Effects of biochemically confirmed smoking cessation on white blood cell count

Environmental chemical-wide associations with immune biomarkers in US adults: A cross-sectional analysis

Environmental chemical exposures influence immune system functions, and humans are exposed to a wide range of chemicals, termed the chemical "exposome". A comprehensive, discovery analysis of the associations of multiple chemical families with immune biomarkers is needed. In this study, we tested the associations between environmental chemical concentrations and immune biomarkers. We analyzed the United States cross-sectional National Health and Nutrition Examination Survey (NHANES, 1999-2018). Chemical biomarker concentrations were measured in blood or urine (196 chemicals, 17 chemical families). Immune biomarkers included counts of lymphocytes, neutrophils, monocytes, basophils, eosinophils, red blood cells, white blood cells, and mean corpuscular volume. We conducted separate survey-weighted, multivariable linear regressions of each log2-transformed chemical and immune measure, adjusted for relevant covariates. We accounted for multiple comparisons using a false discovery rate (FDR). Among 45,528 adult participants, the mean age was 45.7 years, 51.4% were female, and 69.3% were Non-Hispanic White. 71 (36.2%) chemicals were associated with at least one of the eight immune biomarkers. The most chemical associations (FDR<0.05) were observed with mean corpuscular volume (36 chemicals) and red blood cell counts (35 chemicals). For example, a doubling in the concentration of cotinine was associated with 0.16 fL (95% CI: 0.15, 0.17; FDR<0.001) increased mean corpuscular volume, and a doubling in the concentration of blood lead was associated with 61,736 increased red blood cells per μL (95% CI: 54,335, 69,138; FDR<0.001). A wide variety of chemicals, such as metals and smoking-related compounds, were highly associated with immune system biomarkers. This environmental chemical-wide association study identified chemicals from multiple families for further toxicological, immunologic, and epidemiological investigation.

Relationship between tobacco smoking and hematological indices among Sudanese smokers

BACKGROUND

Tobacco Smoking is one of the leading causes of preventable morbidity and mortality in the world. It is well documented that tobacco smoking is risk factor for many diseases like: cancers, chronic respiratory and cardiovascular diseases, and the effects of tobacco smoking on hematological indices gets a little attention: the data is mostly inconsistent regarding the differential of WBCs, a conflicting studies described the effect of smoking on hemoglobin descriptive parameters and a regular monitoring of platelets count in smokers was advised.

OBJECTIVES

The study aimed to evaluate the relationship between tobacco smoking and hematological parameters among Sudanese healthy Smokers at Bahri Town.

METHODS

This was a cross sectional study conducted during 2022 in Bahri town, Khartoum state. A total of 120 male subjects participated in this study. Of them, 60 healthy non-smokers participants (Control), and 60 age matched smokers who were smoking tobacco for a minimum of 1 year. Smokers group was divided into three major sub-groups with each group contains 20 subjects: Cigarettes smokers (CS), Water pipes (Shisha) smokers (WP) and both Cigarettes and water pipes (shisha) smokers (CSWP). Data was collected through questionnaire interviews and laboratory investigation. A sample of Five ml venous blood was taken for Complete blood count testing using Urite 3000 plus semi-automated hematology analyzer. Data were analyzed using SPSS version 25. Assocation between the variables were estimated and p value ≤ 0.05 was considered statistically significant.

RESULTS

Smokers had significantly higher RBCs count (p = 0.017), Hb level (p < 0.001), WBCs count (p = .017), Neutrophils (p < 0.001), MCH (p = 0.029), MCHC (p < 0.001), RDW (p < 0.001), and PDW (p < 0.001) compared to the non-smokers. In contrast, non-smokers had higher MPV (p < 0.001) and MCV (p < 0.001) levels than smokers. Between the non-smokers and different subtypes of the smokers (CS, WP & CSWP), there were significant differences between the subgroups for all hematological parameters except for PLTs and lymphocytes count. CS had lower levels of MCV (p < 0.001), MCHC (p < 0.001), HCT (p = 0.036), and RDW (p < 0.001) compared to the non-smokers, while both cigarette and shisha smokers had the higher levels of neutrophils count (p < 0.001) and PDW (p < 0.001) compared to the non-smokers.

CONCLUSION

Smoking affects hematological parameters; smokers had significantly higher RBCs count, Hb level, WBCs count, Neutrophils, MCH, MCHC, RDW and PDW compared to the non-smoker group. WP smoking caused higher levels of RBCs, Hb, neutrophils, MCH and MCHC. PDW was high in smokers' sub-groups compared to control group, while MPV was lower despite insignificant change In PLTs count.

The relationship between heated cigarette smoking and blood white blood cell count: a population-based cross-sectional study

OBJECTIVES

Conventional cigarette smoking increases inflammation and white blood cell (WBC) counts. However, there have been limited studies on the relationship between heated cigarette smoking and WBC counts. This study aimed to examine this relationship using nationally representative population-based health data.

STUDY DESIGN

This was a population-based cross-sectional study.

METHODS

The Korea National Health and Nutrition Examination Survey database was used to analyze this relationship. Data related to sex, age, body mass index (BMI), WBC count, and smoking history were obtained from the database. The smoking-related questionnaires included smoking status, smoking type (heated or conventional cigarettes), and smoking amount. The summary statistics of the WBC counts were calculated according to sex, smoking status, and smoking type. In addition, the exposure-response relationship between the smoking amount and WBC count was examined by smoking type, controlling for sex, age, and BMI.

RESULTS

In total, 9747 WBC measurements were used in the analyses. WBC count increased in conventional cigarette smokers, while there was no significant difference in WBC count between heated cigarette smokers and non-smokers. The WBC count showed a positive dose-response relationship with the smoking amount in both conventional and heated cigarette smokers.

CONCLUSIONS

The results confirm that conventional cigarette smoking increases WBC counts. Furthermore, the results suggest that heated cigarette smoking does not lead to a significant increase in WBC counts, although it indicates a potential dose-response relationship with WBC count. Further research with larger sample sizes is needed to confirm whether these results reflect true associations.

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.

Interventions for preventing weight gain after smoking cessation

BACKGROUND

Most people who stop smoking gain weight. This can discourage some people from making a quit attempt and risks offsetting some, but not all, of the health advantages of quitting. Interventions to prevent weight gain could improve health outcomes, but there is a concern that they may undermine quitting.

OBJECTIVES

To systematically review the effects of: (1) interventions targeting post-cessation weight gain on weight change and smoking cessation (referred to as 'Part 1') and (2) interventions designed to aid smoking cessation that plausibly affect post-cessation weight gain (referred to as 'Part 2').

SEARCH METHODS

Part 1 - We searched the Cochrane Tobacco Addiction Group's Specialized Register and CENTRAL; latest search 16 October 2020. Part 2 - We searched included studies in the following 'parent' Cochrane reviews: nicotine replacement therapy (NRT), antidepressants, nicotine receptor partial agonists, e-cigarettes, and exercise interventions for smoking cessation published in Issue 10, 2020 of the Cochrane Library. We updated register searches for the review of nicotine receptor partial agonists.

SELECTION CRITERIA

Part 1 - trials of interventions that targeted post-cessation weight gain and had measured weight at any follow-up point or smoking cessation, or both, six or more months after quit day. Part 2 - trials included in the selected parent Cochrane reviews reporting weight change at any time point.

DATA COLLECTION AND ANALYSIS

Screening and data extraction followed standard Cochrane methods. Change in weight was expressed as difference in weight change from baseline to follow-up between trial arms and was reported only in people abstinent from smoking. Abstinence from smoking was expressed as a risk ratio (RR). Where appropriate, we performed meta-analysis using the inverse variance method for weight, and Mantel-Haenszel method for smoking.

