Effectiveness of regular reporting of spirometric results combined with a smoking cessation advice by a primary care physician on smoking quit rate in adult smokers: a randomized controlled trial. ESPIROTAB study

Spirometry and Smoking Cessation in Primary Care: The ESPIROTAB STUDY, A Randomized Clinical Trial

This study aims to evaluate the effect of regularly reporting spirometry results during smoking cessation counseling from a primary care physician on the quit rate in adult smokers.

METHODS

A randomized, two-arm intervention study was conducted at six primary care centers. A total of 350 smokers, ≥18 years of age, who consulted their primary care physician, participated in the study. At the selection visit, smokers who gave their consent to participate underwent spirometry. Subsequently, an appointment (visit 0) was scheduled to complete a nicotine dependence test, a smoking cessation motivation questionnaire, and a sociodemographic questionnaire. Participants were also offered brief, structured advice on how to quit smoking, as well as detailed information on spirometry results. Patients were then randomized and scheduled for follow-up visits at 3, 6, 12, and 24 months. Both arms received brief, structured advice and detailed information on spirometry results at visit 0. At consecutive follow-up visits, the control group only received brief, structured smoking cessation advice, while the intervention group also received information on initial spirometry results at visits 3 and 6, and a spirometry retest at visit 12. Exhaled carbon monoxide testing was used to check smoking cessation.

RESULTS

The study included 350 smokers; 179 were assigned to the control group and 171 to the intervention group. Smoking cessation at one year was 24.0% in the intervention group compared to 16.2% in the control group. At two years, it was 25.2% in the intervention group and 18.4% in the control group. Overall, the adjusted odds of quitting smoking in the intervention group were 42% higher than in the control group (p = 0.018).

CONCLUSIONS

Regular and detailed feedback of spirometry results with smokers increases smoking cessation. Specifically, the likelihood of quitting smoking in the intervention group is 1.42 times higher than in the control group (p = 0.018).

Strategies to improve smoking cessation rates in primary care

BACKGROUND

Primary care is an important setting in which to treat tobacco addiction. However, the rates at which providers address smoking cessation and the success of that support vary. Strategies can be implemented to improve and increase the delivery of smoking cessation support (e.g. through provider training), and to increase the amount and breadth of support given to people who smoke (e.g. through additional counseling or tailored printed materials).

OBJECTIVES

To assess the effectiveness of strategies intended to increase the success of smoking cessation interventions in primary care settings. To assess whether any effect that these interventions have on smoking cessation may be due to increased implementation by healthcare providers.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group's Specialized Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and trial registries to 10 September 2020.

SELECTION CRITERIA

We included randomized controlled trials (RCTs) and cluster-RCTs (cRCTs) carried out in primary care, including non-pregnant adults. Studies investigated a strategy or strategies to improve the implementation or success of smoking cessation treatment in primary care. These strategies could include interventions designed to increase or enhance the quality of existing support, or smoking cessation interventions offered in addition to standard care (adjunctive interventions). Intervention strategies had to be tested in addition to and in comparison with standard care, or in addition to other active intervention strategies if the effect of an individual strategy could be isolated. Standard care typically incorporates physician-delivered brief behavioral support, and an offer of smoking cessation medication, but differs across studies. Studies had to measure smoking abstinence at six months' follow-up or longer.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods. Our primary outcome - smoking abstinence - was measured using the most rigorous intention-to-treat definition available. We also extracted outcome data for quit attempts, and the following markers of healthcare provider performance: asking about smoking status; advising on cessation; assessment of participant readiness to quit; assisting with cessation; arranging follow-up for smoking participants. Where more than one study investigated the same strategy or set of strategies, and measured the same outcome, we conducted meta-analyses using Mantel-Haenszel random-effects methods to generate pooled risk ratios (RRs) and 95% confidence intervals (CIs).

