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Record W4310077430 · doi:10.1016/j.atssr.2022.11.014

Neoadjuvant Targeted Therapy in Non–Small Cell Lung Cancer and Its Impact on Surgical Outcomes

2022· article· en· W4310077430 on OpenAlexafffund
Mark Sorin, Caroline Huynh, Merav Rokah, Laurie-Rose Dubé, Roni Rayes, Linda Ofiara, Benjamin Shieh, Scott Owen, Pierre Fiset, Sophie Cammilleri-Broët, Sara Najmeh, Jonathan Cools‐Lartigue, Lorenzo Ferri, Jonathan Spicer

Bibliographic record

VenueAnnals of Thoracic Surgery Short Reports · 2022
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersCancer Research SocietyNovartis Pharmaceuticals CorporationAstraZenecaTakeda Pharmaceutical CompanyBristol-Myers SquibbBayer CorporationFondation de l'Hôpital Général de MontréalAmgen
KeywordsMedicineNeoadjuvant therapyOncologyTargeted therapyLung cancerInternal medicineCancerBreast cancer

Abstract

fetched live from OpenAlex

Background: The evidence for neoadjuvant targeted therapy in non-small cell lung cancer is limited, with 2 phase 3 trials currently recruiting and no approved indications. Methods: We describe our experience with the use of neoadjuvant targeted therapy for patients with operable non-small cell lung cancer. Results: Our focus is on surgical outcomes, which represent an underreported aspect of the patient trajectory. We argue that surgical outcomes are an essential feature of this strategy with significant potential benefits and risks. Conclusions: Overall, the patient experience can be significantly affected by the use of neoadjuvant targeted therapy and its impact on surgical planning, strategy, and outcomes.

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)0.001
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 score0.065
Threshold uncertainty score0.903

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.052
GPT teacher head0.404
Teacher spread0.352 · 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

Citations4
Published2022
Admission routes2
Has abstractyes

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