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The use of standard protocols in studies supports consistent data collection, improves data quality, and facilitates cross-study analyses. Funded by the National Institutes of Health, the PhenX (consensus measures for Phenotypes and eXposures) Toolkit is a catalog of recommended measurement protocols that address a wide range of research topics and are suitable for inclusion in a variety of study designs. In 2020, a PhenX Working Group of smoking cessation experts followed a well-established consensus process to identify and recommend measurement protocols suitable for inclusion in smoking cessation and smoking harm reduction studies. The broader scientific community was invited to review and provide feedback on the preliminary recommendation of the Working Group. Fourteen selected protocols for measuring smoking cessation, harm reduction, and biomarkers research associated with smoking cessation were released in the PhenX Toolkit ( https://www.phenxtoolkit.org) in February 2021. These protocols complement existing PhenX Toolkit content related to tobacco regulatory research, substance use and addiction research, and other measures of smoking-related health outcomes. Adopting well-established protocols enables consistent data collection and facilitates comparing and combining data across studies, potentially increasing the scientific impact of individual studies.

IntroductionAvailable evidence is mixed concerning associations between smoking status and COVID-19 clinical outcomes. Effects of nicotine replacement therapy (NRT) and vaccination status on COVID-19 outcomes in smokers are unknown.MethodsElectronic health record data from 104 590 COVID-19 patients hospitalized February 1, 2020 to September 30, 2021 in 21 U.S. health systems were analyzed to assess associations of smoking status, in-hospital NRT prescription, and vaccination status with in-hospital death and ICU admission.ResultsCurrent (n = 7764) and never smokers (n = 57 454) did not differ on outcomes after adjustment for age, sex, race, ethnicity, insurance, body mass index, and comorbidities. Former (vs never) smokers (n = 33 101) had higher adjusted odds of death (aOR, 1.11; 95% CI, 1.06-1.17) and ICU admission (aOR, 1.07; 95% CI, 1.04-1.11). Among current smokers, NRT prescription was associated with reduced mortality (aOR, 0.64; 95% CI, 0.50-0.82). Vaccination effects were significantly moderated by smoking status; vaccination was more strongly associated with reduced mortality among current (aOR, 0.29; 95% CI, 0.16-0.66) and former smokers (aOR, 0.47; 95% CI, 0.39-0.57) than for never smokers (aOR, 0.67; 95% CI, 0.57, 0.79). Vaccination was associated with reduced ICU admission more strongly among former (aOR, 0.74; 95% CI, 0.66-0.83) than never smokers (aOR, 0.87; 95% CI, 0.79-0.97).ConclusionsFormer but not current smokers hospitalized with COVID-19 are at higher risk for severe outcomes. SARS-CoV-2 vaccination is associated with better hospital outcomes in COVID-19 patients, especially current and former smokers. NRT during COVID-19 hospitalization may reduce mortality for current smokers.ImplicationsPrior findings regarding associations between smoking and severe COVID-19 disease outcomes have been inconsistent. This large cohort study suggests potential beneficial effects of nicotine replacement therapy on COVID-19 outcomes in current smokers and outsized benefits of SARS-CoV-2 vaccination in current and former smokers. Such findings may influence clinical practice and prevention efforts and motivate additional research that explores mechanisms for these effects.

