Motivating smokers in the hospital pulmonary function laboratory to quit smoking by use of the lung age concept

Short-term effects of announcing spirometric lung-age on smokers' attitudes: results from a Tunisian real-life pilot study

BACKGROUND

To determine the effects of informing smokers of their spirometric lung-age (SLA) on smoking cessation (SC) rates and tobacco consumption.

RESEARCH DESIGN AND METHODS

An interventional study was conducted in real-life through a humanitarian event led by the Red Crescent on 9 January 2022, in Hammam-Sousse (Sousse, Tunisia). The study comprised four steps: i) Medical questionnaire (general questionnaire, Fagerström test for cigarette dependence, SC motivation questionnaire); ii) Measurement of spirometric data; iii) SLA estimation and its announcement to participants; and iv) Self-reported evaluation of smoking behavior three months later through telephonic recall. Smokers were divided into groups (nondependent vs. dependent groups and insufficient/moderate motivation vs. high/very high motivation groups) and categories (ceased smoking, reduced consumption, maintained stable or increased consumption).

RESULTS

Fifty-two smokers were included (94% were males). Three months after the event, i) 9 (17%) smokers ceased smoking, ii) 39 (75%) smokers reduced their daily smoking consumption by 12 ± 8 cigarettes/day, and iii) 4 (8%) smokers maintained stable (n = 3) or increased (n = 1) consumption.

CONCLUSIONS

Informing smokers of their SLA led 92% of them to cease smoking or reduce their consumption. Announcing SLA could be an effective motivational tool and an easy-to-understand concept to help smokers cease their habit.

'Skeletal Age' for mapping the impact of fracture on mortality

Background

Fragility fracture is associated with an increased risk of mortality, but mortality is not part of doctor-patient communication. Here, we introduce a new concept called 'Skeletal Age' as the age of an individual's skeleton resulting from a fragility fracture to convey the combined risk of fracture and fracture-associated mortality for an individual.

Methods

We used the Danish National Hospital Discharge Register which includes the whole-country data of 1,667,339 adults in Denmark born on or before January 1, 1950, who were followed up to December 31, 2016 for incident low-trauma fracture and mortality. Skeletal age is defined as the sum of chronological age and the number of years of life lost (YLL) associated with a fracture. Cox's proportional hazards model was employed to determine the hazard of mortality associated with a specific fracture for a given risk profile, and the hazard was then transformed into YLL using the Gompertz law of mortality.

Results

During the median follow-up period of 16 years, there had been 307,870 fractures and 122,744 post-fracture deaths. A fracture was associated with between 1 and 7 years of life lost, with the loss being greater in men than women. Hip fractures incurred the greatest loss of life years. For instance, a 60-year-old individual with a hip fracture is estimated to have a skeletal age of 66 for men and 65 for women. Skeletal Age was estimated for each age and fracture site stratified by gender.

Conclusions

We propose 'Skeletal Age' as a new metric to assess the impact of a fragility fracture on an individual's life expectancy. This approach will enhance doctor-patient risk communication about the risks associated with osteoporosis.

Funding

National Health and Medical Research Council in Australia and Amgen Competitive Grant Program 2019.

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).

Spirometry as a motivator for smoking cessation among patients attending the smoking cessation clinic of Monastir

BACKGROUND

The choice of spirometry, a biomarker of lung health, as a motivator for smoking cessation is based on its fidelity in emphasizing tobacco adverse effects. Yet, there is a paucity of evidence on its efficacy, and the findings are currently inconclusive. The aim of this study was to determine whether a spirometry and lung age communication has an effect on smoking cessation rates.

METHODOLOGY

We conducted a randomized controlled trial among patients who attended the smoking cessation clinic (SCC) at Fattouma Bourguiba University Hospital in Monastir, from June 2017 to February 2020. Participants were assigned into two groups, a control arm receiving standard program and intervention arm receiving a spirometry and lung age announcement along with usual care. The primary outcomes were the smoking cessation rates after one year of follow-up between the intervention arm and the control arm.

RESULTS

At one-year endpoint, a total of 456 were reachable for assessment, 236 in control group and 220 in spirometry group, which leads to a loss rate equal to 8.8%. One-year smoking cessation rate was higher among the intervention group than among control group (25.5% versus 16.5%), with a considerable statistical significance (p = 0.019). Lung age was significantly higher at paired comparison with chronological age.

CONCLUSION

Smoking cessation is still a challenging procedure with a high risk of relapse, making very valuable any approach that may increase motivation in both unmotivated and motivated smokers. This study is an additional evidence for spirometry and lung age announcement as motivators for smoking cessation.

TRIAL REGISTRATION

Pan African Clinical Trial Registry database ( PACTR202110595729653 ), 06/10/ 2021.

Self-Reported Smoking Status 10-Months After a Single Session Intervention Including an Education Conference About Smoking Harms and Announcement of Spirometric Lung-Age

Background

Studies investigating the effects of announcing spirometric lung-age (SLA) on the smokers' self-reported smoking status reported conflicting results.