MAIN RESULTS

We included 81 RCTs and cRCTs, involving 112,159 participants. Fourteen were rated at low risk of bias, 44 at high risk, and the remainder at unclear risk. We identified moderate-certainty evidence, limited by inconsistency, that the provision of adjunctive counseling by a health professional other than the physician (RR 1.31, 95% CI 1.10 to 1.55; I2 = 44%; 22 studies, 18,150 participants), and provision of cost-free medications (RR 1.36, 95% CI 1.05 to 1.76; I2 = 63%; 10 studies,7560 participants) increased smoking quit rates in primary care. There was also moderate-certainty evidence, limited by risk of bias, that the addition of tailored print materials to standard smoking cessation treatment increased the number of people who had successfully stopped smoking at six months' follow-up or more (RR 1.29, 95% CI 1.04 to 1.59; I2 = 37%; 6 studies, 15,978 participants). There was no clear evidence that providing participants who smoked with biomedical risk feedback increased their likelihood of quitting (RR 1.07, 95% CI 0.81 to 1.41; I2 = 40%; 7 studies, 3491 participants), or that provider smoking cessation training (RR 1.10, 95% CI 0.85 to 1.41; I2 = 66%; 7 studies, 13,685 participants) or provider incentives (RR 1.14, 95% CI 0.97 to 1.34; I2 = 0%; 2 studies, 2454 participants) increased smoking abstinence rates. However, in assessing the former two strategies we judged the evidence to be of low certainty and in assessing the latter strategies it was of very low certainty. We downgraded the evidence due to imprecision, inconsistency and risk of bias across these comparisons. There was some indication that provider training increased the delivery of smoking cessation support, along with the provision of adjunctive counseling and cost-free medications. However, our secondary outcomes were not measured consistently, and in many cases analyses were subject to substantial statistical heterogeneity, imprecision, or both, making it difficult to draw conclusions. Thirty-four studies investigated multicomponent interventions to improve smoking cessation rates. There was substantial variation in the combinations of strategies tested, and the resulting individual study effect estimates, precluding meta-analyses in most cases. Meta-analyses provided some evidence that adjunctive counseling combined with either cost-free medications or provider training enhanced quit rates when compared with standard care alone. However, analyses were limited by small numbers of events, high statistical heterogeneity, and studies at high risk of bias. Analyses looking at the effects of combining provider training with flow sheets to aid physician decision-making, and with outreach facilitation, found no clear evidence that these combinations increased quit rates; however, analyses were limited by imprecision, and there was some indication that these approaches did improve some forms of provider implementation.

AUTHORS' CONCLUSIONS

There is moderate-certainty evidence that providing adjunctive counseling by an allied health professional, cost-free smoking cessation medications, and tailored printed materials as part of smoking cessation support in primary care can increase the number of people who achieve smoking cessation. There is no clear evidence that providing participants with biomedical risk feedback, or primary care providers with training or incentives to provide smoking cessation support enhance quit rates. However, we rated this evidence as of low or very low certainty, and so conclusions are likely to change as further evidence becomes available. Most of the studies in this review evaluated smoking cessation interventions that had already been extensively tested in the general population. Further studies should assess strategies designed to optimize the delivery of those interventions already known to be effective within the primary care setting. Such studies should be cluster-randomized to account for the implications of implementation in this particular setting. Due to substantial variation between studies in this review, identifying optimal characteristics of multicomponent interventions to improve the delivery of smoking cessation treatment was challenging. Future research could use component network meta-analysis to investigate this further.

[The prevalence of strategies for cessation of tobacco use in primary health care: an integrative review]

The habit of tobacco use/smoking, which is a major concern of Primary Health Care (PHC), is a serious public health problem and the main avoidable cause of death in the world. The relevance of actions, whose focus is to facilitate the cessation of this habit, motivates the discussion of studies that have different approaches to tackle this issue by seeking to train PHC professionals accordingly. A search was conducted in the Lilacs, MEDLINE and Web of Science databases for recent scientific publications (2010-2015). The key words were combined with Boolean operators and, after analysis of the articles found, 75 are discussed in this article since they have strategies with a higher prevalence in PHC. The conclusion drawn is that the brief or intense individual approach using the 5A method (Transtheoretical Model) is the most widely adopted, as well as bupropion and nicotine replacement patches. The increasing use of hard technology requires new studies that examine their impact on the treatment of smokers. It was clearly revealed that there is a need for health professionals to be better prepared to address the issue with the users, in addition to a lack of stimulus and proper conditions to work in the PHC team directly reflecting scientific advances in clinical practice.