BackgroundThere is mixed evidence about the relations of current versus past cancer with severe COVID-19 outcomes and how they vary by patient and cancer characteristics.MethodsElectronic health record data of 104,590 adult hospitalized patients with COVID-19 were obtained from 21 United States health systems from February 2020 through September 2021. In-hospital mortality and ICU admission were predicted from current and past cancer diagnoses. Moderation by patient characteristics, vaccination status, cancer type, and year of the pandemic was examined.Results6.8% of the patients had current (n = 7,141) and 6.5% had past (n = 6,749) cancer diagnoses. Current cancer predicted both severe outcomes but past cancer did not; adjusted odds ratios (aOR) for mortality were 1.58 [95% confidence interval (CI), 1.46-1.70] and 1.04 (95% CI, 0.96-1.13), respectively. Mortality rates decreased over the pandemic but the incremental risk of current cancer persisted, with the increment being larger among younger vs. older patients. Prior COVID-19 vaccination reduced mortality generally and among those with current cancer (aOR, 0.69; 95% CI, 0.53-0.90).ConclusionsCurrent cancer, especially among younger patients, posed a substantially increased risk for death and ICU admission among patients with COVID-19; prior COVID-19 vaccination mitigated the risk associated with current cancer. Past history of cancer was not associated with higher risks for severe COVID-19 outcomes for most cancer types.ImpactThis study clarifies the characteristics that modify the risk associated with cancer on severe COVID-19 outcomes across the first 20 months of the COVID-19 pandemic. See related commentary by Egan et al., p. 3.

Objective: The aim of this study was to examine dependence on combustible and e-cigarettes among users of both products (dual users), which may provide important insights into long-term use patterns. Method: Dual users (smoking daily for 3 months, using e-cigarettes at least once/week for the past month; N = 256; 45% women, 71% White, M age 39.0 years) not interested in quitting either product participated in a longitudinal, 2-year, observational study. At baseline, participants completed measures of combustible and e-cigarette dependence (Fagerström Test of Cigarette Dependence [FTCD], e-FTCD, Wisconsin Inventory of Smoking Dependence Motives [WISDM], e-WISDM, Penn State Cigarette Dependence Index, and Penn State E-Cigarette Dependence Index) and carried a study smartphone for 2 weeks to record cigarette and e-cigarette use events. Results: Most measures of dependence were product specific (e.g., FTCD and e-FTCD were not correlated, r = -0.003) and predicted product-specific outcomes (e.g., long-term use of that product). However, individuals used the two products for some of the same secondary dependence motives (e.g., weight control, cognitive and affective enhancement). These secondary, or instrumental, motives predicted use of both products at 1 year. Which product was used first in the morning was strongly related to product dependence scores and likelihood of continued product use at 1 year. Conclusions: Among dual users of combustible and e-cigarettes, measures of e-cigarette and cigarette dependence tended to be unrelated to one another, but dual users tended to use both products for the same instrumental motives. Which product is used first in the morning may serve as a valuable measure of relative dependence on the two products. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The topic of e-cigarettes is controversial. Opponents focus on e-cigarettes' risks for young people, while supporters emphasize the potential for e-cigarettes to assist smokers in quitting smoking. Most US health organizations, media coverage, and policymakers have focused primarily on risks to youths. Because of their messaging, much of the public-including most smokers-now consider e-cigarette use as dangerous as or more dangerous than smoking. By contrast, the National Academies of Science, Engineering, and Medicine concluded that e-cigarette use is likely far less hazardous than smoking. Policies intended to reduce adolescent vaping may also reduce adult smokers' use of e-cigarettes in quit attempts. Because evidence indicates that e-cigarette use can increase the odds of quitting smoking, many scientists, including this essay's authors, encourage the health community, media, and policymakers to more carefully weigh vaping's potential to reduce adult smoking-attributable mortality. We review the health risks of e-cigarette use, the likelihood that vaping increases smoking cessation, concerns about youth vaping, and the need to balance valid concerns about risks to youths with the potential benefits of increasing adult smoking cessation.