MAIN RESULTS

Part 1: We include 37 completed studies; 21 are new to this update. We judged five studies to be at low risk of bias, 17 to be at unclear risk and the remainder at high risk.  An intermittent very low calorie diet (VLCD) comprising full meal replacement provided free of charge and accompanied by intensive dietitian support significantly reduced weight gain at end of treatment compared with education on how to avoid weight gain (mean difference (MD) -3.70 kg, 95% confidence interval (CI) -4.82 to -2.58; 1 study, 121 participants), but there was no evidence of benefit at 12 months (MD -1.30 kg, 95% CI -3.49 to 0.89; 1 study, 62 participants). The VLCD increased the chances of abstinence at 12 months (RR 1.73, 95% CI 1.10 to 2.73; 1 study, 287 participants). However, a second study  found that no-one completed the VLCD intervention or achieved abstinence. Interventions aimed at increasing acceptance of weight gain reported mixed effects at end of treatment, 6 months and 12 months with confidence intervals including both increases and decreases in weight gain compared with no advice or health education. Due to high heterogeneity, we did not combine the data. These interventions increased quit rates at 6 months (RR 1.42, 95% CI 1.03 to 1.96; 4 studies, 619 participants; I² = 21%), but there was no evidence at 12 months (RR 1.25, 95% CI 0.76 to 2.06; 2 studies, 496 participants; I² = 26%). Some pharmacological interventions tested for limiting post-cessation weight gain (PCWG) reduced weight gain at the end of treatment (dexfenfluramine, phenylpropanolamine, naltrexone). The effects of ephedrine and caffeine combined, lorcaserin, and chromium were too imprecise to give useful estimates of treatment effects. There was very low-certainty evidence that personalized weight management support reduced weight gain at end of treatment (MD -1.11 kg, 95% CI -1.93 to -0.29; 3 studies, 121 participants; I² = 0%), but no evidence in the longer-term 12 months (MD -0.44 kg, 95% CI -2.34 to 1.46; 4 studies, 530 participants; I² = 41%). There was low to very low-certainty evidence that detailed weight management education without personalized assessment, planning and feedback did not reduce weight gain and may have reduced smoking cessation rates (12 months: MD -0.21 kg, 95% CI -2.28 to 1.86; 2 studies, 61 participants; I² = 0%; RR for smoking cessation 0.66, 95% CI 0.48 to 0.90; 2 studies, 522 participants; I² = 0%). Part 2: We include 83 completed studies, 27 of which are new to this update. There was low certainty that exercise interventions led to minimal or no weight reduction compared with standard care at end of treatment (MD -0.25 kg, 95% CI -0.78 to 0.29; 4 studies, 404 participants; I² = 0%). However, weight was reduced at 12 months (MD -2.07 kg, 95% CI -3.78 to -0.36; 3 studies, 182 participants; I² = 0%). Both bupropion and fluoxetine limited weight gain at end of treatment (bupropion MD -1.01 kg, 95% CI -1.35 to -0.67; 10 studies, 1098 participants; I² = 3%); (fluoxetine MD -1.01 kg, 95% CI -1.49 to -0.53; 2 studies, 144 participants; I² = 38%; low- and very low-certainty evidence, respectively). There was no evidence of benefit at 12 months for bupropion, but estimates were imprecise (bupropion MD -0.26 kg, 95% CI -1.31 to 0.78; 7 studies, 471 participants; I² = 0%). No studies of fluoxetine provided data at 12 months. There was moderate-certainty that NRT reduced weight at end of treatment (MD -0.52 kg, 95% CI -0.99 to -0.05; 21 studies, 2784 participants; I² = 81%) and moderate-certainty that the effect may be similar at 12 months (MD -0.37 kg, 95% CI -0.86 to 0.11; 17 studies, 1463 participants; I² = 0%), although the estimates are too imprecise to assess long-term benefit. There was mixed evidence of the effect of varenicline on weight, with high-certainty evidence that weight change was very modestly lower at the end of treatment (MD -0.23 kg, 95% CI -0.53 to 0.06; 14 studies, 2566 participants; I² = 32%); a low-certainty estimate gave an imprecise estimate of higher weight at 12 months (MD 1.05 kg, 95% CI -0.58 to 2.69; 3 studies, 237 participants; I² = 0%).

AUTHORS' CONCLUSIONS

Overall, there is no intervention for which there is moderate certainty of a clinically useful effect on long-term weight gain. There is also no moderate- or high-certainty evidence that interventions designed to limit weight gain reduce the chances of people achieving abstinence from smoking.

White blood cell count and clustered components of metabolic syndrome: A study in western Iran

Background

White blood cell count (WBC) is one of the objective parameters of systemic inflammation. The aim of present study was to evaluate the relationship between WBC count and metabolic syndrome.

Methods

In this study on Lor population in Borujerd province (West of Iran), from 2011 to 2013, 800 persons were enrolled. MetS was defined based on ATP III criteria. Differences among the quartiles of WBC were examined by one-way analysis of variance.

Results

Only 14.7% did not have any of the five components and 43% of all subjects had metabolic syndrome. The means of WBC count in MetS group were significantly higher than the control group (p<0.0001). In subjects without any MetS components, the means of WBC was 5.321 /µL, and it was 5.664, 5.714, 5.961, 6.302, and 6.572 /µL in subjects with 1, 2, 3, 4, and 5 components, respectively. These differences show a significant increasing trend (p<0.0001).

Conclusion

WBC count was associated with clustered components of metabolic syndrome. It seems that WBC counts could be considered as a predictive factor for metabolic syndrome in preventive medicine.

Inflammation and cardiovascular disease: From mechanisms to therapeutics

Inflammation constitutes a complex, highly conserved cascade of molecular and cellular events. Inflammation has been labeled as “the fire within,” is highly regulated, and is critical to host defense and tissue repair. In general, inflammation is beneficial and has evolved to promote survival. However, inflammation can also be maladaptive when chronically activated and sustained, leading to progressive tissue injury and reduced survival. Examples of a maladaptive response include rheumatologic disease and atherosclerosis. Despite evidence gathered by Virchow over 100 years ago showing that inflammatory white cells play a role in atherogenesis, atherosclerosis was until recently viewed as a disease of passive cholesterol accumulation in the subendothelial space. This view has been supplanted by considerable basic scientific and clinical evidence demonstrating that every step of atherogenesis, from the development of endothelial cell dysfunction to foam cell formation, plaque formation and progression, and ultimately plaque rupture stemming from architectural instability, is driven by the cytokines, interleukins, and cellular constituents of the inflammatory response. Herein we provide an overview of the role of inflammation in atherosclerotic cardiovascular disease, discuss the predictive value of various biomarkers involved in inflammation, and summarize recent clinical trials that evaluated the capacity of various pharmacologic interventions to attenuate the intensity of inflammation and impact risk for acute cardiovascular events.

CIN or not: An approach to the evaluation and management of chronic idiopathic neutrophilia

Neutrophilia refers to an increase in the number of circulating neutrophils in the peripheral blood. Some common etiologies include infection, inflammatory conditions, myeloproliferative disorders, malignancies, endocrinopathies, drugs, and anemia. Rare disorders such as leukocyte adhesion deficiency can also cause neutrophilia. In many cases, there is an elevation of neutrophil count that persists for months or even years with no clear underlying cause in an otherwise asymptomatic patient. This is referred to as chronic idiopathic neutrophilia (CIN). Despite being a condition encountered by many physicians, there is a paucity of literature addressing CIN. Certain conditions such as stress, exercise, smoking, obesity, and obstructive sleep apnea have been associated with CIN and may provide explanations for neutrophilia previously thought to be idiopathic. Herein, we present a review of the literature on CIN and propose a systematic approach to this commonly encountered clinical condition.

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.

White Blood Cell Count and Risk of Incident Lung Cancer in the UK Biobank

Background

The contribution of measurable immunological and inflammatory parameters to lung cancer development remains unclear, particularly among never smokers. We investigated the relationship between total and differential white blood cell (WBC) counts and incident lung cancer risk overall and among subgroups defined by smoking status and sex in the United Kingdom (UK).

Methods

We evaluated 424 407 adults aged 37-73 years from the UK Biobank. Questionnaires, physical measurements, and blood were administered and collected at baseline in 2006-2010. Complete blood cell counts were measured using standard methods. Lung cancer diagnoses and histological classifications were obtained from cancer registries. Multivariable Cox regression models were used to estimate the hazard ratio (HR) and 95% confidence intervals of incident lung cancer in relation to quartiles (Q) of total WBC and subtype-specific counts, with Q1 as the reference.

Results

There were 1493 incident cases diagnosed over an average 7-year follow-up. Overall, the highest quartile of total WBC count was statistically significantly associated with elevated lung cancer risk (HR_Q4 = 1.67, 95% CI = 1.41 to 1.98). Among women, increased risks were found in current smokers (n _cases / n = 244 / 19 464, HR_Q4 = 2.15, 95% CI = 1.46 to 3.16), former smokers (n _cases / n = 280 / 69 198, HR_Q4 = 1.75, 95% CI = 1.24 to 2.47), and never smokers without environmental tobacco smoke exposure (n_cases / n = 108 / 111 294, HR_Q4 = 1.93, 95% CI = 1.11 to 3.35). Among men, stronger associations were identified in current smokers (n_{case s} / n = 329 / 22 934, HR_Q4 = 2.95, 95% CI = 2.04 to 4.26) and former smokers (n_{c ases} / n = 358/71 616, HR_Q4 = 2.38, 95% CI = 1.74 to 3.27) but not in never smokers. Findings were similar for lung adenocarcinoma and squamous cell carcinoma and were driven primarily by elevated neutrophil fractions.

Conclusions

Elevated WBCs could potentially be one of many important markers for increased lung cancer risk, especially among never-smoking women and ever-smoking men.

White cell counts in relation to mortality in a general population of cohort study in the Netherlands: a mediating effect or not?

BACKGROUND

White cell count (WCC) is a clinical marker of inflammation. Data are limited regarding the association of total and differential WCC with risk of mortality, and its role related with smoking and body mass index (BMI).

METHODS

A total of 14 433 participants (4150 men; 10 283 women; average age 47.3±11.8 years) from the Dutch European Prospective Investigation into Cancer and Nutrition-Netherlands cohort were included. The associations between prediagnostic total WCC and its subtypes and risk of all-cause, cancer and cardiovascular disease (CVD) mortality were assessed. The role of WCC related with smoking and BMI on mortality was further explored. Multivariate Cox regression models were performed to estimate the HR and 95% CI.

RESULTS

After an average follow-up of 15.8 years, a total of 936 death cases were identified (466 cancer; 179 CVD; 291 other causes). Statistically significant graded associations between total WCC, and counts of lymphocytes, monocytes, neutrophils and eosinophils and risk of total mortality were observed. These associations were more apparent in current smokers. Strong associations for all-cause mortality or cancer mortality were observed in subjects with BMI ≥25 kg/m², ever smoking and elevated WCC (HR 3.92, 95% CI 2.76 to 5.57; HR 3.93, 95% CI 2.30 to 6.72). WCC partly mediated the associations between smoking or BMI and all-cause mortality.

CONCLUSIONS

Prediagnostic WCC and its subtypes are associated with all-cause, cancer and CVD mortality risk. It may play a partially mediate role on the association between smoking or obesity and mortality.

Relapse prevention interventions for smoking cessation

BACKGROUND

A number of treatments can help smokers make a successful quit attempt, but many initially successful quitters relapse over time. Several interventions have been proposed to help prevent relapse.

