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Record W3110169719 · doi:10.21037/jtd-20-1565

Central location and risk of imaging occult mediastinal lymph node involvement in cN0T2-4 non-small cell lung cancer

2020· article· en· W3110169719 on OpenAlexaff
Julien Guinde, Etienne Bourdages-Pageau, Paula A. Ugalde, Marc Fortin

Bibliographic record

VenueJournal of Thoracic Disease · 2020
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsInstitut Universitaire de Cardiologie et de Pneumologie de QuébecUniversité Laval
Fundersnot available
KeywordsMedicineOccultMediastinal lymph nodeRadiologyLung cancerLymph nodeDissection (medical)CancerInternal medicinePathologyMetastasis

Abstract

fetched live from OpenAlex

Background: Appropriate pre-operative staging is a cornerstone in the treatment of non-small cell lung cancer (NSCLC). Central location and size greater than 3 cm are amongst indications for pre-operative invasive mediastinal staging but the quality of the evidence behind this recommendation is low. Methods: We retrospectively reviewed all cases of cT2-4N0M0 NSCLCL after CT and TEP-CT which underwent surgical resection with lymph node dissection or had a positive invasive pre-operative mediastinal staging in our institution from 2014 to 2018. Results: Three hundred and ten patients met inclusion criteria, 79 (25.5%) central and 231 (74.5%) peripheral tumors. Central tumor location was associated with a higher prevalence of pN2-3 disease (17.7% vs. 6.1%, P<0.001). In a multivariate analysis, central tumor location remained the only factor statistically associated with imaging occult mediastinal disease (OR 3.23, 95% CI: 1.45–7.18). NPV of PET-CT for occult mediastinal disease was 0.83 (95% CI: 0.72–0.90) in central and 0.94 (95% CI: 0.90–0.97) in peripheral tumor. Central location was also associated with a higher prevalence of occult N1 to N3 disease (43.0% vs. 15.2%, P<0.001). Conclusions: This study suggests that invasive mediastinal staging is required in central cT2-4N0 NSCLC but can be questioned in peripheral one, especially in cT2N2 subgroup if the patient is a candidate for lobar resection.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.416

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.305
Teacher spread0.292 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations9
Published2020
Admission routes1
Has abstractyes

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