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Record W4220684825 · doi:10.1016/j.jtocrr.2022.100316

Comparison of 2-Weekly Versus 4-Weekly Durvalumab Consolidation for Locally Advanced NSCLC Treated With Chemoradiotherapy: A Brief Report

2022· article· en· W4220684825 on OpenAlexaboutno aff
Marie-Hélène Denault, Shelley Kuang, Aria Shokoohi, Bonnie Leung, Mitchell Liu, Eric Berthelet, Janessa Laskin, Sophie Sun, Tina Zhang, Barbara Melosky, Cheryl Ho

Bibliographic record

VenueJTO Clinical and Research Reports · 2022
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsnot available
Fundersnot available
KeywordsDurvalumabMedicineToxicityInternal medicineRegimenCohortChemoradiotherapyLog-rank testCisplatinProportional hazards modelOverall survivalSurgeryChemotherapyCancer

Abstract

fetched live from OpenAlex

IntroductionDurvalumab 10 mg/kg every 2 weeks for 1 year after chemoradiation has improved overall survival (OS) in unresectable stage III NSCLC. Subsequently, a 20 mg/kg 4-weekly regimen was approved. The study goal was to compare the efficacy and toxicity of the two regimens.MethodsAll patients with NSCLC treated with curative-intent chemoradiation followed by durvalumab from March 1, 2018 to December 31, 2020 at BC Cancer, British Columbia, Canada were included in this retrospective review. Durvalumab dosing schedule, toxicity, progression, and OS were collected. Comparisons between treatment groups were made using chi-square and independent t tests. Kaplan-Meier curves and log-rank test were used to analyze OS.ResultsA total of 152 patients were included in the 2-weekly group and 53 patients in the 4-weekly group. The median follow-up was 19.7 months and 12.0 months, respectively. The median OS was not reached, but 12-month survival rates were 88.4% versus 85.2% (p = 0.55). Toxicity profiles were similar in terms of sites and severity.ConclusionsThere was no significant difference in efficacy or toxicity between the 2-weekly and 4-weekly durvalumab in this cohort of patients with advanced NSCLC previously treated with curative-intent chemoradiation.

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.563
Threshold uncertainty score0.501

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.145
GPT teacher head0.488
Teacher spread0.343 · 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

Citations8
Published2022
Admission routes1
Has abstractyes

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