OBJECTIVES

To assess whether specific interventions for relapse prevention reduce the proportion of recent quitters who return to smoking.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group trials register, clinicaltrials.gov, and the ICTRP in May 2019 for studies mentioning relapse prevention or maintenance in their title, abstracts, or keywords.

SELECTION CRITERIA

Randomised or quasi-randomised controlled trials of relapse prevention interventions with a minimum follow-up of six months. We included smokers who quit on their own, were undergoing enforced abstinence, or were participating in treatment programmes. We included studies that compared relapse prevention interventions with a no intervention control, or that compared a cessation programme with additional relapse prevention components with a cessation programme alone.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures expected by Cochrane.

MAIN RESULTS

We included 81 studies (69,094 participants), five of which are new to this update. We judged 22 studies to be at high risk of bias, 53 to be at unclear risk of bias, and six studies to be at low risk of bias. Fifty studies included abstainers, and 30 studies helped people to quit and then tested treatments to prevent relapse. Twenty-eight studies focused on special populations who were abstinent because of pregnancy (19 studies), hospital admission (six studies), or military service (three studies). Most studies used behavioural interventions that tried to teach people skills to cope with the urge to smoke, or followed up with additional support. Some studies tested extended pharmacotherapy. We focused on results from those studies that randomised abstainers, as these are the best test of relapse prevention interventions. Of the 12 analyses we conducted in abstainers, three pharmacotherapy analyses showed benefits of the intervention: extended varenicline in assisted abstainers (2 studies, n = 1297, risk ratio (RR) 1.23, 95% confidence interval (CI) 1.08 to 1.41, I2 = 82%; moderate-certainty evidence), rimonabant in assisted abstainers (1 study, RR 1.29, 95% CI 1.08 to 1.55), and nicotine replacement therapy (NRT) in unaided abstainers (2 studies, n = 2261, RR 1.24, 95% Cl 1.04 to 1.47, I2 = 56%). The remainder of analyses of pharmacotherapies in abstainers had wide confidence intervals consistent with both no effect and a statistically significant effect in favour of the intervention. These included NRT in hospital inpatients (2 studies, n = 1078, RR 1.23, 95% CI 0.94 to 1.60, I2 = 0%), NRT in assisted abstainers (2 studies, n = 553, RR 1.04, 95% CI 0.77 to 1.40, I2 = 0%; low-certainty evidence), extended bupropion in assisted abstainers (6 studies, n = 1697, RR 1.15, 95% CI 0.98 to 1.35, I2 = 0%; moderate-certainty evidence), and bupropion plus NRT (2 studies, n = 243, RR 1.18, 95% CI 0.75 to 1.87, I2 = 66%; low-certainty evidence). Analyses of behavioural interventions in abstainers did not detect an effect. These included studies in abstinent pregnant and postpartum women at the end of pregnancy (8 studies, n = 1523, RR 1.05, 95% CI 0.99 to 1.11, I2 = 0%) and at postpartum follow-up (15 studies, n = 4606, RR 1.02, 95% CI 0.94 to 1.09, I2 = 3%), studies in hospital inpatients (5 studies, n = 1385, RR 1.10, 95% CI 0.82 to 1.47, I2 = 58%), and studies in assisted abstainers (11 studies, n = 5523, RR 0.98, 95% CI 0.87 to 1.11, I2 = 52%; moderate-certainty evidence) and unaided abstainers (5 studies, n = 3561, RR 1.06, 95% CI 0.96 to 1.16, I2 = 1%) from the general population.

AUTHORS' CONCLUSIONS

Behavioural interventions that teach people to recognise situations that are high risk for relapse along with strategies to cope with them provided no worthwhile benefit in preventing relapse in assisted abstainers, although unexplained statistical heterogeneity means we are only moderately certain of this. In people who have successfully quit smoking using pharmacotherapy, there were mixed results regarding extending pharmacotherapy for longer than is standard. Extended treatment with varenicline helped to prevent relapse; evidence for the effect estimate was of moderate certainty, limited by unexplained statistical heterogeneity. Moderate-certainty evidence, limited by imprecision, did not detect a benefit from extended treatment with bupropion, though confidence intervals mean we could not rule out a clinically important benefit at this stage. Low-certainty evidence, limited by imprecision, did not show a benefit of extended treatment with nicotine replacement therapy in preventing relapse in assisted abstainers. More research is needed in this area, especially as the evidence for extended nicotine replacement therapy in unassisted abstainers did suggest a benefit.

Total and differential white blood cell count in cannabis users: results from the cross-sectional National Health and Nutrition Examination Survey, 2005-2016

Background

Elevated white blood cell (WBC) count in tobacco cigarette smokers compared to non-smokers has been well documented, but little is known on circulating WBC counts and cannabis use.

Methods

The National Health and Nutrition Examination Survey (2005–2016) is designed to be nationally representative of United States non-institutionalized population. The current study includes adult participants 20–59 years of age (n = 16,430) who underwent a detailed examination in the mobile examination center (MEC). Cannabis use was measured using Audio Computer-Assisted Self-Interview. Cannabis use was classified into never, former, occasional (1–7 days of the past 30 days), and heavy (> 7 days of the past 30 days). WBC count was measured using the Coulter Counter method.

Results

Total WBC count was higher among heavy cannabis users when compared to never users (β = 189; 95% confidence interval: 74, 304, p = 0.001). Among circulating WBC types, modest differences were observed for neutrophil count. Neither former nor occasional cannabis use was associated with total or differential WBC counts.

Conclusions

A modest association between heavy cannabis use and WBC count was detected. Additional research is needed to understand the immune related effects of different modes of cannabis use and to elucidate the role of proinflammatory chemicals generated from smoking cannabis.

Electronic supplementary material

The online version of this article (10.1186/s42238-019-0007-8) contains supplementary material, which is available to authorized users.

Biomarkers of Exposure and Potential Harm among Natural American Spirit Smokers

OBJECTIVES

We compared biomarkers of exposure and potential harm in smokers of American Spirit (AS) to smokers of Marlboro, Newport, Camel, and Pall Mall.

METHODS

We conducted secondary analysis on: (1) data from a randomized clinical trial (RCT); and (2) the Population Assessment of Tobacco Use and Health (PATH) Study. Biomarkers analyzed included: total nicotine equivalents (TNE); 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol and its glucuronides (total NNAL); N'-nitrosonornicotine and its N-glucuronide (total NNN);3-hydroxypropylmercapturic acid(3-HPMA); 2-hydroxypropylmercapturic acid (2-HPMA), 3-hydroxy-1 methylpropylmercapturic acid (HMPMA); S-phenylmercapturic acid(SPMA); 2-cyanoethylmercapturic acid (CEMA); phenanthrene tetraol(PheT);1-hydroxypyrene (1-HOP);8-iso-PGF2α; white blood count(WBC); prostaglandin E metabolite(PGEM); and high sensitivity C-reactive protein(hsCRP).

RESULTS

AS smokers did not differ in TNE but had higher TNE per cigarette compared to other brands. Total NNAL, total NNN, CEMA, and 3-HPMA were lower in AS smokers. All other biomarkers were no different in AS smokers compared to all or the majority of the other brands.

CONCLUSIONS

Levels of total NNAL, total NNN, acrylonitrile, and acrolein were reduced in AS smokers; however, it is not known whether reductions in exposure to these toxicants contribute to reduced harm. Higher TNE per cigarette smoked in AS smokers suggests a greater addictive potential compared to other brands. Regulatory action to ensure that consumers are not misled about the risks of the AS brand are recommended.

Relapse prevention interventions for smoking cessation

BACKGROUND

A number of treatments can help smokers make a successful quit attempt, but many initially successful quitters relapse over time. Several interventions have been proposed to help prevent relapse.

OBJECTIVES

To assess whether specific interventions for relapse prevention reduce the proportion of recent quitters who return to smoking.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group trials register, clinicaltrials.gov, and the ICTRP in February 2018 for studies mentioning relapse prevention or maintenance in their title, abstracts, or keywords.

SELECTION CRITERIA

Randomised or quasi-randomised controlled trials of relapse prevention interventions with a minimum follow-up of six months. We included smokers who quit on their own, were undergoing enforced abstinence, or were participating in treatment programmes. We included studies that compared relapse prevention interventions with a no intervention control, or that compared a cessation programme with additional relapse prevention components with a cessation programme alone.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures expected by Cochrane.

