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Record W2916321497 · doi:10.3747/co.25.4096

Perspectives on Treatment Advances for Stage III Locally Advanced Unresectable Non-Small-Cell Lung Cancer

2019· review· en· W2916321497 on OpenAlexaffvenue
Parneet Cheema, J. Rothenstein, Barbara Melosky, Anthony Brade, Vera Hirsh

Bibliographic record

VenueCurrent Oncology · 2019
Typereview
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsMcGill UniversityBC Cancer FoundationBC Cancer AgencyUniversity of British ColumbiaCancer Care OntarioSpinal Cord Injury BCQueen's UniversityRoyal Victoria HospitalRegional Municipality of DurhamWilliam Osler Health System
Fundersnot available
KeywordsDurvalumabMedicineOncologyLung cancerInternal medicineStage (stratigraphy)Radiation therapyChemotherapyClinical trialCancerImmunotherapyNivolumab

Abstract

fetched live from OpenAlex

For more than a decade, there has been no improvement in outcomes for patients with unresectable locally advanced (la) non-small-cell lung cancer (nsclc). The standard treatment in that setting is definitive concurrent chemotherapy and radiation (ccrt). Although the intent of treatment is curative, most patients rapidly progress, and their prognosis is poor, with a 5-year overall survival (os) rate in the 15%-25% range. Those patients therefore represent a critical unmet need, warranting expedited approval of, and access to, new treatments that can improve outcomes. The pacific trial, which evaluated durvalumab consolidation therapy after ccrt in unresectable la nsclc, demonstrated a statistically significant and clinically meaningful improvement in progression-free survival (pfs) and a significant improvement in os. Durvalumab thus fills a critical unmet need in the setting of unresectable la nsclc and provides a new option for patients treated with curative intent. Here, we review the treatment of unresectable la nsclc, with a focus on the effect of the clinical data for durvalumab.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.952
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
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 head0.118
GPT teacher head0.482
Teacher spread0.363 · 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.

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

Citations72
Published2019
Admission routes2
Has abstractyes

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