Neoplasms

Respiratory Tract (Lung and Bronchial) Diseases

All Conditions

Lung Neoplasms

Lung Diseases

Respiratory Tract Neoplasms

Thoracic Neoplasms

Respiratory Tract Diseases

Providers in this arm will continue to provide care as usual during lung cancer screening, with no intervention from the study team.

Providers in this arm will receive guidance from the study team about offering lung cancer screening patients proactive cessation care, including cessation medications and behavioral telephone counseling.

For patients of providers assigned to the proactive study group, a local coordinator will review the patient's cessation medication history. If the patient is not currently being provided cessation support medication, the coordinator will enter a note and unsigned order for the provider about the recommended medication indicated by VA formulary guidelines.

Unsigned note to provider about cessation medication prescription

Patients of providers assigned to the proactive study group will be contacted by specially trained counselors at the VA Quitline. Counselors will attempt to provide two sessions of proactive telephone support.

Proactive Telephone Counseling from VA Quitline

Steven B. Zeliadt, PhD MPH

This pragmatic trial will evaluate the value of routinely providing proactive smoking cessation support to current smokers as a part of participating in lung cancer screening within Veterans Health Administration.

This trial is a pragmatic randomized trial targeting the care of current smokers who are participating in lung cancer screening at two VA sites. Primary care providers at these sites will be randomized, and half will be offered tools to help integrate proactive smoking cessation support into the lung cancer screening process. Key proactive elements include proactive telephone outreach to all current smokers by a VA Quitline counselor that follows mailed results letters, and providing providers guidance in offering proactive cessation medication support as part of the lung cancer screening process.

Promoting Smoking Cessation in Lung Cancer Screening Through Proactive Treatment

The investigators anticipate publishing the findings alongside other similar trials funded by NCI through the Smoking Cessation within the Context of Lung Cancer Screening (SCALE) collaboration, with journals that will likely require concurrent publication of de-identified datasets.

The primary outcome measure is self-reported abstinence from smoking 12 months after lung cancer screening, using information obtained from study surveys and electronic medical records

Provider surveys will assess acceptance of and satisfaction with the proactive care approach among primary care clinicians referring Veterans for lung cancer screening

Costs of implementing the proactive care approach will be monitored and analyzed, including intervention staff effort, provider time, costs of telephone counseling, and pharmacotherapy costs

Patient surveys will assess satisfaction with VA Quitline telephone counseling

Surveys will assess patient motivation to quit smoking

Surveys will assess patients' perceived susceptibility to the harmful effects of smoking and perception of screening as protective

Surveys will assess patients' self-efficacy for quitting smoking

Fred Hutchinson Cancer Center

VA Office of Research and Development

Symptoms and General Pathology

Urinary Tract, Sexual Organs, and Pregnancy Conditions

Postoperative Complications

Head and Neck Neoplasms

Urologic Neoplasms

Urogenital Neoplasms

Urogenital Diseases

Female Urogenital Diseases

Pregnancy Complications

Female Urogenital Diseases and Pregnancy Complications

Male Urogenital Diseases

Urologic Diseases

All Drugs and Chemicals

Psychotropic Drugs

Imidacloprid

Bupropion

Nicotine

Varenicline

The study intervention consists of a smoking cessation counselling meeting by a Tabacco Treatment Specialist (TSS) 4 weeks before surgery. The goal of this first intervention meeting is to implement an individual treatment plan for preoperative smoking cessation.

Patients randomised to the control arm will get advice only. Their preoperative course will be as if they were not participating in this study, meaning they will receive inconsistent perioperative smoking cessation advice from nurses, surgeons, or anaesthesiologists but no further study-specific smoking cessation intervention. Importantly, participants in the control group will not be discouraged from using perioperative smoking cessation aids and can still obtain help on one's own initiative.

The study intervention consists of an interview by a Tabacco Treatment Specialist (TSS) 4 weeks before surgery with individual counselling and offered nicotine substitution. The intervention meeting is based on the Chronic Care Model (CCM) to improve quality of ambulatory care.

In brief, the intervention includes:

* Informative content about advantages of smoking cessation
* Scheduling service for a motivational interview by a TSS in office to implement a treatment plan
* For participants willing to quit smoking a preoperative quit day will be scheduled after the first intervention meeting 2-3 weeks before surgery
* Patients will be encouraged by a TSS to use nicotine replacement. Bupropion or Vareniclin will be provided on an individual basis
* TSS will schedule repeated follow-up meetings to support smoking abstinence or nicotine reduction before and after surgery for all patients

Intensive preoperative smoking cessation counselling

Studienkoordination Tumorzentrum

Christian Fankhauser, PD Dr. med.

