 in the second free-of-charge period (group 3) were enrolled in the study. Smoking cessation rates were significantly higher in the self-payment medication group (25%) according to the MoH's free-of-charge project groups. There was no difference in smoking cessation rates between the 2 free-of-charge medication project groups (15% in group 1 and 11% of group 3). Among all the patients, we compared 124 patients who quit smoking with 705 patients who did not. The quitters were older, mostly male, and heavier smokers. In addition, the number of patients with chronic obstructive pulmonary disease and obstructive PFT rates were higher among the quitters. Their dependency score, PFTs, and the use of free medication was lower, and treatment duration was longer. Independent factors that increased smoking cessation success were longer treatment duration, lower dependency score, and self-payment of medication. Free medications provided via 2 different modalities did not increase the smoking cessation success. Paying for the medication, lower dependency score, and longer treatment duration increased smoking cessation success independently.

Improvement in Cardiometabolic Risk Factors During Smoking Cessation Treatment in Patients with Type 2 Diabetes: A Retrospective Cohort Study.

PurposeSmoking cessation reduces morbidity and mortality of cardiovascular diseases. The purpose of this study was to evaluate the effect during smoking cessation treatment on glycemic control and cardiometabolic risk factors, including blood pressure and lipid levels, in patients with type 2 diabetes.Patients and MethodsThis retrospective cohort study included patients with type 2 diabetes who participated in a smoking cessation program, which comprised health education and medication prescription at an outpatient clinic in combination with a 3-month follow-up by phone. Data on patient background characteristics, cardiometabolic factors, smoking status, body weight, and body mass index before and after the program were collected for analysis.ResultsThe analysis included 241 participants with an average age of 58.6 ± 10.6 years. The rate of successful cessation at three months was 34.0%. Compared with the baseline levels, there were significant decreases in the levels of fasting plasma glucose (10.0 ± 46.8 mg/dL, P = 0.001), HbA1c (0.3 ± 1.4%, P = 0.004), systolic blood pressure (4.6 ± 17.5 mmHg, P < 0.001), diastolic blood pressure (2.9 ± 11.3 mmHg, P < 0.001), and total cholesterol (7.9 ± 42.8 mg/dL, P = 0.020) after participation in the smoking cessation program while there was no significant difference in body weight (0.1 ± 1.2 kg, P = 0.444). After adjustment for covariates, the decreases in HbA1c and total cholesterol levels were significantly better in younger participants and higher baseline nicotine dependence scores were associated with decreases in the levels of blood pressure, fasting plasma glucose, and triglycerides. However, the decrease in smoking amount was not associated with the changes in cardiometabolic factors.ConclusionParticipation in a smoking cessation program was associated with improvements in glycemic control and cardiometabolic risk factors in patients with type 2 diabetes. The observed improvements were associated with participation in the program but not with the decrease in smoking amount.

Counseling Effect on Smoking Cessation Behavior in Junior High School Students

The prevalence of smoking habits among children and adolescents has increased quantitative and qualitative, which further elevates the risk of diseases. Furthermore, the 2014 Global Youth Tobacco Survey (GYTS) (data showed the intention to quit smoking by 88.2% of students, although only 24% received assistance in affiliated programs; hence support is required from the immediate environment. Therefore, the purpose of this research, was to determine the effect of counseling in the success of smoking cessation in junior high school students. The research design used was a prospective cohort. The subjects of this research include all junior high school students with the smoking habit, of which 40 participants were selected. These respondents were provided with smoking cessation counseling for six sessions (4 months). Survival analysis was used to evaluate the data collected. After the six counseling sessions, the cessation success and failure rates were 75% and 25%, respectively. Smoking cessation was related to nicotine addiction (p&lt;0.001; Adj.HR 25.2;95% CI 4.9-129.9) and activeness in counseling (p=0.001; Adj.HR 12.8; 95% CI 2.8-57.9). This research is expected to help students with the smoking habit terminate the practice, subsequently reducing the prevalence in Poso Regency.

