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Record W4406413355 · doi:10.1016/j.cllc.2025.01.006

Immunotherapy for Early-Stage Non–Small Cell Lung Cancer: A Practical Guide of Current Controversies

2025· review· en· W4406413355 on OpenAlexaff
William J. Phillips, Ashley Jackson, Biniam Kidane, Vishal Navani, Paul Wheatley‐Price

Bibliographic record

VenueClinical Lung Cancer · 2025
Typereview
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsUniversity of CalgaryOttawa HospitalFoothills Medical CentreUniversity of ManitobaCancerCare ManitobaUniversity of Ottawa
Fundersnot available
KeywordsMedicineStage (stratigraphy)Lung cancerCurrent (fluid)OncologyImmunotherapyIntensive care medicineCancerInternal medicineMedical physics

Abstract

fetched live from OpenAlex

The role of immunotherapy as systemic therapy for nonmetastatic non-small cell lung cancer (NSCLC) has evolved rapidly over the last decade. There are several well-conducted phase 3 clinical trials evaluating immunotherapy in the neoadjuvant, perioperative, adjuvant and nonoperative setting. In this narrative review, we summarize the data from these studies and discuss ongoing controversies in applying these data to clinical practice. These controversies relate to the value of the adjuvant component of perioperative immunotherapy, treatment of patients with PDL1 negative tumors, defining resectability, optimal use of operative versus nonoperative management, the role of stereotactic radiation therapy for very early lung cancers, and management of tumors with an oncogenic driver.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0000.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.003

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 head0.089
GPT teacher head0.522
Teacher spread0.433 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations5
Published2025
Admission routes1
Has abstractyes

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