Background: At present, effectively implementing smoking cessation programs in the health care system constitutes a major challenge. A unique opportunity to initiate smoking cessation focuses on smokers scheduled for surgery. These patients are not only highly motivated to quit smoking but also likely to benefit from a reduction in postoperative complications which may translate into a decrease of costs. Nevertheless, surgical patients are not routinely informed about the benefits of preoperative smoking cessation. Potential reasons for this missed opportunity may be lack of time and training of surgeons and anesthesiologists. The investigators therefore aim to analyse the impact of a preoperative high-intensity smoking cessation intervention on surgical complications up to a 90-day postoperative period in patients of various surgical disciplines. The hypothesis is that preoperative smoking cessation program improves outcomes in smokers undergoing intermediate to high-risk surgery. The primary objective is to compare complications between patients with an institutional multifaceted smoking cessation intervention starting four weeks before surgery compared to patients in the advice only group (control group) within a 90-day postoperative period. The primary endpoint is the Comprehensive Complication Index (CCI®) within 90 days of surgery. Secondary outcomes include length of hospital stay, cost of hospital stay, smoking abstinence, reduction in nicotine consumption.

Methods: The present study is a single center, randomized trial with two parallel groups of smokers scheduled for surgery comparing surgery alone and surgery with preoperative smoking cessation. The investigators plan to randomize 251 patients. The primary endpoint is the Comprehensive Complication Index up to a 90-day postoperative period. The secondary endpoints include comparison of smoking abstinence, quality of life, mental health, length of stay, costs of care and difference in hospital reimbursement between the two groups.

Discussion: The hypothesis is that preoperative smoking cessation program improves outcomes in smokers undergoing surgery.

Patients will be randomised in a 1:1 ratio to either the intervention or control group using service of the University of Graz (www.randomizer.at). Before randomisation patients will be pre-stratified for age (≤60, \>60 years) and procedure (intermediate versus high-risk procedures). Both factors have been identified in a previous retrospective cohort study at our institution as risk factors for complications. For that reason, minimization, as an efficient way to control for confounding in small to moderately sized trials, will be used. Also, minimization automatically ensures concealment of random allocation since there is no pre-existing randomization list.

Throughout the study patient data is collected in the electronic health record (LUKiS) in an uncoded manner. Allocation will be blinded. At the end of the study the LUKiS reporting team will generate a report, which will include all study data in a de-identified form. The analysis of the report with the pseudonymized data will be performed by the project statistician.

Preoperative Smoking Cessation in Patients Undergoing Surgery

Preoperative Smoking Cessation Program in Patients Undergoing Intermediate to High-risk Surgery: a Randomized, Single-blinded, Controlled Trial

The primary endpoint is the Comprehensive Complication Index (CCI) within 90 days of surgery. The CCI is calculated as the sum of all Clavien-Dindo complications that are weighted for their severity (multiplication of the median preference values from patients and physicians). The final formula yields a continuous scale that ranks the cumulative burden from any combination of complications from 0 to 100 with higher values indicating a higher cumulative burden in a single patient. As a composite complication score, the CCI has the advantage of reflecting the overall burden of the postoperative course that affects the health of patients and their quality of life. In addition, the CCI is a powerful endpoint in trials, as it allows sample size up to nine times lower compared with traditional morbidity endpoints.

Days of hospital stay for planned surgery

Costs of hospital stay for planned surgery

Readmission rates for in-patient hospital stay after surgery

Number of patients who successfully quit smoking

Decrease or increase of daily nicotine consumption

The outcome is measured using the Hospital anxiety and depression scale (HADS) before surgery. The score ranges from 0 to 42 with higher values indicating a higher probability of a mood disorder.

unplanned postoperative intermediate care or intensive care unit admission

Stage of the Transtheoretical Model of behaviour change

The outcome is measured using the 36-Item Short Form Survey (SF-36). The score ranges from 0 to 100 with higher values indicating a more favorable health state.

Luzerner Kantonsspital

Principal Investigator

Participants will be sent messages asking them to imagine what their lives will look like in the future if they succeed ("What would quitting mean to you and your family's future?"; Yeager et al., 2014).

Participants will be sent messages that encourage inhibitory control of cravings for cigarettes (e.g., using cognitive reappraisal or attentional control) and that provide strategies to do so (e.g., "When you feel an urge to smoke, think about the health consequences").

Participants will be sent messages that encourage them to consider the core values that drive their desire to quit smoking.