Age as a predictor of quit attempts and quit success in smoking cessation: findings from the International Tobacco Control Four-Country survey (2002-14).

Past research has found that young smokers are more likely to make quit attempts; however, there are conflicting findings regarding age and quit success. This study examined the degree to which smoker age is related to making quit attempts and quit success. Ten waves of the International Tobacco Control Policy Cohort survey (ITC-4C) collected between 2002 and 2014, with nine wave-to-wave transitions with predictors at the first wave predicting quit attempts and success by the next wave. Canada, the United States, the United Kingdom and Australia. Data from 15 874 smokers categorized into four age groups at baseline (18-24, 25-39, 40-54 and 55+years). Age, quit attempts and success (defined as ≥30days abstinence confirmed, if possible, on a third wave for recent attempts). Older smokers were more likely to smoke daily (χ2 =1557.86, r=0.136, P<0.001) than younger smokers. Daily smokers were less likely to report quit attempts (38.1 versus 58.2%) and to achieve 30days of abstinence (22.9 versus 34.3%) than non-daily smokers. Older daily smokers were less likely to make quit attempts [0.61, confidence interval (CI)=0.54-0.70, P<0.001], even after controlling for indicators of nicotine dependence, country, sex, education, income, relationship status and household composition, than younger smokers. Younger smokers (<25) were more likely to succeed for at least 30days of abstinence, but only when compared with those aged 40-54 (OR = 0.83, 95% CI=0.68-0.99). However, when controlling for heaviness of smoking the age effect disappeared. Significant interactions with age were found between age and intention when predicting quit attempts, and age and heaviness of smoking when predicting quit success. An international cohort study indicates that young smokers are more likely to attempt to quit and appear to have similar levels of success in abstaining from smoking compared with older smokers when controlling for dependence. Quit success in all ages is most predicted by lower levels of nicotine dependence.

Association of Stress Management with Success of Smoking Cessation in Korean Female Emotional Labor Workers for Service and Sales.

Emotional labor is paid work that involves managing and regulating one’s emotions during the job including evoking and suppressing one’s feelings. This study examined the factors associated with successful smoking cessation through tailored smoking cessation counseling including stress management among female emotional labor workers. The study was conducted from 1 September 2015 to 31 December 2017. A total of 2674 women registered in the Comprehensive Smoking Cessation Service System and were grouped as either emotional labor workers for service and sales (1002) or other occupations (1672) for analysis. The participants received nine sessions of face-to-face and telephone smoking cessation counseling over 6 months, and follow-up assessments were conducted 4, 6, 12, and 24 weeks after counseling. Smoking cessation counseling involved a stress management program comprising stress tests, depression tests, color therapy, and a buddy program including peer support. Factors associated with successful smoking cessation included the number of counseling sessions, motivation rulers (Importance, Confidence, Readiness), average daily smoking amount, expired carbon monoxide (CO), and nicotine dependence. The most associated factor was the number of counseling sessions. Since counseling focused on stress management, it was the most important factor in smoking cessation, and continuous counseling could help those wanting to quit smoking.

A Genome-Wide Association Study of Nausea Incidence in Varenicline-Treated Cigarette Smokers.

