Evidence map›Paper›PMID 36212737›Full record

ArticleTobacco induced diseases2022

Identification of smoking cessation phenotypes as a basis for individualized counseling: An explorative real-world cohort study.

Maciej Paciorkowski, Florent Baty, Susanne Pohle, Esther Bürki, Martin Brutsche

Open access · goldAbstract read
In one paragraph

Article in Tobacco induced diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 83% 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Maciej PaciorkowskiLung Center, Cantonal Hospital St. Gallen, St. Gallen, Switzerland.
Florent BatyLung Center, Cantonal Hospital St. Gallen, St. Gallen, Switzerland.
Susanne PohleLung Center, Cantonal Hospital St. Gallen, St. Gallen, Switzerland.
Esther BürkiLung Center, Cantonal Hospital St. Gallen, St. Gallen, Switzerland.
Martin BrutscheLung Center, Cantonal Hospital St. Gallen, St. Gallen, Switzerland.
Kantonsspital St. Gallen · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe rate of relapse in smokers attempting to quit is generally high. In order to maximize the chances of success, it is of interest to better understand the dynamic of lapse and relapse during smoking cessation. We hypothesized that specific behavioral patterns in tobacco consumption could predict the probability of quitting success and could open the possibility for a more targeted approach. The aim of the current study was to characterize clusters of quitting trajectories among participants involved in a smoking cessation program.

methodsIn a retrospective real-world cohort study, data from 843 consecutive participants between March 2012 and December 2014 were collected. Data consisted of baseline information on demographics, smoking history and dependence level, as well as longitudinal data about tobacco consumption. The correlations among time series were characterized using principal coordinates analysis. Clusters were identified using

resultsFour distinct clusters of transition phenotypes were identified based on tobacco consumption during the cessation phase: the long-term quitters (30%), the persistent smokers/reducers (44%), the short-term returners (16%) and the repeated try and failers (10%). Significant between-cluster differences were found in terms of baseline characteristics and smoking behavior during follow-up.

conclusionsMeaningful clusters of quitting trajectories could be identified. Such specific behavioral patterns were useful for the application of personalized assistance needed to achieve successful and long-term cessation.

Indexed as

clustersindividualized treatmentpersonasprincipal coordinates analysissmoking cessation

Identifiers

PMID36212737
PMCPMC9502004
OpenAlexW4296836455

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.