Spirometry to increase smoking cessation rate: A systematic review

INTRODUCTION

Addressing tobacco use is an important issue in general health care. In order to improve smoking cessation advice, spirometry values can be displayed to the smoker to demonstrate possible lung function impairment. The estimate of so-called lung age may show a decrease in lung function associated with smoking. It has been suggested that performing spirometry on patients who smoke but are asymptomatic can be a useful way to show the adverse effects of smoking. The aim of this systematic review was to determine if providing spirometry results in combination with smoking cessation counselling can increase smoking cessation rates compared to what is achieved through counselling alone.

METHODS

In this systematic review, we included randomized controlled trials (RCTs) evaluating smoking cessation interventions for adult smokers. The systematic search was performed in PubMed, Medline, Cochrane Library, Cinahl, Embase, Amed and PsycInfo.

RESULTS

The literature search resulted in 946 studies, which, after reading by two independent reviewers, were reduced to seven trials that matched the inclusion criteria. Two RCTs showed significant improvement in smoking cessation when giving patients feedback on spirometry results in combination with smoking cessation counselling, compared to patients who received only smoking cessation counselling. In both studies, the spirometry results were expressed as lung age. In the other five studies no difference was found. Five further published study protocols for ongoing RCT studies in the field have been found, and therefore this systematic overview will likely need to be updated within a few years.

CONCLUSIONS

Few studies have been undertaken to examine the efficacy of spirometry in increasing smoking quit rates. Studies conducted to date have shown mixed results, and there is currently limited evidence in the literature that smoking cessation counselling that includes feedback from spirometry and a demonstration of lung age promotes quit rates.

Biomedical risk assessment as an aid for smoking cessation

BACKGROUND

A possible strategy for increasing smoking cessation rates could be to provide smokers with feedback on the current or potential future biomedical effects of smoking using, for example, measurement of exhaled carbon monoxide (CO), lung function, or genetic susceptibility to lung cancer or other diseases.

OBJECTIVES

The main objective was to determine the efficacy of providing smokers with feedback on their exhaled CO measurement, spirometry results, atherosclerotic plaque imaging, and genetic susceptibility to smoking-related diseases in helping them to quit smoking.

SEARCH METHODS

For the most recent update, we searched the Cochrane Tobacco Addiction Group Specialized Register in March 2018 and ClinicalTrials.gov and the WHO ICTRP in September 2018 for studies added since the last update in 2012.

SELECTION CRITERIA

Inclusion criteria for the review were: a randomised controlled trial design; participants being current smokers; interventions based on a biomedical test to increase smoking cessation rates; control groups receiving all other components of intervention; and an outcome of smoking cessation rate at least six months after the start of the intervention.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures expected by Cochrane. We expressed results as a risk ratio (RR) for smoking cessation with 95% confidence intervals (CI). Where appropriate, we pooled studies using a Mantel-Haenszel random-effects method.