MAIN RESULTS

We included 77 studies (67,285 participants), 15 of which are new to this update. We judged 21 studies to be at high risk of bias, 51 to be at unclear risk of bias, and five studies to be at low risk of bias. Forty-eight studies included abstainers, and 29 studies helped people to quit and then tested treatments to prevent relapse. Twenty-six studies focused on special populations who were abstinent because of pregnancy (18 studies), hospital admission (five studies), or military service (three studies). Most studies used behavioural interventions that tried to teach people skills to cope with the urge to smoke, or followed up with additional support. Some studies tested extended pharmacotherapy.We focused on results from those studies that randomised abstainers, as these are the best test of relapse prevention interventions. Of the 12 analyses we conducted in abstainers, three pharmacotherapy analyses showed benefits of the intervention: extended varenicline in assisted abstainers (2 studies, n = 1297, risk ratio (RR) 1.23, 95% confidence interval (CI) 1.08 to 1.41, I² = 82%; moderate certainty evidence), rimonabant in assisted abstainers (1 study, RR 1.29, 95% CI 1.08 to 1.55), and nicotine replacement therapy (NRT) in unaided abstainers (2 studies, n = 2261, RR 1.24, 95% Cl 1.04 to 1.47, I² = 56%). The remainder of analyses of pharmacotherapies in abstainers had wide confidence intervals consistent with both no effect and a statistically significant effect in favour of the intervention. These included NRT in hospital inpatients (2 studies, n = 1078, RR 1.23, 95% CI 0.94 to 1.60, I² = 0%), NRT in assisted abstainers (2 studies, n = 553, RR 1.04, 95% CI 0.77 to 1.40, I² = 0%; low certainty evidence), extended bupropion in assisted abstainers (6 studies, n = 1697, RR 1.15, 95% CI 0.98 to 1.35, I² = 0%; moderate certainty evidence), and bupropion plus NRT (2 studies, n = 243, RR 1.18, 95% CI 0.75 to 1.87, I² = 66%; low certainty evidence). Analyses of behavioural interventions in abstainers did not detect an effect. These included studies in abstinent pregnant and postpartum women at end of pregnancy (8 studies, n = 1523, RR 1.05, 95% CI 0.99 to 1.11, I² = 0%) and at postpartum follow-up (15 studies, n = 4606, RR 1.02, 95% CI 0.94 to 1.09, I² = 3%), studies in hospital inpatients (4 studies, n = 1300, RR 0.95, 95% CI 0.81 to 1.11, I² = 0%), and studies in assisted abstainers (10 studies, n = 5408, RR 0.99, 95% CI 0.87 to 1.13, I² = 56%; moderate certainty evidence) and unaided abstainers (5 studies, n = 3561, RR 1.06, 95% CI 0.96 to 1.16, I² = 1%) from the general population.

AUTHORS' CONCLUSIONS

Behavioural interventions that teach people to recognise situations that are high risk for relapse along with strategies to cope with them provided no worthwhile benefit in preventing relapse in assisted abstainers, although unexplained statistical heterogeneity means we are only moderately certain of this. In people who have successfully quit smoking using pharmacotherapy, there were mixed results regarding extending pharmacotherapy for longer than is standard. Extended treatment with varenicline helped to prevent relapse; evidence for the effect estimate was of moderate certainty, limited by unexplained statistical heterogeneity. Moderate-certainty evidence, limited by imprecision, did not detect a benefit from extended treatment with bupropion, though confidence intervals mean we could not rule out a clinically important benefit at this stage. Low-certainty evidence, limited by imprecision, did not show a benefit of extended treatment with nicotine replacement therapy in preventing relapse in assisted abstainers. More research is needed in this area, especially as the evidence for extended nicotine replacement therapy in unassisted abstainers did suggest a benefit.

Total and differential white blood cell count in cannabis users: results from the cross-sectional National Health and Nutrition Examination Survey, 2005-2016

BACKGROUND

Elevated white blood cell (WBC) count in tobacco cigarette smokers compared to non-smokers has been well documented, but little is known on circulating WBC counts and cannabis use.

METHODS

The National Health and Nutrition Examination Survey (2005-2016) is designed to be nationally representative of United States non-institutionalized population. The current study includes adult participants 20-59 years of age (n= 16,430) who underwent a detailed examination in the mobile examination center (MEC). Cannabis use was measured using Audio Computer-Assisted Self-Interview. Cannabis use was classified into never, former, occasional (1-7 days of the past 30 days), and heavy (>7 days of the past 30 days). WBC count was measured using the Coulter Counter method.

RESULTS

Total WBC count was higher among heavy cannabis users when compared to never users (β = 189; 95% confidence interval: 74, 304, p = 0.001). Among circulating WBC types, modest differences were observed for neutrophil count. Neither former nor occasional cannabis use was associated with total or differential WBC counts.

CONCLUSIONS

A modest association between heavy cannabis use and WBC count was detected. Additional research is needed to understand the immune related effects of different modes of cannabis use and to elucidate the role of proinflammatory chemicals generated from smoking cannabis.

Leukocytosis and Leukemia

Leukocytosis is among the most common findings on peripheral blood smear. A wide range of causes may mediate this finding, and careful clinical and laboratory evaluation assist in differentiating between benign and malignant causes of increased white blood cell counts. In this article, various nonmalignant causes are explored, including infectious, inflammatory, autoimmune, and allergic. In addition, malignant causes of leukocytosis are discussed, including myeloproliferative disorders, acute leukemia, and chronic leukemia, as well as treatment and monitoring for patients with these diseases.

Current cigarette smoking is a reversible cause of elevated white blood cell count: Cross-sectional and longitudinal studies

While cigarette smoking is a well-recognized cause of elevated white blood cell (WBC) count, studies on longitudinal effect of smoking cessation on WBC count are limited. We attempted to determine causal relationships between smoking and elevated WBC count by retrospective cross-sectional study consisting of 37,972 healthy Japanese adults who had a health check-up between April 1, 2008 and March 31, 2009 and longitudinal study involving 1730 current smokers who had more than four consecutive annual health check-ups between April 1, 2007 and March 31, 2012. In the cross-sectional study, younger age, male gender, increased body mass index, no alcohol habit, current smoking, and elevated C-reactive protein level were associated with elevated WBC count. Among these factors, current smoking had the most significant association with elevated WBC count. In subgroup analyses by WBC differentials, smoking was significantly associated with elevated counts of neutrophils, lymphocytes, monocytes, eosinophils, and basophils. Ex-smoking was not associated with elevated WBC count. In the longitudinal study, both WBC and neutrophil counts decreased significantly in one year after smoking cessation and remained down-regulated for longer than next two years. There was no significant change in either WBC or neutrophil count in those who continued smoking. These findings clearly demonstrated that current smoking is strongly associated with elevated WBC count and smoking cessation leads to recovery of WBC count in one year, which is maintained for longer than subsequent two years. Thus, current smoking is a significant and reversible cause of elevated WBC count in healthy adults.

Evaluating the relationship between biomarkers of potential harm and biomarkers of tobacco exposure among current, past, and nonsmokers: data from the National Health and Nutrition Examination Survey 2007-2012

Potential long-term health effects from tobacco products can be estimated by measuring changes in biochemical indicators of disease mechanisms like inflammation. This study assesses the potential relationships between biomarkers of potential harm (BOPH) and biomarkers of cigarette smoke exposure (BOE) based on data from the NHANES (2007-2012, n = 17,293 respondents). Statistically significant relationships were observed between white blood cells (WBC) and high-density lipoprotein (HDL) and BOE; between WBC and high-sensitivity C-reactive protein and smoking status; and between WBC and HDL and smoking intensity. This analysis suggests that WBC and HDL are useful BOPH in studies assessing the health risks of cigarette smoking.

Evaluation of Tumor Necrosis Factor-Alpha and Granulocyte Colony-Stimulating Factor Serum Levels in Lead-Exposed Smoker Workers

Inorganic lead (Pb) is able to modulate the immune response even at low to moderate exposure levels. It inhibits in vitro and in vivo activities of neutrophil leucocytes and influences their blood count in humans. Neutrophil functions are governed by a number of cytokines. Pb has been shown to affect leukocyte production of some of these cytokines in vitro. The objective of this study is to assess serum tumor necrosis factor-alpha (TNF-α) and granulocyte colony-stimulating factor (G-CSF) levels of thirty-three male lead-exposed (E) workers at a lead recycling plant as compared with twenty-eight male non-exposed (NE) workers at a food processing plant, whose current smoking habit was known. Serum TNF-α and G-CSF levels were measured by a quantitative sandwich enzyme immunoassay. Blood lead levels (Pb-B) were significantly higher in E (geometric mean (GM) 30.7 μg/dl, GSD 1.7; min-max: 9.1–81.6 μg/dl) workers than controls (GM 3.6 μg/dl, GSD 1.7; min-max: 1.0–11.0 μg/dl). E workers had significantly higher serum TNF-α (median: 107.1; min-max: 11.1–623.0 pg/ml) and G-CSF levels (median: 53.0, min-max: 31.1–197.0 pg/ml) than NE workers (TNF-α: median: 12.0; min-max: 9.4–18.8 pg/ml; G-CSF: median: 34.3, min-max: 25.1–52.2 pg/ml). In particular, the TNF-α level was shown to be significantly influenced by lead exposure and smoking habit, as well as by interaction between these two factors. Both serum TNF-α and G-CSF levels were correlated with Pb-B and absolute neutrophil count. This study is the first to detect higher serum levels of G-CSF in E over NE workers. Our data confirm that exposure to low to medium doses of lead may interfere in the complex cytokine network involved in inflammation, especially in workers who are current smokers.

Effects of smoking on healthy young men's hematologic parameters

OBJECTIVE:

Cigarette smoking carries higher risks for most of the chronic diseases. It also has chronic and acute effects on the hematologic system. This study explores the effects of cigarette smoking on some blood values of the healthy young male smokers.

METHODS:

In this study, cigarette smoking and usage of substance, additional diseases, birth places, and education levels of 171 healthy male subjects between the ages of 20 and 30 years were investigated. Anthropometric measurements of the cases were obtained. Thyroid function tests, vitamin B12, folic acid, ferritin, ferrous/ıron, total ıron binding capacity, leucocytes, platelets, hemoglobin, hematocrit, mean corpuscular volume (MCV), mean platelet volume (MPV), HBs AG, Anti-HBs and Anti-HIV were evaluated. Groups of smokers and nonsmokers were compared. The group of smokers was also sorted into subgroups of “2 year-smokers”, “5 year-smokers” and “10 year-smokers” according to their pack-years of smoking. The effects of pack-years of smoking on the blood values were also investigated.

