MétaCan
Menu
Back to cohort
Record W2120225336 · doi:10.1158/1078-0432.ccr-05-9010

Localized Non–Small Cell Lung Cancer: Adjuvant Radiotherapy in the Era of Effective Systemic Therapy

2005· review· en· W2120225336 on OpenAlexaboutno aff
Jeffrey A. Bogart, Jesse N. Aronowitz

Bibliographic record

VenueClinical Cancer Research · 2005
Typereview
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRadiation therapyContext (archaeology)Systemic therapyLung cancerRandomized controlled trialCancerClinical trialOncologyStage (stratigraphy)Intensive care medicineMedical physicsSurgeryInternal medicineBreast cancer

Abstract

fetched live from OpenAlex

Investigators in Europe, Canada, and the United States recently established a definitive role for adjuvant systemic chemotherapy following resection of early-stage non-small cell lung cancer (NSCLC). This was no small accomplishment, as upward of 20 randomized trials had previously been conducted. The role of postoperative radiotherapy (PORT) has been studied with far less vigor in the modern era. A 1998 meta-analysis of randomized trials suggesting that PORT was detrimental to survival included studies of doubtful quality. The value of PORT should be considered in the same context as recent chemotherapy trials. Advances in imaging have improved the accuracy of staging, patient selection, and target definition. Modern dosimetry and accelerator technologies have advanced the capacity to deliver radiation to the target with less tissue toxicity. Evolving philosophies in dosing and fractionation should improve the therapeutic ratio. Finally, it is reasonable to assume that the importance of local control will be enhanced in the setting of better systemic therapies. We will review the data on PORT and address critical issues in the design of trials to assess the role of modern radiotherapy in the integrated approach to management of early-stage NSCLC.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.958
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.004
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 head0.170
GPT teacher head0.559
Teacher spread0.389 · 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 designOther design
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

Citations60
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueClinical Cancer ResearchSame topicLung Cancer Diagnosis and TreatmentFrench-language works237,207