Conceptualizing tobacco dependence as a chronic relapsing condition suggests the need to use analytic strategies that reflect that premise. However, clinical trials for smoking cessation typically define the primary endpoint as a measure of abstinence at a single timepoint distal to the intervention, typically 3–12 months. This reinforces the concept of tobacco outcomes as a dichotomous state—one is, or is not, abstinent. Fortunately, there are several approaches available to handle longitudinal data that reflect the relapsing and remitting nature of tobacco use during treatment studies. In this paper, sponsored by the Society for Research on Nicotine and Tobacco's Treatment Research Network, we present an introductory overview of these techniques and their application in smoking cessation clinical trials. Topics discussed include models to examine abstinence outcomes (eg, trajectory models of abstinence, models for transitions in smoking behavior, models for time to event), models that examine reductions in tobacco use, and models to examine joint outcomes (eg, examining changes in the use of more than one tobacco product). Finally, we discuss three additional relevant topics (ie, heterogeneity of effects, handling missing data, and power and sample size) and provide summary information about the type of model that can be used based on the type of data collected and the focus of the study. We encourage investigators to familiarize themselves with these techniques and use them in the analysis of data from clinical trials of smoking cessation treatment. Implications Clinical trials of tobacco dependence treatment typically measure abstinence 3–12 months after participant enrollment. However, because smoking is a chronic relapsing condition, these measures of intervention success may not accurately reflect the common trajectories of tobacco abstinence and relapse. Several analytical techniques facilitate this type of outcome modeling. This paper is meant to be an introduction to these concepts and techniques to the global nicotine and tobacco research community including which techniques can be used for different research questions with visual summaries of which types of models can be used for different types of data and research questions. [ABSTRACT FROM AUTHOR]

Aim: To compare effects of three post‐relapse interventions on smoking abstinence. Design: Sequential three‐phase multiple assignment randomized trial (SMART). Setting: Eighteen Wisconsin, USA, primary care clinics. Participants: A total of 1154 primary care patients (53.6% women, 81.2% White) interested in quitting smoking enrolled from 2015 to 2019; 582 relapsed and were randomized to relapse recovery treatment. Interventions: In phase 1, patients received cessation counseling and 8 weeks nicotine patch. Those who relapsed and agreed were randomized to a phase 2 relapse recovery group: (1) reduction counseling + nicotine mini‐lozenges + encouragement to quit starting 1 month post‐randomization (preparation); (2) repeated encouragement to quit starting immediately post‐randomization (recycling); or (3) advice to call the tobacco quitline (control). The first two groups could opt into phase 3 new quit treatment [8 weeks nicotine patch + mini‐lozenges plus randomization to two treatment factors (skill training and supportive counseling) in a 2 × 2 design]. Phase 2 and 3 interventions lasted ≤ 15 months. Measurements The study was powered to compare each active phase 2 treatment with the control on the primary outcome: biochemically confirmed 7‐day point‐prevalence abstinence 14 months post initiating phase 2 relapse recovery treatment. Exploratory analyses tested for phase 3 counseling factor effects. Findings Neither skill training nor supportive counseling (each on versus off) increased 14‐month abstinence rates; skills on versus off 9.3% (14/151) versus 5.2% (8/153), P = 0.19; support on versus off 6.6% (10/152) versus 7.9% (12/152), P = 0.73. Phase 2 preparation did not produce higher 14‐month abstinence rates than quitline referral; 3.6% (8/220) versus 2.1% [3/145; risk difference = 1.5%, 95% confidence interval (CI) = −1.8−5.0%, odds ratio (OR) = 1.8, 95% CI = 0.5–6.9]. Recycling, however, produced higher abstinence rates than quitline referral; 6.9% (15/217) versus 2.1% (three of 145; risk difference, 4.8%, 95% CI = 0.7–8.9%, OR = 3.5, 95% CI = 1.0–12.4). Recycling produced greater entry into new quit treatment than preparation: 83.4% (181/217) versus 55.9% (123/220), P < 0.0001. Conclusions: Among people interested in quitting smoking, immediate encouragement post‐relapse to enter a new round of smoking cessation treatment ('recycling') produced higher probability of abstinence than tobacco quitline referral. Recycling produced higher rates of cessation treatment re‐engagement than did preparation/cutting down using more intensive counseling and pharmacotherapy. [ABSTRACT FROM AUTHOR]