Article

Statistical analysis of daily smoking status in smoking cessation clinical trials

Division of Oncology, The Children's Hospital of Philadelphia and Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA 19104, USA.
Addiction (Impact Factor: 4.6). 06/2011; 106(11):2039-46. DOI: 10.1111/j.1360-0443.2011.03519.x
Source: PubMed

ABSTRACT Smoking cessation trials generally record information on daily smoking behavior, but base analyses on measures of smoking status at the end of treatment (EOT). We present an alternative approach that analyzes the entire sequence of daily smoking status observations.
We analyzed daily abstinence data from a smoking cessation trial, using two longitudinal logistic regression methods: a mixed-effects (ME) model and a generalized estimating equations (GEE) model. We compared results to a standard analysis that takes abstinence status at EOT as outcome. We evaluated time-varying covariates (smoking history and time-varying drug effect) in the longitudinal analysis and compared ME and GEE approaches.
We observed some differences in the estimated treatment effect odds ratios across models, with narrower confidence intervals under the longitudinal models. GEE yields similar results to ME when only baseline factors appear in the model, but gives biased results when one includes time-varying covariates. The longitudinal models indicate that the quit probability declines and the drug effect varies over time. Both the previous day's smoking status and recent smoking history predict quit probability, independently of the drug effect.
When analysing outcomes of studies from smoking cessation interventions, longitudinal models with multiple outcome data points, rather than just end of treatment, can makes efficient use of the data and incorporate time-varying covariates. The generalized estimating equations approach should be avoided when using time-varying predictors.

Download full-text

Full-text

Available from: Yimei Li, Aug 13, 2015
0 Followers
 · 
134 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The present trial examined the effectiveness of brief interventions for smokers who joined the Hong Kong Quit to Win Contest to quit smoking. A block randomized controlled trial allocated 1003 adult daily smokers to three groups: (i) The TEL group (n = 338) received a 5-min nurse-led telephone counselling; (ii) The SMS group (n = 335) received eight text messages through mobile phone and (iii) The CONTROL group (n = 330) did not receive the above interventions. Participants with biochemically verified abstinence at 6-month follow-up could receive cash incentive. The primary outcome was the self-reported 7-day point prevalence (PP) of tobacco abstinence at 6-month follow-up. The abstinence rate in the TEL, SMS and CONTROL group was 22.2, 20.6 and 20.3%, respectively (P for TEL versus CONTROL = 0.32; P for SMS versus CONTROL = 0.40). When abstinence at 2-, 6- and 12-month follow-up was modelled simultaneously, the TEL group had a higher abstinence than the CONTROL group (Adjusted OR = 1.38, 95% CI = 1.01-1.88, P = 0 .04). In the Quit to Win Contest, the brief telephone counselling might have increased abstinence, but the text messages had no significant effect. Further studies on intensive intervention and interactive messaging services are warranted. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.
    Health Education Research 06/2015; 30(4). DOI:10.1093/her/cyv023 · 1.66 Impact Factor