Evidence map›Paper›PMID 23235615›Full record

SynthesisThe Cochrane database of systematic reviews2012

Biomedical risk assessment as an aid for smoking cessation.

Raphaël Bize, Bernard Burnand, Yolanda Mueller, Myriam Rège-Walther, Jean-Yves Camain, Jacques Cornuz

Registry-linked trialOpen access · greenAbstract readMeta-AnalysisSystematic Review
PubMed Publisher
In one paragraph

Synthesis in The Cochrane database of systematic reviews, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04132232 (Smoking Reduction In Gravid Women With Substance Use Disorders), which is not on this map. Cited by 36 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 8 pooled it
9.3field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04132232 nacompletednot on this mapstarted 2021, after this paper: background citation

Smoking Reduction In Gravid Women With Substance Use Disorders (SIGS): A Randomized Controlled Trial

TypeinterventionalSponsorUniversity of Alabama at BirminghamRan2021 to 2023Enrolled74ConditionsTobacco Smoking in Mother Complicating Pregnancy, Tobacco Use Disorder, Tobacco SmokingArmsknowledge of expired maternal carbon monoxide and fetal carboxyhemoglobin levels
3 · Its place in the literature

Who cites it

36 citing papers in PubMed, 8 syntheses or guidelines pooled it, 181 citations in OpenAlex.

  1. Biomedical risk assessment as an aid for smoking cessation.The Cochrane database of systematic reviews · 2019
    Pooled it
  2. Pooled it
  3. Nursing interventions for smoking cessation.The Cochrane database of systematic reviews · 2017
    Pooled it
  4. Can Communicating Personalised Disease Risk Promote Healthy Behaviour Change? A Systematic Review of Systematic Reviews.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2017
    Pooled it
  5. Pooled it
  6. Pooled it
  7. Pooled it
  8. Physician advice for smoking cessation.The Cochrane database of systematic reviews · 2013
    Pooled it
  9. Trial
  10. Trial
  11. Predictors of Smoking Cessation Among College Students in a Pragmatic Randomized Controlled Trial.Prevention science : the official journal of the Society for Prevention Research · 2019
    Trial
  12. Trial
  13. Trial
  14. Trial
  15. Trial
  16. Digitalizing Specialist Smoking Cessation Support in Pregnancy: Views of Pregnant Smokers.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2025
    Article
  17. Article
  18. Article
  19. Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Raphaël BizeInstitute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland. raphael.bize@chuv.ch.
Bernard Burnand
Yolanda Mueller
Myriam Rège-Walther
Jean-Yves Camain
Jacques Cornuz
Institute of Social and Preventive Medicine · CHUniversity of Lausanne · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA 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.

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

methodsFor 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

resultsWe 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'

conclusionsThere 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.

Indexed as

Biofeedback, PsychologyBreath TestsCarbon MonoxideGenetic Predisposition to DiseaseHumansRandomized Controlled Trials as TopicRisk AssessmentSmokingSmoking CessationSpirometryCarbon Monoxide

Identifiers

PMID23235615
OpenAlexW1527003992

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.