Varenicline is the most efficacious smoking cessation treatment; however, long-term cessation rates tend to be <25%. Nausea, the most common side effect of varenicline, observed in ~28% of individuals treated, peaks early following treatment initiation and reduces cessation success. Genetic variation influences treatment response, however genetic contributors to individual differences in side effects are less understood. We conducted a genome-wide association study of nausea incidence at 1 week following the initiation of varenicline treatment (corresponding to the target quit date) in 189 cigarette smokers of European ancestry (NCT01314001). Additive genetic models examining the likelihood of experiencing any versus no nausea controlled for population substructure, age, and sex. Variants with minor allele frequencies (MAF)≥10% were considered. Fifty-seven (30.2%) out of 189 participants reported nausea. The top variant associated with nausea was rs1568209 (odds ratio [OR] = 2.61 for A vs. G allele; 95% confidence interval [CI] = 1.65,4.15; p = 2.1e-7; MAF = 48.7%), mapping to the SLCO3A1 drug transporter gene on chromosome 15. In the same trial, rs1568209 was not associated with nausea in either the nicotine patch (p = .56; n = 181) or placebo (p = .59; n = 174) arms. In varenicline-treated smokers, the incidence of nausea was higher in females (44.6%; n = 74) versus males (20.9%; n = 115) (p = .001), however there was no evidence of a difference in the influence of rs1568209 on nausea between the sexes (p for sex*genotype interaction = .36). Future studies in larger samples are required to test the robustness of this finding. Variation in SLCO3A1 may influence the risk for developing nausea in varenicline-treated smokers, which may alter adherence and cessation. Varenicline-associated nausea reduces adherence and limits cessation success. Previous candidate gene association studies showed genetic factors influence nausea on varenicline. This pilot genome-wide investigation of nausea, the most common side effect associated with varenicline treatment and an important cause of treatment discontinuation, suggests the potential involvement of common variation in the SLCO3A1 drug transporter gene.

Association of Spontaneous and Induced Self-Affirmation With Smoking Cessation in Users of a Mobile App: Randomized Controlled Trial.

BackgroundMost smokers attempt to stop using cigarettes numerous times before successfully quitting. Cigarette cravings may undermine perceived competence to quit and thus constitute psychological threats to the individual’s self-concept. Self-affirmation may promote smoking cessation by offsetting these threats.ObjectiveThis study examines whether self-affirmation is associated with smoking cessation in the context of a cessation app. Two types of self-affirmation are examined: tendency to spontaneously self-affirm, and self-affirmation inductions added to a publicly available smoking cessation app (Smoke-Free Quit Smoking Now). In addition, this study explores whether optimism and emotional states (happiness, anger, anxiousness, hopefulness, sadness) predict smoking cessation.MethodsAll users who met the inclusion criteria, provided consent to participate, and completed a baseline assessment, including all individual difference measures, were randomized to 1 of 4 conditions. Half of the participants were randomly assigned to complete a self-affirmation induction upon study entry. Orthogonally, half of the participants were randomly assigned to receive self-affirming text notifications during their quit attempt or to receive conventional notifications. The induction and the text notifications were fully automated, and all data were collected through self-assessments in the app. Self-reported smoking cessation was assessed 1 month and 3 months following study entry.ResultsThe study enrolled 7899 participants; 647 completed the 1-month follow-up. Using an intent-to-treat analysis at the 1-month follow-up, 7.2% (569/7899) of participants self-reported not smoking in the previous week and 6.4% (503/7899) self-reported not smoking in the previous month. Greater tendency to spontaneously self-affirm predicted a greater likelihood of cessation (P<.001) at 1 month after controlling for smoking-related variables. Neither self-affirmation induction influenced cessation. In addition, spontaneous self-affirmation did not moderate the relationship between self-affirmation inductions and cessation. Greater baseline sadness was associated with a lower likelihood of reporting successful cessation. Optimism predicted past-week cessation at the 1-month follow-up, and both happiness and anger predicted past-month cessation at the 1-month follow-up; however, none of these potential predictors moderated the relationship between self-affirmation conditions and successful cessation.ConclusionsSpontaneous self-affirmation may be an important psychological resource for managing threats to self-concept during the smoking cessation process. Sadness may hinder quit attempts. Future research can explicate how spontaneous versus induced self-affirmation can promote smoking cessation and examine boundary conditions for the effectiveness of disseminated self-affirmation interventions.Trial RegistrationISRCTN Registry 56646695; https://www.isrctn.com/ISRCTN56646695

Development of Machine Learning Models for Prediction of Smoking Cessation Outcome