MAIN RESULTS

We included 20 trials using a variety of biomedical tests interventions; one trial included two interventions, for a total of 21 interventions. We included a total of 9262 participants, all of whom were adult smokers. All studies included both men and women adult smokers at different stages of change and motivation for smoking cessation. We judged all but three studies to be at high or unclear risk of bias in at least one domain. We pooled trials in three categories according to the type of biofeedback provided: feedback on risk exposure (five studies); feedback on smoking-related disease risk (five studies); and feedback on smoking-related harm (11 studies). There was no evidence of increased cessation rates from feedback on risk exposure, consisting mainly of feedback on CO measurement, in five pooled trials (RR 1.00, 95% CI 0.83 to 1.21; I² = 0%; n = 2368). Feedback on smoking-related disease risk, including four studies testing feedback on genetic markers for cancer risk and one study with feedback on genetic markers for risk of Crohn's disease, did not show a benefit in smoking cessation (RR 0.80, 95% CI 0.63 to 1.01; I² = 0%; n = 2064). Feedback on smoking-related harm, including nine studies testing spirometry with or without feedback on lung age and two studies on feedback on carotid ultrasound, also did not show a benefit (RR 1.26, 95% CI 0.99 to 1.61; I² = 34%; n = 3314). Only one study directly compared multiple forms of measurement with a single form of measurement, and did not detect a significant difference in effect between measurement of CO plus genetic susceptibility to lung cancer and measurement of CO only (RR 0.82, 95% CI 0.43 to 1.56; n = 189).

AUTHORS' CONCLUSIONS

There is little evidence about the effects of biomedical risk assessment as an aid for smoking cessation. The most promising results relate to spirometry and carotid ultrasound, where moderate-certainty evidence, limited by imprecision and risk of bias, did not detect a statistically significant benefit, but confidence intervals very narrowly missed one, and the point estimate favoured the intervention. A sensitivity analysis removing those studies at high risk of bias did detect a benefit. Moderate-certainty evidence limited by risk of bias did not detect an effect of feedback on smoking exposure by CO monitoring. Low-certainty evidence, limited by risk of bias and imprecision, did not detect a benefit from feedback on smoking-related risk by genetic marker testing. There is insufficient evidence with which to evaluate the hypothesis that multiple types of assessment are more effective than single forms of assessment.

The impact of lung function case-finding tests on smoking behaviour: A nested randomised trial within a case-finding cohort

RATIONALE AIMS AND OBJECTIVES

Increasing awareness of people's lung health through the use of lung function tests or symptom-based questionnaires is a potential method to aid smoking cessation. We investigated the impact of case-finding lung function tests for chronic obstructive pulmonary disease on smoking behaviour.

METHODS

Our trial used a novel waiting list randomised controlled trial design, nested within a case-finding cohort study. The cohort comprised current smokers aged 35 years or more, from general practices in Yorkshire and Humberside, who were randomised to receive lung function tests (spirometry, microspirometry, peak flow meter measurement, and a WheezoMeter) and case-finding questionnaires either immediately ("tests now") or later ("waiting list" control). Outcome measures included self-reported smoking cessation and number of cigarettes smoked at follow-up (at 2, 3, or 6 months after randomisation, depending on study site), with 409 participants included in the primary analysis.

RESULTS

Six hundred seventy-four participants were randomised using stratified block randomisation to the 2 groups (340 to "tests now" and 334 to "waiting list"), with 409 included in the primary analysis (194 in "tests now" and 215 in "waiting list" groups). Smoking cessation at follow-up was very similar across groups (8.8% in the "tests now" group, compared with 9.2% in the "waiting list" group). Completing case-finding lung function tests did not significantly impact smoking cessation (OR 1.00, 95% CI, 0.57-1.77, adjusting for age, sex, baseline number of cigarettes smoked, and study site). A sensitivity analysis, assuming that participants with missing data were still smoking, gave similar results (OR 0.86, 95% CI, 0.47-1.56). Analysis of the number of cigarettes smoked at follow-up using negative binomial regression adjusting for the same factors above gave an incidence rate ratio of 0.95 (95% CI, 0.88-1.03).

CONCLUSIONS

There is no evidence from this trial of an effect of lung function tests on smoking cessation among a population of smokers aged 35 years or over. Indeed, when assuming that those with missing data were smokers, a slightly lower odds of smoking cessation was observed in the "test now" group compared with the "waiting list" group.