RESULTS:

The MCV values of the group of smokers were higher than the values of nonsmokers, which were statistically significant (p<0.05). As a result of the subgroup analyses of smokers, the white blood cell (WBC) counts of the individuals smoking for 5 or more years were significantly higher than those with a history of smoking less than 5 years, (p<0.05).

CONCLUSION:

This study supports the idea that cigarette smoking and especially longer durations of smoking have adverse effects on the hematologic parameters.

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.

Relapse prevention interventions for smoking cessation

BACKGROUND

A number of treatments can help smokers make a successful quit attempt, but many initially successful quitters relapse over time. Several interventions have been proposed to help prevent relapse.

OBJECTIVES

To assess whether specific interventions for relapse prevention reduce the proportion of recent quitters who return to smoking.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group trials register in May 2013 for studies mentioning relapse prevention or maintenance in title, abstracts or keywords.

SELECTION CRITERIA

Randomized or quasi-randomized controlled trials of relapse prevention interventions with a minimum follow-up of six months. We included smokers who quit on their own, were undergoing enforced abstinence, or were participating in treatment programmes. We included trials that compared relapse prevention interventions with a no intervention control, or that compared a cessation programme with additional relapse prevention components with a cessation programme alone.

DATA COLLECTION AND ANALYSIS

Studies were screened and data extracted by one review author, and checked by a second. Disagreements were resolved by discussion or by referral to a third review author.

MAIN RESULTS

Sixty-three studies met inclusion criteria but were heterogeneous in terms of populations and interventions. We considered 41 studies that randomly assigned abstainers separately from studies that randomly assigned participants before their quit date.Upon looking at studies of behavioural interventions that randomly assigned abstainers, we detected no benefit of brief and 'skills-based' relapse prevention methods for women who had quit smoking because of pregnancy, or for smokers undergoing a period of enforced abstinence during hospitalisation or military training. We also failed to detect significant effects of behavioural interventions in trials in unselected groups of smokers who had quit on their own or through a formal programme. Amongst trials randomly assigning smokers before their quit date and evaluating the effects of additional relapse prevention components, we found no evidence of benefit of behavioural interventions or combined behavioural and pharmacotherapeutic interventions in any subgroup. Overall, providing training in skills thought to be needed for relapse avoidance did not reduce relapse, but most studies did not use experimental designs best suited to the task and had limited power to detect expected small differences between interventions. For pharmacological interventions, extended treatment with varenicline significantly reduced relapse in one trial (risk ratio (RR) 1.18, 95% confidence interval (CI) 1.03 to 1.36). Pooling of six studies of extended treatment with bupropion failed to detect a significant effect (RR 1.15, 95% CI 0.98 to 1.35). Two small trials of oral nicotine replacement treatment (NRT) failed to detect an effect, but treatment compliance was low, and in two other trials of oral NRT in which short-term abstainers were randomly assigned, a significant effect of intervention was noted.

AUTHORS' CONCLUSIONS

At the moment, there is insufficient evidence to support the use of any specific behavioural intervention to help smokers who have successfully quit for a short time to avoid relapse. The verdict is strongest for interventions focused on identifying and resolving tempting situations, as most studies were concerned with these. Little research is available regarding other behavioural approaches.Extended treatment with varenicline may prevent relapse. Extended treatment with bupropion is unlikely to have a clinically important effect. Studies of extended treatment with nicotine replacement are needed.

Reduced exposure evaluation of an Electrically Heated Cigarette Smoking System. Part 7: A one-month, randomized, ambulatory, controlled clinical study in Poland

This randomized, open-label, ambulatory, controlled clinical study investigated biomarkers associated with cardiovascular risk and biomarkers of exposure to 10 selected harmful and potentially harmful constituents (HPHC) in cigarette smoke in 316 male and female Polish smokers. Subjects were randomized to continue smoking conventional cigarettes (CC; N=79) or switch to smoking the Electrically Heated Cigarette Smoking System series-K cigarette (EHCSS-K6; N=237). Biomarker assessments were performed at several time points during the study at baseline and during the 1-month investigational period. The primary biomarkers were high-sensitivity C-reactive protein and white blood cell counts. No statistically significant differences in the two primary biomarkers were found between the study groups at the end of the study. End-of-study comparisons of secondary biomarkers between study groups indicated an increase in high-density lipoprotein cholesterol, and reductions in red blood cell count, hemoglobin, and hematocrit levels in the EHCSS-K6 group. All biomarkers of exposure to cigarette smoke HPHC were decreased in the EHCSS-K6 group, despite an increase in cigarette consumption, compared to the CC group. There were no apparent differences in any of the safety assessment parameters between the groups, and the overall incidence of study-related adverse events was low.

Sources of pre-analytical variations in yield of DNA extracted from blood samples: analysis of 50,000 DNA samples in EPIC

The European Prospective Investigation into Cancer and nutrition (EPIC) is a long-term, multi-centric prospective study in Europe investigating the relationships between cancer and nutrition. This study has served as a basis for a number of Genome-Wide Association Studies (GWAS) and other types of genetic analyses. Over a period of 5 years, 52,256 EPIC DNA samples have been extracted using an automated DNA extraction platform. Here we have evaluated the pre-analytical factors affecting DNA yield, including anthropometric, epidemiological and technical factors such as center of subject recruitment, age, gender, body-mass index, disease case or control status, tobacco consumption, number of aliquots of buffy coat used for DNA extraction, extraction machine or procedure, DNA quantification method, degree of haemolysis and variations in the timing of sample processing. We show that the largest significant variations in DNA yield were observed with degree of haemolysis and with center of subject recruitment. Age, gender, body-mass index, cancer case or control status and tobacco consumption also significantly impacted DNA yield. Feedback from laboratories which have analyzed DNA with different SNP genotyping technologies demonstrate that the vast majority of samples (approximately 88%) performed adequately in different types of assays. To our knowledge this study is the largest to date to evaluate the sources of pre-analytical variations in DNA extracted from peripheral leucocytes. The results provide a strong evidence-based rationale for standardized recommendations on blood collection and processing protocols for large-scale genetic studies.

Early impact of smoking on lung function, health, and well-being in adolescents

BACKGROUND

Smoking is the single most important risk factor for the development of chronic obstructive pulmonary disease, and more than 80% of adult smokers started smoking before the age of 20. The aim of our study was to evaluate the early impact of smoking on lung function, health, and well-being in adolescents.

METHODS

Twenty-four non-smokers (10 male, 14 female, mean age 17.6 years) and 24 smokers (mean of 3.5 pack-years; 15 male, 9 female, mean age 17.8 years) were compared in terms of lung function, bronchial hyperreactivity (BHR), levels of exhaled carbon monoxide (eCO), exhaled nitric oxide (eNO), and blood counts. A questionnaire containing items from the ISAAC study was used to detect differences in health and well-being.

RESULTS

There were no significant differences in lung function values between non-smokers and smokers (VC 95% vs. 103%, FEV(1) 106% vs. 116%, FEV(1) %/VC MAX 94.6% vs. 95.2%), whereas BHR significantly differed (P < 0.05). Furthermore, significant differences were found for eCO, eNO, Hb, leukocytes, and neutrophils. Health and well-being in terms of sleep and physical activity were significantly worse in smokers.

CONCLUSION

Our results suggest an early impact of smoking on health after as few as 3.5 pack-years. Early signs of smoking are an increase in BHR, changes in blood count and a decrease of eNO even before changes in lung function become apparent.

Interventions for preventing weight gain after smoking cessation

BACKGROUND

Most people who stop smoking gain weight. There are some interventions that have been designed to reduce weight gain when stopping smoking. Some smoking cessation interventions may also limit weight gain although their effect on weight has not been reviewed.

OBJECTIVES

To systematically review the effect of: (1) Interventions targeting post-cessation weight gain on weight change and smoking cessation.(2) Interventions designed to aid smoking cessation that may also plausibly affect weight on post-cessation weight change.

SEARCH METHODS

Part 1 - We searched the Cochrane Tobacco Addiction Group's Specialized Register and CENTRAL in September 2011.Part 2 - In addition we searched the included studies in the following "parent" Cochrane reviews: nicotine replacement therapy (NRT), antidepressants, nicotine receptor partial agonists, cannabinoid type 1 receptor antagonists and exercise interventions for smoking cessation published in Issue 9, 2011 of the Cochrane Library.

SELECTION CRITERIA

Part 1 - We included trials of interventions that were targeted at post-cessation weight gain and had measured weight at any follow up point and/or smoking cessation six or more months after quit day.Part 2 - We included trials that had been included in the selected parent Cochrane reviews if they had reported weight gain at any time point.

DATA COLLECTION AND ANALYSIS

We extracted data on baseline characteristics of the study population, intervention, outcome and study quality. Change in weight was expressed as difference in weight change from baseline to follow up between trial arms and was reported in abstinent smokers only. Abstinence from smoking was expressed as a risk ratio (RR). We used the most rigorous definition of abstinence available in each trial. Where appropriate, we performed meta-analysis using the inverse variance method for weight and Mantel-Haenszel method for smoking using a fixed-effect model.