Main objective

To evaluate the effects of a single session intervention including an education conference about smoking harms and announcement of SLA on the participants' self-reported smoking status.

Methodology

An interventional study was conducted in a cable factory. The intervention included four steps: PowerPoint presentation about raising smoking hazards awareness; general questionnaire; measurement of the anthropometric and spirometric data, and announcement of SLA; and evaluation of the smokers' self-reported smoking status 10 months later (quitted smoking, decreased consumption; stable consumption, increased consumption).

Results

Thirty-six smokers completed the four steps. Ten months after the intervention, 11.1% of smokers quitted smoking, 52.7% decreased their consumption by 7  ±  4 cigarettes/day, 30.5% kept a stable consumption, and 5.5% increased their consumption by 9  ±  6 cigarettes/day.

Conclusion

Providing an education conference combined with announcing SLA motivated 64% of smokers to quit smoking or to reduce their cigarette consumption.

Comparative Analysis of Three Different Drug Distribution Schemes for Smoking Cessation

OBJECTIVE

This study aimed to compare the success rate of 3 different drug prescription policies: Free drugs with online system prescription, free drugs with doctor's prescription, and drugs paid for by patients with doctor's prescription.

MATERIAL AND METHODS

The effect of 2 different Ministry of Health (MoH) projects with free-of-charge and self-payment pharmacotherapies for smoking cessation were compared. Patients who completed 6 months of pharmacotherapy and follow-up were evaluated. The first period was free-of-charge medication, which was determined by an online system, the following period was the self-payment period, and the third period was free medication, which was prescribed by a doctor. In all the groups, smoking habits in pack years and comorbidities of the patients were recorded, and pulmonary function tests (PFTs) and expiratory carbon dioxide (CO2) measurements were performed. Patients who had an expiratory CO2 level >5 ppm at the control visits were accepted as quitters.

RESULTS

A total of 829 patients with 438 patients in the first free-of-charge period (group 1), 111 in the self-payment period (group 2), and 280 in the second free-of-charge period (group 3) were enrolled in the study. Smoking cessation rates were significantly higher in the self-payment medication group (25%) according to the MoH's free-of-charge project groups. There was no difference in smoking cessation rates between the 2 free-of-charge medication project groups (15% in group 1 and 11% of group 3). Among all the patients, we compared 124 patients who quit smoking with 705 patients who did not. The quitters were older, mostly male, and heavier smokers. In addition, the number of patients with chronic obstructive pulmonary disease and obstructive PFT rates were higher among the quitters. Their dependency score, PFTs, and the use of free medication was lower, and treatment duration was longer. Independent factors that increased smoking cessation success were longer treatment duration, lower dependency score, and self-payment of medication.

CONCLUSION

Free medications provided via 2 different modalities did not increase the smoking cessation success. Paying for the medication, lower dependency score, and longer treatment duration increased smoking cessation success independently.

Chronic obstructive pulmonary disease in severe mental illness: A timely diagnosis to advance the process of quitting smoking

Background

This study has two main objectives: to describe the prevalence of undetected chronic obstructive pulmonary disease (COPD) in a clinical sample of smokers with severe mental illness (SMI), and to assess the value of the Tobacco Intensive Motivational Estimated Risk tool, which informs smokers of their respiratory risk and uses brief text messages to reinforce intervention.

Method

A multicenter, randomized, open-label, and active-controlled clinical trial, with a 12-month follow-up. Outpatients with schizophrenia (SZ) and bipolar disorder were randomized either to the experimental group—studied by spirometry and informed of their calculated lung age and degree of obstruction (if any)—or to the active control group, who followed the 5 A’s intervention.

Results

The study sample consisted of 160 patients (71.9% SZ), 78.1% of whom completed the 12-month follow-up. Of the patients who completed the spirometry test, 23.9% showed evidence of COPD (77.8% in moderate or severe stages). TIMER was associated with a significant reduction in tobacco use at week 12 and in the long term, 21.9% of patients reduced consumption and 14.6% at least halved it. At week 48, six patients (7.3%) allocated to the experimental group achieved the seven-day smoking abstinence confirmed by CO (primary outcome in terms of efficacy), compared to three (3.8%) in the control group.

Conclusion

In this clinical pilot trial, one in four outpatients with an SMI who smoked had undiagnosed COPD. An intensive intervention tool favors the early detection of COPD and maintains its efficacy to quit smoking, compared with the standard 5 A’s intervention.

How effective are 'age' tools at changing patient behaviour? A rapid review

BACKGROUND

A common form of risk communication is to relay the relative risk (%) of an adverse outcome based on surrogate markers associated with the outcome. A novel way of communicating risk is through 'effective age' of a person or specific organ. These tools can be used to change patient behaviour.

OBJECTIVE

To determine the effect of 'effective age' tools on patient behaviour as compared with more traditional methods of risk communication.

STUDY SELECTION

We performed a search of the PubMed database up to February 2019 for systematic reviews and randomised controlled trials (RCT) that answered our question. Interventions were 'effective age' tools, comparators were usual care or alternative risk communication tools. Primary outcomes were behavioural change measures.