In the high-level construal condition, participants will be sent messages asking them to consider why they are quitting ("What are your main reasons for quitting?") and to imagine what their lives will look like in the future if they succeed ("What would quitting mean to you and your family's future?"; Yeager et al., 2014). The corpus for this condition is 100 messages composed by a large independent sample of mTurk workers who are smokers and validated by a team of RAs trained to 0.8 reliability on ratings of high-level construal. To meet criteria for inclusion, a message must be rated as significantly closer to high-level (vs. low-level) on a rating scale of construal level.

In addition to the texting, participants will complete biweekly online "booster" sessions using Qualtrics with a custom, personalized link sent to the participant via email and text.

High-level construal

In the down-regulation of craving condition, participants will be sent messages that encourage inhibitory control of cravings for cigarettes (e.g., using cognitive reappraisal or attentional control) and that provide strategies to do so (e.g., "When you feel an urge to smoke, think about the health consequences"). The corpus for this condition is 100 messages composed by a large, independent sample of mTurk smokers and validated by a team of RAs trained to 0.8 reliability on ratings of plausibility AND effortful cognitive inhibition or control.

In addition to the texting, participants will complete biweekly online "booster" sessions using Qualtrics with a custom, personalized link sent to the participant via email and text.

Down-regulation of craving for cigarettes

In the up-regulation of goal energization condition, participants will be sent messages that encourage them to consider the core values that drive their desire to quit smoking. These messages will name a specific core value that the participant rated in the top three (of 19) during the baseline session, and will draw a connection between quitting and the core value. For example, a message for a person who nominated "family" as one of her top three core values might read, "Quitting will help you model a healthy lifestyle for your family." This intervention is grounded in robust theory and evidence supporting Self-Affirmation Theory. The corpus for this condition is 100 messages composed by a large, independent sample of mTurk smokers and validated by a team of RAs trained to 0.8 reliability in correctly identifying to which core value the message is tied.

In addition to the texting, participants will complete biweekly online "booster" sessions using Qualtrics.

Up-regulation of goal energization

Elliot T Berkman, Ph.D.

Elliot Berkman, Ph.D.

Dasa Zeithamova, Ph.D.

Eric Stice, Ph.D.

Krista DeStasio, BS

Kelsey Shaffer, BA

Elliot T Berkman, PhD

The objective of the proposed research is to conduct a longitudinal experiment on the neurocognitive pathways and individual differences in high-level construal for affect regulation and smoking cessation. The population is adult smokers aged 25-55 who have tried and failed to quit and who are experiencing poverty. The primary endpoints are (a) the similarity in neural representation of high-level construal to one of two candidate pathways, (b) the presence of meaningful individual differences in the neural representation of high-level construal, and (c) as a secondary endpoint, the effect size of the high-level construal condition on smoking as measured by cigarettes per day.

Each of these endpoints corresponds to a specific null hypothesis. The null hypothesis for the first endpoint is that high-level construal is not significantly different in its neural representation from down-regulation of craving, which would suggest that high-level construal does not operate through distinct mechanisms from traditional treatments. The null hypothesis for the second endpoint is that the between-subjects variability in the neural representation of construal level does not significantly relate to relevant individual differences measures (e.g., traits, task behavior), which would suggest that individual differences are not meaningfully related to outcomes. Finally, the null hypothesis for the secondary endpoint is that the magnitude of the effect of high-level construal on smoking as measured by reductions in average cigarettes per day is not significantly greater than in the other conditions, which would suggest that the efficacy of the high-level construal condition is not significantly greater than a standard text-messaging intervention.

The primary endpoints will be assessed at baseline and change from pre-to-post training (8 weeks).

OVERVIEW:

The proposed work will achieve the three specific aims (two confirmatory, one exploratory) in the context of a 3-arm translational experiment. Assessments of neurocognitive mechanisms of high-level construal, as well as of two candidate pathways, will be completed at baseline and endpoint sessions. The 300 participants enrolled in the study will complete a multimodal battery that will assess neural, behavioral, and self-report indices relating to the three processes of interest - construal level, down-regulation of craving, and up-regulation of goal energization - and then are randomized to one of three experimental conditions related to those processes. This design is highly advantageous because it allows for the establishment of the mechanisms of the construal-level intervention, to compare them with the mechanisms of the other two processes, and to test whether, and to what extent, our potentially novel affect regulation strategy engages and alters those mechanisms (Aim 1); and to identify individual differences in the effects of that novel strategy (high-level construal) on patterns of brain activation, affect regulation, and cessation outcomes (Aim 2). Though the translational experiment design is not intended to be an intervention per se (because the evidence base does not yet support a full-scale trial and materials for such an intervention still need to be developed), the investigators will nonetheless quantify the effect size of high-level construal on changes in smoking so future RCTs have that information and can be adequately powered to detect an effect.