MAIN RESULTS

Part 1: Some pharmacological interventions tested for limiting post cessation weight gain (PCWG) resulted in a significant reduction in WG at the end of treatment (dexfenfluramine (Mean difference (MD) -2.50 kg, 95% confidence interval (CI) -2.98 to -2.02, 1 study), phenylpropanolamine (MD -0.50 kg, 95% CI -0.80 to -0.20, N=3), naltrexone (MD -0.78 kg, 95% CI -1.52 to -0.05, N=2). There was no evidence that treatment reduced weight at 6 or 12 months (m). No pharmacological intervention significantly affected smoking cessation rates.Weight management education only was associated with no reduction in PCWG at end of treatment (6 or 12m). However these interventions significantly reduced abstinence at 12m (Risk ratio (RR) 0.66, 95% CI 0.48 to 0.90, N=2). Personalised weight management support reduced PCWG at 12m (MD -2.58 kg, 95% CI -5.11 to -0.05, N=2) and was not associated with a significant reduction of abstinence at 12m (RR 0.74, 95% CI 0.39 to 1.43, N=2). A very low calorie diet (VLCD) significantly reduced PCWG at end of treatment (MD -3.70 kg, 95% CI -4.82 to -2.58, N=1), but not significantly so at 12m (MD -1.30 kg, 95% CI -3.49 to 0.89, N=1). The VLCD increased chances of abstinence at 12m (RR 1.73, 95% CI 1.10 to 2.73, N=1). There was no evidence that cognitive behavioural therapy to allay concern about weight gain (CBT) reduced PCWG, but there was some evidence of increased PCWG at 6m (MD 0.74, 95% CI 0.24 to 1.24). It was associated with improved abstinence at 6m (RR 1.83, 95% CI 1.07 to 3.13, N=2) but not at 12m (RR 1.25, 95% CI 0.83 to 1.86, N=2). However, there was significant statistical heterogeneity.Part 2: We found no evidence that exercise interventions significantly reduced PCWG at end of treatment (MD -0.25 kg, 95% CI -0.78 to 0.29, N=4) however a significant reduction was found at 12m (MD -2.07 kg, 95% CI -3.78 to -0.36, N=3).Both bupropion and fluoxetine limited PCWG at the end of treatment (bupropion MD -1.12 kg, 95% CI -1.47 to -0.77, N=7) (fluoxetine MD -0.99 kg, 95% CI -1.36 to -0.61, N=2). There was no evidence that the effect persisted at 6m (bupropion MD -0.58 kg, 95% CI -2.16 to 1.00, N=4), (fluoxetine MD -0.01 kg, 95% CI -1.11 to 1.10, N=2) or 12m (bupropion MD -0.38 kg, 95% CI -2.00 to 1.24, N=4). There were no data on WG at 12m for fluoxetine.Overall, treatment with NRT attenuated PCWG at the end of treatment (MD -0.69 kg, 95% CI -0.88 to -0.51, N=19), with no strong evidence that the effect differed for the different forms of NRT. There was evidence of significant statistical heterogeneity caused by one study which reported a 4.3 kg reduction in PCWG due to NRT. With this study removed, the difference in weight change at end of treatment was -0.45 kg (95% CI -0.66 to -0.27, N=18). There was no evidence of an effect on PCWG at 12m (MD -0.42 kg, 95% CI -0.92 to 0.08, N=15).We found evidence that varenicline significantly reduced PCWG at end of treatment (MD -0.41 kg, 95% CI -0.63 to -0.19, N=11), but this effect was not maintained at 6 or 12m. Three studies compared the effect of bupropion to varenicline. Participants taking bupropion gained significantly less weight at the end of treatment (-0.51 kg (95% CI -0.93 to -0.09 kg), N=3). Direct comparison showed no significant difference in PCWG between varenicline and NRT.

AUTHORS' CONCLUSIONS

Although some pharmacotherapies tested to limit PCWG show evidence of short-term success, other problems with them and the lack of data on long-term efficacy limits their use. Weight management education only, is not effective and may reduce abstinence. Personalised weight management support may be effective and not reduce abstinence, but there are too few data to be sure. One study showed a VLCD increased abstinence but did not prevent WG in the longer term. CBT to accept WG did not limit PCWG and may not promote abstinence in the long term. Exercise interventions significantly reduced weight in the long term, but not the short term. More studies are needed to clarify whether this is an effect of treatment or a chance finding. Bupropion, fluoxetine, NRT and varenicline reduce PCWG while using the medication. Although this effect was not maintained one year after stopping smoking, the evidence is insufficient to exclude a modest long-term effect. The data are not sufficient to make strong clinical recommendations for effective programmes to prevent weight gain after cessation.

Relationship between biomarkers of cigarette smoke exposure and biomarkers of inflammation, oxidative stress, and platelet activation in adult cigarette smokers

BACKGROUND

Cigarette smoking is a risk factor for several diseases, including cardiovascular disease, chronic obstructive pulmonary disease, and lung cancer, but the role of specific smoke constituents in these diseases has not been clearly established.

METHODS

The relationships between biomarkers of potential harm (BOPH), associated with inflammation [white blood cell (WBC), high sensitivity C-reactive protein (hs-CRP), fibrinogen, and von Willebrand factor (vWF)], oxidative stress [8-epi-prostaglandin F(2α) (8-epiPGF(2α))] and platelet activation [11-dehydro-thromboxin B(2) (11-dehTxB(2))], and machine-measured tar yields (grouped into four categories), biomarkers of exposure (BOE) to cigarette smoke: nicotine and its five metabolites (nicotine equivalents), 4-methylnitrosamino-1-(3-pyridyl)-1-butanol (total NNAL), carboxyhemoglobin, 1-hydroxypyrene, 3-hydroxypropylmercapturic acid, and monohydroxybutenyl-mercapturic acid, were investigated in 3,585 adult smokers and 1,077 nonsmokers.

RESULTS

Overall, adult smokers had higher levels of BOPHs than nonsmokers. Body mass index (BMI), smoking duration, tar category, and some of the BOEs were significant factors in the multiple regression models. Based on the F value, BMI was the highest ranking factor in the models for WBC, hs-CRP, fibrinogen, and 8-epiPGF(2α), respectively, and gender and smoking duration for 11-dehTxB(2) and vWF, respectively.

CONCLUSIONS

Although several demographic factors and some BOEs were statistically significant in the model, the R(2) values indicate that only up to 22% of the variability can be explained by these factors, reflecting the complexity and multifactorial nature of the disease mechanisms.

IMPACT

The relationships between the BOEs and BOPHs observed in this study may help with the identification of appropriate biomarkers and improve the design of clinical studies in smokers.

Longitudinal study on white blood cell count and the incidence of metabolic syndrome

OBJECTIVE

Many studies have revealed that white blood cell count (WBC) is related to insulin resistance which is a central mechanism of metabolic syndrome (MetS). However, few cohort studies have examined the role of WBC in the development of MetS. We hypothesized that WBC is associated with the future development of MetS, and investigated the longitudinal incidence of MetS in healthy workers.

METHODS

WBC was measured in 5,073 workers (mean age 42.5 years) without MetS at baseline. The incidence of MetS was monitored over 7 years of follow-up, in relation to quartiles of WBC. During the follow-up, 925 participants were diagnosed as MetS.

RESULTS

Incidence of MetS was increased in participants with higher WBC: the rates of incidence of MetS were 22.6, 32.9, 42.9, and 57.5 per 1,000 person-years of follow-up in the 1st, 2nd, 3rd, and 4th quartiles of WBC, respectively. After adjustments for confounding factors, the adjusted hazards ratio (95% confidence interval) for MetS was 1.00 (reference), 1.22 (0.98 to 1.51), 1.52 (1.24 to 1.87), and 1.66 (1.35 to 2.04) through the quartiles of WBC, respectively, (p <0.001). This relationship was consistent among current smokers and never smokers, and among male and female genders, respectively.

CONCLUSION

WBC is useful in predicting the future development of MetS which leads to atherosclerotic diseases.

Decreased serum antibody responses to recombinant pneumocystis antigens in HIV-infected and uninfected current smokers

Serologic studies can provide important insights into the epidemiology and transmission of Pneumocystis jirovecii. Exposure to P. jirovecii can be assessed by serum antibody responses to recombinant antigens from the major surface glycoprotein (MsgC), although factors that influence the magnitude of the antibody response are incompletely understood. We determined the magnitudes of antibody responses to P. jirovecii in comparison to adenovirus and respiratory syncytial virus (RSV) in HIV-infected and uninfected patients and identified predictors associated with the magnitude of the response. We performed a cross-sectional analysis using serum samples and data from 153 HIV-positive and 92 HIV-negative subjects enrolled in a feasibility study of the Veterans Aging Cohort 5 Site Study (VACS 5). Antibodies were measured using an enzyme-linked immunosorbent assay (ELISA). Independent predictors of antibody responses were determined using multivariate Tobit regression models. The results showed that serum antibody responses to P. jirovecii MsgC fragments were significantly and independently decreased in current smokers. Antibodies to P. jirovecii also tended to be lower with chronic obstructive pulmonary disease (COPD), hazardous alcohol use, injection drug use, and HIV infection, although these results were not statistically significant. These results were specific to P. jirovecii and did not correlate with adenovirus. Antibody responses to RSV were in the inverse direction. Thus, current smoking was independently associated with decreased P. jirovecii antibody responses. Whether smoking exerts an immunosuppressive effect that affects the P. jirovecii antibody response, colonization, or subsequent risk for disease is unclear; prospective, longitudinal studies are needed to evaluate these findings further.

Cross-sectional study of biomarkers of exposure and biological effect on monozygotic twins discordant for smoking

BACKGROUND

The aim of this study was to investigate the possible correlation between smoking status and biomarkers of exposure (BoE) and biological effect (BoBE) in monozygotic twins discordant for smoking status (smoker and non-smoker pairs). By eliminating potential genetic variability in this manner, a clearer pattern of the effects of lifestyle and environmental exposures should become apparent.

METHODS

This was a cross-sectional study on monozygotic healthy twins (44 subjects, 26 males and 18 females) with a mean age 31.5 years. BoE to cigarette smoke and BoBE were measured in body fluids (24 h urine and blood) after medical pre-screening.

