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.


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


METHODS
We systematically searched the Cochrane Collaboration Tobacco Addiction Group Specialized Register, Cochrane Central Register of Controlled Trials 2008 Issue 4, MEDLINE (1966 to January 2009), and EMBASE (1980 to January 2009). We combined methodological terms with terms related to smoking cessation counselling and biomedical measurements.


METHODS
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.


METHODS
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.


RESULTS
We included eleven 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 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 seven trials. 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). 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. Five trials failed to detect evidence of a significant effect. One of these tested CO feedback alone and CO + genetic susceptibility as two different intervention; none of the three possible comparisons detected significant effects. Three others used a combination of CO and spirometry feedback in different settings, and one tested for a genetic marker.


CONCLUSIONS
There is little evidence about the effects of most types of biomedical tests for risk assessment. Spirometry combined with an interpretation of the results in terms of 'lung age' had a significant effect in a single good quality trial. Mixed quality evidence does not support the hypothesis that other types of biomedical risk assessment increase smoking cessation in comparison to standard treatment. Only two pairs of studies were similar enough in term of recruitment, setting, and intervention to allow meta-analysis.
Department of Ambulatory Care and Community Medicine & Clinical Epidemiology Centre, University of Lausanne, Bugnon 44, Lausanne, Switzerland, CH-1011. raphael.bize@hospvd.ch
Raphaël
R
Bize
Bernard
B
Burnand
Yolanda
Y
Mueller
Myriam
M
Rège Walther
Jacques
J
Cornuz
D001676:Biofeedback, Psychology / Q000379:methods*; D001944:Breath Tests; D002248:Carbon Monoxide / Q000032:analysis; D020022:Genetic Predisposition to Disease; D006801:Humans; D016032:Randomized Controlled Trials as Topic; D018570:Risk Assessment; D012907:Smoking / Q000009:adverse effects* / Q000378:metabolism; D016540:Smoking Cessation / Q000379:methods / Q000523:psychology* / Q000706:statistics & numerical data; D013147:Spirometry
D002248:Carbon Monoxide