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 potentialfuture biomedical effects of smoking using, for example, measurement of exhaled carbon monoxide (CO), lung function, or geneticsusceptibility 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, spirometryresults, atherosclerotic plaque imaging, and genetic susceptibility to smoking-related diseases in helping them to quitsmoking. Search methods: For the most recent update, we searched the Cochrane Tobacco Addiction Group Specialized Register in March 2018 and ClinicalTri-als.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 ona biomedical test to increase smoking cessation rates; control groups receiving all other components of intervention; and an outcomeof 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 cessationwith 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 adultsmokers. All studies included both men and women adult smokersat different stages of change and motivation for smoking cessation. We judged all but three studies to be at high or unclear risk of biasin 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 was1Biomedical risk assessment as an aid for smoking cessation (Review)Copyright © 2019 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd. no evidence of increased cessation rates from feedback on risk exposure, consisting mainly of feedback on CO measurement, in fivepooled trials (RR 1.00, 95% CI 0.83 to 1.21; I2= 0%; n = 2368). Feedback on smoking-related disease risk, including four studiestesting feedback on genetic markers for cancer risk and one study with feedback on genetic markers for risk of Crohn’s disease, didnot 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 formsof measurement with a single form of measurement, and did notdetect a significant difference in effect between measurement ofCOplus 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 resultsrelate to spirometry and carotid ultrasound, where moderate-certainty evidence, limited by imprecision and risk of bias, did not detecta 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 limitedby risk ofbias did not detect an effect of feedback on smoking exposure by CO monitoring. Low-certainty evidence, limited by risk of bias andimprecision, did not detect a benefit from feedback on smoking-related risk by genetic marker testing. There is insufficient evidencewith which to evaluate the hypothesis that multiple types of assessment are more effective than single forms of assessment.