RESULTS

All BoE were significantly higher in the smoker twins. Among BoBE, 11-dehydrothromboxane B(2) (11-dehydro TBX), 2,3-dinorthromboxane B(2) (2,3-dinor TBX), 8-epi-prostaglandin F2α (8-epiPGF), hydroxyproline (OH-P), fibrinogen, white blood cell (WBC), neutrophil and lymphocyte counts and heart rate were statistically significantly increased in the smoker compared to the non-smoker twins. Moreover, statistically significant correlations between neutrophil count and 11-dehydro TBX (r=0.32), WBC and 8-epiPGF (r=0.33), OH-P and 8-epiPGF (r=0.49) and heart rate and fibrinogen (r=0.46) were observed.

CONCLUSIONS

The study results confirmed the reliability of the BoE for the evaluation of smoking status. Moreover, a subset of the BoBE, reported as being associated with inflammatory conditions and early stages of vascular disorders, has emerged as showing a consistent relationship with smoking status from the present and the previous studies. By using monozygotic twin pairs, genetic variability has been excluded as a possible source of variability in this study. These results should assist in the interpretation of other population studies using these biomarkers.

Longitudinal trends of total white blood cell and differential white blood cell counts of atomic bomb survivors

In studying the late health effects of atomic-bomb (A-bomb) survivors, earlier findings were that white blood cell (WBC) count increased with radiation dose in cross-sectional studies. However, a persistent effect of radiation on WBC count and other risk factors has yet to be confirmed. The objectives of the present study were 1) to examine the longitudinal relationship between A-bomb radiation dose and WBC and differential WBC counts among A-bomb survivors and 2) to investigate the potential confounding risk factors (such as age at exposure and smoking status) as well as modification of the radiation dose-response. A total of 7,562 A-bomb survivors in Hiroshima and Nagasaki were included in this study from 1964-2004. A linear mixed model was applied using the repeated WBC measurements. During the study period, a secular downward trend of WBC count was observed. Radiation exposure was a significant risk factor for elevated WBC and differential WBC counts over time. A significant increase of WBC counts among survivors with high radiation dose (> 2 Gy) was detected in men exposed below the age of 20 and in women regardless of age at exposure. Effects on WBC of low dose radiation remain unclear, however. Cigarette smoking produced the most pronounced effect on WBC counts and its impact was much larger than that of radiation exposure.

Short term effects of reduced exposure to cigarette smoke on white blood cells, platelets and red blood cells in adult cigarette smokers

Previous studies indicate that cigarette smokers have a 5-30% higher white blood cell counts (WBC) compared to non-smokers and higher red blood cell counts.

METHODS

This study was to pool hematology data from three similar studies and analyze the data for effects on WBC, its subpopulations, platelets, red blood cell count (RBC) and hematocrit in adult cigarette smokers three days after using an electrically heated cigarette smoking system (EHCSS) as a potential reduced exposure product (PREP) or no-smoking compared to smoking a conventional cigarette.

RESULTS

Lower exposure to cigarette smoke in adult, long term smokers, by using an EHCSS or stopping smoking, leads to statistically significant decreases of up to 9% in WBC, neutrophils, lymphocytes, platelets, RBC and hematocrit within three days. Switching from CC-smoking to EHCSS-smoking or no-smoking resulted in lower WBC and vice versa within 3 days.

CONCLUSION

This clinical model may be used as a screening tool to find new technologies that could provide insights on changes in inflammation resulting from the change in cigarette smoke.

Adaptive regression modeling of biomarkers of potential harm in a population of U.S. adult cigarette smokers and nonsmokers

BACKGROUND

This article describes the data mining analysis of a clinical exposure study of 3585 adult smokers and 1077 nonsmokers. The analysis focused on developing models for four biomarkers of potential harm (BOPH): white blood cell count (WBC), 24 h urine 8-epi-prostaglandin F2alpha (EPI8), 24 h urine 11-dehydro-thromboxane B2 (DEH11), and high-density lipoprotein cholesterol (HDL).

METHODS

Random Forest was used for initial variable selection and Multivariate Adaptive Regression Spline was used for developing the final statistical models

RESULTS

The analysis resulted in the generation of models that predict each of the BOPH as function of selected variables from the smokers and nonsmokers. The statistically significant variables in the models were: platelet count, hemoglobin, C-reactive protein, triglycerides, race and biomarkers of exposure to cigarette smoke for WBC (R-squared = 0.29); creatinine clearance, liver enzymes, weight, vitamin use and biomarkers of exposure for EPI8 (R-squared = 0.41); creatinine clearance, urine creatinine excretion, liver enzymes, use of Non-steroidal antiinflammatory drugs, vitamins and biomarkers of exposure for DEH11 (R-squared = 0.29); and triglycerides, weight, age, sex, alcohol consumption and biomarkers of exposure for HDL (R-squared = 0.39).

CONCLUSIONS

Levels of WBC, EPI8, DEH11 and HDL were statistically associated with biomarkers of exposure to cigarette smoking and demographics and life style factors. All of the predictors together explain 29%-41% of the variability in the BOPH.

Interventions for preventing weight gain after smoking cessation

BACKGROUND

Most people who stop smoking gain weight, on average about 7 kg in the long term. There are some interventions that have been specifically designed to tackle smoking cessation whilst also limiting weight gain. Many smoking cessation pharmacotherapies and other interventions may also limit weight gain.

OBJECTIVES

This review is divided into two parts. (1) Interventions designed specifically to aid smoking cessation and limit post-cessation weight gain (2) Interventions designed to aid smoking cessation that may also plausibly have an effect on weight

SEARCH STRATEGY

Part 1: We searched the Cochrane Tobacco Addiction Group's Specialized Register which includes trials indexed in MEDLINE, EMBASE, SciSearch and PsycINFO, and other reviews and conference abstracts. Part 2: We searched the included studies of Cochrane smoking cessation reviews of nicotine replacement therapy, antidepressants, nicotine receptor partial agonists, cannabinoid type 1 receptor antagonists (rimonabant), and exercise interventions, published in Issue 4, 2008 of The Cochrane Library.

SELECTION CRITERIA

Part 1: We included trials of interventions designed specifically to address both smoking cessation and post-cessation weight gain that had measured weight at any follow-up point and/or smoking six months or more after quitting.Part 2: We included trials from the selected Cochrane reviews that could plausibly modify post-cessation weight gain if they had reported weight gain by trial arm at end of treatment or later.

DATA COLLECTION AND ANALYSIS

We extracted data in duplicate on smoking and weight for part 1 trials, and on weight only for part 2. Abstinence from smoking is expressed as a risk ratio (RR), using the most rigorous definition of abstinence available in each trial, and biochemically validated rates if available. The outcome is expressed as the difference in weight change between trial arms from baseline. Where appropriate, we performed meta-analysis using the Mantel-Haenszel method for smoking and inverse variance for weight using a fixed-effect model.

MAIN RESULTS

We found evidence that pharmacological interventions aimed at reducing post-cessation weight gain resulted in a significant reduction in weight gain at the end of treatment (dexfenfluramine (-2.50kg [-2.98kg to -2.02kg], fluoxetine (-0.80kg [-1.27kg to -0.33kg], phenylpropanolamine (PPA) (-0.50kg [-0.80kg to -0.20kg], naltrexone (-0.76kg [-1.51kg to -0.01kg])). No evidence of maintenance of the treatment effect was found at six or 12 months.Among the behavioural interventions, only weight control advice was associated with no reduction in weight gain and with a possible reduction in abstinence. Individualized programmes were associated with reduced weight gain at end of treatment and at 12 months (-2.58kg [-5.11kg to -0.05kg]), and with no effect on abstinence (RR 0.74 [0.39 to 1.43]). Very low calorie diets (-1.30kg (-3.49kg to 0.89kg] at 12 months) and cognitive behavioural therapy (CBT) (-5.20kg (-9.28kg to -1.12kg] at 12 months) were both associated with improved abstinence and reduced weight gain at end of treatment and at long-term follow up.Both bupropion (300mg/day) and fluoxetine (30mg and 60mg/day combined) were found to limit post-cessation weight gain at the end of treatment (-0.76kg [-1.17kg to -0.35kg] I(2)=48%) and -1.30kg [-1.91kg to -0.69kg]) respectively. There was no evidence that the weight reducing effect of bupropion was dose-dependent. The effect of bupropion at one year was smaller and confidence intervals included no effect (-0.38kg [-2.001kg to 1.24kg]).We found no evidence that exercise interventions significantly reduced post-cessation weight gain at end of treatment but evidence for an effect at 12 months (-2.07kg [-3.78kg, -0.36kg]).Treatment with NRT resulted in attenuation of post-cessation weight gain (-0.45kg [-0.70kg, -0.20kg]) at the end of treatment, with no evidence that the effect differed for different forms of NRT. The estimated weight gain reduction was similar at 12 months (-0.42kg [-0.92kg, 0.08kg]) but the confidence intervals included no effect.There were no relevant data on the effect of rimonabant on weight gain.We found no evidence that varenicline significantly reduced post-cessation weight gain at end of treatment and no follow-up data are currently available. One study randomizing successful quitters to 12 more weeks of active treatment showed weight to be reduced by 0.71kg (-1.04kg to -0.38kg). In three studies, participants taking bupropion gained significantly less weight at the end of treatment than those on varenicline (-0.51kg [-0.93kg to -0.09kg]).

