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Record W3208513157 · doi:10.1016/j.jtocrr.2021.100251

Concurrent Chemoradiation With or Without Durvalumab in Elderly Patients With Unresectable Stage III NSCLC: Safety and Efficacy

2021· article· en· W3208513157 on OpenAlexafffund
Sally C. M. Lau, Malcolm Ryan, Jessica Weiss, Aline Fusco Fares, Miguel García-Pardo, Sabine Schmid, Shelley Kuang, Deirdre Kelly, Ming‐Sound Tsao, Penelope A. Bradbury, B. C. John Cho, A. Sun, Srinivas Raman, Andrew Hope, Meredith Giuliani, Benjamin H. Lok, Andrea Bezjak, Geoffrey Liu, Natasha B. Leighl, Frances A. Shepherd, Adrian G. Sacher

Bibliographic record

VenueJTO Clinical and Research Reports · 2021
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkUniversity of Toronto
FundersTakeda CanadaBristol-Myers Squibb CanadaEMD SeronoAmgenBoehringer IngelheimMeso Scale DiagnosticsSanofiRocheGlaxoSmithKlinePfizerAstraZenecaEli Lilly and CompanyBristol-Myers Squibb
KeywordsDurvalumabMedicineInternal medicineHazard ratioStage (stratigraphy)Adverse effectIncidence (geometry)ChemotherapyOncologyCancerConfidence intervalImmunotherapy

Abstract

fetched live from OpenAlex

INTRODUCTION: The addition of durvalumab after chemoradiation therapy (CRT) in unresectable stage III NSCLC significantly improves survival. The benefit of this approach in elderly patients is controversial given the toxicity associated with CRT and, thus, may be underutilized. We sought to investigate the outcomes of elderly patients treated with CRT without or without durvalumab at our center. METHODS: We reviewed all stage III patients with NSCLC treated with CRT between 2018 and 2020. Patients were analyzed on the basis of age: less than 70 years and 70 years and older. The end points evaluated were treatment patterns, toxicity, progression-free survival, and overall survival. RESULTS: = 0.98). CONCLUSIONS: Well-selected elderly patients can be treated safely with CRT followed by durvalumab with similar survival benefits compared with their younger counterparts. We would advocate for the referral of all elderly patients for oncologic assessment to avoid undertreatment.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.146
Threshold uncertainty score0.323

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.072
GPT teacher head0.421
Teacher spread0.349 · 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

Citations11
Published2021
Admission routes2
Has abstractyes

Explore more

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