scholarly journals Study Characteristics Influence the Efficacy of Substance Abuse Treatments: A Meta-analysis of Medications for Smoking Cessation

2018 ◽  
Vol 22 (3) ◽  
pp. 317-323 ◽  
Author(s):  
Elias M Klemperer ◽  
John R Hughes ◽  
Shelly Naud

Abstract Background Understanding study characteristics’ influence on treatment efficacy could improve interpretation of trials’ outcomes. We examined study characteristics as predictors of outcomes in clinical trials of medications for tobacco use. Methods We obtained and analyzed data on 44 trials of nicotine gum, 37 trials of nicotine patch, 27 trials of varenicline, and 43 trials of bupropion from Cochrane reviews. We extracted and analyzed data for 15 study characteristics, odds ratios (ORs), and percent abstinent in control and medication conditions. We used general linear models to determine which study characteristics explained the variability among outcomes after controlling for medication characteristics. Results Study characteristics accounted for 12% of the variance in odds ratios among patch trials, 16% among gum trials, 16% among varenicline trials, and 34% among bupropion trials above and beyond medication characteristics. Patch and gum trials with industry funding had larger odds ratios than those without. Among patch trials, this appeared to be due to less abstinence in industry-funded trials’ control conditions. Bupropion trials published earlier had larger odds ratios, which appeared to be due to less abstinence in control conditions. The reason for study characteristics’ influence on varenicline trials was unclear. Discussion Study characteristics influenced the assessment of treatment efficacy above and beyond medication characteristics in smoking cessation trials. Our findings that study characteristics are associated with higher or lower efficacy does not suggest that the effect size under one versus another condition is the more valid outcome. Future studies are needed to determine which study characteristics reliably influence efficacy because this would help investigators and clinicians interpret trials. Implications Study characteristics influenced the estimates of treatment efficacy but individual characteristics’ influence on efficacy appeared to differ among different medications for smoking cessation. We encourage researchers to report study characteristics to improve interpretation of findings and systematic reviews, and to account for nontreatment-related variables to better estimate the efficacy of treatments.

1985 ◽  
Vol 10 (2) ◽  
pp. 75-98 ◽  
Author(s):  
Stephen W. Raudenbush ◽  
Anthony S. Bryk

As interest in quantitative research synthesis grows, investigators increasingly seek to use information about study features—study contexts, designs, treatments, and subjects—to account for variation in study outcomes. To facilitate analysis of diverse study findings, a mixed linear model with fixed and random effects is presented and illustrated with data from teacher expectancy experiments. This strategy enables the analyst to (a) estimate the variance of the effect size parameters by means of maximum likelihood; (b) pose a series of linear models to explain the effect parameter variance; (c) use information about study characteristics to derive improved empirical Bayes estimates of individual study effect sizes; and (d) examine the sensitivity of all substantive inferences to likely errors in the estimation of variance components.


1995 ◽  
Vol 37 (10) ◽  
pp. 1191
Author(s):  
Michael C. Fiore ◽  
Stevens S. Smith ◽  
Douglas E. Jorenby ◽  
Timothy B. Baker

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