Predictors for success in smoking cessation have been studied, but a prediction model capable of providing a success rate for each patient attempting to quit smoking is still lacking. The aim of this study is to develop prediction models using machine learning algorithms to predict the outcome of smoking cessation. Data was acquired from patients underwent smoking cessation program at one medical center in Northern Taiwan. A total of 4875 enrollments fulfilled our inclusion criteria. Models with artificial neural network (ANN), support vector machine (SVM), random forest (RF), logistic regression (LoR), k-nearest neighbor (KNN), classification and regression tree (CART), and naïve Bayes (NB) were trained to predict the final smoking status of the patients in a six-month period. Sensitivity, specificity, accuracy, and area under receiver operating characteristic (ROC) curve (AUC or ROC value) were used to determine the performance of the models. We adopted the ANN model which reached a slightly better performance, with a sensitivity of 0.704, a specificity of 0.567, an accuracy of 0.640, and an ROC value of 0.660 (95% confidence interval (CI): 0.617–0.702) for prediction in smoking cessation outcome. A predictive model for smoking cessation was constructed. The model could aid in providing the predicted success rate for all smokers. It also had the potential to achieve personalized and precision medicine for treatment of smoking cessation.

Efficacy of an inpatient smoking cessation program at a single regional cancer center: A prospective observational study.

Smoking is the leading cause of preventable death and a risk factor for cancer, but smoking cessation is difficult even in patients who need hospitalization. This study aimed to investigate the usefulness of an inpatient smoking cessation consultation program and to analyze the clinical factors associated with abstinence. In this observational study, patients received regular counseling for 6 months, and abstinence was objectively assessed via urine and exhaled carbon monoxide testing. Cessation rates were assessed at 4 weeks and 6 months, and clinical characteristics associated with cessation success were investigated. Of the 571 patients referred to participate in the program, 170 (29.8%) were enrolled, and only 2 (1.2%) used smoking cessation drugs in addition to counseling. The smoking cessation rate was 77.6% after 4 weeks and 59.1% after 6 months. The cessation rates were significantly higher in patients with cancer than in those without cancer at both timepoints (63.8% vs 21.9%, P < .001, 53.6% vs 12.5%, P < .001), and they were also higher in the first admission group than in the re-admission group (87.4% vs 74.7%, P = .033, 88.5% vs 76.1%, P = .037). In patients with lung cancer, progression-free survival and overall survival tended to be better in those enrolled in the program (P = .158, P = .183). In conclusion, the inpatient smoking cessation program was associated with a high abstinence rate. Most patients maintained cessation without medication, suggesting that initial admission, along with a cancer diagnosis, can provide enough motivation to abstain from smoking. In addition, the smoking cessation effort showed potential to improve survival during lung cancer treatment.

A Systematic Review and Scoping Analysis of Smoking Cessation after a Urological Cancer Diagnosis

Smoking cessation after a urologic cancer diagnosis significantly benefits patients. It is not well known how often patients quit after diagnosis or how urologists intervene to support patients' smoking cessation efforts. To examine rates of smoking cessation after diagnosis among patients with urologic cancers and to assess how often patients are given advice and support to quit smoking in the urology setting. Following the PRISMA guidelines, a systematic review was conducted of the available studies on smoking cessation after a urologic cancer diagnosis during April 2020 by a trained medical librarian using the MEDLINE, PsycInfo, Embase, and Cochrane CENTRAL databases. Studies were included based on three independent reviews and if they met a priori inclusion/exclusion criteria. In total, 2568 records were identified, 31 of which were included for final analysis. Four studies (patient n=587) reported outcomes related to the prospective implementation of a smoking cessation program with patient-level quit rates ranging from 3.2% to 47.3%. Twenty one studies reported outcomes of passive (no directed, active intervention) smoking cessation after the diagnosis of a urologic cancer (patient n=3669) with widely varying quit rates. In general, the quality of included studies was poor. There was no standardization of the measurement or timing of outcomes and few studies included validated survey instruments or biochemical confirmation of cessation. Seventeen studies included data on whether patients received advice to quit smoking after diagnosis. The proportion of patients in each study who were told to quit ranged from 2.8-78.3%. There are few smoking cessation interventions that have been prospectively implemented and reported in the urology literature and studies on quit rates after diagnosis are limited. The paucity of quality data and lack of smoking cessation interventions being used in routine urologic oncology care underscores the need for more rigorous study and implementation of evidence-based practices in this area.