MétaCan
Menu
Back to cohort

Reporting of tobacco use and impact on outcomes in cancer cooperative group clinical trials: A systematic scoping review.

2021· article· en· W3199828166 on OpenAlexaff
Lawson Eng, Janette Brual, Ahsas Nagee, Spencer Mok, Rouhi Fazelzad, Rebecca Truscott, Nicole Mittmann, Michael Chaiton, Deborah Saunders, Geoffrey Liu, Penelope Ann Bradbury, William K. Evans, Janet Papadakos, Meredith Giuliani

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsNortheast Cancer CentreSunnybrook HospitalCentre for Addiction and Mental HealthMcMaster UniversityCancer Care OntarioHealth Sciences NorthUniversity Health NetworkPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineClinical trialCancerLung cancerInternal medicineSystematic reviewAdverse effectClinical endpointRandomized controlled trialMEDLINEOncology

Abstract

fetched live from OpenAlex

40 Background: Continued smoking after a diagnosis of cancer negatively impacts cancer outcomes but the impact of tobacco on many innovative treatments has not yet been well established. Collecting and evaluating tobacco use in cancer clinical trials may advance understanding of the consequences of tobacco use on specific treatment modalities. We performed a systematic scoping review of the frequency of reporting and analysis of tobacco use in clinical trials run by cancer cooperative clinical trial groups. Methods: A comprehensive literature search was conducted to identify cancer cooperative group clinical trials published from January 2017 to October 2019 using Medline, Epub Ahead of Print and In-Process & Other Non-Indexed Citations, Embase, Cochrane Central Register of Controlled Trials using OvidSP. Eligible studies evaluated either systemic and/or radiation therapies, involved at least one cancer cooperative group, included > 100 adult patients and reported on at least one primary or secondary endpoint, which included overall survival (OS), disease/progression-free survival (DFS/PFS), response rates, toxicities/adverse events, or quality of life (QoL). Secondary analyses of previously published trials were excluded. Results: Among 14843 identified studies, 91 studies representing 90 trials met inclusion criteria. 24% were phase II trials, 2% phase II/III and 74% phase III. Trial start dates ranged from 1995-2015 with most (29%) between 2007-2008; median trial sample size was 406 (range: 100-4994); 86% involved systematic therapy, 35% involved radiation; 14% were lung and 5% were head and neck trials. 51% of trials had a curative intent, 33% were palliative and 16% involved hematologic cancers. 74 studies reported on OS, 73 DFS/PFS, and 88 toxicity/QoL. 19 studies reported baseline tobacco use information, while two reported collecting follow-up tobacco use. Of those collecting baseline tobacco use, only 7 reported any analysis of the impact of tobacco on clinical outcomes. There was significant heterogeneity in the reporting of baseline tobacco use: 5 reported never/ever status, 10 reported never/ex-smoker/current smoker status; 4 reported some measure of smoking intensity; none reported on verifying smoking status or second hand smoke exposure. Trials of tobacco related (lung and head and neck) cancers were more likely to report baseline tobacco use compared to non-tobacco related cancers (83% vs 6% p < 0.001). Conclusions: Few cancer cooperative group clinical trials report and analyze trial participants’ baseline tobacco use, and even fewer collect follow up information. Significant heterogeneity exists in reporting tobacco use. Routine standardized collection and reporting of tobacco use, both at baseline and follow up in clinical trials, should be implemented to enable investigators to evaluate the clinical impact of tobacco use on new cancer therapies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.219
metaresearch head score (Gemma)0.731
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.512
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2190.731
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.813
GPT teacher head0.757
Teacher spread0.057 · 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; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical OncologySame topicDelphi Technique in ResearchFrench-language works237,207