ASSIGNMENT OF PARTICIPANTS TO CONDITION:

Participants will be randomly assigned to a condition using the randomizer function in the RedCap participant tracking and management software. This assignment will happen only after participants are screened, consented, enrolled, and complete the baseline session. In other words, all 300 participants will be treated in exactly the same way through the end of the baseline session, and only at that point will RedCap be used to assign participants to their condition. All participants will have equal probability of being assigned to the conditions (i.e., 33.33% chance of assignment to each). The study coordinator will know which participant is enrolled in each condition, but researchers involved in data analysis (i.e., Drs. Berkman, Fujita, Chavez, and Weston, as well as the graduate students) as well as the research assistants who interact with the participants will be blind to condition during data gathering and analysis.

METHODS FOR SAMPLE SIZE CALCULATION AND DATA ANALYSIS:

The method for selecting the sample size was based on a power analysis of the least sensitive test - Aim 2. The key statistical tests for the three aims are as follows. For Aim 1, the test of neural similarity between conditions is essentially a paired-samples t-test on similarity scores (e.g., pattern correlations calculated within subjects). This is a high-powered comparison because the covariance within subjects of the scores is high. For Aim 2, the individual difference analyses are between-subjects correlations and regression (or partial regression or logistic regression) coefficients relating neural similarity to affect regulation scores, responses to trait and individual difference surveys, and smoking behavior as measured by cigarettes per day. This family of test has relatively low power because it is entirely between subjects. For Exploratory Aim 3, the key test is the condition-by-time interaction (i.e., differences among the groups in change in smoking behavior from pre-to-post training). This test is a within-between (sometimes called "mixed") ANOVA analysis that is more powerful that the individual difference analyses for Aim 2 but less powerful than the fully within-subjects tests for Aim 1.

INTERVENTION CONTENT:

The content for all three training arms is a set of brief (\<160 character) messages designed to enable participants to practice one specific affect regulation strategy (experimental arms). In brief, all messages in the experimental arms are generated by a large group of mTurk workers who are smokers; the process of message generation and validation has already begun. During the award period the investigators will add even more messages to the corpus and validate them. In the high-level construal condition, workers compose messages that encourage thinking about purpose of quitting and future goals (e.g., "What would quitting mean to you and your future?"). In the down-regulation of craving condition, workers compose messages that encourage effortful inhibitory or attentional control of cravings (e.g., "When you feel an urge to smoke, think about the health consequences"). And in the up-regulation of goal energization condition, workers compose messages that tie one specific core value (which the mTurk worker ranked as within his or her top three core values) to the goal of quitting (e.g., for the core value of "family", a message might be, "Quitting will help you model a healthy lifestyle for your family"). The content for the up-regulation of goal energization condition is matched to participants' own top three core values.

INTERVENTION DELIVERY:

All participants receive text messages and complete biweekly online "booster" sessions for 8 weeks.

Beginning on their quit date, participants will be sent messages via SMS text messaging 5 times each day for 28 consecutive days, then 4 times each day for the following 28 days. The investigators chose to increase the messaging frequency in the first month of cessation given the higher likelihood of relapse during this period. The order of the messages will be pseudo-randomized such that each message will be seen no more than three times across the 8-week training period, separated by at least 10 days. The timing of the messages will be adjusted for each participant to be evenly spaced starting at wake-up and ending 15 minutes before bedtime and adjusting for weekday/weekend differences. Participants will reply to each message and use a 5-point scale to rate its perceived helpfulness. Participants can also text "SOS" to the system at any point to initiate support via text if they feel tempted to smoke. Daily text messaging is an ideal delivery format for this training because it allows for in vivo participant contact at moments when smoking decisions are being made. Text messaging has very high adoption rates in the United States even among underserved communities that are typically difficult to sample densely for extended durations, and low SES users are comfortable receiving texts throughout the day. The investigators have used text messaging for experience sampling and for theory-based intervention in a community sample (see Preliminary Studies 5 and 6). Participants will provide their mobile phone number at the baseline session; those without a text message-enabled phone or those who do not wish to use their own, will be provided a prepaid phone at the end of the baseline session.