AUTHORS' CONCLUSIONS

Behavioural interventions of general advice only are not effective and may reduce abstinence. Individualized interventions, very low calorie diets, and CBT may be effective and not reduce abstinence. Exercise interventions are not associated with reduced weight gain at end of treatment, but may be associated with worthwhile reductions in weight gain in the long term, Bupropion, fluoxetine, nicotine replacement therapy, and probably varenicline all reduced weight gain while being used. Although this effect was not maintained one year after quitting for bupropion, fluoxetine, and nicotine replacement, the evidence is insufficient to exclude a modest long-term effect. The data are not sufficient to make strong clinical recommendations for effective programmes.

Relapse prevention interventions for smoking cessation

BACKGROUND

A number of treatments can help smokers make a successful quit attempt, but many initially successful quitters relapse over time. Several interventions were proposed to help prevent relapse.

OBJECTIVES

To assess whether specific interventions for relapse prevention reduce the proportion of recent quitters who return to smoking.

SEARCH STRATEGY

We searched the Cochrane Tobacco Addiction Group trials register in August 2008 for studies mentioning relapse prevention or maintenance in title, abstracts or keywords.

SELECTION CRITERIA

Randomized or quasi-randomized controlled trials of relapse prevention interventions with a minimum follow up of six months. We included smokers who quit on their own, or were undergoing enforced abstinence, or who were participating in treatment programmes. We included trials that compared relapse prevention interventions to a no intervention control, or that compared a cessation programme with additional relapse prevention components to a cessation programme alone.

DATA COLLECTION AND ANALYSIS

Studies were screened and data extracted by one author and checked by a second. Disagreements were resolved by discussion or referral to a third author.

MAIN RESULTS

Fifty-four studies met inclusion criteria, but were heterogeneous in terms of populations and interventions. We considered 36 studies that randomized abstainers separately from studies that randomized participants prior to their quit date.Looking at studies of behavioural interventions which randomised abstainers, we detected no benefit of brief and 'skills-based' relapse prevention methods for women who had quit smoking due to pregnancy, or for smokers undergoing a period of enforced abstinence during hospitalisation or military training. We also failed to detect significant effects of behavioural interventions in trials in unselected groups of smokers who had quit on their own or with a formal programme. Amongst trials randomising smokers prior to their quit date and evaluating the effect of additional relapse prevention components we also found no evidence of benefit of behavioural interventions in any subgroup. Overall, providing training in skills thought to be needed for relapse avoidance did not reduce relapse, but most studies did not use experimental designs best suited to the task, and had limited power to detect expected small differences between interventions. For pharmacological interventions, extended treatment with varenicline significantly reduced relapse in one trial (risk ratio 1.18, 95% confidence interval 1.03 to 1.36). Pooling of five studies of extended treatment with bupropion failed to detect a significant effect (risk ratio 1.17; 95% confidence interval 0.99 to 1.39). Two small trials of oral nicotine replacement treatment (NRT) failed to detect an effect but treatment compliance was low and in two other trials of oral NRT randomizing short-term abstainers there was a significant effect of intervention.

AUTHORS' CONCLUSIONS

At the moment there is insufficient evidence to support the use of any specific behavioural intervention for helping smokers who have successfully quit for a short time to avoid relapse. The verdict is strongest for interventions focusing on identifying and resolving tempting situations, as most studies were concerned with these. There is little research available regarding other behavioural approaches. Extended treatment with varenicline may prevent relapse. Extended treatment with bupropion is unlikely to have a clinically important effect. Studies of extended treatment with nicotine replacement are needed.

Having more healthy practice was associated with low white blood cell counts in middle-aged Japanese male and female workers

White blood cell (WBC) count is well known to be an independent risk marker for cardiovascular disease. The aim of this study is to examine the relationships of WBC counts to seven health practices including obesity, eating habits, smoking, alcohol intake, sleeping, physical activity, and perceived mental stress, and then clustering the relevant healthy practices. The subjects were 1,492 male and 316 female Japanese workers aged 40 yr and over in 2002. Each of seven health practices from a self-administered questionnaire was categorized as a 'healthy' or 'unhealthy' practice, and WBC counts from fasting blood samples were determined by automated particle counters. The means of age and WBC counts were 49.5 yr and 5,375 cells/microl in men, and 48.6 yr and 4,890 cells/microl in women, respectively. After multivariate adjustments for all health practices and age, the estimated WBC counts were significantly lower in normal weight subjects and never or former smokers (p<0.01). Age-adjusted WBC counts decreased significantly by 204.9+/-23.7 cells/microl (means+/-SE) and 117.6+/-53.2 cells/microl for each increase in one healthy practice (p<0.05), respectively, suggesting that cultivating healthier practices would lead to lower WBC counts. This study recommends modifying unhealthy practice one by one and maintaining healthy practices as an effective strategy for the prevention of atherosclerotic diseases, in addition, to quit smoking or abstain from heavy smoking especially in men is important to prevent the low-grade inflammation.

A 12-month, randomized, controlled study to evaluate exposure and cardiovascular risk factors in adult smokers switching from conventional cigarettes to a second-generation electrically heated cigarette smoking system

This randomized, controlled, forced-switching, open-label, parallel-group study in 97 adult male and female smokers of conventional cigarettes evaluated biomarkers of tobacco smoke exposure and cardiovascular risk factors. After baseline measurements, smokers were either switched to a second-generation electrically heated cigarette smoking system (EHCSS) or continued smoking conventional cigarettes for 12 months. Biomarkers of exposure and cardiovascular risk factors were measured at 0.5, 1, 2, 3, 4, 5, 6, 9, and 12 months. There was a rapid and sustained reduction in all biomarkers of exposure after switching to the EHCSS, with statistically significant reductions from baseline in nicotine equivalents (-18%), plasma cotinine (-16%), total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (-73%), total 1-hydroxypyrene (-53%), urine mutagenicity (-52%), 4-aminobiphenyl hemoglobin adducts (-43%), carboxyhemoglobin AUC7-23 h (-80%), and 3-hydroxypropylmercapturic acid (-35%). These reductions in exposure in the EHCSS group were associated with statistically significant and pathophysiologically favorable changes in several cardiovascular risk factors, including white blood cell count (-0.78 x 10(3)/microL), hemoglobin (-0.16 g/dL), hematocrit (-0.44%), urine 11-dehydrothromboxane B2 (-374 ng/24 h), and high-density lipoprotein cholesterol (+5 mg/dL).

Smoking is associated with epicardial coronary endothelial dysfunction and elevated white blood cell count in patients with chest pain and early coronary artery disease

BACKGROUND

Smoking is a major risk factor for cardiovascular events. One of the potential mechanisms may be related to both coronary endothelial dysfunction and increased inflammatory response. The present study was designed to test the hypothesis that smoking is associated with epicardial coronary endothelial dysfunction and inflammation.

METHODS AND RESULTS

Coronary endothelial function in response to acetylcholine was assessed in 881 patients (115 current smokers and 766 nonsmokers, including 314 previous smokers). Smokers were significantly younger than nonsmokers (43+/-1 versus 51+/-1 years, P<0.0001), had more epicardial vasoconstriction in response to intracoronary acetylcholine (-19+/-2% versus -14+/-1% change in coronary artery diameter, P=0.03), and were more likely than nonsmokers to have epicardial endothelial dysfunction (46% versus 35%, P=0.005), but their microvascular endothelial function was intact. Smokers had higher white blood cell counts than nonsmokers (7.7+/-0.2 versus 6.6+/-0.1x10(9)/L, P<0.0001), higher myeloperoxidase (156+/-19 versus 89+/-8 ng/mL), higher lipoprotein-associated phospholipase A2 (242+/-12 versus 215+/-5 ng/mL), and higher levels of intracellular adhesion molecule (283+/-14 versus 252+/-5 ng/mL). There were no differences in the levels of C-reactive protein, fibrinogen, or vascular cell adhesion molecule between the groups.

CONCLUSIONS

Young smokers are characterized by epicardial coronary endothelial dysfunction, preserved microvascular endothelial function, and increased levels of inflammatory biomarkers and oxidative stress. The present study provides further information regarding the potential mechanisms by which smoking contributes to cardiovascular events.

White blood cell count and mortality in the Baltimore Longitudinal Study of Aging

OBJECTIVES

We investigated the secular trend in white blood cell (WBC) count and the relationship between WBC count and mortality between 1958 and 2002.

BACKGROUND

The WBC count is a clinical marker of inflammation and a strong predictor of mortality. Limited data exist on the WBC count secular trend and the relationship between WBC and mortality.

METHODS

One thousand eighty-three women and 1,720 men were evaluated longitudinally in the Baltimore Longitudinal Study of Aging. Blood samples and medical information were collected at the study entry and every 2 years during follow-up visits. The WBC count and all-cause, cardiovascular, and cancer mortality were assessed.

RESULTS

A downward trend in WBC count was observed from 1958 to 2002. The secular downward trend was independent of age, gender, race, smoking, body mass index, and physical activity. The WBC count was nonlinearly associated with all-cause mortality and almost linearly associated with cardiovascular mortality. Participants with baseline WBC <3,500 cells/mm3 and WBC >6,000 cells/mm3 had higher mortality than those with 3,500 to 6,000 WBC/mm3. Within each WBC group, age-adjusted mortality rates declined in successive cohorts from the 1960s to the 1990s. Participants who died had higher WBC than those who survived, and the difference was statistically significant within 5 years before death.

CONCLUSIONS

Our study provides evidence for a secular downward trend in WBC count over the period from 1958 to 2002. Higher WBC counts are associated with higher mortality in successive cohorts. We found no evidence that the decline of age-specific mortality rates that occurred from 1960 to 2000 was attributable to a secular downward trend in WBC.

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.