Effectiveness of advice from physician and nurse on smoking cessation stage in Taiwanese male smokers attending a community-based integrated screening program

BACKGROUND

A screening program provides a teachable moment for primary prevention such as encouraging smoking cessation. However, little is known about the efficacy of smoking cessation intervention delivered to the general population through a community-based screening program.

METHODS

A quasi-experimental untreated control design with pre-test and post-test was conducted with 42 subjects receiving advice from physician and nurses (the PNA group), 39 receiving an informational leaflet (the leaflet group), and 308 control subjects.

RESULTS

The overall rate of reaching the action stage was 25 %, 5.7 %, and 7.8 in the PNA group, the leaflet group, and the control group, respectively. In approximately 45-60 % of all participants, the stage remained unchanged. Such an association between the intervention groups and stage changes was statistically significant (p = 0.02). The PNA group was more likely to have the improvement of stage (forward transition toward action stage) than the control group [adjusted odds ratio (aOR) = 2.27 (1.07-4.84)]. Deterioration (backward transition toward precontemplation) in the PNA intervention group was 37 % lower than that in the control group [aOR = 0.63 (0.20-2.01)].

CONCLUSIONS

This study demonstrated that smoking cessation advice from physician and nurse is conducive to smoking cessation, as shown by greater movement toward and less movement away from smoking cessation through a community-based integrated screening platform.

Multicentric randomized clinical trial to evaluate the long-term effectiveness of a motivational intervention against smoking, based on the information obtained from spirometry in primary care: the RESET study protocol

Background

Spirometry is the recommended method of evaluating pulmonary function when respiratory disease is suspected in smokers. Nonetheless, no evidence exists of the usefulness of information obtained from this test as a motivational strategy for smoking cessation. The primary objective of this study is to evaluate the effectiveness of a motivational intervention based on spirometry results in achieving long-term smoking cessation.

Methods/Design

We propose a multicenter randomized clinical trial in the primary care setting. Study subjects: We will recruit active smokers of both sexes, aged 35-70 years, with a cumulated smoking habit exceeding 10 packs/year and who consult for any reason with their primary care physician in the 20 health centers in the province of Tarragona (Spain). Patients with a history of lung disease or who have undergone exploratory measures of pulmonary function in the preceding 12 months will be excluded. All patients who agree to participate will provide signed informed consent prior to their inclusion. A total of 1000 smokers will be consecutively randomized to a control or intervention group (1:1). Intervention: Participants in both groups will receive brief (5-minute) health counseling, in accordance with usual clinical practice. In a consultation lasting about 15 minutes, participants in the intervention group will also receive detailed, personalized information about the results of a spirometry test and about their lung age compared with their chronological age. Both groups will be followed up for 12 months. Main variables and analysis: The main variable will be sustained smoking abstinence at 12 months after the intervention, as confirmed by CO breath testing and urine cotinine test. Results will be analyzed based on intention to treat, using the chi-square test and logistical regression if necessary to adjust for confounding variables.

Discussion

We expect the rate of prolonged smoking abstinence in the intervention group will be at least 5 % higher than in the control group. If this strategy proves effective, it could easily be included in the health promotion activities offered in primary care settings.

Trial registration

ClinicalTrials.gov Identifier: NCT02153047. Registered on 28/05/2014

Physician advice for smoking cessation

BACKGROUND

Healthcare professionals frequently advise people to improve their health by stopping smoking. Such advice may be brief, or part of more intensive interventions.

OBJECTIVES

The aims of this review were to assess the effectiveness of advice from physicians in promoting smoking cessation; to compare minimal interventions by physicians with more intensive interventions; to assess the effectiveness of various aids to advice in promoting smoking cessation, and to determine the effect of anti-smoking advice on disease-specific and all-cause mortality.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group trials register in January 2013 for trials of interventions involving physicians. We also searched Latin American databases through BVS (Virtual Library in Health) in February 2013.

SELECTION CRITERIA

Randomised trials of smoking cessation advice from a medical practitioner in which abstinence was assessed at least six months after advice was first provided.

