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Record W2810772340 · doi:10.2196/10826

Varenicline and Bupropion for Long-Term Smoking Cessation (the MATCH Study): Protocol for a Real-World, Pragmatic, Randomized Controlled Trial

2018· article· en· W2810772340 on OpenAlexaffvenueabout
Laurie Zawertailo, Tara Mansoursadeghi-Gilan, Helena Zhang, Sarwar Hussain, Bernard Le Foll, Peter Selby

Bibliographic record

VenueJMIR Research Protocols · 2018
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsSinai Health SystemLunenfeld-Tanenbaum Research InstitutePublic Health OntarioUniversity of TorontoCentre for Addiction and Mental Health
FundersPfizer PharmaceuticalsPfizer
KeywordsBupropionVareniclineSmoking cessationRandomized controlled trialMedicineProtocol (science)Term (time)PsychiatryPsychologyAlternative medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Varenicline and bupropion are efficacious, prescription-only pharmacotherapies for smoking cessation; however, their real-world impact is limited by prescriber knowledge, affordability, and accessibility. OBJECTIVE: The primary objective of the MATCH (Medication Aids for Tobacco Cessation Health) study was to evaluate the real-world, long-term effectiveness of mailed bupropion and varenicline in a sample of interested smokers with the utilization of Web-based recruitment and follow-up. In addition, the study aims to investigate the genotypic and phenotypic predictors of cessation. METHODS: This is a two-group, parallel block, randomized (1:1) open-label clinical trial. This study will be conducted online with the baseline enrollment through the study's website and follow-up by emails. In addition, medication prescriptions will be filled by the study contract pharmacy and couriered to participants. Individuals who smoke ≥10 cigarettes per day and intend to quit within the next 30 days will be recruited through Public Health Units and Tobacco Control Area Networks throughout Ontario by word-of-mouth and the internet. Eligible participants will receive an email with a prescription for 12-week assigned medication and a letter to take to their physician. The recruitment and randomization will continue until 500 participants per arm have received medication. All participants will receive weekly motivational emails during the treatment phase. The primary outcome measure is the smoking status after 6 months, biochemically confirmed by mailed-in salivary cotinine. Follow-ups will be conducted through emails after 4, 8, 12, 26, and 52 weeks of starting the treatment to assess the smoking prevalence and continuous smoking abstinence. In addition, mailed-in saliva samples will be used for genetic and nicotine metabolism analyses. Furthermore, personality characteristics will be assessed using the Big Five Aspect Scales. RESULTS: The project was funded in 2014 and enrollment was completed in January 2017. Data analysis is currently underway. CONCLUSIONS: To the best of our knowledge, this is the first randomized controlled trial to mass distribute prescription medications for smoking cessation. We expect this method to be logistically feasible and cost effective with quit outcomes that are comparable to published clinical trials. TRIAL REGISTRATION: ClinicalTrials.gov NCT02146911; https://clinicaltrials.gov/ct2/show/NCT02146911 (Archived by WebCite at http://www.webcitation.org/72CZ6AvXZ). REGISTERED REPORT IDENTIFIER: RR1-10.2196/10826.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.060
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.111
Threshold uncertainty score0.372

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0600.044
Meta-epidemiology (narrow)0.0080.005
Meta-epidemiology (broad)0.0130.006
Bibliometrics0.0040.005
Science and technology studies0.0050.005
Scholarly communication0.0060.005
Open science0.0040.003
Research integrity0.0090.012
Insufficient payload (model declined to judge)0.1110.020

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.205
GPT teacher head0.573
Teacher spread0.368 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2018
Admission routes3
Has abstractyes

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