FINDINGS

We included 1 overview of systematic reviews (level 1 evidence), 2 systematic reviews (level 1 evidence) and 13 RCTs (level 2 evidence). Both systematic reviews concluded the evidence base was not conclusive enough to make specific recommendations.Age tools assessed in the 13 RCTs were: 'lung age' (n=5), 'heart age' (n=3), 'health age' (n=2), 'cardiovascular age' (n=1), 'body age' (n=1) and 'net present value' (n=1). 7/13 (54%) RCTs demonstrated a clinical effect on behaviour change favouring the 'age' tool; 2/13 (15%) demonstrated a null effect; 4/13 (31%) favoured control.

CONCLUSIONS

Our findings indicate that systematic review evidence needs updating. The evidence from RCTs on the effect of using age metrics on patient behaviour is poor. There is a need for high-quality trials to decrease uncertainty in the available evidence.

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.

How old are you, really? Communicating chronic risk through 'effective age' of your body and organs

In communicating chronic risks, there is increasing use of a metaphor that can be termed ‘effective-age’: the age of a ‘healthy’ person who has the same risk profile as the individual in question. Popular measures include ‘real-age’, ‘heart-age’, ‘lung-age’ and so on.

Here we formally define this concept, and illustrate its use in a variety of areas. We explore conditions under which the years lost or gained that are associated with exposure to risk factors depends neither on current chronological age, nor the period over which the risk is defined. These conditions generally hold for all-cause adult mortality, which enables a simple and vivid translation from hazard-ratios to years lost or gained off chronological age. Finally we consider the attractiveness and impact of this concept.

Under reasonable assumptions, the risks associated with specific behaviours can be expressed in terms of years gained or lost off your effective age. The idea of effective age appears a useful and attractive metaphor to vividly communicate risks to individuals.

The effect of motivational lung age feedback on short-term quit rates in smokers seeking intensive group treatment: A randomized controlled pilot study

BACKGROUND

A brief "Lung Age" feedback intervention has shown promise for personalizing the health impact of smoking and promoting cessation in unselected smokers. Now that many healthcare organizations provide face-to-face cessation services, it is reasonable to ask whether such motivational feedback of lung function tests might improve treatment compliance and cessation rates in smokers wanting to quit. This study assessed effects of baseline motivational spirometry-based "Lung Age" feedback on treatment compliance and tobacco abstinence at 28-day follow-up.

METHODS

This randomized controlled pilot study took place in Penn State University-affiliated outpatient medical practices. Participants were 225 adult smokers (≥5 cigarettes/day) willing to attend tobacco dependence treatment. At assessment lung function (FEV-1) and exhaled carbon-monoxide (CO) were assessed. The Intervention group (n=120) were randomly allocated to receive motivational "Lung Age" feedback estimated by FEV-1 and on exhaled CO; Control group (n=105) received minimal feedback. Participants were offered 6 weekly group smoking cessation sessions and nicotine patches and followed-up 28 days after target quit date. The primary outcome measure was self-reported 7-day tobacco abstinence, confirmed by CO<10ppm at 28-day follow-up.

RESULTS

Quit rates were similar at follow-up (Intervention 50.8%; Control 52.4%; p=0.65) after controlling for abstinence predictors. Group attendance and patch use were similar. Among those attending follow-up (n=164, 73%), a greater proportion of the Intervention group had improved lung function (67% vs. 46%; p=0.0083).

CONCLUSIONS

Baseline Lung Age feedback did not improve quit rates or compliance at 28-day follow-up in smokers seeking intensive treatment.

Primary care providers' views on using lung age as an aid to smoking cessation counseling for patients with chronic obstructive pulmonary disease

PURPOSE

Smoking cessation is the primary goal for managing patients with chronic obstructive pulmonary disease (COPD) who smoke. However, previous studies have demonstrated poor cessation rates. The "lung age" concept (an estimate of the age at which the FEV(1) would be considered normal) was developed to present spirometry data in an understandable format and to serve as a tool to encourage smokers to quit. Primary care physicians' (PCPs) views of using lung age to help COPD patients to quit smoking were assessed.

METHODS

Post-intervention interviews were conducted with PCPs in the U.S. who participated in the randomized clinical trial, "Translating the GOLD COPD Guidelines into Primary Care Practice."

RESULTS

29 physicians completed the interview. Themes identified during interviews included: general usefulness of lung age for smoking cessation counseling, ease of understanding the concept, impact on patients' thoughts of quitting smoking, and comparison to FEV(1). Most providers found lung age easy to communicate. Moreover, some found the tool to be less judgmental for smoking cessation and others remarked on the merits of having a simple, tangible number to discuss with their patients. However, some expressed doubt over the long-term benefits of lung age and several others thought that there might be a potential backfire for healthy smokers if their lung age was ≤ to their chronological age.

CONCLUSIONS

This study suggests that lung age was well received by the majority of PCPs and appears feasible to use with COPD patients who smoke. However, further investigation in needed to explore COPD patients' perspectives of obtaining their lung age to help motivate them to quit in randomized clinical trials.

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.