DATA COLLECTION AND ANALYSIS

We extracted data in duplicate on the setting in which advice was given, type of advice given (minimal or intensive), and whether aids to advice were used, the outcome measures, method of randomisation and completeness of follow-up.The main outcome measure was abstinence from smoking after at least six months follow-up. We also considered the effect of advice on mortality where long-term follow-up data were available. We used the most rigorous definition of abstinence in each trial, and biochemically validated rates where available. People lost to follow-up were counted as smokers. Effects were expressed as relative risks. Where possible, we performed meta-analysis using a Mantel-Haenszel fixed-effect model.

MAIN RESULTS

We identified 42 trials, conducted between 1972 and 2012, including over 31,000 smokers. In some trials, participants were at risk of specified diseases (chest disease, diabetes, ischaemic heart disease), but most were from unselected populations. The most common setting for delivery of advice was primary care. Other settings included hospital wards and outpatient clinics, and industrial clinics.Pooled data from 17 trials of brief advice versus no advice (or usual care) detected a significant increase in the rate of quitting (relative risk (RR) 1.66, 95% confidence interval (CI) 1.42 to 1.94). Amongst 11 trials where the intervention was judged to be more intensive the estimated effect was higher (RR 1.84, 95% CI 1.60 to 2.13) but there was no statistical difference between the intensive and minimal subgroups. Direct comparison of intensive versus minimal advice showed a small advantage of intensive advice (RR 1.37, 95% CI 1.20 to 1.56). Direct comparison also suggested a small benefit of follow-up visits. Only one study determined the effect of smoking advice on mortality. This study found no statistically significant differences in death rates at 20 years follow-up.

AUTHORS' CONCLUSIONS

Simple advice has a small effect on cessation rates. Assuming an unassisted quit rate of 2 to 3%, a brief advice intervention can increase quitting by a further 1 to 3%. Additional components appear to have only a small effect, though there is a small additional benefit of more intensive interventions compared to very brief interventions.

Physician advice for smoking cessation

BACKGROUND

Healthcare professionals frequently advise people to improve their health by stopping smoking. Such advice may be brief, or part of more intensive interventions.

OBJECTIVES

The aims of this review were to assess the effectiveness of advice from physicians in promoting smoking cessation; to compare minimal interventions by physicians with more intensive interventions; to assess the effectiveness of various aids to advice in promoting smoking cessation, and to determine the effect of anti-smoking advice on disease-specific and all-cause mortality.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group trials register in January 2013 for trials of interventions involving physicians. We also searched Latin American databases through BVS (Virtual Library in Health) in February 2013.

SELECTION CRITERIA

Randomised trials of smoking cessation advice from a medical practitioner in which abstinence was assessed at least six months after advice was first provided.

DATA COLLECTION AND ANALYSIS

We extracted data in duplicate on the setting in which advice was given, type of advice given (minimal or intensive), and whether aids to advice were used, the outcome measures, method of randomisation and completeness of follow-up.The main outcome measure was abstinence from smoking after at least six months follow-up. We also considered the effect of advice on mortality where long-term follow-up data were available. We used the most rigorous definition of abstinence in each trial, and biochemically validated rates where available. People lost to follow-up were counted as smokers. Effects were expressed as relative risks. Where possible, we performed meta-analysis using a Mantel-Haenszel fixed-effect model.

MAIN RESULTS

We identified 42 trials, conducted between 1972 and 2012, including over 31,000 smokers. In some trials, participants were at risk of specified diseases (chest disease, diabetes, ischaemic heart disease), but most were from unselected populations. The most common setting for delivery of advice was primary care. Other settings included hospital wards and outpatient clinics, and industrial clinics.Pooled data from 17 trials of brief advice versus no advice (or usual care) detected a significant increase in the rate of quitting (relative risk (RR) 1.66, 95% confidence interval (CI) 1.42 to 1.94). Amongst 11 trials where the intervention was judged to be more intensive the estimated effect was higher (RR 1.84, 95% CI 1.60 to 2.13) but there was no statistical difference between the intensive and minimal subgroups. Direct comparison of intensive versus minimal advice showed a small advantage of intensive advice (RR 1.37, 95% CI 1.20 to 1.56). Direct comparison also suggested a small benefit of follow-up visits. Only one study determined the effect of smoking advice on mortality. This study found no statistically significant differences in death rates at 20 years follow-up.