In addition to the text messaging, participants will complete biweekly online "booster" sessions using Qualtrics with a custom, personalized link sent to the participant via email and text. The booster sessions are designed to reinforce the active interventions (high-level construal, goal energization, down-regulation of craving) and provide opportunities to practice the assigned affect regulation strategy. In the sessions, participants will be reminded of their assigned strategy and write brief responses to specific prompts (e.g., "What are two specific ways that quitting now will change your future life?", "Why is quitting important to you today?", and "What are two ways you can change how you think to reduce your craving for cigarettes?"). Participants will also generate triggers to smoking (situations or cues) and practice using down-regulation of craving when they see those triggers. This exercise helps form the habit of deploying the strategy in everyday life. Not all participants have computer access, so, as in previous studies, participants will be provided access in the lab and the research team will work with the local library system to ensure all study sites are accessible from their computers.

BOOSTER COMPLETION AND RETENTION:

Dr. Berkman is currently using similar "booster" sessions, which are programmed in and are delivered via Qualtrics, in a current translational experiment on healthy eating (R01 CA211224). The automated reminders and links, which can be sent via email and text messaging depending on participant preference, greatly increase completion of the boosters. Together with the reminders, graded incentives (e.g., a monetary bonus for completing \>90% of the boosters during the study) have greatly increased completion of the at-home booster sessions.

Construal Level as a Novel Pathway for Affect Regulation and Cancer Control

High-level Construal as a Novel Pathway for Affect Regulation and Cancer Control

Neural similarity as indexed by Pearson's correlations derived from the similarity matrices produced by Representational Similarity Analysis. The correlation is among the vectorized 3D images representing the patterns of BASELINE functional neural activity related to (a) high-level construal, (b) down-regulation, and (c) up-regulation of goal energization. There will be 3 correlations in total (a with b, a with c, and b with c).

Neural similarity as indexed by Pearson's correlations derived from the similarity matrices produced by Representational Similarity Analysis. The correlation is among the vectorized 3D images representing the patterns of PRE-TO-POST CHANGE in the functional neural activity related to (a) high-level construal, (b) down-regulation, and (c) up-regulation of goal energization. There will be 3 correlations in total (a with b, a with c, and b with c).

Correlation between the similarity matrices produced by Representational Similarity Analysis and the self-report measures assessed at baseline. The measure is the Pearson's correlation between (a) the vectorized 3D image representing the patterns of baseline functional neural activity related to high-level construal and (b) the Levels of Personal Agency Questionnaire. The Outcome is the Pearson's r between (a) and (b).

Cross-validated machine learning (ML) prediction of endpoint (56-day) smoking quantity in terms of cigarettes per day based on responses to baseline responses to the Levels of Personal Agency Questionnaire. Degree of prediction will be expressed in Pearson's r correlation between (a) actual # of cigarettes per day at endpoint and (b) ML-predicted # of cigarettes per day.

Cross-validated machine learning prediction of endpoint (56-day) smoking quantity in terms of cigarettes per day based on responses to behavioral performance on the Construal Level Task as measured by the difference in response time in milliseconds between in the high- and low-level conditions. Degree of prediction will be expressed in Pearson's r correlation units.

Cross-validated machine learning prediction of baseline craving ratings during reactivity to personalized cigarette smoking cues based on multivariate neural representation of high-level construal. Ratings are on a 1 to 5 scale from "no craving" to "extreme craving". Degree of prediction will be expressed in Pearson's r units. Higher r values indicate better prediction of craving ratings.

Difference in baseline-to-endpoint change in cigarettes per day among the three conditions.

Trajectory of the group difference of change in cigarettes per day from the baseline assessment.

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Promoting Smoking Cessation in Lung Cancer Screening Through Proactive Treatment	NCT03612804	Smoking Reducti... Tobacco Use Tobacco Smoking Tomography Lung Diseases Lung Neoplasms	Unsigned note t... Proactive Telep...	- 80 Years	VA Office of Research and Development
Promoting Smoking Cessation in Lung Cancer Screening Through Proactive Treatment	NCT03612804	Smoking Reducti... Tobacco Use Tobacco Smoking Tomography Lung Diseases Lung Neoplasms	Unsigned note t... Proactive Telep...	- 80 Years	VA Office of Research and Development
Preoperative Smoking Cessation in Patients Undergoing Surgery	NCT05192837	Smoking Cessati... Smoking Reducti... Surgery--Compli... Surgery Cancer Postoperative C... Perioperative C... Smoking Abdominal Cance... Thoracic Cancer Urologic Cancer Gynecologic Can... Head and Neck C...	Intensive preop...	18 Years -	Luzerner Kantonsspital
Construal Level as a Novel Pathway for Affect Regulation and Cancer Control	NCT04620915	Smoking Cessati... Smoking Reducti... Cancer	High-level cons... Down-regulation... Up-regulation o...	25 Years - 55 Years	University of Oregon

Spots Global Cancer Trial Database for smoking reduction