AUTHORS' CONCLUSIONS

Simple advice has a small effect on cessation rates. Assuming an unassisted quit rate of 2 to 3%, a brief advice intervention can increase quitting by a further 1 to 3%. Additional components appear to have only a small effect, though there is a small additional benefit of more intensive interventions compared to very brief interventions.

Biomedical risk assessment as an aid for smoking cessation

BACKGROUND

A possible strategy for increasing smoking cessation rates could be to provide smokers who have contact with healthcare systems with feedback on the biomedical or potential future effects of smoking, e.g. measurement of exhaled carbon monoxide (CO), lung function, or genetic susceptibility to lung cancer.

OBJECTIVES

To determine the efficacy of biomedical risk assessment provided in addition to various levels of counselling, as a contributing aid to smoking cessation.

SEARCH METHODS

For the most recent update, we searched the Cochrane Collaboration Tobacco Addiction Group Specialized Register in July 2012 for studies added since the last update in 2009.

SELECTION CRITERIA

Inclusion criteria were: a randomized controlled trial design; subjects participating in smoking cessation interventions; interventions based on a biomedical test to increase motivation to quit; control groups receiving all other components of intervention; an outcome of smoking cessation rate at least six months after the start of the intervention.

DATA COLLECTION AND ANALYSIS

Two assessors independently conducted data extraction on each paper, with disagreements resolved by consensus. Results were expressed as a relative risk (RR) for smoking cessation with 95% confidence intervals (CI). Where appropriate, a pooled effect was estimated using a Mantel-Haenszel fixed-effect method.

MAIN RESULTS

We included 15 trials using a variety of biomedical tests. Two pairs of trials had sufficiently similar recruitment, setting and interventions to calculate a pooled effect; there was no evidence that carbon monoxide (CO) measurement in primary care (RR 1.06, 95% CI 0.85 to 1.32) or spirometry in primary care (RR 1.18, 95% CI 0.77 to 1.81) increased cessation rates. We did not pool the other 11 trials due to the presence of substantial clinical heterogeneity. Of the remaining 11 trials, two trials detected statistically significant benefits: one trial in primary care detected a significant benefit of lung age feedback after spirometry (RR 2.12, 95% CI 1.24 to 3.62) and one trial that used ultrasonography of carotid and femoral arteries and photographs of plaques detected a benefit (RR 2.77, 95% CI 1.04 to 7.41) but enrolled a population of light smokers and was judged to be at unclear risk of bias in two domains. Nine further trials did not detect significant effects. One of these tested CO feedback alone and CO combined with genetic susceptibility as two different interventions; none of the three possible comparisons detected significant effects. One trial used CO measurement, one used ultrasonography of carotid arteries and two tested for genetic markers. The four remaining trials used a combination of CO and spirometry feedback in different settings.

AUTHORS' CONCLUSIONS

There is little evidence about the effects of most types of biomedical tests for risk assessment on smoking cessation. Of the fifteen included studies, only two detected a significant effect of the intervention. Spirometry combined with an interpretation of the results in terms of 'lung age' had a significant effect in a single good quality trial but the evidence is not optimal. A trial of carotid plaque screening using ultrasound also detected a significant effect, but a second larger study of a similar feedback mechanism did not detect evidence of an effect. Only two pairs of studies were similar enough in terms of recruitment, setting, and intervention to allow meta-analyses; neither of these found evidence of an effect. Mixed quality evidence does not support the hypothesis that other types of biomedical risk assessment increase smoking cessation in comparison to standard treatment. There is insufficient evidence with which to evaluate the hypothesis that multiple types of assessment are more effective than single forms of assessment.